portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() )","index_df['date'].str[:6].unique().tolist() # The list of months that we need for calculating market cap","'139807', '139808', '139809', '139810', '139811', '139812' ] # The list of months that","(merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split","ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio']","= pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] #","to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded","portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size)","Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11],","= pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] +","'139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610',","all 75 tickers' data me_list = [] for file_number in range(1, 76): print(file_number)","portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions,","non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last()","portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio","rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path,","price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN","labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict()","df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df =","'139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606',","me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')]","= [] for month in mom_months: # Check t-13 price condition and t-1","return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price'])","= portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s =","= (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh)","]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for","data for calculating returns close_list = [] for file_number in range(1, 76): rahavard_path","pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview","[ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size","list of all months months = index_df['date'].str[:6].unique().tolist() # The list of months that","Split each me portfolio into 3 MOM group q = [0, .3, .7,","ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[","jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1,","'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date']",") index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist() # The","= pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers","# Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number)","Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh =","portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size']","for calculating returns close_list = [] for file_number in range(1, 76): rahavard_path =","add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates","ME into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), (","portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist()","df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df","= ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom =","]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio","dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'],","me_df, on=['ticker_num', 'date']) # First, create a NaN column, and then add t-13","'139900')] # Read index df for indicating open market days index_path = r'E:\\Thesis\\New","'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') &","and add it to a list mom = ( ((sh_return + bh_return) /","'139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708',","<reponame>behnoud-bazrafshan/ThesisPortfolio import pandas as pd import numpy as np import jdatetime pd.options.mode.chained_assignment =","= np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate","file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx'","me_list = [] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily","skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from","'139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701',","pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read","1 ) mom_list = [] for month in mom_months: # Check t-13 price","month t # Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh)","'139809', '139810', '139811', '139812' ] # The list of months that we need","MOM mom_months = me_months[1:] # Merge market cap and price dfs merged_df =","df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d')","portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month","monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df","'size', portfolio_size) # Split each me portfolio into 3 MOM group q =","'139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604',","'139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns close_list =","(df['date'] <= '139900')] # Read index df for indicating open market days index_path","= [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410',","& bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio","names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas","shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe","& sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return =","Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create","pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s,","ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] ==","= pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column, and then","'open', 'market_cap'], na_values='-' ) # Change order from old to new dates me_df","t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price =","q = [0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b =","= (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price","need for calculating market cap me_months = [ '139312', '139401', '139402', '139403', '139404',","df for indicating open market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df =","into 3 MOM group q = [0, .3, .7, 1] labels = ['L',","& (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating","in mom_months: # Find t-13 prices for ticker in range(1, 76): t_13 =","previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion &","sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) #","'139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506',","portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3 MOM group q","(merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition","75 tickers' data me_list = [] for file_number in range(1, 76): print(file_number) me_path","days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df",") ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each","t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find t-13","month in mom_months: # Check t-13 price condition and t-1 market cap condition","portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh =","(me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns","dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas add 2 index","== month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition =","months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker)","na_values='-' ) # Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True)","3 MOM group q = [0, .3, .7, 1] labels = ['L', 'M',","bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return","Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) #","pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all","/ merged_df['t-13 price']) - 1 ) mom_list = [] for month in mom_months:",") # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num',","and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months:","b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom","merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition]","market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'],","mom_months: # Find t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month)","'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q,","( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl","dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column,","== 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[","merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return","merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio","cap # Concat all 75 tickers' data me_list = [] for file_number in","for ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date']","all months months = index_df['date'].str[:6].unique().tolist() # The list of months that we need","'139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The list of months","me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409',","price', np.nan) for month in mom_months: # Find t-13 prices for ticker in","= ( ((sh_return + bh_return) / 2) - ((sl_return + bl_return) / 2)","q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q,","'139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703',","<= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns close_list","pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio']","condition and t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition =","months return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13","bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio =","'139212') & (df['date'] <= '139900')] # Read index df for indicating open market","'139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808',","# Read Bourseview data for market cap # Concat all 75 tickers' data","str}, parse_dates=[0] ) # Solve index reading problem, pandas add 2 index to","each month ME into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median()","'139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809',","First, create a NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price',","portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl =","merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios","index reading problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True) #","names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months months =","range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df =","need for camculating MOM mom_months = me_months[1:] # Merge market cap and price","[ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411',","[] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data -","'139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802',","Merge market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) #","month in mom_months: # Find t-13 prices for ticker in range(1, 76): t_13","كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The","usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading","mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME","column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in","== 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) #","MOM group q = [0, .3, .7, 1] labels = ['L', 'M', 'H']","weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a list mom =","= df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') &","None # Read Bourseview data for market cap # Concat all 75 tickers'","sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each","data me_list = [] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New",">= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data","== 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted","return for each portfolio in month t # Set conditions month_condition = (merged_df['date']","'139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812'","me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1,","Check t-13 price condition and t-1 market cap condition previous_month = months[months.index(month) -","jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market cap # Concat","inplace=True) # Read rahavard 365 data for calculating returns close_list = [] for","in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13)","# Check t-13 price condition and t-1 market cap condition previous_month = months[months.index(month)","]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] ==","'139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503',","Concat all 75 tickers' data me_list = [] for file_number in range(1, 76):","open market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1],","(merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion","'139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602',","price' ] = t_13_price except: pass # Calculate last 12 months return for","labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom","numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] ==","portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() #","# Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition =","to a list mom = ( ((sh_return + bh_return) / 2) - ((sl_return","market cap # Concat all 75 tickers' data me_list = [] for file_number","== previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass","pandas as pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None #","me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' )","'139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612',","f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-'","file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date']","me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list,","'139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805',","np.nan) for month in mom_months: # Find t-13 prices for ticker in range(1,","= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist()","value-weighted return for each portfolio in month t # Set conditions month_condition =","bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate","= np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a","range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt' df =","weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap","merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find t-13 prices for","'139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603',","'t-13 price', np.nan) for month in mom_months: # Find t-13 prices for ticker","= merged_df.loc[me_condition & mom_condition] # Split each month ME into two groups conditions","labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = (","the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda","indicating open market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel( index_path,","pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True)","'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict()","ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) -","df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df =","'139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502',","'139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803',","for market cap # Concat all 75 tickers' data me_list = [] for","'139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711',","t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion","df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df)","= pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) #","]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return']","sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL'","Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl)","previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna())","t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion","x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom']","price']) - 1 ) mom_list = [] for month in mom_months: # Check","sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return =","of months that we need for calculating market cap me_months = [ '139312',","'t-13 price' ] = t_13_price except: pass # Calculate last 12 months return","and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a","r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True)","a list mom = ( ((sh_return + bh_return) / 2) - ((sl_return +","mom_list = [] for month in mom_months: # Check t-13 price condition and","bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) #","df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df =","bh_return) / 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom) mom_df =","<= '139900')] # Read index df for indicating open market days index_path =","numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for","= me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard","mom_months: # Check t-13 price condition and t-1 market cap condition previous_month =","'139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707',","] # The list of months that we need for camculating MOM mom_months","dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist()","in month t # Set conditions month_condition = (merged_df['date'] == month) bh_condition =","= (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month","df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] )","we need for calculating market cap me_months = [ '139312', '139401', '139402', '139403',","merged_df['t-13 price']) - 1 ) mom_list = [] for month in mom_months: #","Calculate last 12 months return for month t (t-1, t-12) merged_df['past_year_return'] = (",">= '139212') & (df['date'] <= '139900')] # Read index df for indicating open","portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split","'139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710',","weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add","x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index()",".3, .7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] ==","'139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605',","f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0]","'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect","np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3","portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH'","calculating returns close_list = [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New","me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365","index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list","(merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except:","= merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition","index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] =","cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create","me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df =","= me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create","t # Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition",") bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap )","# Read rahavard 365 data for calculating returns close_list = [] for file_number","dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df =","== previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each","= ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist()","pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve","76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition =","pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column, and then add","in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt' df","me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >=","365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str},","x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s","merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition]","list of months that we need for calculating market cap me_months = [","1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return']","= me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition),","months that we need for camculating MOM mom_months = me_months[1:] # Merge market","[0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size']","'139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801',","it to a list mom = ( ((sh_return + bh_return) / 2) -","then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: #","portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio']","create a NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan)","portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio =","usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old","'139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The list","np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a list","df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index df for indicating","me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) #","ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) #","['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b,","1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ]","'139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704',","dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df","portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom))","df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')]","= merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition]","= me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True)","'139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706',","] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me","'139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ]","add it to a list mom = ( ((sh_return + bh_return) / 2)","13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price","Calculate MOM, and add it to a list mom = ( ((sh_return +","on=['ticker_num', 'date']) # First, create a NaN column, and then add t-13 prices","# The list of months that we need for camculating MOM mom_months =","= (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[","portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh","problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert to","that we need for camculating MOM mom_months = me_months[1:] # Merge market cap","11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old to new","df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index df","of months that we need for camculating MOM mom_months = me_months[1:] # Merge","bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio","'139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806',","merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition &","Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date',","'139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702',","each me portfolio into 3 MOM group q = [0, .3, .7, 1]","in mom_months: # Check t-13 price condition and t-1 market cap condition previous_month","> portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B',","= f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2,","'139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508',","pass # Calculate last 12 months return for month t (t-1, t-12) merged_df['past_year_return']","two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <=","= df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df","import numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data","'') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe","as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market","market cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month)","'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S'","in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df","dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change()","header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas add 2","# Concat all 75 tickers' data me_list = [] for file_number in range(1,","= months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] ==","to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly","The list of months that we need for camculating MOM mom_months = me_months[1:]","Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return,",") sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap )","]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month t # Set","np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM,","= np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return =","# The list of months that we need for calculating market cap me_months","price condition and t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition","list mom = ( ((sh_return + bh_return) / 2) - ((sl_return + bl_return)","Solve index reading problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True)","t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 )","'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas add","(merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME into two","[] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard","old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete","# Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] =","tickers' data me_list = [] for file_number in range(1, 76): print(file_number) me_path =","- 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price'","# Find t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month) -","Read Bourseview data for market cap # Concat all 75 tickers' data me_list","me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True)","usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months months","we need for camculating MOM mom_months = me_months[1:] # Merge market cap and","list of months that we need for camculating MOM mom_months = me_months[1:] #","previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass #","me portfolio into 3 MOM group q = [0, .3, .7, 1] labels","= df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index df for","me_months[1:] # Merge market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num',","'139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504',","file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >=","= df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last()","portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME into two groups","try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1]","= me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date']","'139808', '139809', '139810', '139811', '139812' ] # The list of months that we","'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio']","returns close_list = [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily","prices for ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion =","), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6,","weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap","The list of all months months = index_df['date'].str[:6].unique().tolist() # The list of months","mom_months = me_months[1:] # Merge market cap and price dfs merged_df = pd.merge(df,","# Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) #","& bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] #","= (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] #",") bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] ==","prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find t-13 prices","'139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511',","group q = [0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b","months months = index_df['date'].str[:6].unique().tolist() # The list of months that we need for","= pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of","# Calculate last 12 months return for month t (t-1, t-12) merged_df['past_year_return'] =","days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date':","'139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512',","t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num']","previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month","index df for indicating open market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df","3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old to","= merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion =","# Read index df for indicating open market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص","df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list,","for month in mom_months: # Check t-13 price condition and t-1 market cap",") # Solve index reading problem, pandas add 2 index to the df","inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index()",".7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B'","portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl","import pandas as pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None","ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index","np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average(","inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num',","= df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True)","as pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read","'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return","month ME into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ),","# First, create a NaN column, and then add t-13 prices merged_df.insert(5, 't-13","# Split each me portfolio into 3 MOM group q = [0, .3,","of all months months = index_df['date'].str[:6].unique().tolist() # The list of months that we","['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3 MOM","f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3,","me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly","that we need for calculating market cap me_months = [ '139312', '139401', '139402',","t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list =","for each portfolio in month t # Set conditions month_condition = (merged_df['date'] ==","value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap","market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First,","merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition","= months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df","sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a list mom","Calculating value-weighted return for each portfolio in month t # Set conditions month_condition","'139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709',","76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv(","portfolio_size) # Split each me portfolio into 3 MOM group q = [0,","market cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407',","parse_dates=[0] ) # Solve index reading problem, pandas add 2 index to the","and t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date']","portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating","== 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month t","+ bh_return) / 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom) mom_df","portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in","pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom']","f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7],","& ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month)","+ portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[","merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = []","portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[","month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1","last 12 months return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close']","Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df)","# Calculate MOM, and add it to a list mom = ( ((sh_return","mom = ( ((sh_return + bh_return) / 2) - ((sl_return + bl_return) /","portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl =","'139811', '139812' ] # The list of months that we need for camculating","into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap']","close_list = [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data","t-13 price condition and t-1 market cap condition previous_month = months[months.index(month) - 1]","= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist()","q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] =","= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist()","& ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate last 12","merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate","merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date']","t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] =","'139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611',","Data - Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'],","(merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = [] for month in","Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date':","'139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712',","except: pass # Calculate last 12 months return for month t (t-1, t-12)","portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom)","df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212')","np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market cap","# Solve index reading problem, pandas add 2 index to the df df.reset_index(drop=True,","'139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The","= t_13_price except: pass # Calculate last 12 months return for month t","str} ) index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist() #","= None # Read Bourseview data for market cap # Concat all 75","= portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] =","bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL'","= merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns","= pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True,","] = t_13_price except: pass # Calculate last 12 months return for month","[] for month in mom_months: # Check t-13 price condition and t-1 market","365 data for calculating returns close_list = [] for file_number in range(1, 76):","camculating MOM mom_months = me_months[1:] # Merge market cap and price dfs merged_df","from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') #","- 1 ) mom_list = [] for month in mom_months: # Check t-13","= pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) #","'139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501',","month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition =","'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month t #","'139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810',","= merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition &","Split each month ME into two groups conditions = [ ( portfo_const_df['market_cap'] >","& mom_condition] # Split each month ME into two groups conditions = [","portfolio into 3 MOM group q = [0, .3, .7, 1] labels =","rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index","mom_condition] # Split each month ME into two groups conditions = [ (","<= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) #","((sh_return + bh_return) / 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom)","- 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition","1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition &","me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212')","months = index_df['date'].str[:6].unique().tolist() # The list of months that we need for calculating","= (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME into","for month in mom_months: # Find t-13 prices for ticker in range(1, 76):","'date']) # First, create a NaN column, and then add t-13 prices merged_df.insert(5,",") # Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date']","calculating market cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406',","The list of months that we need for calculating market cap me_months =","rahavard 365 data for calculating returns close_list = [] for file_number in range(1,","- Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open',","7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem,","Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio","= [0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[","Find t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month) - 13]","( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size',","import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market cap #","sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return,","months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df =","me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <=","for indicating open market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel(","'market_cap'], na_values='-' ) # Change order from old to new dates me_df =","portfolio in month t # Set conditions month_condition = (merged_df['date'] == month) bh_condition","index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist() # The list","'139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for","condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition =","to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply(","sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and","s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker","print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path,","sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to","= me_months[1:] # Merge market cap and price dfs merged_df = pd.merge(df, me_df,","( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size =","'139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705',","'139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607',","# Merge market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date'])","- 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try:","'139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601',","close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <=","( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = [] for month","# Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df","conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition","= r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} )","bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return,","2 index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date']","sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted","portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] )","reading problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert","( ((sh_return + bh_return) / 2) - ((sl_return + bl_return) / 2) )","pd.options.mode.chained_assignment = None # Read Bourseview data for market cap # Concat all","inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') )","each portfolio in month t # Set conditions month_condition = (merged_df['date'] == month)","order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '')","'139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510',","index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months","new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days","NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month","range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition","(t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate last","Bourseview data for market cap # Concat all 75 tickers' data me_list =","groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median()","bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition","= [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ]","bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition","/ 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom) mom_df = pd.Series(mom_list).to_excel('mom.xlsx')","Read rahavard 365 data for calculating returns close_list = [] for file_number in","= np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return =","# Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average(","me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition]","'139812' ] # The list of months that we need for camculating MOM","me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13","'139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804',","bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return,","me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7,","merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap )","== t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion &","# Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh","sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average(","= pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom =","a NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for","pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change","# Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition]","df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda x:","bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH'","'139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811',","ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate last 12 months","== 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] ==","= merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition &","for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\","12 months return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] /","me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns close_list = []","# The list of all months months = index_df['date'].str[:6].unique().tolist() # The list of","Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'],","= np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into","file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\ f'{file_number}.txt'","Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return']","monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] =","'139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412',","'139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] #","merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column, and","me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order","ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0]","(merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month =","portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size']","'139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608',","merged_df.loc[me_condition & mom_condition] # Split each month ME into two groups conditions =","= me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open',","add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find","df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df","df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date']","'139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609',","& sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return","'139810', '139811', '139812' ] # The list of months that we need for","month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl)","= merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio =","= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio",") mom_list = [] for month in mom_months: # Check t-13 price condition","= f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2,","# Calculating value-weighted return for each portfolio in month t # Set conditions","for camculating MOM mom_months = me_months[1:] # Merge market cap and price dfs",") # Calculate MOM, and add it to a list mom = (","]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] ==","== 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[","names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old to new dates","me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df =","= [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data -","me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df","t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] ==","'139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807',","data for market cap # Concat all 75 tickers' data me_list = []","sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition &","'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3 MOM group","np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average(","'139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505',","Data - Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date',","- Rahavard 365/'\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0,","pandas add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi","MOM, and add it to a list mom = ( ((sh_return + bh_return)","= merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap","'139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507',","Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-',","me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read","= index_df['date'].str[:6].unique().tolist() # The list of months that we need for calculating market","lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df =","me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True)","(t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list","t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] ==","= [] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data","Read index df for indicating open market days index_path = r'E:\\Thesis\\New Sampling\\TEDPIX\\شاخص كل6.xls'","for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) -","= ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = [] for","bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return","months that we need for calculating market cap me_months = [ '139312', '139401',","cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408',","returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap )","76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\ f'{file_number}.xlsx' me_df = pd.read_excel(","'139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The list of","for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\","Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df =","t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition","# Split each month ME into two groups conditions = [ ( portfo_const_df['market_cap']","]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion","for calculating market cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405',","t_13_price except: pass # Calculate last 12 months return for month t (t-1,","# Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number)","& (df['date'] <= '139900')] # Read index df for indicating open market days",") sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it","sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio =","= merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct","cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition"],"string":"[\n \"== ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month)\",\n \"'139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509',\",\n \"'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio']\",\n \"index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str}\",\n \"portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[\",\n \"conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() )\",\n \"index_df['date'].str[:6].unique().tolist() # The list of months that we need for calculating market cap\",\n \"'139807', '139808', '139809', '139810', '139811', '139812' ] # The list of months that\",\n \"(merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split\",\n \"ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio']\",\n \"= pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] #\",\n \"to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded\",\n \"portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size)\",\n \"Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11],\",\n \"= pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] +\",\n \"'139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610',\",\n \"all 75 tickers' data me_list = [] for file_number in range(1, 76): print(file_number)\",\n \"portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions,\",\n \"non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last()\",\n \"portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio\",\n \"rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path,\",\n \"price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN\",\n \"labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict()\",\n \"df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df =\",\n \"'139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606',\",\n \"me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')]\",\n \"= [] for month in mom_months: # Check t-13 price condition and t-1\",\n \"return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price'])\",\n \"= portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s =\",\n \"= (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh)\",\n \"]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for\",\n \"data for calculating returns close_list = [] for file_number in range(1, 76): rahavard_path\",\n \"pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview\",\n \"[ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size\",\n \"list of all months months = index_df['date'].str[:6].unique().tolist() # The list of months that\",\n \"Split each me portfolio into 3 MOM group q = [0, .3, .7,\",\n \"ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[\",\n \"jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1,\",\n \"'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date']\",\n \") index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist() # The\",\n \"= pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers\",\n \"# Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number)\",\n \"Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh =\",\n \"portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size']\",\n \"for calculating returns close_list = [] for file_number in range(1, 76): rahavard_path =\",\n \"add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates\",\n \"ME into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), (\",\n \"portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist()\",\n \"df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df\",\n \"= ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom =\",\n \"]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio\",\n \"dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'],\",\n \"me_df, on=['ticker_num', 'date']) # First, create a NaN column, and then add t-13\",\n \"'139900')] # Read index df for indicating open market days index_path = r'E:\\\\Thesis\\\\New\",\n \"'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') &\",\n \"and add it to a list mom = ( ((sh_return + bh_return) /\",\n \"'139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708',\",\n \"<reponame>behnoud-bazrafshan/ThesisPortfolio import pandas as pd import numpy as np import jdatetime pd.options.mode.chained_assignment =\",\n \"= np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate\",\n \"file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx'\",\n \"me_list = [] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily\",\n \"skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from\",\n \"'139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701',\",\n \"pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read\",\n \"1 ) mom_list = [] for month in mom_months: # Check t-13 price\",\n \"month t # Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh)\",\n \"'139809', '139810', '139811', '139812' ] # The list of months that we need\",\n \"MOM mom_months = me_months[1:] # Merge market cap and price dfs merged_df =\",\n \"df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d')\",\n \"portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month\",\n \"monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df\",\n \"'size', portfolio_size) # Split each me portfolio into 3 MOM group q =\",\n \"'139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604',\",\n \"'139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns close_list =\",\n \"(df['date'] <= '139900')] # Read index df for indicating open market days index_path\",\n \"= [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410',\",\n \"& bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio\",\n \"names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas\",\n \"shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe\",\n \"& sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return =\",\n \"Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create\",\n \"pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s,\",\n \"ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] ==\",\n \"= pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column, and then\",\n \"'open', 'market_cap'], na_values='-' ) # Change order from old to new dates me_df\",\n \"t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price =\",\n \"q = [0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b =\",\n \"= (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price\",\n \"need for calculating market cap me_months = [ '139312', '139401', '139402', '139403', '139404',\",\n \"df for indicating open market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df =\",\n \"into 3 MOM group q = [0, .3, .7, 1] labels = ['L',\",\n \"& (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating\",\n \"in mom_months: # Find t-13 prices for ticker in range(1, 76): t_13 =\",\n \"previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion &\",\n \"sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) #\",\n \"'139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506',\",\n \"portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3 MOM group q\",\n \"(merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition\",\n \"75 tickers' data me_list = [] for file_number in range(1, 76): print(file_number) me_path\",\n \"days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df\",\n \") ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each\",\n \"t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find t-13\",\n \"month in mom_months: # Check t-13 price condition and t-1 market cap condition\",\n \"portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh =\",\n \"(me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns\",\n \"dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas add 2 index\",\n \"== month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition =\",\n \"months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker)\",\n \"na_values='-' ) # Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True)\",\n \"3 MOM group q = [0, .3, .7, 1] labels = ['L', 'M',\",\n \"bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return\",\n \"Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) #\",\n \"pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all\",\n \"/ merged_df['t-13 price']) - 1 ) mom_list = [] for month in mom_months:\",\n \") # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num',\",\n \"and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months:\",\n \"b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom\",\n \"merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition]\",\n \"market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'],\",\n \"mom_months: # Find t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month)\",\n \"'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q,\",\n \"( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl\",\n \"dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column,\",\n \"== 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[\",\n \"merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return\",\n \"merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio\",\n \"cap # Concat all 75 tickers' data me_list = [] for file_number in\",\n \"for ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date']\",\n \"all months months = index_df['date'].str[:6].unique().tolist() # The list of months that we need\",\n \"'139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The list of months\",\n \"me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409',\",\n \"price', np.nan) for month in mom_months: # Find t-13 prices for ticker in\",\n \"= ( ((sh_return + bh_return) / 2) - ((sl_return + bl_return) / 2)\",\n \"q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q,\",\n \"'139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703',\",\n \"<= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns close_list\",\n \"pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio']\",\n \"condition and t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition =\",\n \"months return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13\",\n \"bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio =\",\n \"'139212') & (df['date'] <= '139900')] # Read index df for indicating open market\",\n \"'139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808',\",\n \"# Read Bourseview data for market cap # Concat all 75 tickers' data\",\n \"str}, parse_dates=[0] ) # Solve index reading problem, pandas add 2 index to\",\n \"each month ME into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median()\",\n \"'139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809',\",\n \"First, create a NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price',\",\n \"portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl =\",\n \"merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios\",\n \"index reading problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True) #\",\n \"names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months months =\",\n \"range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df =\",\n \"need for camculating MOM mom_months = me_months[1:] # Merge market cap and price\",\n \"[ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411',\",\n \"[] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data -\",\n \"'139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802',\",\n \"Merge market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) #\",\n \"month in mom_months: # Find t-13 prices for ticker in range(1, 76): t_13\",\n \"كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The\",\n \"usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading\",\n \"mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME\",\n \"column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in\",\n \"== 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) #\",\n \"MOM group q = [0, .3, .7, 1] labels = ['L', 'M', 'H']\",\n \"weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a list mom =\",\n \"= df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') &\",\n \"None # Read Bourseview data for market cap # Concat all 75 tickers'\",\n \"sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each\",\n \"data me_list = [] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New\",\n \">= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data\",\n \"== 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted\",\n \"return for each portfolio in month t # Set conditions month_condition = (merged_df['date']\",\n \"'139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812'\",\n \"me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1,\",\n \"Check t-13 price condition and t-1 market cap condition previous_month = months[months.index(month) -\",\n \"jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market cap # Concat\",\n \"inplace=True) # Read rahavard 365 data for calculating returns close_list = [] for\",\n \"in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13)\",\n \"# Check t-13 price condition and t-1 market cap condition previous_month = months[months.index(month)\",\n \"]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] ==\",\n \"'139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503',\",\n \"Concat all 75 tickers' data me_list = [] for file_number in range(1, 76):\",\n \"open market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1],\",\n \"(merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion\",\n \"'139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602',\",\n \"price' ] = t_13_price except: pass # Calculate last 12 months return for\",\n \"labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom\",\n \"numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] ==\",\n \"portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() #\",\n \"# Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition =\",\n \"to a list mom = ( ((sh_return + bh_return) / 2) - ((sl_return\",\n \"market cap # Concat all 75 tickers' data me_list = [] for file_number\",\n \"== previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass\",\n \"pandas as pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None #\",\n \"me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' )\",\n \"'139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612',\",\n \"f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-'\",\n \"file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date']\",\n \"me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list,\",\n \"'139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805',\",\n \"np.nan) for month in mom_months: # Find t-13 prices for ticker in range(1,\",\n \"= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist()\",\n \"value-weighted return for each portfolio in month t # Set conditions month_condition =\",\n \"bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate\",\n \"= np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a\",\n \"range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt' df =\",\n \"weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap\",\n \"merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find t-13 prices for\",\n \"'139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603',\",\n \"'t-13 price', np.nan) for month in mom_months: # Find t-13 prices for ticker\",\n \"= merged_df.loc[me_condition & mom_condition] # Split each month ME into two groups conditions\",\n \"labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = (\",\n \"the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda\",\n \"indicating open market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path,\",\n \"pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True)\",\n \"'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict()\",\n \"ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) -\",\n \"df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df =\",\n \"'139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502',\",\n \"'139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803',\",\n \"for market cap # Concat all 75 tickers' data me_list = [] for\",\n \"'139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711',\",\n \"t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion\",\n \"df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df)\",\n \"= pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) #\",\n \"]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return']\",\n \"sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL'\",\n \"Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl)\",\n \"previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna())\",\n \"t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion\",\n \"x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom']\",\n \"price']) - 1 ) mom_list = [] for month in mom_months: # Check\",\n \"sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return =\",\n \"of months that we need for calculating market cap me_months = [ '139312',\",\n \"'t-13 price' ] = t_13_price except: pass # Calculate last 12 months return\",\n \"and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a\",\n \"r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True)\",\n \"a list mom = ( ((sh_return + bh_return) / 2) - ((sl_return +\",\n \"mom_list = [] for month in mom_months: # Check t-13 price condition and\",\n \"bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) #\",\n \"df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df =\",\n \"bh_return) / 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom) mom_df =\",\n \"<= '139900')] # Read index df for indicating open market days index_path =\",\n \"numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for\",\n \"= me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard\",\n \"mom_months: # Check t-13 price condition and t-1 market cap condition previous_month =\",\n \"'139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707',\",\n \"] # The list of months that we need for camculating MOM mom_months\",\n \"dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist()\",\n \"in month t # Set conditions month_condition = (merged_df['date'] == month) bh_condition =\",\n \"= (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month\",\n \"df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] )\",\n \"we need for calculating market cap me_months = [ '139312', '139401', '139402', '139403',\",\n \"merged_df['t-13 price']) - 1 ) mom_list = [] for month in mom_months: #\",\n \"Calculate last 12 months return for month t (t-1, t-12) merged_df['past_year_return'] = (\",\n \">= '139212') & (df['date'] <= '139900')] # Read index df for indicating open\",\n \"portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split\",\n \"'139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710',\",\n \"weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add\",\n \"x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index()\",\n \".3, .7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] ==\",\n \"'139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605',\",\n \"f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0]\",\n \"'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect\",\n \"np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3\",\n \"portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH'\",\n \"calculating returns close_list = [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New\",\n \"me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365\",\n \"index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list\",\n \"(merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except:\",\n \"= merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition\",\n \"index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] =\",\n \"cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create\",\n \"me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df =\",\n \"= me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create\",\n \"t # Set conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition\",\n \") bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap )\",\n \"# Read rahavard 365 data for calculating returns close_list = [] for file_number\",\n \"dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df =\",\n \"== previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each\",\n \"= ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist()\",\n \"pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve\",\n \"76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition =\",\n \"pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column, and then add\",\n \"in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt' df\",\n \"me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >=\",\n \"365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str},\",\n \"x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s\",\n \"merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition]\",\n \"list of months that we need for calculating market cap me_months = [\",\n \"1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return']\",\n \"= me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition),\",\n \"months that we need for camculating MOM mom_months = me_months[1:] # Merge market\",\n \"[0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size']\",\n \"'139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801',\",\n \"it to a list mom = ( ((sh_return + bh_return) / 2) -\",\n \"then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: #\",\n \"portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio']\",\n \"create a NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan)\",\n \"portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio =\",\n \"usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old\",\n \"'139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The list\",\n \"np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a list\",\n \"df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index df for indicating\",\n \"me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) #\",\n \"ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) #\",\n \"['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b,\",\n \"1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ]\",\n \"'139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704',\",\n \"dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df\",\n \"portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom))\",\n \"df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')]\",\n \"= merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition]\",\n \"= me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True)\",\n \"'139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706',\",\n \"] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me\",\n \"'139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ]\",\n \"add it to a list mom = ( ((sh_return + bh_return) / 2)\",\n \"13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price\",\n \"Calculate MOM, and add it to a list mom = ( ((sh_return +\",\n \"on=['ticker_num', 'date']) # First, create a NaN column, and then add t-13 prices\",\n \"# The list of months that we need for camculating MOM mom_months =\",\n \"= (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[\",\n \"portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh\",\n \"problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert to\",\n \"that we need for camculating MOM mom_months = me_months[1:] # Merge market cap\",\n \"11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old to new\",\n \"df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index df\",\n \"of months that we need for camculating MOM mom_months = me_months[1:] # Merge\",\n \"bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio\",\n \"'139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806',\",\n \"merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition &\",\n \"Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date',\",\n \"'139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702',\",\n \"each me portfolio into 3 MOM group q = [0, .3, .7, 1]\",\n \"in mom_months: # Check t-13 price condition and t-1 market cap condition previous_month\",\n \"> portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B',\",\n \"= f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2,\",\n \"'139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508',\",\n \"pass # Calculate last 12 months return for month t (t-1, t-12) merged_df['past_year_return']\",\n \"two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <=\",\n \"= df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df\",\n \"import numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data\",\n \"'') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe\",\n \"as np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market\",\n \"market cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month)\",\n \"'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S'\",\n \"in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df\",\n \"dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change()\",\n \"header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas add 2\",\n \"# Concat all 75 tickers' data me_list = [] for file_number in range(1,\",\n \"= months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] ==\",\n \"to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly\",\n \"The list of months that we need for camculating MOM mom_months = me_months[1:]\",\n \"Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return,\",\n \") sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap )\",\n \"]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month t # Set\",\n \"np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM,\",\n \"= np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return =\",\n \"# The list of months that we need for calculating market cap me_months\",\n \"price condition and t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition\",\n \"list mom = ( ((sh_return + bh_return) / 2) - ((sl_return + bl_return)\",\n \"Solve index reading problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True)\",\n \"t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 )\",\n \"'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem, pandas add\",\n \"(merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME into two\",\n \"[] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard\",\n \"old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete\",\n \"# Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] =\",\n \"tickers' data me_list = [] for file_number in range(1, 76): print(file_number) me_path =\",\n \"- 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price'\",\n \"# Find t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month) -\",\n \"Read Bourseview data for market cap # Concat all 75 tickers' data me_list\",\n \"me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True)\",\n \"usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months months\",\n \"we need for camculating MOM mom_months = me_months[1:] # Merge market cap and\",\n \"list of months that we need for camculating MOM mom_months = me_months[1:] #\",\n \"previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass #\",\n \"me portfolio into 3 MOM group q = [0, .3, .7, 1] labels\",\n \"= df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index df for\",\n \"me_months[1:] # Merge market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num',\",\n \"'139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504',\",\n \"file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >=\",\n \"= df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last()\",\n \"portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME into two groups\",\n \"try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1]\",\n \"= me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date']\",\n \"'139808', '139809', '139810', '139811', '139812' ] # The list of months that we\",\n \"'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio']\",\n \"returns close_list = [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily\",\n \"prices for ticker in range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion =\",\n \"), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6,\",\n \"weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap\",\n \"The list of all months months = index_df['date'].str[:6].unique().tolist() # The list of months\",\n \"mom_months = me_months[1:] # Merge market cap and price dfs merged_df = pd.merge(df,\",\n \"# Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) #\",\n \"& bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] #\",\n \"= (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] #\",\n \") bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] ==\",\n \"prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find t-13 prices\",\n \"'139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511',\",\n \"group q = [0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b\",\n \"months months = index_df['date'].str[:6].unique().tolist() # The list of months that we need for\",\n \"= pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of\",\n \"# Calculate last 12 months return for month t (t-1, t-12) merged_df['past_year_return'] =\",\n \"days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date':\",\n \"'139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512',\",\n \"t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num']\",\n \"previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month\",\n \"index df for indicating open market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df\",\n \"3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old to\",\n \"= merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion =\",\n \"# Read index df for indicating open market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص\",\n \"df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list,\",\n \"for month in mom_months: # Check t-13 price condition and t-1 market cap\",\n \") # Solve index reading problem, pandas add 2 index to the df\",\n \"inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index()\",\n \".7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[ portfo_const_df['size'] == 'B'\",\n \"portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl\",\n \"import pandas as pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None\",\n \"ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <= '139900')] # Read index\",\n \"np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average(\",\n \"inplace=True) # Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num',\",\n \"= df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True)\",\n \"as pd import numpy as np import jdatetime pd.options.mode.chained_assignment = None # Read\",\n \"'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return\",\n \"month ME into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ),\",\n \"# First, create a NaN column, and then add t-13 prices merged_df.insert(5, 't-13\",\n \"# Split each me portfolio into 3 MOM group q = [0, .3,\",\n \"of all months months = index_df['date'].str[:6].unique().tolist() # The list of months that we\",\n \"['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3 MOM\",\n \"f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3,\",\n \"me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly\",\n \"that we need for calculating market cap me_months = [ '139312', '139401', '139402',\",\n \"t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list =\",\n \"for each portfolio in month t # Set conditions month_condition = (merged_df['date'] ==\",\n \"value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap\",\n \"market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First,\",\n \"merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition\",\n \"= months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df\",\n \"sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to a list mom\",\n \"Calculating value-weighted return for each portfolio in month t # Set conditions month_condition\",\n \"'139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709',\",\n \"76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv(\",\n \"portfolio_size) # Split each me portfolio into 3 MOM group q = [0,\",\n \"market cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407',\",\n \"parse_dates=[0] ) # Solve index reading problem, pandas add 2 index to the\",\n \"and t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date']\",\n \"portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating\",\n \"== 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month t\",\n \"+ bh_return) / 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom) mom_df\",\n \"portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in\",\n \"pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom']\",\n \"f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7],\",\n \"& ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month)\",\n \"+ portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[\",\n \"merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = []\",\n \"portfo_const_df.loc[ portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[\",\n \"month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1\",\n \"last 12 months return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close']\",\n \"Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df)\",\n \"# Calculate MOM, and add it to a list mom = ( ((sh_return\",\n \"mom = ( ((sh_return + bh_return) / 2) - ((sl_return + bl_return) /\",\n \"portfo_const_df['size'] + portfo_const_df['mom'] ) bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl =\",\n \"'139811', '139812' ] # The list of months that we need for camculating\",\n \"into two groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap']\",\n \"close_list = [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data\",\n \"t-13 price condition and t-1 market cap condition previous_month = months[months.index(month) - 1]\",\n \"= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist()\",\n \"q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] =\",\n \"= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist()\",\n \"& ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate last 12\",\n \"merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate\",\n \"merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date']\",\n \"t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13 price' ] =\",\n \"'139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609', '139610', '139611',\",\n \"Data - Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'],\",\n \"(merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = [] for month in\",\n \"Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date':\",\n \"'139612', '139701', '139702', '139703', '139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712',\",\n \"except: pass # Calculate last 12 months return for month t (t-1, t-12)\",\n \"portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom)\",\n \"df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212')\",\n \"np import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market cap\",\n \"# Solve index reading problem, pandas add 2 index to the df df.reset_index(drop=True,\",\n \"'139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The\",\n \"= t_13_price except: pass # Calculate last 12 months return for month t\",\n \"str} ) index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist() #\",\n \"= None # Read Bourseview data for market cap # Concat all 75\",\n \"= portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] =\",\n \"bh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL'\",\n \"= merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns\",\n \"= pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True,\",\n \"] = t_13_price except: pass # Calculate last 12 months return for month\",\n \"[] for month in mom_months: # Check t-13 price condition and t-1 market\",\n \"365 data for calculating returns close_list = [] for file_number in range(1, 76):\",\n \"camculating MOM mom_months = me_months[1:] # Merge market cap and price dfs merged_df\",\n \"from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') #\",\n \"- 1 ) mom_list = [] for month in mom_months: # Check t-13\",\n \"= pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) #\",\n \"'139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501',\",\n \"month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition =\",\n \"'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio in month t #\",\n \"'139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810',\",\n \"= merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition &\",\n \"Split each month ME into two groups conditions = [ ( portfo_const_df['market_cap'] >\",\n \"& mom_condition] # Split each month ME into two groups conditions = [\",\n \"portfolio into 3 MOM group q = [0, .3, .7, 1] labels =\",\n \"rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index\",\n \"mom_condition] # Split each month ME into two groups conditions = [ (\",\n \"<= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) #\",\n \"((sh_return + bh_return) / 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom)\",\n \"- 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition\",\n \"1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition &\",\n \"me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212')\",\n \"months = index_df['date'].str[:6].unique().tolist() # The list of months that we need for calculating\",\n \"= (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition] # Split each month ME into\",\n \"for month in mom_months: # Find t-13 prices for ticker in range(1, 76):\",\n \"'date']) # First, create a NaN column, and then add t-13 prices merged_df.insert(5,\",\n \") # Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date']\",\n \"calculating market cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406',\",\n \"The list of months that we need for calculating market cap me_months =\",\n \"rahavard 365 data for calculating returns close_list = [] for file_number in range(1,\",\n \"- Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open',\",\n \"7], names=['date', 'close'], header=0, dtype={'date': str}, parse_dates=[0] ) # Solve index reading problem,\",\n \"Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio\",\n \"= [0, .3, .7, 1] labels = ['L', 'M', 'H'] x_b = portfo_const_df.loc[\",\n \"Find t-13 prices for ticker in range(1, 76): t_13 = months[months.index(month) - 13]\",\n \"( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size = np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size',\",\n \"import jdatetime pd.options.mode.chained_assignment = None # Read Bourseview data for market cap #\",\n \"sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return,\",\n \"months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df =\",\n \"me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <=\",\n \"for indicating open market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel(\",\n \"'market_cap'], na_values='-' ) # Change order from old to new dates me_df =\",\n \"portfolio in month t # Set conditions month_condition = (merged_df['date'] == month) bh_condition\",\n \"index_df.dropna(inplace=True) # The list of all months months = index_df['date'].str[:6].unique().tolist() # The list\",\n \"'139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for\",\n \"condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition =\",\n \"to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply(\",\n \"sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and\",\n \"s_mom = pd.qcut(x=x_s, q=q, labels=labels).to_dict() portfo_const_df['mom'] = pd.Series(b_mom) portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker\",\n \"print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path,\",\n \"sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it to\",\n \"= me_months[1:] # Merge market cap and price dfs merged_df = pd.merge(df, me_df,\",\n \"( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ] portfolio_size =\",\n \"'139605', '139606', '139607', '139608', '139609', '139610', '139611', '139612', '139701', '139702', '139703', '139704', '139705',\",\n \"'139507', '139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607',\",\n \"# Merge market cap and price dfs merged_df = pd.merge(df, me_df, on=['ticker_num', 'date'])\",\n \"- 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try:\",\n \"'139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510', '139511', '139512', '139601',\",\n \"close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date'] <=\",\n \"( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = [] for month\",\n \"# Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df\",\n \"conditions month_condition = (merged_df['date'] == month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition\",\n \"= r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls' index_df = pd.read_excel( index_path, usecols=[1], names=['date'], dtype={'date': str} )\",\n \"bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return = np.average( sl_portfolio.monthly_return,\",\n \"2 index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date']\",\n \"sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted\",\n \"portfo_const_df['mom'].update(pd.Series(s_mom)) # Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] )\",\n \"reading problem, pandas add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert\",\n \"( ((sh_return + bh_return) / 2) - ((sl_return + bl_return) / 2) )\",\n \"pd.options.mode.chained_assignment = None # Read Bourseview data for market cap # Concat all\",\n \"inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') )\",\n \"each portfolio in month t # Set conditions month_condition = (merged_df['date'] == month)\",\n \"order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '')\",\n \"'139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509', '139510',\",\n \"index_path, usecols=[1], names=['date'], dtype={'date': str} ) index_df.dropna(inplace=True) # The list of all months\",\n \"new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days\",\n \"NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month\",\n \"range(1, 76): t_13 = months[months.index(month) - 13] t_13_condtion = (merged_df['date'] == t_13) ticker_condition\",\n \"(t_1_condtion & ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate last\",\n \"Bourseview data for market cap # Concat all 75 tickers' data me_list =\",\n \"groups conditions = [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median()\",\n \"bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition\",\n \"= [ ( portfo_const_df['market_cap'] > portfo_const_df['market_cap'].median() ), ( portfo_const_df['market_cap'] <= portfo_const_df['market_cap'].median() ) ]\",\n \"bl_portfolio = merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition\",\n \"/ 2) - ((sl_return + bl_return) / 2) ) mom_list.append(mom) mom_df = pd.Series(mom_list).to_excel('mom.xlsx')\",\n \"Read rahavard 365 data for calculating returns close_list = [] for file_number in\",\n \"= np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return =\",\n \"# Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average(\",\n \"me_condition = (merged_df['date'] == previous_month) mom_condition = (merged_df['past_year_return'].notna()) portfo_const_df = merged_df.loc[me_condition & mom_condition]\",\n \"'139812' ] # The list of months that we need for camculating MOM\",\n \"me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion & ticker_condition), 't-13\",\n \"'139704', '139705', '139706', '139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804',\",\n \"bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return,\",\n \"me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7,\",\n \"merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap )\",\n \"== t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion &\",\n \"# Extrect portfolio ticker numbers portfo_const_df['portfolio'] = ( portfo_const_df['size'] + portfo_const_df['mom'] ) bh\",\n \"sh_condition] sl_portfolio = merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average(\",\n \"= pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] == 'S' ]['past_year_return'] s_mom =\",\n \"a NaN column, and then add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for\",\n \"pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change\",\n \"# Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio = merged_df.loc[month_condition & bl_condition]\",\n \"df df.reset_index(drop=True, inplace=True) # Convert to shamsi dates df['date'] = df['date'].apply( lambda x:\",\n \"bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH'\",\n \"'139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811',\",\n \"ticker_condition), 't-13 price' ] = t_13_price except: pass # Calculate last 12 months\",\n \"== 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size'] ==\",\n \"= merged_df.loc[month_condition & bl_condition] sh_portfolio = merged_df.loc[month_condition & sh_condition] sl_portfolio = merged_df.loc[month_condition &\",\n \"for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\\",\n \"12 months return for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] /\",\n \"me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns close_list = []\",\n \"# The list of all months months = index_df['date'].str[:6].unique().tolist() # The list of\",\n \"Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'],\",\n \"= np.select(conditions, ['B', 'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into\",\n \"file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\ f'{file_number}.txt'\",\n \"Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return']\",\n \"monthly dataframe df = df.groupby(df['date'].str[:6]).last() df = df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] =\",\n \"'139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412',\",\n \"'139802', '139803', '139804', '139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] #\",\n \"merged_df = pd.merge(df, me_df, on=['ticker_num', 'date']) # First, create a NaN column, and\",\n \"me_path, skiprows=7, usecols=[2, 3, 11], names=['date', 'open', 'market_cap'], na_values='-' ) # Change order\",\n \"ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0]\",\n \"(merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month =\",\n \"portfo_const_df['size'] == 'B' ]['past_year_return'] b_mom = pd.qcut(x=x_b, q=q, labels=labels).to_dict() x_s = portfo_const_df.loc[ portfo_const_df['size']\",\n \"'139508', '139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608',\",\n \"merged_df.loc[me_condition & mom_condition] # Split each month ME into two groups conditions =\",\n \"= me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open',\",\n \"add t-13 prices merged_df.insert(5, 't-13 price', np.nan) for month in mom_months: # Find\",\n \"df.drop(columns=['date']).reset_index() df.insert(1, 'ticker_num', file_number) df['monthly_return'] = df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df\",\n \"df['close'].pct_change() close_list.append(df) df = pd.concat(close_list, ignore_index=True) df = df.loc[(df['date'] >= '139212') & (df['date']\",\n \"'139509', '139510', '139511', '139512', '139601', '139602', '139603', '139604', '139605', '139606', '139607', '139608', '139609',\",\n \"& sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return\",\n \"'139810', '139811', '139812' ] # The list of months that we need for\",\n \"month) bh_condition = merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl)\",\n \"= merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio =\",\n \"= portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SL' ]['ticker_num'].tolist() # Calculating value-weighted return for each portfolio\",\n \") mom_list = [] for month in mom_months: # Check t-13 price condition\",\n \"= f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2,\",\n \"# Calculating value-weighted return for each portfolio in month t # Set conditions\",\n \"for camculating MOM mom_months = me_months[1:] # Merge market cap and price dfs\",\n \") # Calculate MOM, and add it to a list mom = (\",\n \"]['ticker_num'].tolist() sh = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'SH' ]['ticker_num'].tolist() sl = portfo_const_df.loc[ portfo_const_df['portfolio'] ==\",\n \"== 'BH' ]['ticker_num'].tolist() bl = portfo_const_df.loc[ portfo_const_df['portfolio'] == 'BL' ]['ticker_num'].tolist() sh = portfo_const_df.loc[\",\n \"names=['date', 'open', 'market_cap'], na_values='-' ) # Change order from old to new dates\",\n \"me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df =\",\n \"= [] for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data -\",\n \"me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number) me_list.append(me_df) me_df = pd.concat(me_list, ignore_index=True) me_df\",\n \"t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] ==\",\n \"'139707', '139708', '139709', '139710', '139711', '139712', '139801', '139802', '139803', '139804', '139805', '139806', '139807',\",\n \"data for market cap # Concat all 75 tickers' data me_list = []\",\n \"sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition &\",\n \"'S']).tolist() portfo_const_df.insert(6, 'size', portfolio_size) # Split each me portfolio into 3 MOM group\",\n \"np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average(\",\n \"'139405', '139406', '139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505',\",\n \"Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel( me_path, skiprows=7, usecols=[2, 3, 11], names=['date',\",\n \"- Rahavard 365/'\\\\ f'{file_number}.txt' df = pd.read_csv( rahavard_path, usecols=[2, 7], names=['date', 'close'], header=0,\",\n \"pandas add 2 index to the df df.reset_index(drop=True, inplace=True) # Convert to shamsi\",\n \"MOM, and add it to a list mom = ( ((sh_return + bh_return)\",\n \"= merged_df.loc[month_condition & sl_condition] # Calculate value-weighted returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap\",\n \"'139407', '139408', '139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507',\",\n \"Change order from old to new dates me_df = me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-',\",\n \"me_df = me_df.loc[(me_df['date'] >= '139212') & (me_df['date'] <= '139900')] me_df.reset_index(drop=True, inplace=True) # Read\",\n \"= index_df['date'].str[:6].unique().tolist() # The list of months that we need for calculating market\",\n \"lambda x: jdatetime.date.fromgregorian(date=x).strftime('%Y%m%d') ) # Create monthly dataframe df = df.groupby(df['date'].str[:6]).last() df =\",\n \"me_df[::-1].reset_index(drop=True) me_df['date'] = me_df['date'].str.replace('-', '') # Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True)\",\n \"(t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list\",\n \"t-1 market cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] ==\",\n \"= [] for file_number in range(1, 76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data\",\n \"Read index df for indicating open market days index_path = r'E:\\\\Thesis\\\\New Sampling\\\\TEDPIX\\\\شاخص كل6.xls'\",\n \"for month t (t-1, t-12) merged_df['past_year_return'] = ( (merged_df['close'] / merged_df['t-13 price']) -\",\n \"= ( (merged_df['close'] / merged_df['t-13 price']) - 1 ) mom_list = [] for\",\n \"bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap ) sh_return = np.average( sh_portfolio.monthly_return, weights=sh_portfolio.market_cap ) sl_return\",\n \"months that we need for calculating market cap me_months = [ '139312', '139401',\",\n \"cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405', '139406', '139407', '139408',\",\n \"returns bh_return = np.average( bh_portfolio.monthly_return, weights=bh_portfolio.market_cap ) bl_return = np.average( bl_portfolio.monthly_return, weights=bl_portfolio.market_cap )\",\n \"76): print(file_number) me_path = f'E:/Thesis/New Sampling/Daily Data - Bourseview/'\\\\ f'{file_number}.xlsx' me_df = pd.read_excel(\",\n \"'139805', '139806', '139807', '139808', '139809', '139810', '139811', '139812' ] # The list of\",\n \"for file_number in range(1, 76): rahavard_path = f'E:/Thesis/New Sampling/Daily Data - Rahavard 365/'\\\\\",\n \"Delete non-traded days me_df.dropna(subset=['open'], inplace=True) me_df.drop(columns='open', inplace=True) # Create monthly dataframe me_df =\",\n \"t_13) ticker_condition = (merged_df['ticker_num'] == ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition\",\n \"# Split each month ME into two groups conditions = [ ( portfo_const_df['market_cap']\",\n \"]['close'].values[0] previous_month = me_months[me_months.index(month) - 1] t_1_condtion = (merged_df['date'] == previous_month) merged_df.loc[ (t_1_condtion\",\n \"for calculating market cap me_months = [ '139312', '139401', '139402', '139403', '139404', '139405',\",\n \"t_13_price except: pass # Calculate last 12 months return for month t (t-1,\",\n \"# Create monthly dataframe me_df = me_df.groupby(me_df['date'].str[:6]).last() me_df = me_df.drop(columns=['date']).reset_index() me_df.insert(1, 'ticker_num', file_number)\",\n \"& (df['date'] <= '139900')] # Read index df for indicating open market days\",\n \") sl_return = np.average( sl_portfolio.monthly_return, weights=sl_portfolio.market_cap ) # Calculate MOM, and add it\",\n \"sl_condition = merged_df['ticker_num'].isin(sl) # Construct portfolios bh_portfolio = merged_df.loc[month_condition & bh_condition] bl_portfolio =\",\n \"= merged_df['ticker_num'].isin(bh) bl_condition = merged_df['ticker_num'].isin(bl) sh_condition = merged_df['ticker_num'].isin(sh) sl_condition = merged_df['ticker_num'].isin(sl) # Construct\",\n \"cap condition previous_month = months[months.index(month) - 1] me_condition = (merged_df['date'] == previous_month) mom_condition\"\n]","isConversational":false}}},{"rowIdx":75,"cells":{"ngram":{"kind":"list like","value":["s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html","s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix","Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId']","urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e: print('send(..) failed executing","responseData json_response_body = json.dumps(response_body) print('Response body:\\n' + json_response_body) headers = {'content-type': 'application/json', }","responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {}","raise Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR: ' +","= {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url","raise Exception('ERROR: ' + err) print('INFO: ' + filename + ' was downloaded')","req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code:","in event: if status == 401: response = {'status': 'invalide_license_key'} else: response =","response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\n' + json_response_body) headers = {'content-type':","try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to","mmdb = directory + '/' + filename + '.mmdb' s3obj = s3key_prefix +","s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded","failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status","suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data","= 'None' if event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename)","'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os","{'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event:","responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream: ' '' +","in event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event","urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' + suffix)","'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try:","checksum is different. download is failed') return False with tarfile.open('/tmp/' + filename +","= event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\n'","as err: if err.status == 401: return err.status print(err) raise Exception('ERROR: http error')","filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb,","= s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0}","= {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res","+ '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with","Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f:","# get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key']","event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details","+ filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' +","context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename","e: print(e) if event and 'RequestType' in event: response = {'failed_reason': e} send(event,","err) print('INFO: ' + filename + ' was downloaded') return 200 def put_to_s3(filename):","open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: '","url + data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as","import os import tarfile import urllib.error import urllib.parse import urllib.request import boto3 #","requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None'","def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0]","with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if","in put_files: status = download_file(filename) if status == 401: break put_to_s3(filename) except Exception","Inc. or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ =","'.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj))","event: if status == 401: response = {'status': 'invalide_license_key'} else: response = {'status':","'RequestType' in event: if status == 401: response = {'status': 'invalide_license_key'} else: response","= json.dumps(response_body) print('Response body:\\n' + json_response_body) headers = {'content-type': 'application/json', } req =","Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__","= os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda","status = download_file(filename) if status == 401: break put_to_s3(filename) except Exception as e:","import urllib.request import boto3 # get var from lambda environment try: s3bucket_name =","physicalResourceId) if event and 'RequestType' in event: if status == 401: response =","urllib.request import boto3 # get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name']","except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/')","except Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' +","filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data,","status == 401: break put_to_s3(filename) except Exception as e: print(e) if event and","+ mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event,","str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): ' + str(e)) def","'.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR:","= f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz',","json.dumps(response_body) print('Response body:\\n' + json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request(","url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in","401: return err.status print(err) raise Exception('ERROR: http error') except Exception as err: print(err)","return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory =","download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix':","download_file(filename) if status == 401: break put_to_s3(filename) except Exception as e: print(e) if","suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename +","response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId']","filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum)","res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e: print('send(..)","context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId']","if checksum not in calcurated_checksum: print('ERROR: checksum is different. download is failed') return","Exception as e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context):","json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except","filename + '.' + suffix) except urllib.error.HTTPError as err: if err.status == 401:","json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT')","' + err) print('INFO: ' + filename + ' was downloaded') return 200","f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename","tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb' s3obj = s3key_prefix","send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if status","values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve(","urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError","<reponame>aws-samples/siem-on-amazon-opensearch-service<filename>source/lambda/geoip_downloader/index.py # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier:","checksum not in calcurated_checksum: print('ERROR: checksum is different. download is failed') return False","' + filename + ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/'","200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum =","print('Response body:\\n' + json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'],","'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req)","import json import os import tarfile import urllib.error import urllib.parse import urllib.request import","http error') except Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO:","'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename","s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL']","' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>'","in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data =","response, physicalResourceId) if event and 'RequestType' in event: if status == 401: response","mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context,","'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City',","tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb","event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData","= noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\n' + json_response_body) headers","affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ =","suffix) except urllib.error.HTTPError as err: if err.status == 401: return err.status print(err) raise","str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event))","print('ERROR: checksum is different. download is failed') return False with tarfile.open('/tmp/' + filename","+ context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] =","calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different. download","( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId']","__copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__","get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name)","os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files =","as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' +","{'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url +","urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' +","with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/')","Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3')","f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different.","+ suffix) except urllib.error.HTTPError as err: if err.status == 401: return err.status print(err)","'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' +","Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service'","' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if","or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] =","= '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib","== 401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context,","= boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country']","+ '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory +","if status == 401: break put_to_s3(filename) except Exception as e: print(e) if event","environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url =","urllib.error import urllib.parse import urllib.request import boto3 # get var from lambda environment","send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body","response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType'","= directory + '/' + filename + '.mmdb' s3obj = s3key_prefix + filename","as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename","for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix}","directory + '/' + filename + '.mmdb' s3obj = s3key_prefix + filename +","'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename in put_files: status","= event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body =","False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name","import tarfile import urllib.error import urllib.parse import urllib.request import boto3 # get var","= ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values =","= 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import","license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix","if event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if status","headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try:","as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is","bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def","put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO:","f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb')","' + str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): ' +","+ '/' + filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb'","# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0","data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.'","boto3 # get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key =","for filename in put_files: status = download_file(filename) if status == 401: break put_to_s3(filename)","Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. '","is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf:","print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb'","hashlib import json import os import tarfile import urllib.error import urllib.parse import urllib.request","print(err) raise Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR: '","print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename + ' was","== 401: break put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType'","'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename,","= responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream: ' ''","context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho","response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body","'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import urllib.error import urllib.parse","filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as err: if err.status","tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename +","as e: print(e) if event and 'RequestType' in event: response = {'failed_reason': e}","Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates.","s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN',","as e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId","+ str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): ' + str(e))","= urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e: print('send(..) failed","# SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All","failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory","lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR:","{'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res =","print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as","checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename +","or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0'","import urllib.error import urllib.parse import urllib.request import boto3 # get var from lambda","to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket =","401: break put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType' in","response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data']","SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights","+ data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as err:","if status == 401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'}","{} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream:","'2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import","' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum","https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] =","__version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import","from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise","def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try:","with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum:","== 401: return err.status print(err) raise Exception('ERROR: http error') except Exception as err:","noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus","Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright","boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def","event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body)","context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body =","except Exception as e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event,","= urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' +","print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in","err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename + '","{'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS', response, physicalResourceId) return(json.dumps(response))","= {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS', response, physicalResourceId)","401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS',","if err.status == 401: return err.status print(err) raise Exception('ERROR: http error') except Exception","'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__","except urllib.error.HTTPError as err: if err.status == 401: return err.status print(err) raise Exception('ERROR:","print('INFO: ' + filename + ' was downloaded') return 200 def put_to_s3(filename): with","+ json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers,","{0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False):","= '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile","event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and","+ filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not","+ '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum:","physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] =","CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name)","try: for filename in put_files: status = download_file(filename) if status == 401: break","+ '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name,","response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS', response,","filename + ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename","+ filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' +","bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename):","return err.status print(err) raise Exception('ERROR: http error') except Exception as err: print(err) raise","not in calcurated_checksum: print('ERROR: checksum is different. download is failed') return False with","if event and 'RequestType' in event: if status == 401: response = {'status':","data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as err: if","= download_file(filename) if status == 401: break put_to_s3(filename) except Exception as e: print(e)","'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']:","print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData,","os import tarfile import urllib.error import urllib.parse import urllib.request import boto3 # get","to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): #","response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream: '","executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status =","'' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId']","= responseData json_response_body = json.dumps(response_body) print('Response body:\\n' + json_response_body) headers = {'content-type': 'application/json',","print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if status == 401:","print('Status code: ' + str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..):","__license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json","Exception('ERROR: ' + err) print('INFO: ' + filename + ' was downloaded') return","Exception as e: print(e) if event and 'RequestType' in event: response = {'failed_reason':","urllib.error.HTTPError as err: if err.status == 401: return err.status print(err) raise Exception('ERROR: http","= ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__ =","# https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason']","'<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import","impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket","directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb'","os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment')","def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key,","= 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz',","filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in","'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/'","or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com,","'.' + suffix) except urllib.error.HTTPError as err: if err.status == 401: return err.status","its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__","put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values","+ filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb =","event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status))","= 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import urllib.error import","+ filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format(","+ str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event:","uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None,","put_files: status = download_file(filename) if status == 401: break put_to_s3(filename) except Exception as","= os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix =","} req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status","= {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch Log","if event and 'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED',","is different. download is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz',","urllib.parse import urllib.request import boto3 # get var from lambda environment try: s3bucket_name","affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or","different. download is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz')","KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3","= hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different. download is","['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values)","import hashlib import json import os import tarfile import urllib.error import urllib.parse import","response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\n' + json_response_body)","['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id':","s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get","physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename in","json_response_body = json.dumps(response_body) print('Response body:\\n' + json_response_body) headers = {'content-type': 'application/json', } req","'None' if event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if","Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__","+ filename + ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' +","e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId =","method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as","in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or","err: if err.status == 401: return err.status print(err) raise Exception('ERROR: http error') except","All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its","Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] =","get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except","status = 'None' if event: print(json.dumps(event)) try: for filename in put_files: status =","Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename","raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 =","'.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/'","import boto3 # get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key","download is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as","err.status print(err) raise Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR:","= ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] =","lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for","license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' +","responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See","mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl","+ filename + '.' + suffix) except urllib.error.HTTPError as err: if err.status ==","import urllib.parse import urllib.request import boto3 # get var from lambda environment try:","= os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files","tarfile import urllib.error import urllib.parse import urllib.request import boto3 # get var from","in calcurated_checksum: print('ERROR: checksum is different. download is failed') return False with tarfile.open('/tmp/'","e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if","its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc.","= tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb' s3obj","and 'RequestType' in event: if status == 401: response = {'status': 'invalide_license_key'} else:","'/' + filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/'","break put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType' in event:","'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum","noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\n' + json_response_body) headers =","filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory","s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to","tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb' s3obj =","open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum","s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?'","'.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/'","' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256')","= event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the","Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ =","and 'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId)","('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1'","os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix',","hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different. download is failed')","= {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in","s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus,","put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType' in event: response","the details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = (","'.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO:","+ '.' + suffix) except urllib.error.HTTPError as err: if err.status == 401: return","filename in put_files: status = download_file(filename) if status == 401: break put_to_s3(filename) except","Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ =","environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible","' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId']","checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest()","status == 401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event,","+ checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum =","responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status']","physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho']","downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f:","response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch","= ('See the details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId']","= s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for","('See the details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] =","+ '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj)","was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as","+ ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename +","lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url","return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum","s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl =","headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception","try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e:","as err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename +","calcurated_checksum: print('ERROR: checksum is different. download is failed') return False with tarfile.open('/tmp/' +","= urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: '","event and 'RequestType' in event: if status == 401: response = {'status': 'invalide_license_key'}","body:\\n' + json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(),","err.status == 401: return err.status print(err) raise Exception('ERROR: http error') except Exception as","error') except Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO: '","response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response","event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\n' +","context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if status ==","try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' + suffix) except","event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if status ==","__url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import urllib.error","details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId","= 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename in put_files:","'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if","response_body['Reason'] = ('See the details in CloudWatch Log Stream: ' '' + context.log_stream_name)","var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError:","event and 'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED', response,","code: ' + str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): '","print(e) if event and 'RequestType' in event: response = {'failed_reason': e} send(event, context,","'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if status == 401:","+ err) print('INFO: ' + filename + ' was downloaded') return 200 def","__author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import","json import os import tarfile import urllib.error import urllib.parse import urllib.request import boto3","Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR: ' + err)","filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb,","except Exception as e: print(e) if event and 'RequestType' in event: response =","'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key':","= event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] =","def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl)","MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.')"],"string":"[\n \"s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html\",\n \"s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix\",\n \"Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId']\",\n \"urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e: print('send(..) failed executing\",\n \"responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers = {'content-type': 'application/json', }\",\n \"responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {}\",\n \"raise Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR: ' +\",\n \"= {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url\",\n \"raise Exception('ERROR: ' + err) print('INFO: ' + filename + ' was downloaded')\",\n \"req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code:\",\n \"in event: if status == 401: response = {'status': 'invalide_license_key'} else: response =\",\n \"response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers = {'content-type':\",\n \"try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to\",\n \"mmdb = directory + '/' + filename + '.mmdb' s3obj = s3key_prefix +\",\n \"s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded\",\n \"failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status\",\n \"suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data\",\n \"= 'None' if event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename)\",\n \"'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os\",\n \"{'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event:\",\n \"responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream: ' '' +\",\n \"in event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event\",\n \"urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' + suffix)\",\n \"'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try:\",\n \"checksum is different. download is failed') return False with tarfile.open('/tmp/' + filename +\",\n \"= event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n'\",\n \"as err: if err.status == 401: return err.status print(err) raise Exception('ERROR: http error')\",\n \"filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb,\",\n \"= s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0}\",\n \"= {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res\",\n \"+ '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with\",\n \"Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f:\",\n \"# get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key']\",\n \"event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details\",\n \"+ filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' +\",\n \"context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename\",\n \"e: print(e) if event and 'RequestType' in event: response = {'failed_reason': e} send(event,\",\n \"err) print('INFO: ' + filename + ' was downloaded') return 200 def put_to_s3(filename):\",\n \"open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: '\",\n \"url + data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as\",\n \"import os import tarfile import urllib.error import urllib.parse import urllib.request import boto3 #\",\n \"requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None'\",\n \"def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0]\",\n \"with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if\",\n \"in put_files: status = download_file(filename) if status == 401: break put_to_s3(filename) except Exception\",\n \"Inc. or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ =\",\n \"'.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj))\",\n \"event: if status == 401: response = {'status': 'invalide_license_key'} else: response = {'status':\",\n \"'RequestType' in event: if status == 401: response = {'status': 'invalide_license_key'} else: response\",\n \"= json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers = {'content-type': 'application/json', } req =\",\n \"Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__\",\n \"= os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda\",\n \"status = download_file(filename) if status == 401: break put_to_s3(filename) except Exception as e:\",\n \"import urllib.request import boto3 # get var from lambda environment try: s3bucket_name =\",\n \"physicalResourceId) if event and 'RequestType' in event: if status == 401: response =\",\n \"urllib.request import boto3 # get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name']\",\n \"except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/')\",\n \"except Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' +\",\n \"filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data,\",\n \"status == 401: break put_to_s3(filename) except Exception as e: print(e) if event and\",\n \"+ mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event,\",\n \"str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): ' + str(e)) def\",\n \"'.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR:\",\n \"= f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz',\",\n \"json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request(\",\n \"url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in\",\n \"401: return err.status print(err) raise Exception('ERROR: http error') except Exception as err: print(err)\",\n \"return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory =\",\n \"download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix':\",\n \"download_file(filename) if status == 401: break put_to_s3(filename) except Exception as e: print(e) if\",\n \"suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename +\",\n \"response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId']\",\n \"filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum)\",\n \"res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e: print('send(..)\",\n \"context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId']\",\n \"if checksum not in calcurated_checksum: print('ERROR: checksum is different. download is failed') return\",\n \"Exception as e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context):\",\n \"json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except\",\n \"filename + '.' + suffix) except urllib.error.HTTPError as err: if err.status == 401:\",\n \"json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT')\",\n \"' + err) print('INFO: ' + filename + ' was downloaded') return 200\",\n \"f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename\",\n \"tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb' s3obj = s3key_prefix\",\n \"send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if status\",\n \"values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve(\",\n \"urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError\",\n \"<reponame>aws-samples/siem-on-amazon-opensearch-service<filename>source/lambda/geoip_downloader/index.py # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier:\",\n \"checksum not in calcurated_checksum: print('ERROR: checksum is different. download is failed') return False\",\n \"' + filename + ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/'\",\n \"200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum =\",\n \"print('Response body:\\\\n' + json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'],\",\n \"'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req)\",\n \"import json import os import tarfile import urllib.error import urllib.parse import urllib.request import\",\n \"http error') except Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO:\",\n \"'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename\",\n \"s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL']\",\n \"' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>'\",\n \"in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data =\",\n \"response, physicalResourceId) if event and 'RequestType' in event: if status == 401: response\",\n \"mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context,\",\n \"'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City',\",\n \"tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb\",\n \"event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData\",\n \"= noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers\",\n \"affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ =\",\n \"suffix) except urllib.error.HTTPError as err: if err.status == 401: return err.status print(err) raise\",\n \"str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event))\",\n \"print('ERROR: checksum is different. download is failed') return False with tarfile.open('/tmp/' + filename\",\n \"+ context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] =\",\n \"calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different. download\",\n \"( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId']\",\n \"__copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__\",\n \"get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name)\",\n \"os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files =\",\n \"as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' +\",\n \"{'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url +\",\n \"urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' +\",\n \"with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/')\",\n \"Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3')\",\n \"f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different.\",\n \"+ suffix) except urllib.error.HTTPError as err: if err.status == 401: return err.status print(err)\",\n \"'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' +\",\n \"Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service'\",\n \"' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if\",\n \"or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] =\",\n \"= '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib\",\n \"== 401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context,\",\n \"= boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country']\",\n \"+ '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory +\",\n \"if status == 401: break put_to_s3(filename) except Exception as e: print(e) if event\",\n \"environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url =\",\n \"urllib.error import urllib.parse import urllib.request import boto3 # get var from lambda environment\",\n \"send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body\",\n \"response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType'\",\n \"= directory + '/' + filename + '.mmdb' s3obj = s3key_prefix + filename\",\n \"as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename\",\n \"for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix}\",\n \"directory + '/' + filename + '.mmdb' s3obj = s3key_prefix + filename +\",\n \"'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename in put_files: status\",\n \"= event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body =\",\n \"False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name\",\n \"import tarfile import urllib.error import urllib.parse import urllib.request import boto3 # get var\",\n \"= ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values =\",\n \"= 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import\",\n \"license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix\",\n \"if event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if status\",\n \"headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try:\",\n \"as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is\",\n \"bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def\",\n \"put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO:\",\n \"f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb')\",\n \"' + str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): ' +\",\n \"+ '/' + filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb'\",\n \"# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0\",\n \"data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.'\",\n \"boto3 # get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key =\",\n \"for filename in put_files: status = download_file(filename) if status == 401: break put_to_s3(filename)\",\n \"Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. '\",\n \"is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf:\",\n \"print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb'\",\n \"hashlib import json import os import tarfile import urllib.error import urllib.parse import urllib.request\",\n \"print(err) raise Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR: '\",\n \"print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename + ' was\",\n \"== 401: break put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType'\",\n \"'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename,\",\n \"= responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream: ' ''\",\n \"context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho\",\n \"response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body\",\n \"'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import urllib.error import urllib.parse\",\n \"filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as err: if err.status\",\n \"tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename +\",\n \"as e: print(e) if event and 'RequestType' in event: response = {'failed_reason': e}\",\n \"Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates.\",\n \"s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN',\",\n \"as e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId\",\n \"+ str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): ' + str(e))\",\n \"= urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e: print('send(..) failed\",\n \"# SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All\",\n \"failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as tf: directory\",\n \"lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR:\",\n \"{'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res =\",\n \"print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as\",\n \"checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/' + filename +\",\n \"or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0'\",\n \"import urllib.error import urllib.parse import urllib.request import boto3 # get var from lambda\",\n \"to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket =\",\n \"401: break put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType' in\",\n \"response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data']\",\n \"SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights\",\n \"+ data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as err:\",\n \"if status == 401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'}\",\n \"{} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream:\",\n \"'2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import\",\n \"' + checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum\",\n \"https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] =\",\n \"__version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import\",\n \"from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise\",\n \"def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try:\",\n \"with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum:\",\n \"== 401: return err.status print(err) raise Exception('ERROR: http error') except Exception as err:\",\n \"noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus\",\n \"Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright\",\n \"boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def\",\n \"event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body)\",\n \"context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body =\",\n \"except Exception as e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event,\",\n \"= urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' +\",\n \"print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in\",\n \"err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename + '\",\n \"{'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS', response, physicalResourceId) return(json.dumps(response))\",\n \"= {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS', response, physicalResourceId)\",\n \"401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS',\",\n \"if err.status == 401: return err.status print(err) raise Exception('ERROR: http error') except Exception\",\n \"'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__\",\n \"except urllib.error.HTTPError as err: if err.status == 401: return err.status print(err) raise Exception('ERROR:\",\n \"print('INFO: ' + filename + ' was downloaded') return 200 def put_to_s3(filename): with\",\n \"+ json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers,\",\n \"{0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False):\",\n \"= '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile\",\n \"event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and\",\n \"+ filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not\",\n \"+ '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum:\",\n \"physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] =\",\n \"CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name)\",\n \"try: for filename in put_files: status = download_file(filename) if status == 401: break\",\n \"+ '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name,\",\n \"response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event, context, 'SUCCESS', response,\",\n \"filename + ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename\",\n \"+ filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' +\",\n \"bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename):\",\n \"return err.status print(err) raise Exception('ERROR: http error') except Exception as err: print(err) raise\",\n \"not in calcurated_checksum: print('ERROR: checksum is different. download is failed') return False with\",\n \"if event and 'RequestType' in event: if status == 401: response = {'status':\",\n \"data, filename='/tmp/' + filename + '.' + suffix) except urllib.error.HTTPError as err: if\",\n \"= download_file(filename) if status == 401: break put_to_s3(filename) except Exception as e: print(e)\",\n \"'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']:\",\n \"print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData,\",\n \"os import tarfile import urllib.error import urllib.parse import urllib.request import boto3 # get\",\n \"to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): #\",\n \"response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch Log Stream: '\",\n \"executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status =\",\n \"'' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId']\",\n \"= responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers = {'content-type': 'application/json',\",\n \"print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if status == 401:\",\n \"print('Status code: ' + str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..):\",\n \"__license__ = 'MIT-0' __author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json\",\n \"Exception('ERROR: ' + err) print('INFO: ' + filename + ' was downloaded') return\",\n \"Exception as e: print(e) if event and 'RequestType' in event: response = {'failed_reason':\",\n \"urllib.error.HTTPError as err: if err.status == 401: return err.status print(err) raise Exception('ERROR: http\",\n \"= ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__ =\",\n \"# https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason']\",\n \"'<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import\",\n \"impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket\",\n \"directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb'\",\n \"os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment')\",\n \"def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key,\",\n \"= 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz',\",\n \"filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in\",\n \"'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/'\",\n \"or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com,\",\n \"'.' + suffix) except urllib.error.HTTPError as err: if err.status == 401: return err.status\",\n \"its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__\",\n \"put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values\",\n \"+ filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb =\",\n \"event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status))\",\n \"= 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import urllib.error import\",\n \"+ filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format(\",\n \"+ str(e)) def lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event:\",\n \"uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None,\",\n \"put_files: status = download_file(filename) if status == 401: break put_to_s3(filename) except Exception as\",\n \"= os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix =\",\n \"} req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status\",\n \"= {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch Log\",\n \"if event and 'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED',\",\n \"is different. download is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz',\",\n \"urllib.parse import urllib.request import boto3 # get var from lambda environment try: s3bucket_name\",\n \"affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or\",\n \"different. download is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz')\",\n \"KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3\",\n \"= hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different. download is\",\n \"['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key': license_key, 'suffix': suffix} data = urllib.parse.urlencode(values)\",\n \"import hashlib import json import os import tarfile import urllib.error import urllib.parse import\",\n \"response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n' + json_response_body)\",\n \"['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id':\",\n \"s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get\",\n \"physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename in\",\n \"json_response_body = json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers = {'content-type': 'application/json', } req\",\n \"'None' if event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if\",\n \"Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1' __license__\",\n \"+ filename + ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' +\",\n \"e: print('send(..) failed executing requests.put(..): ' + str(e)) def lambda_handler(event, context): physicalResourceId =\",\n \"method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as\",\n \"in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or\",\n \"err: if err.status == 401: return err.status print(err) raise Exception('ERROR: http error') except\",\n \"All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its\",\n \"Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] =\",\n \"get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except\",\n \"status = 'None' if event: print(json.dumps(event)) try: for filename in put_files: status =\",\n \"Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename\",\n \"raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 =\",\n \"'.tar.gz.sha256') as f: checksum = f.read().split()[0] print('INFO: Checksum: ' + checksum) with open('/tmp/'\",\n \"import boto3 # get var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key\",\n \"download is failed') return False with tarfile.open('/tmp/' + filename + '.tar.gz', 'r:gz') as\",\n \"err.status print(err) raise Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR:\",\n \"= ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] =\",\n \"lambda_handler(event, context): physicalResourceId = 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for\",\n \"license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url + data, filename='/tmp/' +\",\n \"responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See\",\n \"mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl\",\n \"+ filename + '.' + suffix) except urllib.error.HTTPError as err: if err.status ==\",\n \"import urllib.parse import urllib.request import boto3 # get var from lambda environment try:\",\n \"= os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files\",\n \"tarfile import urllib.error import urllib.parse import urllib.request import boto3 # get var from\",\n \"in calcurated_checksum: print('ERROR: checksum is different. download is failed') return False with tarfile.open('/tmp/'\",\n \"e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if\",\n \"its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ = ('Copyright Amazon.com, Inc.\",\n \"= tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb' s3obj\",\n \"and 'RequestType' in event: if status == 401: response = {'status': 'invalide_license_key'} else:\",\n \"'/' + filename + '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/'\",\n \"break put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType' in event:\",\n \"'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum\",\n \"noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n' + json_response_body) headers =\",\n \"filename + '.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory\",\n \"s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to\",\n \"tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/' + filename + '.mmdb' s3obj =\",\n \"open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum\",\n \"s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?'\",\n \"'.tar.gz', 'r:gz') as tf: directory = tf.getmembers()[0].name tf.extractall(path='/tmp/') mmdb = directory + '/'\",\n \"' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256')\",\n \"= event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the\",\n \"Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 __copyright__ =\",\n \"and 'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId)\",\n \"('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.') __version__ = '2.7.1'\",\n \"os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible to get lambda environment') s3key_prefix = os.environ.get('s3key_prefix',\",\n \"hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum is different. download is failed')\",\n \"= {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in\",\n \"s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus,\",\n \"put_to_s3(filename) except Exception as e: print(e) if event and 'RequestType' in event: response\",\n \"the details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = (\",\n \"'.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO:\",\n \"+ '.' + suffix) except urllib.error.HTTPError as err: if err.status == 401: return\",\n \"filename in put_files: status = download_file(filename) if status == 401: break put_to_s3(filename) except\",\n \"Rights Reserved.') __version__ = '2.7.1' __license__ = 'MIT-0' __author__ = '<NAME>' __url__ =\",\n \"environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError: raise Exception('ERROR: impossible\",\n \"' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId']\",\n \"checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum = hashlib.sha256(f.read()).hexdigest()\",\n \"status == 401: response = {'status': 'invalide_license_key'} else: response = {'status': 'downloaded'} send(event,\",\n \"+ checksum) with open('/tmp/' + filename + '.tar.gz', 'rb') as f: calcurated_checksum =\",\n \"responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl) response_body = {} response_body['Status']\",\n \"physicalResourceId or context.log_stream_name) response_body['StackId'] = event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho']\",\n \"downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f:\",\n \"response_body = {} response_body['Status'] = responseStatus response_body['Reason'] = ('See the details in CloudWatch\",\n \"= ('See the details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId']\",\n \"= s3.Bucket(s3bucket_name) url = 'https://download.maxmind.com/app/geoip_download?' put_files = ['GeoLite2-City', 'GeoLite2-ASN', 'GeoLite2-Country'] def download_file(filename): for\",\n \"('See the details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] =\",\n \"+ '.mmdb' s3obj = s3key_prefix + filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj)\",\n \"was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as\",\n \"+ ' was downloaded') return 200 def put_to_s3(filename): with open('/tmp/' + filename +\",\n \"lambda environment') s3key_prefix = os.environ.get('s3key_prefix', 'GeoLite2/') s3 = boto3.resource('s3') bucket = s3.Bucket(s3bucket_name) url\",\n \"return 200 def put_to_s3(filename): with open('/tmp/' + filename + '.tar.gz.sha256') as f: checksum\",\n \"s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl =\",\n \"headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception\",\n \"try: res = urllib.request.urlopen(req) print('Status code: ' + str(res.status)) except Exception as e:\",\n \"as err: print(err) raise Exception('ERROR: ' + err) print('INFO: ' + filename +\",\n \"calcurated_checksum: print('ERROR: checksum is different. download is failed') return False with tarfile.open('/tmp/' +\",\n \"= urllib.request.Request( event['ResponseURL'], json_response_body.encode(), headers=headers, method='PUT') try: res = urllib.request.urlopen(req) print('Status code: '\",\n \"event and 'RequestType' in event: if status == 401: response = {'status': 'invalide_license_key'}\",\n \"body:\\\\n' + json_response_body) headers = {'content-type': 'application/json', } req = urllib.request.Request( event['ResponseURL'], json_response_body.encode(),\",\n \"err.status == 401: return err.status print(err) raise Exception('ERROR: http error') except Exception as\",\n \"error') except Exception as err: print(err) raise Exception('ERROR: ' + err) print('INFO: '\",\n \"response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response\",\n \"event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] = responseData json_response_body = json.dumps(response_body) print('Response body:\\\\n' +\",\n \"context, 'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if status ==\",\n \"try: urllib.request.urlretrieve( url + data, filename='/tmp/' + filename + '.' + suffix) except\",\n \"event: print(json.dumps(event)) try: for filename in put_files: status = download_file(filename) if status ==\",\n \"__url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import tarfile import urllib.error\",\n \"details in CloudWatch Log Stream: ' '' + context.log_stream_name) response_body['PhysicalResourceId'] = ( physicalResourceId\",\n \"= 'geoipdb' status = 'None' if event: print(json.dumps(event)) try: for filename in put_files:\",\n \"'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED', response, physicalResourceId) if\",\n \"response_body['Reason'] = ('See the details in CloudWatch Log Stream: ' '' + context.log_stream_name)\",\n \"var from lambda environment try: s3bucket_name = os.environ['s3bucket_name'] license_key = os.environ['license_key'] except KeyError:\",\n \"event and 'RequestType' in event: response = {'failed_reason': e} send(event, context, 'FAILED', response,\",\n \"code: ' + str(res.status)) except Exception as e: print('send(..) failed executing requests.put(..): '\",\n \"print(e) if event and 'RequestType' in event: response = {'failed_reason': e} send(event, context,\",\n \"'FAILED', response, physicalResourceId) if event and 'RequestType' in event: if status == 401:\",\n \"+ err) print('INFO: ' + filename + ' was downloaded') return 200 def\",\n \"__author__ = '<NAME>' __url__ = 'https://github.com/aws-samples/siem-on-amazon-opensearch-service' import hashlib import json import os import\",\n \"json import os import tarfile import urllib.error import urllib.parse import urllib.request import boto3\",\n \"Exception('ERROR: http error') except Exception as err: print(err) raise Exception('ERROR: ' + err)\",\n \"filename + '.mmdb' bucket.upload_file('/tmp/' + mmdb, s3obj) print('INFO: uploaded {0} to s3://{1}/{2}'.format( mmdb,\",\n \"except Exception as e: print(e) if event and 'RequestType' in event: response =\",\n \"'GeoLite2-Country'] def download_file(filename): for suffix in ['tar.gz', 'tar.gz.sha256']: values = {'edition_id': filename, 'license_key':\",\n \"= event['StackId'] response_body['RequestId'] = event['RequestId'] response_body['LogicalResourceId'] = event['LogicalResourceId'] response_body['NoEcho'] = noEcho response_body['Data'] =\",\n \"def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html responseUrl = event['ResponseURL'] print(responseUrl)\",\n \"MIT-0 __copyright__ = ('Copyright Amazon.com, Inc. or its affiliates. ' 'All Rights Reserved.')\"\n]","isConversational":false}}},{"rowIdx":76,"cells":{"ngram":{"kind":"list like","value":["in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in","Unless required by applicable law or agreed to in writing, software # distributed","Save the position offset # Calculate a new start time relativeSlaveTime = slaveTime[i]","export laws and regulations. # The user has the responsibility to obtain export","= ('Location at which to compute baselines - \"all\" implies '+ 'top, middle,","return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self):","def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def","cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) )","= [] return None def createPorts(self): # Set input ports # It looks","port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb = []","the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the","None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None","range and azimuth pixel sizes # the two starting ranges, a planet, and","port() lookVector = self.calculateLookVector() az_offset = [] vb = [] hb = []","range and azimuth pixel sizes, starting ranges, # satellite heights and times for","Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector #","c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two frames","[(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the difference between the","master image, '+ '\"middle\" implies near middle of master image. '+ 'To be","near middle of master image. '+ 'To be used in case there is","# Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed","asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize)","midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius =","vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \"velocity\" component","z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius","+= MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize","orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn","vector v = MM.normalizeVector(v) # Turn the velocity vector into a unit vector","if not (size == 3): print(\"Error. Expecting input vectors of length 3.\") raise","sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity","self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height","retstr += \"Bulk Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range","def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def","\"velocity\" component that is perpendicular to the cross-track direction and position basis =","IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or","self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2","time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb","Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \"Initial Baseline estimates \\n\"","MM.norm(v) return normV # Given an orbit and a time, calculate an orthogonal","the gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg =","the responsibility to obtain export licenses, or other export # authority as may","class to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self):","middle of master image. '+ 'To be used in case there is a","= MM.crossProduct(c,r) # Calculate a the \"velocity\" component that is perpendicular to the","# # United States Government Sponsorship acknowledged. This software is subject to #","self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ',","Government Sponsorship acknowledged. This software is subject to # U.S. export control laws","default = 'all', type=str, mandatory=False, doc = ('Location at which to compute baselines","'all', type=str, mandatory=False, doc = ('Location at which to compute baselines - \"all\"","length.\") raise Exception if not (size == 3): print(\"Error. Expecting input vectors of","= [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using","self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of","need two orbits, a time, range and azimuth pixel sizes # the two","s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 =","software # distributed under the License is distributed on an \"AS IS\" BASIS,","masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom':","and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating","self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master",") # print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1)","orbits # These provide the range and azimuth pixel sizes, starting ranges, #","and a basis, calculate the offset between the two positions in this basis","Baseline at the start of the scene, mid-scene, and the end of the","+ self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range:","= self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline point if","a prohibited end use). By downloading this software, # the user agrees to","at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() +","the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law","M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size):","attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0]","= csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2","= (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 -","self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom","self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle","= {} self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self): #","self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables","implies near start of master image, '+ '\"bottom\" implies at bottom of master","Calculate the gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg","'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at which to compute","this is the c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r)","and # limitations under the License. # # United States Government Sponsorship acknowledged.","the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length","r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the","masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master","at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0),","the License. # # United States Government Sponsorship acknowledged. This software is subject","or in support of a prohibited end use). By downloading this software, #","%s\\n\" retlst += (self.pBaselineTop,) retstr += \"Bulk Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,)","crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2]","which to compute baselines - \"all\" implies '+ 'top, middle, bottom of master","None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius = None","# Calculate the look vector of the master frame def calculateLookVector(self): try: z","import datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule","[cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite')","image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() ==","= frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject()","vb = [] hb = [] csb = [] asb = [] s","Required except when exporting to an embargoed country, # end user, or in","midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit","master image, '+ '\"top\" implies near start of master image, '+ '\"bottom\" implies","= self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize =","time and a method that calls this method #TODO multiple times to calculate","10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 =","the Look Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return","# U.S. export control laws and regulations and has been classified as 'EAR99","'\"middle\" implies near middle of master image. '+ 'To be used in case","2010 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the","perpendicular to the platform position and velocity, this is the c, or cross-track","try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur","def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3","the baseline between #TODO frames when given a master time and a slave","# Calculate the Baseline at the start of the scene, mid-scene, and the","cross-track and velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv","self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset","export # authority as may be required before exporting this software to any","return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return","frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self):","and velocity at the start of the scene self.logger.info(\"Sampling time %s\" % i)","[Export] License Required except when exporting to an embargoed country, # end user,","print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL:","= MM.normalizeVector(v) # Turn the velocity vector into a unit vector c =","not use this file except in compliance with the License. # You may","self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables","California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache","= 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at which to","for j in range(len(x1))] # Calculate the difference between the master and slave","self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1","distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY","Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,)","Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset: %s\\n\" retlst +=","MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize =","Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the","under the License. # # United States Government Sponsorship acknowledged. This software is","self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def","= self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition()","to obtain export licenses, or other export # authority as may be required","for i in range(size) ] for j in range(size)] for j in range(size):","unit vector v = MM.normalizeVector(v) # Turn the velocity vector into a unit","0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV =","agreed to in writing, software # distributed under the License is distributed on","normV = MM.norm(v) return normV # Given an orbit and a time, calculate","regulations. # The user has the responsibility to obtain export licenses, or other","self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle","is perpendicular to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v)","h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg =","\"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr += \"Bulk Azimuth Offset: %s\\n\" retlst","', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar","start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate","polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\"Error. Expecting input vectors","setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v","getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self):","self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit","= csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset =","a slave time and a method that calls this method #TODO multiple times","verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1]","raise Exception Y = [0]*size A = [0]*size M = [[0 for i","'+ '\"middle\" implies near middle of master image. '+ 'To be used in","frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def","Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3 = [] #","x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset #","z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height +","[self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at the start of","# Calculate a the \"velocity\" component that is perpendicular to the cross-track direction","ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2","j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j]","to in writing, software # distributed under the License is distributed on an","First, get the position and velocity at the start of the scene self.logger.info(\"Sampling","implied. # See the License for the specific language governing permissions and #","of the scene # First, get the position and velocity at the start","datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image') masterTime","= self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the baseline polynomial","frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR","self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \"Initial Baseline estimates \\n\" retstr","setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name =","getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self):","Calculate the Baseline at the start of the scene, mid-scene, and the end","calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r =","time %s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the","scene, mid-scene, and the end of the scene # First, get the position","(self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr += \"Perpendicular Baseline:","class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return","Calculate the look vector of the master frame def calculateLookVector(self): try: z =","frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None","Apache License, Version 2.0 (the \"License\"); # you may not use this file","countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from","master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look","family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look","class Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3 = []","az_offset.append(z_offset) # Save the position offset # Calculate a new start time relativeSlaveTime","image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() ==","offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset =","specific language governing permissions and # limitations under the License. # # United","self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst","return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return","+= \"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\" retlst","* 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1","component that is perpendicular to the cross-track direction and position basis = BaselineBasis()","# See the License for the specific language governing permissions and # limitations","the License is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR","masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline","classified as 'EAR99 NLR' # (No [Export] License Required except when exporting to","Set input ports # It looks like we really need two orbits, a","scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV","into a method that calculates the baseline between #TODO frames when given a","the Apache License, Version 2.0 (the \"License\"); # you may not use this","export licenses, or other export # authority as may be required before exporting","self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius","you may not use this file except in compliance with the License. #","type=str, mandatory=False, doc = ('Location at which to compute baselines - \"all\" implies","deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i],","def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame","= None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop =","MM from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis vectors","print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the","location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime","= ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height","+ vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by the look","= crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop =","self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom","deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2","getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION","basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors","'bottom': print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0),","# Licensed under the Apache License, Version 2.0 (the \"License\"); # you may","Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under","#TODO This could be further refactored into a method that calculates the baseline","def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate","Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef)","crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0]","the last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0])","self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(),","{} self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self): # Set","def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def","except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/(","of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif","datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3):","baseline change over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset","and azimuth pixel sizes, starting ranges, # satellite heights and times for the","= frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try:","perpendicular to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c)","(self.pBaselineTop,) retstr += \"Bulk Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk","Calculate the difference between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector())","def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days *","MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position and velocity, this","Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at","def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def","#Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate","of master image, '+ '\"middle\" implies near middle of master image. '+ 'To","3.\") raise Exception Y = [0]*size A = [0]*size M = [[0 for","vectors and a basis, calculate the offset between the two positions in this","return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius return","', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ',","= (self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr += \"Perpendicular","+= \"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr += \"Bulk Azimuth Offset: %s\\n\"","master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower()","laws and regulations. # The user has the responsibility to obtain export licenses,","pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius","a basis, calculate the offset between the two positions in this basis def","baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] =","None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None","datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of","self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl)","# Set input ports # It looks like we really need two orbits,","isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class to","math import datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import","# satellite heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort","azimuth pixel sizes, starting ranges, # satellite heights and times for the first","used in case there is a large shift between images.') ) class Baseline(Component):","class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate","The user has the responsibility to obtain export licenses, or other export #","self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame def","'\"top\" implies near start of master image, '+ '\"bottom\" implies at bottom of","'+ '\"top\" implies near start of master image, '+ '\"bottom\" implies at bottom","MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two","# the two starting ranges, a planet, and the two prfs # These","'top, middle, bottom of master image, '+ '\"top\" implies near start of master","{} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = []","provide the orbits # These provide the range and azimuth pixel sizes, starting","retstr = \"Initial Baseline estimates \\n\" retstr += \"Cross-track Baseline: %s\\n\" retlst =","the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j])","'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the master frame","the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)):","= self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last","time, range and azimuth pixel sizes # the two starting ranges, a planet,","print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl =","normV # Given an orbit and a time, calculate an orthogonal basis for","= [] self.x2 = [] self.x3 = [] # A class to hold","vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] #","= None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom =","the platform position and velocity, this is the c, or cross-track vector c","# Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables =","the scene, mid-scene, and the end of the scene # First, get the","on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,","user, or in support of a prohibited end use). By downloading this software,","self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''):","the length of the projection of the difference in position and the \"velocity\"","getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td):","and azimuth pixel sizes # the two starting ranges, a planet, and the","self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit","# print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl)","Given an orbit and a time, calculate an orthogonal basis for cross-track and","A = [0]*size M = [[0 for i in range(size) ] for j","logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the","basis for cross-track and velocity directions # based on the spacecraft position def","position and velocity at the start of the scene self.logger.info(\"Sampling time %s\" %","and velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv =","except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame","in position and the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return","creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid =","See the License for the specific language governing permissions and # limitations under","self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV","hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 =","- datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition()","basis # Given two position vectors and a basis, calculate the offset between","the start of the scene self.logger.info(\"Sampling time %s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i])","# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in","len(yRef)): print(\"Error. Expecting input vectors of same length.\") raise Exception if not (size","to compute baselines - \"all\" implies '+ 'top, middle, bottom of master image,","basis.setCrossTrackVector(c) return basis # Given two position vectors and a basis, calculate the","the two prfs # These provide the orbits # These provide the range","# Given two position vectors and a basis, calculate the offset between the","self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset","print(\"Error. Expecting input vectors of same length.\") raise Exception if not (size ==","createPorts(self): # Set input ports # It looks like we really need two","the position vector into a unit vector v = MM.normalizeVector(v) # Turn the","slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \"Initial Baseline","= crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate =","i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for","raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() +","+ self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ',","method that calculates the baseline between #TODO frames when given a master time","calculate the offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx","the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis","between two frames def baseline(self): #TODO This could be further refactored into a","based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 =","getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0","basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and a basis,","Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License,","between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] -","between #TODO frames when given a master time and a slave time and","- asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc","this method #TODO multiple times to calculate the rate of baseline change over","sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into a unit vector","# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0","return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False,","isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis vectors class Basis(object):","def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def","%s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset: %s\\n\" retlst += (self.orbSlcRangeOffset,)","user has the responsibility to obtain export licenses, or other export # authority","masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr","csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 #","2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius) #","A class to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def","the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate","BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1","vector of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z","sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1)","this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))]","= (BASELINE_LOCATION,) # Calculate the Look Angle of the master frame def calculateLookAngle(self):","#TODO multiple times to calculate the rate of baseline change over time. for","= None self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1 =","end use). By downloading this software, # the user agrees to comply with","regulations and has been classified as 'EAR99 NLR' # (No [Export] License Required","self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3","= self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset)","# Calculate the length of the projection of the difference in position and","{0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime =","range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv =","[self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation))","required before exporting this software to any 'EAR99' # embargoed foreign country or","= self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self,","return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return","and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two","self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger","an orthogonal basis for cross-track and velocity directions # based on the spacecraft","getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self):","KIND, either express or implied. # See the License for the specific language","for j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] =","j in range(len(x1))] # Calculate the difference between the master and slave position","self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) +","# the user agrees to comply with all applicable U.S. export laws and","self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame =","self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating baselines') masterTime =","ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height =","asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc =","citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime","self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def","+ self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius: ',","as 'EAR99 NLR' # (No [Export] License Required except when exporting to an","ANY KIND, either express or implied. # See the License for the specific","'+ '\"bottom\" implies at bottom of master image, '+ '\"middle\" implies near middle","%s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance","start of the scene self.logger.info(\"Sampling time %s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV","position vectors and a basis, calculate the offset between the two positions in","any 'EAR99' # embargoed foreign country or citizen of those countries. # #","#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. # #","WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See","= range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop","az_offset = [] vb = [] hb = [] csb = [] asb","with all applicable U.S. export laws and regulations. # The user has the","fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef)","start of master image, '+ '\"bottom\" implies at bottom of master image, '+","= [] hb = [] csb = [] asb = [] s =","mid-scene, and the end of the scene # First, get the position and","cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis #","return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return","Calculate the distance moved since the last baseline point if (i > 0):","at the start of the scene self.logger.info(\"Sampling time %s\" % i) masterBasis =","offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) #","is the c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) #","[] self.optionalVariables = [] return None def createPorts(self): # Set input ports #","= [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating","== 'all': print('Using entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()]","method that calls this method #TODO multiple times to calculate the rate of","range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize","public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at which","permissions and # limitations under the License. # # United States Government Sponsorship","the scene self.logger.info(\"Sampling time %s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i])","image, '+ '\"bottom\" implies at bottom of master image, '+ '\"middle\" implies near","# Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size =","be used in case there is a large shift between images.') ) class","subject to # U.S. export control laws and regulations and has been classified","# Calculate the vector perpendicular to the platform position and velocity, this is","platform position and velocity, this is the c, or cross-track vector c =","None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline')","radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range","getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds","spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV =","', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl]","self.x1 = [] self.x2 = [] self.x3 = [] # A class to","under the License is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES","self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize","to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) ==","\"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express","masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 =","for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return","= c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default","size = len(xRef) if not (len(xRef) == len(yRef)): print(\"Error. Expecting input vectors of","the position and velocity at the start of the scene self.logger.info(\"Sampling time %s\"","large shift between images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline'","the start of the scene, mid-scene, and the end of the scene #","applicable law or agreed to in writing, software # distributed under the License","= Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location","change over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset =","components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients =","getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str,","\"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the","\"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\" retlst +=","CONDITIONS OF ANY KIND, either express or implied. # See the License for","= frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize","of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version","retlst += (self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr +=","writing, software # distributed under the License is distributed on an \"AS IS\"","ports # It looks like we really need two orbits, a time, range","verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset","for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x","= self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets","= orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV # Given","frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid","- datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() -","# It looks like we really need two orbits, a time, range and","= frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV =","the baseline components between two frames def baseline(self): #TODO This could be further","compliance with the License. # You may obtain a copy of the License","entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() ==","of same length.\") raise Exception if not (size == 3): print(\"Error. Expecting input","def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def","= MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the difference in","self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg","= masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position","# Calculate the baseline components between two frames def baseline(self): #TODO This could","Baseline estimates \\n\" retstr += \"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr +=","logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {}","None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None","we really need two orbits, a time, range and azimuth pixel sizes #","v = sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit and","= az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a","frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame","heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame)","class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop =","= slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate","= len(xRef) if not (len(xRef) == len(yRef)): print(\"Error. Expecting input vectors of same","basis, calculate the offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis):","('Location at which to compute baselines - \"all\" implies '+ 'top, middle, bottom","= math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for","for cross-track and velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time):","dx = [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the difference","self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc","= [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating","(td.microseconds + (td.seconds + td.days * 24.0 * 3600) * 10**6) / 10**6","def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def","self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop","Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j in","(the \"License\"); # you may not use this file except in compliance with","[self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i","self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self):","of a prohibited end use). By downloading this software, # the user agrees","distance moved since the last baseline point if (i > 0): deltaT =","return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return","# Unless required by applicable law or agreed to in writing, software #","other export # authority as may be required before exporting this software to","by applicable law or agreed to in writing, software # distributed under the","self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf","as may be required before exporting this software to any 'EAR99' # embargoed","self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) #","when given a master time and a slave time and a method that","starting ranges, a planet, and the two prfs # These provide the orbits","+= (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset: %s\\n\" retlst += (self.orbSlcRangeOffset,) return retstr","position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity()","file except in compliance with the License. # You may obtain a copy","# print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate","print(\"Error. Expecting input vectors of length 3.\") raise Exception Y = [0]*size A","These provide the range and azimuth pixel sizes, starting ranges, # satellite heights","the position offset # Calculate a new start time relativeSlaveTime = slaveTime[i] -","by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb)","az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset =","self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop","in support of a prohibited end use). By downloading this software, # the","offset # Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV","self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \"Initial Baseline estimates \\n\" retstr +=","def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return","and has been classified as 'EAR99 NLR' # (No [Export] License Required except","def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\"Error. Expecting input","input ports # It looks like we really need two orbits, a time,","self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a new start time","MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the difference in position","or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import","basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3","self.x3 = [] # A class to hold three-dimensional basis vectors for spacecraft","software is subject to # U.S. export control laws and regulations and has","elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image') masterTime =","(-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class","try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height","= verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset =","= self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame","licenses, or other export # authority as may be required before exporting this","None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None","Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2","a time, range and azimuth pixel sizes # the two starting ranges, a","x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply","# slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at","OR CONDITIONS OF ANY KIND, either express or implied. # See the License","may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #","asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span","of the projection of the difference in position and the \"velocity\" component v_offset","self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize","- datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at","math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame def calculateLookVector(self): try:","= range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self):","MM.normalizeVector(x1) # Turn the position vector into a unit vector v = MM.normalizeVector(v)","a planet, and the two prfs # These provide the orbits # These","retlst = (self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr +=","self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit","look vector of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except:","planet, and the two prfs # These provide the orbits # These provide","# # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component","the scene # First, get the position and velocity at the start of","def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def","ranges, a planet, and the two prfs # These provide the orbits #","vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position","span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle':","- \"all\" implies '+ 'top, middle, bottom of master image, '+ '\"top\" implies","= radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 =","def createPorts(self): # Set input ports # It looks like we really need","self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate","two frames def baseline(self): #TODO This could be further refactored into a method","cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv =","Calculate the Look Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector()","self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc","to an embargoed country, # end user, or in support of a prohibited","/ 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange()","(td.seconds + td.days * 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self):","return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return","__str__(self): retstr = \"Initial Baseline estimates \\n\" retstr += \"Cross-track Baseline: %s\\n\" retlst","math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j","vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by the look angle","azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg","getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def","position offset # Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV))","new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') #","def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all',","self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a()","x1[j]) for j in range(len(x1))] # Calculate the difference between the master and","= float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 =","when exporting to an embargoed country, # end user, or in support of","# (No [Export] License Required except when exporting to an embargoed country, #","self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset)","= pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius =","range(3): # Calculate the Baseline at the start of the scene, mid-scene, and","two prfs # These provide the orbits # These provide the range and","to comply with all applicable U.S. export laws and regulations. # The user","= [[0 for i in range(size) ] for j in range(size)] for j","self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset","vector into a unit vector v = MM.normalizeVector(v) # Turn the velocity vector","== len(yRef)): print(\"Error. Expecting input vectors of same length.\") raise Exception if not","frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(),","td.days * 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame =","range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return","self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION',","+= \"Bulk Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset:","= [0]*size M = [[0 for i in range(size) ] for j in","self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables","self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the","z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius:","= 'all', type=str, mandatory=False, doc = ('Location at which to compute baselines -","masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i],","master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise","range(len(x1))] # Calculate the difference between the master and slave position vectors z_offset","def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2",") class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) #","Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = []","x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return","range(size)] for j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j]","slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a","the Baseline at the start of the scene, mid-scene, and the end of","the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0","to the platform position and velocity, this is the c, or cross-track vector","- self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate =","self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master","time and a slave time and a method that calls this method #TODO","provide the range and azimuth pixel sizes, starting ranges, # satellite heights and","Licensed under the Apache License, Version 2.0 (the \"License\"); # you may not","this software to any 'EAR99' # embargoed foreign country or citizen of those","start of the scene, mid-scene, and the end of the scene # First,","z_offset,v_offset,c_offset # Calculate the baseline components between two frames def baseline(self): #TODO This","elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image') masterTime =","slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()]","for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb =","image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown","+ z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) #","into a unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to","+ az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset","is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF","MM.invertMatrix(M) for i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return","self.optionalVariables = [] return None def createPorts(self): # Set input ports # It","middle, bottom of master image, '+ '\"top\" implies near start of master image,","baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the","relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets","setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate","+ deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition()","3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame","masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the","r = MM.normalizeVector(x1) # Turn the position vector into a unit vector v","of the difference in position and the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset","= [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating","- x1[j]) for j in range(len(x1))] # Calculate the difference between the master","self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset","#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import Component, Port from","return normV # Given an orbit and a time, calculate an orthogonal basis","return None def createPorts(self): # Set input ports # It looks like we","def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def","self.height = float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1","foreign country or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import","of the scene self.logger.info(\"Sampling time %s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV =","the License for the specific language governing permissions and # limitations under the","self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline point if (i","(i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV","to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2","vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the","frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight","', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1","- cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv","image. '+ 'To be used in case there is a large shift between","None self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None","a time, calculate an orthogonal basis for cross-track and velocity directions # based","= frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height =","Calculate the baseline components between two frames def baseline(self): #TODO This could be","= None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() #","\"Initial Baseline estimates \\n\" retstr += \"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr","= [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the difference between","= midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius","getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self):","None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None","a method that calculates the baseline between #TODO frames when given a master","baseline between #TODO frames when given a master time and a slave time","# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #","[] self.x3 = [] # A class to hold three-dimensional basis vectors for","verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset","%s\\n\" retlst = (self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr","and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the","[] self.x2 = [] self.x3 = [] # A class to hold three-dimensional","0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height)","a master time and a slave time and a method that calls this","# Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV =","and regulations. # The user has the responsibility to obtain export licenses, or","range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in","= yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j in range(size):","RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0 (the \"License\");","baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid()","def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius","License Required except when exporting to an embargoed country, # end user, or","def __str__(self): retstr = \"Initial Baseline estimates \\n\" retstr += \"Cross-track Baseline: %s\\n\"","in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return","image, '+ '\"middle\" implies near middle of master image. '+ 'To be used","self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset","= None self.height = None self.radius = None self.startingRange1 = None self.startingRange2 =","csb = [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all':","+ datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom","= self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z)","slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at the","self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV","be further refactored into a method that calculates the baseline between #TODO frames","bottom of master image, '+ '\"middle\" implies near middle of master image. '+","= sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into a unit","two position vectors and a basis, calculate the offset between the two positions","Version 2.0 (the \"License\"); # you may not use this file except in","iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import","# Calculate the Look Angle of the master frame def calculateLookAngle(self): lookVector =","if self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating baselines') masterTime","= MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two frames def","addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit()","time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the","the offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx =","Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {}","def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def","for j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize =","= verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom =","master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl","csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1","i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A def","(self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate","self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate","positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j","velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v)","scene self.logger.info(\"Sampling time %s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) #","print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return","print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop()","Look Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0]))","'+ 'To be used in case there is a large shift between images.')","= MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position and velocity,","\"Bulk Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset: %s\\n\"","the difference in position and the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset =","angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb)","spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v =","this software, # the user agrees to comply with all applicable U.S. export","masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset","ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0 (the","None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None","return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize","and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0","= [] csb = [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower()","v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return","slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 =","sizes, starting ranges, # satellite heights and times for the first lines masterFramePort","+ (td.seconds + td.days * 24.0 * 3600) * 10**6) / 10**6 def","the user agrees to comply with all applicable U.S. export laws and regulations.","self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation',","None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy","spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def","Expecting input vectors of same length.\") raise Exception if not (size == 3):","# Calculate the distance moved since the last baseline point if (i >","velocity vector into a unit vector c = MM.crossProduct(r,v) # Calculate the vector","method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit","self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop()","calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the","setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var):","24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame","baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients","look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients =","calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV","image, '+ '\"top\" implies near start of master image, '+ '\"bottom\" implies at","of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif","component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline","Exception if not (size == 3): print(\"Error. Expecting input vectors of length 3.\")","= frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid","as MM from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis","# These provide the range and azimuth pixel sizes, starting ranges, # satellite","OF ANY KIND, either express or implied. # See the License for the","the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients","- masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV =","Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime,","= -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old","slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection","comply with all applicable U.S. export laws and regulations. # The user has","+= (self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr += \"Bulk","use). By downloading this software, # the user agrees to comply with all","= frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit =","to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return","return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return","center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)]","refactored into a method that calculates the baseline between #TODO frames when given","A class to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 =","control laws and regulations and has been classified as 'EAR99 NLR' # (No","self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1]","basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))] #","quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not","self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame","[] vb = [] hb = [] csb = [] asb = []","and velocity, this is the c, or cross-track vector c = MM.normalizeVector(c) v","could be further refactored into a method that calculates the baseline between #TODO","c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \"velocity\" component that","name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None","length of the projection of the difference in position and the \"velocity\" component","self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius)","= None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family,","= Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \"Initial Baseline estimates","- datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in","def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return","estimates \\n\" retstr += \"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr += \"Vertical","top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)]","{} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return None def","= None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize =","def __init__(self): self.x1 = [] self.x2 = [] self.x3 = [] # A","= sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector","hb = [] csb = [] asb = [] s = [0.,0.,0.] if","None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name)","normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline point","super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables","like we really need two orbits, a time, range and azimuth pixel sizes","def baseline(self): #TODO This could be further refactored into a method that calculates","Calculate the vector perpendicular to the platform position and velocity, this is the","Calculate the length of the projection of the difference in position and the","class to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = []","datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0),","or agreed to in writing, software # distributed under the License is distributed","return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return","= 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the master","self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate","of the scene, mid-scene, and the end of the scene # First, get","self.height = None self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop","calculate an orthogonal basis for cross-track and velocity directions # based on the","raise Exception if not (size == 3): print(\"Error. Expecting input vectors of length","'+ 'top, middle, bottom of master image, '+ '\"top\" implies near start of","of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating","under the Apache License, Version 2.0 (the \"License\"); # you may not use","\"all\" implies '+ 'top, middle, bottom of master image, '+ '\"top\" implies near","masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top':","shift between images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list","applicable U.S. export laws and regulations. # The user has the responsibility to","License. # You may obtain a copy of the License at # #","yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j in range(size): A[i]","= [0]*size A = [0]*size M = [[0 for i in range(size) ]","of master image, '+ '\"bottom\" implies at bottom of master image, '+ '\"middle\"","return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c):","= None self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop =","self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset","= frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame =","getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self):","def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 * 3600) *","Expecting input vectors of length 3.\") raise Exception Y = [0]*size A =","= ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) #","of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable","= (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg -","a large shift between images.') ) class Baseline(Component): family = 'baseline' logging_name =","csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by the","and the end of the scene # First, get the position and velocity","[0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating baselines')","= self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis)","sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV #","master image, '+ '\"bottom\" implies at bottom of master image, '+ '\"middle\" implies","the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None","c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a","= BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and","License, Version 2.0 (the \"License\"); # you may not use this file except","from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis vectors class","estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center","calls this method #TODO multiple times to calculate the rate of baseline change","except when exporting to an embargoed country, # end user, or in support","hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def","position vector into a unit vector v = MM.normalizeVector(v) # Turn the velocity","3): print(\"Error. Expecting input vectors of length 3.\") raise Exception Y = [0]*size","datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image') masterTime","three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 = []","self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height)","elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image') masterTime =","sizes # the two starting ranges, a planet, and the two prfs #","the two starting ranges, a planet, and the two prfs # These provide","self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at","+ datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the","h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop","self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset","= math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def","copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by","at which to compute baselines - \"all\" implies '+ 'top, middle, bottom of","MInv = MM.invertMatrix(M) for i in range(size): for j in range(size): A[i] +=","range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset","the c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate","self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts()","self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb = [] hb =","self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop","last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i]","between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the","+ datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image')","self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc","frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None","and a slave time and a method that calls this method #TODO multiple","__init__(self): self.x1 = [] self.x2 = [] self.x3 = [] # A class","getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self):","pixel sizes # the two starting ranges, a planet, and the two prfs","* 3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame =","None self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1 = None","near start of master image, '+ '\"bottom\" implies at bottom of master image,","implies near middle of master image. '+ 'To be used in case there","method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save","None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999","import math import datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule","return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return","self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline","logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM from","self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid()","'top': print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() +","self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset","[0]*size A = [0]*size M = [[0 for i in range(size) ] for","# Calculate the gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0","baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] #","to any 'EAR99' # embargoed foreign country or citizen of those countries. #","or implied. # See the License for the specific language governing permissions and","and regulations and has been classified as 'EAR99 NLR' # (No [Export] License","baselines - \"all\" implies '+ 'top, middle, bottom of master image, '+ '\"top\"","= None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset =","first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def","= 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius +","float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range","# A class to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis):","and a method that calls this method #TODO multiple times to calculate the","= None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset =","lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self):","[0]*size M = [[0 for i in range(size) ] for j in range(size)]","cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \"velocity\"","import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class to hold","[] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image","= self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a new start","retstr += \"Bulk Range Offset: %s\\n\" retlst += (self.orbSlcRangeOffset,) return retstr % retlst","datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset)","+ asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 -","(self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset: %s\\n\" retlst += (self.orbSlcRangeOffset,) return retstr %","vector perpendicular to the platform position and velocity, this is the c, or","master time and a slave time and a method that calls this method","= None self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize =","for i in range(3): # Calculate the Baseline at the start of the","support of a prohibited end use). By downloading this software, # the user","vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3 =","hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by","It looks like we really need two orbits, a time, range and azimuth","= [] # A class to hold three-dimensional basis vectors for spacecraft baselines","Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v =","of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z =","self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the baseline polynomial def","def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def","for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M)","ranges, # satellite heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame)","use this file except in compliance with the License. # You may obtain","import Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector","United States Government Sponsorship acknowledged. This software is subject to # U.S. export","the difference between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) #","multiple times to calculate the rate of baseline change over time. for port","- datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime","ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp()","U.S. export control laws and regulations and has been classified as 'EAR99 NLR'","None self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None","that is perpendicular to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r)","input vectors of same length.\") raise Exception if not (size == 3): print(\"Error.","all applicable U.S. export laws and regulations. # The user has the responsibility","exporting this software to any 'EAR99' # embargoed foreign country or citizen of","getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self):","getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self):","around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() +","downloading this software, # the user agrees to comply with all applicable U.S.","for the specific language governing permissions and # limitations under the License. #","+= \"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\" retlst","slave time and a method that calls this method #TODO multiple times to","setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c","x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position","vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components","- h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes","not (size == 3): print(\"Error. Expecting input vectors of length 3.\") raise Exception","the \"velocity\" component that is perpendicular to the cross-track direction and position basis","[] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire","really need two orbits, a time, range and azimuth pixel sizes # the","'middle': print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0),","lookVector = self.calculateLookVector() az_offset = [] vb = [] hb = [] csb","[self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines","'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of","to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self)","= None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height =","[self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines","setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius):","pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var)","z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the difference","velocity at the start of the scene self.logger.info(\"Sampling time %s\" % i) masterBasis","= None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc =","an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either","return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds +","retstr += \"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr += \"Bulk Azimuth Offset:","= [] vb = [] hb = [] csb = [] asb =","None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None","vectors of same length.\") raise Exception if not (size == 3): print(\"Error. Expecting","return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return","# A class to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1","= MM.norm(v) return normV # Given an orbit and a time, calculate an","ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame =","= None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc =","] for j in range(size)] for j in range(size): for i in range(size):","self.startingRange2 # Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size","A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return","slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) =","# distributed under the License is distributed on an \"AS IS\" BASIS, #","Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A","from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class","[] # A class to hold three-dimensional basis vectors for spacecraft baselines class","of master image. '+ 'To be used in case there is a large","embargoed country, # end user, or in support of a prohibited end use).","def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def","master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower()","Given two position vectors and a basis, calculate the offset between the two","method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the","BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc =","scene # First, get the position and velocity at the start of the","parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the master frame def","return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return","= None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius =","Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,)","the look vector of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight","midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame","orbit and a time, calculate an orthogonal basis for cross-track and velocity directions","Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset: %s\\n\" retlst","#TODO frames when given a master time and a slave time and a","with the License. # You may obtain a copy of the License at","obtain export licenses, or other export # authority as may be required before","self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop","= {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables =","datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime =","return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time,","# print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl","((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height:","x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the","a the \"velocity\" component that is perpendicular to the cross-track direction and position","\"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\" retlst +=","law or agreed to in writing, software # distributed under the License is","the velocity vector into a unit vector c = MM.crossProduct(r,v) # Calculate the","frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None","= orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) #","self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg","= [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location:","country or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math","# based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1","and the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset #","of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else:","compute baselines - \"all\" implies '+ 'top, middle, bottom of master image, '+","directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite')","a unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the","== 'middle': print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() -","= None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate =","= None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst =","implies '+ 'top, middle, bottom of master image, '+ '\"top\" implies near start","import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM","# Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import","v = MM.crossProduct(c,r) # Calculate a the \"velocity\" component that is perpendicular to","return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return","in compliance with the License. # You may obtain a copy of the","License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or","v = MM.normalizeVector(v) # Turn the velocity vector into a unit vector c","(No [Export] License Required except when exporting to an embargoed country, # end","responsibility to obtain export licenses, or other export # authority as may be","'EAR99' # embargoed foreign country or citizen of those countries. # # Author:","s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite')","BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.","self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom","return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION =","self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return","a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required","def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def","if not (len(xRef) == len(yRef)): print(\"Error. Expecting input vectors of same length.\") raise","self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 =","return z_offset,v_offset,c_offset # Calculate the baseline components between two frames def baseline(self): #TODO","method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with","range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def","# These provide the orbits # These provide the range and azimuth pixel","basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1","old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables =","projection of the difference in position and the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector())","= {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return None","def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of","cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft","'all': print('Using entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif","Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr += \"Bulk Azimuth Offset: %s\\n\" retlst +=","j in range(size)] for j in range(size): for i in range(size): M[j][i] =","range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def","MM.normalizeVector(v) # Turn the velocity vector into a unit vector c = MM.crossProduct(r,v)","ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height","getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self):","crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1]","components between two frames def baseline(self): #TODO This could be further refactored into","vectors of length 3.\") raise Exception Y = [0]*size A = [0]*size M","or other export # authority as may be required before exporting this software","# print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) #","two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for","MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional","self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid)","horizontal and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0])","the specific language governing permissions and # limitations under the License. # #","with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius","= None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate =","= 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle","a unit vector v = MM.normalizeVector(v) # Turn the velocity vector into a","image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines","same length.\") raise Exception if not (size == 3): print(\"Error. Expecting input vectors","acknowledged. This software is subject to # U.S. export control laws and regulations","method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) =","a method that calls this method #TODO multiple times to calculate the rate","retstr += \"Vertical Baseline: %s\\n\" retlst += (self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\"","[self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image') masterTime","- vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1]","def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds +","sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into","method #TODO multiple times to calculate the rate of baseline change over time.","to calculate the rate of baseline change over time. for port in self.inputPorts:","= (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate","frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize","= None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset =","distributed under the License is distributed on an \"AS IS\" BASIS, # WITHOUT","self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline","length 3.\") raise Exception Y = [0]*size A = [0]*size M = [[0","= self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates","-99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component","lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master","in range(3): # Calculate the Baseline at the start of the scene, mid-scene,","two orbits, a time, range and azimuth pixel sizes # the two starting","States Government Sponsorship acknowledged. This software is subject to # U.S. export control","self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables =","the projection of the difference in position and the \"velocity\" component v_offset =","and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort)","over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = []","calculates the baseline between #TODO frames when given a master time and a","vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate","(self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr += \"Bulk Azimuth","range(size) ] for j in range(size)] for j in range(size): for i in","times to calculate the rate of baseline change over time. for port in","(az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize)","self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return","end user, or in support of a prohibited end use). By downloading this","None def createPorts(self): # Set input ports # It looks like we really","this file except in compliance with the License. # You may obtain a","Turn the position vector into a unit vector v = MM.normalizeVector(v) # Turn","baseline components between two frames def baseline(self): #TODO This could be further refactored","the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v","s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image for","def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 =","position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position","is a large shift between images.') ) class Baseline(Component): family = 'baseline' logging_name","is subject to # U.S. export control laws and regulations and has been","By downloading this software, # the user agrees to comply with all applicable","= [] self.x3 = [] # A class to hold three-dimensional basis vectors","= [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at the start","that calls this method #TODO multiple times to calculate the rate of baseline","= (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0]","i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since","into a unit vector v = MM.normalizeVector(v) # Turn the velocity vector into","baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\"Error.","bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()]","baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart()","= self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth","None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None","laws and regulations and has been classified as 'EAR99 NLR' # (No [Export]","Y = [0]*size A = [0]*size M = [[0 for i in range(size)","in range(size)] for j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i)","at bottom of master image, '+ '\"middle\" implies near middle of master image.","asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1","self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate","master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of","self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset","datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as","= slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the","of master image, '+ '\"top\" implies near start of master image, '+ '\"bottom\"","self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] #","== 'bottom': print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() -","self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate","crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg = (az_offset[0] +","export control laws and regulations and has been classified as 'EAR99 NLR' #","(size == 3): print(\"Error. Expecting input vectors of length 3.\") raise Exception Y","end of the scene # First, get the position and velocity at the","(len(xRef) == len(yRef)): print(\"Error. Expecting input vectors of same length.\") raise Exception if","Calculate a the \"velocity\" component that is perpendicular to the cross-track direction and","of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate","there is a large shift between images.') ) class Baseline(Component): family = 'baseline'","moved since the last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i]","\\n\" retstr += \"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr += \"Vertical Baseline:","= slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2","datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top","az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) #","retlst += (self.pBaselineTop,) retstr += \"Bulk Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr","# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to","bottom of master image, '+ '\"top\" implies near start of master image, '+","[[0 for i in range(size) ] for j in range(size)] for j in","= None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop =","return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return","self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1 = None self.startingRange2","that calculates the baseline between #TODO frames when given a master time and","= x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self):","None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None","frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl =","self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius","position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of","None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None","required by applicable law or agreed to in writing, software # distributed under","= midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange()","retstr += \"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,) retstr += \"Vertical Baseline: %s\\n\"","Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) #","= pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height =","Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] +","since the last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] -","asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate =","the end of the scene # First, get the position and velocity at","None self.height = None self.radius = None self.startingRange1 = None self.startingRange2 = None","method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset)","point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1]","baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() -","10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf","for j in range(size)] for j in range(size): for i in range(size): M[j][i]","self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def","a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite')","frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid","get the position and velocity at the start of the scene self.logger.info(\"Sampling time","in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb = [] hb","None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle = None","master image. '+ 'To be used in case there is a large shift","= [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of","U.S. export laws and regulations. # The user has the responsibility to obtain","You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #","== 3): print(\"Error. Expecting input vectors of length 3.\") raise Exception Y =","return None def __str__(self): retstr = \"Initial Baseline estimates \\n\" retstr += \"Cross-track","has been classified as 'EAR99 NLR' # (No [Export] License Required except when","None def __str__(self): retstr = \"Initial Baseline estimates \\n\" retstr += \"Cross-track Baseline:","the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity()","self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 -","__init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v):","_timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 * 3600) * 10**6)","self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): #","= MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \"velocity\" component that is","c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default =","at the start of the scene, mid-scene, and the end of the scene","= s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1","c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position and","setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range):","baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of","self.calculateLookVector() az_offset = [] vb = [] hb = [] csb = []","datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline","= None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger =","an orbit and a time, calculate an orthogonal basis for cross-track and velocity","[] hb = [] csb = [] asb = [] s = [0.,0.,0.]","self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds","getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self):","self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the baseline","def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf =","crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross","This software is subject to # U.S. export control laws and regulations and","# First, get the position and velocity at the start of the scene","RESERVED. # # Licensed under the Apache License, Version 2.0 (the \"License\"); #","# embargoed foreign country or citizen of those countries. # # Author: <NAME>","= crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg = (az_offset[0]","return (td.microseconds + (td.seconds + td.days * 24.0 * 3600) * 10**6) /","images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,)","# you may not use this file except in compliance with the License.","in range(len(x1))] # Calculate the difference between the master and slave position vectors","return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 *","in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv","def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def","[] return None def createPorts(self): # Set input ports # It looks like","else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid()","azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] +","governing permissions and # limitations under the License. # # United States Government","self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and","#UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except:","= frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit =","be required before exporting this software to any 'EAR99' # embargoed foreign country","def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 =","def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def","authority as may be required before exporting this software to any 'EAR99' #","setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range):","Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \"Initial","before exporting this software to any 'EAR99' # embargoed foreign country or citizen","self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc","been classified as 'EAR99 NLR' # (No [Export] License Required except when exporting","StateVector # A class to hold three-dimensional basis vectors class Basis(object): def __init__(self):","and the two prfs # These provide the orbits # These provide the","= MM.normalizeVector(x1) # Turn the position vector into a unit vector v =","frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit()","further refactored into a method that calculates the baseline between #TODO frames when","software, # the user agrees to comply with all applicable U.S. export laws","doc = ('Location at which to compute baselines - \"all\" implies '+ 'top,","self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 -","self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate","License for the specific language governing permissions and # limitations under the License.","self.logger.info(\"Sampling time %s\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate","the distance moved since the last baseline point if (i > 0): deltaT","# Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2]","azimuth pixel sizes # the two starting ranges, a planet, and the two","\"License\"); # you may not use this file except in compliance with the","obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless","Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)]","= verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset =","* 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject()","vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 =","language governing permissions and # limitations under the License. # # United States","== 'top': print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart()","+ datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image')","# Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0]","import StateVector # A class to hold three-dimensional basis vectors class Basis(object): def","# Turn the position vector into a unit vector v = MM.normalizeVector(v) #","Exception Y = [0]*size A = [0]*size M = [[0 for i in","addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency()","of baseline change over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector()","from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit","gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0]","times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort)","http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing,","in writing, software # distributed under the License is distributed on an \"AS","These provide the orbits # These provide the range and azimuth pixel sizes,","# United States Government Sponsorship acknowledged. This software is subject to # U.S.","M = [[0 for i in range(size) ] for j in range(size)] for","return basis # Given two position vectors and a basis, calculate the offset","prohibited end use). By downloading this software, # the user agrees to comply","frames when given a master time and a slave time and a method","user agrees to comply with all applicable U.S. export laws and regulations. #","difference between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate","def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius return def","prfs # These provide the orbits # These provide the range and azimuth","peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius =","Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import Component,","(BASELINE_LOCATION,) # Calculate the Look Angle of the master frame def calculateLookAngle(self): lookVector","agrees to comply with all applicable U.S. export laws and regulations. # The","the horizontal and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] -","or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the","MM.crossProduct(c,r) # Calculate a the \"velocity\" component that is perpendicular to the cross-track","(z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a new","print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(),","def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return def","Sponsorship acknowledged. This software is subject to # U.S. export control laws and","This could be further refactored into a method that calculates the baseline between","sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit and a time,","(z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and","return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame def calculateLookVector(self):","baseline(self): #TODO This could be further refactored into a method that calculates the","Turn the velocity vector into a unit vector c = MM.crossProduct(r,v) # Calculate","limitations under the License. # # United States Government Sponsorship acknowledged. This software","three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x):","for i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A","position and velocity, this is the c, or cross-track vector c = MM.normalizeVector(c)","self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc","# The user has the responsibility to obtain export licenses, or other export","= self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite')","2.0 (the \"License\"); # you may not use this file except in compliance","country, # end user, or in support of a prohibited end use). By","__init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame =","WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the","vector into a unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular","calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the","orbits, a time, range and azimuth pixel sizes # the two starting ranges,","= \"Initial Baseline estimates \\n\" retstr += \"Cross-track Baseline: %s\\n\" retlst = (self.hBaselineTop,)","self.x2 = [] self.x3 = [] # A class to hold three-dimensional basis","'\"bottom\" implies at bottom of master image, '+ '\"middle\" implies near middle of","# Given an orbit and a time, calculate an orthogonal basis for cross-track","# # Unless required by applicable law or agreed to in writing, software","calculate the rate of baseline change over time. for port in self.inputPorts: port()","express or implied. # See the License for the specific language governing permissions","MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \"velocity\" component that is perpendicular","looks like we really need two orbits, a time, range and azimuth pixel","vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline","= crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc =","direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given","self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid","r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop =","unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform","frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector","either express or implied. # See the License for the specific language governing","self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 * 3600)","given a master time and a slave time and a method that calls","A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize):","satellite heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort =","MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two frames def baseline(self):","= self.calculateLookVector() az_offset = [] vb = [] hb = [] csb =","# Calculate the difference between the master and slave position vectors z_offset =","v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components","retlst += (self.orbSlcAzimuthOffset,) retstr += \"Bulk Range Offset: %s\\n\" retlst += (self.orbSlcRangeOffset,) return","self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline,","i in range(3): # Calculate the Baseline at the start of the scene,","the License. # You may obtain a copy of the License at #","in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize):","self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(),","self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize()","NLR' # (No [Export] License Required except when exporting to an embargoed country,","= frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def","j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize","an embargoed country, # end user, or in support of a prohibited end","self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop","v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into a","the range and azimuth pixel sizes, starting ranges, # satellite heights and times","> 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV","self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit","# authority as may be required before exporting this software to any 'EAR99'","the rate of baseline change over time. for port in self.inputPorts: port() lookVector","name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {}","(asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2","# end user, or in support of a prohibited end use). By downloading","# # Licensed under the Apache License, Version 2.0 (the \"License\"); # you","Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop","<NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import Component, Port","slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis)","the vector perpendicular to the platform position and velocity, this is the c,","pixel sizes, starting ranges, # satellite heights and times for the first lines","= None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle =","of length 3.\") raise Exception Y = [0]*size A = [0]*size M =","# limitations under the License. # # United States Government Sponsorship acknowledged. This","two starting ranges, a planet, and the two prfs # These provide the","software to any 'EAR99' # embargoed foreign country or citizen of those countries.","the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables","= MM.invertMatrix(M) for i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j]","in case there is a large shift between images.') ) class Baseline(Component): family","basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and a basis, calculate","= MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between","Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0","# Turn the velocity vector into a unit vector c = MM.crossProduct(r,v) #","difference in position and the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector())","prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite')","<gh_stars>1-10 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. #","polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\"Error. Expecting","= ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame","frames def baseline(self): #TODO This could be further refactored into a method that","between images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list =","= frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit =","at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed","case there is a large shift between images.') ) class Baseline(Component): family =","position and the \"velocity\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset","velocity, this is the c, or cross-track vector c = MM.normalizeVector(c) v =","self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self): # Set input","math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time):","'EAR99 NLR' # (No [Export] License Required except when exporting to an embargoed","those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging","implies at bottom of master image, '+ '\"middle\" implies near middle of master","on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition()","calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius +","# Save the position offset # Calculate a new start time relativeSlaveTime =","def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r","i in range(size) ] for j in range(size)] for j in range(size): for","verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range","of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import","= r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to","self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst","self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid =","the orbits # These provide the range and azimuth pixel sizes, starting ranges,","exporting to an embargoed country, # end user, or in support of a","for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around","a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if","# Multiply the horizontal and vertical baseline components by the look angle vector","BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and a","orthogonal basis for cross-track and velocity directions # based on the spacecraft position","self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid()","and a time, calculate an orthogonal basis for cross-track and velocity directions #","% i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved","+= (self.pBaselineTop,) retstr += \"Bulk Azimuth Offset: %s\\n\" retlst += (self.orbSlcAzimuthOffset,) retstr +=","len(xRef) if not (len(xRef) == len(yRef)): print(\"Error. Expecting input vectors of same length.\")","None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None","if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] +","in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i","None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None","'To be used in case there is a large shift between images.') )","self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset)","except in compliance with the License. # You may obtain a copy of","the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1])","az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic","= logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables =","return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc","setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self):","starting ranges, # satellite heights and times for the first lines masterFramePort =","embargoed foreign country or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~","= [] self.optionalVariables = [] return None def createPorts(self): # Set input ports","self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height","velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time,","may not use this file except in compliance with the License. # You","License is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS","License. # # United States Government Sponsorship acknowledged. This software is subject to","= Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr =","+ td.days * 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame","return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return","= v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self):","time, calculate an orthogonal basis for cross-track and velocity directions # based on","may be required before exporting this software to any 'EAR99' # embargoed foreign","baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self):","self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days","rate of baseline change over time. for port in self.inputPorts: port() lookVector =","- self.startingRange2 # Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef):","mandatory=False, doc = ('Location at which to compute baselines - \"all\" implies '+","= [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for","has the responsibility to obtain export licenses, or other export # authority as","print('Using entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower()","orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV # Given an","[] csb = [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() ==","= [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image')","# Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v","in range(size) ] for j in range(size)] for j in range(size): for i","offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j]","= sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit and a","frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize =","Multiply the horizontal and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1]","def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit =","print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0),","input vectors of length 3.\") raise Exception Y = [0]*size A = [0]*size","%s\\n\" retlst += (self.vBaselineTop,) retstr += \"Perpendicular Baseline: %s\\n\" retlst += (self.pBaselineTop,) retstr","to # U.S. export control laws and regulations and has been classified as","not (len(xRef) == len(yRef)): print(\"Error. Expecting input vectors of same length.\") raise Exception","= self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical","def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name","slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal"],"string":"[\n \"in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in\",\n \"Unless required by applicable law or agreed to in writing, software # distributed\",\n \"Save the position offset # Calculate a new start time relativeSlaveTime = slaveTime[i]\",\n \"export laws and regulations. # The user has the responsibility to obtain export\",\n \"= ('Location at which to compute baselines - \\\"all\\\" implies '+ 'top, middle,\",\n \"return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self):\",\n \"def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def\",\n \"cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) )\",\n \"= [] return None def createPorts(self): # Set input ports # It looks\",\n \"port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb = []\",\n \"the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the\",\n \"None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None\",\n \"range and azimuth pixel sizes # the two starting ranges, a planet, and\",\n \"port() lookVector = self.calculateLookVector() az_offset = [] vb = [] hb = []\",\n \"range and azimuth pixel sizes, starting ranges, # satellite heights and times for\",\n \"Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector #\",\n \"c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two frames\",\n \"[(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the difference between the\",\n \"master image, '+ '\\\"middle\\\" implies near middle of master image. '+ 'To be\",\n \"near middle of master image. '+ 'To be used in case there is\",\n \"# Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed\",\n \"asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize)\",\n \"midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius =\",\n \"vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\" component\",\n \"z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius\",\n \"+= MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize\",\n \"orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn\",\n \"vector v = MM.normalizeVector(v) # Turn the velocity vector into a unit vector\",\n \"if not (size == 3): print(\\\"Error. Expecting input vectors of length 3.\\\") raise\",\n \"sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity\",\n \"self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height\",\n \"retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range\",\n \"def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def\",\n \"\\\"velocity\\\" component that is perpendicular to the cross-track direction and position basis =\",\n \"IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or\",\n \"self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2\",\n \"time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb\",\n \"Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \\\"Initial Baseline estimates \\\\n\\\"\",\n \"MM.norm(v) return normV # Given an orbit and a time, calculate an orthogonal\",\n \"the gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg =\",\n \"the responsibility to obtain export licenses, or other export # authority as may\",\n \"class to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self):\",\n \"middle of master image. '+ 'To be used in case there is a\",\n \"= MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\" component that is perpendicular to the\",\n \"# # United States Government Sponsorship acknowledged. This software is subject to #\",\n \"self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ',\",\n \"Government Sponsorship acknowledged. This software is subject to # U.S. export control laws\",\n \"default = 'all', type=str, mandatory=False, doc = ('Location at which to compute baselines\",\n \"'all', type=str, mandatory=False, doc = ('Location at which to compute baselines - \\\"all\\\"\",\n \"length.\\\") raise Exception if not (size == 3): print(\\\"Error. Expecting input vectors of\",\n \"= [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using\",\n \"self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of\",\n \"need two orbits, a time, range and azimuth pixel sizes # the two\",\n \"s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 =\",\n \"software # distributed under the License is distributed on an \\\"AS IS\\\" BASIS,\",\n \"masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom':\",\n \"and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating\",\n \"self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master\",\n \") # print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1)\",\n \"orbits # These provide the range and azimuth pixel sizes, starting ranges, #\",\n \"and a basis, calculate the offset between the two positions in this basis\",\n \"Baseline at the start of the scene, mid-scene, and the end of the\",\n \"+ self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range:\",\n \"= self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline point if\",\n \"a prohibited end use). By downloading this software, # the user agrees to\",\n \"at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() +\",\n \"the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law\",\n \"M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size):\",\n \"attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0]\",\n \"= csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2\",\n \"= (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 -\",\n \"self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom\",\n \"self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle\",\n \"= {} self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self): #\",\n \"self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables\",\n \"implies near start of master image, '+ '\\\"bottom\\\" implies at bottom of master\",\n \"Calculate the gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg\",\n \"'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at which to compute\",\n \"this is the c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r)\",\n \"and # limitations under the License. # # United States Government Sponsorship acknowledged.\",\n \"the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length\",\n \"r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the\",\n \"masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master\",\n \"at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0),\",\n \"the License. # # United States Government Sponsorship acknowledged. This software is subject\",\n \"or in support of a prohibited end use). By downloading this software, #\",\n \"%s\\\\n\\\" retlst += (self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,)\",\n \"crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2]\",\n \"which to compute baselines - \\\"all\\\" implies '+ 'top, middle, bottom of master\",\n \"None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius = None\",\n \"# Calculate the look vector of the master frame def calculateLookVector(self): try: z\",\n \"import datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule\",\n \"[cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite')\",\n \"image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() ==\",\n \"= frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject()\",\n \"vb = [] hb = [] csb = [] asb = [] s\",\n \"Required except when exporting to an embargoed country, # end user, or in\",\n \"midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit\",\n \"master image, '+ '\\\"top\\\" implies near start of master image, '+ '\\\"bottom\\\" implies\",\n \"= self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize =\",\n \"time and a method that calls this method #TODO multiple times to calculate\",\n \"10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 =\",\n \"the Look Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return\",\n \"# U.S. export control laws and regulations and has been classified as 'EAR99\",\n \"'\\\"middle\\\" implies near middle of master image. '+ 'To be used in case\",\n \"2010 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the\",\n \"perpendicular to the platform position and velocity, this is the c, or cross-track\",\n \"try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur\",\n \"def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3\",\n \"the baseline between #TODO frames when given a master time and a slave\",\n \"# Calculate the Baseline at the start of the scene, mid-scene, and the\",\n \"cross-track and velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv\",\n \"self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset\",\n \"export # authority as may be required before exporting this software to any\",\n \"return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return\",\n \"frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self):\",\n \"and velocity at the start of the scene self.logger.info(\\\"Sampling time %s\\\" % i)\",\n \"[Export] License Required except when exporting to an embargoed country, # end user,\",\n \"print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL:\",\n \"= MM.normalizeVector(v) # Turn the velocity vector into a unit vector c =\",\n \"not use this file except in compliance with the License. # You may\",\n \"self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables\",\n \"California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache\",\n \"= 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at which to\",\n \"for j in range(len(x1))] # Calculate the difference between the master and slave\",\n \"self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1\",\n \"distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY\",\n \"Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,)\",\n \"Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset: %s\\\\n\\\" retlst +=\",\n \"MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize =\",\n \"Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the\",\n \"under the License. # # United States Government Sponsorship acknowledged. This software is\",\n \"self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def\",\n \"= self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition()\",\n \"to obtain export licenses, or other export # authority as may be required\",\n \"for i in range(size) ] for j in range(size)] for j in range(size):\",\n \"unit vector v = MM.normalizeVector(v) # Turn the velocity vector into a unit\",\n \"0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV =\",\n \"agreed to in writing, software # distributed under the License is distributed on\",\n \"normV = MM.norm(v) return normV # Given an orbit and a time, calculate\",\n \"regulations. # The user has the responsibility to obtain export licenses, or other\",\n \"self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle\",\n \"is perpendicular to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v)\",\n \"h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg =\",\n \"\\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst\",\n \"', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar\",\n \"start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate\",\n \"polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\\\"Error. Expecting input vectors\",\n \"setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v\",\n \"getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self):\",\n \"self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit\",\n \"= csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset =\",\n \"a slave time and a method that calls this method #TODO multiple times\",\n \"verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1]\",\n \"raise Exception Y = [0]*size A = [0]*size M = [[0 for i\",\n \"'+ '\\\"middle\\\" implies near middle of master image. '+ 'To be used in\",\n \"frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def\",\n \"Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3 = [] #\",\n \"x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset #\",\n \"z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height +\",\n \"[self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at the start of\",\n \"# Calculate a the \\\"velocity\\\" component that is perpendicular to the cross-track direction\",\n \"ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2\",\n \"j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j]\",\n \"to in writing, software # distributed under the License is distributed on an\",\n \"First, get the position and velocity at the start of the scene self.logger.info(\\\"Sampling\",\n \"implied. # See the License for the specific language governing permissions and #\",\n \"of the scene # First, get the position and velocity at the start\",\n \"datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image') masterTime\",\n \"= self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the baseline polynomial\",\n \"frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR\",\n \"self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \\\"Initial Baseline estimates \\\\n\\\" retstr\",\n \"setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name =\",\n \"getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self):\",\n \"Calculate the Baseline at the start of the scene, mid-scene, and the end\",\n \"calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r =\",\n \"time %s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the\",\n \"scene, mid-scene, and the end of the scene # First, get the position\",\n \"(self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline:\",\n \"class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return\",\n \"Calculate the look vector of the master frame def calculateLookVector(self): try: z =\",\n \"frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None\",\n \"Apache License, Version 2.0 (the \\\"License\\\"); # you may not use this file\",\n \"countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from\",\n \"master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look\",\n \"family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look\",\n \"class Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3 = []\",\n \"az_offset.append(z_offset) # Save the position offset # Calculate a new start time relativeSlaveTime\",\n \"image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() ==\",\n \"offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset =\",\n \"specific language governing permissions and # limitations under the License. # # United\",\n \"self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst\",\n \"return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return\",\n \"+= \\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst\",\n \"* 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1\",\n \"component that is perpendicular to the cross-track direction and position basis = BaselineBasis()\",\n \"# See the License for the specific language governing permissions and # limitations\",\n \"the License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR\",\n \"masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline\",\n \"classified as 'EAR99 NLR' # (No [Export] License Required except when exporting to\",\n \"Set input ports # It looks like we really need two orbits, a\",\n \"scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV\",\n \"into a method that calculates the baseline between #TODO frames when given a\",\n \"the Apache License, Version 2.0 (the \\\"License\\\"); # you may not use this\",\n \"export licenses, or other export # authority as may be required before exporting\",\n \"self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius\",\n \"you may not use this file except in compliance with the License. #\",\n \"type=str, mandatory=False, doc = ('Location at which to compute baselines - \\\"all\\\" implies\",\n \"deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i],\",\n \"def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame\",\n \"= None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop =\",\n \"MM from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis vectors\",\n \"print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the\",\n \"location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime\",\n \"= ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height\",\n \"+ vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by the look\",\n \"= crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop =\",\n \"self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom\",\n \"deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2\",\n \"getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION\",\n \"basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors\",\n \"'bottom': print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0),\",\n \"# Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you may\",\n \"Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under\",\n \"#TODO This could be further refactored into a method that calculates the baseline\",\n \"def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate\",\n \"Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef)\",\n \"crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0]\",\n \"the last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0])\",\n \"self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(),\",\n \"{} self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self): # Set\",\n \"def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def\",\n \"except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/(\",\n \"of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif\",\n \"datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3):\",\n \"baseline change over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset\",\n \"and azimuth pixel sizes, starting ranges, # satellite heights and times for the\",\n \"= frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try:\",\n \"perpendicular to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c)\",\n \"(self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk\",\n \"Calculate the difference between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector())\",\n \"def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days *\",\n \"MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position and velocity, this\",\n \"Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at\",\n \"def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def\",\n \"#Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate\",\n \"of master image, '+ '\\\"middle\\\" implies near middle of master image. '+ 'To\",\n \"3.\\\") raise Exception Y = [0]*size A = [0]*size M = [[0 for\",\n \"vectors and a basis, calculate the offset between the two positions in this\",\n \"return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius return\",\n \"', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ',\",\n \"= (self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular\",\n \"+= \\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\"\",\n \"master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower()\",\n \"laws and regulations. # The user has the responsibility to obtain export licenses,\",\n \"pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius\",\n \"a basis, calculate the offset between the two positions in this basis def\",\n \"baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] =\",\n \"None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None\",\n \"datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of\",\n \"self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl)\",\n \"# Set input ports # It looks like we really need two orbits,\",\n \"isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class to\",\n \"math import datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import\",\n \"# satellite heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort\",\n \"azimuth pixel sizes, starting ranges, # satellite heights and times for the first\",\n \"used in case there is a large shift between images.') ) class Baseline(Component):\",\n \"class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate\",\n \"The user has the responsibility to obtain export licenses, or other export #\",\n \"self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame def\",\n \"'\\\"top\\\" implies near start of master image, '+ '\\\"bottom\\\" implies at bottom of\",\n \"'+ '\\\"top\\\" implies near start of master image, '+ '\\\"bottom\\\" implies at bottom\",\n \"MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two\",\n \"# the two starting ranges, a planet, and the two prfs # These\",\n \"'top, middle, bottom of master image, '+ '\\\"top\\\" implies near start of master\",\n \"{} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = []\",\n \"provide the orbits # These provide the range and azimuth pixel sizes, starting\",\n \"retstr = \\\"Initial Baseline estimates \\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst =\",\n \"the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j])\",\n \"'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the master frame\",\n \"the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)):\",\n \"= self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last\",\n \"time, range and azimuth pixel sizes # the two starting ranges, a planet,\",\n \"print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl =\",\n \"normV # Given an orbit and a time, calculate an orthogonal basis for\",\n \"= [] self.x2 = [] self.x3 = [] # A class to hold\",\n \"vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] #\",\n \"= None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom =\",\n \"the platform position and velocity, this is the c, or cross-track vector c\",\n \"# Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables =\",\n \"the scene, mid-scene, and the end of the scene # First, get the\",\n \"on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,\",\n \"user, or in support of a prohibited end use). By downloading this software,\",\n \"self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''):\",\n \"the length of the projection of the difference in position and the \\\"velocity\\\"\",\n \"getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td):\",\n \"and azimuth pixel sizes # the two starting ranges, a planet, and the\",\n \"self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit\",\n \"# print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl)\",\n \"Given an orbit and a time, calculate an orthogonal basis for cross-track and\",\n \"A = [0]*size M = [[0 for i in range(size) ] for j\",\n \"logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the\",\n \"basis for cross-track and velocity directions # based on the spacecraft position def\",\n \"position and velocity at the start of the scene self.logger.info(\\\"Sampling time %s\\\" %\",\n \"and velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv =\",\n \"except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame\",\n \"in position and the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return\",\n \"creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid =\",\n \"See the License for the specific language governing permissions and # limitations under\",\n \"self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV\",\n \"hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 =\",\n \"- datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition()\",\n \"basis # Given two position vectors and a basis, calculate the offset between\",\n \"the start of the scene self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i])\",\n \"# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in\",\n \"len(yRef)): print(\\\"Error. Expecting input vectors of same length.\\\") raise Exception if not (size\",\n \"to compute baselines - \\\"all\\\" implies '+ 'top, middle, bottom of master image,\",\n \"basis.setCrossTrackVector(c) return basis # Given two position vectors and a basis, calculate the\",\n \"the two prfs # These provide the orbits # These provide the range\",\n \"# Given two position vectors and a basis, calculate the offset between the\",\n \"self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset\",\n \"print(\\\"Error. Expecting input vectors of same length.\\\") raise Exception if not (size ==\",\n \"createPorts(self): # Set input ports # It looks like we really need two\",\n \"the position vector into a unit vector v = MM.normalizeVector(v) # Turn the\",\n \"slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \\\"Initial Baseline\",\n \"= crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate =\",\n \"i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for\",\n \"raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() +\",\n \"+ self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ',\",\n \"method that calculates the baseline between #TODO frames when given a master time\",\n \"calculate the offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx\",\n \"the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis\",\n \"between two frames def baseline(self): #TODO This could be further refactored into a\",\n \"based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 =\",\n \"getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0\",\n \"basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and a basis,\",\n \"Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License,\",\n \"between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] -\",\n \"between #TODO frames when given a master time and a slave time and\",\n \"- asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc\",\n \"this method #TODO multiple times to calculate the rate of baseline change over\",\n \"sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into a unit vector\",\n \"# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0\",\n \"return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False,\",\n \"isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis vectors class Basis(object):\",\n \"def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def\",\n \"%s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset: %s\\\\n\\\" retlst += (self.orbSlcRangeOffset,)\",\n \"user has the responsibility to obtain export licenses, or other export # authority\",\n \"masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr\",\n \"csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 #\",\n \"2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius) #\",\n \"A class to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def\",\n \"the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate\",\n \"BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1\",\n \"vector of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z\",\n \"sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1)\",\n \"this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))]\",\n \"= (BASELINE_LOCATION,) # Calculate the Look Angle of the master frame def calculateLookAngle(self):\",\n \"#TODO multiple times to calculate the rate of baseline change over time. for\",\n \"= None self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1 =\",\n \"end use). By downloading this software, # the user agrees to comply with\",\n \"regulations and has been classified as 'EAR99 NLR' # (No [Export] License Required\",\n \"self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3\",\n \"= self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset)\",\n \"# Calculate the length of the projection of the difference in position and\",\n \"{0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime =\",\n \"range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv =\",\n \"[self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation))\",\n \"required before exporting this software to any 'EAR99' # embargoed foreign country or\",\n \"= self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self,\",\n \"return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return\",\n \"and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two\",\n \"self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger\",\n \"an orthogonal basis for cross-track and velocity directions # based on the spacecraft\",\n \"getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self):\",\n \"KIND, either express or implied. # See the License for the specific language\",\n \"for j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] =\",\n \"j in range(len(x1))] # Calculate the difference between the master and slave position\",\n \"self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) +\",\n \"# the user agrees to comply with all applicable U.S. export laws and\",\n \"self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame =\",\n \"self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating baselines') masterTime =\",\n \"ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height =\",\n \"asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc =\",\n \"citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime\",\n \"self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def\",\n \"+ self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius: ',\",\n \"as 'EAR99 NLR' # (No [Export] License Required except when exporting to an\",\n \"ANY KIND, either express or implied. # See the License for the specific\",\n \"'+ '\\\"bottom\\\" implies at bottom of master image, '+ '\\\"middle\\\" implies near middle\",\n \"%s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance\",\n \"start of the scene self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV\",\n \"position vectors and a basis, calculate the offset between the two positions in\",\n \"any 'EAR99' # embargoed foreign country or citizen of those countries. # #\",\n \"#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. # #\",\n \"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See\",\n \"= range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop\",\n \"az_offset = [] vb = [] hb = [] csb = [] asb\",\n \"with all applicable U.S. export laws and regulations. # The user has the\",\n \"fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef)\",\n \"start of master image, '+ '\\\"bottom\\\" implies at bottom of master image, '+\",\n \"= [] hb = [] csb = [] asb = [] s =\",\n \"mid-scene, and the end of the scene # First, get the position and\",\n \"cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis #\",\n \"return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return\",\n \"Calculate the distance moved since the last baseline point if (i > 0):\",\n \"at the start of the scene self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis =\",\n \"offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) #\",\n \"is the c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) #\",\n \"[] self.optionalVariables = [] return None def createPorts(self): # Set input ports #\",\n \"= [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating\",\n \"== 'all': print('Using entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()]\",\n \"method that calls this method #TODO multiple times to calculate the rate of\",\n \"range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize\",\n \"public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location at which\",\n \"permissions and # limitations under the License. # # United States Government Sponsorship\",\n \"the scene self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i])\",\n \"image, '+ '\\\"bottom\\\" implies at bottom of master image, '+ '\\\"middle\\\" implies near\",\n \"# Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size =\",\n \"be used in case there is a large shift between images.') ) class\",\n \"subject to # U.S. export control laws and regulations and has been classified\",\n \"# Calculate the vector perpendicular to the platform position and velocity, this is\",\n \"platform position and velocity, this is the c, or cross-track vector c =\",\n \"None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline')\",\n \"radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range\",\n \"getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds\",\n \"spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV =\",\n \"', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl]\",\n \"self.x1 = [] self.x2 = [] self.x3 = [] # A class to\",\n \"under the License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES\",\n \"self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize\",\n \"to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) ==\",\n \"\\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express\",\n \"masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 =\",\n \"for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return\",\n \"= c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default\",\n \"size = len(xRef) if not (len(xRef) == len(yRef)): print(\\\"Error. Expecting input vectors of\",\n \"the position and velocity at the start of the scene self.logger.info(\\\"Sampling time %s\\\"\",\n \"large shift between images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline'\",\n \"the start of the scene, mid-scene, and the end of the scene #\",\n \"applicable law or agreed to in writing, software # distributed under the License\",\n \"= Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc = ('Location\",\n \"change over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset =\",\n \"components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients =\",\n \"getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str,\",\n \"\\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the\",\n \"\\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst +=\",\n \"CONDITIONS OF ANY KIND, either express or implied. # See the License for\",\n \"= frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize\",\n \"of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version\",\n \"retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr +=\",\n \"writing, software # distributed under the License is distributed on an \\\"AS IS\\\"\",\n \"ports # It looks like we really need two orbits, a time, range\",\n \"verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset\",\n \"for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x\",\n \"= self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets\",\n \"= orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV # Given\",\n \"frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid\",\n \"- datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() -\",\n \"# It looks like we really need two orbits, a time, range and\",\n \"= frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV =\",\n \"the baseline components between two frames def baseline(self): #TODO This could be further\",\n \"compliance with the License. # You may obtain a copy of the License\",\n \"entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() ==\",\n \"of same length.\\\") raise Exception if not (size == 3): print(\\\"Error. Expecting input\",\n \"def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def\",\n \"= MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the difference in\",\n \"self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg\",\n \"= masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position\",\n \"# Calculate the baseline components between two frames def baseline(self): #TODO This could\",\n \"Baseline estimates \\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr +=\",\n \"logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {}\",\n \"None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None\",\n \"we really need two orbits, a time, range and azimuth pixel sizes #\",\n \"v = sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit and\",\n \"= az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a\",\n \"frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame\",\n \"heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame)\",\n \"class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop =\",\n \"= slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate\",\n \"= len(xRef) if not (len(xRef) == len(yRef)): print(\\\"Error. Expecting input vectors of same\",\n \"basis, calculate the offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis):\",\n \"('Location at which to compute baselines - \\\"all\\\" implies '+ 'top, middle, bottom\",\n \"= math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for\",\n \"for cross-track and velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time):\",\n \"dx = [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the difference\",\n \"self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc\",\n \"= [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating\",\n \"(td.microseconds + (td.seconds + td.days * 24.0 * 3600) * 10**6) / 10**6\",\n \"def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def\",\n \"self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop\",\n \"Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j in\",\n \"(the \\\"License\\\"); # you may not use this file except in compliance with\",\n \"[self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i\",\n \"self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self):\",\n \"of a prohibited end use). By downloading this software, # the user agrees\",\n \"distance moved since the last baseline point if (i > 0): deltaT =\",\n \"return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return\",\n \"# Unless required by applicable law or agreed to in writing, software #\",\n \"other export # authority as may be required before exporting this software to\",\n \"by applicable law or agreed to in writing, software # distributed under the\",\n \"self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf\",\n \"as may be required before exporting this software to any 'EAR99' # embargoed\",\n \"self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) #\",\n \"when given a master time and a slave time and a method that\",\n \"starting ranges, a planet, and the two prfs # These provide the orbits\",\n \"+= (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset: %s\\\\n\\\" retlst += (self.orbSlcRangeOffset,) return retstr\",\n \"position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity()\",\n \"file except in compliance with the License. # You may obtain a copy\",\n \"# print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate\",\n \"print(\\\"Error. Expecting input vectors of length 3.\\\") raise Exception Y = [0]*size A\",\n \"These provide the range and azimuth pixel sizes, starting ranges, # satellite heights\",\n \"the position offset # Calculate a new start time relativeSlaveTime = slaveTime[i] -\",\n \"by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb)\",\n \"az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset =\",\n \"self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop\",\n \"in support of a prohibited end use). By downloading this software, # the\",\n \"offset # Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV\",\n \"self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \\\"Initial Baseline estimates \\\\n\\\" retstr +=\",\n \"def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return\",\n \"and has been classified as 'EAR99 NLR' # (No [Export] License Required except\",\n \"def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\\\"Error. Expecting input\",\n \"input ports # It looks like we really need two orbits, a time,\",\n \"self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a new start time\",\n \"MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the difference in position\",\n \"or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import\",\n \"basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3\",\n \"self.x3 = [] # A class to hold three-dimensional basis vectors for spacecraft\",\n \"software is subject to # U.S. export control laws and regulations and has\",\n \"elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image') masterTime =\",\n \"(-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class\",\n \"try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height\",\n \"= verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset =\",\n \"= self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame\",\n \"licenses, or other export # authority as may be required before exporting this\",\n \"None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None\",\n \"Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2\",\n \"a time, range and azimuth pixel sizes # the two starting ranges, a\",\n \"x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply\",\n \"# slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at\",\n \"OR CONDITIONS OF ANY KIND, either express or implied. # See the License\",\n \"may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #\",\n \"asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span\",\n \"of the projection of the difference in position and the \\\"velocity\\\" component v_offset\",\n \"self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize\",\n \"- datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at\",\n \"math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame def calculateLookVector(self): try:\",\n \"= range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self):\",\n \"MM.normalizeVector(x1) # Turn the position vector into a unit vector v = MM.normalizeVector(v)\",\n \"a planet, and the two prfs # These provide the orbits # These\",\n \"retlst = (self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr +=\",\n \"self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit\",\n \"look vector of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except:\",\n \"planet, and the two prfs # These provide the orbits # These provide\",\n \"# # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component\",\n \"the scene # First, get the position and velocity at the start of\",\n \"def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def\",\n \"ranges, a planet, and the two prfs # These provide the orbits #\",\n \"vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position\",\n \"span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle':\",\n \"- \\\"all\\\" implies '+ 'top, middle, bottom of master image, '+ '\\\"top\\\" implies\",\n \"= radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 =\",\n \"def createPorts(self): # Set input ports # It looks like we really need\",\n \"self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate\",\n \"two frames def baseline(self): #TODO This could be further refactored into a method\",\n \"cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv =\",\n \"Calculate the Look Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector()\",\n \"self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc\",\n \"to an embargoed country, # end user, or in support of a prohibited\",\n \"/ 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange()\",\n \"(td.seconds + td.days * 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self):\",\n \"return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return\",\n \"__str__(self): retstr = \\\"Initial Baseline estimates \\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst\",\n \"math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j\",\n \"vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by the look angle\",\n \"azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg\",\n \"getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def\",\n \"position offset # Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV))\",\n \"new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') #\",\n \"def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all',\",\n \"self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a()\",\n \"x1[j]) for j in range(len(x1))] # Calculate the difference between the master and\",\n \"= float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 =\",\n \"when exporting to an embargoed country, # end user, or in support of\",\n \"# (No [Export] License Required except when exporting to an embargoed country, #\",\n \"self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset)\",\n \"= pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius =\",\n \"range(3): # Calculate the Baseline at the start of the scene, mid-scene, and\",\n \"two prfs # These provide the orbits # These provide the range and\",\n \"to comply with all applicable U.S. export laws and regulations. # The user\",\n \"= [[0 for i in range(size) ] for j in range(size)] for j\",\n \"self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset\",\n \"vector into a unit vector v = MM.normalizeVector(v) # Turn the velocity vector\",\n \"== len(yRef)): print(\\\"Error. Expecting input vectors of same length.\\\") raise Exception if not\",\n \"frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(),\",\n \"td.days * 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame =\",\n \"range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return\",\n \"self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION',\",\n \"+= \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset:\",\n \"= [0]*size M = [[0 for i in range(size) ] for j in\",\n \"self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables\",\n \"self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the\",\n \"z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius:\",\n \"= 'all', type=str, mandatory=False, doc = ('Location at which to compute baselines -\",\n \"masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i],\",\n \"master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise\",\n \"range(len(x1))] # Calculate the difference between the master and slave position vectors z_offset\",\n \"def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2\",\n \") class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) #\",\n \"Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = []\",\n \"x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return\",\n \"range(size)] for j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j]\",\n \"slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a\",\n \"the Baseline at the start of the scene, mid-scene, and the end of\",\n \"the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0\",\n \"to the platform position and velocity, this is the c, or cross-track vector\",\n \"- self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate =\",\n \"self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master\",\n \"time and a slave time and a method that calls this method #TODO\",\n \"provide the range and azimuth pixel sizes, starting ranges, # satellite heights and\",\n \"Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you may not\",\n \"this software to any 'EAR99' # embargoed foreign country or citizen of those\",\n \"start of the scene, mid-scene, and the end of the scene # First,\",\n \"z_offset,v_offset,c_offset # Calculate the baseline components between two frames def baseline(self): #TODO This\",\n \"elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image') masterTime =\",\n \"slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()]\",\n \"for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb =\",\n \"image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown\",\n \"+ z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) #\",\n \"into a unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to\",\n \"+ az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset\",\n \"is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF\",\n \"MM.invertMatrix(M) for i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return\",\n \"self.optionalVariables = [] return None def createPorts(self): # Set input ports # It\",\n \"middle, bottom of master image, '+ '\\\"top\\\" implies near start of master image,\",\n \"baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the\",\n \"relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets\",\n \"setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate\",\n \"+ deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition()\",\n \"3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame\",\n \"masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the\",\n \"r = MM.normalizeVector(x1) # Turn the position vector into a unit vector v\",\n \"of the difference in position and the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset\",\n \"= [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating\",\n \"- x1[j]) for j in range(len(x1))] # Calculate the difference between the master\",\n \"self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset\",\n \"#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import Component, Port from\",\n \"return normV # Given an orbit and a time, calculate an orthogonal basis\",\n \"return None def createPorts(self): # Set input ports # It looks like we\",\n \"def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def\",\n \"self.height = float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1\",\n \"foreign country or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import\",\n \"of the scene self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV =\",\n \"the License for the specific language governing permissions and # limitations under the\",\n \"self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline point if (i\",\n \"(i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV\",\n \"to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2\",\n \"vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the\",\n \"frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight\",\n \"', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1\",\n \"- cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv\",\n \"image. '+ 'To be used in case there is a large shift between\",\n \"None self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None\",\n \"a time, calculate an orthogonal basis for cross-track and velocity directions # based\",\n \"= frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height =\",\n \"Calculate the baseline components between two frames def baseline(self): #TODO This could be\",\n \"= None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() #\",\n \"\\\"Initial Baseline estimates \\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr\",\n \"= [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the difference between\",\n \"= midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius\",\n \"getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self):\",\n \"None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None\",\n \"a method that calculates the baseline between #TODO frames when given a master\",\n \"baseline between #TODO frames when given a master time and a slave time\",\n \"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #\",\n \"[] self.x3 = [] # A class to hold three-dimensional basis vectors for\",\n \"verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset\",\n \"%s\\\\n\\\" retlst = (self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr\",\n \"and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the\",\n \"[] self.x2 = [] self.x3 = [] # A class to hold three-dimensional\",\n \"0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height)\",\n \"a master time and a slave time and a method that calls this\",\n \"# Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV =\",\n \"and regulations. # The user has the responsibility to obtain export licenses, or\",\n \"range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in\",\n \"= yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j in range(size):\",\n \"RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0 (the \\\"License\\\");\",\n \"baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid()\",\n \"def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius\",\n \"License Required except when exporting to an embargoed country, # end user, or\",\n \"def __str__(self): retstr = \\\"Initial Baseline estimates \\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\"\",\n \"in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return\",\n \"image, '+ '\\\"middle\\\" implies near middle of master image. '+ 'To be used\",\n \"self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset\",\n \"= None self.height = None self.radius = None self.startingRange1 = None self.startingRange2 =\",\n \"csb = [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all':\",\n \"+ datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom\",\n \"= self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z)\",\n \"slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at the\",\n \"self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV\",\n \"be further refactored into a method that calculates the baseline between #TODO frames\",\n \"bottom of master image, '+ '\\\"middle\\\" implies near middle of master image. '+\",\n \"= sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into a unit\",\n \"two position vectors and a basis, calculate the offset between the two positions\",\n \"Version 2.0 (the \\\"License\\\"); # you may not use this file except in\",\n \"iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import\",\n \"# Calculate the Look Angle of the master frame def calculateLookAngle(self): lookVector =\",\n \"if self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating baselines') masterTime\",\n \"= MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two frames def\",\n \"addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit()\",\n \"time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the\",\n \"the offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx =\",\n \"Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {}\",\n \"def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst def\",\n \"for j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize =\",\n \"= verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom =\",\n \"master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl\",\n \"csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1\",\n \"i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A def\",\n \"(self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate\",\n \"self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate\",\n \"positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j\",\n \"velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v)\",\n \"scene self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) #\",\n \"print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return\",\n \"print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop()\",\n \"Look Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0]))\",\n \"'+ 'To be used in case there is a large shift between images.')\",\n \"= MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position and velocity,\",\n \"\\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset: %s\\\\n\\\"\",\n \"the difference in position and the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset =\",\n \"angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb)\",\n \"spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v =\",\n \"this software, # the user agrees to comply with all applicable U.S. export\",\n \"masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset\",\n \"ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0 (the\",\n \"None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None\",\n \"return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize\",\n \"and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0\",\n \"= [] csb = [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower()\",\n \"v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return\",\n \"slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 =\",\n \"sizes, starting ranges, # satellite heights and times for the first lines masterFramePort\",\n \"+ (td.seconds + td.days * 24.0 * 3600) * 10**6) / 10**6 def\",\n \"the user agrees to comply with all applicable U.S. export laws and regulations.\",\n \"self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation',\",\n \"None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy\",\n \"spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def\",\n \"Expecting input vectors of same length.\\\") raise Exception if not (size == 3):\",\n \"# Calculate the distance moved since the last baseline point if (i >\",\n \"velocity vector into a unit vector c = MM.crossProduct(r,v) # Calculate the vector\",\n \"method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit\",\n \"self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop()\",\n \"calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the\",\n \"setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var):\",\n \"24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame\",\n \"baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients\",\n \"look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients =\",\n \"calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV\",\n \"image, '+ '\\\"top\\\" implies near start of master image, '+ '\\\"bottom\\\" implies at\",\n \"of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif\",\n \"component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline\",\n \"Exception if not (size == 3): print(\\\"Error. Expecting input vectors of length 3.\\\")\",\n \"= frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid\",\n \"as MM from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis\",\n \"# These provide the range and azimuth pixel sizes, starting ranges, # satellite\",\n \"OF ANY KIND, either express or implied. # See the License for the\",\n \"the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients\",\n \"- masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV =\",\n \"Calculate a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime,\",\n \"= -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old\",\n \"slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection\",\n \"comply with all applicable U.S. export laws and regulations. # The user has\",\n \"+= (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr += \\\"Bulk\",\n \"use). By downloading this software, # the user agrees to comply with all\",\n \"= frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit =\",\n \"to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return\",\n \"return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return\",\n \"center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)]\",\n \"refactored into a method that calculates the baseline between #TODO frames when given\",\n \"A class to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 =\",\n \"control laws and regulations and has been classified as 'EAR99 NLR' # (No\",\n \"self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1]\",\n \"basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))] #\",\n \"quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not\",\n \"self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame\",\n \"[] vb = [] hb = [] csb = [] asb = []\",\n \"and velocity, this is the c, or cross-track vector c = MM.normalizeVector(c) v\",\n \"could be further refactored into a method that calculates the baseline between #TODO\",\n \"c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\" component that\",\n \"name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None\",\n \"length of the projection of the difference in position and the \\\"velocity\\\" component\",\n \"self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height) # print('Radius: ', self.radius)\",\n \"= None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family,\",\n \"= Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \\\"Initial Baseline estimates\",\n \"- datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in\",\n \"def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return\",\n \"estimates \\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr += \\\"Vertical\",\n \"top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)]\",\n \"{} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return None def\",\n \"= None self.slaveFrame = None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize =\",\n \"def __init__(self): self.x1 = [] self.x2 = [] self.x3 = [] # A\",\n \"= sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector\",\n \"hb = [] csb = [] asb = [] s = [0.,0.,0.] if\",\n \"None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name)\",\n \"normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline point\",\n \"super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables\",\n \"like we really need two orbits, a time, range and azimuth pixel sizes\",\n \"def baseline(self): #TODO This could be further refactored into a method that calculates\",\n \"Calculate the vector perpendicular to the platform position and velocity, this is the\",\n \"Calculate the length of the projection of the difference in position and the\",\n \"class to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = []\",\n \"datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0),\",\n \"or agreed to in writing, software # distributed under the License is distributed\",\n \"return self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return\",\n \"= 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the master\",\n \"self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate\",\n \"of the scene, mid-scene, and the end of the scene # First, get\",\n \"self.height = None self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop\",\n \"calculate an orthogonal basis for cross-track and velocity directions # based on the\",\n \"raise Exception if not (size == 3): print(\\\"Error. Expecting input vectors of length\",\n \"'+ 'top, middle, bottom of master image, '+ '\\\"top\\\" implies near start of\",\n \"of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating\",\n \"under the Apache License, Version 2.0 (the \\\"License\\\"); # you may not use\",\n \"\\\"all\\\" implies '+ 'top, middle, bottom of master image, '+ '\\\"top\\\" implies near\",\n \"masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top':\",\n \"shift between images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list\",\n \"applicable U.S. export laws and regulations. # The user has the responsibility to\",\n \"License. # You may obtain a copy of the License at # #\",\n \"yRef[j] MInv = MM.invertMatrix(M) for i in range(size): for j in range(size): A[i]\",\n \"= [0]*size A = [0]*size M = [[0 for i in range(size) ]\",\n \"of master image, '+ '\\\"bottom\\\" implies at bottom of master image, '+ '\\\"middle\\\"\",\n \"return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c):\",\n \"= None self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop =\",\n \"self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset\",\n \"= frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame =\",\n \"getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self):\",\n \"def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 * 3600) *\",\n \"Expecting input vectors of length 3.\\\") raise Exception Y = [0]*size A =\",\n \"= ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) #\",\n \"of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable\",\n \"= (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg -\",\n \"a large shift between images.') ) class Baseline(Component): family = 'baseline' logging_name =\",\n \"csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by the\",\n \"and the end of the scene # First, get the position and velocity\",\n \"[0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image for estimating baselines')\",\n \"= self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis)\",\n \"sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV #\",\n \"master image, '+ '\\\"bottom\\\" implies at bottom of master image, '+ '\\\"middle\\\" implies\",\n \"the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None\",\n \"c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a\",\n \"= BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and\",\n \"License, Version 2.0 (the \\\"License\\\"); # you may not use this file except\",\n \"from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional basis vectors class\",\n \"estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center\",\n \"calls this method #TODO multiple times to calculate the rate of baseline change\",\n \"except when exporting to an embargoed country, # end user, or in support\",\n \"hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def\",\n \"position vector into a unit vector v = MM.normalizeVector(v) # Turn the velocity\",\n \"3): print(\\\"Error. Expecting input vectors of length 3.\\\") raise Exception Y = [0]*size\",\n \"datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image') masterTime\",\n \"three-dimensional basis vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 = []\",\n \"self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height: ', self.height)\",\n \"elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image') masterTime =\",\n \"sizes # the two starting ranges, a planet, and the two prfs #\",\n \"the two starting ranges, a planet, and the two prfs # These provide\",\n \"self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at\",\n \"+ datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the\",\n \"h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop\",\n \"self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset\",\n \"= math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def\",\n \"copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by\",\n \"at which to compute baselines - \\\"all\\\" implies '+ 'top, middle, bottom of\",\n \"MInv = MM.invertMatrix(M) for i in range(size): for j in range(size): A[i] +=\",\n \"range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset\",\n \"the c, or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate\",\n \"self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts()\",\n \"self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb = [] hb =\",\n \"self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop\",\n \"last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i]\",\n \"between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the\",\n \"+ datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines at bottom of master image')\",\n \"self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc\",\n \"frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None\",\n \"and a slave time and a method that calls this method #TODO multiple\",\n \"__init__(self): self.x1 = [] self.x2 = [] self.x3 = [] # A class\",\n \"getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self):\",\n \"pixel sizes # the two starting ranges, a planet, and the two prfs\",\n \"* 3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame =\",\n \"None self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1 = None\",\n \"near start of master image, '+ '\\\"bottom\\\" implies at bottom of master image,\",\n \"implies near middle of master image. '+ 'To be used in case there\",\n \"method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save\",\n \"None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999\",\n \"import math import datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule\",\n \"return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return\",\n \"self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since the last baseline\",\n \"logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM from\",\n \"self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid()\",\n \"'top': print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() +\",\n \"self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc = verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset\",\n \"[0]*size A = [0]*size M = [[0 for i in range(size) ] for\",\n \"# Calculate the gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0\",\n \"baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] #\",\n \"to any 'EAR99' # embargoed foreign country or citizen of those countries. #\",\n \"or implied. # See the License for the specific language governing permissions and\",\n \"and regulations and has been classified as 'EAR99 NLR' # (No [Export] License\",\n \"baselines - \\\"all\\\" implies '+ 'top, middle, bottom of master image, '+ '\\\"top\\\"\",\n \"= None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset =\",\n \"first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def\",\n \"= 0.0 cosl = ((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius +\",\n \"float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range\",\n \"# A class to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis):\",\n \"and a method that calls this method #TODO multiple times to calculate the\",\n \"= None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset =\",\n \"lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self):\",\n \"[0]*size M = [[0 for i in range(size) ] for j in range(size)]\",\n \"cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\"\",\n \"import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class to hold\",\n \"[] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image\",\n \"= self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a new start\",\n \"retstr += \\\"Bulk Range Offset: %s\\\\n\\\" retlst += (self.orbSlcRangeOffset,) return retstr % retlst\",\n \"datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset)\",\n \"+ asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 -\",\n \"(self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset: %s\\\\n\\\" retlst += (self.orbSlcRangeOffset,) return retstr %\",\n \"vector perpendicular to the platform position and velocity, this is the c, or\",\n \"master time and a slave time and a method that calls this method\",\n \"= None self.masterFrame = None self.slaveFrame = None self.lookAngle = None self.rangePixelSize =\",\n \"for i in range(3): # Calculate the Baseline at the start of the\",\n \"support of a prohibited end use). By downloading this software, # the user\",\n \"vectors class Basis(object): def __init__(self): self.x1 = [] self.x2 = [] self.x3 =\",\n \"hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components by\",\n \"It looks like we really need two orbits, a time, range and azimuth\",\n \"= [] # A class to hold three-dimensional basis vectors for spacecraft baselines\",\n \"Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v =\",\n \"of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z =\",\n \"self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the baseline polynomial def\",\n \"def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def\",\n \"for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M)\",\n \"ranges, # satellite heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame)\",\n \"use this file except in compliance with the License. # You may obtain\",\n \"import Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector\",\n \"United States Government Sponsorship acknowledged. This software is subject to # U.S. export\",\n \"the difference between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) #\",\n \"multiple times to calculate the rate of baseline change over time. for port\",\n \"- datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime\",\n \"ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp()\",\n \"U.S. export control laws and regulations and has been classified as 'EAR99 NLR'\",\n \"None self.radius = None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None\",\n \"that is perpendicular to the cross-track direction and position basis = BaselineBasis() basis.setPositionVector(r)\",\n \"input vectors of same length.\\\") raise Exception if not (size == 3): print(\\\"Error.\",\n \"all applicable U.S. export laws and regulations. # The user has the responsibility\",\n \"exporting this software to any 'EAR99' # embargoed foreign country or citizen of\",\n \"getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self):\",\n \"getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self):\",\n \"around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() +\",\n \"downloading this software, # the user agrees to comply with all applicable U.S.\",\n \"for the specific language governing permissions and # limitations under the License. #\",\n \"+= \\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst\",\n \"slave time and a method that calls this method #TODO multiple times to\",\n \"setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c\",\n \"x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position\",\n \"vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline components\",\n \"- h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes\",\n \"not (size == 3): print(\\\"Error. Expecting input vectors of length 3.\\\") raise Exception\",\n \"the \\\"velocity\\\" component that is perpendicular to the cross-track direction and position basis\",\n \"[] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire\",\n \"really need two orbits, a time, range and azimuth pixel sizes # the\",\n \"'middle': print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0),\",\n \"lookVector = self.calculateLookVector() az_offset = [] vb = [] hb = [] csb\",\n \"[self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines\",\n \"'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of\",\n \"to hold three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self)\",\n \"= None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height =\",\n \"[self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=2.0)] elif self.baselineLocation.lower() == 'bottom': print('Estimating baselines\",\n \"setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius):\",\n \"pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var)\",\n \"z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of the difference\",\n \"velocity at the start of the scene self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis\",\n \"= None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc =\",\n \"an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either\",\n \"return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds +\",\n \"retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset:\",\n \"= [] vb = [] hb = [] csb = [] asb =\",\n \"None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None\",\n \"vectors of same length.\\\") raise Exception if not (size == 3): print(\\\"Error. Expecting\",\n \"return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return\",\n \"# A class to hold three-dimensional basis vectors class Basis(object): def __init__(self): self.x1\",\n \"= MM.norm(v) return normV # Given an orbit and a time, calculate an\",\n \"ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame =\",\n \"= None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc =\",\n \"] for j in range(size)] for j in range(size): for i in range(size):\",\n \"self.startingRange2 # Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size\",\n \"A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return\",\n \"slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) =\",\n \"# distributed under the License is distributed on an \\\"AS IS\\\" BASIS, #\",\n \"Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A\",\n \"from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class\",\n \"[] # A class to hold three-dimensional basis vectors for spacecraft baselines class\",\n \"of master image. '+ 'To be used in case there is a large\",\n \"embargoed country, # end user, or in support of a prohibited end use).\",\n \"def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return self.orbSlcAzimuthOffset def\",\n \"master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower()\",\n \"Given two position vectors and a basis, calculate the offset between the two\",\n \"method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the\",\n \"BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default = 'all', type=str, mandatory=False, doc =\",\n \"scene # First, get the position and velocity at the start of the\",\n \"parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle of the master frame def\",\n \"return self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return\",\n \"= None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None self.radius =\",\n \"Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,)\",\n \"the look vector of the master frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight\",\n \"midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame\",\n \"orbit and a time, calculate an orthogonal basis for cross-track and velocity directions\",\n \"Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset: %s\\\\n\\\" retlst\",\n \"#TODO frames when given a master time and a slave time and a\",\n \"with the License. # You may obtain a copy of the License at\",\n \"obtain export licenses, or other export # authority as may be required before\",\n \"self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop\",\n \"= {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables =\",\n \"datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime =\",\n \"return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time,\",\n \"# print('Radius: ', self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl\",\n \"((self.height-z)*(2*self.radius + self.height + z) + self.startingRange1*self.startingRange1)/( 2*self.startingRange1*(self.radius + self.height) ) # print('Height:\",\n \"x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the\",\n \"a the \\\"velocity\\\" component that is perpendicular to the cross-track direction and position\",\n \"\\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst +=\",\n \"law or agreed to in writing, software # distributed under the License is\",\n \"the velocity vector into a unit vector c = MM.crossProduct(r,v) # Calculate the\",\n \"frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None\",\n \"= orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) #\",\n \"self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg\",\n \"= [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location:\",\n \"country or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math\",\n \"# based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1\",\n \"and the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset #\",\n \"of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else:\",\n \"compute baselines - \\\"all\\\" implies '+ 'top, middle, bottom of master image, '+\",\n \"directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite')\",\n \"a unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the\",\n \"== 'middle': print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() -\",\n \"= None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate =\",\n \"= None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst =\",\n \"implies '+ 'top, middle, bottom of master image, '+ '\\\"top\\\" implies near start\",\n \"import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM\",\n \"# Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import\",\n \"v = MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\" component that is perpendicular to\",\n \"return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return\",\n \"in compliance with the License. # You may obtain a copy of the\",\n \"License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or\",\n \"v = MM.normalizeVector(v) # Turn the velocity vector into a unit vector c\",\n \"(No [Export] License Required except when exporting to an embargoed country, # end\",\n \"responsibility to obtain export licenses, or other export # authority as may be\",\n \"'EAR99' # embargoed foreign country or citizen of those countries. # # Author:\",\n \"s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite')\",\n \"BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\",\n \"self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom\",\n \"return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION =\",\n \"self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return\",\n \"a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required\",\n \"def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def\",\n \"if not (len(xRef) == len(yRef)): print(\\\"Error. Expecting input vectors of same length.\\\") raise\",\n \"self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 =\",\n \"return z_offset,v_offset,c_offset # Calculate the baseline components between two frames def baseline(self): #TODO\",\n \"method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with\",\n \"range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def\",\n \"# These provide the orbits # These provide the range and azimuth pixel\",\n \"basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1\",\n \"old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables =\",\n \"projection of the difference in position and the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector())\",\n \"= {} self.descriptionOfVariables = {} self.mandatoryVariables = [] self.optionalVariables = [] return None\",\n \"def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of\",\n \"cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft\",\n \"'all': print('Using entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif\",\n \"Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst +=\",\n \"j in range(size)] for j in range(size): for i in range(size): M[j][i] =\",\n \"range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def\",\n \"MM.normalizeVector(v) # Turn the velocity vector into a unit vector c = MM.crossProduct(r,v)\",\n \"ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height\",\n \"getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self):\",\n \"crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1]\",\n \"components between two frames def baseline(self): #TODO This could be further refactored into\",\n \"vectors of length 3.\\\") raise Exception Y = [0]*size A = [0]*size M\",\n \"or other export # authority as may be required before exporting this software\",\n \"# print('Height: ', self.height) # print('Radius: ', self.radius) # print('Range: ', self.startingRange1) #\",\n \"two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for\",\n \"MathModule as MM from isceobj.Orbit.Orbit import StateVector # A class to hold three-dimensional\",\n \"self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid)\",\n \"horizontal and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0])\",\n \"the specific language governing permissions and # limitations under the License. # #\",\n \"with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius\",\n \"= None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate =\",\n \"= 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the Look Angle\",\n \"a unit vector v = MM.normalizeVector(v) # Turn the velocity vector into a\",\n \"image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines\",\n \"same length.\\\") raise Exception if not (size == 3): print(\\\"Error. Expecting input vectors\",\n \"acknowledged. This software is subject to # U.S. export control laws and regulations\",\n \"method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) =\",\n \"a method that calls this method #TODO multiple times to calculate the rate\",\n \"retstr += \\\"Vertical Baseline: %s\\\\n\\\" retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\"\",\n \"[self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image') masterTime\",\n \"- vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1]\",\n \"def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds +\",\n \"sv.getPosition() v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into\",\n \"method #TODO multiple times to calculate the rate of baseline change over time.\",\n \"to calculate the rate of baseline change over time. for port in self.inputPorts:\",\n \"= (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate\",\n \"frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize\",\n \"= None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset =\",\n \"distributed under the License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT\",\n \"self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical baseline\",\n \"length 3.\\\") raise Exception Y = [0]*size A = [0]*size M = [[0\",\n \"= self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates\",\n \"-99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component\",\n \"lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master\",\n \"in range(3): # Calculate the Baseline at the start of the scene, mid-scene,\",\n \"two orbits, a time, range and azimuth pixel sizes # the two starting\",\n \"States Government Sponsorship acknowledged. This software is subject to # U.S. export control\",\n \"self).__init__(family=self.__class__.family, name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables =\",\n \"the projection of the difference in position and the \\\"velocity\\\" component v_offset =\",\n \"and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort)\",\n \"over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = []\",\n \"calculates the baseline between #TODO frames when given a master time and a\",\n \"vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate\",\n \"(self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr += \\\"Bulk Azimuth\",\n \"range(size) ] for j in range(size)] for j in range(size): for i in\",\n \"times to calculate the rate of baseline change over time. for port in\",\n \"(az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize)\",\n \"self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self): return\",\n \"end user, or in support of a prohibited end use). By downloading this\",\n \"None def createPorts(self): # Set input ports # It looks like we really\",\n \"this file except in compliance with the License. # You may obtain a\",\n \"Turn the position vector into a unit vector v = MM.normalizeVector(v) # Turn\",\n \"baseline components between two frames def baseline(self): #TODO This could be further refactored\",\n \"the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v\",\n \"s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of image for\",\n \"def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 =\",\n \"position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position\",\n \"is a large shift between images.') ) class Baseline(Component): family = 'baseline' logging_name\",\n \"is subject to # U.S. export control laws and regulations and has been\",\n \"By downloading this software, # the user agrees to comply with all applicable\",\n \"= [] self.x3 = [] # A class to hold three-dimensional basis vectors\",\n \"= [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline at the start\",\n \"that calls this method #TODO multiple times to calculate the rate of baseline\",\n \"= (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0]\",\n \"i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved since\",\n \"into a unit vector v = MM.normalizeVector(v) # Turn the velocity vector into\",\n \"baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\\\"Error.\",\n \"bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()]\",\n \"baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStart()\",\n \"= self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth\",\n \"None self.startingRange1 = None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None\",\n \"laws and regulations and has been classified as 'EAR99 NLR' # (No [Export]\",\n \"Y = [0]*size A = [0]*size M = [[0 for i in range(size)\",\n \"in range(size)] for j in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i)\",\n \"at bottom of master image, '+ '\\\"middle\\\" implies near middle of master image.\",\n \"asb_avg = (asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1\",\n \"self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate\",\n \"master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of\",\n \"self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop = None self.pBaselineBottom = None self.orbSlcAzimuthOffset\",\n \"datetime import logging from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as\",\n \"= slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the\",\n \"of master image, '+ '\\\"top\\\" implies near start of master image, '+ '\\\"bottom\\\"\",\n \"self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 - cosl*cosl) return [cosl,sinl] #\",\n \"== 'bottom': print('Estimating baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() -\",\n \"self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate\",\n \"crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg = (az_offset[0] +\",\n \"export control laws and regulations and has been classified as 'EAR99 NLR' #\",\n \"(size == 3): print(\\\"Error. Expecting input vectors of length 3.\\\") raise Exception Y\",\n \"end of the scene # First, get the position and velocity at the\",\n \"(len(xRef) == len(yRef)): print(\\\"Error. Expecting input vectors of same length.\\\") raise Exception if\",\n \"Calculate a the \\\"velocity\\\" component that is perpendicular to the cross-track direction and\",\n \"of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate\",\n \"there is a large shift between images.') ) class Baseline(Component): family = 'baseline'\",\n \"moved since the last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i]\",\n \"\\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr += \\\"Vertical Baseline:\",\n \"= slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2\",\n \"datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(), self.masterFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top\",\n \"az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) #\",\n \"retlst += (self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr\",\n \"# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to\",\n \"bottom of master image, '+ '\\\"top\\\" implies near start of master image, '+\",\n \"[[0 for i in range(size) ] for j in range(size)] for j in\",\n \"= None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None self.pBaselineTop =\",\n \"return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def getOrbSlcAzimuthOffset(self): return\",\n \"self.azimuthPixelSize = None self.height = None self.radius = None self.startingRange1 = None self.startingRange2\",\n \"that calculates the baseline between #TODO frames when given a master time and\",\n \"= x def getPositionVector(self): return self.x1 def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self):\",\n \"None self.lookAngle = None self.rangePixelSize = None self.azimuthPixelSize = None self.height = None\",\n \"frame def calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl =\",\n \"self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius\",\n \"position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate the length of the projection of\",\n \"None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc = None\",\n \"required by applicable law or agreed to in writing, software # distributed under\",\n \"= midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange()\",\n \"retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,) retstr += \\\"Vertical Baseline: %s\\\\n\\\"\",\n \"Angle of the master frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) #\",\n \"= pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height =\",\n \"Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] +\",\n \"since the last baseline point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] -\",\n \"asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate =\",\n \"the end of the scene # First, get the position and velocity at\",\n \"None self.height = None self.radius = None self.startingRange1 = None self.startingRange2 = None\",\n \"method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset)\",\n \"point if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1]\",\n \"baselines at bottom of master image') masterTime = [self.masterFrame.getSensingStop() - datetime.timedelta(seconds=2.0), self.masterFrame.getSensingStop() -\",\n \"10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf\",\n \"for j in range(size)] for j in range(size): for i in range(size): M[j][i]\",\n \"self.startingRange2 = range return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def\",\n \"a new start time relativeSlaveTime = slaveTime[i] - datetime.timedelta(seconds=(z_offset/normV)) slaveSV = self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite')\",\n \"frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid\",\n \"get the position and velocity at the start of the scene self.logger.info(\\\"Sampling time\",\n \"in self.inputPorts: port() lookVector = self.calculateLookVector() az_offset = [] vb = [] hb\",\n \"None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle = None\",\n \"master image. '+ 'To be used in case there is a large shift\",\n \"= [] s = [0.,0.,0.] if self.baselineLocation.lower() == 'all': print('Using entire span of\",\n \"U.S. export laws and regulations. # The user has the responsibility to obtain\",\n \"You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #\",\n \"== 3): print(\\\"Error. Expecting input vectors of length 3.\\\") raise Exception Y =\",\n \"return None def __str__(self): retstr = \\\"Initial Baseline estimates \\\\n\\\" retstr += \\\"Cross-track\",\n \"has been classified as 'EAR99 NLR' # (No [Export] License Required except when\",\n \"None def __str__(self): retstr = \\\"Initial Baseline estimates \\\\n\\\" retstr += \\\"Cross-track Baseline:\",\n \"the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity()\",\n \"self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 -\",\n \"__init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self): return self.x1 def setVelocityVector(self,v):\",\n \"_timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 * 3600) * 10**6)\",\n \"self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): #\",\n \"= MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\" component that is\",\n \"c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name = 'BASELINE_LOCATION', default =\",\n \"at the start of the scene, mid-scene, and the end of the scene\",\n \"= s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite') slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1\",\n \"c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform position and\",\n \"setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range):\",\n \"baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of\",\n \"self.calculateLookVector() az_offset = [] vb = [] hb = [] csb = []\",\n \"datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for i in range(3): # Calculate the Baseline\",\n \"= None self.rangeOffset = None self.phaseConst = -99999 super(Baseline, self).__init__(family=self.__class__.family, name=name) self.logger =\",\n \"an orbit and a time, calculate an orthogonal basis for cross-track and velocity\",\n \"[] hb = [] csb = [] asb = [] s = [0.,0.,0.]\",\n \"self.rangeOffset def getPhaseConst(self): return self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds\",\n \"getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self):\",\n \"self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to the baseline\",\n \"def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf =\",\n \"crossTrackBaselinePolynomialCoefficients = self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross\",\n \"This software is subject to # U.S. export control laws and regulations and\",\n \"# First, get the position and velocity at the start of the scene\",\n \"RESERVED. # # Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); #\",\n \"# embargoed foreign country or citizen of those countries. # # Author: <NAME>\",\n \"= crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range offsets azb_avg = (az_offset[0]\",\n \"return (td.microseconds + (td.seconds + td.days * 24.0 * 3600) * 10**6) /\",\n \"images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,)\",\n \"# you may not use this file except in compliance with the License.\",\n \"in range(len(x1))] # Calculate the difference between the master and slave position vectors\",\n \"return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 *\",\n \"in range(size): for i in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv\",\n \"def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def\",\n \"[] return None def createPorts(self): # Set input ports # It looks like\",\n \"else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid()\",\n \"azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0] +\",\n \"governing permissions and # limitations under the License. # # United States Government\",\n \"self.polynomialFit(s,hb) verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and\",\n \"#UAVSAR frame creates ellipsoid with peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except:\",\n \"= frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit =\",\n \"be required before exporting this software to any 'EAR99' # embargoed foreign country\",\n \"def setVelocityVector(self,v): self.x2 = v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 =\",\n \"def getVBaselineAcc(self): return self.vBaselineAcc def getPBaselineTop(self): return self.pBaselineTop def getPBaselineBottom(self): return self.pBaselineBottom def\",\n \"authority as may be required before exporting this software to any 'EAR99' #\",\n \"setRadius(self,radius): self.radius = radius return def setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range):\",\n \"Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr = \\\"Initial\",\n \"before exporting this software to any 'EAR99' # embargoed foreign country or citizen\",\n \"self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop = None self.vBaselineRate = None self.vBaselineAcc\",\n \"been classified as 'EAR99 NLR' # (No [Export] License Required except when exporting\",\n \"StateVector # A class to hold three-dimensional basis vectors class Basis(object): def __init__(self):\",\n \"and the two prfs # These provide the orbits # These provide the\",\n \"= MM.normalizeVector(x1) # Turn the position vector into a unit vector v =\",\n \"frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit()\",\n \"further refactored into a method that calculates the baseline between #TODO frames when\",\n \"software, # the user agrees to comply with all applicable U.S. export laws\",\n \"doc = ('Location at which to compute baselines - \\\"all\\\" implies '+ 'top,\",\n \"self.radius) # print('Range: ', self.startingRange1) # print('COSL: ', cosl) sinl = math.sqrt(1 -\",\n \"self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate\",\n \"License for the specific language governing permissions and # limitations under the License.\",\n \"self.logger.info(\\\"Sampling time %s\\\" % i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate\",\n \"the distance moved since the last baseline point if (i > 0): deltaT\",\n \"# Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2]\",\n \"azimuth pixel sizes # the two starting ranges, a planet, and the two\",\n \"\\\"License\\\"); # you may not use this file except in compliance with the\",\n \"obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless\",\n \"Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)]\",\n \"= verticalBaselinePolynomialCoefficients[2] self.pBaselineTop = csb[0] self.pBaselineBottom = csb[-1] self.orbSlcAzimuthOffset = az_offset self.orbSlcRangeOffset =\",\n \"* 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject()\",\n \"vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 =\",\n \"language governing permissions and # limitations under the License. # # United States\",\n \"== 'top': print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart()\",\n \"+ datetime.timedelta(seconds=1.0)] elif self.baselineLocation.lower() == 'top': print('Estimating baselines at top of master image')\",\n \"# Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0]\",\n \"import StateVector # A class to hold three-dimensional basis vectors class Basis(object): def\",\n \"# Turn the position vector into a unit vector v = MM.normalizeVector(v) #\",\n \"Exception Y = [0]*size A = [0]*size M = [[0 for i in\",\n \"addMasterFrame(self): frame = self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency()\",\n \"of baseline change over time. for port in self.inputPorts: port() lookVector = self.calculateLookVector()\",\n \"from iscesys.Component.Component import Component, Port from isceobj.Util.mathModule import MathModule as MM from isceobj.Orbit.Orbit\",\n \"gross azimuth and range offsets azb_avg = (az_offset[0] + az_offset[-1])/2.0 asb_avg = (asb[0]\",\n \"times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort)\",\n \"http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing,\",\n \"in writing, software # distributed under the License is distributed on an \\\"AS\",\n \"These provide the orbits # These provide the range and azimuth pixel sizes,\",\n \"# United States Government Sponsorship acknowledged. This software is subject to # U.S.\",\n \"M = [[0 for i in range(size) ] for j in range(size)] for\",\n \"return basis # Given two position vectors and a basis, calculate the offset\",\n \"prohibited end use). By downloading this software, # the user agrees to comply\",\n \"frames when given a master time and a slave time and a method\",\n \"user agrees to comply with all applicable U.S. export laws and regulations. #\",\n \"difference between the master and slave position vectors z_offset = MM.dotProduct(dx,basis.getVelocityVector()) # Calculate\",\n \"def setHeight(self,var): self.height = float(var) return def setRadius(self,radius): self.radius = radius return def\",\n \"prfs # These provide the orbits # These provide the range and azimuth\",\n \"peg self.radius = ellipsoid.pegRadCur self.height = frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius =\",\n \"Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import Component,\",\n \"(BASELINE_LOCATION,) # Calculate the Look Angle of the master frame def calculateLookAngle(self): lookVector\",\n \"agrees to comply with all applicable U.S. export laws and regulations. # The\",\n \"the horizontal and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] -\",\n \"or cross-track vector c = MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the\",\n \"MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\" component that is perpendicular to the cross-track\",\n \"(z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) az_offset.append(z_offset) # Save the position offset # Calculate a new\",\n \"print('Estimating baselines around center of master image') masterTime = [self.masterFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingMid(),\",\n \"def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height = float(var) return def\",\n \"Sponsorship acknowledged. This software is subject to # U.S. export control laws and\",\n \"This could be further refactored into a method that calculates the baseline between\",\n \"sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit and a time,\",\n \"(z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and\",\n \"return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector of the master frame def calculateLookVector(self):\",\n \"baseline(self): #TODO This could be further refactored into a method that calculates the\",\n \"Turn the velocity vector into a unit vector c = MM.crossProduct(r,v) # Calculate\",\n \"limitations under the License. # # United States Government Sponsorship acknowledged. This software\",\n \"three-dimensional basis vectors for spacecraft baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x):\",\n \"for i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A\",\n \"position and velocity, this is the c, or cross-track vector c = MM.normalizeVector(c)\",\n \"self.hBaselineAcc def getVBaselineTop(self): return self.vBaselineTop def getVBaselineRate(self): return self.vBaselineRate def getVBaselineAcc(self): return self.vBaselineAcc\",\n \"# The user has the responsibility to obtain export licenses, or other export\",\n \"= self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV = self.masterOrbit.interpolateOrbit(masterTime[i], method='hermite')\",\n \"2.0 (the \\\"License\\\"); # you may not use this file except in compliance\",\n \"country, # end user, or in support of a prohibited end use). By\",\n \"__init__(self, name=''): self.masterOrbit = None self.slaveOrbit = None self.masterFrame = None self.slaveFrame =\",\n \"WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the\",\n \"vector into a unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular\",\n \"calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in range(len(x1))] # Calculate the\",\n \"orbits, a time, range and azimuth pixel sizes # the two starting ranges,\",\n \"= \\\"Initial Baseline estimates \\\\n\\\" retstr += \\\"Cross-track Baseline: %s\\\\n\\\" retlst = (self.hBaselineTop,)\",\n \"self.x2 = [] self.x3 = [] # A class to hold three-dimensional basis\",\n \"'\\\"bottom\\\" implies at bottom of master image, '+ '\\\"middle\\\" implies near middle of\",\n \"# Given an orbit and a time, calculate an orthogonal basis for cross-track\",\n \"# # Unless required by applicable law or agreed to in writing, software\",\n \"calculate the rate of baseline change over time. for port in self.inputPorts: port()\",\n \"express or implied. # See the License for the specific language governing permissions\",\n \"MM.normalizeVector(c) v = MM.crossProduct(c,r) # Calculate a the \\\"velocity\\\" component that is perpendicular\",\n \"looks like we really need two orbits, a time, range and azimuth pixel\",\n \"vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1] - vb[i]*lookVector[0]) #Calculating baseline\",\n \"= crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop = verticalBaselinePolynomialCoefficients[0] self.vBaselineRate = verticalBaselinePolynomialCoefficients[1] self.vBaselineAcc =\",\n \"direction and position basis = BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given\",\n \"self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid = frame._ellipsoid #UAVSAR frame creates ellipsoid\",\n \"r_offset = (self.startingRange1 - self.startingRange2 - asb_avg)/(self.rangePixelSize) # Populate class attributes self.hBaselineTop =\",\n \"unit vector c = MM.crossProduct(r,v) # Calculate the vector perpendicular to the platform\",\n \"frame def calculateLookAngle(self): lookVector = self.calculateLookVector() return math.degrees(math.atan2(lookVector[1],lookVector[0])) # Calculate the look vector\",\n \"either express or implied. # See the License for the specific language governing\",\n \"self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days * 24.0 * 3600)\",\n \"given a master time and a slave time and a method that calls\",\n \"A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize):\",\n \"satellite heights and times for the first lines masterFramePort = Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort =\",\n \"MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between two frames def baseline(self):\",\n \"= self.calculateLookVector() az_offset = [] vb = [] hb = [] csb =\",\n \"# Calculate the difference between the master and slave position vectors z_offset =\",\n \"v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components\",\n \"retlst += (self.orbSlcAzimuthOffset,) retstr += \\\"Bulk Range Offset: %s\\\\n\\\" retlst += (self.orbSlcRangeOffset,) return\",\n \"self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None self.phaseConst = -99999 super(Baseline,\",\n \"i in range(3): # Calculate the Baseline at the start of the scene,\",\n \"the License. # You may obtain a copy of the License at #\",\n \"in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize):\",\n \"self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(),\",\n \"self._inputPorts.getPort(name='masterFrame').getObject() self.masterFrame = frame self.startingRange1 = frame.getStartingRange() prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize()\",\n \"NLR' # (No [Export] License Required except when exporting to an embargoed country,\",\n \"= frame.platformHeight except: ellipsoid = frame.getInstrument().getPlatform().getPlanet().get_elp() self.radius = ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def\",\n \"j in range(size): A[i] += MInv[i][j]*Y[j] return A def setRangePixelSize(self,pixelSize): self.rangePixelSize = pixelSize\",\n \"an embargoed country, # end user, or in support of a prohibited end\",\n \"self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None self.vBaselineTop\",\n \"v = sv.getVelocity() r = MM.normalizeVector(x1) # Turn the position vector into a\",\n \"the range and azimuth pixel sizes, starting ranges, # satellite heights and times\",\n \"> 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] + deltaT*normV masterSV\",\n \"self.startingRange2 = frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit\",\n \"# authority as may be required before exporting this software to any 'EAR99'\",\n \"the rate of baseline change over time. for port in self.inputPorts: port() lookVector\",\n \"name=name) self.logger = logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {}\",\n \"(asb[0] + asb[-1])/2.0 az_offset = (-azb_avg - h_rate*self.startingRange1*lookVector[1])/(self.azimuthPixelSize) r_offset = (self.startingRange1 - self.startingRange2\",\n \"# end user, or in support of a prohibited end use). By downloading\",\n \"# # Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you\",\n \"Populate class attributes self.hBaselineTop = crossTrackBaselinePolynomialCoefficients[0] self.hBaselineRate = crossTrackBaselinePolynomialCoefficients[1] self.hBaselineAcc = crossTrackBaselinePolynomialCoefficients[2] self.vBaselineTop\",\n \"<NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging from iscesys.Component.Component import Component, Port\",\n \"slaveSV = self.slaveOrbit.interpolateOrbit(slaveTime[i], method='hermite') x1 = masterSV.getPosition() x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis)\",\n \"the vector perpendicular to the platform position and velocity, this is the c,\",\n \"pixel sizes, starting ranges, # satellite heights and times for the first lines\",\n \"= None self.slaveOrbit = None self.masterFrame = None self.slaveFrame = None self.lookAngle =\",\n \"of length 3.\\\") raise Exception Y = [0]*size A = [0]*size M =\",\n \"# limitations under the License. # # United States Government Sponsorship acknowledged. This\",\n \"two starting ranges, a planet, and the two prfs # These provide the\",\n \"software to any 'EAR99' # embargoed foreign country or citizen of those countries.\",\n \"the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables = {} self.descriptionOfVariables = {} self.mandatoryVariables\",\n \"= MM.invertMatrix(M) for i in range(size): for j in range(size): A[i] += MInv[i][j]*Y[j]\",\n \"in case there is a large shift between images.') ) class Baseline(Component): family\",\n \"basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and a basis, calculate\",\n \"= MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset # Calculate the baseline components between\",\n \"Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0\",\n \"# Turn the velocity vector into a unit vector c = MM.crossProduct(r,v) #\",\n \"difference in position and the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector())\",\n \"prf = frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite')\",\n \"<gh_stars>1-10 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. #\",\n \"polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if not (len(xRef) == len(yRef)): print(\\\"Error. Expecting\",\n \"= ellipsoid.get_a() self.height = midSV.calculateHeight(ellipsoid) def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame\",\n \"frames def baseline(self): #TODO This could be further refactored into a method that\",\n \"between images.') ) class Baseline(Component): family = 'baseline' logging_name = 'isce.mroipac.baseline' parameter_list =\",\n \"= frame.getStartingRange() self.slaveOrbit = frame.getOrbit() def __init__(self, name=''): self.masterOrbit = None self.slaveOrbit =\",\n \"at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed\",\n \"case there is a large shift between images.') ) class Baseline(Component): family =\",\n \"position and the \\\"velocity\\\" component v_offset = MM.dotProduct(dx,basis.getPositionVector()) c_offset = MM.dotProduct(dx,basis.getCrossTrackVector()) return z_offset,v_offset,c_offset\",\n \"velocity, this is the c, or cross-track vector c = MM.normalizeVector(c) v =\",\n \"self.mandatoryVariables = [] self.optionalVariables = [] return None def createPorts(self): # Set input\",\n \"math.sqrt(1 - cosl*cosl) return [cosl,sinl] # Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time):\",\n \"'EAR99 NLR' # (No [Export] License Required except when exporting to an embargoed\",\n \"those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import logging\",\n \"implies at bottom of master image, '+ '\\\"middle\\\" implies near middle of master\",\n \"on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition()\",\n \"calculateLookVector(self): try: z = self.masterFrame.terrainHeight except: z = 0.0 cosl = ((self.height-z)*(2*self.radius +\",\n \"# Save the position offset # Calculate a new start time relativeSlaveTime =\",\n \"def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') x1 = sv.getPosition() v = sv.getVelocity() r\",\n \"i in range(size) ] for j in range(size)] for j in range(size): for\",\n \"verticalBaselinePolynomialCoefficients = self.polynomialFit(s,vb) h_rate = crossTrackBaselinePolynomialCoefficients[1] # Calculate the gross azimuth and range\",\n \"of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import math import datetime import\",\n \"= r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic fit to\",\n \"self.orbSlcAzimuthOffset def getOrbSlcRangeOffset(self): return self.orbSlcRangeOffset def getRangeOffset(self): return self.rangeOffset def getPhaseConst(self): return self.phaseConst\",\n \"self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize = midSV.getScalarVelocity()/prf try: ellipsoid =\",\n \"the orbits # These provide the range and azimuth pixel sizes, starting ranges,\",\n \"exporting to an embargoed country, # end user, or in support of a\",\n \"for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around\",\n \"a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef): size = len(xRef) if\",\n \"# Multiply the horizontal and vertical baseline components by the look angle vector\",\n \"BaselineBasis() basis.setPositionVector(r) basis.setVelocityVector(v) basis.setCrossTrackVector(c) return basis # Given two position vectors and a\",\n \"orthogonal basis for cross-track and velocity directions # based on the spacecraft position\",\n \"self.masterFrame.getSensingStop() - datetime.timedelta(seconds=1.0), self.masterFrame.getSensingStop()] else: raise Exception('Unknown baseline location: {0}'.format(self.baselineLocation)) slaveTime = [self.slaveFrame.getSensingMid()\",\n \"and a time, calculate an orthogonal basis for cross-track and velocity directions #\",\n \"% i) masterBasis = self.calculateBasis(self.masterOrbit,masterTime[i]) normV = self.calculateScalarVelocity(self.masterOrbit,masterTime[i]) # Calculate the distance moved\",\n \"+= (self.pBaselineTop,) retstr += \\\"Bulk Azimuth Offset: %s\\\\n\\\" retlst += (self.orbSlcAzimuthOffset,) retstr +=\",\n \"len(xRef) if not (len(xRef) == len(yRef)): print(\\\"Error. Expecting input vectors of same length.\\\")\",\n \"None self.startingRange2 = None self.hBaselineTop = None self.hBaselineRate = None self.hBaselineAcc = None\",\n \"if (i > 0): deltaT = self._timeDeltaToSeconds(masterTime[i] - masterTime[0]) s[i] = s[i-1] +\",\n \"in range(size): M[j][i] = math.pow(xRef[j],i) Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i\",\n \"None self.pBaselineBottom = None self.orbSlcAzimuthOffset = None self.orbSlcRangeOffset = None self.rangeOffset = None\",\n \"'To be used in case there is a large shift between images.') )\",\n \"self.slaveOrbit.interpolateOrbit(relativeSlaveTime, method='hermite') # Recalculate the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset)\",\n \"except in compliance with the License. # You may obtain a copy of\",\n \"the offsets x2 = slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1])\",\n \"az_offset self.orbSlcRangeOffset = r_offset self.rangeOffset = self.startingRange1 - self.startingRange2 # Calculate a quadratic\",\n \"= logging.getLogger('isce.mroipac.baseline') self.createPorts() # Satisfy the old Component self.dictionaryOfOutputVariables = {} self.dictionaryOfVariables =\",\n \"return def getHBaselineTop(self): return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc\",\n \"setMasterStartingRange(self,range): self.startingRange1 = range return def setSlaveStartingRange(self,range): self.startingRange2 = range return def getHBaselineTop(self):\",\n \"starting ranges, # satellite heights and times for the first lines masterFramePort =\",\n \"embargoed foreign country or citizen of those countries. # # Author: <NAME> #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\",\n \"= [] self.optionalVariables = [] return None def createPorts(self): # Set input ports\",\n \"self.rangePixelSize = pixelSize return def setAzimuthPixelSize(self,pixelSize): self.azimuthPixelSize = pixelSize return def setHeight(self,var): self.height\",\n \"velocity directions # based on the spacecraft position def calculateBasis(self,orbit,time): sv = orbit.interpolateOrbit(time,\",\n \"may not use this file except in compliance with the License. # You\",\n \"License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS\",\n \"License. # # United States Government Sponsorship acknowledged. This software is subject to\",\n \"= Port(name='masterFrame',method=self.addMasterFrame) slaveFramePort = Port(name='slaveFrame',method=self.addSlaveFrame) self._inputPorts.add(masterFramePort) self._inputPorts.add(slaveFramePort) return None def __str__(self): retstr =\",\n \"+ td.days * 24.0 * 3600) * 10**6) / 10**6 def addMasterFrame(self): frame\",\n \"return self.hBaselineTop def getHBaselineRate(self): return self.hBaselineRate def getHBaselineAcc(self): return self.hBaselineAcc def getVBaselineTop(self): return\",\n \"= v def getVelocityVector(self): return self.x2 def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self):\",\n \"time, calculate an orthogonal basis for cross-track and velocity directions # based on\",\n \"may be required before exporting this software to any 'EAR99' # embargoed foreign\",\n \"baselines class BaselineBasis(Basis): def __init__(self): Basis.__init__(self) def setPositionVector(self,x): self.x1 = x def getPositionVector(self):\",\n \"self.phaseConst def getLookAngle(self): return self.lookAngle def _timeDeltaToSeconds(self,td): return (td.microseconds + (td.seconds + td.days\",\n \"rate of baseline change over time. for port in self.inputPorts: port() lookVector =\",\n \"- self.startingRange2 # Calculate a quadratic fit to the baseline polynomial def polynomialFit(self,xRef,yRef):\",\n \"mandatory=False, doc = ('Location at which to compute baselines - \\\"all\\\" implies '+\",\n \"= [self.slaveFrame.getSensingMid() - datetime.timedelta(seconds=1.0), self.slaveFrame.getSensingMid(), self.slaveFrame.getSensingMid() + datetime.timedelta(seconds=1.0)] # slaveTime = [self.slaveFrame.getSensingStart(),self.slaveFrame.getSensingMid(),self.slaveFrame.getSensingStop()] for\",\n \"has the responsibility to obtain export licenses, or other export # authority as\",\n \"print('Using entire span of image for estimating baselines') masterTime = [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower()\",\n \"orbit.interpolateOrbit(time, method='hermite') v = sv.getVelocity() normV = MM.norm(v) return normV # Given an\",\n \"[] csb = [] asb = [] s = [0.,0.,0.] if self.baselineLocation.lower() ==\",\n \"= [self.masterFrame.getSensingStart(),self.masterFrame.getSensingMid(),self.masterFrame.getSensingStop()] elif self.baselineLocation.lower() == 'middle': print('Estimating baselines around center of master image')\",\n \"# Calculate the scalar spacecraft velocity def calculateScalarVelocity(self,orbit,time): sv = orbit.interpolateOrbit(time, method='hermite') v\",\n \"in range(size) ] for j in range(size)] for j in range(size): for i\",\n \"offset between the two positions in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j]\",\n \"= sv.getVelocity() normV = MM.norm(v) return normV # Given an orbit and a\",\n \"frame.getInstrument().getPulseRepetitionFrequency() self.rangePixelSize = frame.getInstrument().getRangePixelSize() self.masterOrbit = frame.getOrbit() midSV = self.masterOrbit.interpolateOrbit(frame.getSensingMid(), method='hermite') self.azimuthPixelSize =\",\n \"Multiply the horizontal and vertical baseline components by the look angle vector asb.append(-hb[i]*lookVector[1]\",\n \"def addSlaveFrame(self): frame = self._inputPorts.getPort(name='slaveFrame').getObject() self.slaveFrame = frame self.startingRange2 = frame.getStartingRange() self.slaveOrbit =\",\n \"print('Estimating baselines at top of master image') masterTime = [self.masterFrame.getSensingStart(), self.masterFrame.getSensingStart() + datetime.timedelta(seconds=1.0),\",\n \"input vectors of length 3.\\\") raise Exception Y = [0]*size A = [0]*size\",\n \"%s\\\\n\\\" retlst += (self.vBaselineTop,) retstr += \\\"Perpendicular Baseline: %s\\\\n\\\" retlst += (self.pBaselineTop,) retstr\",\n \"to # U.S. export control laws and regulations and has been classified as\",\n \"not (len(xRef) == len(yRef)): print(\\\"Error. Expecting input vectors of same length.\\\") raise Exception\",\n \"= self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal and vertical\",\n \"def setCrossTrackVector(self,c): self.x3 = c def getCrossTrackVector(self): return self.x3 BASELINE_LOCATION = Component.Parameter('baselineLocation', public_name\",\n \"slaveSV.getPosition() (z_offset,v_offset,c_offset) = self.calculateBasisOffset(x1,x2,masterBasis) vb.append(v_offset) hb.append(c_offset) csb.append(-hb[i]*lookVector[0] + vb[i]*lookVector[1]) # Multiply the horizontal\"\n]","isConversational":false}}},{"rowIdx":77,"cells":{"ngram":{"kind":"list like","value":["range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK:","cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return","seed the static deck with the list of unique card integers. Each object","for i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def","__init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def","__str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the","def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck","def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards)","the standard 52 card deck for rank in Card.STR_RANKS: for suit, val in","Card class Deck: \"\"\" Class representing a deck. The first time we create,","== 1: return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return","create the standard 52 card deck for rank in Card.STR_RANKS: for suit, val","random import shuffle as rshuffle from .card import Card class Deck: \"\"\" Class","return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard","n=1): if n == 1: return self.cards.pop(0) cards = [] for i in","# and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n","simply makes a copy of this object and shuffles it. \"\"\" _FULL_DECK =","= Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0) cards","of unique card integers. Each object instantiated simply makes a copy of this","card integers. Each object instantiated simply makes a copy of this object and","if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck for rank","cards = [] for i in range(n): cards.append(self.draw()) return cards def __str__(self): return","\"\"\" Class representing a deck. The first time we create, we seed the","draw(self, n=1): if n == 1: return self.cards.pop(0) cards = [] for i","shuffles it. \"\"\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and","Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52","from .card import Card class Deck: \"\"\" Class representing a deck. The first","\"\"\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle","shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if","we seed the static deck with the list of unique card integers. Each","with the list of unique card integers. Each object instantiated simply makes a","list of unique card integers. Each object instantiated simply makes a copy of","the static deck with the list of unique card integers. Each object instantiated","for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank + suit)) return","shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return","self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return cards def __str__(self):","the list of unique card integers. Each object instantiated simply makes a copy","static deck with the list of unique card integers. Each object instantiated simply","GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck for","<filename>src/modules/deuces/deck.py from random import shuffle as rshuffle from .card import Card class Deck:","first time we create, we seed the static deck with the list of","rshuffle from .card import Card class Deck: \"\"\" Class representing a deck. The","rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0) cards = []","@staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card","and shuffles it. \"\"\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): #","list(Deck._FULL_DECK) # create the standard 52 card deck for rank in Card.STR_RANKS: for","card deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank +","object and shuffles it. \"\"\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self):","return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK)","integers. Each object instantiated simply makes a copy of this object and shuffles",".card import Card class Deck: \"\"\" Class representing a deck. The first time","copy of this object and shuffles it. \"\"\" _FULL_DECK = [] def __init__(self):","= [] for i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards)","import shuffle as rshuffle from .card import Card class Deck: \"\"\" Class representing","then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1:","n == 1: return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw())","if n == 1: return self.cards.pop(0) cards = [] for i in range(n):","time we create, we seed the static deck with the list of unique","= [] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards =","of this object and shuffles it. \"\"\" _FULL_DECK = [] def __init__(self): self.shuffle()","cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) #","unique card integers. Each object instantiated simply makes a copy of this object","[] for i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod","we create, we seed the static deck with the list of unique card","i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck():","_FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards","1: return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return cards","create, we seed the static deck with the list of unique card integers.","[] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck()","and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n ==","return list(Deck._FULL_DECK) # create the standard 52 card deck for rank in Card.STR_RANKS:","a deck. The first time we create, we seed the static deck with","self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0)","instantiated simply makes a copy of this object and shuffles it. \"\"\" _FULL_DECK","self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self,","# create the standard 52 card deck for rank in Card.STR_RANKS: for suit,","Class representing a deck. The first time we create, we seed the static","return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return cards def","it. \"\"\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and then","def draw(self, n=1): if n == 1: return self.cards.pop(0) cards = [] for","Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck for rank in","representing a deck. The first time we create, we seed the static deck","Each object instantiated simply makes a copy of this object and shuffles it.","Deck: \"\"\" Class representing a deck. The first time we create, we seed","deck. The first time we create, we seed the static deck with the","shuffle as rshuffle from .card import Card class Deck: \"\"\" Class representing a","a copy of this object and shuffles it. \"\"\" _FULL_DECK = [] def","in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if","def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create","object instantiated simply makes a copy of this object and shuffles it. \"\"\"","from random import shuffle as rshuffle from .card import Card class Deck: \"\"\"","Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0) cards =","this object and shuffles it. \"\"\" _FULL_DECK = [] def __init__(self): self.shuffle() def","standard 52 card deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items():","The first time we create, we seed the static deck with the list","as rshuffle from .card import Card class Deck: \"\"\" Class representing a deck.","class Deck: \"\"\" Class representing a deck. The first time we create, we","52 card deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank","def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1):","import Card class Deck: \"\"\" Class representing a deck. The first time we","deck with the list of unique card integers. Each object instantiated simply makes","deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank + suit))","rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank + suit)) return list(Deck._FULL_DECK)","makes a copy of this object and shuffles it. \"\"\" _FULL_DECK = []"],"string":"[\n \"range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK:\",\n \"cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return\",\n \"seed the static deck with the list of unique card integers. Each object\",\n \"for i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def\",\n \"__init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def\",\n \"__str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the\",\n \"def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck\",\n \"def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards)\",\n \"the standard 52 card deck for rank in Card.STR_RANKS: for suit, val in\",\n \"Card class Deck: \\\"\\\"\\\" Class representing a deck. The first time we create,\",\n \"== 1: return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return\",\n \"create the standard 52 card deck for rank in Card.STR_RANKS: for suit, val\",\n \"random import shuffle as rshuffle from .card import Card class Deck: \\\"\\\"\\\" Class\",\n \"return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard\",\n \"n=1): if n == 1: return self.cards.pop(0) cards = [] for i in\",\n \"# and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n\",\n \"simply makes a copy of this object and shuffles it. \\\"\\\"\\\" _FULL_DECK =\",\n \"= Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0) cards\",\n \"of unique card integers. Each object instantiated simply makes a copy of this\",\n \"card integers. Each object instantiated simply makes a copy of this object and\",\n \"if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck for rank\",\n \"cards = [] for i in range(n): cards.append(self.draw()) return cards def __str__(self): return\",\n \"\\\"\\\"\\\" Class representing a deck. The first time we create, we seed the\",\n \"draw(self, n=1): if n == 1: return self.cards.pop(0) cards = [] for i\",\n \"shuffles it. \\\"\\\"\\\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and\",\n \"Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52\",\n \"from .card import Card class Deck: \\\"\\\"\\\" Class representing a deck. The first\",\n \"\\\"\\\"\\\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle\",\n \"shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if\",\n \"we seed the static deck with the list of unique card integers. Each\",\n \"with the list of unique card integers. Each object instantiated simply makes a\",\n \"list of unique card integers. Each object instantiated simply makes a copy of\",\n \"the static deck with the list of unique card integers. Each object instantiated\",\n \"for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank + suit)) return\",\n \"shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return\",\n \"self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return cards def __str__(self):\",\n \"the list of unique card integers. Each object instantiated simply makes a copy\",\n \"static deck with the list of unique card integers. Each object instantiated simply\",\n \"GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck for\",\n \"<filename>src/modules/deuces/deck.py from random import shuffle as rshuffle from .card import Card class Deck:\",\n \"first time we create, we seed the static deck with the list of\",\n \"rshuffle from .card import Card class Deck: \\\"\\\"\\\" Class representing a deck. The\",\n \"rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0) cards = []\",\n \"@staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card\",\n \"and shuffles it. \\\"\\\"\\\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): #\",\n \"list(Deck._FULL_DECK) # create the standard 52 card deck for rank in Card.STR_RANKS: for\",\n \"card deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank +\",\n \"object and shuffles it. \\\"\\\"\\\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self):\",\n \"return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK)\",\n \"integers. Each object instantiated simply makes a copy of this object and shuffles\",\n \".card import Card class Deck: \\\"\\\"\\\" Class representing a deck. The first time\",\n \"copy of this object and shuffles it. \\\"\\\"\\\" _FULL_DECK = [] def __init__(self):\",\n \"= [] for i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards)\",\n \"import shuffle as rshuffle from .card import Card class Deck: \\\"\\\"\\\" Class representing\",\n \"then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1:\",\n \"n == 1: return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw())\",\n \"if n == 1: return self.cards.pop(0) cards = [] for i in range(n):\",\n \"time we create, we seed the static deck with the list of unique\",\n \"= [] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards =\",\n \"of this object and shuffles it. \\\"\\\"\\\" _FULL_DECK = [] def __init__(self): self.shuffle()\",\n \"cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) #\",\n \"unique card integers. Each object instantiated simply makes a copy of this object\",\n \"[] for i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod\",\n \"we create, we seed the static deck with the list of unique card\",\n \"i in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck():\",\n \"_FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards\",\n \"1: return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return cards\",\n \"create, we seed the static deck with the list of unique card integers.\",\n \"[] def __init__(self): self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck()\",\n \"and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n ==\",\n \"return list(Deck._FULL_DECK) # create the standard 52 card deck for rank in Card.STR_RANKS:\",\n \"a deck. The first time we create, we seed the static deck with\",\n \"self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0)\",\n \"instantiated simply makes a copy of this object and shuffles it. \\\"\\\"\\\" _FULL_DECK\",\n \"self.shuffle() def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self,\",\n \"# create the standard 52 card deck for rank in Card.STR_RANKS: for suit,\",\n \"Class representing a deck. The first time we create, we seed the static\",\n \"return self.cards.pop(0) cards = [] for i in range(n): cards.append(self.draw()) return cards def\",\n \"it. \\\"\\\"\\\" _FULL_DECK = [] def __init__(self): self.shuffle() def shuffle(self): # and then\",\n \"def draw(self, n=1): if n == 1: return self.cards.pop(0) cards = [] for\",\n \"Deck._FULL_DECK: return list(Deck._FULL_DECK) # create the standard 52 card deck for rank in\",\n \"representing a deck. The first time we create, we seed the static deck\",\n \"Each object instantiated simply makes a copy of this object and shuffles it.\",\n \"Deck: \\\"\\\"\\\" Class representing a deck. The first time we create, we seed\",\n \"deck. The first time we create, we seed the static deck with the\",\n \"shuffle as rshuffle from .card import Card class Deck: \\\"\\\"\\\" Class representing a\",\n \"a copy of this object and shuffles it. \\\"\\\"\\\" _FULL_DECK = [] def\",\n \"in range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if\",\n \"def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK: return list(Deck._FULL_DECK) # create\",\n \"object instantiated simply makes a copy of this object and shuffles it. \\\"\\\"\\\"\",\n \"from random import shuffle as rshuffle from .card import Card class Deck: \\\"\\\"\\\"\",\n \"Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1): if n == 1: return self.cards.pop(0) cards =\",\n \"this object and shuffles it. \\\"\\\"\\\" _FULL_DECK = [] def __init__(self): self.shuffle() def\",\n \"standard 52 card deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items():\",\n \"The first time we create, we seed the static deck with the list\",\n \"as rshuffle from .card import Card class Deck: \\\"\\\"\\\" Class representing a deck.\",\n \"class Deck: \\\"\\\"\\\" Class representing a deck. The first time we create, we\",\n \"52 card deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank\",\n \"def shuffle(self): # and then shuffle self.cards = Deck.GetFullDeck() rshuffle(self.cards) def draw(self, n=1):\",\n \"import Card class Deck: \\\"\\\"\\\" Class representing a deck. The first time we\",\n \"deck with the list of unique card integers. Each object instantiated simply makes\",\n \"deck for rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank + suit))\",\n \"rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank + suit)) return list(Deck._FULL_DECK)\",\n \"makes a copy of this object and shuffles it. \\\"\\\"\\\" _FULL_DECK = []\"\n]","isConversational":false}}},{"rowIdx":78,"cells":{"ngram":{"kind":"list like","value":["the current scopeset if we do not already have on. :rtype: string or","list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token: #","by # the user! Also, even if it has expired, we might still","due to a server error or because the account or token was lacking","if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile,","that we will try to use for our webserver WEB_PORTS = [12345, 23456]","that whenever this file is touched, the cache lock is held \"\"\" assert","the account or token was lacking specific permissions. \"\"\" if not self.last_returned_uuid: raise","token to be removed from cache \"\"\" self.debug('Removing token %s from cache', uuid)","start a new webserver on one of the WEB_PORTS, and then either show","None # We did not have a valid token, now comes the hard","import requests import sys from openidc_client import release # The ports that we","to use POST submission of client secrets rather than Authorization header :kwarg client_id:","client. :kwarg new_token: If True, we will actively request the user to get","data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None","was valid but your request failed due to a server error or because","UUID. If the user cancelled (or we got another error), we will return",":returns: True if the token was succesfully refreshed, False otherwise \"\"\" oldtoken =","secret. :kwarg useragent: Useragent string to use. If not provided, defaults to \"python-openidc-client/VERSION\"","(string, dict) or None :returns: Token UUID and contents or None if no","not new_token: return None # We did not have a valid token, now","if we do not already have on. :kwarg auto_refresh: If False, will not","try: from urllib import urlencode except ImportError: from urllib.parse import urlencode from uuid","your request failed due to a server error or because the account or","kv = dict([v.split('=', 1) for v in split]) if 'error' in kv: self.debug('Error","if we already have a token with the current app_identifier that has the","in incorrect cases. :kwargs http_method: The HTTP method to use, defaults to POST..","A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR","import json import logging from threading import Lock import time try: from StringIO","not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not","anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to cache on disk. Requires","even if it has expired, we might still be able to # refresh","% method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token","with the specified scopes. The webserver will then need to catch the return","reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result","to catch the return with either an Authorization Code (that we will exchange","method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not","self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not token: return","unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {}",":rtype: bool :returns: True if the token was succesfully refreshed, False otherwise \"\"\"","return code in incorrect cases. :kwargs http_method: The HTTP method to use, defaults","auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args,","{'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes':","else: self._retrieved_code = kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')])","'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data)","token we can use to refresh the access token # scopes: A list","%s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at':","renew the token or delete the token. :kwarg scopes: A list of scopes","dict. :rtype: string :returns: The IdP URL \"\"\" if method in self.idp_mapping: return","'%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd)","token cache is a json serialized dict # This dict contains uuid: token","_refresh_token(self, uuid): \"\"\"Tries to refresh a token and put the refreshed token in","is True. :kwarg new_token: If True, we will actively request the user to","self._retrieved_code is not None if self._retrieved_code is False: # The user cancelled the","to permit persons to whom the Software is # furnished to do so,","except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes:","_cachefile(self): \"\"\"Property to get the cache file name for the current client. This","= (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method):","'.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query'","from the cache and writes cache to disk. cache_lock may not be held","self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if","Allarguments and keyword arguments are like the arguments to requests, except for `scopes`,","= [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every app","== 401: # We got a 401 and this is a retry. Report","We got a 401 and this is a retry. Report error self.report_token_issue() return","and this permission notice shall be included in # all copies or substantial","= False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error with the last token","client. This assures that whenever this file is touched, the cache lock is","with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return","to get token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s',","\"\"\"Function to retrieve tokens with specific scopes. This function will block until a","LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION","as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the","possible_token = None self.debug('Trying to get token with scopes %s', scopes) for uuid","uuid, token # This is a token that may or may not still",":returns: String bearer token if possible or None \"\"\" if not isinstance(scopes, list):","resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a 401","in self._cache The caller is responsible for either removing the token if it","an Authorization Code (that we will exchange for an access token) or the","WEB_PORT.\"\"\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server","self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache for","__refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. Requires cache_lock to be","server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False: # The","report issue before requesting token') if self.problem_reported: # We were reported an issue","from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del","to automatically report token issues on 401. This helps with broken apps that","self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to cache on disk. Requires cache_lock to","token = self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if 'json'","the client_id. May be None if your IdP does not require you to",":kwarg use_post: Whether to use POST submission of client secrets rather than Authorization","WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This","*args, **kwargs): \"\"\"Make an python-requests POST request. Allarguments and keyword arguments are like","resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'],","`new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for","to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory in which to store the token caches.","disk. cache_lock may not be held by anyone. :param uuid: UUID of the","return True def _get_server(self, app): \"\"\"This function returns a SimpleServer with an available","a token to the cache and writes cache to disk. cache_lock may not","lacking specific permissions. \"\"\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting","def _refresh_token(self, uuid): \"\"\"Tries to refresh a token and put the refreshed token","new webserver on one of the WEB_PORTS, and then either show the user","cache_lock may not be held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes","be refreshable. :param scopes: List of scopes that need to be in the","def __write_cache(self): \"\"\"Wirtes self._cache to cache on disk. Requires cache_lock to be held","no applicable tokens were found \"\"\" possible_token = None self.debug('Trying to get token","or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code =","ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh',","one continue def _get_new_token(self, scopes): \"\"\"This function kicks off some magic. We will","of scopes that we had requested with the token def __init__(self, app_identifier, id_provider,","the required scopes, we will return it. This function will return a bearer","return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error with the last token that was","BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN","the cache on disk. cache_lock may not be held by anyone.\"\"\" with self._cache_lock:","if renewal was succesful. :param uuid: The UUID of the cached token to","the requested method. :param method: The method name in the IdP mapping dict.","your application that the token you sent was invalid, you should call it.","CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT","it. You should explicitly NOT call this function if the token was valid","app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with","no such tokens exist it will return the possibly expired token: it might","refreshed, False otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data =","Default is ~/.openidc. If this does not exist and we are unable to","continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes']))","will be thrown. :kwargs printfd: The File object to print token instructions to.","(%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return","already have on. :rtype: string or None :returns: String bearer token if possible","self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating","uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] =","def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for","access token. If it did not work, we will return None and remove","self._printfd = printfd def get_token(self, scopes, new_token=True): \"\"\"Function to retrieve tokens with specific","_token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for","resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True","the new access token. If it did not work, we will return None","indicates the token should still be valid, it may have been revoked by","the token should still be valid, it may have been revoked by #","\"\"\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh =","retrieved tokens :param id_provider: URL of the identity provider to get tokens from","writes cache to disk. cache_lock may not be held by anyone. :param uuid:","in ['POST']: raise ValueError('Cannot use POST tokens in %s method' % method) if","self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. Requires cache_lock","you sent was invalid, you should call it. You should explicitly NOT call","a json dict with the following keys: # idp: The URL of the","'POST') is_retry = False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try","cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache:","token in self._cache The caller is responsible for either removing the token if","token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid","DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR","from urllib.parse import urlencode from uuid import uuid4 as uuidgen import webbrowser from","found \"\"\" possible_token = None self.debug('Trying to get token with scopes %s', scopes)","but if no such tokens exist it will return the possibly expired token:","The caller is responsible for either removing the token if it could not","Token UUID and contents or None if no applicable tokens were found \"\"\"","NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE","the return with either an Authorization Code (that we will exchange for an","software and associated documentation files (the \"Software\"), to deal # in the Software","URL of the idp that issued the token # sub: The subject that","for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes","resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif","self._retrieved_code = None resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization","implementation of tokens: # Every app id has its own token cache #","to # refresh the token. # refresh_token: The token we can use to","to the cache and writes cache to disk. cache_lock may not be held","and to permit persons to whom the Software is # furnished to do","kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return a message","a new token with the specified scopes. The webserver will then need to","# furnished to do so, subject to the following conditions: # # The","the Software, and to permit persons to whom the Software is # furnished","server except socket.error: # This port did not work. Switch to next one","'text/plain')]) return [u'You can close this window and return to the CLI'.encode('ascii')] self._retrieved_code","If this does not exist and we are unable to create it, the","# indicates the token should still be valid, it may have been revoked","to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating","authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' %","gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache for any tokens that have the","= None self.debug('Trying to get token with scopes %s', scopes) for uuid in","scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp']","name in the IdP mapping dict. :rtype: string :returns: The IdP URL \"\"\"","ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE","'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST',","\"\"\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=',","token should still be valid, it may have been revoked by # the","services relying on OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens","401 and this is a retry. Report error self.report_token_issue() return resp else: return","got another error), we will return None. \"\"\" def _token_app(environ, start_response): query =","\"\"\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in","not None if self._retrieved_code is False: # The user cancelled the request self._retrieved_code","list of scopes that we had requested with the token def __init__(self, app_identifier,","the cancellation message. This function will store the new token in the local","token to be updated :param toupdate: Dict indicating which fields need to be","not provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory in which to store","~/.openidc. If this does not exist and we are unable to create it,","return resp @property def _cachefile(self): \"\"\"Property to get the cache file name for","'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST',","CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH","return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp':","if possible or None \"\"\" if not isinstance(scopes, list): raise ValueError('Scopes must be","socket.error: # This port did not work. Switch to next one continue def","resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self,","comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported","= False else: self._retrieved_code = kv['code'] # Just return a message start_response('200 OK',","client_id. May be None if your IdP does not require you to use","PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT","release # The ports that we will try to use for our webserver","from openidc_client import release # The ports that we will try to use","a server error or because the account or token was lacking specific permissions.","to refresh a token and put the refreshed token in self._cache The caller","supposed to still be valid, prefer it # over any others we have","another error), we will return None. \"\"\" def _token_app(environ, start_response): query = environ['QUERY_STRING']","'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE","a secret. :kwarg useragent: Useragent string to use. If not provided, defaults to","we will return None. \"\"\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split =","def _refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. cache_lock may not","to be added to the cache \"\"\" uuid = uuidgen().hex self.debug('Adding token %s","time, but if no such tokens exist it will return the possibly expired","webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes)","Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY","True, we will actively request the user to get a new token with","self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid","if we do not already have on. :rtype: string or None :returns: String","Useragent string to use. If not provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The","self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error with the last token that was returned.","be the Authorization endpoint of the IdP with a request for our client_id","to deal # in the Software without restriction, including without limitation the rights","to any person obtaining a copy # of this software and associated documentation","IdP URL for the requested method. :param method: The method name in the","a token is not present with this token, a new one will be","were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery =","\"\"\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported:","json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache from the cache","def send_request(self, *args, **kwargs): \"\"\"Make an python-requests POST request. Allarguments and keyword arguments","% server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id']","OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #","return token[1]['access_token'] elif not new_token: return None # We did not have a","return uuid, token # This is a token that may or may not","return the possibly expired token: it might be refreshable. :param scopes: List of","app) return server except socket.error: # This port did not work. Switch to","= self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate a webserver')","uuid: token pairs # Every \"token\" object is a json dict with the","server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] =","from urllib import urlencode except ImportError: from urllib.parse import urlencode from uuid import","In that case, you will want to call report_token_issue() to try to renew","this does not exist and we are unable to create it, the OSError","os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as","current app_identifier that has the required scopes, we will return it. This function",":kwarg client_secret: The client \"secret\" that goes with the client_id. May be None","from cache \"\"\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if","method) def _refresh_token(self, uuid): \"\"\"Tries to refresh a token and put the refreshed","with specific scopes. This function will block until a token is retrieved if","self.debug('User cancelled') return None self.debug('We got an authorization code!') data = {'client_id': self.client_id,","this is a retry. Report error self.report_token_issue() return resp else: return resp @property","the idp that issued the token # sub: The subject that owns the","in the IdP mapping dict. :rtype: string :returns: The IdP URL \"\"\" if","revoked by the user or expired. In that case, you will want to","uuid import uuid4 as uuidgen import webbrowser from wsgiref import simple_server import requests","= id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s'","refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args,","valid but your request failed due to a server error or because the","this software and associated documentation files (the \"Software\"), to deal # in the","current client. This assures that whenever this file is touched, the cache lock","The Client Identifier used to request credentials :kwarg client_secret: The client \"secret\" that","credentials :kwarg client_secret: The client \"secret\" that goes with the client_id. May be","POST submission of client secrets rather than Authorization header :kwarg client_id: The Client","self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return None","have a token with the current app_identifier that has the required scopes, we","be requested unless nonblocking is True. :kwarg new_token: If True, we will actively","new_token: return None # We did not have a valid token, now comes","server error or because the account or token was lacking specific permissions. \"\"\"","If we had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported =","self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \"\"\"This function returns a","if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \"\"\"Returns the IdP","granted, free of charge, to any person obtaining a copy # of this","to retrieve tokens with specific scopes. This function will block until a token","that was last returned. If that worked, we will return the new access","Code (that we will exchange for an access token) or the cancellation message.","be held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to cache","but your request failed due to a server error or because the account","`scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required","import simple_server import requests import sys from openidc_client import release # The ports","1) for v in split]) if 'error' in kv: self.debug('Error code returned: %s","remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid)","the current scopeset if we do not already have on. :kwarg auto_refresh: If","to. \"\"\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post =","app): \"\"\"This function returns a SimpleServer with an available WEB_PORT.\"\"\" for port in","the IdP with a request for our client_id to get a new token","of scopes that need to be in the returned token :rtype: (string, dict)","will return None and remove this token from the cache. If you get","# Permission is hereby granted, free of charge, to any person obtaining a","urllib import urlencode except ImportError: from urllib.parse import urlencode from uuid import uuid4","id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' %","with this token, a new one will be requested unless nonblocking is True.","not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \"\"\"Removes","IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF","= id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent =","self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed","uuid4 as uuidgen import webbrowser from wsgiref import simple_server import requests import sys","resp.status_code == 401: # We got a 401 and this is a retry.","will return the possibly expired token: it might be refreshable. :param scopes: List","function will return a bearer token or None. Note that the bearer token","self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue","to still be valid, prefer it # over any others we have self.debug('Not","still be able to # refresh the token. # refresh_token: The token we","'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers'","relying on OpenID Connect for authentication.\"\"\" from __future__ import print_function from copy import","self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make an python-requests POST","def _delete_token(self, uuid): \"\"\"Removes a token from the cache and writes cache to","OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION","self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f:","without restriction, including without limitation the rights # to use, copy, modify, merge,","**kwargs): \"\"\"Make an python-requests POST request. Allarguments and keyword arguments are like the","than Authorization header :kwarg client_id: The Client Identifier used to request credentials :kwarg","token to attempt to refresh. :rtype: bool :returns: True if the token was","the token or delete the token. :kwarg scopes: A list of scopes required","port did not work. Switch to next one continue def _get_new_token(self, scopes): \"\"\"This","to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope']","return the new access token. If it did not work, we will return","to use a secret. :kwarg useragent: Useragent string to use. If not provided,","this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return","has expired, we might still be able to # refresh the token. #","token was valid but your request failed due to a server error or","time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE","token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing","# Every app id has its own token cache # The token cache","is_retry = False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try =","token') if self.problem_reported: # We were reported an issue before. Let's just remove","None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp,","uuid def _delete_token(self, uuid): \"\"\"Removes a token from the cache and writes cache","a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = '","be None if your IdP does not require you to use a secret.","the cache \"\"\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with","updated :param toupdate: Dict indicating which fields need to be updated \"\"\" self.debug('Updating","copies of the Software, and to permit persons to whom the Software is","it to the valid cache, and then return the UUID. If the user","uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error with the","URL, or if possible, kick off their browser. This URL will be the","if self.problem_reported: # We were reported an issue before. Let's just remove this","a post call') if method not in ['POST']: raise ValueError('Cannot use POST tokens","import urlencode except ImportError: from urllib.parse import urlencode from uuid import uuid4 as","ports that we will try to use for our webserver WEB_PORTS = [12345,","is responsible for either removing the token if it could not be refreshed","call it. You should explicitly NOT call this function if the token was","\"\"\"Tries to refresh a token and put the refreshed token in self._cache The","to get a new token with the current scopeset if we do not","\"Bearer\" # expires_at: Token expiration UTC time. NOTE: Even if the expires_at #","uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid):","obtaining a copy # of this software and associated documentation files (the \"Software\"),","on. :rtype: string or None :returns: String bearer token if possible or None","http_method: The HTTP method to use, defaults to POST.. \"\"\" ckwargs = copy(kwargs)","on one of the WEB_PORTS, and then either show the user a URL,","requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None,","cache on disk. cache_lock may not be held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache()","also lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache","scopes. It will prefer to return tokens whose expires_at is still before the","that issued the token # sub: The subject that owns the token #","Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes,","caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not","IdP URL \"\"\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return","Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not","return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'),","you should call it. You should explicitly NOT call this function if the","requested unless nonblocking is True. :kwarg new_token: If True, we will actively request","get a new token with the specified scopes. The webserver will then need","resp @property def _cachefile(self): \"\"\"Property to get the cache file name for the","If False, will not try to automatically report token issues on 401. This","False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']})","code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret:","cache. If you get an indication from your application that the token you","will try to use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object):","resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None","will attempt to renew the token that was last returned. If that worked,","True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make an python-requests POST request. Allarguments","time try: from StringIO import StringIO except ImportError: from io import StringIO import","%i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk.","user! Also, even if it has expired, we might still be able to","by anyone. :param token: Dict of the token to be added to the","# idp: The URL of the idp that issued the token # sub:","of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a","from copy import copy import json import logging from threading import Lock import","function will block until a token is retrieved if requested. It is always","401. This helps with broken apps that may send a 401 return code","scopes: A list of scopes required for the current client. :kwarg new_token: If","self._cache from the cache on disk. cache_lock may not be held by anyone.\"\"\"","any person obtaining a copy # of this software and associated documentation files","you will want to call report_token_issue() to try to renew the token or","explicitly NOT call this function if the token was valid but your request","You should explicitly NOT call this function if the token was valid but","an python-requests POST request. Allarguments and keyword arguments are like the arguments to","self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to refresh,","IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED,","tokens in %s method' % method) if 'data' not in ckwargs: ckwargs['data'] =","a copy # of this software and associated documentation files (the \"Software\"), to","revoked by # the user! Also, even if it has expired, we might","lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache =","token else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer","the user a URL, or if possible, kick off their browser. This URL","return tokens whose expires_at is still before the current time, but if no","with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a token to","dict) or None :returns: Token UUID and contents or None if no applicable","not present with this token, a new one will be requested unless nonblocking","AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #","(the \"Software\"), to deal # in the Software without restriction, including without limitation","= 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] =","for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] !=","of client secrets rather than Authorization header :kwarg client_id: The Client Identifier used","token that may or may not still be valid self.debug('Possible') possible_token = (uuid,","charge, to any person obtaining a copy # of this software and associated","will return it. This function will return a bearer token or None. Note","path for %s' % method) def _refresh_token(self, uuid): \"\"\"Tries to refresh a token","use POST submission of client secrets rather than Authorization header :kwarg client_id: The","'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401","this function if the token was valid but your request failed due to","one of the WEB_PORTS, and then either show the user a URL, or","cache \"\"\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock:","and put the refreshed token in self._cache The caller is responsible for either","if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code","be updated :param toupdate: Dict indicating which fields need to be updated \"\"\"","rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id","limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or","the cache file name for the current client. This assures that whenever this","token) or the cancellation message. This function will store the new token in","return possible_token def _idp_url(self, method): \"\"\"Returns the IdP URL for the requested method.","self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code = None #","Report error self.report_token_issue() return resp else: return resp @property def _cachefile(self): \"\"\"Property to","client_secret self.useragent = useragent or 'python-openid-client/%s' % \\ release.VERSION self.cachedir = os.path.expanduser(cachedir or","serialized dict # This dict contains uuid: token pairs # Every \"token\" object","self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock a filesystem lock","{} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers'] = {}","we have self.debug('Not yet expired, returning') return uuid, token # This is a","not include path for %s' % method) def _refresh_token(self, uuid): \"\"\"Tries to refresh","\"\"\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache()","a new webserver on one of the WEB_PORTS, and then either show the","valid token, now comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid","_get_server(self, app): \"\"\"This function returns a SimpleServer with an available WEB_PORT.\"\"\" for port","THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR","if the token was valid but your request failed due to a server","the token that was last returned. If that worked, we will return the","if self._retrieved_code is False: # The user cancelled the request self._retrieved_code = None","Even if the expires_at # indicates the token should still be valid, it","EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,","\"\"\"Wirtes self._cache to cache on disk. Requires cache_lock to be held by caller.\"\"\"","We did not have a valid token, now comes the hard part... uuid","a token that may or may not still be valid self.debug('Possible') possible_token =","to use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal","for specific endpoints on the IdP. :kwarg use_post: Whether to use POST submission","bearer token or None. Note that the bearer token might have been revoked","valid, prefer it # over any others we have self.debug('Not yet expired, returning')","just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result:","if requested. It is always safe to call this though, since if we","None. Note that the bearer token might have been revoked by the user","environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v in split]) if","'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app):","resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in","new_token: If True, we will actively request the user to get a new","in the cache. cache_lock may not be held by anyone. :param token: UUID","set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a token that's","that was returned. This will attempt to renew the token that was last","value # token_type: Token type. Currently supported: \"Bearer\" # expires_at: Token expiration UTC","# # Permission is hereby granted, free of charge, to any person obtaining","socket import os try: from urllib import urlencode except ImportError: from urllib.parse import","from :param id_provider_mapping: Mapping with URLs to use for specific endpoints on the","token with the current scopeset if we do not already have on. :kwarg","DEALINGS IN THE # SOFTWARE. \"\"\"Client for applications relying on OpenID Connect for","object to print token instructions to. \"\"\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug","by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to cache on disk.","OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \"\"\"Client for applications","if token['expires_at'] < time.time(): # This is a token that's supposed to still","as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i","if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token(","if your IdP does not require you to use a secret. :kwarg useragent:","= self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code ==","others we have self.debug('Not yet expired, returning') return uuid, token # This is","use_post: Whether to use POST submission of client secrets rather than Authorization header","browser. This URL will be the Authorization endpoint of the IdP with a","use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation","for an access token) or the cancellation message. This function will store the","'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} #","FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE","PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING","client_secret: The client \"secret\" that goes with the client_id. May be None if","# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS","OpenIDCClient(object): # Internal implementation of tokens: # Every app id has its own","include path for %s' % method) def _refresh_token(self, uuid): \"\"\"Tries to refresh a","open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self):","exchange for an access token) or the cancellation message. This function will store","the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell","submission of client secrets rather than Authorization header :kwarg client_id: The Client Identifier","have been revoked by the user or expired. In that case, you will","for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except","and remove this token from the cache. If you get an indication from","return None. \"\"\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv","of the Software, and to permit persons to whom the Software is #",":kwarg useragent: Useragent string to use. If not provided, defaults to \"python-openidc-client/VERSION\" :kwarg","cached token to attempt to refresh. :rtype: bool :returns: True if the token","the token # access_token: Token value # token_type: Token type. Currently supported: \"Bearer\"","to a server error or because the account or token was lacking specific","code in incorrect cases. :kwargs http_method: The HTTP method to use, defaults to","an available WEB_PORT.\"\"\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app)","self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code","to the cache \"\"\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid)","id has its own token cache # The token cache is a json","expires_at # indicates the token should still be valid, it may have been","method: The method name in the IdP mapping dict. :rtype: string :returns: The","be added to the cache \"\"\" uuid = uuidgen().hex self.debug('Adding token %s to","to cache on disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked()","simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port did not work.","on disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache')","self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp =","scopes: A list of scopes that we had requested with the token def","self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request(","self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error with the last","with the following keys: # idp: The URL of the idp that issued","os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code","kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can","including without limitation the rights # to use, copy, modify, merge, publish, distribute,","self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token']","# This port did not work. Switch to next one continue def _get_new_token(self,","= dict([v.split('=', 1) for v in split]) if 'error' in kv: self.debug('Error code","removing the token if it could not be refreshed or saving the cache","token: UUID of the token to be updated :param toupdate: Dict indicating which","cache, and then return the UUID. If the user cancelled (or we got","new_token=new_token) if not token: return None if self.use_post: if 'json' in ckwargs: raise","cache # The token cache is a json serialized dict # This dict","token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token","printfd=sys.stdout): \"\"\"Client for interacting with web services relying on OpenID Connect. :param app_identifier:","cache_lock a filesystem lock so we also lock across # multiple invocations self._cache_lock","returned. This will attempt to renew the token that was last returned. If","return uuid def _update_token(self, uuid, toupdate): \"\"\"Updates a token in the cache. cache_lock","_refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. cache_lock may not be","can close this window and return to the CLI'.encode('ascii')] self._retrieved_code = None server","OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS","self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True): \"\"\"Function","'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request(","This helps with broken apps that may send a 401 return code in","= ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True token =","token pairs # Every \"token\" object is a json dict with the following","**ckwargs) if resp.status_code == 401 and not is_retry: if not auto_refresh: return resp","this token, a new one will be requested unless nonblocking is True. :kwarg","= 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query =","if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if","Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free of","assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache from","self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to cache on disk. Requires cache_lock to be","the Software is # furnished to do so, subject to the following conditions:","subject to the following conditions: # # The above copyright notice and this","filesystem lock so we also lock across # multiple invocations self._cache_lock = Lock()","(that we will exchange for an access token) or the cancellation message. This","for interacting with web services relying on OpenID Connect. :param app_identifier: Identifier for","If a token is not present with this token, a new one will","is a json serialized dict # This dict contains uuid: token pairs #","a token is retrieved if requested. It is always safe to call this","not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try:","TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.","until a token is retrieved if requested. It is always safe to call","Every \"token\" object is a json dict with the following keys: # idp:","query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v in","split = query.split('&') kv = dict([v.split('=', 1) for v in split]) if 'error'","self._cache from the cache on disk. Requires cache_lock to be held by caller.\"\"\"","This function will return a bearer token or None. Note that the bearer","storage of retrieved tokens :param id_provider: URL of the identity provider to get","have a valid token, now comes the hard part... uuid = self._get_new_token(scopes) if","token and put the refreshed token in self._cache The caller is responsible for","%s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just","have on. :rtype: string or None :returns: String bearer token if possible or","that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return","= True token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token)","SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #","Dict indicating which fields need to be updated \"\"\" self.debug('Updating token %s in","'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid,","# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies","import os try: from urllib import urlencode except ImportError: from urllib.parse import urlencode","tokens whose expires_at is still before the current time, but if no such","client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with web services relying on","a bearer token or None. Note that the bearer token might have been","cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid]","it. This function will return a bearer token or None. Note that the","is hereby granted, free of charge, to any person obtaining a copy #","23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every app id has","raise Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1]","\"\"\"Property to get the cache file name for the current client. This assures","refresh the token. # refresh_token: The token we can use to refresh the","are unable to create it, the OSError will be thrown. :kwargs printfd: The","-*- coding: utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat, Inc.","# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE","the cache for any tokens that have the requested scopes. It will prefer","= self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url =","import copy import json import logging from threading import Lock import time try:",":kwarg scopes: A list of scopes required for the current client. :kwarg new_token:","lock so we also lock across # multiple invocations self._cache_lock = Lock() with","set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at']","contents or None if no applicable tokens were found \"\"\" possible_token = None","send a 401 return code in incorrect cases. :kwargs http_method: The HTTP method","token from the cache. If you get an indication from your application that","token to be added to the cache \"\"\" uuid = uuidgen().hex self.debug('Adding token","broken apps that may send a 401 return code in incorrect cases. :kwargs","%s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token')","401 return code in incorrect cases. :kwargs http_method: The HTTP method to use,","access token) or the cancellation message. This function will store the new token","auto_refresh: If False, will not try to automatically report token issues on 401.","None self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri':","self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code =","token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \"\"\"Updates a token in the","print token instructions to. \"\"\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id =","try to automatically report token issues on 401. This helps with broken apps","arguments are like the arguments to requests, except for `scopes`, `new_token` and `auto_refresh`","so, subject to the following conditions: # # The above copyright notice and","in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else:","succesful. :param uuid: The UUID of the cached token to attempt to refresh.","get tokens from :param id_provider_mapping: Mapping with URLs to use for specific endpoints","+ self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for %s' %","applicable tokens were found \"\"\" possible_token = None self.debug('Trying to get token with","self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \"\"\"Removes a token","the cache on disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked()","copy # of this software and associated documentation files (the \"Software\"), to deal","retry. Report error self.report_token_issue() return resp else: return resp @property def _cachefile(self): \"\"\"Property",":rtype: string or None :returns: String bearer token if possible or None \"\"\"","resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at'])","our client_id to get a new token with the specified scopes. The webserver","file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False:","message. This function will store the new token in the local cache, add","the token caches. Will be put through expanduer. Default is ~/.openidc. If this","a valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token']","self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE! \\o/ return self._add_token(token)","requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error'","refresh_token: The token we can use to refresh the access token # scopes:","the user or expired. In that case, you will want to call report_token_issue()","fields need to be updated \"\"\" self.debug('Updating token %s in cache, fields %s',","UUID of the token to be removed from cache \"\"\" self.debug('Removing token %s","else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make an python-requests","Identifier used to request credentials :kwarg client_secret: The client \"secret\" that goes with","\"\"\" if not isinstance(scopes, list): raise ValueError('Scopes must be a list') token =","from threading import Lock import time try: from StringIO import StringIO except ImportError:","is not present with this token, a new one will be requested unless","get the cache file name for the current client. This assures that whenever","in the local cache, add it to the valid cache, and then return","self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in resp:","do not already have on. :kwarg auto_refresh: If False, will not try to","len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. cache_lock may","sublicense, and/or sell # copies of the Software, and to permit persons to","self.debug('Returning possible token') return possible_token def _idp_url(self, method): \"\"\"Returns the IdP URL for","cache to disk. cache_lock may not be held by anyone. :param token: Dict","cachedir: The directory in which to store the token caches. Will be put","that worked, we will return the new access token. If it did not","Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted,","subject that owns the token # access_token: Token value # token_type: Token type.","__future__ import print_function from copy import copy import json import logging from threading","= useragent or 'python-openid-client/%s' % \\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid","worked, we will return the new access token. If it did not work,","to get a new token with the specified scopes. The webserver will then","scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time():","type. Currently supported: \"Bearer\" # expires_at: Token expiration UTC time. NOTE: Even if","is a token that may or may not still be valid self.debug('Possible') possible_token","is False: # The user cancelled the request self._retrieved_code = None self.debug('User cancelled')","to refresh the access token # scopes: A list of scopes that we","IN THE # SOFTWARE. \"\"\"Client for applications relying on OpenID Connect for authentication.\"\"\"","the token to be added to the cache \"\"\" uuid = uuidgen().hex self.debug('Adding","int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE! \\o/","cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir):","with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True):","to the valid cache, and then return the UUID. If the user cancelled","= environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v in split])","self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \"\"\"Updates",":param toupdate: Dict indicating which fields need to be updated \"\"\" self.debug('Updating token","= kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You","if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported: #","= Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self,","scopes: List of scopes that need to be in the returned token :rtype:","# copies of the Software, and to permit persons to whom the Software","be removed from cache \"\"\" self.debug('Removing token %s from cache', uuid) with self._cache_lock:","return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make","that owns the token # access_token: Token value # token_type: Token type. Currently","required for this call. If a token is not present with this token,","raise ValueError('Cannot provide json in a post call') if method not in ['POST']:","held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to cache on","instructions to. \"\"\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post","token. If it did not work, we will return None and remove this","= requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if","self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self,","this permission notice shall be included in # all copies or substantial portions","assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile):","will store the new token in the local cache, add it to the","scopes that need to be in the returned token :rtype: (string, dict) or","resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'],","= logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp =","The token we can use to refresh the access token # scopes: A","was lacking specific permissions. \"\"\" if not self.last_returned_uuid: raise Exception('Cannot report issue before","token, a new one will be requested unless nonblocking is True. :kwarg new_token:","client \"secret\" that goes with the client_id. May be None if your IdP","CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #","still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token')","a SimpleServer with an available WEB_PORT.\"\"\" for port in WEB_PORTS: try: server =","in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \"\"\"Removes a","on disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache","token): \"\"\"Adds a token to the cache and writes cache to disk. cache_lock","self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code =","the token was succesfully refreshed, False otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token","client_id: The Client Identifier used to request credentials :kwarg client_secret: The client \"secret\"","ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token: # If we","token or None. Note that the bearer token might have been revoked by","did not have a valid token, now comes the hard part... uuid =","\"\"\"Updates a token in the cache. cache_lock may not be held by anyone.","web services relying on OpenID Connect. :param app_identifier: Identifier for storage of retrieved","'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'),","token or delete the token. :kwarg scopes: A list of scopes required for","start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v","application that the token you sent was invalid, you should call it. You","FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF","then need to catch the return with either an Authorization Code (that we","though, since if we already have a token with the current app_identifier that","with an available WEB_PORT.\"\"\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port,","do not already have on. :rtype: string or None :returns: String bearer token","token if it could not be refreshed or saving the cache if renewal","code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code']","merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to","return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a 401 and","['POST']: raise ValueError('Cannot use POST tokens in %s method' % method) if 'data'","+ resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \"\"\"This function","'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return","its own token cache # The token cache is a json serialized dict","in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp =","arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is","== 401 and not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue()","A list of scopes required for the current client. :kwarg new_token: If True,","multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd =","raise ValueError('Cannot use POST tokens in %s method' % method) if 'data' not","= resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return","elif resp.status_code == 401: # We got a 401 and this is a","nonblocking is True. :kwarg new_token: If True, we will actively request the user","% token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not","ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False","token with the current scopeset if we do not already have on. :rtype:","with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate):","not require you to use a secret. :kwarg useragent: Useragent string to use.","= token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return None #","whom the Software is # furnished to do so, subject to the following","to create it, the OSError will be thrown. :kwargs printfd: The File object","cancelled') return None self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type':","function returns a SimpleServer with an available WEB_PORT.\"\"\" for port in WEB_PORTS: try:","401: # We got a 401 and this is a retry. Report error","of tokens: # Every app id has its own token cache # The","with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token):","the local cache, add it to the valid cache, and then return the","copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software,","to call this though, since if we already have a token with the","continue if token['expires_at'] < time.time(): # This is a token that's supposed to","return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a","a json serialized dict # This dict contains uuid: token pairs # Every","failed due to a server error or because the account or token was","\"\"\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post","Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not","coding: utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat, Inc. #","prefer it # over any others we have self.debug('Not yet expired, returning') return","got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code':","the token to be removed from cache \"\"\" self.debug('Removing token %s from cache',","is # furnished to do so, subject to the following conditions: # #","StringIO except ImportError: from io import StringIO import socket import os try: from","= None server = self._get_server(_token_app) if not server: raise Exception('We were unable to","access token # scopes: A list of scopes that we had requested with","' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] =","before the current time, but if no such tokens exist it will return","self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes):","The IdP URL \"\"\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else:","it did not work, we will return None and remove this token from","had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False return","%s' % method) def _refresh_token(self, uuid): \"\"\"Tries to refresh a token and put","id_provider_mapping: Mapping with URLs to use for specific endpoints on the IdP. :kwarg","'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery)","user to get a new token with the current scopeset if we do","401 and not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if","self._cache to cache on disk. Requires cache_lock to be held by caller.\"\"\" assert","file is touched, the cache lock is held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir,","as uuidgen import webbrowser from wsgiref import simple_server import requests import sys from","self._retrieved_code is False: # The user cancelled the request self._retrieved_code = None self.debug('User","directory in which to store the token caches. Will be put through expanduer.","\"\"\"Report an error with the last token that was returned. This will attempt","self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache","# access_token: Token value # token_type: Token type. Currently supported: \"Bearer\" # expires_at:","was succesfully refreshed, False otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid)","OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE","in %s method' % method) if 'data' not in ckwargs: ckwargs['data'] = {}","utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat, Inc. # Red","token from the cache and writes cache to disk. cache_lock may not be","URLs to use for specific endpoints on the IdP. :kwarg use_post: Whether to","incorrect cases. :kwargs http_method: The HTTP method to use, defaults to POST.. \"\"\"","POST tokens in %s method' % method) if 'data' not in ckwargs: ckwargs['data']","None else: token = self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post:","be valid, prefer it # over any others we have self.debug('Not yet expired,","provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory in which to store the",":param id_provider: URL of the identity provider to get tokens from :param id_provider_mapping:","uuid: The UUID of the cached token to attempt to refresh. :rtype: bool","= {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] =","to renew the token or delete the token. :kwarg scopes: A list of","from the cache on disk. cache_lock may not be held by anyone.\"\"\" with","valid, it may have been revoked by # the user! Also, even if","permissions. \"\"\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if","a new one will be requested unless nonblocking is True. :kwarg new_token: If","%s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None","self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if","in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: #","cache on disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing","use for specific endpoints on the IdP. :kwarg use_post: Whether to use POST","and keyword arguments are like the arguments to requests, except for `scopes`, `new_token`","be thrown. :kwargs printfd: The File object to print token instructions to. \"\"\"","return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs)","by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if","import Lock import time try: from StringIO import StringIO except ImportError: from io","the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout):","OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY,","query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close()","print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert","[u'You can close this window and return to the CLI'.encode('ascii')] self._retrieved_code = None","before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if","= {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'],","returning') return uuid, token # This is a token that may or may","used to request credentials :kwarg client_secret: The client \"secret\" that goes with the","keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for this call. If","to call report_token_issue() to try to renew the token or delete the token.","be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with","a token and put the refreshed token in self._cache The caller is responsible","furnished to do so, subject to the following conditions: # # The above","return None and remove this token from the cache. If you get an","arguments. `scopes` is required. :kwarg scopes: Scopes required for this call. If a","False otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id':","resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \"\"\"This function returns","False else: self._retrieved_code = kv['code'] # Just return a message start_response('200 OK', [('Content-Type',","some magic. We will start a new webserver on one of the WEB_PORTS,","on OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens :param id_provider:","string to use. If not provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory","then either show the user a URL, or if possible, kick off their","provide json in a post call') if method not in ['POST']: raise ValueError('Cannot","for v in split]) if 'error' in kv: self.debug('Error code returned: %s (%s)',","your IdP does not require you to use a secret. :kwarg useragent: Useragent","self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache))","\"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT","the identity provider to get tokens from :param id_provider_mapping: Mapping with URLs to","get an indication from your application that the token you sent was invalid,","method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else:","return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query)","sub: The subject that owns the token # access_token: Token value # token_type:","return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in","be included in # all copies or substantial portions of the Software. #","or None \"\"\" if not isinstance(scopes, list): raise ValueError('Scopes must be a list')","the current client. :kwarg new_token: If True, we will actively request the user","disk. cache_lock may not be held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self):","removed from cache \"\"\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache()","if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def","we might still be able to # refresh the token. # refresh_token: The","refreshed token in self._cache The caller is responsible for either removing the token","dict([v.split('=', 1) for v in split]) if 'error' in kv: self.debug('Error code returned:","method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True token","elif not new_token: return None # We did not have a valid token,","scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid]","else: return ValueError('Idp Mapping did not include path for %s' % method) def","import urlencode from uuid import uuid4 as uuidgen import webbrowser from wsgiref import","window and return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if","__init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting","self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in a post call')","app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL of the identity","may not be held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache","token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])):",":param app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL of the","has its own token cache # The token cache is a json serialized","send_request(self, *args, **kwargs): \"\"\"Make an python-requests POST request. Allarguments and keyword arguments are","held by anyone. :param token: Dict of the token to be added to","'json' in ckwargs: raise ValueError('Cannot provide json in a post call') if method","IdP. :kwarg use_post: Whether to use POST submission of client secrets rather than","os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as","to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def","uuid def _update_token(self, uuid, toupdate): \"\"\"Updates a token in the cache. cache_lock may","an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code}","NOT call this function if the token was valid but your request failed","be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory')","cases. :kwargs http_method: The HTTP method to use, defaults to POST.. \"\"\" ckwargs","create it, the OSError will be thrown. :kwargs printfd: The File object to","use to refresh the access token # scopes: A list of scopes that","if resp.status_code == 401 and not is_retry: if not auto_refresh: return resp self.token_to_try","self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error'","this file is touched, the cache lock is held \"\"\" assert self._cache_lock.locked() return","resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND","webbrowser from wsgiref import simple_server import requests import sys from openidc_client import release","renew the token that was last returned. If that worked, we will return","The UUID of the cached token to attempt to refresh. :rtype: bool :returns:","tokens from :param id_provider_mapping: Mapping with URLs to use for specific endpoints on","for authentication.\"\"\" from __future__ import print_function from copy import copy import json import","to use for specific endpoints on the IdP. :kwarg use_post: Whether to use","on disk. cache_lock may not be held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def","could not be refreshed or saving the cache if renewal was succesful. :param","import StringIO except ImportError: from io import StringIO import socket import os try:","not have a valid token, now comes the hard part... uuid = self._get_new_token(scopes)","else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s'","import webbrowser from wsgiref import simple_server import requests import sys from openidc_client import","Internal implementation of tokens: # Every app id has its own token cache","be valid, it may have been revoked by # the user! Also, even","we had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False","Authorization endpoint of the IdP with a request for our client_id to get","self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try =","file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache","saving the cache if renewal was succesful. :param uuid: The UUID of the","return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() +","= os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None","\"\"\"Removes a token from the cache and writes cache to disk. cache_lock may","and contents or None if no applicable tokens were found \"\"\" possible_token =","self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache:","idp: The URL of the idp that issued the token # sub: The","isinstance(scopes, list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token:","invalid, you should call it. You should explicitly NOT call this function if","so we also lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock:","# Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free","resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error'])","scopeset if we do not already have on. :kwarg auto_refresh: If False, will","If that worked, we will return the new access token. If it did","import time try: from StringIO import StringIO except ImportError: from io import StringIO","of the idp that issued the token # sub: The subject that owns","will block until a token is retrieved if requested. It is always safe","error or because the account or token was lacking specific permissions. \"\"\" if","from the cache on disk. Requires cache_lock to be held by caller.\"\"\" assert","of the cached token to attempt to refresh. :rtype: bool :returns: True if","'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes","we will exchange for an access token) or the cancellation message. This function","expanduer. Default is ~/.openidc. If this does not exist and we are unable","were reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None","uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp:","cancelled the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an","add it to the valid cache, and then return the UUID. If the","the IdP mapping dict. :rtype: string :returns: The IdP URL \"\"\" if method","string or None :returns: String bearer token if possible or None \"\"\" if","user or expired. In that case, you will want to call report_token_issue() to","_get_token_with_scopes(self, scopes): \"\"\"Searches the cache for any tokens that have the requested scopes.","and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for this","copyright notice and this permission notice shall be included in # all copies","resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']),","token caches. Will be put through expanduer. Default is ~/.openidc. If this does","copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method","deal # in the Software without restriction, including without limitation the rights #","from your application that the token you sent was invalid, you should call","it may have been revoked by # the user! Also, even if it","= {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri']","automatically report token issues on 401. This helps with broken apps that may","urlencode from uuid import uuid4 as uuidgen import webbrowser from wsgiref import simple_server","the self._cache from the cache on disk. cache_lock may not be held by","does not exist and we are unable to create it, the OSError will","that's supposed to still be valid, prefer it # over any others we","open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a token to the","dict with the following keys: # idp: The URL of the idp that","whenever this file is touched, the cache lock is held \"\"\" assert self._cache_lock.locked()","function if the token was valid but your request failed due to a","Mapping with URLs to use for specific endpoints on the IdP. :kwarg use_post:","HTTP method to use, defaults to POST.. \"\"\" ckwargs = copy(kwargs) scopes =","query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to","was invalid, you should call it. You should explicitly NOT call this function","be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return","call this though, since if we already have a token with the current",":rtype: (string, dict) or None :returns: Token UUID and contents or None if","<<EMAIL>> # # Permission is hereby granted, free of charge, to any person","scopes, we will return it. This function will return a bearer token or","returned token :rtype: (string, dict) or None :returns: Token UUID and contents or","\"token\" object is a json dict with the following keys: # idp: The","name for the current client. This assures that whenever this file is touched,","self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\ release.VERSION self.cachedir =","= [] self._printfd = printfd def get_token(self, scopes, new_token=True): \"\"\"Function to retrieve tokens","the token you sent was invalid, you should call it. You should explicitly","the Authorization endpoint of the IdP with a request for our client_id to","Switch to next one continue def _get_new_token(self, scopes): \"\"\"This function kicks off some","# token_type: Token type. Currently supported: \"Bearer\" # expires_at: Token expiration UTC time.","KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF","not try to automatically report token issues on 401. This helps with broken","<NAME> <<EMAIL>> # # Permission is hereby granted, free of charge, to any","to whom the Software is # furnished to do so, subject to the","UUID and contents or None if no applicable tokens were found \"\"\" possible_token","have been revoked by # the user! Also, even if it has expired,","keys: # idp: The URL of the idp that issued the token #","String bearer token if possible or None \"\"\" if not isinstance(scopes, list): raise","call') if method not in ['POST']: raise ValueError('Cannot use POST tokens in %s","f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a token to the cache and writes","to be in the returned token :rtype: (string, dict) or None :returns: Token","not be held by anyone.\"\"\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to","through expanduer. Default is ~/.openidc. If this does not exist and we are","in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in","the token to be updated :param toupdate: Dict indicating which fields need to","the current app_identifier that has the required scopes, we will return it. This","that has the required scopes, we will return it. This function will return","%s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if","# Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME>","expired, we might still be able to # refresh the token. # refresh_token:","exchanging authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'],",":kwargs http_method: The HTTP method to use, defaults to POST.. \"\"\" ckwargs =","might still be able to # refresh the token. # refresh_token: The token","catch the return with either an Authorization Code (that we will exchange for","self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \"\"\"Removes a token from the cache","self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status()","a 401 return code in incorrect cases. :kwargs http_method: The HTTP method to","a token that's supposed to still be valid, prefer it # over any","OR OTHER DEALINGS IN THE # SOFTWARE. \"\"\"Client for applications relying on OpenID","# The ports that we will try to use for our webserver WEB_PORTS","ValueError('Idp Mapping did not include path for %s' % method) def _refresh_token(self, uuid):","True def _get_server(self, app): \"\"\"This function returns a SimpleServer with an available WEB_PORT.\"\"\"","THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR","f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache))","token in the local cache, add it to the valid cache, and then","this though, since if we already have a token with the current app_identifier","be held by anyone. :param token: UUID of the token to be updated","with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache =","{'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret","still be valid, it may have been revoked by # the user! Also,","the OSError will be thrown. :kwargs printfd: The File object to print token","if no applicable tokens were found \"\"\" possible_token = None self.debug('Trying to get","Authorization header :kwarg client_id: The Client Identifier used to request credentials :kwarg client_secret:","'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token","instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] =","that goes with the client_id. May be None if your IdP does not","self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping","not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported: # We","json dict with the following keys: # idp: The URL of the idp","data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret']","ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST')","NOTE: Even if the expires_at # indicates the token should still be valid,","function will store the new token in the local cache, add it to","= {} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers'] =","UUID of the token to be updated :param toupdate: Dict indicating which fields",":kwarg auto_refresh: If False, will not try to automatically report token issues on","This dict contains uuid: token pairs # Every \"token\" object is a json","refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True","OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR","if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already","cache on disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing","= uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] =","or saving the cache if renewal was succesful. :param uuid: The UUID of","sell # copies of the Software, and to permit persons to whom the","= 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code ==","# We got a 401 and this is a retry. Report error self.report_token_issue()","cache if renewal was succesful. :param uuid: The UUID of the cached token","possible_token def _idp_url(self, method): \"\"\"Returns the IdP URL for the requested method. :param","# all copies or substantial portions of the Software. # # THE SOFTWARE","or expired. In that case, you will want to call report_token_issue() to try","ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args,","self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] <","if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self,","# sub: The subject that owns the token # access_token: Token value #","rather than Authorization header :kwarg client_id: The Client Identifier used to request credentials","THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \"\"\"Client for applications relying","all copies or substantial portions of the Software. # # THE SOFTWARE IS","return it. This function will return a bearer token or None. Note that","already have on. :kwarg auto_refresh: If False, will not try to automatically report","self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token","URL will be the Authorization endpoint of the IdP with a request for","bearer token if possible or None \"\"\" if not isinstance(scopes, list): raise ValueError('Scopes","cache. cache_lock may not be held by anyone. :param token: UUID of the","(C) 2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> #","{'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s',","BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR","anyone. :param token: Dict of the token to be added to the cache","to disk. cache_lock may not be held by anyone. :param uuid: UUID of","prefer to return tokens whose expires_at is still before the current time, but","# If we had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported","return uuid def _delete_token(self, uuid): \"\"\"Removes a token from the cache and writes","Token expiration UTC time. NOTE: Even if the expires_at # indicates the token","not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We","OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT","printfd def get_token(self, scopes, new_token=True): \"\"\"Function to retrieve tokens with specific scopes. This","use a secret. :kwarg useragent: Useragent string to use. If not provided, defaults","files (the \"Software\"), to deal # in the Software without restriction, including without","Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby","def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache for any tokens that have the requested","an access token) or the cancellation message. This function will store the new","server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False: # The user","id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent","= client_secret self.useragent = useragent or 'python-openid-client/%s' % \\ release.VERSION self.cachedir = os.path.expanduser(cachedir","or None if no applicable tokens were found \"\"\" possible_token = None self.debug('Trying","post call') if method not in ['POST']: raise ValueError('Cannot use POST tokens in","to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server: raise","refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token':","self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an authorization code!') data","following conditions: # # The above copyright notice and this permission notice shall","an error with the last token that was returned. This will attempt to","Scopes required for this call. If a token is not present with this","idp that issued the token # sub: The subject that owns the token","assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f:","URL of the identity provider to get tokens from :param id_provider_mapping: Mapping with","= simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port did not","# SOFTWARE. \"\"\"Client for applications relying on OpenID Connect for authentication.\"\"\" from __future__","always safe to call this though, since if we already have a token","self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']}","or 'python-openid-client/%s' % \\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None","kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code","The above copyright notice and this permission notice shall be included in #","owns the token # access_token: Token value # token_type: Token type. Currently supported:","self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True): \"\"\"Function to","request. Allarguments and keyword arguments are like the arguments to requests, except for","the WEB_PORTS, and then either show the user a URL, or if possible,","in the returned token :rtype: (string, dict) or None :returns: Token UUID and","or delete the token. :kwarg scopes: A list of scopes required for the","self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self):","required. :kwarg scopes: Scopes required for this call. If a token is not","request for our client_id to get a new token with the specified scopes.","error with the last token that was returned. This will attempt to renew","requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg","disk. cache_lock may not be held by anyone. :param token: Dict of the","is a retry. Report error self.report_token_issue() return resp else: return resp @property def","def report_token_issue(self): \"\"\"Report an error with the last token that was returned. This","[] self._printfd = printfd def get_token(self, scopes, new_token=True): \"\"\"Function to retrieve tokens with","it # over any others we have self.debug('Not yet expired, returning') return uuid,","HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN","webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: #","def _get_server(self, app): \"\"\"This function returns a SimpleServer with an available WEB_PORT.\"\"\" for","Authorization Code (that we will exchange for an access token) or the cancellation","'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code'","request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an authorization code!')","threading import Lock import time try: from StringIO import StringIO except ImportError: from","has the required scopes, we will return it. This function will return a","cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with web services relying on OpenID Connect. :param","= self._get_token_with_scopes(scopes) if token: # If we had a valid token, use that","with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token =","be held by anyone. :param uuid: UUID of the token to be removed","None if self._retrieved_code is False: # The user cancelled the request self._retrieved_code =","toupdate: Dict indicating which fields need to be updated \"\"\" self.debug('Updating token %s","and this is a retry. Report error self.report_token_issue() return resp else: return resp","a new token with the current scopeset if we do not already have","the token. # refresh_token: The token we can use to refresh the access","part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return","= self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if","# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER","specific scopes. This function will block until a token is retrieved if requested.","new access token. If it did not work, we will return None and","If not provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory in which to","`auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for this call.","responsible for either removing the token if it could not be refreshed or","off their browser. This URL will be the Authorization endpoint of the IdP","been revoked by the user or expired. In that case, you will want","def get_token(self, scopes, new_token=True): \"\"\"Function to retrieve tokens with specific scopes. This function","notice shall be included in # all copies or substantial portions of the","None # TODO: Make cache_lock a filesystem lock so we also lock across","we had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None,","self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp =","across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = []","This is a token that may or may not still be valid self.debug('Possible')","user a URL, or if possible, kick off their browser. This URL will","Token value # token_type: Token type. Currently supported: \"Bearer\" # expires_at: Token expiration","NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY","resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time()","were found \"\"\" possible_token = None self.debug('Trying to get token with scopes %s',","urlencode except ImportError: from urllib.parse import urlencode from uuid import uuid4 as uuidgen","returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] #","for applications relying on OpenID Connect for authentication.\"\"\" from __future__ import print_function from","tokens were found \"\"\" possible_token = None self.debug('Trying to get token with scopes","since if we already have a token with the current app_identifier that has","with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else:","the cached token to attempt to refresh. :rtype: bool :returns: True if the","self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id","if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue","json import logging from threading import Lock import time try: from StringIO import","return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache from the cache","= ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method',","try: from StringIO import StringIO except ImportError: from io import StringIO import socket","requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable","report token issues on 401. This helps with broken apps that may send","False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error with the last token that","= True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make an python-requests POST request.","urllib.parse import urlencode from uuid import uuid4 as uuidgen import webbrowser from wsgiref","if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None else: token","% self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. Requires","either an Authorization Code (that we will exchange for an access token) or","in which to store the token caches. Will be put through expanduer. Default","dict # This dict contains uuid: token pairs # Every \"token\" object is","expired. In that case, you will want to call report_token_issue() to try to","to get the cache file name for the current client. This assures that","token # access_token: Token value # token_type: Token type. Currently supported: \"Bearer\" #","cache lock is held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def","return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type']","None :returns: String bearer token if possible or None \"\"\" if not isinstance(scopes,","else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache for any","the requested scopes. It will prefer to return tokens whose expires_at is still","on 401. This helps with broken apps that may send a 401 return","False, will not try to automatically report token issues on 401. This helps","server = self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate a","token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None","we also lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache()","a request for our client_id to get a new token with the specified","self.problem_reported = False self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock","it might be refreshable. :param scopes: List of scopes that need to be","cache file name for the current client. This assures that whenever this file","False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None else:","'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a token to the cache","The HTTP method to use, defaults to POST.. \"\"\" ckwargs = copy(kwargs) scopes","uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid,","OpenID Connect for authentication.\"\"\" from __future__ import print_function from copy import copy import","able to # refresh the token. # refresh_token: The token we can use","new token with the specified scopes. The webserver will then need to catch","ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT,","for the current client. :kwarg new_token: If True, we will actively request the","self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if 'json' in ckwargs:","with self._cache_lock: self.__refresh_cache() def __write_cache(self): \"\"\"Wirtes self._cache to cache on disk. Requires cache_lock","Lock import time try: from StringIO import StringIO except ImportError: from io import","in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not in","disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if","may not be held by anyone. :param uuid: UUID of the token to","uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an","not be held by anyone. :param uuid: UUID of the token to be","file name for the current client. This assures that whenever this file is","self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make an python-requests POST request. Allarguments and keyword","'python-openid-client/%s' % \\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported","returns a SimpleServer with an available WEB_PORT.\"\"\" for port in WEB_PORTS: try: server","False return token[1]['access_token'] elif not new_token: return None # We did not have","token. # refresh_token: The token we can use to refresh the access token","method to use, defaults to POST.. \"\"\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes')","None \"\"\" if not isinstance(scopes, list): raise ValueError('Scopes must be a list') token","to next one continue def _get_new_token(self, scopes): \"\"\"This function kicks off some magic.","None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported =","OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and return to the","put through expanduer. Default is ~/.openidc. If this does not exist and we","be a list') token = self._get_token_with_scopes(scopes) if token: # If we had a","token: it might be refreshable. :param scopes: List of scopes that need to","hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False","to the following conditions: # # The above copyright notice and this permission","import logging from threading import Lock import time try: from StringIO import StringIO","message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and return","secrets rather than Authorization header :kwarg client_id: The Client Identifier used to request","self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \"\"\"Updates a token in the cache.","scopes): \"\"\"Searches the cache for any tokens that have the requested scopes. It","is a json dict with the following keys: # idp: The URL of","the last token that was returned. This will attempt to renew the token","Every app id has its own token cache # The token cache is","such tokens exist it will return the possibly expired token: it might be","apps that may send a 401 return code in incorrect cases. :kwargs http_method:","magic. We will start a new webserver on one of the WEB_PORTS, and","self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of","it has expired, we might still be able to # refresh the token.","token # scopes: A list of scopes that we had requested with the","of the identity provider to get tokens from :param id_provider_mapping: Mapping with URLs","True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if","rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' %","in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token = {'access_token':","openidc_client import release # The ports that we will try to use for","will be requested unless nonblocking is True. :kwarg new_token: If True, we will","python-requests POST request. Allarguments and keyword arguments are like the arguments to requests,","is touched, the cache lock is held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json'","self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for %s'","Software is # furnished to do so, subject to the following conditions: #","# -*- coding: utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat,","os try: from urllib import urlencode except ImportError: from urllib.parse import urlencode from","use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with web services relying on OpenID","if no such tokens exist it will return the possibly expired token: it","io import StringIO import socket import os try: from urllib import urlencode except","(self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request()","may not be held by anyone. :param token: UUID of the token to","the cache if renewal was succesful. :param uuid: The UUID of the cached","may or may not still be valid self.debug('Possible') possible_token = (uuid, token) if","Will be put through expanduer. Default is ~/.openidc. If this does not exist","'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s","list of scopes required for the current client. :kwarg new_token: If True, we","(or we got another error), we will return None. \"\"\" def _token_app(environ, start_response):","_add_token(self, token): \"\"\"Adds a token to the cache and writes cache to disk.","that we had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id,","wsgiref import simple_server import requests import sys from openidc_client import release # The",":kwargs printfd: The File object to print token instructions to. \"\"\" self.logger =","= ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode']","Exception('Cannot report issue before requesting token') if self.problem_reported: # We were reported an","use, defaults to POST.. \"\"\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token =","self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on","# This is a token that may or may not still be valid","is still before the current time, but if no such tokens exist it","token that was returned. This will attempt to renew the token that was","with a request for our client_id to get a new token with the","{'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp =","= None self.problem_reported = False self.token_to_try = None self._retrieved_code = None # TODO:","f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens',","store the new token in the local cache, add it to the valid","try to use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): #","issue before requesting token') if self.problem_reported: # We were reported an issue before.","cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with","and then return the UUID. If the user cancelled (or we got another","if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile,","the token was valid but your request failed due to a server error","one will be requested unless nonblocking is True. :kwarg new_token: If True, we","resp else: return resp @property def _cachefile(self): \"\"\"Property to get the cache file","use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret","self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\","was already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache for any tokens that","caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as","Currently supported: \"Bearer\" # expires_at: Token expiration UTC time. NOTE: Even if the","to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'],","in split]) if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description'))","copy import json import logging from threading import Lock import time try: from","This function will block until a token is retrieved if requested. It is","can use to refresh the access token # scopes: A list of scopes","self._get_token_with_scopes(scopes) if token: # If we had a valid token, use that self.last_returned_uuid","to try to renew the token or delete the token. :kwarg scopes: A","possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \"\"\"Returns the IdP URL","if not token: return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot","self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret","with either an Authorization Code (that we will exchange for an access token)","# over any others we have self.debug('Not yet expired, returning') return uuid, token","added to the cache \"\"\" uuid = uuidgen().hex self.debug('Adding token %s to cache',","with the client_id. May be None if your IdP does not require you","use. If not provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory in which","in ckwargs: raise ValueError('Cannot provide json in a post call') if method not","have the requested scopes. It will prefer to return tokens whose expires_at is",":returns: The IdP URL \"\"\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method]","WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT","need to catch the return with either an Authorization Code (that we will","OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN","a list') token = self._get_token_with_scopes(scopes) if token: # If we had a valid","self.debug('Not yet expired, returning') return uuid, token # This is a token that","THE # SOFTWARE. \"\"\"Client for applications relying on OpenID Connect for authentication.\"\"\" from","kicks off some magic. We will start a new webserver on one of","case, you will want to call report_token_issue() to try to renew the token","ckwargs: raise ValueError('Cannot provide json in a post call') if method not in","None self._retrieved_code = None # TODO: Make cache_lock a filesystem lock so we","use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the","function kicks off some magic. We will start a new webserver on one","= json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache from the","= None resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization code:","the following conditions: # # The above copyright notice and this permission notice","authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if","identity provider to get tokens from :param id_provider_mapping: Mapping with URLs to use","token[1]['access_token'] elif not new_token: return None # We did not have a valid","= query.split('&') kv = dict([v.split('=', 1) for v in split]) if 'error' in","LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND","may have been revoked by # the user! Also, even if it has","@property def _cachefile(self): \"\"\"Property to get the cache file name for the current","f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a token to the cache and writes cache","rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #","if possible, kick off their browser. This URL will be the Authorization endpoint","# We were reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid)","attempt to refresh. :rtype: bool :returns: True if the token was succesfully refreshed,","scopes, new_token=True): \"\"\"Function to retrieve tokens with specific scopes. This function will block","self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type':","header :kwarg client_id: The Client Identifier used to request credentials :kwarg client_secret: The","succesfully refreshed, False otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data","%s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): #","rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url","import socket import os try: from urllib import urlencode except ImportError: from urllib.parse","OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING","A list of scopes that we had requested with the token def __init__(self,","self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not token: return None","client secrets rather than Authorization header :kwarg client_id: The Client Identifier used to","new token with the current scopeset if we do not already have on.","= requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry: if not","to do so, subject to the following conditions: # # The above copyright","= 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit","token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret:","a token in the cache. cache_lock may not be held by anyone. :param","uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone')","to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required.","of the token to be added to the cache \"\"\" uuid = uuidgen().hex","to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not","from io import StringIO import socket import os try: from urllib import urlencode","by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w')","for the current client. This assures that whenever this file is touched, the","\"\"\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache()","= self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping =","= client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\ release.VERSION","self.debug('Trying to get token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking","expires_at is still before the current time, but if no such tokens exist","token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry:","bool :returns: True if the token was succesfully refreshed, False otherwise \"\"\" oldtoken","StringIO import socket import os try: from urllib import urlencode except ImportError: from","token # This is a token that may or may not still be","OTHER DEALINGS IN THE # SOFTWARE. \"\"\"Client for applications relying on OpenID Connect","open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read())","token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client","if not server: raise Exception('We were unable to instantiate a webserver') return_uri =","self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope:","self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache from","self.report_token_issue() return resp else: return resp @property def _cachefile(self): \"\"\"Property to get the","the cache. If you get an indication from your application that the token","self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for %s' % method)","return a bearer token or None. Note that the bearer token might have","we can use to refresh the access token # scopes: A list of","'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk.","without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense,","# expires_at: Token expiration UTC time. NOTE: Even if the expires_at # indicates","= self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def","return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \"\"\"Removes a token from","self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \"\"\"Updates a","requested method. :param method: The method name in the IdP mapping dict. :rtype:","authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at':","\"secret\" that goes with the client_id. May be None if your IdP does","server: raise Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' %","of retrieved tokens :param id_provider: URL of the identity provider to get tokens","data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json()","self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate a webserver') return_uri","The ports that we will try to use for our webserver WEB_PORTS =","permission notice shall be included in # all copies or substantial portions of","ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs:","before requesting token') if self.problem_reported: # We were reported an issue before. Let's","and not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not","json serialized dict # This dict contains uuid: token pairs # Every \"token\"","def _get_new_token(self, scopes): \"\"\"This function kicks off some magic. We will start a","\"\"\"This function returns a SimpleServer with an available WEB_PORT.\"\"\" for port in WEB_PORTS:","the new token in the local cache, add it to the valid cache,","self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported: # We were","None self.debug('User cancelled') return None self.debug('We got an authorization code!') data = {'client_id':","is held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes","not be held by anyone. :param token: UUID of the token to be","None server = self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate","issued the token # sub: The subject that owns the token # access_token:","None. \"\"\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv =","toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache()","IdP does not require you to use a secret. :kwarg useragent: Useragent string","cancellation message. This function will store the new token in the local cache,","the expires_at # indicates the token should still be valid, it may have","Mapping did not include path for %s' % method) def _refresh_token(self, uuid): \"\"\"Tries","the token. :kwarg scopes: A list of scopes required for the current client.","by anyone. :param token: UUID of the token to be updated :param toupdate:","\"\"\"Make an python-requests POST request. Allarguments and keyword arguments are like the arguments","scopes that we had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping,","def __refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. Requires cache_lock to","a token from the cache and writes cache to disk. cache_lock may not","self._retrieved_code = None # TODO: Make cache_lock a filesystem lock so we also","did not work, we will return None and remove this token from the","method. :param method: The method name in the IdP mapping dict. :rtype: string","resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry: if","# This dict contains uuid: token pairs # Every \"token\" object is a","method name in the IdP mapping dict. :rtype: string :returns: The IdP URL","if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did","shall be included in # all copies or substantial portions of the Software.","our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens:","the cache lock is held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id)","True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True","new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry","endpoints on the IdP. :kwarg use_post: Whether to use POST submission of client","work. Switch to next one continue def _get_new_token(self, scopes): \"\"\"This function kicks off","from wsgiref import simple_server import requests import sys from openidc_client import release #","or token was lacking specific permissions. \"\"\" if not self.last_returned_uuid: raise Exception('Cannot report","requested scopes. It will prefer to return tokens whose expires_at is still before","return the UUID. If the user cancelled (or we got another error), we","None self.debug('Trying to get token with scopes %s', scopes) for uuid in self._cache:","modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and","ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES","if 'json' in ckwargs: raise ValueError('Cannot provide json in a post call') if","which to store the token caches. Will be put through expanduer. Default is","This assures that whenever this file is touched, the cache lock is held","held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes the","logging from threading import Lock import time try: from StringIO import StringIO except","we already have a token with the current app_identifier that has the required","call report_token_issue() to try to renew the token or delete the token. :kwarg","publish, distribute, sublicense, and/or sell # copies of the Software, and to permit","We will start a new webserver on one of the WEB_PORTS, and then","rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please","%s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and","self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def","import print_function from copy import copy import json import logging from threading import","%s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is","for any tokens that have the requested scopes. It will prefer to return","%s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a token","have on. :kwarg auto_refresh: If False, will not try to automatically report token","a URL, or if possible, kick off their browser. This URL will be","or because the account or token was lacking specific permissions. \"\"\" if not","if token: # If we had a valid token, use that self.last_returned_uuid =","is required. :kwarg scopes: Scopes required for this call. If a token is","None if no applicable tokens were found \"\"\" possible_token = None self.debug('Trying to","import release # The ports that we will try to use for our","ImportError: from urllib.parse import urlencode from uuid import uuid4 as uuidgen import webbrowser","If you get an indication from your application that the token you sent","File object to print token instructions to. \"\"\" self.logger = logging.getLogger(__name__) self.debug =","= use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret =","that the token you sent was invalid, you should call it. You should","False self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock a filesystem","thrown. :kwargs printfd: The File object to print token instructions to. \"\"\" self.logger","URL \"\"\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp","user cancelled the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got","cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens',","then return the UUID. If the user cancelled (or we got another error),","we do not already have on. :rtype: string or None :returns: String bearer","want to call report_token_issue() to try to renew the token or delete the","%s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret']","be in the returned token :rtype: (string, dict) or None :returns: Token UUID","updated \"\"\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock:","need to be updated \"\"\" self.debug('Updating token %s in cache, fields %s', uuid,","'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def","AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR","anyone. :param uuid: UUID of the token to be removed from cache \"\"\"","try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port","simple_server import requests import sys from openidc_client import release # The ports that","defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory in which to store the token","def _update_token(self, uuid, toupdate): \"\"\"Updates a token in the cache. cache_lock may not","to be removed from cache \"\"\" self.debug('Removing token %s from cache', uuid) with","get token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid)","def _idp_url(self, method): \"\"\"Returns the IdP URL for the requested method. :param method:","\"\"\"Searches the cache for any tokens that have the requested scopes. It will","if not isinstance(scopes, list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes)","and return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not","self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp')","refresh the access token # scopes: A list of scopes that we had","to refresh. :rtype: bool :returns: True if the token was succesfully refreshed, False","self._retrieved_code = kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return","will not try to automatically report token issues on 401. This helps with","that case, you will want to call report_token_issue() to try to renew the","self.useragent = useragent or 'python-openid-client/%s' % \\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc')","invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd","is always safe to call this though, since if we already have a","TODO: Make cache_lock a filesystem lock so we also lock across # multiple","unless nonblocking is True. :kwarg new_token: If True, we will actively request the","to use, defaults to POST.. \"\"\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token","self.debug('Error exchanging authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token':","use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token:","Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free of charge, to","will return a bearer token or None. Note that the bearer token might","< time.time(): # This is a token that's supposed to still be valid,","ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True token = self.token_to_try","with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def","may not still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning","self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f:","# in the Software without restriction, including without limitation the rights # to","renewal was succesful. :param uuid: The UUID of the cached token to attempt","will then need to catch the return with either an Authorization Code (that","Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free of charge,","`scopes` is required. :kwarg scopes: Scopes required for this call. If a token","os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with","is retrieved if requested. It is always safe to call this though, since","self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401:","import uuid4 as uuidgen import webbrowser from wsgiref import simple_server import requests import","the access token # scopes: A list of scopes that we had requested","in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include","json in a post call') if method not in ['POST']: raise ValueError('Cannot use","# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS","of the IdP with a request for our client_id to get a new","uuid): \"\"\"Removes a token from the cache and writes cache to disk. cache_lock","safe to call this though, since if we already have a token with","True. :kwarg new_token: If True, we will actively request the user to get","the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an authorization","a valid token, now comes the hard part... uuid = self._get_new_token(scopes) if uuid:","not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return","be refreshed or saving the cache if renewal was succesful. :param uuid: The","scopes): \"\"\"This function kicks off some magic. We will start a new webserver","# scopes: A list of scopes that we had requested with the token","!= self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset","data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in resp: self.debug('Error","{} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if","if the token was succesfully refreshed, False otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing","AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE","the self._cache from the cache on disk. Requires cache_lock to be held by",":kwarg new_token: If True, we will actively request the user to get a","token = self._get_token_with_scopes(scopes) if token: # If we had a valid token, use","of the token to be removed from cache \"\"\" self.debug('Removing token %s from","the user to get a new token with the current scopeset if we","not already have on. :rtype: string or None :returns: String bearer token if","this token from the cache. If you get an indication from your application","require you to use a secret. :kwarg useragent: Useragent string to use. If","CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server: raise Exception('We were","cache to disk. cache_lock may not be held by anyone. :param uuid: UUID","The webserver will then need to catch the return with either an Authorization","token. :kwarg scopes: A list of scopes required for the current client. :kwarg","token: return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json","= self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return","will be the Authorization endpoint of the IdP with a request for our","indicating which fields need to be updated \"\"\" self.debug('Updating token %s in cache,","the current time, but if no such tokens exist it will return the","or the cancellation message. This function will store the new token in the","oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status()","-*- # # Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat","get a new token with the current scopeset if we do not already","List of scopes that need to be in the returned token :rtype: (string,","refresh a token and put the refreshed token in self._cache The caller is","WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO","that need to be in the returned token :rtype: (string, dict) or None","The client \"secret\" that goes with the client_id. May be None if your","in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect","request failed due to a server error or because the account or token","may send a 401 return code in incorrect cases. :kwargs http_method: The HTTP","over any others we have self.debug('Not yet expired, returning') return uuid, token #","= resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return","supported: \"Bearer\" # expires_at: Token expiration UTC time. NOTE: Even if the expires_at","COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER","cache for any tokens that have the requested scopes. It will prefer to","data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret","ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code","time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \"\"\"This","we will try to use for our webserver WEB_PORTS = [12345, 23456] class","kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return a","the valid cache, and then return the UUID. If the user cancelled (or","raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token: # If",":param id_provider_mapping: Mapping with URLs to use for specific endpoints on the IdP.","object is a json dict with the following keys: # idp: The URL","the possibly expired token: it might be refreshable. :param scopes: List of scopes","except socket.error: # This port did not work. Switch to next one continue","expiration UTC time. NOTE: Even if the expires_at # indicates the token should","to return tokens whose expires_at is still before the current time, but if","self._cache The caller is responsible for either removing the token if it could","copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED","None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \"\"\"Removes a token from the","required scopes, we will return it. This function will return a bearer token","_delete_token(self, uuid): \"\"\"Removes a token from the cache and writes cache to disk.","scopes required for the current client. :kwarg new_token: If True, we will actively","token you sent was invalid, you should call it. You should explicitly NOT","disk. Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with","SOFTWARE. \"\"\"Client for applications relying on OpenID Connect for authentication.\"\"\" from __future__ import","token might have been revoked by the user or expired. In that case,","WEB_PORTS, and then either show the user a URL, or if possible, kick","%s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not","if method not in ['POST']: raise ValueError('Cannot use POST tokens in %s method'","list') token = self._get_token_with_scopes(scopes) if token: # If we had a valid token,","an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result =","token cache # The token cache is a json serialized dict # This","the cache. cache_lock may not be held by anyone. :param token: UUID of","'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to","Permission is hereby granted, free of charge, to any person obtaining a copy","in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token':","id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with web services","cancelled (or we got another error), we will return None. \"\"\" def _token_app(environ,","IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT","useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with web services relying on OpenID Connect.","Software without restriction, including without limitation the rights # to use, copy, modify,","from the cache. If you get an indication from your application that the","their browser. This URL will be the Authorization endpoint of the IdP with","should explicitly NOT call this function if the token was valid but your","%s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() +","class OpenIDCClient(object): # Internal implementation of tokens: # Every app id has its","Also, even if it has expired, we might still be able to #","resp.status_code == 401 and not is_retry: if not auto_refresh: return resp self.token_to_try =","os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on","THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \"\"\"Client","# The above copyright notice and this permission notice shall be included in","# of this software and associated documentation files (the \"Software\"), to deal #","If it did not work, we will return None and remove this token","scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method =","client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with web services relying","in a post call') if method not in ['POST']: raise ValueError('Cannot use POST","'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token =","UTC time. NOTE: Even if the expires_at # indicates the token should still","WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE.","substantial portions of the Software. # # THE SOFTWARE IS PROVIDED \"AS IS\",","the token if it could not be refreshed or saving the cache if","that the bearer token might have been revoked by the user or expired.","token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not","bearer token might have been revoked by the user or expired. In that","restriction, including without limitation the rights # to use, copy, modify, merge, publish,","expires_at: Token expiration UTC time. NOTE: Even if the expires_at # indicates the","self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return a message start_response('200","scopes: Scopes required for this call. If a token is not present with","cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self,","= {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs)","\"\"\"Refreshes the self._cache from the cache on disk. Requires cache_lock to be held","release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try","already have a token with the current app_identifier that has the required scopes,","uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token",":param token: UUID of the token to be updated :param toupdate: Dict indicating","token, now comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid =","= ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry =","sys from openidc_client import release # The ports that we will try to",":param uuid: The UUID of the cached token to attempt to refresh. :rtype:","need to be in the returned token :rtype: (string, dict) or None :returns:","# the user! Also, even if it has expired, we might still be","for this call. If a token is not present with this token, a","IdP with a request for our client_id to get a new token with","issues on 401. This helps with broken apps that may send a 401","# Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close","any others we have self.debug('Not yet expired, returning') return uuid, token # This","set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a token that's supposed","token to the cache and writes cache to disk. cache_lock may not be","UUID of the cached token to attempt to refresh. :rtype: bool :returns: True","ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method,","if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token","% authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code","for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of","current time, but if no such tokens exist it will return the possibly","may not be held by anyone. :param token: Dict of the token to","this call. If a token is not present with this token, a new","self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path","logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider","the specified scopes. The webserver will then need to catch the return with","block until a token is retrieved if requested. It is always safe to","IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR","def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1)","= uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error with","the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server: raise Exception('We","valid cache, and then return the UUID. If the user cancelled (or we","we are unable to create it, the OSError will be thrown. :kwargs printfd:","None if your IdP does not require you to use a secret. :kwarg","with the current scopeset if we do not already have on. :kwarg auto_refresh:","\"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache","to POST.. \"\"\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True)","OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER","the user! Also, even if it has expired, we might still be able","with the current scopeset if we do not already have on. :rtype: string","return server except socket.error: # This port did not work. Switch to next","app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id","current scopeset if we do not already have on. :rtype: string or None","the bearer token might have been revoked by the user or expired. In","raise Exception('Cannot report issue before requesting token') if self.problem_reported: # We were reported","current scopeset if we do not already have on. :kwarg auto_refresh: If False,","put the refreshed token in self._cache The caller is responsible for either removing","request credentials :kwarg client_secret: The client \"secret\" that goes with the client_id. May","%s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \"\"\"This function returns a SimpleServer with","or None :returns: String bearer token if possible or None \"\"\" if not","# Every \"token\" object is a json dict with the following keys: #","= None # TODO: Make cache_lock a filesystem lock so we also lock","associated documentation files (the \"Software\"), to deal # in the Software without restriction,","def _cachefile(self): \"\"\"Property to get the cache file name for the current client.","return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for","of this software and associated documentation files (the \"Software\"), to deal # in","exist it will return the possibly expired token: it might be refreshable. :param","self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp","pairs # Every \"token\" object is a json dict with the following keys:","'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in","delete the token. :kwarg scopes: A list of scopes required for the current","self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s'","# # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,","except ImportError: from io import StringIO import socket import os try: from urllib","with broken apps that may send a 401 return code in incorrect cases.","The subject that owns the token # access_token: Token value # token_type: Token","return None self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code',","token: # If we had a valid token, use that self.last_returned_uuid = token[0]","if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' %","retrieve tokens with specific scopes. This function will block until a token is","should call it. You should explicitly NOT call this function if the token","report_token_issue(self): \"\"\"Report an error with the last token that was returned. This will","been revoked by # the user! Also, even if it has expired, we","use POST tokens in %s method' % method) if 'data' not in ckwargs:","is ~/.openidc. If this does not exist and we are unable to create","self.problem_reported: # We were reported an issue before. Let's just remove this token.","id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \"\"\"Client for interacting with web","get_token(self, scopes, new_token=True): \"\"\"Function to retrieve tokens with specific scopes. This function will","resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json()","held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir)","to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of","else: return resp @property def _cachefile(self): \"\"\"Property to get the cache file name","of scopes required for the current client. :kwarg new_token: If True, we will","this window and return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app)","specific permissions. \"\"\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token')","if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s","relying on OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens :param","= token else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] =","= return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'),","token with the current app_identifier that has the required scopes, we will return","\"\"\"Adds a token to the cache and writes cache to disk. cache_lock may","EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,","len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a token","the Software without restriction, including without limitation the rights # to use, copy,","ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN","token') return possible_token def _idp_url(self, method): \"\"\"Returns the IdP URL for the requested","2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # #","person obtaining a copy # of this software and associated documentation files (the","if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp","return None # We did not have a valid token, now comes the","server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port did","data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to refresh, error:","token_type: Token type. Currently supported: \"Bearer\" # expires_at: Token expiration UTC time. NOTE:","self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s',","# # Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat Author:","above copyright notice and this permission notice shall be included in # all","token with the specified scopes. The webserver will then need to catch the","self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def","not be refreshed or saving the cache if renewal was succesful. :param uuid:","% method) def _refresh_token(self, uuid): \"\"\"Tries to refresh a token and put the","If the user cancelled (or we got another error), we will return None.","else: token = self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if","= {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp","or may not still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token:","= token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \"\"\"Updates a token in","rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query","goes with the client_id. May be None if your IdP does not require","on the IdP. :kwarg use_post: Whether to use POST submission of client secrets","are like the arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword","persons to whom the Software is # furnished to do so, subject to","method not in ['POST']: raise ValueError('Cannot use POST tokens in %s method' %","POST request. Allarguments and keyword arguments are like the arguments to requests, except","rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri","conditions: # # The above copyright notice and this permission notice shall be","INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A","token # sub: The subject that owns the token # access_token: Token value","del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the","self._cache[uuid]['expires_at']) return True def _get_server(self, app): \"\"\"This function returns a SimpleServer with an","store the token caches. Will be put through expanduer. Default is ~/.openidc. If","OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,","documentation files (the \"Software\"), to deal # in the Software without restriction, including","possibly expired token: it might be refreshable. :param scopes: List of scopes that","report_token_issue() to try to renew the token or delete the token. :kwarg scopes:","cache and writes cache to disk. cache_lock may not be held by anyone.","the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported =","or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED \"AS","uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid]","new one will be requested unless nonblocking is True. :kwarg new_token: If True,","notice and this permission notice shall be included in # all copies or","interacting with web services relying on OpenID Connect. :param app_identifier: Identifier for storage","of charge, to any person obtaining a copy # of this software and","held by anyone. :param token: UUID of the token to be updated :param","applications relying on OpenID Connect for authentication.\"\"\" from __future__ import print_function from copy","new token in the local cache, add it to the valid cache, and","not work. Switch to next one continue def _get_new_token(self, scopes): \"\"\"This function kicks","return ValueError('Idp Mapping did not include path for %s' % method) def _refresh_token(self,","is not None if self._retrieved_code is False: # The user cancelled the request","None :returns: Token UUID and contents or None if no applicable tokens were","\"\"\"This function kicks off some magic. We will start a new webserver on","= requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp:","time.time(): # This is a token that's supposed to still be valid, prefer","refreshed or saving the cache if renewal was succesful. :param uuid: The UUID","tokens: # Every app id has its own token cache # The token","self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was","ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry =","cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self,","included in # all copies or substantial portions of the Software. # #","= self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp","start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and return to","POST.. \"\"\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh","May be None if your IdP does not require you to use a","now comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid","access_token: Token value # token_type: Token type. Currently supported: \"Bearer\" # expires_at: Token","the Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF","cache_lock may not be held by anyone. :param uuid: UUID of the token","self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache()","and associated documentation files (the \"Software\"), to deal # in the Software without","not be held by anyone. :param token: Dict of the token to be","any tokens that have the requested scopes. It will prefer to return tokens","request the user to get a new token with the current scopeset if","useragent or 'python-openid-client/%s' % \\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid =","otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id,","to print token instructions to. \"\"\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id","The directory in which to store the token caches. Will be put through","idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes),",":param method: The method name in the IdP mapping dict. :rtype: string :returns:","in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def","you to use a secret. :kwarg useragent: Useragent string to use. If not","is_retry = True token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes,","LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #","\"\"\"Client for interacting with web services relying on OpenID Connect. :param app_identifier: Identifier","% \\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported =","It is always safe to call this though, since if we already have","on. :kwarg auto_refresh: If False, will not try to automatically report token issues","WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every","= copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True)","\"python-openidc-client/VERSION\" :kwarg cachedir: The directory in which to store the token caches. Will","valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif","to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache))","user cancelled (or we got another error), we will return None. \"\"\" def","helps with broken apps that may send a 401 return code in incorrect","resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s',","# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR","'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE! \\o/ return","= self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not token:","% (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url)","OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE","requests import sys from openidc_client import release # The ports that we will","required for the current client. :kwarg new_token: If True, we will actively request","assert self._retrieved_code is not None if self._retrieved_code is False: # The user cancelled","either removing the token if it could not be refreshed or saving the","resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes}","by the user or expired. In that case, you will want to call","uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until","self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or","possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self,","token was lacking specific permissions. \"\"\" if not self.last_returned_uuid: raise Exception('Cannot report issue","None resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s',","the current client. This assures that whenever this file is touched, the cache","client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\ release.VERSION self.cachedir","work, we will return None and remove this token from the cache. If","# We did not have a valid token, now comes the hard part...","# The token cache is a json serialized dict # This dict contains","a retry. Report error self.report_token_issue() return resp else: return resp @property def _cachefile(self):","of the Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY","call. If a token is not present with this token, a new one","defaults to POST.. \"\"\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token',","returned. If that worked, we will return the new access token. If it","self._retrieved_code = None server = self._get_server(_token_app) if not server: raise Exception('We were unable","\"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type':","will prefer to return tokens whose expires_at is still before the current time,","will actively request the user to get a new token with the current","the IdP URL for the requested method. :param method: The method name in","not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if","last returned. If that worked, we will return the new access token. If","the arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes`","%s method' % method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token']","None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in a","= False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None","self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report an error","token that's supposed to still be valid, prefer it # over any others","Dict of the token to be added to the cache \"\"\" uuid =","a filesystem lock so we also lock across # multiple invocations self._cache_lock =","f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache","uuidgen import webbrowser from wsgiref import simple_server import requests import sys from openidc_client","held by anyone. :param uuid: UUID of the token to be removed from","Token type. Currently supported: \"Bearer\" # expires_at: Token expiration UTC time. NOTE: Even","tokens with specific scopes. This function will block until a token is retrieved","resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False","id_provider: URL of the identity provider to get tokens from :param id_provider_mapping: Mapping","token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return","if it has expired, we might still be able to # refresh the","or None :returns: Token UUID and contents or None if no applicable tokens","= None self.debug('User cancelled') return None self.debug('We got an authorization code!') data =","self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp","\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False","token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not","Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this","and we are unable to create it, the OSError will be thrown. :kwargs","to store the token caches. Will be put through expanduer. Default is ~/.openidc.","sent was invalid, you should call it. You should explicitly NOT call this","ValueError('Cannot use POST tokens in %s method' % method) if 'data' not in","or if possible, kick off their browser. This URL will be the Authorization","%s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid","the user cancelled (or we got another error), we will return None. \"\"\"","self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping","not already have on. :kwarg auto_refresh: If False, will not try to automatically","not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp","= False self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock a","v in split]) if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'],","possible, kick off their browser. This URL will be the Authorization endpoint of","self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None else: token =","# Internal implementation of tokens: # Every app id has its own token","2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission","in # all copies or substantial portions of the Software. # # THE","SimpleServer with an available WEB_PORT.\"\"\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0',","method' % method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] =","dict contains uuid: token pairs # Every \"token\" object is a json dict","\"\"\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping","# The user cancelled the request self._retrieved_code = None self.debug('User cancelled') return None","visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code","useragent: Useragent string to use. If not provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir:","string :returns: The IdP URL \"\"\" if method in self.idp_mapping: return self.idp +","= urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant","return [u'You can close this window and return to the CLI'.encode('ascii')] self._retrieved_code =","self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri,","fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return","not exist and we are unable to create it, the OSError will be","The method name in the IdP mapping dict. :rtype: string :returns: The IdP","cache \"\"\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid","with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None,","free of charge, to any person obtaining a copy # of this software","import sys from openidc_client import release # The ports that we will try","\"\"\"Client for applications relying on OpenID Connect for authentication.\"\"\" from __future__ import print_function","self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent","token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \"\"\"Returns the","# refresh the token. # refresh_token: The token we can use to refresh","we do not already have on. :kwarg auto_refresh: If False, will not try","refresh. :rtype: bool :returns: True if the token was succesfully refreshed, False otherwise","show the user a URL, or if possible, kick off their browser. This","new_token=True): \"\"\"Function to retrieve tokens with specific scopes. This function will block until","with the current app_identifier that has the required scopes, we will return it.","This URL will be the Authorization endpoint of the IdP with a request","= None else: token = self.get_token(scopes, new_token=new_token) if not token: return None if","StringIO import StringIO except ImportError: from io import StringIO import socket import os","present with this token, a new one will be requested unless nonblocking is","cache_lock may not be held by anyone. :param token: UUID of the token","webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False: #","from __future__ import print_function from copy import copy import json import logging from","provider to get tokens from :param id_provider_mapping: Mapping with URLs to use for","webserver will then need to catch the return with either an Authorization Code","not server: raise Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/'","we got another error), we will return None. \"\"\" def _token_app(environ, start_response): query","not work, we will return None and remove this token from the cache.","\"\"\"Returns the IdP URL for the requested method. :param method: The method name","uuid): \"\"\"Tries to refresh a token and put the refreshed token in self._cache","if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: #","off some magic. We will start a new webserver on one of the","for our client_id to get a new token with the specified scopes. The","oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token',",":kwarg client_id: The Client Identifier used to request credentials :kwarg client_secret: The client","uuid: UUID of the token to be removed from cache \"\"\" self.debug('Removing token","This port did not work. Switch to next one continue def _get_new_token(self, scopes):","THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN","with web services relying on OpenID Connect. :param app_identifier: Identifier for storage of","__write_cache(self): \"\"\"Wirtes self._cache to cache on disk. Requires cache_lock to be held by","return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported","tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a","authentication.\"\"\" from __future__ import print_function from copy import copy import json import logging","FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #","SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES","time. NOTE: Even if the expires_at # indicates the token should still be","authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if","Software, and to permit persons to whom the Software is # furnished to","USE OR OTHER DEALINGS IN THE # SOFTWARE. \"\"\"Client for applications relying on","valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token","which fields need to be updated \"\"\" self.debug('Updating token %s in cache, fields","did not include path for %s' % method) def _refresh_token(self, uuid): \"\"\"Tries to","toupdate): \"\"\"Updates a token in the cache. cache_lock may not be held by","to get tokens from :param id_provider_mapping: Mapping with URLs to use for specific","Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>>","= False return token[1]['access_token'] elif not new_token: return None # We did not","This is a token that's supposed to still be valid, prefer it #","except ImportError: from urllib.parse import urlencode from uuid import uuid4 as uuidgen import","the following keys: # idp: The URL of the idp that issued the","token was succesfully refreshed, False otherwise \"\"\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s',","from uuid import uuid4 as uuidgen import webbrowser from wsgiref import simple_server import","be able to # refresh the token. # refresh_token: The token we can","token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches","The user cancelled the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We","an indication from your application that the token you sent was invalid, you","with the last token that was returned. This will attempt to renew the","caches. Will be put through expanduer. Default is ~/.openidc. If this does not","contains uuid: token pairs # Every \"token\" object is a json dict with","None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make an","%s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if","Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery","# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,","**kwargs) elif resp.status_code == 401: # We got a 401 and this is","token if possible or None \"\"\" if not isinstance(scopes, list): raise ValueError('Scopes must","remove this token from the cache. If you get an indication from your","We were reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return","token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return None # We","self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got","The token cache is a json serialized dict # This dict contains uuid:","webserver on one of the WEB_PORTS, and then either show the user a","and then either show the user a URL, or if possible, kick off","will want to call report_token_issue() to try to renew the token or delete","return resp else: return resp @property def _cachefile(self): \"\"\"Property to get the cache","to renew the token that was last returned. If that worked, we will","and writes cache to disk. cache_lock may not be held by anyone. :param","token, use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not","keyword arguments are like the arguments to requests, except for `scopes`, `new_token` and","still be valid, prefer it # over any others we have self.debug('Not yet",":param uuid: UUID of the token to be removed from cache \"\"\" self.debug('Removing","port, app) return server except socket.error: # This port did not work. Switch","mapping dict. :rtype: string :returns: The IdP URL \"\"\" if method in self.idp_mapping:","'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data)","whose expires_at is still before the current time, but if no such tokens","in the Software without restriction, including without limitation the rights # to use,","to use. If not provided, defaults to \"python-openidc-client/VERSION\" :kwarg cachedir: The directory in","be held by anyone. :param token: Dict of the token to be added","auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try:","PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS","to request credentials :kwarg client_secret: The client \"secret\" that goes with the client_id.","the token # sub: The subject that owns the token # access_token: Token","had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False,","resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in resp: self.debug('Error exchanging","token instructions to. \"\"\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier","The URL of the idp that issued the token # sub: The subject","possible token') return possible_token def _idp_url(self, method): \"\"\"Returns the IdP URL for the","is a token that's supposed to still be valid, prefer it # over","local cache, add it to the valid cache, and then return the UUID.","will return the new access token. If it did not work, we will","exist and we are unable to create it, the OSError will be thrown.","not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w')",":param token: Dict of the token to be added to the cache \"\"\"","cache is a json serialized dict # This dict contains uuid: token pairs","not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r')","anyone. :param token: UUID of the token to be updated :param toupdate: Dict","requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry: if not auto_refresh:","= self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing","should still be valid, it may have been revoked by # the user!",":kwarg scopes: Scopes required for this call. If a token is not present","like the arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments.","error self.report_token_issue() return resp else: return resp @property def _cachefile(self): \"\"\"Property to get","NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE","token that was last returned. If that worked, we will return the new","method): \"\"\"Returns the IdP URL for the requested method. :param method: The method","of the WEB_PORTS, and then either show the user a URL, or if","cache, add it to the valid cache, and then return the UUID. If","MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL","it, the OSError will be thrown. :kwargs printfd: The File object to print","to be updated :param toupdate: Dict indicating which fields need to be updated","call this function if the token was valid but your request failed due","Client Identifier used to request credentials :kwarg client_secret: The client \"secret\" that goes","yet expired, returning') return uuid, token # This is a token that may","if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code =","token is not present with this token, a new one will be requested","and/or sell # copies of the Software, and to permit persons to whom","# multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd","will start a new webserver on one of the WEB_PORTS, and then either","a token with the current app_identifier that has the required scopes, we will","it could not be refreshed or saving the cache if renewal was succesful.","for storage of retrieved tokens :param id_provider: URL of the identity provider to","tokens :param id_provider: URL of the identity provider to get tokens from :param","'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded","self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache for any tokens","error), we will return None. \"\"\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split","True if the token was succesfully refreshed, False otherwise \"\"\" oldtoken = self._cache[uuid]","app id has its own token cache # The token cache is a","uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token']","the UUID. If the user cancelled (or we got another error), we will","own token cache # The token cache is a json serialized dict #","TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE","return with either an Authorization Code (that we will exchange for an access","continue def _get_new_token(self, scopes): \"\"\"This function kicks off some magic. We will start","for either removing the token if it could not be refreshed or saving","for the requested method. :param method: The method name in the IdP mapping","you get an indication from your application that the token you sent was","if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp","tokens exist it will return the possibly expired token: it might be refreshable.","# # The above copyright notice and this permission notice shall be included","\"Software\"), to deal # in the Software without restriction, including without limitation the","close this window and return to the CLI'.encode('ascii')] self._retrieved_code = None server =","last token that was returned. This will attempt to renew the token that","caller is responsible for either removing the token if it could not be","the cache and writes cache to disk. cache_lock may not be held by","be put through expanduer. Default is ~/.openidc. If this does not exist and","of the token to be updated :param toupdate: Dict indicating which fields need","be updated \"\"\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with",":rtype: string :returns: The IdP URL \"\"\" if method in self.idp_mapping: return self.idp","have self.debug('Not yet expired, returning') return uuid, token # This is a token","Note that the bearer token might have been revoked by the user or","scopes. The webserver will then need to catch the return with either an","[('Content-Type', 'text/plain')]) return [u'You can close this window and return to the CLI'.encode('ascii')]","self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file')","self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def","if it could not be refreshed or saving the cache if renewal was","This will attempt to renew the token that was last returned. If that","possible or None \"\"\" if not isinstance(scopes, list): raise ValueError('Scopes must be a","self.problem_reported = False return token[1]['access_token'] elif not new_token: return None # We did","IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR","self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a 401 and this","token :rtype: (string, dict) or None :returns: Token UUID and contents or None","uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache()","assures that whenever this file is touched, the cache lock is held \"\"\"","to attempt to refresh. :rtype: bool :returns: True if the token was succesfully","urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization'","distribute, sublicense, and/or sell # copies of the Software, and to permit persons","printfd: The File object to print token instructions to. \"\"\" self.logger = logging.getLogger(__name__)","that may or may not still be valid self.debug('Possible') possible_token = (uuid, token)","the IdP. :kwarg use_post: Whether to use POST submission of client secrets rather","if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \"\"\"Report","endpoint of the IdP with a request for our client_id to get a","= printfd def get_token(self, scopes, new_token=True): \"\"\"Function to retrieve tokens with specific scopes.",":param scopes: List of scopes that need to be in the returned token","'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False","Requires cache_lock to be held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with %i","Connect for authentication.\"\"\" from __future__ import print_function from copy import copy import json","writes cache to disk. cache_lock may not be held by anyone. :param token:","WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO","account or token was lacking specific permissions. \"\"\" if not self.last_returned_uuid: raise Exception('Cannot","is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return","with URLs to use for specific endpoints on the IdP. :kwarg use_post: Whether","uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate)","WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED","we will return it. This function will return a bearer token or None.","if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in a post","that have the requested scopes. It will prefer to return tokens whose expires_at","grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None","OSError will be thrown. :kwargs printfd: The File object to print token instructions","to disk. cache_lock may not be held by anyone. :param token: Dict of","\"\"\"Refreshes the self._cache from the cache on disk. cache_lock may not be held","Connect. :param app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL of","def _add_token(self, token): \"\"\"Adds a token to the cache and writes cache to","it will return the possibly expired token: it might be refreshable. :param scopes:","%i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds","ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers']","specific endpoints on the IdP. :kwarg use_post: Whether to use POST submission of","not still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible","None self.problem_reported = False self.token_to_try = None self._retrieved_code = None # TODO: Make","touched, the cache lock is held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' %",":returns: Token UUID and contents or None if no applicable tokens were found","app_identifier that has the required scopes, we will return it. This function will","not isinstance(scopes, list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if","portions of the Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT","the returned token :rtype: (string, dict) or None :returns: Token UUID and contents","return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \"\"\"Make an python-requests POST request. Allarguments and","do so, subject to the following conditions: # # The above copyright notice","until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \"\"\"This function returns a SimpleServer","might be refreshable. :param scopes: List of scopes that need to be in","expired token: it might be refreshable. :param scopes: List of scopes that need","port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error:","if the expires_at # indicates the token should still be valid, it may","lock is held \"\"\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self):","not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This","ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization']","None and remove this token from the cache. If you get an indication","permit persons to whom the Software is # furnished to do so, subject","= app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id =","was last returned. If that worked, we will return the new access token.","held by caller.\"\"\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile,","tokens that have the requested scopes. It will prefer to return tokens whose","did not work. Switch to next one continue def _get_new_token(self, scopes): \"\"\"This function","# TODO: Make cache_lock a filesystem lock so we also lock across #","(uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \"\"\"Returns","Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission is","a 401 and this is a retry. Report error self.report_token_issue() return resp else:","If True, we will actively request the user to get a new token","split]) if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code","# refresh_token: The token we can use to refresh the access token #","expired, returning') return uuid, token # This is a token that may or","= self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if 'json' in","self.__write_cache() return uuid def _delete_token(self, uuid): \"\"\"Removes a token from the cache and","= self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token':","uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not","will return None. \"\"\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&')","import StringIO import socket import os try: from urllib import urlencode except ImportError:","cache_lock may not be held by anyone. :param token: Dict of the token","directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({}))","scopes. This function will block until a token is retrieved if requested. It","must be a list') token = self._get_token_with_scopes(scopes) if token: # If we had","_get_new_token(self, scopes): \"\"\"This function kicks off some magic. We will start a new","'~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code = None","will exchange for an access token) or the cancellation message. This function will","try to renew the token or delete the token. :kwarg scopes: A list","\"\"\" possible_token = None self.debug('Trying to get token with scopes %s', scopes) for","subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is","retrieved if requested. It is always safe to call this though, since if","actively request the user to get a new token with the current scopeset","not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self,","by anyone. :param uuid: UUID of the token to be removed from cache","The File object to print token instructions to. \"\"\" self.logger = logging.getLogger(__name__) self.debug","Identifier for storage of retrieved tokens :param id_provider: URL of the identity provider","attempt to renew the token that was last returned. If that worked, we","refreshable. :param scopes: List of scopes that need to be in the returned","FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS","True token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if","as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \"\"\"Adds a token to the cache and","*args, **ckwargs) if resp.status_code == 401 and not is_retry: if not auto_refresh: return","= '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url,","that may send a 401 return code in incorrect cases. :kwargs http_method: The","scopeset if we do not already have on. :rtype: string or None :returns:","available WEB_PORT.\"\"\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return","the refreshed token in self._cache The caller is responsible for either removing the","was returned. This will attempt to renew the token that was last returned.","indication from your application that the token you sent was invalid, you should","does not require you to use a secret. :kwarg useragent: Useragent string to","It will prefer to return tokens whose expires_at is still before the current","ImportError: from io import StringIO import socket import os try: from urllib import","copy import copy import json import logging from threading import Lock import time","[12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every app id","self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \"\"\"Refreshes the self._cache from the","to be updated \"\"\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys())","IdP mapping dict. :rtype: string :returns: The IdP URL \"\"\" if method in",":kwarg cachedir: The directory in which to store the token caches. Will be","IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE","error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'],","next one continue def _get_new_token(self, scopes): \"\"\"This function kicks off some magic. We","we will actively request the user to get a new token with the","client_id to get a new token with the specified scopes. The webserver will","might have been revoked by the user or expired. In that case, you","self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs):","was succesful. :param uuid: The UUID of the cached token to attempt to","not in ['POST']: raise ValueError('Cannot use POST tokens in %s method' % method)","either show the user a URL, or if possible, kick off their browser.","self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else:","self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True): \"\"\"Function to retrieve","kick off their browser. This URL will be the Authorization endpoint of the","= ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry","following keys: # idp: The URL of the idp that issued the token","Whether to use POST submission of client secrets rather than Authorization header :kwarg","self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def","for %s' % method) def _refresh_token(self, uuid): \"\"\"Tries to refresh a token and","token['expires_at'] < time.time(): # This is a token that's supposed to still be","requested. It is always safe to call this though, since if we already","+ int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE!","# This is a token that's supposed to still be valid, prefer it","query.split('&') kv = dict([v.split('=', 1) for v in split]) if 'error' in kv:","current client. :kwarg new_token: If True, we will actively request the user to","got a 401 and this is a retry. Report error self.report_token_issue() return resp","token: Dict of the token to be added to the cache \"\"\" uuid","still before the current time, but if no such tokens exist it will","a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and","specified scopes. The webserver will then need to catch the return with either","ValueError('Cannot provide json in a post call') if method not in ['POST']: raise","or None. Note that the bearer token might have been revoked by the","URL for the requested method. :param method: The method name in the IdP","= None self._retrieved_code = None # TODO: Make cache_lock a filesystem lock so","token issues on 401. This helps with broken apps that may send a","on OpenID Connect for authentication.\"\"\" from __future__ import print_function from copy import copy","'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp =","return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window","from StringIO import StringIO except ImportError: from io import StringIO import socket import","resp = resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error'])","token is retrieved if requested. It is always safe to call this though,","already gone') def _get_token_with_scopes(self, scopes): \"\"\"Searches the cache for any tokens that have","token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type':","_update_token(self, uuid, toupdate): \"\"\"Updates a token in the cache. cache_lock may not be","unable to create it, the OSError will be thrown. :kwargs printfd: The File","tokens', len(self._cache)) def _refresh_cache(self): \"\"\"Refreshes the self._cache from the cache on disk. cache_lock","we will return the new access token. If it did not work, we","hereby granted, free of charge, to any person obtaining a copy # of","requesting token') if self.problem_reported: # We were reported an issue before. Let's just","This function will store the new token in the local cache, add it","not token: return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide","issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid)","OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL","we will return None and remove this token from the cache. If you","SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \"\"\"Client for","_idp_url(self, method): \"\"\"Returns the IdP URL for the requested method. :param method: The","because the account or token was lacking specific permissions. \"\"\" if not self.last_returned_uuid:","token in the cache. cache_lock may not be held by anyone. :param token:","{} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] =","self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \"\"\"Updates a token","print_function from copy import copy import json import logging from threading import Lock","uuid, toupdate): \"\"\"Updates a token in the cache. cache_lock may not be held","return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server:","Make cache_lock a filesystem lock so we also lock across # multiple invocations","authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is","code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time()","False: # The user cancelled the request self._retrieved_code = None self.debug('User cancelled') return"],"string":"[\n \"the current scopeset if we do not already have on. :rtype: string or\",\n \"list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token: #\",\n \"by # the user! Also, even if it has expired, we might still\",\n \"due to a server error or because the account or token was lacking\",\n \"if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile,\",\n \"that we will try to use for our webserver WEB_PORTS = [12345, 23456]\",\n \"that whenever this file is touched, the cache lock is held \\\"\\\"\\\" assert\",\n \"the account or token was lacking specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise\",\n \"token to be removed from cache \\\"\\\"\\\" self.debug('Removing token %s from cache', uuid)\",\n \"start a new webserver on one of the WEB_PORTS, and then either show\",\n \"None # We did not have a valid token, now comes the hard\",\n \"import requests import sys from openidc_client import release # The ports that we\",\n \"to use POST submission of client secrets rather than Authorization header :kwarg client_id:\",\n \"client. :kwarg new_token: If True, we will actively request the user to get\",\n \"data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None\",\n \"was valid but your request failed due to a server error or because\",\n \"UUID. If the user cancelled (or we got another error), we will return\",\n \":returns: True if the token was succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken =\",\n \"secret. :kwarg useragent: Useragent string to use. If not provided, defaults to \\\"python-openidc-client/VERSION\\\"\",\n \"(string, dict) or None :returns: Token UUID and contents or None if no\",\n \"not new_token: return None # We did not have a valid token, now\",\n \"if we do not already have on. :kwarg auto_refresh: If False, will not\",\n \"try: from urllib import urlencode except ImportError: from urllib.parse import urlencode from uuid\",\n \"your request failed due to a server error or because the account or\",\n \"kv = dict([v.split('=', 1) for v in split]) if 'error' in kv: self.debug('Error\",\n \"if we already have a token with the current app_identifier that has the\",\n \"in incorrect cases. :kwargs http_method: The HTTP method to use, defaults to POST..\",\n \"A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR\",\n \"import json import logging from threading import Lock import time try: from StringIO\",\n \"not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not\",\n \"anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on disk. Requires\",\n \"even if it has expired, we might still be able to # refresh\",\n \"% method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token\",\n \"with the specified scopes. The webserver will then need to catch the return\",\n \"reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result\",\n \"to catch the return with either an Authorization Code (that we will exchange\",\n \"method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not\",\n \"self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not token: return\",\n \"unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {}\",\n \":rtype: bool :returns: True if the token was succesfully refreshed, False otherwise \\\"\\\"\\\"\",\n \"return code in incorrect cases. :kwargs http_method: The HTTP method to use, defaults\",\n \"auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args,\",\n \"{'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes':\",\n \"else: self._retrieved_code = kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')])\",\n \"'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data)\",\n \"token we can use to refresh the access token # scopes: A list\",\n \"%s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at':\",\n \"renew the token or delete the token. :kwarg scopes: A list of scopes\",\n \"dict. :rtype: string :returns: The IdP URL \\\"\\\"\\\" if method in self.idp_mapping: return\",\n \"'%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd)\",\n \"token cache is a json serialized dict # This dict contains uuid: token\",\n \"_refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a token and put the refreshed token in\",\n \"is True. :kwarg new_token: If True, we will actively request the user to\",\n \"self._retrieved_code is not None if self._retrieved_code is False: # The user cancelled the\",\n \"to permit persons to whom the Software is # furnished to do so,\",\n \"except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes:\",\n \"_cachefile(self): \\\"\\\"\\\"Property to get the cache file name for the current client. This\",\n \"= (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method):\",\n \"'.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query'\",\n \"from the cache and writes cache to disk. cache_lock may not be held\",\n \"self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if\",\n \"Allarguments and keyword arguments are like the arguments to requests, except for `scopes`,\",\n \"= [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every app\",\n \"== 401: # We got a 401 and this is a retry. Report\",\n \"We got a 401 and this is a retry. Report error self.report_token_issue() return\",\n \"and this permission notice shall be included in # all copies or substantial\",\n \"= False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error with the last token\",\n \"client. This assures that whenever this file is touched, the cache lock is\",\n \"with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return\",\n \"to get token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s',\",\n \"\\\"\\\"\\\"Function to retrieve tokens with specific scopes. This function will block until a\",\n \"LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION\",\n \"as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the\",\n \"possible_token = None self.debug('Trying to get token with scopes %s', scopes) for uuid\",\n \"uuid, token # This is a token that may or may not still\",\n \":returns: String bearer token if possible or None \\\"\\\"\\\" if not isinstance(scopes, list):\",\n \"resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a 401\",\n \"in self._cache The caller is responsible for either removing the token if it\",\n \"an Authorization Code (that we will exchange for an access token) or the\",\n \"WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server\",\n \"self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for\",\n \"__refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. Requires cache_lock to be\",\n \"server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False: # The\",\n \"report issue before requesting token') if self.problem_reported: # We were reported an issue\",\n \"from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del\",\n \"to automatically report token issues on 401. This helps with broken apps that\",\n \"self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on disk. Requires cache_lock to\",\n \"token = self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if 'json'\",\n \"the client_id. May be None if your IdP does not require you to\",\n \":kwarg use_post: Whether to use POST submission of client secrets rather than Authorization\",\n \"WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This\",\n \"*args, **kwargs): \\\"\\\"\\\"Make an python-requests POST request. Allarguments and keyword arguments are like\",\n \"resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'],\",\n \"`new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for\",\n \"to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in which to store the token caches.\",\n \"disk. cache_lock may not be held by anyone. :param uuid: UUID of the\",\n \"return True def _get_server(self, app): \\\"\\\"\\\"This function returns a SimpleServer with an available\",\n \"a token to the cache and writes cache to disk. cache_lock may not\",\n \"lacking specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting\",\n \"def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a token and put the refreshed token\",\n \"new webserver on one of the WEB_PORTS, and then either show the user\",\n \"cache_lock may not be held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes\",\n \"be refreshable. :param scopes: List of scopes that need to be in the\",\n \"def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on disk. Requires cache_lock to be held\",\n \"no applicable tokens were found \\\"\\\"\\\" possible_token = None self.debug('Trying to get token\",\n \"or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code =\",\n \"ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh',\",\n \"one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off some magic. We will\",\n \"of scopes that we had requested with the token def __init__(self, app_identifier, id_provider,\",\n \"the required scopes, we will return it. This function will return a bearer\",\n \"return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error with the last token that was\",\n \"BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN\",\n \"the cache on disk. cache_lock may not be held by anyone.\\\"\\\"\\\" with self._cache_lock:\",\n \"if renewal was succesful. :param uuid: The UUID of the cached token to\",\n \"the requested method. :param method: The method name in the IdP mapping dict.\",\n \"your application that the token you sent was invalid, you should call it.\",\n \"CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT\",\n \"it. You should explicitly NOT call this function if the token was valid\",\n \"app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with\",\n \"no such tokens exist it will return the possibly expired token: it might\",\n \"refreshed, False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data =\",\n \"Default is ~/.openidc. If this does not exist and we are unable to\",\n \"continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes']))\",\n \"will be thrown. :kwargs printfd: The File object to print token instructions to.\",\n \"(%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return\",\n \"already have on. :rtype: string or None :returns: String bearer token if possible\",\n \"self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating\",\n \"uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] =\",\n \"def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for\",\n \"access token. If it did not work, we will return None and remove\",\n \"self._printfd = printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens with specific\",\n \"_token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for\",\n \"resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True\",\n \"the new access token. If it did not work, we will return None\",\n \"indicates the token should still be valid, it may have been revoked by\",\n \"the token should still be valid, it may have been revoked by #\",\n \"\\\"\\\"\\\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh =\",\n \"retrieved tokens :param id_provider: URL of the identity provider to get tokens from\",\n \"writes cache to disk. cache_lock may not be held by anyone. :param uuid:\",\n \"in ['POST']: raise ValueError('Cannot use POST tokens in %s method' % method) if\",\n \"self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. Requires cache_lock\",\n \"you sent was invalid, you should call it. You should explicitly NOT call\",\n \"a json dict with the following keys: # idp: The URL of the\",\n \"'POST') is_retry = False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try\",\n \"cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache:\",\n \"token in self._cache The caller is responsible for either removing the token if\",\n \"token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid\",\n \"DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR\",\n \"from urllib.parse import urlencode from uuid import uuid4 as uuidgen import webbrowser from\",\n \"found \\\"\\\"\\\" possible_token = None self.debug('Trying to get token with scopes %s', scopes)\",\n \"but if no such tokens exist it will return the possibly expired token:\",\n \"The caller is responsible for either removing the token if it could not\",\n \"Token UUID and contents or None if no applicable tokens were found \\\"\\\"\\\"\",\n \"NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE\",\n \"the return with either an Authorization Code (that we will exchange for an\",\n \"software and associated documentation files (the \\\"Software\\\"), to deal # in the Software\",\n \"URL of the idp that issued the token # sub: The subject that\",\n \"for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes\",\n \"resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif\",\n \"self._retrieved_code = None resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization\",\n \"implementation of tokens: # Every app id has its own token cache #\",\n \"to # refresh the token. # refresh_token: The token we can use to\",\n \"to the cache and writes cache to disk. cache_lock may not be held\",\n \"and to permit persons to whom the Software is # furnished to do\",\n \"kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return a message\",\n \"a new token with the specified scopes. The webserver will then need to\",\n \"# furnished to do so, subject to the following conditions: # # The\",\n \"the Software, and to permit persons to whom the Software is # furnished\",\n \"server except socket.error: # This port did not work. Switch to next one\",\n \"'text/plain')]) return [u'You can close this window and return to the CLI'.encode('ascii')] self._retrieved_code\",\n \"If this does not exist and we are unable to create it, the\",\n \"# indicates the token should still be valid, it may have been revoked\",\n \"to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating\",\n \"authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' %\",\n \"gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for any tokens that have the\",\n \"= None self.debug('Trying to get token with scopes %s', scopes) for uuid in\",\n \"scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp']\",\n \"name in the IdP mapping dict. :rtype: string :returns: The IdP URL \\\"\\\"\\\"\",\n \"ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE\",\n \"'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST',\",\n \"\\\"\\\"\\\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=',\",\n \"token should still be valid, it may have been revoked by # the\",\n \"services relying on OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens\",\n \"401 and this is a retry. Report error self.report_token_issue() return resp else: return\",\n \"got another error), we will return None. \\\"\\\"\\\" def _token_app(environ, start_response): query =\",\n \"\\\"\\\"\\\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in\",\n \"not None if self._retrieved_code is False: # The user cancelled the request self._retrieved_code\",\n \"list of scopes that we had requested with the token def __init__(self, app_identifier,\",\n \"the cancellation message. This function will store the new token in the local\",\n \"token to be updated :param toupdate: Dict indicating which fields need to be\",\n \"not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in which to store\",\n \"~/.openidc. If this does not exist and we are unable to create it,\",\n \"return resp @property def _cachefile(self): \\\"\\\"\\\"Property to get the cache file name for\",\n \"'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST',\",\n \"CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH\",\n \"return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp':\",\n \"if possible or None \\\"\\\"\\\" if not isinstance(scopes, list): raise ValueError('Scopes must be\",\n \"socket.error: # This port did not work. Switch to next one continue def\",\n \"resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self,\",\n \"comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported\",\n \"= False else: self._retrieved_code = kv['code'] # Just return a message start_response('200 OK',\",\n \"client_id. May be None if your IdP does not require you to use\",\n \"PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT\",\n \"release # The ports that we will try to use for our webserver\",\n \"from openidc_client import release # The ports that we will try to use\",\n \"a server error or because the account or token was lacking specific permissions.\",\n \"to refresh a token and put the refreshed token in self._cache The caller\",\n \"supposed to still be valid, prefer it # over any others we have\",\n \"another error), we will return None. \\\"\\\"\\\" def _token_app(environ, start_response): query = environ['QUERY_STRING']\",\n \"'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE\",\n \"a secret. :kwarg useragent: Useragent string to use. If not provided, defaults to\",\n \"we will return None. \\\"\\\"\\\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split =\",\n \"def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. cache_lock may not\",\n \"to be added to the cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token %s\",\n \"time, but if no such tokens exist it will return the possibly expired\",\n \"webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes)\",\n \"Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY\",\n \"True, we will actively request the user to get a new token with\",\n \"self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid\",\n \"if we do not already have on. :rtype: string or None :returns: String\",\n \"Useragent string to use. If not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The\",\n \"self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error with the last token that was returned.\",\n \"be the Authorization endpoint of the IdP with a request for our client_id\",\n \"to deal # in the Software without restriction, including without limitation the rights\",\n \"to any person obtaining a copy # of this software and associated documentation\",\n \"IdP URL for the requested method. :param method: The method name in the\",\n \"a token is not present with this token, a new one will be\",\n \"were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery =\",\n \"\\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported:\",\n \"json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache\",\n \"def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests POST request. Allarguments and keyword arguments\",\n \"% server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id']\",\n \"OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #\",\n \"return token[1]['access_token'] elif not new_token: return None # We did not have a\",\n \"return uuid, token # This is a token that may or may not\",\n \"return the possibly expired token: it might be refreshable. :param scopes: List of\",\n \"app) return server except socket.error: # This port did not work. Switch to\",\n \"= self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate a webserver')\",\n \"uuid: token pairs # Every \\\"token\\\" object is a json dict with the\",\n \"server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] =\",\n \"from urllib import urlencode except ImportError: from urllib.parse import urlencode from uuid import\",\n \"In that case, you will want to call report_token_issue() to try to renew\",\n \"this does not exist and we are unable to create it, the OSError\",\n \"os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as\",\n \"current app_identifier that has the required scopes, we will return it. This function\",\n \":kwarg client_secret: The client \\\"secret\\\" that goes with the client_id. May be None\",\n \"from cache \\\"\\\"\\\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if\",\n \"method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a token and put the refreshed\",\n \"with specific scopes. This function will block until a token is retrieved if\",\n \"self.debug('User cancelled') return None self.debug('We got an authorization code!') data = {'client_id': self.client_id,\",\n \"this is a retry. Report error self.report_token_issue() return resp else: return resp @property\",\n \"the idp that issued the token # sub: The subject that owns the\",\n \"in the IdP mapping dict. :rtype: string :returns: The IdP URL \\\"\\\"\\\" if\",\n \"revoked by the user or expired. In that case, you will want to\",\n \"uuid import uuid4 as uuidgen import webbrowser from wsgiref import simple_server import requests\",\n \"= id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s'\",\n \"refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args,\",\n \"valid but your request failed due to a server error or because the\",\n \"this software and associated documentation files (the \\\"Software\\\"), to deal # in the\",\n \"current client. This assures that whenever this file is touched, the cache lock\",\n \"The Client Identifier used to request credentials :kwarg client_secret: The client \\\"secret\\\" that\",\n \"credentials :kwarg client_secret: The client \\\"secret\\\" that goes with the client_id. May be\",\n \"POST submission of client secrets rather than Authorization header :kwarg client_id: The Client\",\n \"self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return None\",\n \"have a token with the current app_identifier that has the required scopes, we\",\n \"be requested unless nonblocking is True. :kwarg new_token: If True, we will actively\",\n \"new_token: return None # We did not have a valid token, now comes\",\n \"server error or because the account or token was lacking specific permissions. \\\"\\\"\\\"\",\n \"If we had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported =\",\n \"self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \\\"\\\"\\\"This function returns a\",\n \"if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP\",\n \"granted, free of charge, to any person obtaining a copy # of this\",\n \"to retrieve tokens with specific scopes. This function will block until a token\",\n \"that was last returned. If that worked, we will return the new access\",\n \"Code (that we will exchange for an access token) or the cancellation message.\",\n \"be held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache\",\n \"but your request failed due to a server error or because the account\",\n \"`scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required\",\n \"import simple_server import requests import sys from openidc_client import release # The ports\",\n \"1) for v in split]) if 'error' in kv: self.debug('Error code returned: %s\",\n \"remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid)\",\n \"the current scopeset if we do not already have on. :kwarg auto_refresh: If\",\n \"to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post =\",\n \"app): \\\"\\\"\\\"This function returns a SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for port in\",\n \"the IdP with a request for our client_id to get a new token\",\n \"of scopes that need to be in the returned token :rtype: (string, dict)\",\n \"will return None and remove this token from the cache. If you get\",\n \"# Permission is hereby granted, free of charge, to any person obtaining a\",\n \"urllib import urlencode except ImportError: from urllib.parse import urlencode from uuid import uuid4\",\n \"id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' %\",\n \"with this token, a new one will be requested unless nonblocking is True.\",\n \"not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes\",\n \"IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF\",\n \"= id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent =\",\n \"self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed\",\n \"uuid4 as uuidgen import webbrowser from wsgiref import simple_server import requests import sys\",\n \"resp.status_code == 401: # We got a 401 and this is a retry.\",\n \"will return the possibly expired token: it might be refreshable. :param scopes: List\",\n \"function will return a bearer token or None. Note that the bearer token\",\n \"self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue\",\n \"to still be valid, prefer it # over any others we have self.debug('Not\",\n \"still be able to # refresh the token. # refresh_token: The token we\",\n \"'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers'\",\n \"relying on OpenID Connect for authentication.\\\"\\\"\\\" from __future__ import print_function from copy import\",\n \"self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests POST\",\n \"def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token from the cache and writes cache to\",\n \"OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION\",\n \"self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f:\",\n \"without restriction, including without limitation the rights # to use, copy, modify, merge,\",\n \"**kwargs): \\\"\\\"\\\"Make an python-requests POST request. Allarguments and keyword arguments are like the\",\n \"than Authorization header :kwarg client_id: The Client Identifier used to request credentials :kwarg\",\n \"token to attempt to refresh. :rtype: bool :returns: True if the token was\",\n \"the token or delete the token. :kwarg scopes: A list of scopes required\",\n \"port did not work. Switch to next one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This\",\n \"to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope']\",\n \"return the new access token. If it did not work, we will return\",\n \"to use a secret. :kwarg useragent: Useragent string to use. If not provided,\",\n \"this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return\",\n \"has expired, we might still be able to # refresh the token. #\",\n \"token was valid but your request failed due to a server error or\",\n \"time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE\",\n \"token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing\",\n \"# Every app id has its own token cache # The token cache\",\n \"is_retry = False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try =\",\n \"token') if self.problem_reported: # We were reported an issue before. Let's just remove\",\n \"None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp,\",\n \"uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token from the cache and writes cache\",\n \"a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = '\",\n \"be None if your IdP does not require you to use a secret.\",\n \"the cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with\",\n \"updated :param toupdate: Dict indicating which fields need to be updated \\\"\\\"\\\" self.debug('Updating\",\n \"copies of the Software, and to permit persons to whom the Software is\",\n \"it to the valid cache, and then return the UUID. If the user\",\n \"uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error with the\",\n \"URL, or if possible, kick off their browser. This URL will be the\",\n \"if self.problem_reported: # We were reported an issue before. Let's just remove this\",\n \"a post call') if method not in ['POST']: raise ValueError('Cannot use POST tokens\",\n \"import urlencode except ImportError: from urllib.parse import urlencode from uuid import uuid4 as\",\n \"ports that we will try to use for our webserver WEB_PORTS = [12345,\",\n \"is responsible for either removing the token if it could not be refreshed\",\n \"call it. You should explicitly NOT call this function if the token was\",\n \"\\\"\\\"\\\"Tries to refresh a token and put the refreshed token in self._cache The\",\n \"to get a new token with the current scopeset if we do not\",\n \"\\\"Bearer\\\" # expires_at: Token expiration UTC time. NOTE: Even if the expires_at #\",\n \"uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid):\",\n \"obtaining a copy # of this software and associated documentation files (the \\\"Software\\\"),\",\n \"on. :rtype: string or None :returns: String bearer token if possible or None\",\n \"http_method: The HTTP method to use, defaults to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs)\",\n \"on one of the WEB_PORTS, and then either show the user a URL,\",\n \"requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None,\",\n \"cache on disk. cache_lock may not be held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache()\",\n \"also lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache\",\n \"scopes. It will prefer to return tokens whose expires_at is still before the\",\n \"that issued the token # sub: The subject that owns the token #\",\n \"Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes,\",\n \"caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not\",\n \"IdP URL \\\"\\\"\\\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return\",\n \"Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not\",\n \"return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'),\",\n \"you should call it. You should explicitly NOT call this function if the\",\n \"requested unless nonblocking is True. :kwarg new_token: If True, we will actively request\",\n \"get a new token with the specified scopes. The webserver will then need\",\n \"resp @property def _cachefile(self): \\\"\\\"\\\"Property to get the cache file name for the\",\n \"If False, will not try to automatically report token issues on 401. This\",\n \"False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']})\",\n \"code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret:\",\n \"cache. If you get an indication from your application that the token you\",\n \"will try to use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object):\",\n \"resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None\",\n \"will attempt to renew the token that was last returned. If that worked,\",\n \"True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests POST request. Allarguments\",\n \"time try: from StringIO import StringIO except ImportError: from io import StringIO import\",\n \"%i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk.\",\n \"user! Also, even if it has expired, we might still be able to\",\n \"by anyone. :param token: Dict of the token to be added to the\",\n \"# idp: The URL of the idp that issued the token # sub:\",\n \"of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a\",\n \"from copy import copy import json import logging from threading import Lock import\",\n \"function will block until a token is retrieved if requested. It is always\",\n \"401. This helps with broken apps that may send a 401 return code\",\n \"scopes: A list of scopes required for the current client. :kwarg new_token: If\",\n \"self._cache from the cache on disk. cache_lock may not be held by anyone.\\\"\\\"\\\"\",\n \"any person obtaining a copy # of this software and associated documentation files\",\n \"you will want to call report_token_issue() to try to renew the token or\",\n \"explicitly NOT call this function if the token was valid but your request\",\n \"You should explicitly NOT call this function if the token was valid but\",\n \"an python-requests POST request. Allarguments and keyword arguments are like the arguments to\",\n \"self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to refresh,\",\n \"IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED,\",\n \"tokens in %s method' % method) if 'data' not in ckwargs: ckwargs['data'] =\",\n \"a copy # of this software and associated documentation files (the \\\"Software\\\"), to\",\n \"revoked by # the user! Also, even if it has expired, we might\",\n \"lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache =\",\n \"token else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer\",\n \"the user a URL, or if possible, kick off their browser. This URL\",\n \"return tokens whose expires_at is still before the current time, but if no\",\n \"with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a token to\",\n \"dict) or None :returns: Token UUID and contents or None if no applicable\",\n \"not present with this token, a new one will be requested unless nonblocking\",\n \"AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #\",\n \"(the \\\"Software\\\"), to deal # in the Software without restriction, including without limitation\",\n \"= 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] =\",\n \"for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] !=\",\n \"of client secrets rather than Authorization header :kwarg client_id: The Client Identifier used\",\n \"token that may or may not still be valid self.debug('Possible') possible_token = (uuid,\",\n \"charge, to any person obtaining a copy # of this software and associated\",\n \"will return it. This function will return a bearer token or None. Note\",\n \"path for %s' % method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a token\",\n \"use POST submission of client secrets rather than Authorization header :kwarg client_id: The\",\n \"'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401\",\n \"this function if the token was valid but your request failed due to\",\n \"one of the WEB_PORTS, and then either show the user a URL, or\",\n \"cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock:\",\n \"and put the refreshed token in self._cache The caller is responsible for either\",\n \"if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code\",\n \"be updated :param toupdate: Dict indicating which fields need to be updated \\\"\\\"\\\"\",\n \"rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id\",\n \"limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or\",\n \"the cache file name for the current client. This assures that whenever this\",\n \"token) or the cancellation message. This function will store the new token in\",\n \"return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL for the requested method.\",\n \"self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code = None #\",\n \"Report error self.report_token_issue() return resp else: return resp @property def _cachefile(self): \\\"\\\"\\\"Property to\",\n \"client_secret self.useragent = useragent or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or\",\n \"serialized dict # This dict contains uuid: token pairs # Every \\\"token\\\" object\",\n \"self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock a filesystem lock\",\n \"{} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers'] = {}\",\n \"we have self.debug('Not yet expired, returning') return uuid, token # This is a\",\n \"not include path for %s' % method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh\",\n \"\\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache()\",\n \"a new webserver on one of the WEB_PORTS, and then either show the\",\n \"valid token, now comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid\",\n \"_get_server(self, app): \\\"\\\"\\\"This function returns a SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for port\",\n \"THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\",\n \"if the token was valid but your request failed due to a server\",\n \"the token that was last returned. If that worked, we will return the\",\n \"if self._retrieved_code is False: # The user cancelled the request self._retrieved_code = None\",\n \"Even if the expires_at # indicates the token should still be valid, it\",\n \"EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,\",\n \"\\\"\\\"\\\"Wirtes self._cache to cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\"\",\n \"We did not have a valid token, now comes the hard part... uuid\",\n \"a token that may or may not still be valid self.debug('Possible') possible_token =\",\n \"to use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal\",\n \"for specific endpoints on the IdP. :kwarg use_post: Whether to use POST submission\",\n \"bearer token or None. Note that the bearer token might have been revoked\",\n \"valid, prefer it # over any others we have self.debug('Not yet expired, returning')\",\n \"just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result:\",\n \"if requested. It is always safe to call this though, since if we\",\n \"None. Note that the bearer token might have been revoked by the user\",\n \"environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v in split]) if\",\n \"'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app):\",\n \"resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in\",\n \"new_token: If True, we will actively request the user to get a new\",\n \"in the cache. cache_lock may not be held by anyone. :param token: UUID\",\n \"set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a token that's\",\n \"that was returned. This will attempt to renew the token that was last\",\n \"value # token_type: Token type. Currently supported: \\\"Bearer\\\" # expires_at: Token expiration UTC\",\n \"# # Permission is hereby granted, free of charge, to any person obtaining\",\n \"socket import os try: from urllib import urlencode except ImportError: from urllib.parse import\",\n \"from :param id_provider_mapping: Mapping with URLs to use for specific endpoints on the\",\n \"token with the current scopeset if we do not already have on. :kwarg\",\n \"DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client for applications relying on OpenID Connect for\",\n \"object to print token instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug\",\n \"by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on disk.\",\n \"OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client for applications\",\n \"if token['expires_at'] < time.time(): # This is a token that's supposed to still\",\n \"as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i\",\n \"if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token(\",\n \"if your IdP does not require you to use a secret. :kwarg useragent:\",\n \"= self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code ==\",\n \"others we have self.debug('Not yet expired, returning') return uuid, token # This is\",\n \"use_post: Whether to use POST submission of client secrets rather than Authorization header\",\n \"browser. This URL will be the Authorization endpoint of the IdP with a\",\n \"use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation\",\n \"for an access token) or the cancellation message. This function will store the\",\n \"'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} #\",\n \"FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE\",\n \"PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING\",\n \"client_secret: The client \\\"secret\\\" that goes with the client_id. May be None if\",\n \"# THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS\",\n \"OpenIDCClient(object): # Internal implementation of tokens: # Every app id has its own\",\n \"include path for %s' % method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a\",\n \"open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self):\",\n \"exchange for an access token) or the cancellation message. This function will store\",\n \"the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\",\n \"submission of client secrets rather than Authorization header :kwarg client_id: The Client Identifier\",\n \"have been revoked by the user or expired. In that case, you will\",\n \"for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except\",\n \"and remove this token from the cache. If you get an indication from\",\n \"return None. \\\"\\\"\\\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv\",\n \"of the Software, and to permit persons to whom the Software is #\",\n \":kwarg useragent: Useragent string to use. If not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg\",\n \"cached token to attempt to refresh. :rtype: bool :returns: True if the token\",\n \"the token # access_token: Token value # token_type: Token type. Currently supported: \\\"Bearer\\\"\",\n \"to a server error or because the account or token was lacking specific\",\n \"code in incorrect cases. :kwargs http_method: The HTTP method to use, defaults to\",\n \"an available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app)\",\n \"self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code\",\n \"to the cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid)\",\n \"id has its own token cache # The token cache is a json\",\n \"expires_at # indicates the token should still be valid, it may have been\",\n \"method: The method name in the IdP mapping dict. :rtype: string :returns: The\",\n \"be added to the cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token %s to\",\n \"to cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked()\",\n \"simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port did not work.\",\n \"on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache')\",\n \"self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp =\",\n \"scopes: A list of scopes that we had requested with the token def\",\n \"self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request(\",\n \"self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error with the last\",\n \"with the following keys: # idp: The URL of the idp that issued\",\n \"os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code\",\n \"kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can\",\n \"including without limitation the rights # to use, copy, modify, merge, publish, distribute,\",\n \"self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token']\",\n \"# This port did not work. Switch to next one continue def _get_new_token(self,\",\n \"= dict([v.split('=', 1) for v in split]) if 'error' in kv: self.debug('Error code\",\n \"removing the token if it could not be refreshed or saving the cache\",\n \"token: UUID of the token to be updated :param toupdate: Dict indicating which\",\n \"cache, and then return the UUID. If the user cancelled (or we got\",\n \"new_token=new_token) if not token: return None if self.use_post: if 'json' in ckwargs: raise\",\n \"cache # The token cache is a json serialized dict # This dict\",\n \"token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token\",\n \"printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web services relying on OpenID Connect. :param app_identifier:\",\n \"cache_lock a filesystem lock so we also lock across # multiple invocations self._cache_lock\",\n \"returned. This will attempt to renew the token that was last returned. If\",\n \"return uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token in the cache. cache_lock\",\n \"_refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. cache_lock may not be\",\n \"can close this window and return to the CLI'.encode('ascii')] self._retrieved_code = None server\",\n \"OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\",\n \"self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function\",\n \"'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request(\",\n \"This helps with broken apps that may send a 401 return code in\",\n \"= ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True token =\",\n \"token pairs # Every \\\"token\\\" object is a json dict with the following\",\n \"**ckwargs) if resp.status_code == 401 and not is_retry: if not auto_refresh: return resp\",\n \"this token, a new one will be requested unless nonblocking is True. :kwarg\",\n \"= 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query =\",\n \"if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if\",\n \"Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free of\",\n \"assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from\",\n \"self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on disk. Requires cache_lock to be\",\n \"the Software is # furnished to do so, subject to the following conditions:\",\n \"subject to the following conditions: # # The above copyright notice and this\",\n \"filesystem lock so we also lock across # multiple invocations self._cache_lock = Lock()\",\n \"(that we will exchange for an access token) or the cancellation message. This\",\n \"for interacting with web services relying on OpenID Connect. :param app_identifier: Identifier for\",\n \"If a token is not present with this token, a new one will\",\n \"is a json serialized dict # This dict contains uuid: token pairs #\",\n \"a token is retrieved if requested. It is always safe to call this\",\n \"not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try:\",\n \"TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\",\n \"until a token is retrieved if requested. It is always safe to call\",\n \"Every \\\"token\\\" object is a json dict with the following keys: # idp:\",\n \"query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v in\",\n \"split = query.split('&') kv = dict([v.split('=', 1) for v in split]) if 'error'\",\n \"self._cache from the cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\"\",\n \"This function will return a bearer token or None. Note that the bearer\",\n \"storage of retrieved tokens :param id_provider: URL of the identity provider to get\",\n \"have a valid token, now comes the hard part... uuid = self._get_new_token(scopes) if\",\n \"token and put the refreshed token in self._cache The caller is responsible for\",\n \"%s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just\",\n \"have on. :rtype: string or None :returns: String bearer token if possible or\",\n \"that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return\",\n \"= True token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token)\",\n \"SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #\",\n \"Dict indicating which fields need to be updated \\\"\\\"\\\" self.debug('Updating token %s in\",\n \"'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid,\",\n \"# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies\",\n \"import os try: from urllib import urlencode except ImportError: from urllib.parse import urlencode\",\n \"tokens whose expires_at is still before the current time, but if no such\",\n \"client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web services relying on\",\n \"a bearer token or None. Note that the bearer token might have been\",\n \"cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid]\",\n \"it. This function will return a bearer token or None. Note that the\",\n \"is hereby granted, free of charge, to any person obtaining a copy #\",\n \"23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every app id has\",\n \"raise Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1]\",\n \"\\\"\\\"\\\"Property to get the cache file name for the current client. This assures\",\n \"refresh the token. # refresh_token: The token we can use to refresh the\",\n \"are unable to create it, the OSError will be thrown. :kwargs printfd: The\",\n \"-*- coding: utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat, Inc.\",\n \"# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\",\n \"the cache for any tokens that have the requested scopes. It will prefer\",\n \"= self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url =\",\n \"import copy import json import logging from threading import Lock import time try:\",\n \":kwarg scopes: A list of scopes required for the current client. :kwarg new_token:\",\n \"lock so we also lock across # multiple invocations self._cache_lock = Lock() with\",\n \"set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at']\",\n \"contents or None if no applicable tokens were found \\\"\\\"\\\" possible_token = None\",\n \"send a 401 return code in incorrect cases. :kwargs http_method: The HTTP method\",\n \"token from the cache. If you get an indication from your application that\",\n \"token to be added to the cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token\",\n \"broken apps that may send a 401 return code in incorrect cases. :kwargs\",\n \"%s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token')\",\n \"401 return code in incorrect cases. :kwargs http_method: The HTTP method to use,\",\n \"access token) or the cancellation message. This function will store the new token\",\n \"auto_refresh: If False, will not try to automatically report token issues on 401.\",\n \"None self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri':\",\n \"self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code =\",\n \"token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token in the\",\n \"print token instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id =\",\n \"try to automatically report token issues on 401. This helps with broken apps\",\n \"arguments are like the arguments to requests, except for `scopes`, `new_token` and `auto_refresh`\",\n \"so, subject to the following conditions: # # The above copyright notice and\",\n \"in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else:\",\n \"succesful. :param uuid: The UUID of the cached token to attempt to refresh.\",\n \"get tokens from :param id_provider_mapping: Mapping with URLs to use for specific endpoints\",\n \"+ self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for %s' %\",\n \"applicable tokens were found \\\"\\\"\\\" possible_token = None self.debug('Trying to get token with\",\n \"self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token\",\n \"the cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked()\",\n \"copy # of this software and associated documentation files (the \\\"Software\\\"), to deal\",\n \"retry. Report error self.report_token_issue() return resp else: return resp @property def _cachefile(self): \\\"\\\"\\\"Property\",\n \":rtype: string or None :returns: String bearer token if possible or None \\\"\\\"\\\"\",\n \"resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at'])\",\n \"our client_id to get a new token with the specified scopes. The webserver\",\n \"file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False:\",\n \"message. This function will store the new token in the local cache, add\",\n \"the token caches. Will be put through expanduer. Default is ~/.openidc. If this\",\n \"a valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token']\",\n \"self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE! \\\\o/ return self._add_token(token)\",\n \"requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error'\",\n \"refresh_token: The token we can use to refresh the access token # scopes:\",\n \"the user or expired. In that case, you will want to call report_token_issue()\",\n \"fields need to be updated \\\"\\\"\\\" self.debug('Updating token %s in cache, fields %s',\",\n \"UUID of the token to be removed from cache \\\"\\\"\\\" self.debug('Removing token %s\",\n \"else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests\",\n \"Identifier used to request credentials :kwarg client_secret: The client \\\"secret\\\" that goes with\",\n \"\\\"\\\"\\\" if not isinstance(scopes, list): raise ValueError('Scopes must be a list') token =\",\n \"from threading import Lock import time try: from StringIO import StringIO except ImportError:\",\n \"is not present with this token, a new one will be requested unless\",\n \"get the cache file name for the current client. This assures that whenever\",\n \"in the local cache, add it to the valid cache, and then return\",\n \"self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in resp:\",\n \"do not already have on. :kwarg auto_refresh: If False, will not try to\",\n \"len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. cache_lock may\",\n \"sublicense, and/or sell # copies of the Software, and to permit persons to\",\n \"self.debug('Returning possible token') return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL for\",\n \"cache to disk. cache_lock may not be held by anyone. :param token: Dict\",\n \"cachedir: The directory in which to store the token caches. Will be put\",\n \"that worked, we will return the new access token. If it did not\",\n \"Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted,\",\n \"subject that owns the token # access_token: Token value # token_type: Token type.\",\n \"__future__ import print_function from copy import copy import json import logging from threading\",\n \"= useragent or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid\",\n \"worked, we will return the new access token. If it did not work,\",\n \"to get a new token with the specified scopes. The webserver will then\",\n \"scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time():\",\n \"type. Currently supported: \\\"Bearer\\\" # expires_at: Token expiration UTC time. NOTE: Even if\",\n \"is a token that may or may not still be valid self.debug('Possible') possible_token\",\n \"is False: # The user cancelled the request self._retrieved_code = None self.debug('User cancelled')\",\n \"to refresh the access token # scopes: A list of scopes that we\",\n \"IN THE # SOFTWARE. \\\"\\\"\\\"Client for applications relying on OpenID Connect for authentication.\\\"\\\"\\\"\",\n \"the token to be added to the cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding\",\n \"int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE! \\\\o/\",\n \"cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir):\",\n \"with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True):\",\n \"to the valid cache, and then return the UUID. If the user cancelled\",\n \"= environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v in split])\",\n \"self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates\",\n \":param toupdate: Dict indicating which fields need to be updated \\\"\\\"\\\" self.debug('Updating token\",\n \"= kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You\",\n \"if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported: #\",\n \"= Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self,\",\n \"scopes: List of scopes that need to be in the returned token :rtype:\",\n \"# copies of the Software, and to permit persons to whom the Software\",\n \"be removed from cache \\\"\\\"\\\" self.debug('Removing token %s from cache', uuid) with self._cache_lock:\",\n \"return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make\",\n \"that owns the token # access_token: Token value # token_type: Token type. Currently\",\n \"required for this call. If a token is not present with this token,\",\n \"raise ValueError('Cannot provide json in a post call') if method not in ['POST']:\",\n \"held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on\",\n \"instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post\",\n \"token. If it did not work, we will return None and remove this\",\n \"= requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if\",\n \"self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self,\",\n \"this permission notice shall be included in # all copies or substantial portions\",\n \"assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile):\",\n \"will store the new token in the local cache, add it to the\",\n \"scopes that need to be in the returned token :rtype: (string, dict) or\",\n \"resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'],\",\n \"= logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp =\",\n \"The token we can use to refresh the access token # scopes: A\",\n \"was lacking specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot report issue before\",\n \"token, a new one will be requested unless nonblocking is True. :kwarg new_token:\",\n \"client \\\"secret\\\" that goes with the client_id. May be None if your IdP\",\n \"CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #\",\n \"still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token')\",\n \"a SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try: server =\",\n \"in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a\",\n \"on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache\",\n \"token): \\\"\\\"\\\"Adds a token to the cache and writes cache to disk. cache_lock\",\n \"self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code =\",\n \"the token was succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token\",\n \"client_id: The Client Identifier used to request credentials :kwarg client_secret: The client \\\"secret\\\"\",\n \"ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token: # If we\",\n \"token or None. Note that the bearer token might have been revoked by\",\n \"did not have a valid token, now comes the hard part... uuid =\",\n \"\\\"\\\"\\\"Updates a token in the cache. cache_lock may not be held by anyone.\",\n \"web services relying on OpenID Connect. :param app_identifier: Identifier for storage of retrieved\",\n \"'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'),\",\n \"token or delete the token. :kwarg scopes: A list of scopes required for\",\n \"start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1) for v\",\n \"application that the token you sent was invalid, you should call it. You\",\n \"FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF\",\n \"then need to catch the return with either an Authorization Code (that we\",\n \"though, since if we already have a token with the current app_identifier that\",\n \"with an available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port,\",\n \"do not already have on. :rtype: string or None :returns: String bearer token\",\n \"token if it could not be refreshed or saving the cache if renewal\",\n \"code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code']\",\n \"merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to\",\n \"return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a 401 and\",\n \"['POST']: raise ValueError('Cannot use POST tokens in %s method' % method) if 'data'\",\n \"+ resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \\\"\\\"\\\"This function\",\n \"'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return\",\n \"its own token cache # The token cache is a json serialized dict\",\n \"in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp =\",\n \"arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is\",\n \"== 401 and not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue()\",\n \"A list of scopes required for the current client. :kwarg new_token: If True,\",\n \"multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd =\",\n \"raise ValueError('Cannot use POST tokens in %s method' % method) if 'data' not\",\n \"= resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return\",\n \"elif resp.status_code == 401: # We got a 401 and this is a\",\n \"nonblocking is True. :kwarg new_token: If True, we will actively request the user\",\n \"% token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not\",\n \"ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False\",\n \"token with the current scopeset if we do not already have on. :rtype:\",\n \"with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate):\",\n \"not require you to use a secret. :kwarg useragent: Useragent string to use.\",\n \"= token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return None #\",\n \"whom the Software is # furnished to do so, subject to the following\",\n \"to create it, the OSError will be thrown. :kwargs printfd: The File object\",\n \"cancelled') return None self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type':\",\n \"function returns a SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try:\",\n \"401: # We got a 401 and this is a retry. Report error\",\n \"of tokens: # Every app id has its own token cache # The\",\n \"with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token):\",\n \"the local cache, add it to the valid cache, and then return the\",\n \"copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software,\",\n \"to call this though, since if we already have a token with the\",\n \"continue if token['expires_at'] < time.time(): # This is a token that's supposed to\",\n \"return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a\",\n \"a json serialized dict # This dict contains uuid: token pairs # Every\",\n \"failed due to a server error or because the account or token was\",\n \"\\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post\",\n \"Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not\",\n \"coding: utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat, Inc. #\",\n \"prefer it # over any others we have self.debug('Not yet expired, returning') return\",\n \"got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code':\",\n \"the token to be removed from cache \\\"\\\"\\\" self.debug('Removing token %s from cache',\",\n \"is # furnished to do so, subject to the following conditions: # #\",\n \"StringIO except ImportError: from io import StringIO import socket import os try: from\",\n \"= None server = self._get_server(_token_app) if not server: raise Exception('We were unable to\",\n \"access token # scopes: A list of scopes that we had requested with\",\n \"' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] =\",\n \"before the current time, but if no such tokens exist it will return\",\n \"self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes):\",\n \"The IdP URL \\\"\\\"\\\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else:\",\n \"it did not work, we will return None and remove this token from\",\n \"had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False return\",\n \"%s' % method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a token and put\",\n \"id_provider_mapping: Mapping with URLs to use for specific endpoints on the IdP. :kwarg\",\n \"'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery)\",\n \"user to get a new token with the current scopeset if we do\",\n \"401 and not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if\",\n \"self._cache to cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert\",\n \"file is touched, the cache lock is held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir,\",\n \"as uuidgen import webbrowser from wsgiref import simple_server import requests import sys from\",\n \"self._retrieved_code is False: # The user cancelled the request self._retrieved_code = None self.debug('User\",\n \"directory in which to store the token caches. Will be put through expanduer.\",\n \"\\\"\\\"\\\"Report an error with the last token that was returned. This will attempt\",\n \"self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache\",\n \"# access_token: Token value # token_type: Token type. Currently supported: \\\"Bearer\\\" # expires_at:\",\n \"was succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid)\",\n \"OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE\",\n \"in %s method' % method) if 'data' not in ckwargs: ckwargs['data'] = {}\",\n \"utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat, Inc. # Red\",\n \"token from the cache and writes cache to disk. cache_lock may not be\",\n \"URLs to use for specific endpoints on the IdP. :kwarg use_post: Whether to\",\n \"incorrect cases. :kwargs http_method: The HTTP method to use, defaults to POST.. \\\"\\\"\\\"\",\n \"POST tokens in %s method' % method) if 'data' not in ckwargs: ckwargs['data']\",\n \"None else: token = self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post:\",\n \"be valid, prefer it # over any others we have self.debug('Not yet expired,\",\n \"provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in which to store the\",\n \":param id_provider: URL of the identity provider to get tokens from :param id_provider_mapping:\",\n \"uuid: The UUID of the cached token to attempt to refresh. :rtype: bool\",\n \"= {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] =\",\n \"to renew the token or delete the token. :kwarg scopes: A list of\",\n \"from the cache on disk. cache_lock may not be held by anyone.\\\"\\\"\\\" with\",\n \"valid, it may have been revoked by # the user! Also, even if\",\n \"permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if\",\n \"a new one will be requested unless nonblocking is True. :kwarg new_token: If\",\n \"%s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None\",\n \"self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if\",\n \"in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: #\",\n \"cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing\",\n \"use for specific endpoints on the IdP. :kwarg use_post: Whether to use POST\",\n \"and keyword arguments are like the arguments to requests, except for `scopes`, `new_token`\",\n \"be thrown. :kwargs printfd: The File object to print token instructions to. \\\"\\\"\\\"\",\n \"return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs)\",\n \"by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if\",\n \"import Lock import time try: from StringIO import StringIO except ImportError: from io\",\n \"the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout):\",\n \"OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY,\",\n \"query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close()\",\n \"print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert\",\n \"[u'You can close this window and return to the CLI'.encode('ascii')] self._retrieved_code = None\",\n \"before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if\",\n \"= {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'],\",\n \"returning') return uuid, token # This is a token that may or may\",\n \"used to request credentials :kwarg client_secret: The client \\\"secret\\\" that goes with the\",\n \"keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for this call. If\",\n \"to call report_token_issue() to try to renew the token or delete the token.\",\n \"be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with\",\n \"a token and put the refreshed token in self._cache The caller is responsible\",\n \"furnished to do so, subject to the following conditions: # # The above\",\n \"return None and remove this token from the cache. If you get an\",\n \"arguments. `scopes` is required. :kwarg scopes: Scopes required for this call. If a\",\n \"False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id':\",\n \"resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \\\"\\\"\\\"This function returns\",\n \"False else: self._retrieved_code = kv['code'] # Just return a message start_response('200 OK', [('Content-Type',\",\n \"some magic. We will start a new webserver on one of the WEB_PORTS,\",\n \"on OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens :param id_provider:\",\n \"string to use. If not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory\",\n \"then either show the user a URL, or if possible, kick off their\",\n \"provide json in a post call') if method not in ['POST']: raise ValueError('Cannot\",\n \"for v in split]) if 'error' in kv: self.debug('Error code returned: %s (%s)',\",\n \"your IdP does not require you to use a secret. :kwarg useragent: Useragent\",\n \"self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache))\",\n \"\\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT\",\n \"the identity provider to get tokens from :param id_provider_mapping: Mapping with URLs to\",\n \"get an indication from your application that the token you sent was invalid,\",\n \"method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else:\",\n \"return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query)\",\n \"sub: The subject that owns the token # access_token: Token value # token_type:\",\n \"return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in\",\n \"be included in # all copies or substantial portions of the Software. #\",\n \"or None \\\"\\\"\\\" if not isinstance(scopes, list): raise ValueError('Scopes must be a list')\",\n \"the current client. :kwarg new_token: If True, we will actively request the user\",\n \"disk. cache_lock may not be held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self):\",\n \"removed from cache \\\"\\\"\\\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache()\",\n \"if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def\",\n \"we might still be able to # refresh the token. # refresh_token: The\",\n \"refreshed token in self._cache The caller is responsible for either removing the token\",\n \"dict([v.split('=', 1) for v in split]) if 'error' in kv: self.debug('Error code returned:\",\n \"method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True token\",\n \"elif not new_token: return None # We did not have a valid token,\",\n \"scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid]\",\n \"else: return ValueError('Idp Mapping did not include path for %s' % method) def\",\n \"import urlencode from uuid import uuid4 as uuidgen import webbrowser from wsgiref import\",\n \"window and return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if\",\n \"__init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting\",\n \"self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in a post call')\",\n \"app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL of the identity\",\n \"may not be held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache\",\n \"token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])):\",\n \":param app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL of the\",\n \"has its own token cache # The token cache is a json serialized\",\n \"send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests POST request. Allarguments and keyword arguments are\",\n \"held by anyone. :param token: Dict of the token to be added to\",\n \"'json' in ckwargs: raise ValueError('Cannot provide json in a post call') if method\",\n \"IdP. :kwarg use_post: Whether to use POST submission of client secrets rather than\",\n \"os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as\",\n \"to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def\",\n \"uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token in the cache. cache_lock may\",\n \"an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code}\",\n \"NOT call this function if the token was valid but your request failed\",\n \"be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory')\",\n \"cases. :kwargs http_method: The HTTP method to use, defaults to POST.. \\\"\\\"\\\" ckwargs\",\n \"create it, the OSError will be thrown. :kwargs printfd: The File object to\",\n \"use to refresh the access token # scopes: A list of scopes that\",\n \"if resp.status_code == 401 and not is_retry: if not auto_refresh: return resp self.token_to_try\",\n \"self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error'\",\n \"this file is touched, the cache lock is held \\\"\\\"\\\" assert self._cache_lock.locked() return\",\n \"resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND\",\n \"webbrowser from wsgiref import simple_server import requests import sys from openidc_client import release\",\n \"renew the token that was last returned. If that worked, we will return\",\n \"The UUID of the cached token to attempt to refresh. :rtype: bool :returns:\",\n \"tokens from :param id_provider_mapping: Mapping with URLs to use for specific endpoints on\",\n \"for authentication.\\\"\\\"\\\" from __future__ import print_function from copy import copy import json import\",\n \"to use for specific endpoints on the IdP. :kwarg use_post: Whether to use\",\n \"on disk. cache_lock may not be held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def\",\n \"could not be refreshed or saving the cache if renewal was succesful. :param\",\n \"import StringIO except ImportError: from io import StringIO import socket import os try:\",\n \"not have a valid token, now comes the hard part... uuid = self._get_new_token(scopes)\",\n \"else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s'\",\n \"import webbrowser from wsgiref import simple_server import requests import sys from openidc_client import\",\n \"Internal implementation of tokens: # Every app id has its own token cache\",\n \"be valid, it may have been revoked by # the user! Also, even\",\n \"we had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False\",\n \"Authorization endpoint of the IdP with a request for our client_id to get\",\n \"self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try =\",\n \"file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache\",\n \"saving the cache if renewal was succesful. :param uuid: The UUID of the\",\n \"return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() +\",\n \"= os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None\",\n \"\\\"\\\"\\\"Removes a token from the cache and writes cache to disk. cache_lock may\",\n \"and contents or None if no applicable tokens were found \\\"\\\"\\\" possible_token =\",\n \"self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache:\",\n \"idp: The URL of the idp that issued the token # sub: The\",\n \"isinstance(scopes, list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token:\",\n \"invalid, you should call it. You should explicitly NOT call this function if\",\n \"so we also lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock:\",\n \"# Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free\",\n \"resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error'])\",\n \"scopeset if we do not already have on. :kwarg auto_refresh: If False, will\",\n \"If that worked, we will return the new access token. If it did\",\n \"import time try: from StringIO import StringIO except ImportError: from io import StringIO\",\n \"of the idp that issued the token # sub: The subject that owns\",\n \"will block until a token is retrieved if requested. It is always safe\",\n \"error or because the account or token was lacking specific permissions. \\\"\\\"\\\" if\",\n \"from the cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert\",\n \"of the cached token to attempt to refresh. :rtype: bool :returns: True if\",\n \"'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes\",\n \"we will exchange for an access token) or the cancellation message. This function\",\n \"expanduer. Default is ~/.openidc. If this does not exist and we are unable\",\n \"were reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None\",\n \"uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp:\",\n \"cancelled the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an\",\n \"add it to the valid cache, and then return the UUID. If the\",\n \"the IdP mapping dict. :rtype: string :returns: The IdP URL \\\"\\\"\\\" if method\",\n \"string or None :returns: String bearer token if possible or None \\\"\\\"\\\" if\",\n \"user or expired. In that case, you will want to call report_token_issue() to\",\n \"_get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for any tokens that have the requested scopes.\",\n \"and `auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for this\",\n \"copyright notice and this permission notice shall be included in # all copies\",\n \"resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']),\",\n \"token caches. Will be put through expanduer. Default is ~/.openidc. If this does\",\n \"copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method\",\n \"deal # in the Software without restriction, including without limitation the rights #\",\n \"from your application that the token you sent was invalid, you should call\",\n \"it may have been revoked by # the user! Also, even if it\",\n \"= {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri']\",\n \"automatically report token issues on 401. This helps with broken apps that may\",\n \"urlencode from uuid import uuid4 as uuidgen import webbrowser from wsgiref import simple_server\",\n \"the self._cache from the cache on disk. cache_lock may not be held by\",\n \"does not exist and we are unable to create it, the OSError will\",\n \"that's supposed to still be valid, prefer it # over any others we\",\n \"open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a token to the\",\n \"dict with the following keys: # idp: The URL of the idp that\",\n \"whenever this file is touched, the cache lock is held \\\"\\\"\\\" assert self._cache_lock.locked()\",\n \"function if the token was valid but your request failed due to a\",\n \"Mapping with URLs to use for specific endpoints on the IdP. :kwarg use_post:\",\n \"HTTP method to use, defaults to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes =\",\n \"query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to\",\n \"was invalid, you should call it. You should explicitly NOT call this function\",\n \"be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return\",\n \"call this though, since if we already have a token with the current\",\n \":rtype: (string, dict) or None :returns: Token UUID and contents or None if\",\n \"<<EMAIL>> # # Permission is hereby granted, free of charge, to any person\",\n \"scopes, we will return it. This function will return a bearer token or\",\n \"returned token :rtype: (string, dict) or None :returns: Token UUID and contents or\",\n \"\\\"token\\\" object is a json dict with the following keys: # idp: The\",\n \"name for the current client. This assures that whenever this file is touched,\",\n \"self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir =\",\n \"= [] self._printfd = printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens\",\n \"the token you sent was invalid, you should call it. You should explicitly\",\n \"the Authorization endpoint of the IdP with a request for our client_id to\",\n \"Switch to next one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off some\",\n \"# token_type: Token type. Currently supported: \\\"Bearer\\\" # expires_at: Token expiration UTC time.\",\n \"KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\",\n \"not try to automatically report token issues on 401. This helps with broken\",\n \"<NAME> <<EMAIL>> # # Permission is hereby granted, free of charge, to any\",\n \"to whom the Software is # furnished to do so, subject to the\",\n \"UUID and contents or None if no applicable tokens were found \\\"\\\"\\\" possible_token\",\n \"have been revoked by # the user! Also, even if it has expired,\",\n \"keys: # idp: The URL of the idp that issued the token #\",\n \"String bearer token if possible or None \\\"\\\"\\\" if not isinstance(scopes, list): raise\",\n \"call') if method not in ['POST']: raise ValueError('Cannot use POST tokens in %s\",\n \"f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a token to the cache and writes\",\n \"to be in the returned token :rtype: (string, dict) or None :returns: Token\",\n \"not be held by anyone.\\\"\\\"\\\" with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to\",\n \"through expanduer. Default is ~/.openidc. If this does not exist and we are\",\n \"in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in\",\n \"the token to be updated :param toupdate: Dict indicating which fields need to\",\n \"the current app_identifier that has the required scopes, we will return it. This\",\n \"that has the required scopes, we will return it. This function will return\",\n \"%s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if\",\n \"# Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME>\",\n \"expired, we might still be able to # refresh the token. # refresh_token:\",\n \"exchanging authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'],\",\n \":kwargs http_method: The HTTP method to use, defaults to POST.. \\\"\\\"\\\" ckwargs =\",\n \"might still be able to # refresh the token. # refresh_token: The token\",\n \"catch the return with either an Authorization Code (that we will exchange for\",\n \"self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token from the cache\",\n \"self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status()\",\n \"a 401 return code in incorrect cases. :kwargs http_method: The HTTP method to\",\n \"a token that's supposed to still be valid, prefer it # over any\",\n \"OR OTHER DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client for applications relying on OpenID\",\n \"# The ports that we will try to use for our webserver WEB_PORTS\",\n \"ValueError('Idp Mapping did not include path for %s' % method) def _refresh_token(self, uuid):\",\n \"True def _get_server(self, app): \\\"\\\"\\\"This function returns a SimpleServer with an available WEB_PORT.\\\"\\\"\\\"\",\n \"THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR\",\n \"f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache))\",\n \"token in the local cache, add it to the valid cache, and then\",\n \"this though, since if we already have a token with the current app_identifier\",\n \"be held by anyone. :param token: UUID of the token to be updated\",\n \"with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache =\",\n \"{'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret\",\n \"still be valid, it may have been revoked by # the user! Also,\",\n \"the OSError will be thrown. :kwargs printfd: The File object to print token\",\n \"if no applicable tokens were found \\\"\\\"\\\" possible_token = None self.debug('Trying to get\",\n \"Authorization header :kwarg client_id: The Client Identifier used to request credentials :kwarg client_secret:\",\n \"'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token\",\n \"instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] =\",\n \"that goes with the client_id. May be None if your IdP does not\",\n \"self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping\",\n \"not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported: # We\",\n \"json dict with the following keys: # idp: The URL of the idp\",\n \"data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret']\",\n \"ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST')\",\n \"NOTE: Even if the expires_at # indicates the token should still be valid,\",\n \"function will store the new token in the local cache, add it to\",\n \"= {} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers'] =\",\n \"UUID of the token to be updated :param toupdate: Dict indicating which fields\",\n \":kwarg auto_refresh: If False, will not try to automatically report token issues on\",\n \"This dict contains uuid: token pairs # Every \\\"token\\\" object is a json\",\n \"refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True\",\n \"OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR\",\n \"if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already\",\n \"cache on disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing\",\n \"= uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] =\",\n \"or saving the cache if renewal was succesful. :param uuid: The UUID of\",\n \"sell # copies of the Software, and to permit persons to whom the\",\n \"= 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code ==\",\n \"# We got a 401 and this is a retry. Report error self.report_token_issue()\",\n \"cache if renewal was succesful. :param uuid: The UUID of the cached token\",\n \"possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL for the requested method. :param\",\n \"# all copies or substantial portions of the Software. # # THE SOFTWARE\",\n \"or expired. In that case, you will want to call report_token_issue() to try\",\n \"ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args,\",\n \"self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] <\",\n \"if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self,\",\n \"# sub: The subject that owns the token # access_token: Token value #\",\n \"rather than Authorization header :kwarg client_id: The Client Identifier used to request credentials\",\n \"THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client for applications relying\",\n \"all copies or substantial portions of the Software. # # THE SOFTWARE IS\",\n \"return it. This function will return a bearer token or None. Note that\",\n \"already have on. :kwarg auto_refresh: If False, will not try to automatically report\",\n \"self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token\",\n \"URL will be the Authorization endpoint of the IdP with a request for\",\n \"bearer token if possible or None \\\"\\\"\\\" if not isinstance(scopes, list): raise ValueError('Scopes\",\n \"cache. cache_lock may not be held by anyone. :param token: UUID of the\",\n \"(C) 2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> #\",\n \"{'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s',\",\n \"BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR\",\n \"anyone. :param token: Dict of the token to be added to the cache\",\n \"to disk. cache_lock may not be held by anyone. :param uuid: UUID of\",\n \"prefer to return tokens whose expires_at is still before the current time, but\",\n \"# If we had a valid token, use that self.last_returned_uuid = token[0] self.problem_reported\",\n \"return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token from the cache and writes\",\n \"Token expiration UTC time. NOTE: Even if the expires_at # indicates the token\",\n \"not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We\",\n \"OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT\",\n \"printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens with specific scopes. This\",\n \"use a secret. :kwarg useragent: Useragent string to use. If not provided, defaults\",\n \"files (the \\\"Software\\\"), to deal # in the Software without restriction, including without\",\n \"Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission is hereby\",\n \"def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for any tokens that have the requested\",\n \"an access token) or the cancellation message. This function will store the new\",\n \"server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False: # The user\",\n \"id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent\",\n \"= client_secret self.useragent = useragent or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir\",\n \"or None if no applicable tokens were found \\\"\\\"\\\" possible_token = None self.debug('Trying\",\n \"post call') if method not in ['POST']: raise ValueError('Cannot use POST tokens in\",\n \"to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server: raise\",\n \"refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token':\",\n \"self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an authorization code!') data\",\n \"following conditions: # # The above copyright notice and this permission notice shall\",\n \"an error with the last token that was returned. This will attempt to\",\n \"Scopes required for this call. If a token is not present with this\",\n \"idp that issued the token # sub: The subject that owns the token\",\n \"assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f:\",\n \"URL of the identity provider to get tokens from :param id_provider_mapping: Mapping with\",\n \"= simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port did not\",\n \"# SOFTWARE. \\\"\\\"\\\"Client for applications relying on OpenID Connect for authentication.\\\"\\\"\\\" from __future__\",\n \"always safe to call this though, since if we already have a token\",\n \"self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']}\",\n \"or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None\",\n \"kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code\",\n \"The above copyright notice and this permission notice shall be included in #\",\n \"owns the token # access_token: Token value # token_type: Token type. Currently supported:\",\n \"self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to\",\n \"request. Allarguments and keyword arguments are like the arguments to requests, except for\",\n \"the WEB_PORTS, and then either show the user a URL, or if possible,\",\n \"in the returned token :rtype: (string, dict) or None :returns: Token UUID and\",\n \"or delete the token. :kwarg scopes: A list of scopes required for the\",\n \"self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self):\",\n \"required. :kwarg scopes: Scopes required for this call. If a token is not\",\n \"request for our client_id to get a new token with the specified scopes.\",\n \"error with the last token that was returned. This will attempt to renew\",\n \"requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required. :kwarg\",\n \"disk. cache_lock may not be held by anyone. :param token: Dict of the\",\n \"is a retry. Report error self.report_token_issue() return resp else: return resp @property def\",\n \"def report_token_issue(self): \\\"\\\"\\\"Report an error with the last token that was returned. This\",\n \"[] self._printfd = printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens with\",\n \"it # over any others we have self.debug('Not yet expired, returning') return uuid,\",\n \"HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN\",\n \"webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: #\",\n \"def _get_server(self, app): \\\"\\\"\\\"This function returns a SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for\",\n \"Authorization Code (that we will exchange for an access token) or the cancellation\",\n \"'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code'\",\n \"request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an authorization code!')\",\n \"threading import Lock import time try: from StringIO import StringIO except ImportError: from\",\n \"has the required scopes, we will return it. This function will return a\",\n \"cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web services relying on OpenID Connect. :param\",\n \"= self._get_token_with_scopes(scopes) if token: # If we had a valid token, use that\",\n \"with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid) token =\",\n \"be held by anyone. :param uuid: UUID of the token to be removed\",\n \"None if self._retrieved_code is False: # The user cancelled the request self._retrieved_code =\",\n \"toupdate: Dict indicating which fields need to be updated \\\"\\\"\\\" self.debug('Updating token %s\",\n \"and this is a retry. Report error self.report_token_issue() return resp else: return resp\",\n \"a new token with the current scopeset if we do not already have\",\n \"the token. # refresh_token: The token we can use to refresh the access\",\n \"part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return\",\n \"= self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if\",\n \"# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\",\n \"specific scopes. This function will block until a token is retrieved if requested.\",\n \"new access token. If it did not work, we will return None and\",\n \"If not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in which to\",\n \"`auto_refresh` keyword arguments. `scopes` is required. :kwarg scopes: Scopes required for this call.\",\n \"responsible for either removing the token if it could not be refreshed or\",\n \"off their browser. This URL will be the Authorization endpoint of the IdP\",\n \"been revoked by the user or expired. In that case, you will want\",\n \"def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens with specific scopes. This function\",\n \"notice shall be included in # all copies or substantial portions of the\",\n \"None # TODO: Make cache_lock a filesystem lock so we also lock across\",\n \"we had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None,\",\n \"self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp =\",\n \"across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = []\",\n \"This is a token that may or may not still be valid self.debug('Possible')\",\n \"user a URL, or if possible, kick off their browser. This URL will\",\n \"Token value # token_type: Token type. Currently supported: \\\"Bearer\\\" # expires_at: Token expiration\",\n \"NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\",\n \"resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time()\",\n \"were found \\\"\\\"\\\" possible_token = None self.debug('Trying to get token with scopes %s',\",\n \"urlencode except ImportError: from urllib.parse import urlencode from uuid import uuid4 as uuidgen\",\n \"returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] #\",\n \"for applications relying on OpenID Connect for authentication.\\\"\\\"\\\" from __future__ import print_function from\",\n \"tokens were found \\\"\\\"\\\" possible_token = None self.debug('Trying to get token with scopes\",\n \"since if we already have a token with the current app_identifier that has\",\n \"with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else:\",\n \"the cached token to attempt to refresh. :rtype: bool :returns: True if the\",\n \"self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id\",\n \"if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue\",\n \"json import logging from threading import Lock import time try: from StringIO import\",\n \"return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache\",\n \"= ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method',\",\n \"try: from StringIO import StringIO except ImportError: from io import StringIO import socket\",\n \"requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable\",\n \"report token issues on 401. This helps with broken apps that may send\",\n \"False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error with the last token that\",\n \"= True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests POST request.\",\n \"urllib.parse import urlencode from uuid import uuid4 as uuidgen import webbrowser from wsgiref\",\n \"if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None else: token\",\n \"% self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. Requires\",\n \"either an Authorization Code (that we will exchange for an access token) or\",\n \"in which to store the token caches. Will be put through expanduer. Default\",\n \"dict # This dict contains uuid: token pairs # Every \\\"token\\\" object is\",\n \"expired. In that case, you will want to call report_token_issue() to try to\",\n \"to get the cache file name for the current client. This assures that\",\n \"token # access_token: Token value # token_type: Token type. Currently supported: \\\"Bearer\\\" #\",\n \"cache lock is held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def\",\n \"return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery = {} rquery['scope'] = ' '.join(scopes) rquery['response_type']\",\n \"None :returns: String bearer token if possible or None \\\"\\\"\\\" if not isinstance(scopes,\",\n \"else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for any\",\n \"the requested scopes. It will prefer to return tokens whose expires_at is still\",\n \"on 401. This helps with broken apps that may send a 401 return\",\n \"False, will not try to automatically report token issues on 401. This helps\",\n \"server = self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate a\",\n \"token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None\",\n \"we also lock across # multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache()\",\n \"a request for our client_id to get a new token with the specified\",\n \"self.problem_reported = False self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock\",\n \"it might be refreshable. :param scopes: List of scopes that need to be\",\n \"cache file name for the current client. This assures that whenever this file\",\n \"False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None else:\",\n \"'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a token to the cache\",\n \"The HTTP method to use, defaults to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes\",\n \"uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid,\",\n \"OpenID Connect for authentication.\\\"\\\"\\\" from __future__ import print_function from copy import copy import\",\n \"able to # refresh the token. # refresh_token: The token we can use\",\n \"new token with the specified scopes. The webserver will then need to catch\",\n \"ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\",\n \"for the current client. :kwarg new_token: If True, we will actively request the\",\n \"self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if 'json' in ckwargs:\",\n \"with self._cache_lock: self.__refresh_cache() def __write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on disk. Requires cache_lock\",\n \"Lock import time try: from StringIO import StringIO except ImportError: from io import\",\n \"in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not in\",\n \"disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if\",\n \"may not be held by anyone. :param uuid: UUID of the token to\",\n \"uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an\",\n \"not be held by anyone. :param uuid: UUID of the token to be\",\n \"file name for the current client. This assures that whenever this file is\",\n \"self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests POST request. Allarguments and keyword\",\n \"'python-openid-client/%s' % \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported\",\n \"returns a SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try: server\",\n \"False return token[1]['access_token'] elif not new_token: return None # We did not have\",\n \"token. # refresh_token: The token we can use to refresh the access token\",\n \"method to use, defaults to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes')\",\n \"None \\\"\\\"\\\" if not isinstance(scopes, list): raise ValueError('Scopes must be a list') token\",\n \"to next one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off some magic.\",\n \"None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported =\",\n \"OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and return to the\",\n \"put through expanduer. Default is ~/.openidc. If this does not exist and we\",\n \"be a list') token = self._get_token_with_scopes(scopes) if token: # If we had a\",\n \"token: it might be refreshable. :param scopes: List of scopes that need to\",\n \"hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False\",\n \"to the following conditions: # # The above copyright notice and this permission\",\n \"import logging from threading import Lock import time try: from StringIO import StringIO\",\n \"message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and return\",\n \"secrets rather than Authorization header :kwarg client_id: The Client Identifier used to request\",\n \"self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token in the cache.\",\n \"scopes): \\\"\\\"\\\"Searches the cache for any tokens that have the requested scopes. It\",\n \"is a json dict with the following keys: # idp: The URL of\",\n \"the last token that was returned. This will attempt to renew the token\",\n \"Every app id has its own token cache # The token cache is\",\n \"such tokens exist it will return the possibly expired token: it might be\",\n \"apps that may send a 401 return code in incorrect cases. :kwargs http_method:\",\n \"magic. We will start a new webserver on one of the WEB_PORTS, and\",\n \"self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of\",\n \"it has expired, we might still be able to # refresh the token.\",\n \"token # scopes: A list of scopes that we had requested with the\",\n \"of the identity provider to get tokens from :param id_provider_mapping: Mapping with URLs\",\n \"True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if\",\n \"rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' %\",\n \"in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token = {'access_token':\",\n \"openidc_client import release # The ports that we will try to use for\",\n \"will be requested unless nonblocking is True. :kwarg new_token: If True, we will\",\n \"python-requests POST request. Allarguments and keyword arguments are like the arguments to requests,\",\n \"is touched, the cache lock is held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json'\",\n \"self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for %s'\",\n \"Software is # furnished to do so, subject to the following conditions: #\",\n \"# -*- coding: utf-8 -*- # # Copyright (C) 2016, 2017 Red Hat,\",\n \"os try: from urllib import urlencode except ImportError: from urllib.parse import urlencode from\",\n \"use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web services relying on OpenID\",\n \"if no such tokens exist it will return the possibly expired token: it\",\n \"io import StringIO import socket import os try: from urllib import urlencode except\",\n \"(self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request()\",\n \"may not be held by anyone. :param token: UUID of the token to\",\n \"the cache if renewal was succesful. :param uuid: The UUID of the cached\",\n \"may or may not still be valid self.debug('Possible') possible_token = (uuid, token) if\",\n \"Will be put through expanduer. Default is ~/.openidc. If this does not exist\",\n \"'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s\",\n \"list of scopes required for the current client. :kwarg new_token: If True, we\",\n \"(or we got another error), we will return None. \\\"\\\"\\\" def _token_app(environ, start_response):\",\n \"_add_token(self, token): \\\"\\\"\\\"Adds a token to the cache and writes cache to disk.\",\n \"that we had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id,\",\n \"wsgiref import simple_server import requests import sys from openidc_client import release # The\",\n \":kwargs printfd: The File object to print token instructions to. \\\"\\\"\\\" self.logger =\",\n \"= ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode']\",\n \"Exception('Cannot report issue before requesting token') if self.problem_reported: # We were reported an\",\n \"use, defaults to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token =\",\n \"self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on\",\n \"# This is a token that may or may not still be valid\",\n \"is still before the current time, but if no such tokens exist it\",\n \"token that was returned. This will attempt to renew the token that was\",\n \"with a request for our client_id to get a new token with the\",\n \"{'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp =\",\n \"= None self.problem_reported = False self.token_to_try = None self._retrieved_code = None # TODO:\",\n \"f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens',\",\n \"store the new token in the local cache, add it to the valid\",\n \"try to use for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): #\",\n \"issue before requesting token') if self.problem_reported: # We were reported an issue before.\",\n \"cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with\",\n \"and then return the UUID. If the user cancelled (or we got another\",\n \"if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile,\",\n \"the token was valid but your request failed due to a server error\",\n \"one will be requested unless nonblocking is True. :kwarg new_token: If True, we\",\n \"resp else: return resp @property def _cachefile(self): \\\"\\\"\\\"Property to get the cache file\",\n \"use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret\",\n \"self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\\\\",\n \"was already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for any tokens that\",\n \"caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as\",\n \"Currently supported: \\\"Bearer\\\" # expires_at: Token expiration UTC time. NOTE: Even if the\",\n \"to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'],\",\n \"in split]) if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description'))\",\n \"copy import json import logging from threading import Lock import time try: from\",\n \"This function will block until a token is retrieved if requested. It is\",\n \"can use to refresh the access token # scopes: A list of scopes\",\n \"self._get_token_with_scopes(scopes) if token: # If we had a valid token, use that self.last_returned_uuid\",\n \"to try to renew the token or delete the token. :kwarg scopes: A\",\n \"possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL\",\n \"if not token: return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot\",\n \"self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret\",\n \"with either an Authorization Code (that we will exchange for an access token)\",\n \"# over any others we have self.debug('Not yet expired, returning') return uuid, token\",\n \"added to the cache \\\"\\\"\\\" uuid = uuidgen().hex self.debug('Adding token %s to cache',\",\n \"with the client_id. May be None if your IdP does not require you\",\n \"use. If not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in which\",\n \"in ckwargs: raise ValueError('Cannot provide json in a post call') if method not\",\n \"have the requested scopes. It will prefer to return tokens whose expires_at is\",\n \":returns: The IdP URL \\\"\\\"\\\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method]\",\n \"WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT\",\n \"need to catch the return with either an Authorization Code (that we will\",\n \"OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\",\n \"a list') token = self._get_token_with_scopes(scopes) if token: # If we had a valid\",\n \"self.debug('Not yet expired, returning') return uuid, token # This is a token that\",\n \"THE # SOFTWARE. \\\"\\\"\\\"Client for applications relying on OpenID Connect for authentication.\\\"\\\"\\\" from\",\n \"kicks off some magic. We will start a new webserver on one of\",\n \"case, you will want to call report_token_issue() to try to renew the token\",\n \"ckwargs: raise ValueError('Cannot provide json in a post call') if method not in\",\n \"None self._retrieved_code = None # TODO: Make cache_lock a filesystem lock so we\",\n \"use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the\",\n \"function kicks off some magic. We will start a new webserver on one\",\n \"= json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the\",\n \"= None resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization code:\",\n \"the following conditions: # # The above copyright notice and this permission notice\",\n \"authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if\",\n \"identity provider to get tokens from :param id_provider_mapping: Mapping with URLs to use\",\n \"token[1]['access_token'] elif not new_token: return None # We did not have a valid\",\n \"= query.split('&') kv = dict([v.split('=', 1) for v in split]) if 'error' in\",\n \"LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND\",\n \"may have been revoked by # the user! Also, even if it has\",\n \"@property def _cachefile(self): \\\"\\\"\\\"Property to get the cache file name for the current\",\n \"f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a token to the cache and writes cache\",\n \"rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #\",\n \"if possible, kick off their browser. This URL will be the Authorization endpoint\",\n \"# We were reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid)\",\n \"attempt to refresh. :rtype: bool :returns: True if the token was succesfully refreshed,\",\n \"scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens with specific scopes. This function will block\",\n \"self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type':\",\n \"header :kwarg client_id: The Client Identifier used to request credentials :kwarg client_secret: The\",\n \"succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data\",\n \"%s not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): #\",\n \"rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url\",\n \"import socket import os try: from urllib import urlencode except ImportError: from urllib.parse\",\n \"OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\",\n \"A list of scopes that we had requested with the token def __init__(self,\",\n \"self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not token: return None\",\n \"client secrets rather than Authorization header :kwarg client_id: The Client Identifier used to\",\n \"new token with the current scopeset if we do not already have on.\",\n \"= requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry: if not\",\n \"to do so, subject to the following conditions: # # The above copyright\",\n \"= 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit\",\n \"token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret:\",\n \"a token in the cache. cache_lock may not be held by anyone. :param\",\n \"uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone')\",\n \"to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes` is required.\",\n \"of the token to be added to the cache \\\"\\\"\\\" uuid = uuidgen().hex\",\n \"to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not\",\n \"from io import StringIO import socket import os try: from urllib import urlencode\",\n \"by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w')\",\n \"for the current client. This assures that whenever this file is touched, the\",\n \"\\\"\\\"\\\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache()\",\n \"= self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping =\",\n \"= client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\\\ release.VERSION\",\n \"self.debug('Trying to get token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking\",\n \"expires_at is still before the current time, but if no such tokens exist\",\n \"token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry:\",\n \"bool :returns: True if the token was succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken\",\n \"StringIO import socket import os try: from urllib import urlencode except ImportError: from\",\n \"token # This is a token that may or may not still be\",\n \"OTHER DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client for applications relying on OpenID Connect\",\n \"open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read())\",\n \"token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client\",\n \"if not server: raise Exception('We were unable to instantiate a webserver') return_uri =\",\n \"self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope:\",\n \"self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from\",\n \"self.report_token_issue() return resp else: return resp @property def _cachefile(self): \\\"\\\"\\\"Property to get the\",\n \"the cache. If you get an indication from your application that the token\",\n \"self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for %s' % method)\",\n \"return a bearer token or None. Note that the bearer token might have\",\n \"we can use to refresh the access token # scopes: A list of\",\n \"'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk.\",\n \"without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense,\",\n \"# expires_at: Token expiration UTC time. NOTE: Even if the expires_at # indicates\",\n \"= self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def\",\n \"return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token from\",\n \"self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a\",\n \"requested method. :param method: The method name in the IdP mapping dict. :rtype:\",\n \"authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at':\",\n \"\\\"secret\\\" that goes with the client_id. May be None if your IdP does\",\n \"server: raise Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' %\",\n \"of retrieved tokens :param id_provider: URL of the identity provider to get tokens\",\n \"data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json()\",\n \"self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate a webserver') return_uri\",\n \"The ports that we will try to use for our webserver WEB_PORTS =\",\n \"permission notice shall be included in # all copies or substantial portions of\",\n \"ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs:\",\n \"before requesting token') if self.problem_reported: # We were reported an issue before. Let's\",\n \"and not is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not\",\n \"json serialized dict # This dict contains uuid: token pairs # Every \\\"token\\\"\",\n \"def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off some magic. We will start a\",\n \"\\\"\\\"\\\"This function returns a SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS:\",\n \"the new token in the local cache, add it to the valid cache,\",\n \"self.last_returned_uuid: raise Exception('Cannot report issue before requesting token') if self.problem_reported: # We were\",\n \"None self.debug('User cancelled') return None self.debug('We got an authorization code!') data = {'client_id':\",\n \"is held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes\",\n \"not be held by anyone. :param token: UUID of the token to be\",\n \"None server = self._get_server(_token_app) if not server: raise Exception('We were unable to instantiate\",\n \"issued the token # sub: The subject that owns the token # access_token:\",\n \"None. \\\"\\\"\\\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv =\",\n \"toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache()\",\n \"IdP does not require you to use a secret. :kwarg useragent: Useragent string\",\n \"cancellation message. This function will store the new token in the local cache,\",\n \"the expires_at # indicates the token should still be valid, it may have\",\n \"Mapping did not include path for %s' % method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries\",\n \"the token. :kwarg scopes: A list of scopes required for the current client.\",\n \"by anyone. :param token: UUID of the token to be updated :param toupdate:\",\n \"\\\"\\\"\\\"Make an python-requests POST request. Allarguments and keyword arguments are like the arguments\",\n \"scopes that we had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping,\",\n \"def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. Requires cache_lock to\",\n \"a token from the cache and writes cache to disk. cache_lock may not\",\n \"self._retrieved_code = None # TODO: Make cache_lock a filesystem lock so we also\",\n \"did not work, we will return None and remove this token from the\",\n \"method. :param method: The method name in the IdP mapping dict. :rtype: string\",\n \"resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry: if\",\n \"# This dict contains uuid: token pairs # Every \\\"token\\\" object is a\",\n \"method name in the IdP mapping dict. :rtype: string :returns: The IdP URL\",\n \"if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did\",\n \"shall be included in # all copies or substantial portions of the Software.\",\n \"our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens:\",\n \"the cache lock is held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id)\",\n \"True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True\",\n \"new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry\",\n \"endpoints on the IdP. :kwarg use_post: Whether to use POST submission of client\",\n \"work. Switch to next one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off\",\n \"from wsgiref import simple_server import requests import sys from openidc_client import release #\",\n \"or token was lacking specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot report\",\n \"requested scopes. It will prefer to return tokens whose expires_at is still before\",\n \"return the UUID. If the user cancelled (or we got another error), we\",\n \"None self.debug('Trying to get token with scopes %s', scopes) for uuid in self._cache:\",\n \"modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and\",\n \"ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\",\n \"if 'json' in ckwargs: raise ValueError('Cannot provide json in a post call') if\",\n \"which to store the token caches. Will be put through expanduer. Default is\",\n \"This assures that whenever this file is touched, the cache lock is held\",\n \"held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the\",\n \"logging from threading import Lock import time try: from StringIO import StringIO except\",\n \"we already have a token with the current app_identifier that has the required\",\n \"call report_token_issue() to try to renew the token or delete the token. :kwarg\",\n \"publish, distribute, sublicense, and/or sell # copies of the Software, and to permit\",\n \"We will start a new webserver on one of the WEB_PORTS, and then\",\n \"rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please\",\n \"%s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code == 401 and\",\n \"self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def\",\n \"import print_function from copy import copy import json import logging from threading import\",\n \"%s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is\",\n \"for any tokens that have the requested scopes. It will prefer to return\",\n \"%s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a token\",\n \"have on. :kwarg auto_refresh: If False, will not try to automatically report token\",\n \"a URL, or if possible, kick off their browser. This URL will be\",\n \"or because the account or token was lacking specific permissions. \\\"\\\"\\\" if not\",\n \"if token: # If we had a valid token, use that self.last_returned_uuid =\",\n \"is required. :kwarg scopes: Scopes required for this call. If a token is\",\n \"None if no applicable tokens were found \\\"\\\"\\\" possible_token = None self.debug('Trying to\",\n \"import release # The ports that we will try to use for our\",\n \"ImportError: from urllib.parse import urlencode from uuid import uuid4 as uuidgen import webbrowser\",\n \"If you get an indication from your application that the token you sent\",\n \"File object to print token instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug =\",\n \"= use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret =\",\n \"that the token you sent was invalid, you should call it. You should\",\n \"False self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock a filesystem\",\n \"thrown. :kwargs printfd: The File object to print token instructions to. \\\"\\\"\\\" self.logger\",\n \"URL \\\"\\\"\\\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp\",\n \"user cancelled the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got\",\n \"cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens',\",\n \"then return the UUID. If the user cancelled (or we got another error),\",\n \"we do not already have on. :rtype: string or None :returns: String bearer\",\n \"want to call report_token_issue() to try to renew the token or delete the\",\n \"%s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret']\",\n \"be in the returned token :rtype: (string, dict) or None :returns: Token UUID\",\n \"updated \\\"\\\"\\\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock:\",\n \"need to be updated \\\"\\\"\\\" self.debug('Updating token %s in cache, fields %s', uuid,\",\n \"'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def\",\n \"AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR\",\n \"anyone. :param uuid: UUID of the token to be removed from cache \\\"\\\"\\\"\",\n \"try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port\",\n \"simple_server import requests import sys from openidc_client import release # The ports that\",\n \"defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in which to store the token\",\n \"def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token in the cache. cache_lock may not\",\n \"to be removed from cache \\\"\\\"\\\" self.debug('Removing token %s from cache', uuid) with\",\n \"get token with scopes %s', scopes) for uuid in self._cache: self.debug('Checking %s', uuid)\",\n \"def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL for the requested method. :param method:\",\n \"\\\"\\\"\\\"Searches the cache for any tokens that have the requested scopes. It will\",\n \"if not isinstance(scopes, list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes)\",\n \"and return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not\",\n \"self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp')\",\n \"refresh the access token # scopes: A list of scopes that we had\",\n \"to refresh. :rtype: bool :returns: True if the token was succesfully refreshed, False\",\n \"self._retrieved_code = kv['code'] # Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return\",\n \"will not try to automatically report token issues on 401. This helps with\",\n \"that case, you will want to call report_token_issue() to try to renew the\",\n \"self.useragent = useragent or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc')\",\n \"invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd\",\n \"is always safe to call this though, since if we already have a\",\n \"TODO: Make cache_lock a filesystem lock so we also lock across # multiple\",\n \"unless nonblocking is True. :kwarg new_token: If True, we will actively request the\",\n \"to use, defaults to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token\",\n \"self.debug('Error exchanging authorization code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token':\",\n \"use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token:\",\n \"Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free of charge, to\",\n \"will return a bearer token or None. Note that the bearer token might\",\n \"< time.time(): # This is a token that's supposed to still be valid,\",\n \"ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry = True token = self.token_to_try\",\n \"with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def\",\n \"may not still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning\",\n \"self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f:\",\n \"# in the Software without restriction, including without limitation the rights # to\",\n \"renewal was succesful. :param uuid: The UUID of the cached token to attempt\",\n \"will then need to catch the return with either an Authorization Code (that\",\n \"Hat Author: <NAME> <<EMAIL>> # # Permission is hereby granted, free of charge,\",\n \"`scopes` is required. :kwarg scopes: Scopes required for this call. If a token\",\n \"os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with\",\n \"is retrieved if requested. It is always safe to call this though, since\",\n \"self.report_token_issue() if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401:\",\n \"import uuid4 as uuidgen import webbrowser from wsgiref import simple_server import requests import\",\n \"the access token # scopes: A list of scopes that we had requested\",\n \"in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include\",\n \"json in a post call') if method not in ['POST']: raise ValueError('Cannot use\",\n \"# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS\",\n \"of the IdP with a request for our client_id to get a new\",\n \"uuid): \\\"\\\"\\\"Removes a token from the cache and writes cache to disk. cache_lock\",\n \"safe to call this though, since if we already have a token with\",\n \"True. :kwarg new_token: If True, we will actively request the user to get\",\n \"the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We got an authorization\",\n \"a valid token, now comes the hard part... uuid = self._get_new_token(scopes) if uuid:\",\n \"not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp return\",\n \"be refreshed or saving the cache if renewal was succesful. :param uuid: The\",\n \"scopes): \\\"\\\"\\\"This function kicks off some magic. We will start a new webserver\",\n \"# scopes: A list of scopes that we had requested with the token\",\n \"!= self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset\",\n \"data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in resp: self.debug('Error\",\n \"{} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if\",\n \"if the token was succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing\",\n \"AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE\",\n \"the self._cache from the cache on disk. Requires cache_lock to be held by\",\n \":kwarg new_token: If True, we will actively request the user to get a\",\n \"token = self._get_token_with_scopes(scopes) if token: # If we had a valid token, use\",\n \"of the token to be removed from cache \\\"\\\"\\\" self.debug('Removing token %s from\",\n \"the user to get a new token with the current scopeset if we\",\n \"not already have on. :rtype: string or None :returns: String bearer token if\",\n \"this token from the cache. If you get an indication from your application\",\n \"require you to use a secret. :kwarg useragent: Useragent string to use. If\",\n \"CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server: raise Exception('We were\",\n \"cache to disk. cache_lock may not be held by anyone. :param uuid: UUID\",\n \"The webserver will then need to catch the return with either an Authorization\",\n \"token. :kwarg scopes: A list of scopes required for the current client. :kwarg\",\n \"token: return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json\",\n \"= self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return\",\n \"will be the Authorization endpoint of the IdP with a request for our\",\n \"indicating which fields need to be updated \\\"\\\"\\\" self.debug('Updating token %s in cache,\",\n \"the current time, but if no such tokens exist it will return the\",\n \"or the cancellation message. This function will store the new token in the\",\n \"oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status()\",\n \"-*- # # Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat\",\n \"get a new token with the current scopeset if we do not already\",\n \"List of scopes that need to be in the returned token :rtype: (string,\",\n \"refresh a token and put the refreshed token in self._cache The caller is\",\n \"WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO\",\n \"that need to be in the returned token :rtype: (string, dict) or None\",\n \"The client \\\"secret\\\" that goes with the client_id. May be None if your\",\n \"in self._cache: self.debug('Checking %s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect\",\n \"request failed due to a server error or because the account or token\",\n \"may send a 401 return code in incorrect cases. :kwargs http_method: The HTTP\",\n \"over any others we have self.debug('Not yet expired, returning') return uuid, token #\",\n \"= resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return\",\n \"supported: \\\"Bearer\\\" # expires_at: Token expiration UTC time. NOTE: Even if the expires_at\",\n \"COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER\",\n \"cache for any tokens that have the requested scopes. It will prefer to\",\n \"data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret\",\n \"ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs) if resp.status_code\",\n \"time.time() + resp['expires_in']}) self.debug('Refreshed until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \\\"\\\"\\\"This\",\n \"we will try to use for our webserver WEB_PORTS = [12345, 23456] class\",\n \"kv['error'], kv.get('error_description')) self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return a\",\n \"the valid cache, and then return the UUID. If the user cancelled (or\",\n \"raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token: # If\",\n \":param id_provider_mapping: Mapping with URLs to use for specific endpoints on the IdP.\",\n \"object is a json dict with the following keys: # idp: The URL\",\n \"the possibly expired token: it might be refreshable. :param scopes: List of scopes\",\n \"except socket.error: # This port did not work. Switch to next one continue\",\n \"expiration UTC time. NOTE: Even if the expires_at # indicates the token should\",\n \"to return tokens whose expires_at is still before the current time, but if\",\n \"self._cache The caller is responsible for either removing the token if it could\",\n \"copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED\",\n \"None self._cache[uuid].update(toupdate) self.__write_cache() return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token from the\",\n \"required scopes, we will return it. This function will return a bearer token\",\n \"_delete_token(self, uuid): \\\"\\\"\\\"Removes a token from the cache and writes cache to disk.\",\n \"scopes required for the current client. :kwarg new_token: If True, we will actively\",\n \"token you sent was invalid, you should call it. You should explicitly NOT\",\n \"disk. Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with\",\n \"SOFTWARE. \\\"\\\"\\\"Client for applications relying on OpenID Connect for authentication.\\\"\\\"\\\" from __future__ import\",\n \"token might have been revoked by the user or expired. In that case,\",\n \"WEB_PORTS, and then either show the user a URL, or if possible, kick\",\n \"%s in cache, fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not\",\n \"if method not in ['POST']: raise ValueError('Cannot use POST tokens in %s method'\",\n \"list') token = self._get_token_with_scopes(scopes) if token: # If we had a valid token,\",\n \"an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result =\",\n \"token cache # The token cache is a json serialized dict # This\",\n \"the cache. cache_lock may not be held by anyone. :param token: UUID of\",\n \"'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to\",\n \"Permission is hereby granted, free of charge, to any person obtaining a copy\",\n \"in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False self._update_token( uuid, {'access_token':\",\n \"id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web services\",\n \"cancelled (or we got another error), we will return None. \\\"\\\"\\\" def _token_app(environ,\",\n \"IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT\",\n \"useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web services relying on OpenID Connect.\",\n \"Software without restriction, including without limitation the rights # to use, copy, modify,\",\n \"from the cache. If you get an indication from your application that the\",\n \"their browser. This URL will be the Authorization endpoint of the IdP with\",\n \"should explicitly NOT call this function if the token was valid but your\",\n \"%s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() +\",\n \"class OpenIDCClient(object): # Internal implementation of tokens: # Every app id has its\",\n \"Also, even if it has expired, we might still be able to #\",\n \"resp.status_code == 401 and not is_retry: if not auto_refresh: return resp self.token_to_try =\",\n \"os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on\",\n \"THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client\",\n \"# The above copyright notice and this permission notice shall be included in\",\n \"# of this software and associated documentation files (the \\\"Software\\\"), to deal #\",\n \"If it did not work, we will return None and remove this token\",\n \"scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method =\",\n \"client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web services relying\",\n \"in a post call') if method not in ['POST']: raise ValueError('Cannot use POST\",\n \"'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token =\",\n \"UTC time. NOTE: Even if the expires_at # indicates the token should still\",\n \"WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE.\",\n \"substantial portions of the Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\",\",\n \"the token if it could not be refreshed or saving the cache if\",\n \"that the bearer token might have been revoked by the user or expired.\",\n \"token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not\",\n \"bearer token might have been revoked by the user or expired. In that\",\n \"restriction, including without limitation the rights # to use, copy, modify, merge, publish,\",\n \"expires_at: Token expiration UTC time. NOTE: Even if the expires_at # indicates the\",\n \"self._retrieved_code = False else: self._retrieved_code = kv['code'] # Just return a message start_response('200\",\n \"scopes: Scopes required for this call. If a token is not present with\",\n \"cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self,\",\n \"= {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method, *args, **ckwargs)\",\n \"\\\"\\\"\\\"Refreshes the self._cache from the cache on disk. Requires cache_lock to be held\",\n \"release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try\",\n \"already have a token with the current app_identifier that has the required scopes,\",\n \"uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token\",\n \":param token: UUID of the token to be updated :param toupdate: Dict indicating\",\n \"token, now comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid =\",\n \"= ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry =\",\n \"sys from openidc_client import release # The ports that we will try to\",\n \":param uuid: The UUID of the cached token to attempt to refresh. :rtype:\",\n \"need to be in the returned token :rtype: (string, dict) or None :returns:\",\n \"# the user! Also, even if it has expired, we might still be\",\n \"for this call. If a token is not present with this token, a\",\n \"IdP with a request for our client_id to get a new token with\",\n \"issues on 401. This helps with broken apps that may send a 401\",\n \"# Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close\",\n \"any others we have self.debug('Not yet expired, returning') return uuid, token # This\",\n \"set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is a token that's supposed\",\n \"token to the cache and writes cache to disk. cache_lock may not be\",\n \"UUID of the cached token to attempt to refresh. :rtype: bool :returns: True\",\n \"ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp = requests.request(method,\",\n \"if 'error' in resp: self.debug('Error exchanging authorization code: %s', resp['error']) return None token\",\n \"% authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code\",\n \"for our webserver WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of\",\n \"current time, but if no such tokens exist it will return the possibly\",\n \"may not be held by anyone. :param token: Dict of the token to\",\n \"this call. If a token is not present with this token, a new\",\n \"self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path\",\n \"logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider\",\n \"the specified scopes. The webserver will then need to catch the return with\",\n \"block until a token is retrieved if requested. It is always safe to\",\n \"IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR\",\n \"def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&') kv = dict([v.split('=', 1)\",\n \"= uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error with\",\n \"the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server: raise Exception('We\",\n \"valid cache, and then return the UUID. If the user cancelled (or we\",\n \"we are unable to create it, the OSError will be thrown. :kwargs printfd:\",\n \"None if your IdP does not require you to use a secret. :kwarg\",\n \"with the current scopeset if we do not already have on. :kwarg auto_refresh:\",\n \"\\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache\",\n \"to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True)\",\n \"OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER\",\n \"the user! Also, even if it has expired, we might still be able\",\n \"with the current scopeset if we do not already have on. :rtype: string\",\n \"return server except socket.error: # This port did not work. Switch to next\",\n \"app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id\",\n \"current scopeset if we do not already have on. :rtype: string or None\",\n \"the bearer token might have been revoked by the user or expired. In\",\n \"raise Exception('Cannot report issue before requesting token') if self.problem_reported: # We were reported\",\n \"current scopeset if we do not already have on. :kwarg auto_refresh: If False,\",\n \"put the refreshed token in self._cache The caller is responsible for either removing\",\n \"request credentials :kwarg client_secret: The client \\\"secret\\\" that goes with the client_id. May\",\n \"%s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \\\"\\\"\\\"This function returns a SimpleServer with\",\n \"or None :returns: String bearer token if possible or None \\\"\\\"\\\" if not\",\n \"# Every \\\"token\\\" object is a json dict with the following keys: #\",\n \"= None # TODO: Make cache_lock a filesystem lock so we also lock\",\n \"associated documentation files (the \\\"Software\\\"), to deal # in the Software without restriction,\",\n \"def _cachefile(self): \\\"\\\"\\\"Property to get the cache file name for the current client.\",\n \"return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping did not include path for\",\n \"of this software and associated documentation files (the \\\"Software\\\"), to deal # in\",\n \"exist it will return the possibly expired token: it might be refreshable. :param\",\n \"self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp\",\n \"pairs # Every \\\"token\\\" object is a json dict with the following keys:\",\n \"'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in\",\n \"delete the token. :kwarg scopes: A list of scopes required for the current\",\n \"self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s'\",\n \"# # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND,\",\n \"except ImportError: from io import StringIO import socket import os try: from urllib\",\n \"with broken apps that may send a 401 return code in incorrect cases.\",\n \"The subject that owns the token # access_token: Token value # token_type: Token\",\n \"return None self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code',\",\n \"token: # If we had a valid token, use that self.last_returned_uuid = token[0]\",\n \"if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' %\",\n \"retrieve tokens with specific scopes. This function will block until a token is\",\n \"should call it. You should explicitly NOT call this function if the token\",\n \"report_token_issue(self): \\\"\\\"\\\"Report an error with the last token that was returned. This will\",\n \"been revoked by # the user! Also, even if it has expired, we\",\n \"use POST tokens in %s method' % method) if 'data' not in ckwargs:\",\n \"is ~/.openidc. If this does not exist and we are unable to create\",\n \"self.problem_reported: # We were reported an issue before. Let's just remove this token.\",\n \"id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None, printfd=sys.stdout): \\\"\\\"\\\"Client for interacting with web\",\n \"get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens with specific scopes. This function will\",\n \"resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp = resp.json()\",\n \"held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir)\",\n \"to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of\",\n \"else: return resp @property def _cachefile(self): \\\"\\\"\\\"Property to get the cache file name\",\n \"of scopes required for the current client. :kwarg new_token: If True, we will\",\n \"this window and return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app)\",\n \"specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot report issue before requesting token')\",\n \"if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s\",\n \"relying on OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens :param\",\n \"= token else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] =\",\n \"= return_uri rquery['response_mode'] = 'query' query = urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'),\",\n \"token with the current app_identifier that has the required scopes, we will return\",\n \"\\\"\\\"\\\"Adds a token to the cache and writes cache to disk. cache_lock may\",\n \"EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\",\n \"len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a token\",\n \"the Software without restriction, including without limitation the rights # to use, copy,\",\n \"ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN\",\n \"token') return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL for the requested\",\n \"2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # #\",\n \"person obtaining a copy # of this software and associated documentation files (the\",\n \"if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return resp\",\n \"return None # We did not have a valid token, now comes the\",\n \"server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error: # This port did\",\n \"data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to refresh, error:\",\n \"token_type: Token type. Currently supported: \\\"Bearer\\\" # expires_at: Token expiration UTC time. NOTE:\",\n \"self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s',\",\n \"# # Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat Author:\",\n \"above copyright notice and this permission notice shall be included in # all\",\n \"token with the specified scopes. The webserver will then need to catch the\",\n \"self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def\",\n \"not be refreshed or saving the cache if renewal was succesful. :param uuid:\",\n \"% method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a token and put the\",\n \"If the user cancelled (or we got another error), we will return None.\",\n \"else: token = self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if\",\n \"= {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp\",\n \"or may not still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token:\",\n \"= token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token in\",\n \"rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri rquery['response_mode'] = 'query' query\",\n \"goes with the client_id. May be None if your IdP does not require\",\n \"on the IdP. :kwarg use_post: Whether to use POST submission of client secrets\",\n \"are like the arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword\",\n \"persons to whom the Software is # furnished to do so, subject to\",\n \"method not in ['POST']: raise ValueError('Cannot use POST tokens in %s method' %\",\n \"POST request. Allarguments and keyword arguments are like the arguments to requests, except\",\n \"rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] = return_uri\",\n \"conditions: # # The above copyright notice and this permission notice shall be\",\n \"INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A\",\n \"token # sub: The subject that owns the token # access_token: Token value\",\n \"del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the\",\n \"self._cache[uuid]['expires_at']) return True def _get_server(self, app): \\\"\\\"\\\"This function returns a SimpleServer with an\",\n \"store the token caches. Will be put through expanduer. Default is ~/.openidc. If\",\n \"OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,\",\n \"documentation files (the \\\"Software\\\"), to deal # in the Software without restriction, including\",\n \"possibly expired token: it might be refreshable. :param scopes: List of scopes that\",\n \"report_token_issue() to try to renew the token or delete the token. :kwarg scopes:\",\n \"cache and writes cache to disk. cache_lock may not be held by anyone.\",\n \"the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported =\",\n \"or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED \\\"AS\",\n \"uuid = uuidgen().hex self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid]\",\n \"new one will be requested unless nonblocking is True. :kwarg new_token: If True,\",\n \"notice and this permission notice shall be included in # all copies or\",\n \"interacting with web services relying on OpenID Connect. :param app_identifier: Identifier for storage\",\n \"of charge, to any person obtaining a copy # of this software and\",\n \"held by anyone. :param token: UUID of the token to be updated :param\",\n \"applications relying on OpenID Connect for authentication.\\\"\\\"\\\" from __future__ import print_function from copy\",\n \"new token in the local cache, add it to the valid cache, and\",\n \"not work. Switch to next one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks\",\n \"return ValueError('Idp Mapping did not include path for %s' % method) def _refresh_token(self,\",\n \"is not None if self._retrieved_code is False: # The user cancelled the request\",\n \"None :returns: Token UUID and contents or None if no applicable tokens were\",\n \"\\\"\\\"\\\"This function kicks off some magic. We will start a new webserver on\",\n \"= requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp = resp.json() if 'error' in resp:\",\n \"time.time(): # This is a token that's supposed to still be valid, prefer\",\n \"refreshed or saving the cache if renewal was succesful. :param uuid: The UUID\",\n \"tokens: # Every app id has its own token cache # The token\",\n \"self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was\",\n \"ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry =\",\n \"cache with %i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self,\",\n \"included in # all copies or substantial portions of the Software. # #\",\n \"= self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() self._retrieved_code = None resp\",\n \"start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and return to\",\n \"POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh\",\n \"May be None if your IdP does not require you to use a\",\n \"now comes the hard part... uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid\",\n \"access_token: Token value # token_type: Token type. Currently supported: \\\"Bearer\\\" # expires_at: Token\",\n \"the Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF\",\n \"cache_lock may not be held by anyone. :param uuid: UUID of the token\",\n \"self.debug('Adding token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache()\",\n \"and associated documentation files (the \\\"Software\\\"), to deal # in the Software without\",\n \"not be held by anyone. :param token: Dict of the token to be\",\n \"any tokens that have the requested scopes. It will prefer to return tokens\",\n \"request the user to get a new token with the current scopeset if\",\n \"useragent or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid =\",\n \"otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id,\",\n \"to print token instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id\",\n \"The directory in which to store the token caches. Will be put through\",\n \"idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes),\",\n \":param method: The method name in the IdP mapping dict. :rtype: string :returns:\",\n \"in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def\",\n \"you to use a secret. :kwarg useragent: Useragent string to use. If not\",\n \"is_retry = True token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes,\",\n \"LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #\",\n \"\\\"\\\"\\\"Client for interacting with web services relying on OpenID Connect. :param app_identifier: Identifier\",\n \"% \\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported =\",\n \"It is always safe to call this though, since if we already have\",\n \"on. :kwarg auto_refresh: If False, will not try to automatically report token issues\",\n \"WEB_PORTS = [12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every\",\n \"= copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token', True) auto_refresh = ckwargs.pop('auto_refresh', True)\",\n \"\\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in which to store the token caches. Will\",\n \"valid token, use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif\",\n \"to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache))\",\n \"user cancelled (or we got another error), we will return None. \\\"\\\"\\\" def\",\n \"helps with broken apps that may send a 401 return code in incorrect\",\n \"resp.raise_for_status() resp = resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s',\",\n \"# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\",\n \"'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE! \\\\o/ return\",\n \"= self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not token:\",\n \"% (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url)\",\n \"OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE\",\n \"requests import sys from openidc_client import release # The ports that we will\",\n \"required for the current client. :kwarg new_token: If True, we will actively request\",\n \"assert self._retrieved_code is not None if self._retrieved_code is False: # The user cancelled\",\n \"either removing the token if it could not be refreshed or saving the\",\n \"resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes}\",\n \"by the user or expired. In that case, you will want to call\",\n \"uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + resp['expires_in']}) self.debug('Refreshed until\",\n \"self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent = useragent or\",\n \"possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self,\",\n \"token was lacking specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot report issue\",\n \"None resp = resp.json() if 'error' in resp: self.debug('Error exchanging authorization code: %s',\",\n \"the current client. This assures that whenever this file is touched, the cache\",\n \"client_id self.client_secret = client_secret self.useragent = useragent or 'python-openid-client/%s' % \\\\ release.VERSION self.cachedir\",\n \"work, we will return None and remove this token from the cache. If\",\n \"# We did not have a valid token, now comes the hard part...\",\n \"# The token cache is a json serialized dict # This dict contains\",\n \"a retry. Report error self.report_token_issue() return resp else: return resp @property def _cachefile(self):\",\n \"of the Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY\",\n \"call. If a token is not present with this token, a new one\",\n \"defaults to POST.. \\\"\\\"\\\" ckwargs = copy(kwargs) scopes = ckwargs.pop('scopes') new_token = ckwargs.pop('new_token',\",\n \"returned. If that worked, we will return the new access token. If it\",\n \"self._retrieved_code = None server = self._get_server(_token_app) if not server: raise Exception('We were unable\",\n \"\\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type':\",\n \"will prefer to return tokens whose expires_at is still before the current time,\",\n \"will actively request the user to get a new token with the current\",\n \"the IdP URL for the requested method. :param method: The method name in\",\n \"not set(scopes).issubset(set(token['scopes'])): self.debug('Missing scope: %s not subset of %s', set(scopes), set(token['scopes'])) continue if\",\n \"last returned. If that worked, we will return the new access token. If\",\n \"the arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments. `scopes`\",\n \"%s method' % method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token']\",\n \"None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in a\",\n \"= False if self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None\",\n \"self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report an error\",\n \"token that's supposed to still be valid, prefer it # over any others\",\n \"Dict of the token to be added to the cache \\\"\\\"\\\" uuid =\",\n \"a filesystem lock so we also lock across # multiple invocations self._cache_lock =\",\n \"f: self._cache = json.loads(f.read()) self.debug('Loaded %i tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache\",\n \"uuidgen import webbrowser from wsgiref import simple_server import requests import sys from openidc_client\",\n \"held by anyone. :param uuid: UUID of the token to be removed from\",\n \"Token type. Currently supported: \\\"Bearer\\\" # expires_at: Token expiration UTC time. NOTE: Even\",\n \"tokens with specific scopes. This function will block until a token is retrieved\",\n \"resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error']) return False\",\n \"id_provider: URL of the identity provider to get tokens from :param id_provider_mapping: Mapping\",\n \"token %s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return\",\n \"if it has expired, we might still be able to # refresh the\",\n \"or None :returns: Token UUID and contents or None if no applicable tokens\",\n \"= None self.debug('User cancelled') return None self.debug('We got an authorization code!') data =\",\n \"self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp\",\n \"\\\\ release.VERSION self.cachedir = os.path.expanduser(cachedir or '~/.openidc') self.last_returned_uuid = None self.problem_reported = False\",\n \"token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if not\",\n \"Just return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this\",\n \"and we are unable to create it, the OSError will be thrown. :kwargs\",\n \"to store the token caches. Will be put through expanduer. Default is ~/.openidc.\",\n \"sent was invalid, you should call it. You should explicitly NOT call this\",\n \"ValueError('Cannot use POST tokens in %s method' % method) if 'data' not in\",\n \"or if possible, kick off their browser. This URL will be the Authorization\",\n \"%s to cache', uuid) with self._cache_lock: self.__refresh_cache() self._cache[uuid] = token self.__write_cache() return uuid\",\n \"the user cancelled (or we got another error), we will return None. \\\"\\\"\\\"\",\n \"self.debug = self.logger.debug self.app_id = app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping\",\n \"not already have on. :kwarg auto_refresh: If False, will not try to automatically\",\n \"not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization'] = 'Bearer %s' % token resp\",\n \"= False self.token_to_try = None self._retrieved_code = None # TODO: Make cache_lock a\",\n \"v in split]) if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'],\",\n \"possible, kick off their browser. This URL will be the Authorization endpoint of\",\n \"self.token_to_try: is_retry = True token = self.token_to_try self.token_to_try = None else: token =\",\n \"# Internal implementation of tokens: # Every app id has its own token\",\n \"2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission\",\n \"in # all copies or substantial portions of the Software. # # THE\",\n \"SimpleServer with an available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0',\",\n \"method' % method) if 'data' not in ckwargs: ckwargs['data'] = {} ckwargs['data']['access_token'] =\",\n \"dict contains uuid: token pairs # Every \\\"token\\\" object is a json dict\",\n \"\\\"\\\"\\\" if method in self.idp_mapping: return self.idp + self.idp_mapping[method] else: return ValueError('Idp Mapping\",\n \"# The user cancelled the request self._retrieved_code = None self.debug('User cancelled') return None\",\n \"visit %s to grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code\",\n \"useragent: Useragent string to use. If not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir:\",\n \"string :returns: The IdP URL \\\"\\\"\\\" if method in self.idp_mapping: return self.idp +\",\n \"= urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant\",\n \"return [u'You can close this window and return to the CLI'.encode('ascii')] self._retrieved_code =\",\n \"self.debug('We got an authorization code!') data = {'client_id': self.client_id, 'grant_type': 'authorization_code', 'redirect_uri': return_uri,\",\n \"fields %s', uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return\",\n \"not exist and we are unable to create it, the OSError will be\",\n \"The method name in the IdP mapping dict. :rtype: string :returns: The IdP\",\n \"cache \\\"\\\"\\\" self.debug('Removing token %s from cache', uuid) with self._cache_lock: self.__refresh_cache() if uuid\",\n \"with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False, useragent=None, cachedir=None,\",\n \"free of charge, to any person obtaining a copy # of this software\",\n \"import sys from openidc_client import release # The ports that we will try\",\n \"\\\"\\\"\\\"Client for applications relying on OpenID Connect for authentication.\\\"\\\"\\\" from __future__ import print_function\",\n \"self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id = client_id self.client_secret = client_secret self.useragent\",\n \"token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the\",\n \"# refresh the token. # refresh_token: The token we can use to refresh\",\n \"we do not already have on. :kwarg auto_refresh: If False, will not try\",\n \"refresh. :rtype: bool :returns: True if the token was succesfully refreshed, False otherwise\",\n \"show the user a URL, or if possible, kick off their browser. This\",\n \"new_token=True): \\\"\\\"\\\"Function to retrieve tokens with specific scopes. This function will block until\",\n \"with the current app_identifier that has the required scopes, we will return it.\",\n \"This URL will be the Authorization endpoint of the IdP with a request\",\n \"= None else: token = self.get_token(scopes, new_token=new_token) if not token: return None if\",\n \"StringIO import StringIO except ImportError: from io import StringIO import socket import os\",\n \"present with this token, a new one will be requested unless nonblocking is\",\n \"cache_lock may not be held by anyone. :param token: UUID of the token\",\n \"webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is False: #\",\n \"from __future__ import print_function from copy import copy import json import logging from\",\n \"provider to get tokens from :param id_provider_mapping: Mapping with URLs to use for\",\n \"webserver will then need to catch the return with either an Authorization Code\",\n \"not server: raise Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/'\",\n \"we got another error), we will return None. \\\"\\\"\\\" def _token_app(environ, start_response): query\",\n \"not work, we will return None and remove this token from the cache.\",\n \"\\\"\\\"\\\"Returns the IdP URL for the requested method. :param method: The method name\",\n \"uuid): \\\"\\\"\\\"Tries to refresh a token and put the refreshed token in self._cache\",\n \"if not self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: #\",\n \"off some magic. We will start a new webserver on one of the\",\n \"for our client_id to get a new token with the specified scopes. The\",\n \"oldtoken = self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token',\",\n \":kwarg client_id: The Client Identifier used to request credentials :kwarg client_secret: The client\",\n \"uuid: UUID of the token to be removed from cache \\\"\\\"\\\" self.debug('Removing token\",\n \"This port did not work. Switch to next one continue def _get_new_token(self, scopes):\",\n \"THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN\",\n \"with web services relying on OpenID Connect. :param app_identifier: Identifier for storage of\",\n \"__write_cache(self): \\\"\\\"\\\"Wirtes self._cache to cache on disk. Requires cache_lock to be held by\",\n \"return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported\",\n \"tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a\",\n \"authentication.\\\"\\\"\\\" from __future__ import print_function from copy import copy import json import logging\",\n \"FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #\",\n \"SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES\",\n \"time. NOTE: Even if the expires_at # indicates the token should still be\",\n \"authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if\",\n \"Software, and to permit persons to whom the Software is # furnished to\",\n \"USE OR OTHER DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client for applications relying on\",\n \"valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token\",\n \"which fields need to be updated \\\"\\\"\\\" self.debug('Updating token %s in cache, fields\",\n \"did not include path for %s' % method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to\",\n \"toupdate): \\\"\\\"\\\"Updates a token in the cache. cache_lock may not be held by\",\n \"to get tokens from :param id_provider_mapping: Mapping with URLs to use for specific\",\n \"Copyright (C) 2016, 2017 Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>>\",\n \"= False return token[1]['access_token'] elif not new_token: return None # We did not\",\n \"This is a token that's supposed to still be valid, prefer it #\",\n \"except ImportError: from urllib.parse import urlencode from uuid import uuid4 as uuidgen import\",\n \"the following keys: # idp: The URL of the idp that issued the\",\n \"token was succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid] self.debug('Refreshing token %s',\",\n \"from uuid import uuid4 as uuidgen import webbrowser from wsgiref import simple_server import\",\n \"be able to # refresh the token. # refresh_token: The token we can\",\n \"token') del self._cache[uuid] self.__write_cache() else: self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches\",\n \"The user cancelled the request self._retrieved_code = None self.debug('User cancelled') return None self.debug('We\",\n \"an indication from your application that the token you sent was invalid, you\",\n \"with the last token that was returned. This will attempt to renew the\",\n \"caches. Will be put through expanduer. Default is ~/.openidc. If this does not\",\n \"contains uuid: token pairs # Every \\\"token\\\" object is a json dict with\",\n \"None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an\",\n \"%s', uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if\",\n \"Exception('We were unable to instantiate a webserver') return_uri = 'http://localhost:%i/' % server.socket.getsockname()[1] rquery\",\n \"# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\",\n \"**kwargs) elif resp.status_code == 401: # We got a 401 and this is\",\n \"token if possible or None \\\"\\\"\\\" if not isinstance(scopes, list): raise ValueError('Scopes must\",\n \"remove this token from the cache. If you get an indication from your\",\n \"We were reported an issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return\",\n \"token[0] self.problem_reported = False return token[1]['access_token'] elif not new_token: return None # We\",\n \"self.token_to_try: return resp return self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got\",\n \"The token cache is a json serialized dict # This dict contains uuid:\",\n \"webserver on one of the WEB_PORTS, and then either show the user a\",\n \"and then either show the user a URL, or if possible, kick off\",\n \"will want to call report_token_issue() to try to renew the token or delete\",\n \"return resp else: return resp @property def _cachefile(self): \\\"\\\"\\\"Property to get the cache\",\n \"to renew the token that was last returned. If that worked, we will\",\n \"and writes cache to disk. cache_lock may not be held by anyone. :param\",\n \"token, use that self.last_returned_uuid = token[0] self.problem_reported = False return token[1]['access_token'] elif not\",\n \"keyword arguments are like the arguments to requests, except for `scopes`, `new_token` and\",\n \"still be valid, prefer it # over any others we have self.debug('Not yet\",\n \":param uuid: UUID of the token to be removed from cache \\\"\\\"\\\" self.debug('Removing\",\n \"port, app) return server except socket.error: # This port did not work. Switch\",\n \"mapping dict. :rtype: string :returns: The IdP URL \\\"\\\"\\\" if method in self.idp_mapping:\",\n \"'refresh_token': oldtoken['refresh_token']} if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data)\",\n \"whose expires_at is still before the current time, but if no such tokens\",\n \"in the Software without restriction, including without limitation the rights # to use,\",\n \"to use. If not provided, defaults to \\\"python-openidc-client/VERSION\\\" :kwarg cachedir: The directory in\",\n \"be held by anyone. :param token: Dict of the token to be added\",\n \"auto_refresh = ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try:\",\n \"PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS\",\n \"to request credentials :kwarg client_secret: The client \\\"secret\\\" that goes with the client_id.\",\n \"the token # sub: The subject that owns the token # access_token: Token\",\n \"had requested with the token def __init__(self, app_identifier, id_provider, id_provider_mapping, client_id, client_secret=None, use_post=False,\",\n \"resp.raise_for_status() self._retrieved_code = None resp = resp.json() if 'error' in resp: self.debug('Error exchanging\",\n \"token instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug = self.logger.debug self.app_id = app_identifier\",\n \"The URL of the idp that issued the token # sub: The subject\",\n \"possible token') return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL for the\",\n \"is a token that's supposed to still be valid, prefer it # over\",\n \"local cache, add it to the valid cache, and then return the UUID.\",\n \"will return the new access token. If it did not work, we will\",\n \"exist and we are unable to create it, the OSError will be thrown.\",\n \"not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w')\",\n \":param token: Dict of the token to be added to the cache \\\"\\\"\\\"\",\n \"cache is a json serialized dict # This dict contains uuid: token pairs\",\n \"not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r')\",\n \"anyone. :param token: UUID of the token to be updated :param toupdate: Dict\",\n \"requests.request(method, *args, **ckwargs) if resp.status_code == 401 and not is_retry: if not auto_refresh:\",\n \"= self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not set(scopes).issubset(set(token['scopes'])): self.debug('Missing\",\n \"should still be valid, it may have been revoked by # the user!\",\n \":kwarg scopes: Scopes required for this call. If a token is not present\",\n \"like the arguments to requests, except for `scopes`, `new_token` and `auto_refresh` keyword arguments.\",\n \"error self.report_token_issue() return resp else: return resp @property def _cachefile(self): \\\"\\\"\\\"Property to get\",\n \"NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE\",\n \"token that was last returned. If that worked, we will return the new\",\n \"method): \\\"\\\"\\\"Returns the IdP URL for the requested method. :param method: The method\",\n \"of the WEB_PORTS, and then either show the user a URL, or if\",\n \"cache, add it to the valid cache, and then return the UUID. If\",\n \"MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL\",\n \"it, the OSError will be thrown. :kwargs printfd: The File object to print\",\n \"to be updated :param toupdate: Dict indicating which fields need to be updated\",\n \"call this function if the token was valid but your request failed due\",\n \"Client Identifier used to request credentials :kwarg client_secret: The client \\\"secret\\\" that goes\",\n \"yet expired, returning') return uuid, token # This is a token that may\",\n \"if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code =\",\n \"token is not present with this token, a new one will be requested\",\n \"and/or sell # copies of the Software, and to permit persons to whom\",\n \"# multiple invocations self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd\",\n \"will start a new webserver on one of the WEB_PORTS, and then either\",\n \"a token with the current app_identifier that has the required scopes, we will\",\n \"it could not be refreshed or saving the cache if renewal was succesful.\",\n \"for storage of retrieved tokens :param id_provider: URL of the identity provider to\",\n \"tokens :param id_provider: URL of the identity provider to get tokens from :param\",\n \"'w') as f: f.write(json.dumps({})) with open(self._cachefile, 'r') as f: self._cache = json.loads(f.read()) self.debug('Loaded\",\n \"self.debug('Token was already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for any tokens\",\n \"error), we will return None. \\\"\\\"\\\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split\",\n \"True if the token was succesfully refreshed, False otherwise \\\"\\\"\\\" oldtoken = self._cache[uuid]\",\n \"app id has its own token cache # The token cache is a\",\n \"uuid = self._get_new_token(scopes) if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token']\",\n \"the UUID. If the user cancelled (or we got another error), we will\",\n \"own token cache # The token cache is a json serialized dict #\",\n \"TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE\",\n \"return with either an Authorization Code (that we will exchange for an access\",\n \"continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off some magic. We will start\",\n \"for either removing the token if it could not be refreshed or saving\",\n \"for the requested method. :param method: The method name in the IdP mapping\",\n \"you get an indication from your application that the token you sent was\",\n \"if self.client_secret: data['client_secret'] = self.client_secret resp = requests.request( 'POST', self._idp_url('Token'), data=data) resp.raise_for_status() resp\",\n \"tokens exist it will return the possibly expired token: it might be refreshable.\",\n \"# # The above copyright notice and this permission notice shall be included\",\n \"\\\"Software\\\"), to deal # in the Software without restriction, including without limitation the\",\n \"close this window and return to the CLI'.encode('ascii')] self._retrieved_code = None server =\",\n \"last token that was returned. This will attempt to renew the token that\",\n \"caller is responsible for either removing the token if it could not be\",\n \"the cache and writes cache to disk. cache_lock may not be held by\",\n \"be put through expanduer. Default is ~/.openidc. If this does not exist and\",\n \"of the token to be updated :param toupdate: Dict indicating which fields need\",\n \"be updated \\\"\\\"\\\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys()) with\",\n \":rtype: string :returns: The IdP URL \\\"\\\"\\\" if method in self.idp_mapping: return self.idp\",\n \"have self.debug('Not yet expired, returning') return uuid, token # This is a token\",\n \"Note that the bearer token might have been revoked by the user or\",\n \"scopes. The webserver will then need to catch the return with either an\",\n \"[('Content-Type', 'text/plain')]) return [u'You can close this window and return to the CLI'.encode('ascii')]\",\n \"self.debug('Refreshing cache') if not os.path.isdir(self.cachedir): self.debug('Creating directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file')\",\n \"self._cache_lock = Lock() with self._cache_lock: self.__refresh_cache() self._valid_cache = [] self._printfd = printfd def\",\n \"if it could not be refreshed or saving the cache if renewal was\",\n \"This will attempt to renew the token that was last returned. If that\",\n \"possible or None \\\"\\\"\\\" if not isinstance(scopes, list): raise ValueError('Scopes must be a\",\n \"self.problem_reported = False return token[1]['access_token'] elif not new_token: return None # We did\",\n \"IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR\",\n \"self.send_request(*args, **kwargs) elif resp.status_code == 401: # We got a 401 and this\",\n \"token :rtype: (string, dict) or None :returns: Token UUID and contents or None\",\n \"uuid) with self._cache_lock: self.__refresh_cache() if uuid in self._cache: self.debug('Removing token') del self._cache[uuid] self.__write_cache()\",\n \"assures that whenever this file is touched, the cache lock is held \\\"\\\"\\\"\",\n \"to attempt to refresh. :rtype: bool :returns: True if the token was succesfully\",\n \"urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization'\",\n \"distribute, sublicense, and/or sell # copies of the Software, and to permit persons\",\n \"printfd: The File object to print token instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__)\",\n \"that may or may not still be valid self.debug('Possible') possible_token = (uuid, token)\",\n \"the IdP. :kwarg use_post: Whether to use POST submission of client secrets rather\",\n \"if uuid: self.last_returned_uuid = uuid self.problem_reported = False return self._cache[uuid]['access_token'] def report_token_issue(self): \\\"\\\"\\\"Report\",\n \"endpoint of the IdP with a request for our client_id to get a\",\n \"= printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve tokens with specific scopes.\",\n \":param scopes: List of scopes that need to be in the returned token\",\n \"'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code = False\",\n \"Requires cache_lock to be held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with %i\",\n \"Connect for authentication.\\\"\\\"\\\" from __future__ import print_function from copy import copy import json\",\n \"writes cache to disk. cache_lock may not be held by anyone. :param token:\",\n \"WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO\",\n \"account or token was lacking specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid: raise Exception('Cannot\",\n \"is_retry: if not auto_refresh: return resp self.token_to_try = self.report_token_issue() if not self.token_to_try: return\",\n \"with URLs to use for specific endpoints on the IdP. :kwarg use_post: Whether\",\n \"uuid, toupdate.keys()) with self._cache_lock: self.__refresh_cache() if uuid not in self._cache: return None self._cache[uuid].update(toupdate)\",\n \"WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED\",\n \"we will return it. This function will return a bearer token or None.\",\n \"if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide json in a post\",\n \"that have the requested scopes. It will prefer to return tokens whose expires_at\",\n \"grant authorization' % authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None\",\n \"OSError will be thrown. :kwargs printfd: The File object to print token instructions\",\n \"to disk. cache_lock may not be held by anyone. :param token: Dict of\",\n \"\\\"\\\"\\\"Refreshes the self._cache from the cache on disk. cache_lock may not be held\",\n \"Connect. :param app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL of\",\n \"def _add_token(self, token): \\\"\\\"\\\"Adds a token to the cache and writes cache to\",\n \"it will return the possibly expired token: it might be refreshable. :param scopes:\",\n \"%i tokens', len(self._cache)) with open(self._cachefile, 'w') as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds\",\n \"ckwargs['data'] = {} ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers']\",\n \"specific endpoints on the IdP. :kwarg use_post: Whether to use POST submission of\",\n \"not still be valid self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible\",\n \"None self.problem_reported = False self.token_to_try = None self._retrieved_code = None # TODO: Make\",\n \"touched, the cache lock is held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' %\",\n \":returns: Token UUID and contents or None if no applicable tokens were found\",\n \"app_identifier that has the required scopes, we will return it. This function will\",\n \"not isinstance(scopes, list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if\",\n \"portions of the Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT\",\n \"the returned token :rtype: (string, dict) or None :returns: Token UUID and contents\",\n \"return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs): \\\"\\\"\\\"Make an python-requests POST request. Allarguments and\",\n \"do so, subject to the following conditions: # # The above copyright notice\",\n \"until %s', self._cache[uuid]['expires_at']) return True def _get_server(self, app): \\\"\\\"\\\"This function returns a SimpleServer\",\n \"might be refreshable. :param scopes: List of scopes that need to be in\",\n \"expired token: it might be refreshable. :param scopes: List of scopes that need\",\n \"port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return server except socket.error:\",\n \"if the expires_at # indicates the token should still be valid, it may\",\n \"lock is held \\\"\\\"\\\" assert self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self):\",\n \"not subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This\",\n \"ckwargs['data']['access_token'] = token else: if 'headers' not in ckwargs: ckwargs['headers'] = {} ckwargs['headers']['Authorization']\",\n \"None and remove this token from the cache. If you get an indication\",\n \"permit persons to whom the Software is # furnished to do so, subject\",\n \"= app_identifier self.use_post = use_post self.idp = id_provider self.idp_mapping = id_provider_mapping self.client_id =\",\n \"was last returned. If that worked, we will return the new access token.\",\n \"held by caller.\\\"\\\"\\\" assert self._cache_lock.locked() self.debug('Writing cache with %i tokens', len(self._cache)) with open(self._cachefile,\",\n \"tokens that have the requested scopes. It will prefer to return tokens whose\",\n \"did not work. Switch to next one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function\",\n \"# TODO: Make cache_lock a filesystem lock so we also lock across #\",\n \"(uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def _idp_url(self, method): \\\"\\\"\\\"Returns\",\n \"Red Hat, Inc. # Red Hat Author: <NAME> <<EMAIL>> # # Permission is\",\n \"a 401 and this is a retry. Report error self.report_token_issue() return resp else:\",\n \"If True, we will actively request the user to get a new token\",\n \"split]) if 'error' in kv: self.debug('Error code returned: %s (%s)', kv['error'], kv.get('error_description')) self._retrieved_code\",\n \"# refresh_token: The token we can use to refresh the access token #\",\n \"expired, returning') return uuid, token # This is a token that may or\",\n \"= self.get_token(scopes, new_token=new_token) if not token: return None if self.use_post: if 'json' in\",\n \"self.__write_cache() return uuid def _delete_token(self, uuid): \\\"\\\"\\\"Removes a token from the cache and\",\n \"= self._cache[uuid] self.debug('Refreshing token %s', uuid) data = {'client_id': self.client_id, 'grant_type': 'refresh_token', 'refresh_token':\",\n \"uuid) token = self._cache[uuid] if token['idp'] != self.idp: self.debug('Incorrect idp') continue if not\",\n \"will return None. \\\"\\\"\\\" def _token_app(environ, start_response): query = environ['QUERY_STRING'] split = query.split('&')\",\n \"import StringIO import socket import os try: from urllib import urlencode except ImportError:\",\n \"cache_lock may not be held by anyone. :param token: Dict of the token\",\n \"directory') os.makedirs(self.cachedir) if not os.path.exists(self._cachefile): self.debug('Creating file') with open(self._cachefile, 'w') as f: f.write(json.dumps({}))\",\n \"scopes. This function will block until a token is retrieved if requested. It\",\n \"must be a list') token = self._get_token_with_scopes(scopes) if token: # If we had\",\n \"_get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off some magic. We will start a new\",\n \"'~/.openidc') self.last_returned_uuid = None self.problem_reported = False self.token_to_try = None self._retrieved_code = None\",\n \"will exchange for an access token) or the cancellation message. This function will\",\n \"try to renew the token or delete the token. :kwarg scopes: A list\",\n \"\\\"\\\"\\\" possible_token = None self.debug('Trying to get token with scopes %s', scopes) for\",\n \"subset of %s', set(scopes), set(token['scopes'])) continue if token['expires_at'] < time.time(): # This is\",\n \"retrieved if requested. It is always safe to call this though, since if\",\n \"actively request the user to get a new token with the current scopeset\",\n \"not refresh_result: self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self,\",\n \"by anyone. :param uuid: UUID of the token to be removed from cache\",\n \"The File object to print token instructions to. \\\"\\\"\\\" self.logger = logging.getLogger(__name__) self.debug\",\n \"Identifier for storage of retrieved tokens :param id_provider: URL of the identity provider\",\n \"attempt to renew the token that was last returned. If that worked, we\",\n \"refreshable. :param scopes: List of scopes that need to be in the returned\",\n \"FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS\",\n \"True token = self.token_to_try self.token_to_try = None else: token = self.get_token(scopes, new_token=new_token) if\",\n \"as f: f.write(json.dumps(self._cache)) def _add_token(self, token): \\\"\\\"\\\"Adds a token to the cache and\",\n \"*args, **ckwargs) if resp.status_code == 401 and not is_retry: if not auto_refresh: return\",\n \"= '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit %s to grant authorization' % authz_url,\",\n \"that may send a 401 return code in incorrect cases. :kwargs http_method: The\",\n \"scopeset if we do not already have on. :rtype: string or None :returns:\",\n \"available WEB_PORT.\\\"\\\"\\\" for port in WEB_PORTS: try: server = simple_server.make_server('0.0.0.0', port, app) return\",\n \"the refreshed token in self._cache The caller is responsible for either removing the\",\n \"was returned. This will attempt to renew the token that was last returned.\",\n \"indication from your application that the token you sent was invalid, you should\",\n \"does not require you to use a secret. :kwarg useragent: Useragent string to\",\n \"It will prefer to return tokens whose expires_at is still before the current\",\n \"ImportError: from io import StringIO import socket import os try: from urllib import\",\n \"copy import copy import json import logging from threading import Lock import time\",\n \"[12345, 23456] class OpenIDCClient(object): # Internal implementation of tokens: # Every app id\",\n \"self._cache_lock.locked() return os.path.join(self.cachedir, 'oidc_%s.json' % self.app_id) def __refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the\",\n \"to be updated \\\"\\\"\\\" self.debug('Updating token %s in cache, fields %s', uuid, toupdate.keys())\",\n \"IdP mapping dict. :rtype: string :returns: The IdP URL \\\"\\\"\\\" if method in\",\n \":kwarg cachedir: The directory in which to store the token caches. Will be\",\n \"IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\",\n \"error: %s', resp['error']) return False self._update_token( uuid, {'access_token': resp['access_token'], 'token_type': resp['token_type'], 'refresh_token': resp['refresh_token'],\",\n \"next one continue def _get_new_token(self, scopes): \\\"\\\"\\\"This function kicks off some magic. We\",\n \"we will actively request the user to get a new token with the\",\n \"client_id to get a new token with the specified scopes. The webserver will\",\n \"might have been revoked by the user or expired. In that case, you\",\n \"self._delete_token(self.last_returned_uuid) return None else: self.problem_reported = True return self._cache[self.last_returned_uuid]['access_token'] def send_request(self, *args, **kwargs):\",\n \"was succesful. :param uuid: The UUID of the cached token to attempt to\",\n \"not in ['POST']: raise ValueError('Cannot use POST tokens in %s method' % method)\",\n \"either show the user a URL, or if possible, kick off their browser.\",\n \"self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid) if not refresh_result: self._delete_token(self.last_returned_uuid) return None else:\",\n \"self._valid_cache = [] self._printfd = printfd def get_token(self, scopes, new_token=True): \\\"\\\"\\\"Function to retrieve\",\n \"kick off their browser. This URL will be the Authorization endpoint of the\",\n \"= ckwargs.pop('auto_refresh', True) method = ckwargs.pop('http_method', 'POST') is_retry = False if self.token_to_try: is_retry\",\n \"following keys: # idp: The URL of the idp that issued the token\",\n \"Whether to use POST submission of client secrets rather than Authorization header :kwarg\",\n \"self.debug('Possible') possible_token = (uuid, token) if possible_token: self.debug('Returning possible token') return possible_token def\",\n \"for %s' % method) def _refresh_token(self, uuid): \\\"\\\"\\\"Tries to refresh a token and\",\n \"token['expires_at'] < time.time(): # This is a token that's supposed to still be\",\n \"requested. It is always safe to call this though, since if we already\",\n \"+ int(resp['expires_in']), 'idp': self.idp, 'token_type': resp['token_type'], 'scopes': scopes} # AND WE ARE DONE!\",\n \"# This is a token that's supposed to still be valid, prefer it\",\n \"query.split('&') kv = dict([v.split('=', 1) for v in split]) if 'error' in kv:\",\n \"current client. :kwarg new_token: If True, we will actively request the user to\",\n \"got a 401 and this is a retry. Report error self.report_token_issue() return resp\",\n \"token: Dict of the token to be added to the cache \\\"\\\"\\\" uuid\",\n \"still before the current time, but if no such tokens exist it will\",\n \"a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window and\",\n \"specified scopes. The webserver will then need to catch the return with either\",\n \"ValueError('Cannot provide json in a post call') if method not in ['POST']: raise\",\n \"or None. Note that the bearer token might have been revoked by the\",\n \"URL for the requested method. :param method: The method name in the IdP\",\n \"= None self._retrieved_code = None # TODO: Make cache_lock a filesystem lock so\",\n \"token issues on 401. This helps with broken apps that may send a\",\n \"on OpenID Connect for authentication.\\\"\\\"\\\" from __future__ import print_function from copy import copy\",\n \"'grant_type': 'authorization_code', 'redirect_uri': return_uri, 'code': self._retrieved_code} if self.client_secret: data['client_secret'] = self.client_secret resp =\",\n \"return a message start_response('200 OK', [('Content-Type', 'text/plain')]) return [u'You can close this window\",\n \"from StringIO import StringIO except ImportError: from io import StringIO import socket import\",\n \"resp = resp.json() if 'error' in resp: self.debug('Unable to refresh, error: %s', resp['error'])\",\n \"token is retrieved if requested. It is always safe to call this though,\",\n \"already gone') def _get_token_with_scopes(self, scopes): \\\"\\\"\\\"Searches the cache for any tokens that have\",\n \"token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time() + int(resp['expires_in']), 'idp': self.idp, 'token_type':\",\n \"_update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token in the cache. cache_lock may not be\",\n \"unable to create it, the OSError will be thrown. :kwargs printfd: The File\",\n \"tokens', len(self._cache)) def _refresh_cache(self): \\\"\\\"\\\"Refreshes the self._cache from the cache on disk. cache_lock\",\n \"we will return the new access token. If it did not work, we\",\n \"hereby granted, free of charge, to any person obtaining a copy # of\",\n \"requesting token') if self.problem_reported: # We were reported an issue before. Let's just\",\n \"This function will store the new token in the local cache, add it\",\n \"not token: return None if self.use_post: if 'json' in ckwargs: raise ValueError('Cannot provide\",\n \"issue before. Let's just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid)\",\n \"OpenID Connect. :param app_identifier: Identifier for storage of retrieved tokens :param id_provider: URL\",\n \"we will return None and remove this token from the cache. If you\",\n \"SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. \\\"\\\"\\\"Client for\",\n \"_idp_url(self, method): \\\"\\\"\\\"Returns the IdP URL for the requested method. :param method: The\",\n \"because the account or token was lacking specific permissions. \\\"\\\"\\\" if not self.last_returned_uuid:\",\n \"token in the cache. cache_lock may not be held by anyone. :param token:\",\n \"{} rquery['scope'] = ' '.join(scopes) rquery['response_type'] = 'code' rquery['client_id'] = self.client_id rquery['redirect_uri'] =\",\n \"self._cache[uuid] = token self.__write_cache() return uuid def _update_token(self, uuid, toupdate): \\\"\\\"\\\"Updates a token\",\n \"print_function from copy import copy import json import logging from threading import Lock\",\n \"uuid, toupdate): \\\"\\\"\\\"Updates a token in the cache. cache_lock may not be held\",\n \"return to the CLI'.encode('ascii')] self._retrieved_code = None server = self._get_server(_token_app) if not server:\",\n \"Make cache_lock a filesystem lock so we also lock across # multiple invocations\",\n \"authz_url, file=self._printfd) webbrowser.open(authz_url) server.handle_request() server.server_close() assert self._retrieved_code is not None if self._retrieved_code is\",\n \"code: %s', resp['error']) return None token = {'access_token': resp['access_token'], 'refresh_token': resp['refresh_token'], 'expires_at': time.time()\",\n \"False: # The user cancelled the request self._retrieved_code = None self.debug('User cancelled') return\"\n]","isConversational":false}}},{"rowIdx":79,"cells":{"ngram":{"kind":"list like","value":["and this permission notice shall be included in all # copies of this","elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else","or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #-------------------------------------------------------------------------------","#------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\"LiteralData\" if is_input else","TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.","= avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges","the Software is # furnished to do so, subject to the following conditions:","EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,","SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection,","'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements","the Software without restriction, including without limitation the rights # to use, copy,","not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if","ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN","= (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm,","= None, [], [] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return","person obtaining a copy # of this software and associated documentation files (the","None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [],","_encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding))","attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference","ranges = avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype =","if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None:","this permission notice shall be included in all # copies of this Software","A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR","SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #","# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies","frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not None:","EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright","!= 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval)))","return elem def encode_output_descr(prm): \"\"\" Encode process description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm))","dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v))","= {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is","#------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\",","LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import (","None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if","WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj","of this Software or works derived from this Software. # # THE SOFTWARE","enum.values) for range_ in ranges: attr, elms = {}, [] if range_.closure !=","[] if range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not","is hereby granted, free of charge, to any person obtaining a copy #","<NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT","None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input):","persons to whom the Software is # furnished to do so, subject to","*[OWS(\"UOM\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is","outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs']","conditions: # # The above copyright notice and this permission notice shall be","INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A","ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in","avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange):","# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE","attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference","def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\"LiteralData\" if is_input else \"LiteralOutput\")","OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,","documentation files (the \"Software\"), to deal # in the Software without restriction, including","elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif","_encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\",","# THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum,","isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj,","to permit persons to whom the Software is # furnished to do so,","EOX IT Services GmbH # # Permission is hereby granted, free of charge,","ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT,","elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def","BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \"\"\" Encode common part of the","prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist","isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm,","*_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode common part of the execure response data","in ranges: attr, elms = {}, [] if range_.closure != 'closed': attr =","of charge, to any person obtaining a copy # of this software and","be included in all # copies of this Software or works derived from","range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing)))","elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not","**attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input else",") def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not None:","True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \"\"\" Encode process","elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny):","False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem","encode_input_exec(prm): \"\"\" Encode common part of the execure response data input.\"\"\" return WPS(\"Input\",","so, subject to the following conditions: # # The above copyright notice and","LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION","None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #-------------------------------------------------------------------------------","#------------------------------------------------------------------------------- # # WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org>","outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not","def encode_input_descr(prm): \"\"\" Encode process description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] =","attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval","outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema']","*elms, **attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input","elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if","if range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not None:","encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>>","GmbH # # Permission is hereby granted, free of charge, to any person","is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def","copy # of this software and associated documentation files (the \"Software\"), to deal","data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode common part of","\"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges","common sub-elements of all XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if prm.title or","_encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of all XML parameters.\"\"\" elist = [OWS(\"Identifier\",","\"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u","to the following conditions: # # The above copyright notice and this permission","def encode_output_def(outdef): \"\"\" Encode the execure response output definition.\"\"\" attrib = {} if","False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of all XML parameters.\"\"\"","execure response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the execure","Encode common sub-elements of all XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if prm.title","prm.dtype elem = NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name,","for range_ in ranges: attr, elms = {}, [] if range_.closure != 'closed':","attr, elms = {}, [] if range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure}","THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #-------------------------------------------------------------------------------","is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist =","( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process description","#------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH # # Permission is","dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\",","and associated documentation files (the \"Software\"), to deal # in the Software without","dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\",","encode_input_descr(prm): \"\"\" Encode process description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\",","prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u in prm.uoms]) ))","of all XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\",","elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\"LiteralData\" if is_input","frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema))","if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\",","})) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u in","eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from","from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\"","LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #","= NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData):","BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN","data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the execure response output","sublicense, and/or sell # copies of the Software, and to permit persons to","Software is # furnished to do so, subject to the following conditions: #","outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not","if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\"Spacing\",","isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed value object!","# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR","elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \"\"\" Encode process description output.\"\"\" elem =","_encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\")","parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> #","CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT","is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] =","= outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is","OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE","AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def","elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\",","\"\"\" Encode common part of the execure response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm))","elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem =","NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is","[], [] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{","elem def encode_output_descr(prm): \"\"\" Encode process description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if","response output definition.\"\"\" attrib = {} if outdef.uom is not None: attrib['uom'] =","2013 EOX IT Services GmbH # # Permission is hereby granted, free of","<http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C)","NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm,","# copies of the Software, and to permit persons to whom the Software","None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if","str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if","is not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\"","in all # copies of this Software or works derived from this Software.","attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def","[OWS(\"Identifier\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\",","frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\",","DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR","description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm,","not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type","elms = {}, [] if range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if","elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return","NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()])","if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is not None:",") #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm))","execure response output definition.\"\"\" attrib = {} if outdef.uom is not None: attrib['uom']","*_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True))","elem def encode_input_exec(prm): \"\"\" Encode common part of the execure response data input.\"\"\"","THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import","def encode_input_exec(prm): \"\"\" Encode common part of the execure response data input.\"\"\" return","prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return","is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] =","not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing","eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode","copies of this Software or works derived from this Software. # # THE","outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false'","= prm.dtype elem = NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"):","# WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors:","NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE","dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values) for","Encode common part of the execure response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def","software and associated documentation files (the \"Software\"), to deal # in the Software","is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema)) return","WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT","if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\", *[NIL(\"CRS\", prm.encode_crs(crs)) for crs in","OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN","elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return","isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm):","else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common","{}, [] if range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is","not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms,","f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding","isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \"\"\" Encode process description output.\"\"\"","and to permit persons to whom the Software is # furnished to do","use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the","prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if","the following conditions: # # The above copyright notice and this permission notice","= 'true' if outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm,","LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND","# furnished to do so, subject to the following conditions: # # The","avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges =","the Software, and to permit persons to whom the Software is # furnished","shall be included in all # copies of this Software or works derived","return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, })","rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #","# copies of this Software or works derived from this Software. # #","\"\"\" Encode common sub-elements of all XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if","not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False),","attrib = {} if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs","# Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #-------------------------------------------------------------------------------","_encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\"Format\",","FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF","None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if","merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to","for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None:","OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING","from this Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY","OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData,","OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process description input.\"\"\"","elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if","ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE","range_.closure} if range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not None:","to do so, subject to the following conditions: # # The above copyright","elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm,","IT Services GmbH # # Permission is hereby granted, free of charge, to","None, [], [] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\",","common part of the execure response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def","or works derived from this Software. # # THE SOFTWARE IS PROVIDED \"AS","is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if","dtype.encode(v)) for v in enum.values) for range_ in ranges: attr, elms = {},","elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed value","NIL(\"Supported\", *[OWS(\"UOM\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default","<NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH #","else: raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype()","the execure response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the","ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for","is not None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] =","= \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif","elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \"\"\" Encode","whom the Software is # furnished to do so, subject to the following","CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH","allowed value object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is","all XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\", prm.title","outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding']","free of charge, to any person obtaining a copy # of this software","return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input else \"ComplexOutput\",","elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \"\"\" Encode","PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT","copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software,","elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \"\"\" Encode common part of the execure","if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype","USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import (","return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum =","ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj,","OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters","elist = [OWS(\"Identifier\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if","None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if","without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense,","not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values) for range_ in ranges: attr,","NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif","is # furnished to do so, subject to the following conditions: # #","avobj.ranges else: raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype =","Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY","<<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services","if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None:","encode_output_def(outdef): \"\"\" Encode the execure response output definition.\"\"\" attrib = {} if outdef.uom","if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None:","to deal # in the Software without restriction, including without limitation the rights","to any person obtaining a copy # of this software and associated documentation","elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \"\"\" Encode process description","= avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype = avobj.dtype","NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms:","None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib)","title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def","input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if","OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #","is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\", *[NIL(\"CRS\", prm.encode_crs(crs)) for crs in prm.crss])","ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS,","= avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for","THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN","OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE","elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\",","is_input): return NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f","FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #","SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES","works derived from this Software. # # THE SOFTWARE IS PROVIDED \"AS IS\",","not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem","elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum,","= outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is","return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\",","= outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is","= {}, [] if range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval","Software, and to permit persons to whom the Software is # furnished to","None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if","part of the execure response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm):","AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #-------------------------------------------------------------------------------","\"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem","WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE.","*_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm,","this software and associated documentation files (the \"Software\"), to deal # in the","title_required=True): \"\"\" Encode common sub-elements of all XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)]","if prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges,","if frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\"Schema\",","1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>>","ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj,","this Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF","in enum.values) for range_ in ranges: attr, elms = {}, [] if range_.closure","execure response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode common","avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges =","if prm.title or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return","OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY,","NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process description input.\"\"\" elem =","granted, free of charge, to any person obtaining a copy # of this","response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the execure response","{ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not","BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \"\"\" Encode process description output.\"\"\" elem","outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference']","def encode_output_exec(prm): \"\"\" Encode common part of the execure response data output.\"\"\" return","= outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is","furnished to do so, subject to the following conditions: # # The above","modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and","ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES","# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,","= NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if","prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype =","# Permission is hereby granted, free of charge, to any person obtaining a","enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif","v in enum.values) for range_ in ranges: attr, elms = {}, [] if","definition.\"\"\" attrib = {} if outdef.uom is not None: attrib['uom'] = outdef.uom if","IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF","Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX","# # WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> #","description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\"","WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME>","None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input","sub-elements of all XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if prm.title or title_required:","publish, distribute, sublicense, and/or sell # copies of the Software, and to permit","outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType']","frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm,","else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\", *[NIL(\"CRS\", prm.encode_crs(crs)) for crs in prm.crss]) )","\"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT","if outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\"","elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def","dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not None:","if range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist)","True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem","else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt):","elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference):","if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return","process description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif","**attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of all XML parameters.\"\"\" elist","OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION","TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum",")) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem","without restriction, including without limitation the rights # to use, copy, modify, merge,","not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None,","in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is","\"\"\" Encode process description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm,","if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None:","LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True))","NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\",","in the Software without restriction, including without limitation the rights # to use,","PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS","is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\",","copies of the Software, and to permit persons to whom the Software is","OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values))","**{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u)","_encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\", *[NIL(\"CRS\",","frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return","def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of all XML parameters.\"\"\" elist =","ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise","Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- #","AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR","ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \"\"\"","def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\",","= NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema","= [OWS(\"Identifier\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract:","if enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values) for range_","WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of all","is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def","notice shall be included in all # copies of this Software or works","SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from","#------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference,","enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype","notice and this permission notice shall be included in all # copies of","elem = NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, }))","obtaining a copy # of this software and associated documentation files (the \"Software\"),","part of the execure response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\"","AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url,","NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE","isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\":","MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL","for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if","None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is","*_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of all XML","The above copyright notice and this permission notice shall be included in all","and/or sell # copies of the Software, and to permit persons to whom","prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input):","False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \"\"\" Encode common","input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode common part of the","\"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])),","enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values) for range_ in","OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\",","\"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm,","outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not","# in the Software without restriction, including without limitation the rights # to","avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v","the execure response output definition.\"\"\" attrib = {} if outdef.uom is not None:","( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import","from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, )","Encode the execure response output definition.\"\"\" attrib = {} if outdef.uom is not","None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr))","TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE","}) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj]","return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\", *[NIL(\"CRS\", prm.encode_crs(crs)) for","*[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type))","IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN #","# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS","Copyright (C) 2013 EOX IT Services GmbH # # Permission is hereby granted,","encode_output_exec(prm): \"\"\" Encode common part of the execure response data output.\"\"\" return WPS(\"Output\",","elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \"\"\" Encode common part","not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm,","any person obtaining a copy # of this software and associated documentation files","# # The above copyright notice and this permission notice shall be included","not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true'","\"Software\"), to deal # in the Software without restriction, including without limitation the","AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL,","elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj,","elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u in prm.uoms]) )) if","NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\", *[NIL(\"CRS\", prm.encode_crs(crs)) for crs","elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def","*_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the execure response output definition.\"\"\" attrib = {}","AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE","IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED,","process description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] =","a copy # of this software and associated documentation files (the \"Software\"), to","deal # in the Software without restriction, including without limitation the rights #","elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm,","outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode","AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, )","DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData,","if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u in prm.uoms])","Software or works derived from this Software. # # THE SOFTWARE IS PROVIDED","elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm,","return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\"LiteralData\" if","#------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"]","(C) 2013 EOX IT Services GmbH # # Permission is hereby granted, free","AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #","(the \"Software\"), to deal # in the Software without restriction, including without limitation","import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process","elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], []","IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR","all # copies of this Software or works derived from this Software. #","output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the execure response output definition.\"\"\"","return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the execure response output definition.\"\"\" attrib","distribute, sublicense, and/or sell # copies of the Software, and to permit persons","import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util","return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj,","raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if","is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj):","charge, to any person obtaining a copy # of this software and associated","WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO","if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData):","AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj)","elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True))","'true' if outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True):","common part of the execure response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef):","is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] =","enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum,","range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist) #-------------------------------------------------------------------------------","NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem =","\"\"\" Encode common part of the execure response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm,","True)) return elem def encode_output_descr(prm): \"\"\" Encode process description output.\"\"\" elem = NIL(\"Output\",","elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum,","WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO","is_input): dtype = prm.dtype elem = NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name,","# Copyright (C) 2013 EOX IT Services GmbH # # Permission is hereby","WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED","KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF","to whom the Software is # furnished to do so, subject to the","return NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in","limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or","COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER","if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData):","Encode common part of the execure response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False))","False)) return elem def encode_input_exec(prm): \"\"\" Encode common part of the execure response","AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection):","None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values) for range_ in ranges: attr, elms","= outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else","#------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))),","= [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\"Invalid","elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return","def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return","do so, subject to the following conditions: # # The above copyright notice","range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not None: elms.append(OWS(\"MinimumValue\",","if frmt.schema is not None: elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input):","THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR","THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange,","avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed value object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype","# #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH # # Permission","permit persons to whom the Software is # furnished to do so, subject","Permission is hereby granted, free of charge, to any person obtaining a copy","THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR","WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode the execure response output definition.\"\"\" attrib =","prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\"LiteralData\"","is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] =","IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT","EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,","Software without restriction, including without limitation the rights # to use, copy, modify,","is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\"Output\", *_encode_param_common(outdef,","of the execure response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\"","dtype = prm.dtype elem = NIL(\"LiteralData\" if is_input else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{","# The above copyright notice and this permission notice shall be included in","# of this software and associated documentation files (the \"Software\"), to deal #","OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR","above copyright notice and this permission notice shall be included in all #","CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE","object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None:","sell # copies of the Software, and to permit persons to whom the","OBJ=%r\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\"Value\",","elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values) for range_ in ranges: attr, elms =","XML parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\", prm.title or","isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm):","elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return","parameters.\"\"\" elist = [OWS(\"Identifier\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier))","prm.title or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist","# # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> #","<<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH # #","range_ in ranges: attr, elms = {}, [] if range_.closure != 'closed': attr","# <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH","restriction, including without limitation the rights # to use, copy, modify, merge, publish,","else \"LiteralOutput\") elem.append(OWS(\"DataType\", dtype.name, **{ ns_ows(\"reference\"): \"http://www.w3.org/TR/xmlschema-2/#%s\"%dtype.name, })) if prm.uoms: elem.append(NIL(\"UOMs\", NIL(\"Default\", OWS(\"UOM\",","output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData):","FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS","return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode common part of the execure","# # Permission is hereby granted, free of charge, to any person obtaining","not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema","u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not","Encode process description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False))","ranges: attr, elms = {}, [] if range_.closure != 'closed': attr = {ns_ows(\"rangeClosure\"):","prm.identifier)] if prm.title or title_required: elist.append(OWS(\"Title\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract))","ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \"\"\"","outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\"Output\",","or prm.identifier)) if prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype","BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR","LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False))","NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\"Encoding\", frmt.encoding)) if frmt.schema is not","(\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData):",") from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm):","def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\"Encoding\",","FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE","OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT","PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING","isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum):","for v in enum.values) for range_ in ranges: attr, elms = {}, []","[avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\"Invalid allowed","'closed': attr = {ns_ows(\"rangeClosure\"): range_.closure} if range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if","files (the \"Software\"), to deal # in the Software without restriction, including without","# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS","= {} if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is","not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding","def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f)","{} if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is not","isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \"\"\" Encode common part of","AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum","the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell","BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS,","isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges","# Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013","following conditions: # # The above copyright notice and this permission notice shall","of the Software, and to permit persons to whom the Software is #","**{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif","if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for f in prm.formats.itervalues()]) )","output definition.\"\"\" attrib = {} if outdef.uom is not None: attrib['uom'] = outdef.uom","prm.abstract: elist.append(OWS(\"Abstract\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem","ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process description input.\"\"\" elem = NIL(\"Input\",","Encode process description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"]","attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema","this Software or works derived from this Software. # # THE SOFTWARE IS","is_input): return NIL(\"BoundingBoxData\" if is_input else \"BoundingBoxOutput\", NIL(\"Default\", NIL(\"CRS\", prm.encode_crs(prm.default_crs))), NIL(\"Supported\", *[NIL(\"CRS\", prm.encode_crs(crs))","AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else:","\"0\")[bool(prm.is_optional)] elem.attrib[\"maxOccurs\"] = \"1\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm,","return elem def encode_input_exec(prm): \"\"\" Encode common part of the execure response data","XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME>","IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR","of the execure response data output.\"\"\" return WPS(\"Output\", *_encode_param_common(prm)) def encode_output_def(outdef): \"\"\" Encode","[] if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"):","\"\"\" Encode process description input.\"\"\" elem = NIL(\"Input\", *_encode_param_common(prm)) elem.attrib[\"minOccurs\"] = (\"1\", \"0\")[bool(prm.is_optional)]","encode_output_descr(prm): \"\"\" Encode process description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData):","AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows,","IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny,","attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type","if isinstance(avobj, AllowedAny): return OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url,","elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif","\"\"\" Encode the execure response output definition.\"\"\" attrib = {} if outdef.uom is","response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode common part","if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default))) return elem def","outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not","OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER","HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN","including without limitation the rights # to use, copy, modify, merge, publish, distribute,","if range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\",","_encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)), NIL(\"Supported\", *[_encode_format(f) for","Services GmbH # # Permission is hereby granted, free of charge, to any","<reponame>constantinius/eoxserver_combined<filename>eoxserver/services/ows/wps/v10/encoders/parameters.py #------------------------------------------------------------------------------- # # WPS 1.0 parameters' XML encoders # # Project: EOxServer","permission notice shall be included in all # copies of this Software or","range_.minval is not None: elms.append(OWS(\"MinimumValue\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval)))","copyright notice and this permission notice shall be included in all # copies","def encode_output_descr(prm): \"\"\" Encode process description output.\"\"\" elem = NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm,","False)) def encode_output_exec(prm): \"\"\" Encode common part of the execure response data output.\"\"\"","prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\"Format\", NIL(\"MimeType\", frmt.mime_type)) if frmt.encoding is not","# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER","in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\"DefaultValue\", str(prm.default)))","u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\"DefaultValue\",","OWS(\"AnyValue\") elif isinstance(avobj, AllowedByReference): return WPS(\"ValuesReference\", **{ ns_ows(\"reference\"): avobj.url, \"valuesForm\": avobj.url, }) elif","associated documentation files (the \"Software\"), to deal # in the Software without restriction,","return WPS(\"Output\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of","ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\", *elms, **attr)) return OWS(\"AllowedValues\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\"","hereby granted, free of charge, to any person obtaining a copy # of","of this software and associated documentation files (the \"Software\"), to deal # in","included in all # copies of this Software or works derived from this","OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS","attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding","value object! OBJ=%r\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not","# # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,","WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode common part of the execure response","WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \"\"\" Encode process description input.\"\"\" elem","*elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\"ComplexData\" if is_input else \"ComplexOutput\", NIL(\"Default\", _encode_format(prm.default_format)),","is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\"Spacing\", ddtype.encode(range_.spacing))) elist.append(OWS(\"Range\",","= NIL(\"Output\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False))","is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values) for range_ in ranges:","not None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs","NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY","OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData,","= dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\"Value\", dtype.encode(v)) for v in enum.values)","the execure response data input.\"\"\" return WPS(\"Input\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \"\"\" Encode","NIL(\"Default\", OWS(\"UOM\", prm.uoms[0])), NIL(\"Supported\", *[OWS(\"UOM\", u) for u in prm.uoms]) )) if is_input:","to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of","isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm,","derived from this Software. # # THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT","subject to the following conditions: # # The above copyright notice and this"],"string":"[\n \"and this permission notice shall be included in all # copies of this\",\n \"elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else\",\n \"or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #-------------------------------------------------------------------------------\",\n \"#------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input else\",\n \"TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\",\n \"= avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges\",\n \"the Software is # furnished to do so, subject to the following conditions:\",\n \"EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\",\n \"SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection,\",\n \"'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements\",\n \"the Software without restriction, including without limitation the rights # to use, copy,\",\n \"not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if\",\n \"ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN\",\n \"= (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm,\",\n \"= None, [], [] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return\",\n \"person obtaining a copy # of this software and associated documentation files (the\",\n \"None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [],\",\n \"_encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding))\",\n \"attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference\",\n \"ranges = avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype =\",\n \"if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None:\",\n \"this permission notice shall be included in all # copies of this Software\",\n \"A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR\",\n \"SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #\",\n \"# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies\",\n \"frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not None:\",\n \"EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright\",\n \"!= 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval)))\",\n \"return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm))\",\n \"dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v))\",\n \"= {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is\",\n \"#------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\",\",\n \"LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import (\",\n \"None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if\",\n \"WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj\",\n \"of this Software or works derived from this Software. # # THE SOFTWARE\",\n \"enum.values) for range_ in ranges: attr, elms = {}, [] if range_.closure !=\",\n \"[] if range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not\",\n \"is hereby granted, free of charge, to any person obtaining a copy #\",\n \"<NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT\",\n \"None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input):\",\n \"persons to whom the Software is # furnished to do so, subject to\",\n \"*[OWS(\\\"UOM\\\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is\",\n \"outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs']\",\n \"conditions: # # The above copyright notice and this permission notice shall be\",\n \"INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A\",\n \"ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in\",\n \"avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange):\",\n \"# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\",\n \"attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference\",\n \"def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\")\",\n \"OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,\",\n \"documentation files (the \\\"Software\\\"), to deal # in the Software without restriction, including\",\n \"elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif\",\n \"_encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\",\",\n \"# THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum,\",\n \"isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj,\",\n \"to permit persons to whom the Software is # furnished to do so,\",\n \"EOX IT Services GmbH # # Permission is hereby granted, free of charge,\",\n \"ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\",\n \"elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def\",\n \"BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common part of the\",\n \"prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist\",\n \"isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm,\",\n \"*_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data\",\n \"in ranges: attr, elms = {}, [] if range_.closure != 'closed': attr =\",\n \"of charge, to any person obtaining a copy # of this software and\",\n \"be included in all # copies of this Software or works derived from\",\n \"range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing)))\",\n \"elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not\",\n \"**attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input else\",\n \") def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not None:\",\n \"True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process\",\n \"elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny):\",\n \"False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem\",\n \"encode_input_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\",\",\n \"so, subject to the following conditions: # # The above copyright notice and\",\n \"LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION\",\n \"None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #-------------------------------------------------------------------------------\",\n \"#------------------------------------------------------------------------------- # # WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org>\",\n \"outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not\",\n \"def encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] =\",\n \"attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval\",\n \"outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema']\",\n \"*elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input\",\n \"elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if\",\n \"if range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not None:\",\n \"encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>>\",\n \"GmbH # # Permission is hereby granted, free of charge, to any person\",\n \"is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def\",\n \"copy # of this software and associated documentation files (the \\\"Software\\\"), to deal\",\n \"data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common part of\",\n \"\\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges\",\n \"common sub-elements of all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or\",\n \"_encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements of all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\",\",\n \"\\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u\",\n \"to the following conditions: # # The above copyright notice and this permission\",\n \"def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response output definition.\\\"\\\"\\\" attrib = {} if\",\n \"False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements of all XML parameters.\\\"\\\"\\\"\",\n \"execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure\",\n \"Encode common sub-elements of all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title\",\n \"prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name,\",\n \"for range_ in ranges: attr, elms = {}, [] if range_.closure != 'closed':\",\n \"attr, elms = {}, [] if range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure}\",\n \"THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #-------------------------------------------------------------------------------\",\n \"is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist =\",\n \"( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process description\",\n \"#------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH # # Permission is\",\n \"dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\",\",\n \"and associated documentation files (the \\\"Software\\\"), to deal # in the Software without\",\n \"dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\",\",\n \"encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\",\",\n \"prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in prm.uoms]) ))\",\n \"of all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\",\",\n \"elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input\",\n \"frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema))\",\n \"if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\",\",\n \"})) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in\",\n \"eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from\",\n \"from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\"\",\n \"LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #\",\n \"= NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData):\",\n \"BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN\",\n \"data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response output\",\n \"sublicense, and/or sell # copies of the Software, and to permit persons to\",\n \"Software is # furnished to do so, subject to the following conditions: #\",\n \"outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not\",\n \"if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\",\",\n \"isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed value object!\",\n \"# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\",\n \"elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem =\",\n \"_encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\")\",\n \"parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> #\",\n \"CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT\",\n \"is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] =\",\n \"= outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is\",\n \"OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE\",\n \"AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def\",\n \"elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\",\",\n \"\\\"\\\"\\\" Encode common part of the execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm))\",\n \"elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem =\",\n \"NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is\",\n \"[], [] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{\",\n \"elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if\",\n \"response output definition.\\\"\\\"\\\" attrib = {} if outdef.uom is not None: attrib['uom'] =\",\n \"2013 EOX IT Services GmbH # # Permission is hereby granted, free of\",\n \"<http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C)\",\n \"NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm,\",\n \"# copies of the Software, and to permit persons to whom the Software\",\n \"None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if\",\n \"str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if\",\n \"is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\"\",\n \"in all # copies of this Software or works derived from this Software.\",\n \"attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def\",\n \"[OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\",\",\n \"frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\",\",\n \"DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR\",\n \"description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm,\",\n \"not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type\",\n \"elms = {}, [] if range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if\",\n \"elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return\",\n \"NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()])\",\n \"if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is not None:\",\n \") #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm))\",\n \"execure response output definition.\\\"\\\"\\\" attrib = {} if outdef.uom is not None: attrib['uom']\",\n \"*_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True))\",\n \"elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data input.\\\"\\\"\\\"\",\n \"THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import\",\n \"def encode_input_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data input.\\\"\\\"\\\" return\",\n \"prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return\",\n \"is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] =\",\n \"not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing\",\n \"eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode\",\n \"copies of this Software or works derived from this Software. # # THE\",\n \"outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false'\",\n \"= prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"):\",\n \"# WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors:\",\n \"NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE\",\n \"dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values) for\",\n \"Encode common part of the execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def\",\n \"software and associated documentation files (the \\\"Software\\\"), to deal # in the Software\",\n \"is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return\",\n \"WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT\",\n \"if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\", *[NIL(\\\"CRS\\\", prm.encode_crs(crs)) for crs in\",\n \"OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\",\n \"elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return\",\n \"isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm):\",\n \"else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common\",\n \"{}, [] if range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is\",\n \"not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms,\",\n \"f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding\",\n \"isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\"\",\n \"and to permit persons to whom the Software is # furnished to do\",\n \"use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the\",\n \"prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if\",\n \"the following conditions: # # The above copyright notice and this permission notice\",\n \"= 'true' if outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm,\",\n \"LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND\",\n \"# furnished to do so, subject to the following conditions: # # The\",\n \"avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges =\",\n \"the Software, and to permit persons to whom the Software is # furnished\",\n \"shall be included in all # copies of this Software or works derived\",\n \"return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, })\",\n \"rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #\",\n \"# copies of this Software or works derived from this Software. # #\",\n \"\\\"\\\"\\\" Encode common sub-elements of all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if\",\n \"not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False),\",\n \"attrib = {} if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs\",\n \"# Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #-------------------------------------------------------------------------------\",\n \"_encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\\\"Format\\\",\",\n \"FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF\",\n \"None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if\",\n \"merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to\",\n \"for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None:\",\n \"OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\",\n \"from this Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY\",\n \"OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData,\",\n \"OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\"\",\n \"elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if\",\n \"ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE\",\n \"range_.closure} if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not None:\",\n \"to do so, subject to the following conditions: # # The above copyright\",\n \"elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm,\",\n \"IT Services GmbH # # Permission is hereby granted, free of charge, to\",\n \"None, [], [] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\",\",\n \"common part of the execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def\",\n \"or works derived from this Software. # # THE SOFTWARE IS PROVIDED \\\"AS\",\n \"is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if\",\n \"dtype.encode(v)) for v in enum.values) for range_ in ranges: attr, elms = {},\",\n \"elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed value\",\n \"NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default\",\n \"<NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH #\",\n \"else: raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype()\",\n \"the execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the\",\n \"ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for\",\n \"is not None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] =\",\n \"= \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif\",\n \"elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode\",\n \"whom the Software is # furnished to do so, subject to the following\",\n \"CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH\",\n \"allowed value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is\",\n \"all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title\",\n \"outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding']\",\n \"free of charge, to any person obtaining a copy # of this software\",\n \"return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\",\",\n \"elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode\",\n \"PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT\",\n \"copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software,\",\n \"elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common part of the execure\",\n \"if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype\",\n \"USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import (\",\n \"return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum =\",\n \"ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj,\",\n \"OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters\",\n \"elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if\",\n \"None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema if\",\n \"without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense,\",\n \"not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values) for range_ in ranges: attr,\",\n \"NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif\",\n \"is # furnished to do so, subject to the following conditions: # #\",\n \"avobj.ranges else: raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype =\",\n \"Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY\",\n \"<<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services\",\n \"if outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None:\",\n \"encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response output definition.\\\"\\\"\\\" attrib = {} if outdef.uom\",\n \"if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None:\",\n \"to deal # in the Software without restriction, including without limitation the rights\",\n \"to any person obtaining a copy # of this software and associated documentation\",\n \"elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process description\",\n \"= avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype\",\n \"NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms:\",\n \"None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib)\",\n \"title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def\",\n \"input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if\",\n \"OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #\",\n \"is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\", *[NIL(\\\"CRS\\\", prm.encode_crs(crs)) for crs in prm.crss])\",\n \"ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS,\",\n \"= avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for\",\n \"THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN\",\n \"OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE\",\n \"elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\",\",\n \"is_input): return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f\",\n \"FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #\",\n \"SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES\",\n \"works derived from this Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\",\",\n \"not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem\",\n \"elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum,\",\n \"= outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is\",\n \"return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\",\",\n \"= outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema is\",\n \"= {}, [] if range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval\",\n \"Software, and to permit persons to whom the Software is # furnished to\",\n \"None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if\",\n \"part of the execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm):\",\n \"AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #-------------------------------------------------------------------------------\",\n \"\\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem\",\n \"WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE.\",\n \"*_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm,\",\n \"this software and associated documentation files (the \\\"Software\\\"), to deal # in the\",\n \"title_required=True): \\\"\\\"\\\" Encode common sub-elements of all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)]\",\n \"if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges,\",\n \"if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\",\",\n \"1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>>\",\n \"ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj,\",\n \"this Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF\",\n \"in enum.values) for range_ in ranges: attr, elms = {}, [] if range_.closure\",\n \"execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common\",\n \"avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges =\",\n \"if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return\",\n \"OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY,\",\n \"NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem =\",\n \"granted, free of charge, to any person obtaining a copy # of this\",\n \"response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response\",\n \"{ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not\",\n \"BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem\",\n \"outdef.schema is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference']\",\n \"def encode_output_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data output.\\\"\\\"\\\" return\",\n \"= outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is\",\n \"furnished to do so, subject to the following conditions: # # The above\",\n \"modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and\",\n \"ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\",\n \"# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\",\n \"= NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if\",\n \"prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype =\",\n \"# Permission is hereby granted, free of charge, to any person obtaining a\",\n \"enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif\",\n \"v in enum.values) for range_ in ranges: attr, elms = {}, [] if\",\n \"definition.\\\"\\\"\\\" attrib = {} if outdef.uom is not None: attrib['uom'] = outdef.uom if\",\n \"IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF\",\n \"Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX\",\n \"# # WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> #\",\n \"description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\"\",\n \"WPS 1.0 parameters' XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME>\",\n \"None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input\",\n \"sub-elements of all XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required:\",\n \"publish, distribute, sublicense, and/or sell # copies of the Software, and to permit\",\n \"outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType']\",\n \"frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm,\",\n \"else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\", *[NIL(\\\"CRS\\\", prm.encode_crs(crs)) for crs in prm.crss]) )\",\n \"\\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT\",\n \"if outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\"\",\n \"elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def\",\n \"dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not None:\",\n \"if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist)\",\n \"True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem\",\n \"else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt):\",\n \"elist = None, [], [] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference):\",\n \"if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return\",\n \"process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif\",\n \"**attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements of all XML parameters.\\\"\\\"\\\" elist\",\n \"OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION\",\n \"TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum\",\n \")) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem\",\n \"without restriction, including without limitation the rights # to use, copy, modify, merge,\",\n \"not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None,\",\n \"in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is\",\n \"\\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm,\",\n \"if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None:\",\n \"LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True))\",\n \"NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\",\",\n \"in the Software without restriction, including without limitation the rights # to use,\",\n \"PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS\",\n \"is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\",\",\n \"copies of the Software, and to permit persons to whom the Software is\",\n \"OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values))\",\n \"**{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u)\",\n \"_encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\", *[NIL(\\\"CRS\\\",\",\n \"frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return\",\n \"def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements of all XML parameters.\\\"\\\"\\\" elist =\",\n \"ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise\",\n \"Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- #\",\n \"AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR\",\n \"ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm): \\\"\\\"\\\"\",\n \"def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\",\",\n \"= NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema\",\n \"= [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract:\",\n \"if enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values) for range_\",\n \"WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements of all\",\n \"is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def\",\n \"notice shall be included in all # copies of this Software or works\",\n \"SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from\",\n \"#------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference,\",\n \"enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype\",\n \"notice and this permission notice shall be included in all # copies of\",\n \"elem = NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, }))\",\n \"obtaining a copy # of this software and associated documentation files (the \\\"Software\\\"),\",\n \"part of the execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\"\",\n \"AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url,\",\n \"NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE\",\n \"isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\":\",\n \"MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL\",\n \"for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if\",\n \"None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is\",\n \"*_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements of all XML\",\n \"The above copyright notice and this permission notice shall be included in all\",\n \"and/or sell # copies of the Software, and to permit persons to whom\",\n \"prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input):\",\n \"False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common\",\n \"input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common part of the\",\n \"\\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])),\",\n \"enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values) for range_ in\",\n \"OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\",\",\n \"\\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm,\",\n \"outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not\",\n \"# in the Software without restriction, including without limitation the rights # to\",\n \"avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v\",\n \"the execure response output definition.\\\"\\\"\\\" attrib = {} if outdef.uom is not None:\",\n \"( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import\",\n \"from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, )\",\n \"Encode the execure response output definition.\\\"\\\"\\\" attrib = {} if outdef.uom is not\",\n \"None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr))\",\n \"TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE\",\n \"}) elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj]\",\n \"return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\", *[NIL(\\\"CRS\\\", prm.encode_crs(crs)) for\",\n \"*[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type))\",\n \"IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN #\",\n \"# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS\",\n \"Copyright (C) 2013 EOX IT Services GmbH # # Permission is hereby granted,\",\n \"encode_output_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\",\",\n \"elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common part\",\n \"not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm,\",\n \"any person obtaining a copy # of this software and associated documentation files\",\n \"# # The above copyright notice and this permission notice shall be included\",\n \"not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true'\",\n \"\\\"Software\\\"), to deal # in the Software without restriction, including without limitation the\",\n \"AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL,\",\n \"elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj,\",\n \"elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in prm.uoms]) )) if\",\n \"NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\", *[NIL(\\\"CRS\\\", prm.encode_crs(crs)) for crs\",\n \"elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def\",\n \"*_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response output definition.\\\"\\\"\\\" attrib = {}\",\n \"AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE\",\n \"IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED,\",\n \"process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] =\",\n \"a copy # of this software and associated documentation files (the \\\"Software\\\"), to\",\n \"deal # in the Software without restriction, including without limitation the rights #\",\n \"elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm,\",\n \"outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode\",\n \"AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, )\",\n \"DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData,\",\n \"if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in prm.uoms])\",\n \"Software or works derived from this Software. # # THE SOFTWARE IS PROVIDED\",\n \"elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm,\",\n \"return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\\\"LiteralData\\\" if\",\n \"#------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"]\",\n \"(C) 2013 EOX IT Services GmbH # # Permission is hereby granted, free\",\n \"AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #\",\n \"(the \\\"Software\\\"), to deal # in the Software without restriction, including without limitation\",\n \"import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process\",\n \"elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], []\",\n \"IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR\",\n \"all # copies of this Software or works derived from this Software. #\",\n \"output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response output definition.\\\"\\\"\\\"\",\n \"return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response output definition.\\\"\\\"\\\" attrib\",\n \"distribute, sublicense, and/or sell # copies of the Software, and to permit persons\",\n \"import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util\",\n \"return elem def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj,\",\n \"raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if\",\n \"is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj):\",\n \"charge, to any person obtaining a copy # of this software and associated\",\n \"WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO\",\n \"if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData):\",\n \"AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj)\",\n \"elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True))\",\n \"'true' if outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True):\",\n \"common part of the execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef):\",\n \"is not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] =\",\n \"enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum,\",\n \"range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #-------------------------------------------------------------------------------\",\n \"NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()]) ) def _encode_format(frmt): elem =\",\n \"\\\"\\\"\\\" Encode common part of the execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm,\",\n \"True)) return elem def encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\",\",\n \"elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def _encode_allowed_value(avobj): enum,\",\n \"WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO\",\n \"is_input): dtype = prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name,\",\n \"# Copyright (C) 2013 EOX IT Services GmbH # # Permission is hereby\",\n \"WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED\",\n \"KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\",\n \"to whom the Software is # furnished to do so, subject to the\",\n \"return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in\",\n \"limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or\",\n \"COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER\",\n \"if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData):\",\n \"Encode common part of the execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False))\",\n \"False)) return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common part of the execure response\",\n \"AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection):\",\n \"None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values) for range_ in ranges: attr, elms\",\n \"= outdef.schema if outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else\",\n \"#------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))),\",\n \"= [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid\",\n \"elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return\",\n \"def _encode_allowed_value(avobj): enum, ranges, elist = None, [], [] if isinstance(avobj, AllowedAny): return\",\n \"do so, subject to the following conditions: # # The above copyright notice\",\n \"range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\",\",\n \"if frmt.schema is not None: elem.append(NIL(\\\"Schema\\\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input):\",\n \"THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR\",\n \"THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange,\",\n \"avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype\",\n \"# #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH # # Permission\",\n \"permit persons to whom the Software is # furnished to do so, subject\",\n \"Permission is hereby granted, free of charge, to any person obtaining a copy\",\n \"THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\",\n \"WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode the execure response output definition.\\\"\\\"\\\" attrib =\",\n \"prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem = NIL(\\\"LiteralData\\\"\",\n \"is not None: attrib['schema'] = outdef.schema if outdef.as_reference is not None: attrib['asReference'] =\",\n \"IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT\",\n \"EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,\",\n \"Software without restriction, including without limitation the rights # to use, copy, modify,\",\n \"is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\\\"Output\\\", *_encode_param_common(outdef,\",\n \"of the execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\"\",\n \"dtype = prm.dtype elem = NIL(\\\"LiteralData\\\" if is_input else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{\",\n \"# The above copyright notice and this permission notice shall be included in\",\n \"# of this software and associated documentation files (the \\\"Software\\\"), to deal #\",\n \"OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR\",\n \"above copyright notice and this permission notice shall be included in all #\",\n \"CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE\",\n \"object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None:\",\n \"sell # copies of the Software, and to permit persons to whom the\",\n \"OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\\\"Value\\\",\",\n \"elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values) for range_ in ranges: attr, elms =\",\n \"XML parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or\",\n \"isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, True)) return elem def encode_output_descr(prm):\",\n \"elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return\",\n \"parameters.\\\"\\\"\\\" elist = [OWS(\\\"Identifier\\\", prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier))\",\n \"prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist\",\n \"# # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> #\",\n \"<<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH # #\",\n \"range_ in ranges: attr, elms = {}, [] if range_.closure != 'closed': attr\",\n \"# <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013 EOX IT Services GmbH\",\n \"restriction, including without limitation the rights # to use, copy, modify, merge, publish,\",\n \"else \\\"LiteralOutput\\\") elem.append(OWS(\\\"DataType\\\", dtype.name, **{ ns_ows(\\\"reference\\\"): \\\"http://www.w3.org/TR/xmlschema-2/#%s\\\"%dtype.name, })) if prm.uoms: elem.append(NIL(\\\"UOMs\\\", NIL(\\\"Default\\\", OWS(\\\"UOM\\\",\",\n \"output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData):\",\n \"FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS\",\n \"return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common part of the execure\",\n \"# # Permission is hereby granted, free of charge, to any person obtaining\",\n \"not None: attrib['encoding'] = outdef.encoding if outdef.schema is not None: attrib['schema'] = outdef.schema\",\n \"u) for u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not\",\n \"Encode process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False))\",\n \"ranges: attr, elms = {}, [] if range_.closure != 'closed': attr = {ns_ows(\\\"rangeClosure\\\"):\",\n \"prm.identifier)] if prm.title or title_required: elist.append(OWS(\\\"Title\\\", prm.title or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract))\",\n \"ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \\\"\\\"\\\"\",\n \"outdef.as_reference is not None: attrib['asReference'] = 'true' if outdef.as_reference else 'false' return WPS(\\\"Output\\\",\",\n \"or prm.identifier)) if prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype\",\n \"BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR\",\n \"LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False))\",\n \"NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\", frmt.encoding)) if frmt.schema is not\",\n \"(\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData):\",\n \") from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm):\",\n \"def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not None: elem.append(NIL(\\\"Encoding\\\",\",\n \"FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE\",\n \"OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT\",\n \"PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING\",\n \"isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum):\",\n \"for v in enum.values) for range_ in ranges: attr, elms = {}, []\",\n \"[avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else: raise TypeError(\\\"Invalid allowed\",\n \"'closed': attr = {ns_ows(\\\"rangeClosure\\\"): range_.closure} if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if\",\n \"files (the \\\"Software\\\"), to deal # in the Software without restriction, including without\",\n \"# THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS\",\n \"= {} if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is\",\n \"not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding\",\n \"def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f)\",\n \"{} if outdef.uom is not None: attrib['uom'] = outdef.uom if outdef.crs is not\",\n \"isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm, False)) return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common part of\",\n \"AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum\",\n \"the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\",\n \"BoundingBoxData, AllowedAny, AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS,\",\n \"isinstance(avobj, AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges\",\n \"# Authors: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # #------------------------------------------------------------------------------- # Copyright (C) 2013\",\n \"following conditions: # # The above copyright notice and this permission notice shall\",\n \"of the Software, and to permit persons to whom the Software is #\",\n \"**{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif isinstance(avobj, AllowedEnum): enum = avobj elif\",\n \"if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for f in prm.formats.itervalues()]) )\",\n \"output definition.\\\"\\\"\\\" attrib = {} if outdef.uom is not None: attrib['uom'] = outdef.uom\",\n \"prm.abstract: elist.append(OWS(\\\"Abstract\\\", prm.abstract)) return elist #------------------------------------------------------------------------------- def _encode_literal(prm, is_input): dtype = prm.dtype elem\",\n \"ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\",\",\n \"Encode process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"]\",\n \"attrib['mimeType'] = outdef.mime_type if outdef.encoding is not None: attrib['encoding'] = outdef.encoding if outdef.schema\",\n \"this Software or works derived from this Software. # # THE SOFTWARE IS\",\n \"is_input): return NIL(\\\"BoundingBoxData\\\" if is_input else \\\"BoundingBoxOutput\\\", NIL(\\\"Default\\\", NIL(\\\"CRS\\\", prm.encode_crs(prm.default_crs))), NIL(\\\"Supported\\\", *[NIL(\\\"CRS\\\", prm.encode_crs(crs))\",\n \"AllowedRange): ranges = [avobj] elif isinstance(avobj, AllowedRangeCollection): enum, ranges = avobj.enum, avobj.ranges else:\",\n \"\\\"0\\\")[bool(prm.is_optional)] elem.attrib[\\\"maxOccurs\\\"] = \\\"1\\\" if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm,\",\n \"return elem def encode_input_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data\",\n \"XML encoders # # Project: EOxServer <http://eoxserver.org> # Authors: <NAME> <<EMAIL>> # <NAME>\",\n \"IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR\",\n \"of the execure response data output.\\\"\\\"\\\" return WPS(\\\"Output\\\", *_encode_param_common(prm)) def encode_output_def(outdef): \\\"\\\"\\\" Encode\",\n \"[] if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"):\",\n \"\\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem = NIL(\\\"Input\\\", *_encode_param_common(prm)) elem.attrib[\\\"minOccurs\\\"] = (\\\"1\\\", \\\"0\\\")[bool(prm.is_optional)]\",\n \"encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData):\",\n \"AllowedEnum, AllowedRange, AllowedRangeCollection, AllowedByReference, ) from eoxserver.services.ows.wps.v10.util import ( OWS, WPS, NIL, ns_ows,\",\n \"IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData, BoundingBoxData, AllowedAny,\",\n \"attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type\",\n \"if isinstance(avobj, AllowedAny): return OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url,\",\n \"elif isinstance(avobj, AllowedEnum): enum = avobj elif isinstance(avobj, AllowedRange): ranges = [avobj] elif\",\n \"\\\"\\\"\\\" Encode the execure response output definition.\\\"\\\"\\\" attrib = {} if outdef.uom is\",\n \"response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common part\",\n \"if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default))) return elem def\",\n \"outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs if outdef.mime_type is not\",\n \"OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER\",\n \"HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN\",\n \"including without limitation the rights # to use, copy, modify, merge, publish, distribute,\",\n \"if range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\",\",\n \"_encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)), NIL(\\\"Supported\\\", *[_encode_format(f) for\",\n \"Services GmbH # # Permission is hereby granted, free of charge, to any\",\n \"<reponame>constantinius/eoxserver_combined<filename>eoxserver/services/ows/wps/v10/encoders/parameters.py #------------------------------------------------------------------------------- # # WPS 1.0 parameters' XML encoders # # Project: EOxServer\",\n \"permission notice shall be included in all # copies of this Software or\",\n \"range_.minval is not None: elms.append(OWS(\\\"MinimumValue\\\", dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval)))\",\n \"copyright notice and this permission notice shall be included in all # copies\",\n \"def encode_output_descr(prm): \\\"\\\"\\\" Encode process description output.\\\"\\\"\\\" elem = NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm,\",\n \"False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common part of the execure response data output.\\\"\\\"\\\"\",\n \"prm.formats.itervalues()]) ) def _encode_format(frmt): elem = NIL(\\\"Format\\\", NIL(\\\"MimeType\\\", frmt.mime_type)) if frmt.encoding is not\",\n \"# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\",\n \"in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\", str(prm.default)))\",\n \"u in prm.uoms]) )) if is_input: elem.append(_encode_allowed_value(prm.allowed_values)) if prm.default is not None: elem.append(NIL(\\\"DefaultValue\\\",\",\n \"OWS(\\\"AnyValue\\\") elif isinstance(avobj, AllowedByReference): return WPS(\\\"ValuesReference\\\", **{ ns_ows(\\\"reference\\\"): avobj.url, \\\"valuesForm\\\": avobj.url, }) elif\",\n \"associated documentation files (the \\\"Software\\\"), to deal # in the Software without restriction,\",\n \"return WPS(\\\"Output\\\", *_encode_param_common(outdef, False), **attrib) def _encode_param_common(prm, title_required=True): \\\"\\\"\\\" Encode common sub-elements of\",\n \"ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\", *elms, **attr)) return OWS(\\\"AllowedValues\\\", *elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\"\",\n \"hereby granted, free of charge, to any person obtaining a copy # of\",\n \"of this software and associated documentation files (the \\\"Software\\\"), to deal # in\",\n \"included in all # copies of this Software or works derived from this\",\n \"OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\",\n \"attrib['crs'] = outdef.crs if outdef.mime_type is not None: attrib['mimeType'] = outdef.mime_type if outdef.encoding\",\n \"value object! OBJ=%r\\\"%avobj) dtype = avobj.dtype ddtype = dtype.get_diff_dtype() if enum is not\",\n \"# # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND,\",\n \"WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode common part of the execure response\",\n \"WPS, NIL, ns_ows, ) #------------------------------------------------------------------------------- def encode_input_descr(prm): \\\"\\\"\\\" Encode process description input.\\\"\\\"\\\" elem\",\n \"*elist) #------------------------------------------------------------------------------- def _encode_complex(prm, is_input): return NIL(\\\"ComplexData\\\" if is_input else \\\"ComplexOutput\\\", NIL(\\\"Default\\\", _encode_format(prm.default_format)),\",\n \"is not None: elms.append(OWS(\\\"MaximumValue\\\", dtype.encode(range_.maxval))) if range_.spacing is not None: elms.append(OWS(\\\"Spacing\\\", ddtype.encode(range_.spacing))) elist.append(OWS(\\\"Range\\\",\",\n \"= NIL(\\\"Output\\\", *_encode_param_common(prm)) if isinstance(prm, LiteralData): elem.append(_encode_literal(prm, False)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, False))\",\n \"is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values) for range_ in ranges:\",\n \"not None: attrib['uom'] = outdef.uom if outdef.crs is not None: attrib['crs'] = outdef.crs\",\n \"NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\",\n \"OTHER DEALINGS IN # THE SOFTWARE. #------------------------------------------------------------------------------- from eoxserver.services.ows.wps.parameters import ( LiteralData, ComplexData,\",\n \"= dtype.get_diff_dtype() if enum is not None: elist.extend(OWS(\\\"Value\\\", dtype.encode(v)) for v in enum.values)\",\n \"the execure response data input.\\\"\\\"\\\" return WPS(\\\"Input\\\", *_encode_param_common(prm, False)) def encode_output_exec(prm): \\\"\\\"\\\" Encode\",\n \"NIL(\\\"Default\\\", OWS(\\\"UOM\\\", prm.uoms[0])), NIL(\\\"Supported\\\", *[OWS(\\\"UOM\\\", u) for u in prm.uoms]) )) if is_input:\",\n \"to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of\",\n \"isinstance(prm, LiteralData): elem.append(_encode_literal(prm, True)) elif isinstance(prm, ComplexData): elem.append(_encode_complex(prm, True)) elif isinstance(prm, BoundingBoxData): elem.append(_encode_bbox(prm,\",\n \"derived from this Software. # # THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT\",\n \"subject to the following conditions: # # The above copyright notice and this\"\n]","isConversational":false}}},{"rowIdx":80,"cells":{"ngram":{"kind":"list like","value":["Error uploading ' + archive_file + ' to ' + bucket + '","downloading ' + key + ' from ' + bucket + ' bucket.","data object to archive. This value is required. ''' if bucket is None","archive_key: The vp_save data's location (S3 bucket and file path). This value is","None or len(bucket) <= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk)","try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error uploading","vp_save_pk + '.json' # Upload curation data to S3 archive bucket. s3_client =","archive location. :param str bucket: The name of the S3 bucket for the","as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save","bucket + ' bucket. ERROR\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps)","raise return archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save object.","import datetime import uuid import simplejson as json from src.db.s3_client import Client as","' + bucket + ' bucket. ERROR\\n%s' %e) raise return archive_object def build(vp_save={}):","for the archive. This value is required. :param str vp_save_pk: The vp_save PK","save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' #","archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation data","archive. This value is required. ''' if bucket is None or len(bucket) <=","save data. If the upload fails, an exception is raised. If successful, returns","If successful, returns the archive location. :param str bucket: The name of the","a JSON file to S3. The location of the archive depends on the","ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if not","Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3. :param str archive_key:","attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now =","bucket + ' bucket. ERROR\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds","JSON file to S3. The location of the archive depends on the bucket","<= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise","or len(bucket) <= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <=","given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now","required. :param str vp_save_pk: The vp_save PK to use as the name of","now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data):","vp_save_pk, save_data): ''' Archives a vp save data to S3. Uploads the save","Archives a vp save data to S3. Uploads the save data object as","key + ' from ' + bucket + ' bucket. ERROR\\n%s' %e) raise","+ '/' + vp_save_pk + '.json' # Upload curation data to S3 archive","or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError() archive_file =","ERROR\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and returns a valid","= json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' + key","new vp_save object by creating default values for required fields and combines any","value is required. :param obj save_data: The save data object to archive. This","The vp_save PK to use as the name of the JSON file. This","+ vp_save_pk + '.json' # Upload curation data to S3 archive bucket. s3_client","bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal)","bucket. ERROR\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and returns a","to ' + bucket + ' bucket. ERROR\\n%s' %e) raise archive_key_comps = [bucket,","vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise","save data object as a JSON file to S3. The location of the","archive. This value is required. :param str vp_save_pk: The vp_save PK to use","vp_save object by creating default values for required fields and combines any of","of the archive depends on the bucket and the primary key of the","''' if archive_key is None or '/' not in archive_key: raise ValueError() bucket,","archive_key is None or '/' not in archive_key: raise ValueError() bucket, key =","a VP Save from S3. :param str archive_key: The vp_save data's location (S3","src.db.s3_client import Client as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download","This value is required. ''' if archive_key is None or '/' not in","bucket is None or len(bucket) <= 0: raise ValueError() if vp_save_pk is None","for required fields and combines any of the given attributes. ''' vp_save['PK'] =","data's location (S3 bucket and file path). This value is required. ''' if","is required. ''' if bucket is None or len(bucket) <= 0: raise ValueError()","<= 0: raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) +","+ ' bucket. ERROR\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def","if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk +","s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e:","' to ' + bucket + ' bucket. ERROR\\n%s' %e) raise archive_key_comps =","uuid import simplejson as json from src.db.s3_client import Client as S3Client from decimal","Error downloading ' + key + ' from ' + bucket + '","' bucket. ERROR\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def __archive_key(save_data):","a valid vp_save object. Builds a new vp_save object by creating default values","to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file )","uploading ' + archive_file + ' to ' + bucket + ' bucket.","fields and combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) #","by creating default values for required fields and combines any of the given","is required. :param obj save_data: The save data object to archive. This value","PK to use as the name of the JSON file. This value is","the save data. If the upload fails, an exception is raised. If successful,","# Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified']","str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now","not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client()","build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds a new vp_save","bucket. ERROR\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def __archive_key(save_data): return","of the save data. If the upload fails, an exception is raised. If","get_from_archive(archive_key): ''' Download a VP Save from S3. :param str archive_key: The vp_save","= archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception","ERROR\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def __archive_key(save_data): return save_data['PK']","+ ' to ' + bucket + ' bucket. ERROR\\n%s' %e) raise archive_key_comps","json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' + key +","is None or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError()","and returns a valid vp_save object. Builds a new vp_save object by creating","is required. :param str vp_save_pk: The vp_save PK to use as the name","of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new","key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' + key + '","data to S3. Uploads the save data object as a JSON file to","Client as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP","str archive_key: The vp_save data's location (S3 bucket and file path). This value",":param str vp_save_pk: The vp_save PK to use as the name of the","now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a","S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading","location. :param str bucket: The name of the S3 bucket for the archive.","file path). This value is required. ''' if archive_key is None or '/'","object to archive. This value is required. ''' if bucket is None or","or '/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client","location (S3 bucket and file path). This value is required. ''' if archive_key","S3. The location of the archive depends on the bucket and the primary","S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except","= __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation data to","= now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk,","vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): '''","archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' +","datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def","raised. If successful, returns the archive location. :param str bucket: The name of","'/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client =","This value is required. :param obj save_data: The save data object to archive.","= 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save","as a JSON file to S3. The location of the archive depends on","Exception as e: print('ERROR: Error downloading ' + key + ' from '","def get_from_archive(archive_key): ''' Download a VP Save from S3. :param str archive_key: The",":param str bucket: The name of the S3 bucket for the archive. This","ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket,","if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if not save_data:","not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json'","location of the archive depends on the bucket and the primary key of","+ '.json' # Upload curation data to S3 archive bucket. s3_client = S3Client()","from src.db.s3_client import Client as S3Client from decimal import Decimal def get_from_archive(archive_key): '''","archive depends on the bucket and the primary key of the save data.","= str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] =","bucket, archive_file ) except Exception as e: print('ERROR: Error uploading ' + archive_file","= now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives","' from ' + bucket + ' bucket. ERROR\\n%s' %e) raise return archive_object","depends on the bucket and the primary key of the save data. If","S3. :param str archive_key: The vp_save data's location (S3 bucket and file path).","archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception","in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try:","object as a JSON file to S3. The location of the archive depends","object. Builds a new vp_save object by creating default values for required fields","name of the JSON file. This value is required. :param obj save_data: The","' + key + ' from ' + bucket + ' bucket. ERROR\\n%s'",") except Exception as e: print('ERROR: Error uploading ' + archive_file + '","the bucket and the primary key of the save data. If the upload","# Upload curation data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object(","a vp save data to S3. Uploads the save data object as a","' bucket. ERROR\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and returns","object by creating default values for required fields and combines any of the","(S3 bucket and file path). This value is required. ''' if archive_key is","Download a VP Save from S3. :param str archive_key: The vp_save data's location","bucket for the archive. This value is required. :param str vp_save_pk: The vp_save","vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created']","the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data)","e: print('ERROR: Error downloading ' + key + ' from ' + bucket","and file path). This value is required. ''' if archive_key is None or","len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data)","+ archive_file + ' to ' + bucket + ' bucket. ERROR\\n%s' %e)","is None or len(bucket) <= 0: raise ValueError() if vp_save_pk is None or","the archive. This value is required. :param str vp_save_pk: The vp_save PK to","bucket and the primary key of the save data. If the upload fails,","vp save data to S3. Uploads the save data object as a JSON","save data object to archive. This value is required. ''' if bucket is","as e: print('ERROR: Error uploading ' + archive_file + ' to ' +","ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk","Uploads the save data object as a JSON file to S3. The location","required. :param obj save_data: The save data object to archive. This value is","archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object","json from src.db.s3_client import Client as S3Client from decimal import Decimal def get_from_archive(archive_key):","+ ' from ' + bucket + ' bucket. ERROR\\n%s' %e) raise return","vp_save PK to use as the name of the JSON file. This value","an exception is raised. If successful, returns the archive location. :param str bucket:","'/' + vp_save_pk + '.json' # Upload curation data to S3 archive bucket.","S3. Uploads the save data object as a JSON file to S3. The","None or '/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1)","print('ERROR: Error downloading ' + key + ' from ' + bucket +","bucket and file path). This value is required. ''' if archive_key is None","if archive_key is None or '/' not in archive_key: raise ValueError() bucket, key","''' if bucket is None or len(bucket) <= 0: raise ValueError() if vp_save_pk","exception is raised. If successful, returns the archive location. :param str bucket: The","vp_save data's location (S3 bucket and file path). This value is required. '''","combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps","file to S3. The location of the archive depends on the bucket and","archive_file + ' to ' + bucket + ' bucket. ERROR\\n%s' %e) raise","import simplejson as json from src.db.s3_client import Client as S3Client from decimal import","raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload","This value is required. ''' if bucket is None or len(bucket) <= 0:","archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as","decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3. :param","+ bucket + ' bucket. ERROR\\n%s' %e) raise return archive_object def build(vp_save={}): '''","(for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type']","bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as","save_data): ''' Archives a vp save data to S3. Uploads the save data","str vp_save_pk: The vp_save PK to use as the name of the JSON","except Exception as e: print('ERROR: Error uploading ' + archive_file + ' to","S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save from","raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' +","+ ' bucket. ERROR\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and","creating default values for required fields and combines any of the given attributes.","archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds a","save_data: The save data object to archive. This value is required. ''' if","print('ERROR: Error uploading ' + archive_file + ' to ' + bucket +","data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file","bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error uploading ' +","ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation","''' Download a VP Save from S3. :param str archive_key: The vp_save data's","of the S3 bucket for the archive. This value is required. :param str","and combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set","'.json' # Upload curation data to S3 archive bucket. s3_client = S3Client() try:","name of the S3 bucket for the archive. This value is required. :param","any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for","value is required. :param str vp_save_pk: The vp_save PK to use as the","curation data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket,","raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object =","valid vp_save object. Builds a new vp_save object by creating default values for","vp_save object. Builds a new vp_save object by creating default values for required","as json from src.db.s3_client import Client as S3Client from decimal import Decimal def","This value is required. :param str vp_save_pk: The vp_save PK to use as","VP Save from S3. :param str archive_key: The vp_save data's location (S3 bucket","from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3.","str bucket: The name of the S3 bucket for the archive. This value","1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e:","is raised. If successful, returns the archive location. :param str bucket: The name","timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now","required. ''' if archive_key is None or '/' not in archive_key: raise ValueError()","= S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error","default values for required fields and combines any of the given attributes. '''","successful, returns the archive location. :param str bucket: The name of the S3","values for required fields and combines any of the given attributes. ''' vp_save['PK']","from ' + bucket + ' bucket. ERROR\\n%s' %e) raise return archive_object def","e: print('ERROR: Error uploading ' + archive_file + ' to ' + bucket","s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error uploading '","bucket: The name of the S3 bucket for the archive. This value is","return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to","import uuid import simplejson as json from src.db.s3_client import Client as S3Client from","use as the name of the JSON file. This value is required. :param",":param obj save_data: The save data object to archive. This value is required.","Upload curation data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')),","The save data object to archive. This value is required. ''' if bucket","Save from S3. :param str archive_key: The vp_save data's location (S3 bucket and","''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat()","returns the archive location. :param str bucket: The name of the S3 bucket","the archive depends on the bucket and the primary key of the save","= S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR:","as e: print('ERROR: Error downloading ' + key + ' from ' +","+ bucket + ' bucket. ERROR\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return","to archive. This value is required. ''' if bucket is None or len(bucket)","__archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation data to S3","return archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds","import Client as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a","The location of the archive depends on the bucket and the primary key","vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to S3.","value is required. ''' if bucket is None or len(bucket) <= 0: raise","a new vp_save object by creating default values for required fields and combines","Exception as e: print('ERROR: Error uploading ' + archive_file + ' to '","S3 bucket for the archive. This value is required. :param str vp_save_pk: The","new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] =","+ key + ' from ' + bucket + ' bucket. ERROR\\n%s' %e)","now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return","None or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError() archive_file","of the JSON file. This value is required. :param obj save_data: The save","vp_save_pk: The vp_save PK to use as the name of the JSON file.","is required. ''' if archive_key is None or '/' not in archive_key: raise","= datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save","Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] =","the upload fails, an exception is raised. If successful, returns the archive location.","the S3 bucket for the archive. This value is required. :param str vp_save_pk:","key of the save data. If the upload fails, an exception is raised.","as the name of the JSON file. This value is required. :param obj",":param str archive_key: The vp_save data's location (S3 bucket and file path). This","value is required. ''' if archive_key is None or '/' not in archive_key:","returns a valid vp_save object. Builds a new vp_save object by creating default","If the upload fails, an exception is raised. If successful, returns the archive","vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp","import Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3. :param str","Builds and returns a valid vp_save object. Builds a new vp_save object by","and the primary key of the save data. If the upload fails, an","raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if","JSON file. This value is required. :param obj save_data: The save data object","''' Archives a vp save data to S3. Uploads the save data object","primary key of the save data. If the upload fails, an exception is","vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket,","' + bucket + ' bucket. ERROR\\n%s' %e) raise archive_key_comps = [bucket, archive_file]","try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading '","obj save_data: The save data object to archive. This value is required. '''","def build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds a new","required fields and combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4())","archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to S3. Uploads the","path). This value is required. ''' if archive_key is None or '/' not","S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error","the JSON file. This value is required. :param obj save_data: The save data","fails, an exception is raised. If successful, returns the archive location. :param str","simplejson as json from src.db.s3_client import Client as S3Client from decimal import Decimal","is None or '/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/',","0: raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/'","key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except","len(bucket) <= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0:","from S3. :param str archive_key: The vp_save data's location (S3 bucket and file","The vp_save data's location (S3 bucket and file path). This value is required.","to S3. Uploads the save data object as a JSON file to S3.","the archive location. :param str bucket: The name of the S3 bucket for","Builds a new vp_save object by creating default values for required fields and","data. If the upload fails, an exception is raised. If successful, returns the","0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError()","datetime import uuid import simplejson as json from src.db.s3_client import Client as S3Client","'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data","file. This value is required. :param obj save_data: The save data object to","%e) raise return archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save","The name of the S3 bucket for the archive. This value is required.","to use as the name of the JSON file. This value is required.","required. ''' if bucket is None or len(bucket) <= 0: raise ValueError() if","data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save'","to S3. The location of the archive depends on the bucket and the","''' Builds and returns a valid vp_save object. Builds a new vp_save object","except Exception as e: print('ERROR: Error downloading ' + key + ' from","the save data object as a JSON file to S3. The location of","archive_file ) except Exception as e: print('ERROR: Error uploading ' + archive_file +","def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to S3. Uploads","on the bucket and the primary key of the save data. If the","data object as a JSON file to S3. The location of the archive","upload fails, an exception is raised. If successful, returns the archive location. :param","s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR:","' + archive_file + ' to ' + bucket + ' bucket. ERROR\\n%s'","the name of the JSON file. This value is required. :param obj save_data:","save data to S3. Uploads the save data object as a JSON file","the primary key of the save data. If the upload fails, an exception","if bucket is None or len(bucket) <= 0: raise ValueError() if vp_save_pk is"],"string":"[\n \"Error uploading ' + archive_file + ' to ' + bucket + '\",\n \"downloading ' + key + ' from ' + bucket + ' bucket.\",\n \"data object to archive. This value is required. ''' if bucket is None\",\n \"archive_key: The vp_save data's location (S3 bucket and file path). This value is\",\n \"None or len(bucket) <= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk)\",\n \"try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error uploading\",\n \"vp_save_pk + '.json' # Upload curation data to S3 archive bucket. s3_client =\",\n \"archive location. :param str bucket: The name of the S3 bucket for the\",\n \"as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save\",\n \"bucket + ' bucket. ERROR\\\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps)\",\n \"raise return archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save object.\",\n \"import datetime import uuid import simplejson as json from src.db.s3_client import Client as\",\n \"' + bucket + ' bucket. ERROR\\\\n%s' %e) raise return archive_object def build(vp_save={}):\",\n \"for the archive. This value is required. :param str vp_save_pk: The vp_save PK\",\n \"save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' #\",\n \"archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation data\",\n \"archive. This value is required. ''' if bucket is None or len(bucket) <=\",\n \"save data. If the upload fails, an exception is raised. If successful, returns\",\n \"If successful, returns the archive location. :param str bucket: The name of the\",\n \"a JSON file to S3. The location of the archive depends on the\",\n \"ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if not\",\n \"Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3. :param str archive_key:\",\n \"attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now =\",\n \"bucket + ' bucket. ERROR\\\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds\",\n \"JSON file to S3. The location of the archive depends on the bucket\",\n \"<= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise\",\n \"or len(bucket) <= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <=\",\n \"given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now\",\n \"required. :param str vp_save_pk: The vp_save PK to use as the name of\",\n \"now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data):\",\n \"vp_save_pk, save_data): ''' Archives a vp save data to S3. Uploads the save\",\n \"Archives a vp save data to S3. Uploads the save data object as\",\n \"key + ' from ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise\",\n \"+ '/' + vp_save_pk + '.json' # Upload curation data to S3 archive\",\n \"or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError() archive_file =\",\n \"ERROR\\\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and returns a valid\",\n \"= json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' + key\",\n \"new vp_save object by creating default values for required fields and combines any\",\n \"value is required. :param obj save_data: The save data object to archive. This\",\n \"The vp_save PK to use as the name of the JSON file. This\",\n \"+ vp_save_pk + '.json' # Upload curation data to S3 archive bucket. s3_client\",\n \"bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal)\",\n \"bucket. ERROR\\\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and returns a\",\n \"to ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise archive_key_comps = [bucket,\",\n \"vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise\",\n \"save data object as a JSON file to S3. The location of the\",\n \"archive. This value is required. :param str vp_save_pk: The vp_save PK to use\",\n \"vp_save object by creating default values for required fields and combines any of\",\n \"of the archive depends on the bucket and the primary key of the\",\n \"''' if archive_key is None or '/' not in archive_key: raise ValueError() bucket,\",\n \"archive_key is None or '/' not in archive_key: raise ValueError() bucket, key =\",\n \"a VP Save from S3. :param str archive_key: The vp_save data's location (S3\",\n \"src.db.s3_client import Client as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download\",\n \"This value is required. ''' if archive_key is None or '/' not in\",\n \"bucket is None or len(bucket) <= 0: raise ValueError() if vp_save_pk is None\",\n \"for required fields and combines any of the given attributes. ''' vp_save['PK'] =\",\n \"data's location (S3 bucket and file path). This value is required. ''' if\",\n \"is required. ''' if bucket is None or len(bucket) <= 0: raise ValueError()\",\n \"<= 0: raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) +\",\n \"+ ' bucket. ERROR\\\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def\",\n \"if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk +\",\n \"s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e:\",\n \"' to ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise archive_key_comps =\",\n \"uuid import simplejson as json from src.db.s3_client import Client as S3Client from decimal\",\n \"Error downloading ' + key + ' from ' + bucket + '\",\n \"' bucket. ERROR\\\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def __archive_key(save_data):\",\n \"a valid vp_save object. Builds a new vp_save object by creating default values\",\n \"to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file )\",\n \"uploading ' + archive_file + ' to ' + bucket + ' bucket.\",\n \"fields and combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) #\",\n \"by creating default values for required fields and combines any of the given\",\n \"is required. :param obj save_data: The save data object to archive. This value\",\n \"PK to use as the name of the JSON file. This value is\",\n \"the save data. If the upload fails, an exception is raised. If successful,\",\n \"# Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified']\",\n \"str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now\",\n \"not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client()\",\n \"build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds a new vp_save\",\n \"bucket. ERROR\\\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def __archive_key(save_data): return\",\n \"of the save data. If the upload fails, an exception is raised. If\",\n \"get_from_archive(archive_key): ''' Download a VP Save from S3. :param str archive_key: The vp_save\",\n \"= archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception\",\n \"ERROR\\\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return '/'.join(archive_key_comps) def __archive_key(save_data): return save_data['PK']\",\n \"+ ' to ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise archive_key_comps\",\n \"json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' + key +\",\n \"is None or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError()\",\n \"and returns a valid vp_save object. Builds a new vp_save object by creating\",\n \"is required. :param str vp_save_pk: The vp_save PK to use as the name\",\n \"of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new\",\n \"key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' + key + '\",\n \"data to S3. Uploads the save data object as a JSON file to\",\n \"Client as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP\",\n \"str archive_key: The vp_save data's location (S3 bucket and file path). This value\",\n \":param str vp_save_pk: The vp_save PK to use as the name of the\",\n \"now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a\",\n \"S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading\",\n \"location. :param str bucket: The name of the S3 bucket for the archive.\",\n \"file path). This value is required. ''' if archive_key is None or '/'\",\n \"object to archive. This value is required. ''' if bucket is None or\",\n \"or '/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client\",\n \"location (S3 bucket and file path). This value is required. ''' if archive_key\",\n \"S3. The location of the archive depends on the bucket and the primary\",\n \"S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except\",\n \"= __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation data to\",\n \"= now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk,\",\n \"vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): '''\",\n \"archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading ' +\",\n \"datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def\",\n \"raised. If successful, returns the archive location. :param str bucket: The name of\",\n \"'/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client =\",\n \"This value is required. :param obj save_data: The save data object to archive.\",\n \"= 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save\",\n \"as a JSON file to S3. The location of the archive depends on\",\n \"Exception as e: print('ERROR: Error downloading ' + key + ' from '\",\n \"def get_from_archive(archive_key): ''' Download a VP Save from S3. :param str archive_key: The\",\n \":param str bucket: The name of the S3 bucket for the archive. This\",\n \"ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket,\",\n \"if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if not save_data:\",\n \"not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json'\",\n \"location of the archive depends on the bucket and the primary key of\",\n \"+ '.json' # Upload curation data to S3 archive bucket. s3_client = S3Client()\",\n \"from src.db.s3_client import Client as S3Client from decimal import Decimal def get_from_archive(archive_key): '''\",\n \"archive depends on the bucket and the primary key of the save data.\",\n \"= str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] =\",\n \"bucket, archive_file ) except Exception as e: print('ERROR: Error uploading ' + archive_file\",\n \"= now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives\",\n \"' from ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise return archive_object\",\n \"depends on the bucket and the primary key of the save data. If\",\n \"S3. :param str archive_key: The vp_save data's location (S3 bucket and file path).\",\n \"archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception\",\n \"in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try:\",\n \"object as a JSON file to S3. The location of the archive depends\",\n \"object. Builds a new vp_save object by creating default values for required fields\",\n \"name of the JSON file. This value is required. :param obj save_data: The\",\n \"' + key + ' from ' + bucket + ' bucket. ERROR\\\\n%s'\",\n \") except Exception as e: print('ERROR: Error uploading ' + archive_file + '\",\n \"the bucket and the primary key of the save data. If the upload\",\n \"# Upload curation data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object(\",\n \"a vp save data to S3. Uploads the save data object as a\",\n \"' bucket. ERROR\\\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and returns\",\n \"object by creating default values for required fields and combines any of the\",\n \"(S3 bucket and file path). This value is required. ''' if archive_key is\",\n \"Download a VP Save from S3. :param str archive_key: The vp_save data's location\",\n \"bucket for the archive. This value is required. :param str vp_save_pk: The vp_save\",\n \"vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created']\",\n \"the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data)\",\n \"e: print('ERROR: Error downloading ' + key + ' from ' + bucket\",\n \"and file path). This value is required. ''' if archive_key is None or\",\n \"len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data)\",\n \"+ archive_file + ' to ' + bucket + ' bucket. ERROR\\\\n%s' %e)\",\n \"is None or len(bucket) <= 0: raise ValueError() if vp_save_pk is None or\",\n \"the archive. This value is required. :param str vp_save_pk: The vp_save PK to\",\n \"bucket and the primary key of the save data. If the upload fails,\",\n \"vp save data to S3. Uploads the save data object as a JSON\",\n \"save data object to archive. This value is required. ''' if bucket is\",\n \"as e: print('ERROR: Error uploading ' + archive_file + ' to ' +\",\n \"ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk\",\n \"Uploads the save data object as a JSON file to S3. The location\",\n \"required. :param obj save_data: The save data object to archive. This value is\",\n \"archive_key: raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object\",\n \"json from src.db.s3_client import Client as S3Client from decimal import Decimal def get_from_archive(archive_key):\",\n \"+ ' from ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise return\",\n \"vp_save PK to use as the name of the JSON file. This value\",\n \"an exception is raised. If successful, returns the archive location. :param str bucket:\",\n \"'/' + vp_save_pk + '.json' # Upload curation data to S3 archive bucket.\",\n \"S3. Uploads the save data object as a JSON file to S3. The\",\n \"None or '/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/', 1)\",\n \"print('ERROR: Error downloading ' + key + ' from ' + bucket +\",\n \"bucket and file path). This value is required. ''' if archive_key is None\",\n \"if archive_key is None or '/' not in archive_key: raise ValueError() bucket, key\",\n \"''' if bucket is None or len(bucket) <= 0: raise ValueError() if vp_save_pk\",\n \"exception is raised. If successful, returns the archive location. :param str bucket: The\",\n \"vp_save data's location (S3 bucket and file path). This value is required. '''\",\n \"combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps\",\n \"file to S3. The location of the archive depends on the bucket and\",\n \"archive_file + ' to ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise\",\n \"import simplejson as json from src.db.s3_client import Client as S3Client from decimal import\",\n \"raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload\",\n \"This value is required. ''' if bucket is None or len(bucket) <= 0:\",\n \"archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as\",\n \"decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3. :param\",\n \"+ bucket + ' bucket. ERROR\\\\n%s' %e) raise return archive_object def build(vp_save={}): '''\",\n \"(for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type']\",\n \"bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as\",\n \"save_data): ''' Archives a vp save data to S3. Uploads the save data\",\n \"str vp_save_pk: The vp_save PK to use as the name of the JSON\",\n \"except Exception as e: print('ERROR: Error uploading ' + archive_file + ' to\",\n \"S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save from\",\n \"raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/' +\",\n \"+ ' bucket. ERROR\\\\n%s' %e) raise return archive_object def build(vp_save={}): ''' Builds and\",\n \"creating default values for required fields and combines any of the given attributes.\",\n \"archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds a\",\n \"save_data: The save data object to archive. This value is required. ''' if\",\n \"print('ERROR: Error uploading ' + archive_file + ' to ' + bucket +\",\n \"data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file\",\n \"bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error uploading ' +\",\n \"ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation\",\n \"''' Download a VP Save from S3. :param str archive_key: The vp_save data's\",\n \"of the S3 bucket for the archive. This value is required. :param str\",\n \"and combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set\",\n \"'.json' # Upload curation data to S3 archive bucket. s3_client = S3Client() try:\",\n \"name of the S3 bucket for the archive. This value is required. :param\",\n \"any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for\",\n \"value is required. :param str vp_save_pk: The vp_save PK to use as the\",\n \"curation data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket,\",\n \"raise ValueError() bucket, key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object =\",\n \"valid vp_save object. Builds a new vp_save object by creating default values for\",\n \"vp_save object. Builds a new vp_save object by creating default values for required\",\n \"as json from src.db.s3_client import Client as S3Client from decimal import Decimal def\",\n \"This value is required. :param str vp_save_pk: The vp_save PK to use as\",\n \"VP Save from S3. :param str archive_key: The vp_save data's location (S3 bucket\",\n \"from decimal import Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3.\",\n \"str bucket: The name of the S3 bucket for the archive. This value\",\n \"1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e:\",\n \"is raised. If successful, returns the archive location. :param str bucket: The name\",\n \"timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now\",\n \"required. ''' if archive_key is None or '/' not in archive_key: raise ValueError()\",\n \"= S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error\",\n \"default values for required fields and combines any of the given attributes. '''\",\n \"successful, returns the archive location. :param str bucket: The name of the S3\",\n \"values for required fields and combines any of the given attributes. ''' vp_save['PK']\",\n \"from ' + bucket + ' bucket. ERROR\\\\n%s' %e) raise return archive_object def\",\n \"e: print('ERROR: Error uploading ' + archive_file + ' to ' + bucket\",\n \"s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error uploading '\",\n \"bucket: The name of the S3 bucket for the archive. This value is\",\n \"return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to\",\n \"import uuid import simplejson as json from src.db.s3_client import Client as S3Client from\",\n \"use as the name of the JSON file. This value is required. :param\",\n \":param obj save_data: The save data object to archive. This value is required.\",\n \"Upload curation data to S3 archive bucket. s3_client = S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')),\",\n \"The save data object to archive. This value is required. ''' if bucket\",\n \"Save from S3. :param str archive_key: The vp_save data's location (S3 bucket and\",\n \"''' vp_save['PK'] = str(uuid.uuid4()) # Set timestamps (for new data) now = datetime.datetime.now().isoformat()\",\n \"returns the archive location. :param str bucket: The name of the S3 bucket\",\n \"the archive depends on the bucket and the primary key of the save\",\n \"= S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR:\",\n \"as e: print('ERROR: Error downloading ' + key + ' from ' +\",\n \"+ bucket + ' bucket. ERROR\\\\n%s' %e) raise archive_key_comps = [bucket, archive_file] return\",\n \"to archive. This value is required. ''' if bucket is None or len(bucket)\",\n \"__archive_key(save_data) + '/' + vp_save_pk + '.json' # Upload curation data to S3\",\n \"return archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds\",\n \"import Client as S3Client from decimal import Decimal def get_from_archive(archive_key): ''' Download a\",\n \"The location of the archive depends on the bucket and the primary key\",\n \"vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to S3.\",\n \"value is required. ''' if bucket is None or len(bucket) <= 0: raise\",\n \"a new vp_save object by creating default values for required fields and combines\",\n \"Exception as e: print('ERROR: Error uploading ' + archive_file + ' to '\",\n \"S3 bucket for the archive. This value is required. :param str vp_save_pk: The\",\n \"new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] =\",\n \"+ key + ' from ' + bucket + ' bucket. ERROR\\\\n%s' %e)\",\n \"now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return\",\n \"None or len(vp_save_pk) <= 0: raise ValueError() if not save_data: raise ValueError() archive_file\",\n \"of the JSON file. This value is required. :param obj save_data: The save\",\n \"vp_save_pk: The vp_save PK to use as the name of the JSON file.\",\n \"is required. ''' if archive_key is None or '/' not in archive_key: raise\",\n \"= datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save\",\n \"Set timestamps (for new data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] =\",\n \"the upload fails, an exception is raised. If successful, returns the archive location.\",\n \"the S3 bucket for the archive. This value is required. :param str vp_save_pk:\",\n \"key of the save data. If the upload fails, an exception is raised.\",\n \"as the name of the JSON file. This value is required. :param obj\",\n \":param str archive_key: The vp_save data's location (S3 bucket and file path). This\",\n \"value is required. ''' if archive_key is None or '/' not in archive_key:\",\n \"returns a valid vp_save object. Builds a new vp_save object by creating default\",\n \"If the upload fails, an exception is raised. If successful, returns the archive\",\n \"vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp\",\n \"import Decimal def get_from_archive(archive_key): ''' Download a VP Save from S3. :param str\",\n \"Builds and returns a valid vp_save object. Builds a new vp_save object by\",\n \"and the primary key of the save data. If the upload fails, an\",\n \"raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError() if\",\n \"JSON file. This value is required. :param obj save_data: The save data object\",\n \"''' Archives a vp save data to S3. Uploads the save data object\",\n \"primary key of the save data. If the upload fails, an exception is\",\n \"vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save' return vp_save def archive(bucket,\",\n \"' + bucket + ' bucket. ERROR\\\\n%s' %e) raise archive_key_comps = [bucket, archive_file]\",\n \"try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR: Error downloading '\",\n \"obj save_data: The save data object to archive. This value is required. '''\",\n \"def build(vp_save={}): ''' Builds and returns a valid vp_save object. Builds a new\",\n \"required fields and combines any of the given attributes. ''' vp_save['PK'] = str(uuid.uuid4())\",\n \"archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to S3. Uploads the\",\n \"path). This value is required. ''' if archive_key is None or '/' not\",\n \"S3Client() try: s3_client.put_object( bytes(json.dumps(save_data).encode('UTF-8')), bucket, archive_file ) except Exception as e: print('ERROR: Error\",\n \"the JSON file. This value is required. :param obj save_data: The save data\",\n \"fails, an exception is raised. If successful, returns the archive location. :param str\",\n \"simplejson as json from src.db.s3_client import Client as S3Client from decimal import Decimal\",\n \"is None or '/' not in archive_key: raise ValueError() bucket, key = archive_key.split('/',\",\n \"0: raise ValueError() if not save_data: raise ValueError() archive_file = __archive_key(save_data) + '/'\",\n \"key = archive_key.split('/', 1) s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except\",\n \"len(bucket) <= 0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0:\",\n \"from S3. :param str archive_key: The vp_save data's location (S3 bucket and file\",\n \"The vp_save data's location (S3 bucket and file path). This value is required.\",\n \"to S3. Uploads the save data object as a JSON file to S3.\",\n \"the archive location. :param str bucket: The name of the S3 bucket for\",\n \"Builds a new vp_save object by creating default values for required fields and\",\n \"data. If the upload fails, an exception is raised. If successful, returns the\",\n \"0: raise ValueError() if vp_save_pk is None or len(vp_save_pk) <= 0: raise ValueError()\",\n \"datetime import uuid import simplejson as json from src.db.s3_client import Client as S3Client\",\n \"'vp_save' return vp_save def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data\",\n \"file. This value is required. :param obj save_data: The save data object to\",\n \"%e) raise return archive_object def build(vp_save={}): ''' Builds and returns a valid vp_save\",\n \"The name of the S3 bucket for the archive. This value is required.\",\n \"to use as the name of the JSON file. This value is required.\",\n \"required. ''' if bucket is None or len(bucket) <= 0: raise ValueError() if\",\n \"data) now = datetime.datetime.now().isoformat() vp_save['date_created'] = now vp_save['last_modified'] = now vp_save['item_type'] = 'vp_save'\",\n \"to S3. The location of the archive depends on the bucket and the\",\n \"''' Builds and returns a valid vp_save object. Builds a new vp_save object\",\n \"except Exception as e: print('ERROR: Error downloading ' + key + ' from\",\n \"the save data object as a JSON file to S3. The location of\",\n \"archive_file ) except Exception as e: print('ERROR: Error uploading ' + archive_file +\",\n \"def archive(bucket, vp_save_pk, save_data): ''' Archives a vp save data to S3. Uploads\",\n \"on the bucket and the primary key of the save data. If the\",\n \"data object as a JSON file to S3. The location of the archive\",\n \"upload fails, an exception is raised. If successful, returns the archive location. :param\",\n \"s3_client = S3Client() try: archive_object = json.loads(s3_client.get_object(bucket, key)['Body'].read(),parse_float=Decimal) except Exception as e: print('ERROR:\",\n \"' + archive_file + ' to ' + bucket + ' bucket. ERROR\\\\n%s'\",\n \"the name of the JSON file. This value is required. :param obj save_data:\",\n \"save data to S3. Uploads the save data object as a JSON file\",\n \"the primary key of the save data. If the upload fails, an exception\",\n \"if bucket is None or len(bucket) <= 0: raise ValueError() if vp_save_pk is\"\n]","isConversational":false}}},{"rowIdx":81,"cells":{"ngram":{"kind":"list like","value":["plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x","= brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0,","plt from brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax","import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as np fig","basic usage of brokenaxes \"\"\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes","usage of brokenaxes \"\"\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import","Basic usage =========== This example presents the basic usage of brokenaxes \"\"\" import","brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4,","of brokenaxes \"\"\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy","1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x,","matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as np fig =","as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7),","bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x =","1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos') bax.legend(loc=3)","the basic usage of brokenaxes \"\"\" import matplotlib.pyplot as plt from brokenaxes import","\"\"\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as np",".7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x),","hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10","= np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x),","(.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x,","import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)),","as plt from brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2))","= plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05)","ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 *","import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1),","fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)),","100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos') bax.legend(loc=3) bax.set_xlabel('time')","This example presents the basic usage of brokenaxes \"\"\" import matplotlib.pyplot as plt",".1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100)","brokenaxes \"\"\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as","numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1,","example presents the basic usage of brokenaxes \"\"\" import matplotlib.pyplot as plt from","brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1,","np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos')","presents the basic usage of brokenaxes \"\"\" import matplotlib.pyplot as plt from brokenaxes","x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 *","usage =========== This example presents the basic usage of brokenaxes \"\"\" import matplotlib.pyplot","=========== This example presents the basic usage of brokenaxes \"\"\" import matplotlib.pyplot as","bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos') bax.legend(loc=3) bax.set_xlabel('time') bax.set_ylabel('value')","from brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax =","brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0,","(.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin')",".7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10","np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79,","\"\"\" Basic usage =========== This example presents the basic usage of brokenaxes \"\"\""],"string":"[\n \"plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x\",\n \"= brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0,\",\n \"plt from brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax\",\n \"import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as np fig\",\n \"basic usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes\",\n \"usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import\",\n \"Basic usage =========== This example presents the basic usage of brokenaxes \\\"\\\"\\\" import\",\n \"brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4,\",\n \"of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy\",\n \"1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x,\",\n \"matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as np fig =\",\n \"as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7),\",\n \"bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x =\",\n \"1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos') bax.legend(loc=3)\",\n \"the basic usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt from brokenaxes import\",\n \"\\\"\\\"\\\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as np\",\n \".7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x),\",\n \"hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10\",\n \"= np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x),\",\n \"(.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x,\",\n \"import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)),\",\n \"as plt from brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2))\",\n \"= plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05)\",\n \"ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 *\",\n \"import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1),\",\n \"fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)),\",\n \"100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos') bax.legend(loc=3) bax.set_xlabel('time')\",\n \"This example presents the basic usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt\",\n \".1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100)\",\n \"brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt from brokenaxes import brokenaxes import numpy as\",\n \"numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1,\",\n \"example presents the basic usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt from\",\n \"brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1,\",\n \"np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos')\",\n \"presents the basic usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as plt from brokenaxes\",\n \"x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 *\",\n \"usage =========== This example presents the basic usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot\",\n \"=========== This example presents the basic usage of brokenaxes \\\"\\\"\\\" import matplotlib.pyplot as\",\n \"bax.plot(x, np.sin(10 * x), label='sin') bax.plot(x, np.cos(10 * x), label='cos') bax.legend(loc=3) bax.set_xlabel('time') bax.set_ylabel('value')\",\n \"from brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax =\",\n \"brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0,\",\n \"(.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10 * x), label='sin')\",\n \".7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0, 1, 100) bax.plot(x, np.sin(10\",\n \"np fig = plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79,\",\n \"\\\"\\\"\\\" Basic usage =========== This example presents the basic usage of brokenaxes \\\"\\\"\\\"\"\n]","isConversational":false}}},{"rowIdx":82,"cells":{"ngram":{"kind":"list like","value":["suffix = tmp[1] ln = suffix ln_org = \"\" if ln in ln_map:","wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki = {} if os.path.exists(db_path): with open(db_path)","{} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with","RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in","label if \"labels\" in obj and \"ja\" in obj[\"labels\"]: stmt = (subject, RDFS.label,","prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org = \"\" if","as f: wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db:","URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif","places: places[suffix] = { \"lat\" : float(value[0]), \"long\": float(value[1]) } all.add(stmt) ''' #","# 位置情報 ''' if \"point\" in obj and prefix == \"place\": value =","URIRef(value)) all.add(stmt) # 位置情報 ''' if \"point\" in obj and prefix == \"place\":","[] for obj in result: fields = [\"spatial\", \"agential\"] for field in fields:","if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if label[\"lang\"]","in ln_map: ln_org = ln ln = ln_map[ln] if len(ln) > 20: continue","elif prefix == \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix ==","(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"),","= Graph() with open(\"data/dict.json\") as f: ln_map = json.load(f) st_path = \"../data/index.json\" with","RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\"","BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import","in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \"point\"","label[\"lang\"] == \"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj:","in uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\":\") prefix =","ln_map = json.load(f) st_path = \"../data/index.json\" with open(st_path) as f: result = json.load(f)","all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt","open(wiki_path) as f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url))","in values: uri = \"chname:\"+value if field == \"spatial\": uri = \"place:\"+value if","Namespace all = Graph() with open(\"data/dict.json\") as f: ln_map = json.load(f) st_path =","= (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"]","= (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path = \"data/all.json\" all.serialize(destination=path, format='json-ld') all.serialize(destination=path.replace(\".json\", \".rdf\"), format='pretty-xml')","ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path = \"data/all.json\" all.serialize(destination=path, format='json-ld') all.serialize(destination=path.replace(\".json\",","prefix == \"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\":","description if \"descriptions\" in obj and \"ja\" in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"),","obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value = label[\"value\"] if \"http://dbpedia.org\"","import urllib import ssl import csv import time import requests import json import","(subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if \"labels\" in obj and \"ja\"","yaml import sys import urllib import ssl import csv import time import requests","csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS,","if label[\"lang\"] == \"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in","= {} wiki = {} if os.path.exists(db_path): with open(db_path) as f: db =","stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\"","in labels: if label[\"lang\"] == \"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if","obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value = label[\"value\"] if \"http://dbpedia.org\" in value or","= [] for obj in result: fields = [\"spatial\", \"agential\"] for field in","== \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\": stmt","\"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\": stmt =","elif prefix == \"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj","obj[field] for value in values: uri = \"chname:\"+value if field == \"spatial\": uri","\"labels\" in obj and \"ja\" in obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt)","== \"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels","} all.add(stmt) ''' # 正規化前 if ln_org != \"\" and ln != ln_org:","if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in value: stmt","\"lat\" : float(value[0]), \"long\": float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix","= json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri =","value or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"),","db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db: print(\"not\" , db_uri) continue #","XSD from rdflib import Namespace all = Graph() with open(\"data/dict.json\") as f: ln_map","suffix ln_org = \"\" if ln in ln_map: ln_org = ln ln =","= \"chname:\"+value if field == \"spatial\": uri = \"place:\"+value if uri not in","URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in","= uri.split(\":\") prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org =","= obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri = addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1])","stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"]","if ln in ln_map: ln_org = ln ln = ln_map[ln] if len(ln) >","or \"www.wikidata.org\" in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 '''","in places: places[suffix] = { \"lat\" : float(value[0]), \"long\": float(value[1]) } all.add(stmt) '''","ln = wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db = {}","stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if \"labels\" in obj",": float(value[0]), \"long\": float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not","import Namespace all = Graph() with open(\"data/dict.json\") as f: ln_map = json.load(f) st_path","== \"place\": value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri = addGeo({ \"lat\" :","or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value))","(subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"]))","ln_map: ln_org = ln ln = ln_map[ln] if len(ln) > 20: continue #","tmp = uri.split(\":\") prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org","labels: value = label[\"value\"] if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in value or","{} wiki = {} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f)","# description if \"descriptions\" in obj and \"ja\" in obj[\"descriptions\"]: stmt = (subject,","= json.load(f) st_path = \"../data/index.json\" with open(st_path) as f: result = json.load(f) uris","# label if \"labels\" in obj and \"ja\" in obj[\"labels\"]: stmt = (subject,","\"long\": float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in places:","URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in places: places[suffix] = { \"lat\" : float(value[0]),","f: wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db: print(\"not\"","shutil import os import json import glob import yaml import sys import urllib","time import requests import json import csv from rdflib import URIRef, BNode, Literal,","if db_uri not in db: print(\"not\" , db_uri) continue # ###### subject =","== \"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\": stmt","open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki","RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt)","import RDF, RDFS, FOAF, XSD from rdflib import Namespace all = Graph() with","json import csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import","f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f)","import json import csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace","RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt)","with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f:","stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\": stmt = (subject,","[\"spatial\", \"agential\"] for field in fields: values = obj[field] for value in values:","(subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path =","stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \"point\" in obj","\"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stmt =","in labels: value = label[\"value\"] if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in value","= (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\": stmt = (subject, RDF.type,","''' # 正規化前 if ln_org != \"\" and ln != ln_org: stmt =","ln = suffix ln_org = \"\" if ln in ln_map: ln_org = ln","\"place:\"+value if uri not in uris: uris.append(uri) for uri in uris: print(uri) tmp","if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if","len(ln) > 20: continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki","(subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in obj","= (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject,","lang=\"ja\")) all.add(stmt) # label if \"labels\" in obj and \"ja\" in obj[\"labels\"]: stmt","json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln","uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\":\") prefix = tmp[0]","not in uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\":\") prefix","{ \"lat\" : float(value[0]), \"long\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org","stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\": stmt = (subject,","result = json.load(f) uris = [] for obj in result: fields = [\"spatial\",","float(value[0]), \"long\": float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in","obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path =","uri = \"chname:\"+value if field == \"spatial\": uri = \"place:\"+value if uri not","value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri = addGeo({ \"lat\" : float(value[0]), \"long\":","正規化前 if ln_org != \"\" and ln != ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"),","= \"../data/index.json\" with open(st_path) as f: result = json.load(f) uris = [] for","= (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\": stmt = (subject, RDF.type,","obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as","\"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj = db[db_uri] stmt","\"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj:","''' if \"point\" in obj and prefix == \"place\": value = obj[\"point\"][\"value\"].split(\" \")","json.load(f) # sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] #","with open(wiki_path) as f: wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not","= \"\" if ln in ln_map: ln_org = ln ln = ln_map[ln] if","\"place\": value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri = addGeo({ \"lat\" : float(value[0]),","URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in obj and \"ja\"","wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki","obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels =","RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt)","obj and \"ja\" in obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln =","for label in labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\"","all.add(stmt) # 位置情報 ''' if \"point\" in obj and prefix == \"place\": value","= addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri)","= tmp[1] ln = suffix ln_org = \"\" if ln in ln_map: ln_org","stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\"","RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri))","in value or \"www.wikidata.org\" in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) #","= obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path)","stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\": stmt = (subject,","in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value = label[\"value\"] if","if \"descriptions\" in obj and \"ja\" in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"],","addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if","rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD","= (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for","all.add(stmt) elif prefix == \"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ######","uri.split(\":\") prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org = \"\"","in value or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in value: stmt = (subject,","and \"ja\" in obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1]","in obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path","continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt = (subject,","= obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt)","elif prefix == \"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix ==","for field in fields: values = obj[field] for value in values: uri =","if len(ln) > 20: continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\"","ln = ln_map[ln] if len(ln) > 20: continue # ln = obj[\"uri\"].split(\":\")[1] '''","obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"],","= (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in places: places[suffix] = { \"lat\"","= tmp[0] suffix = tmp[1] ln = suffix ln_org = \"\" if ln","ln_org != \"\" and ln != ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt)","= URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif","in uris: print(uri) tmp = uri.split(\":\") prefix = tmp[0] suffix = tmp[1] ln","and ln != ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path = \"data/all.json\"","\"../data/index.json\" with open(st_path) as f: result = json.load(f) uris = [] for obj","import os import json import glob import yaml import sys import urllib import","uris = [] for obj in result: fields = [\"spatial\", \"agential\"] for field","with open(\"data/dict.json\") as f: ln_map = json.load(f) st_path = \"../data/index.json\" with open(st_path) as","= (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stmt = (subject, RDF.type,","FOAF, XSD from rdflib import Namespace all = Graph() with open(\"data/dict.json\") as f:","print(uri) tmp = uri.split(\":\") prefix = tmp[0] suffix = tmp[1] ln = suffix","fields: values = obj[field] for value in values: uri = \"chname:\"+value if field","\"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki = {} if os.path.exists(db_path): with","= (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path","import yaml import sys import urllib import ssl import csv import time import","RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt)","stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in places: places[suffix] = {","addGeo関数 geoUri = addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1]) }) stmt = (subject,","stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\": stmt = (subject,","all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value","}) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in places: places[suffix] =","(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\"))","import glob import yaml import sys import urllib import ssl import csv import","db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt =","\"descriptions\" in obj and \"ja\" in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\"))","uri in uris: print(uri) tmp = uri.split(\":\") prefix = tmp[0] suffix = tmp[1]","\"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db: print(\"not\" , db_uri) continue # ###### subject","(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\"))","all.add(stmt) elif prefix == \"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix","if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path)","URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label","os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt = (subject,","== \"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\": stmt","value = label[\"value\"] if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\"","= json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db: print(\"not\" , db_uri)","if \"labels\" in obj and \"ja\" in obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"]))","obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if label[\"lang\"] == \"ja\": stmt","stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\": stmt = (subject,","(subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label","rdflib import Namespace all = Graph() with open(\"data/dict.json\") as f: ln_map = json.load(f)","ln_org = ln ln = ln_map[ln] if len(ln) > 20: continue # ln","Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db","ln != ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path = \"data/all.json\" all.serialize(destination=path,","labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels","obj = db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj:","\"www.wikidata.org\" in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if","= [\"spatial\", \"agential\"] for field in fields: values = obj[field] for value in","stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path = \"data/all.json\" all.serialize(destination=path, format='json-ld') all.serialize(destination=path.replace(\".json\", \".rdf\"),","requests import json import csv from rdflib import URIRef, BNode, Literal, Graph from","not in db: print(\"not\" , db_uri) continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if","in labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj:","RDF, RDFS, FOAF, XSD from rdflib import Namespace all = Graph() with open(\"data/dict.json\")","\"ja\" in obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln = wiki_url.split(\"/\")[-1] '''","all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if","prefix == \"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\":","st_path = \"../data/index.json\" with open(st_path) as f: result = json.load(f) uris = []","\"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f)","if suffix not in places: places[suffix] = { \"lat\" : float(value[0]), \"long\": float(value[1])","for obj in result: fields = [\"spatial\", \"agential\"] for field in fields: values","stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject,","\"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\": stmt =","uris: print(uri) tmp = uri.split(\":\") prefix = tmp[0] suffix = tmp[1] ln =","= (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\": stmt = (subject, RDF.type,","import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from","= db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt","== \"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stmt","labels: if label[\"lang\"] == \"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\"","label in labels: value = label[\"value\"] if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in","from rdflib import Namespace all = Graph() with open(\"data/dict.json\") as f: ln_map =","RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt)","float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in places: places[suffix]","in obj and prefix == \"place\": value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri","labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value = label[\"value\"] if \"http://dbpedia.org\" in","stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj = db[db_uri] stmt =","URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in obj and","(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\"))","import time import requests import json import csv from rdflib import URIRef, BNode,","(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\"))","obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if \"labels\" in","# addGeo関数 geoUri = addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1]) }) stmt =","if uri not in uris: uris.append(uri) for uri in uris: print(uri) tmp =","db = {} wiki = {} if os.path.exists(db_path): with open(db_path) as f: db","not in places: places[suffix] = { \"lat\" : float(value[0]), \"long\": float(value[1]) } all.add(stmt)","tmp[1] ln = suffix ln_org = \"\" if ln in ln_map: ln_org =","20: continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {}","(subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \"point\" in obj and prefix","# sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description","= obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if label[\"lang\"] == \"ja\": stmt = (subject,","!= ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path = \"data/all.json\" all.serialize(destination=path, format='json-ld')","labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if label[\"lang\"] == \"ja\": stmt =","db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri","elif prefix == \"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix ==","values: uri = \"chname:\"+value if field == \"spatial\": uri = \"place:\"+value if uri","in obj and \"ja\" in obj[\"labels\"]: stmt = (subject, RDFS.label, Literal(obj[\"labels\"][\"ja\"][\"value\"])) all.add(stmt) ln","uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\":\") prefix = tmp[0] suffix","ln in ln_map: ln_org = ln ln = ln_map[ln] if len(ln) > 20:","\"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\": stmt =","if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt =","= ln ln = ln_map[ln] if len(ln) > 20: continue # ln =","= {} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path):","for uri in uris: print(uri) tmp = uri.split(\":\") prefix = tmp[0] suffix =","URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib","ssl import csv import time import requests import json import csv from rdflib","float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \"\" and ln !=","import csv import time import requests import json import csv from rdflib import","== \"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj = db[db_uri]","elif prefix == \"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix ==","labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"]))","Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in","all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\"","label[\"value\"] if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in value:","stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stmt = (subject,","all.add(stmt) # label if \"labels\" in obj and \"ja\" in obj[\"labels\"]: stmt =","ln ln = ln_map[ln] if len(ln) > 20: continue # ln = obj[\"uri\"].split(\":\")[1]",", db_uri) continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt","obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in obj and \"ja\" in obj[\"descriptions\"]:","\"point\" in obj and prefix == \"place\": value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数","label in labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in","if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt =","URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix","as f: result = json.load(f) uris = [] for obj in result: fields","import json import glob import yaml import sys import urllib import ssl import","= (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for","Graph() with open(\"data/dict.json\") as f: ln_map = json.load(f) st_path = \"../data/index.json\" with open(st_path)","import shutil import os import json import glob import yaml import sys import","obj and \"ja\" in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) #","(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\"))","all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in obj and \"ja\" in","os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as","= wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki","###### obj = db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in","RDFS, FOAF, XSD from rdflib import Namespace all = Graph() with open(\"data/dict.json\") as","f: ln_map = json.load(f) st_path = \"../data/index.json\" with open(st_path) as f: result =","all.add(stmt) elif prefix == \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix","all.add(stmt) ''' # 正規化前 if ln_org != \"\" and ln != ln_org: stmt","json.load(f) uris = [] for obj in result: fields = [\"spatial\", \"agential\"] for","= \"place:\"+value if uri not in uris: uris.append(uri) for uri in uris: print(uri)","value or \"www.wikidata.org\" in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報","# 正規化前 if ln_org != \"\" and ln != ln_org: stmt = (subject,","fields = [\"spatial\", \"agential\"] for field in fields: values = obj[field] for value","\"lat\" : float(value[0]), \"long\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org !=","= obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value = label[\"value\"] if \"http://dbpedia.org\" in value","\"\" if ln in ln_map: ln_org = ln ln = ln_map[ln] if len(ln)","import csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF,","wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki =","in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if label[\"lang\"] == \"ja\":","in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt = (subject, URIRef(\"http://schema.org/description\"),","print(\"not\" , db_uri) continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\":","URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif","\") # addGeo関数 geoUri = addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1]) }) stmt","(subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label","if \"point\" in obj and prefix == \"place\": value = obj[\"point\"][\"value\"].split(\" \") #","\"spatial\": uri = \"place:\"+value if uri not in uris: uris.append(uri) for uri in","\"ja\" in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if","###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\"))","places[suffix] = { \"lat\" : float(value[0]), \"long\": float(value[1]) } all.add(stmt) ''' # 正規化前","obj in result: fields = [\"spatial\", \"agential\"] for field in fields: values =","db: print(\"not\" , db_uri) continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix ==","float(value[0]), \"long\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \"\" and","value in values: uri = \"chname:\"+value if field == \"spatial\": uri = \"place:\"+value","db_uri) continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt =","prefix == \"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\":","= ln_map[ln] if len(ln) > 20: continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path","{} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt","json.load(f) st_path = \"../data/index.json\" with open(st_path) as f: result = json.load(f) uris =","with open(st_path) as f: result = json.load(f) uris = [] for obj in","\"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels =","RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt)","# ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path):","import requests import json import csv from rdflib import URIRef, BNode, Literal, Graph","Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace","as f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt)","if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in","\"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if label[\"lang\"] ==","= suffix ln_org = \"\" if ln in ln_map: ln_org = ln ln","result: fields = [\"spatial\", \"agential\"] for field in fields: values = obj[field] for","as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki =","\"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt)","ln_map[ln] if len(ln) > 20: continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path =","URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif","prefix == \"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj =","if ln_org != \"\" and ln != ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org))","(subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for","all = Graph() with open(\"data/dict.json\") as f: ln_map = json.load(f) st_path = \"../data/index.json\"","= json.load(f) uris = [] for obj in result: fields = [\"spatial\", \"agential\"]","in obj and \"ja\" in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt)","= (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in","in fields: values = obj[field] for value in values: uri = \"chname:\"+value if","from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF,","wiki = {} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if","URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif","open(wiki_path) as f: wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in","db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki = {} if","\"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in value: stmt =","URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt)","stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels =","if field == \"spatial\": uri = \"place:\"+value if uri not in uris: uris.append(uri)","uri not in uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\":\")","''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f:","Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if \"labels\" in obj and \"ja\" in obj[\"labels\"]:","obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri = addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1]) })","uri = \"place:\"+value if uri not in uris: uris.append(uri) for uri in uris:","elif prefix == \"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix ==","''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki = {}","\"\" and ln != ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path =","\"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix == \"org\": stmt =","== \"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\": stmt","as f: ln_map = json.load(f) st_path = \"../data/index.json\" with open(st_path) as f: result","wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) #","and \"ja\" in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label","!= \"\" and ln != ln_org: stmt = (subject, URIRef(\"http://schema.org/name\"), Literal(ln_org)) all.add(stmt) path","# ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt = (subject, RDF.type,","glob import yaml import sys import urllib import ssl import csv import time","= \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db: print(\"not\" , db_uri) continue # ######","= {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs","subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix == \"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt)","= (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if \"labels\" in obj and","URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif","f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj","for label in labels: if label[\"lang\"] == \"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"]))","obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if label[\"lang\"] == \"ja\": stmt = (subject, RDFS.label,","all.add(stmt) elif prefix == \"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\")) all.add(stmt) elif prefix","prefix == \"place\": value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri = addGeo({ \"lat\"","geoUri = addGeo({ \"lat\" : float(value[0]), \"long\": float(value[1]) }) stmt = (subject, URIRef(\"http://schema.org/geo\"),","geoUri) if suffix not in places: places[suffix] = { \"lat\" : float(value[0]), \"long\":","in result: fields = [\"spatial\", \"agential\"] for field in fields: values = obj[field]","in obj[\"descriptions\"]: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if \"labels\"","field == \"spatial\": uri = \"place:\"+value if uri not in uris: uris.append(uri) for","URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix == \"type\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) #","prefix == \"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\":","open(\"data/dict.json\") as f: ln_map = json.load(f) st_path = \"../data/index.json\" with open(st_path) as f:","if prefix == \"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix ==","all.add(stmt) elif prefix == \"keyword\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Keyword\")) all.add(stmt) elif prefix","for label in labels: value = label[\"value\"] if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\"","URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if","if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value =","obj and prefix == \"place\": value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri =","label in labels: if label[\"lang\"] == \"ja\": stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt)","import sys import urllib import ssl import csv import time import requests import","ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path): with","lang=label[\"lang\"])) all.add(stmt) if \"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels:","open(st_path) as f: result = json.load(f) uris = [] for obj in result:","f: result = json.load(f) uris = [] for obj in result: fields =","\"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt = (subject,","urllib import ssl import csv import time import requests import json import csv","wiki = json.load(f) # sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj =","rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace all = Graph()","\"data/wikidata/\"+ln+\".json\" db = {} wiki = {} if os.path.exists(db_path): with open(db_path) as f:","= (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\" in obj: stmt = (subject, URIRef(\"http://schema.org/image\"),","from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace all =","= \"data/wikidata/\"+ln+\".json\" db = {} wiki = {} if os.path.exists(db_path): with open(db_path) as","= (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\": stmt = (subject, RDF.type,","value: stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \"point\" in","= (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \"point\" in obj and","csv import time import requests import json import csv from rdflib import URIRef,","with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"),","sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if","suffix not in places: places[suffix] = { \"lat\" : float(value[0]), \"long\": float(value[1]) }","= { \"lat\" : float(value[0]), \"long\": float(value[1]) } all.add(stmt) ''' # 正規化前 if","位置情報 ''' if \"point\" in obj and prefix == \"place\": value = obj[\"point\"][\"value\"].split(\"","in obj: stmt = (subject, URIRef(\"http://schema.org/image\"), URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels","\"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\": stmt =","values = obj[field] for value in values: uri = \"chname:\"+value if field ==","= \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki = {} if os.path.exists(db_path):","for value in values: uri = \"chname:\"+value if field == \"spatial\": uri =","db_uri not in db: print(\"not\" , db_uri) continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln)","== \"chname\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Agent\")) all.add(stmt) elif prefix == \"time\": stmt","and prefix == \"place\": value = obj[\"point\"][\"value\"].split(\" \") # addGeo関数 geoUri = addGeo({","sys import urllib import ssl import csv import time import requests import json","(subject, URIRef(\"http://schema.org/geo\"), geoUri) if suffix not in places: places[suffix] = { \"lat\" :","= wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in obj and \"ja\" in obj[\"descriptions\"]: stmt","in db: print(\"not\" , db_uri) continue # ###### subject = URIRef(\"https://shibusawa-dlab.github.io/lab1/api/\"+prefix+\"/\"+ln) if prefix","\"long\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \"\" and ln","\"chname:\"+value if field == \"spatial\": uri = \"place:\"+value if uri not in uris:","stmt = (subject, RDFS.label, Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"]","URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \"point\" in obj and prefix ==","continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki = {} if","== \"spatial\": uri = \"place:\"+value if uri not in uris: uris.append(uri) for uri","all.add(stmt) elif prefix == \"time\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix","prefix == \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\":","> 20: continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path = \"data/wikidata/\"+ln+\".json\" wiki =","Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace all","= (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\")) all.add(stmt) elif prefix == \"keyword\": stmt = (subject, RDF.type,","json import glob import yaml import sys import urllib import ssl import csv","json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db: print(\"not\" , db_uri) continue","wiki[\"entities\"][wiki_url.split(\"/\")[-1]] # description if \"descriptions\" in obj and \"ja\" in obj[\"descriptions\"]: stmt =","tmp[0] suffix = tmp[1] ln = suffix ln_org = \"\" if ln in","\"http://www.w3.org/2002/07/owl#sameAs\" in obj: labels = obj[\"http://www.w3.org/2002/07/owl#sameAs\"] for label in labels: value = label[\"value\"]","os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri","os import json import glob import yaml import sys import urllib import ssl","# ###### obj = db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt) if \"http://dbpedia.org/ontology/thumbnail\"","\"agential\"] for field in fields: values = obj[field] for value in values: uri","obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels: stmt = (subject, URIRef(\"http://schema.org/description\"), Literal(label[\"value\"], lang=label[\"lang\"])) all.add(stmt) if","(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Event\"))","= label[\"value\"] if \"http://dbpedia.org\" in value or \"http://ja.dbpedia.org\" in value or \"www.wikidata.org\" in","field in fields: values = obj[field] for value in values: uri = \"chname:\"+value","Literal(label[\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#comment\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#comment\"] for label in labels:",": float(value[0]), \"long\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \"\"","all.add(stmt) ln = wiki_url.split(\"/\")[-1] ''' db_path = \"data/dbpedia_ja/\"+ln+\".json\" wiki_path = \"data/wikidata/\"+ln+\".json\" db =","= json.load(f) # sameAs stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\"entities\"][wiki_url.split(\"/\")[-1]]","prefix == \"place\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Place\")) all.add(stmt) elif prefix == \"event\":","URIRef(\"https://jpsearch.go.jp/term/type/Type\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\"http://www.w3.org/2002/07/owl#sameAs\"), URIRef(db_uri)) all.add(stmt)","= obj[field] for value in values: uri = \"chname:\"+value if field == \"spatial\":","URIRef(\"http://schema.org/description\"), Literal(obj[\"descriptions\"][\"ja\"][\"value\"], lang=\"ja\")) all.add(stmt) # label if \"labels\" in obj and \"ja\" in","ln_org = \"\" if ln in ln_map: ln_org = ln ln = ln_map[ln]","URIRef(obj[\"http://dbpedia.org/ontology/thumbnail\"][0][\"value\"])) all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels:","wiki = json.load(f) db_uri = \"http://ja.dbpedia.org/resource/\"+ln if db_uri not in db: print(\"not\" ,","import ssl import csv import time import requests import json import csv from","= \"data/wikidata/\"+ln+\".json\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki =","all.add(stmt) if \"http://www.w3.org/2000/01/rdf-schema#label\" in obj: labels = obj[\"http://www.w3.org/2000/01/rdf-schema#label\"] for label in labels: if"],"string":"[\n \"suffix = tmp[1] ln = suffix ln_org = \\\"\\\" if ln in ln_map:\",\n \"wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki = {} if os.path.exists(db_path): with open(db_path)\",\n \"{} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with\",\n \"RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in\",\n \"label if \\\"labels\\\" in obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label,\",\n \"prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org = \\\"\\\" if\",\n \"as f: wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db:\",\n \"URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif\",\n \"places: places[suffix] = { \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) ''' #\",\n \"# 位置情報 ''' if \\\"point\\\" in obj and prefix == \\\"place\\\": value =\",\n \"URIRef(value)) all.add(stmt) # 位置情報 ''' if \\\"point\\\" in obj and prefix == \\\"place\\\":\",\n \"[] for obj in result: fields = [\\\"spatial\\\", \\\"agential\\\"] for field in fields:\",\n \"if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if label[\\\"lang\\\"]\",\n \"in ln_map: ln_org = ln ln = ln_map[ln] if len(ln) > 20: continue\",\n \"elif prefix == \\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix ==\",\n \"(subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"),\",\n \"= Graph() with open(\\\"data/dict.json\\\") as f: ln_map = json.load(f) st_path = \\\"../data/index.json\\\" with\",\n \"RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\"\",\n \"BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import\",\n \"in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \\\"point\\\"\",\n \"label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj:\",\n \"in uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\\\":\\\") prefix =\",\n \"ln_map = json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path) as f: result = json.load(f)\",\n \"all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt\",\n \"open(wiki_path) as f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url))\",\n \"in values: uri = \\\"chname:\\\"+value if field == \\\"spatial\\\": uri = \\\"place:\\\"+value if\",\n \"Namespace all = Graph() with open(\\\"data/dict.json\\\") as f: ln_map = json.load(f) st_path =\",\n \"= (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"]\",\n \"= (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path = \\\"data/all.json\\\" all.serialize(destination=path, format='json-ld') all.serialize(destination=path.replace(\\\".json\\\", \\\".rdf\\\"), format='pretty-xml')\",\n \"ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path = \\\"data/all.json\\\" all.serialize(destination=path, format='json-ld') all.serialize(destination=path.replace(\\\".json\\\",\",\n \"prefix == \\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\":\",\n \"description if \\\"descriptions\\\" in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"),\",\n \"obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\"\",\n \"import urllib import ssl import csv import time import requests import json import\",\n \"(subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\" in obj and \\\"ja\\\"\",\n \"yaml import sys import urllib import ssl import csv import time import requests\",\n \"csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS,\",\n \"if label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in\",\n \"= {} wiki = {} if os.path.exists(db_path): with open(db_path) as f: db =\",\n \"stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\"\",\n \"in labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if\",\n \"obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or\",\n \"= [] for obj in result: fields = [\\\"spatial\\\", \\\"agential\\\"] for field in\",\n \"== \\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\": stmt\",\n \"\\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\": stmt =\",\n \"elif prefix == \\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj\",\n \"obj[field] for value in values: uri = \\\"chname:\\\"+value if field == \\\"spatial\\\": uri\",\n \"\\\"labels\\\" in obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt)\",\n \"== \\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels\",\n \"} all.add(stmt) ''' # 正規化前 if ln_org != \\\"\\\" and ln != ln_org:\",\n \"if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in value: stmt\",\n \"\\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix\",\n \"= json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri =\",\n \"value or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"),\",\n \"db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db: print(\\\"not\\\" , db_uri) continue #\",\n \"XSD from rdflib import Namespace all = Graph() with open(\\\"data/dict.json\\\") as f: ln_map\",\n \"suffix ln_org = \\\"\\\" if ln in ln_map: ln_org = ln ln =\",\n \"= \\\"chname:\\\"+value if field == \\\"spatial\\\": uri = \\\"place:\\\"+value if uri not in\",\n \"URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in\",\n \"= uri.split(\\\":\\\") prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org =\",\n \"= obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri = addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1])\",\n \"stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"]\",\n \"if ln in ln_map: ln_org = ln ln = ln_map[ln] if len(ln) >\",\n \"or \\\"www.wikidata.org\\\" in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 '''\",\n \"in places: places[suffix] = { \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) '''\",\n \"ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {}\",\n \"stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\" in obj\",\n \": float(value[0]), \\\"long\\\": float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not\",\n \"import Namespace all = Graph() with open(\\\"data/dict.json\\\") as f: ln_map = json.load(f) st_path\",\n \"== \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri = addGeo({ \\\"lat\\\" :\",\n \"or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value))\",\n \"(subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"]))\",\n \"ln_map: ln_org = ln ln = ln_map[ln] if len(ln) > 20: continue #\",\n \"tmp = uri.split(\\\":\\\") prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org\",\n \"labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in value or\",\n \"{} wiki = {} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f)\",\n \"# description if \\\"descriptions\\\" in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject,\",\n \"= json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path) as f: result = json.load(f) uris\",\n \"# label if \\\"labels\\\" in obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject,\",\n \"\\\"long\\\": float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in places:\",\n \"URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in places: places[suffix] = { \\\"lat\\\" : float(value[0]),\",\n \"f: wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db: print(\\\"not\\\"\",\n \"shutil import os import json import glob import yaml import sys import urllib\",\n \"time import requests import json import csv from rdflib import URIRef, BNode, Literal,\",\n \"if db_uri not in db: print(\\\"not\\\" , db_uri) continue # ###### subject =\",\n \"== \\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\": stmt\",\n \"open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki\",\n \"RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt)\",\n \"import RDF, RDFS, FOAF, XSD from rdflib import Namespace all = Graph() with\",\n \"json import csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import\",\n \"f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f)\",\n \"import json import csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace\",\n \"RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt)\",\n \"with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f:\",\n \"stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\": stmt = (subject,\",\n \"[\\\"spatial\\\", \\\"agential\\\"] for field in fields: values = obj[field] for value in values:\",\n \"(subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path =\",\n \"stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \\\"point\\\" in obj\",\n \"\\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\": stmt =\",\n \"in labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in value\",\n \"= (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\": stmt = (subject, RDF.type,\",\n \"''' # 正規化前 if ln_org != \\\"\\\" and ln != ln_org: stmt =\",\n \"ln = suffix ln_org = \\\"\\\" if ln in ln_map: ln_org = ln\",\n \"\\\"place:\\\"+value if uri not in uris: uris.append(uri) for uri in uris: print(uri) tmp\",\n \"if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if\",\n \"len(ln) > 20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki\",\n \"(subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in obj\",\n \"= (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject,\",\n \"lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\" in obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt\",\n \"json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln\",\n \"uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\\\":\\\") prefix = tmp[0]\",\n \"not in uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\\\":\\\") prefix\",\n \"{ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org\",\n \"stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\": stmt = (subject,\",\n \"result = json.load(f) uris = [] for obj in result: fields = [\\\"spatial\\\",\",\n \"float(value[0]), \\\"long\\\": float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in\",\n \"obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path =\",\n \"uri = \\\"chname:\\\"+value if field == \\\"spatial\\\": uri = \\\"place:\\\"+value if uri not\",\n \"value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri = addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\":\",\n \"正規化前 if ln_org != \\\"\\\" and ln != ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"),\",\n \"= \\\"../data/index.json\\\" with open(st_path) as f: result = json.load(f) uris = [] for\",\n \"= (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\": stmt = (subject, RDF.type,\",\n \"obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as\",\n \"\\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj = db[db_uri] stmt\",\n \"\\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj:\",\n \"''' if \\\"point\\\" in obj and prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\")\",\n \"json.load(f) # sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] #\",\n \"with open(wiki_path) as f: wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not\",\n \"= \\\"\\\" if ln in ln_map: ln_org = ln ln = ln_map[ln] if\",\n \"\\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri = addGeo({ \\\"lat\\\" : float(value[0]),\",\n \"URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in obj and \\\"ja\\\"\",\n \"wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki\",\n \"obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels =\",\n \"RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt)\",\n \"obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln =\",\n \"for label in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\"\",\n \"all.add(stmt) # 位置情報 ''' if \\\"point\\\" in obj and prefix == \\\"place\\\": value\",\n \"= addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri)\",\n \"= tmp[1] ln = suffix ln_org = \\\"\\\" if ln in ln_map: ln_org\",\n \"stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\"\",\n \"RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri))\",\n \"in value or \\\"www.wikidata.org\\\" in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) #\",\n \"= obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path)\",\n \"stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\": stmt = (subject,\",\n \"in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value = label[\\\"value\\\"] if\",\n \"if \\\"descriptions\\\" in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"],\",\n \"addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if\",\n \"rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD\",\n \"= (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for\",\n \"all.add(stmt) elif prefix == \\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ######\",\n \"uri.split(\\\":\\\") prefix = tmp[0] suffix = tmp[1] ln = suffix ln_org = \\\"\\\"\",\n \"in value or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in value: stmt = (subject,\",\n \"and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1]\",\n \"in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path\",\n \"continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt = (subject,\",\n \"= obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt)\",\n \"elif prefix == \\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix ==\",\n \"for field in fields: values = obj[field] for value in values: uri =\",\n \"if len(ln) > 20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\"\",\n \"ln = ln_map[ln] if len(ln) > 20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] '''\",\n \"obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"],\",\n \"= (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in places: places[suffix] = { \\\"lat\\\"\",\n \"= tmp[0] suffix = tmp[1] ln = suffix ln_org = \\\"\\\" if ln\",\n \"ln_org != \\\"\\\" and ln != ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt)\",\n \"= URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif\",\n \"in uris: print(uri) tmp = uri.split(\\\":\\\") prefix = tmp[0] suffix = tmp[1] ln\",\n \"and ln != ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path = \\\"data/all.json\\\"\",\n \"\\\"../data/index.json\\\" with open(st_path) as f: result = json.load(f) uris = [] for obj\",\n \"import os import json import glob import yaml import sys import urllib import\",\n \"uris = [] for obj in result: fields = [\\\"spatial\\\", \\\"agential\\\"] for field\",\n \"with open(\\\"data/dict.json\\\") as f: ln_map = json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path) as\",\n \"= (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\": stmt = (subject, RDF.type,\",\n \"FOAF, XSD from rdflib import Namespace all = Graph() with open(\\\"data/dict.json\\\") as f:\",\n \"print(uri) tmp = uri.split(\\\":\\\") prefix = tmp[0] suffix = tmp[1] ln = suffix\",\n \"fields: values = obj[field] for value in values: uri = \\\"chname:\\\"+value if field\",\n \"\\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki = {} if os.path.exists(db_path): with\",\n \"= (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path\",\n \"import yaml import sys import urllib import ssl import csv import time import\",\n \"RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt)\",\n \"stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in places: places[suffix] = {\",\n \"addGeo関数 geoUri = addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }) stmt = (subject,\",\n \"stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\": stmt = (subject,\",\n \"all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value\",\n \"}) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in places: places[suffix] =\",\n \"(subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\"))\",\n \"import glob import yaml import sys import urllib import ssl import csv import\",\n \"db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt =\",\n \"\\\"descriptions\\\" in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\"))\",\n \"uri in uris: print(uri) tmp = uri.split(\\\":\\\") prefix = tmp[0] suffix = tmp[1]\",\n \"\\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db: print(\\\"not\\\" , db_uri) continue # ###### subject\",\n \"(subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\"))\",\n \"all.add(stmt) elif prefix == \\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix\",\n \"if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path)\",\n \"URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label\",\n \"os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt = (subject,\",\n \"== \\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\": stmt\",\n \"value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\"\",\n \"= json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db: print(\\\"not\\\" , db_uri)\",\n \"if \\\"labels\\\" in obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"]))\",\n \"obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt\",\n \"stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\": stmt = (subject,\",\n \"(subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label\",\n \"rdflib import Namespace all = Graph() with open(\\\"data/dict.json\\\") as f: ln_map = json.load(f)\",\n \"ln_org = ln ln = ln_map[ln] if len(ln) > 20: continue # ln\",\n \"Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db\",\n \"ln != ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path = \\\"data/all.json\\\" all.serialize(destination=path,\",\n \"labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels\",\n \"obj = db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj:\",\n \"\\\"www.wikidata.org\\\" in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if\",\n \"= [\\\"spatial\\\", \\\"agential\\\"] for field in fields: values = obj[field] for value in\",\n \"stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path = \\\"data/all.json\\\" all.serialize(destination=path, format='json-ld') all.serialize(destination=path.replace(\\\".json\\\", \\\".rdf\\\"),\",\n \"requests import json import csv from rdflib import URIRef, BNode, Literal, Graph from\",\n \"not in db: print(\\\"not\\\" , db_uri) continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if\",\n \"in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj:\",\n \"RDF, RDFS, FOAF, XSD from rdflib import Namespace all = Graph() with open(\\\"data/dict.json\\\")\",\n \"\\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] '''\",\n \"all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if\",\n \"prefix == \\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\":\",\n \"st_path = \\\"../data/index.json\\\" with open(st_path) as f: result = json.load(f) uris = []\",\n \"\\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f)\",\n \"if suffix not in places: places[suffix] = { \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1])\",\n \"for obj in result: fields = [\\\"spatial\\\", \\\"agential\\\"] for field in fields: values\",\n \"stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject,\",\n \"\\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\": stmt =\",\n \"uris: print(uri) tmp = uri.split(\\\":\\\") prefix = tmp[0] suffix = tmp[1] ln =\",\n \"= (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\": stmt = (subject, RDF.type,\",\n \"import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from\",\n \"= db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt\",\n \"== \\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\": stmt\",\n \"labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"\",\n \"label in labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in\",\n \"from rdflib import Namespace all = Graph() with open(\\\"data/dict.json\\\") as f: ln_map =\",\n \"RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt)\",\n \"float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in places: places[suffix]\",\n \"in obj and prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri\",\n \"labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in\",\n \"stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj = db[db_uri] stmt =\",\n \"URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in obj and\",\n \"(subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\"))\",\n \"import time import requests import json import csv from rdflib import URIRef, BNode,\",\n \"(subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\"))\",\n \"obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\" in\",\n \"# addGeo関数 geoUri = addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }) stmt =\",\n \"if uri not in uris: uris.append(uri) for uri in uris: print(uri) tmp =\",\n \"db = {} wiki = {} if os.path.exists(db_path): with open(db_path) as f: db\",\n \"not in places: places[suffix] = { \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt)\",\n \"tmp[1] ln = suffix ln_org = \\\"\\\" if ln in ln_map: ln_org =\",\n \"20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {}\",\n \"(subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \\\"point\\\" in obj and prefix\",\n \"# sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description\",\n \"= obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject,\",\n \"!= ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path = \\\"data/all.json\\\" all.serialize(destination=path, format='json-ld')\",\n \"labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt =\",\n \"db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri\",\n \"elif prefix == \\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix ==\",\n \"values: uri = \\\"chname:\\\"+value if field == \\\"spatial\\\": uri = \\\"place:\\\"+value if uri\",\n \"in obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt = (subject, RDFS.label, Literal(obj[\\\"labels\\\"][\\\"ja\\\"][\\\"value\\\"])) all.add(stmt) ln\",\n \"uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\\\":\\\") prefix = tmp[0] suffix\",\n \"ln in ln_map: ln_org = ln ln = ln_map[ln] if len(ln) > 20:\",\n \"\\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\": stmt =\",\n \"if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt =\",\n \"= ln ln = ln_map[ln] if len(ln) > 20: continue # ln =\",\n \"= {} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path):\",\n \"for uri in uris: print(uri) tmp = uri.split(\\\":\\\") prefix = tmp[0] suffix =\",\n \"URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib\",\n \"ssl import csv import time import requests import json import csv from rdflib\",\n \"float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \\\"\\\" and ln !=\",\n \"import csv import time import requests import json import csv from rdflib import\",\n \"== \\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj = db[db_uri]\",\n \"elif prefix == \\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix ==\",\n \"labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"]))\",\n \"Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in\",\n \"all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\"\",\n \"label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in value:\",\n \"stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\": stmt = (subject,\",\n \"all.add(stmt) # label if \\\"labels\\\" in obj and \\\"ja\\\" in obj[\\\"labels\\\"]: stmt =\",\n \"ln ln = ln_map[ln] if len(ln) > 20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1]\",\n \", db_uri) continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt\",\n \"obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]:\",\n \"\\\"point\\\" in obj and prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数\",\n \"label in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in\",\n \"if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt =\",\n \"URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix\",\n \"as f: result = json.load(f) uris = [] for obj in result: fields\",\n \"import json import glob import yaml import sys import urllib import ssl import\",\n \"= (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for\",\n \"Graph() with open(\\\"data/dict.json\\\") as f: ln_map = json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path)\",\n \"import shutil import os import json import glob import yaml import sys import\",\n \"obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) #\",\n \"(subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\"))\",\n \"all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in obj and \\\"ja\\\" in\",\n \"os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as\",\n \"= wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki\",\n \"###### obj = db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in\",\n \"RDFS, FOAF, XSD from rdflib import Namespace all = Graph() with open(\\\"data/dict.json\\\") as\",\n \"f: ln_map = json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path) as f: result =\",\n \"all.add(stmt) elif prefix == \\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix\",\n \"all.add(stmt) ''' # 正規化前 if ln_org != \\\"\\\" and ln != ln_org: stmt\",\n \"json.load(f) uris = [] for obj in result: fields = [\\\"spatial\\\", \\\"agential\\\"] for\",\n \"= \\\"place:\\\"+value if uri not in uris: uris.append(uri) for uri in uris: print(uri)\",\n \"value or \\\"www.wikidata.org\\\" in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報\",\n \"# 正規化前 if ln_org != \\\"\\\" and ln != ln_org: stmt = (subject,\",\n \"fields = [\\\"spatial\\\", \\\"agential\\\"] for field in fields: values = obj[field] for value\",\n \"\\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org !=\",\n \"= obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value\",\n \"\\\"\\\" if ln in ln_map: ln_org = ln ln = ln_map[ln] if len(ln)\",\n \"import csv from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF,\",\n \"wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki =\",\n \"in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if label[\\\"lang\\\"] == \\\"ja\\\":\",\n \"in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"),\",\n \"print(\\\"not\\\" , db_uri) continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\":\",\n \"URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif\",\n \"\\\") # addGeo関数 geoUri = addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }) stmt\",\n \"(subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label\",\n \"if \\\"point\\\" in obj and prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") #\",\n \"\\\"spatial\\\": uri = \\\"place:\\\"+value if uri not in uris: uris.append(uri) for uri in\",\n \"\\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if\",\n \"###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\"))\",\n \"places[suffix] = { \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) ''' # 正規化前\",\n \"obj in result: fields = [\\\"spatial\\\", \\\"agential\\\"] for field in fields: values =\",\n \"db: print(\\\"not\\\" , db_uri) continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix ==\",\n \"float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \\\"\\\" and\",\n \"value in values: uri = \\\"chname:\\\"+value if field == \\\"spatial\\\": uri = \\\"place:\\\"+value\",\n \"db_uri) continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt =\",\n \"prefix == \\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\":\",\n \"= ln_map[ln] if len(ln) > 20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path\",\n \"{} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt\",\n \"json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path) as f: result = json.load(f) uris =\",\n \"with open(st_path) as f: result = json.load(f) uris = [] for obj in\",\n \"\\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels =\",\n \"RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt)\",\n \"# ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path):\",\n \"import requests import json import csv from rdflib import URIRef, BNode, Literal, Graph\",\n \"Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace\",\n \"as f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt)\",\n \"if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in\",\n \"\\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if label[\\\"lang\\\"] ==\",\n \"= suffix ln_org = \\\"\\\" if ln in ln_map: ln_org = ln ln\",\n \"result: fields = [\\\"spatial\\\", \\\"agential\\\"] for field in fields: values = obj[field] for\",\n \"as f: db = json.load(f) if os.path.exists(wiki_path): with open(wiki_path) as f: wiki =\",\n \"\\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt)\",\n \"ln_map[ln] if len(ln) > 20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path =\",\n \"URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif\",\n \"prefix == \\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj =\",\n \"if ln_org != \\\"\\\" and ln != ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org))\",\n \"(subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for\",\n \"all = Graph() with open(\\\"data/dict.json\\\") as f: ln_map = json.load(f) st_path = \\\"../data/index.json\\\"\",\n \"= json.load(f) uris = [] for obj in result: fields = [\\\"spatial\\\", \\\"agential\\\"]\",\n \"in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt)\",\n \"= (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in\",\n \"in fields: values = obj[field] for value in values: uri = \\\"chname:\\\"+value if\",\n \"from rdflib import URIRef, BNode, Literal, Graph from rdflib.namespace import RDF, RDFS, FOAF,\",\n \"wiki = {} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if\",\n \"URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif\",\n \"open(wiki_path) as f: wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in\",\n \"db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki = {} if\",\n \"\\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in value: stmt =\",\n \"URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt)\",\n \"stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels =\",\n \"if field == \\\"spatial\\\": uri = \\\"place:\\\"+value if uri not in uris: uris.append(uri)\",\n \"uri not in uris: uris.append(uri) for uri in uris: print(uri) tmp = uri.split(\\\":\\\")\",\n \"''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f:\",\n \"Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\" in obj and \\\"ja\\\" in obj[\\\"labels\\\"]:\",\n \"obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri = addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) })\",\n \"uri = \\\"place:\\\"+value if uri not in uris: uris.append(uri) for uri in uris:\",\n \"elif prefix == \\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix ==\",\n \"''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki = {}\",\n \"\\\"\\\" and ln != ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path =\",\n \"\\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix == \\\"org\\\": stmt =\",\n \"== \\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\": stmt\",\n \"as f: ln_map = json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path) as f: result\",\n \"wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) #\",\n \"and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label\",\n \"!= \\\"\\\" and ln != ln_org: stmt = (subject, URIRef(\\\"http://schema.org/name\\\"), Literal(ln_org)) all.add(stmt) path\",\n \"# ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt = (subject, RDF.type,\",\n \"glob import yaml import sys import urllib import ssl import csv import time\",\n \"= \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db: print(\\\"not\\\" , db_uri) continue # ######\",\n \"= {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) # sameAs\",\n \"subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix == \\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt)\",\n \"= (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\" in obj and\",\n \"URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix == \\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif\",\n \"f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj\",\n \"for label in labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"]))\",\n \"obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject, RDFS.label,\",\n \"all.add(stmt) elif prefix == \\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\")) all.add(stmt) elif prefix\",\n \"prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri = addGeo({ \\\"lat\\\"\",\n \"geoUri = addGeo({ \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }) stmt = (subject, URIRef(\\\"http://schema.org/geo\\\"),\",\n \"geoUri) if suffix not in places: places[suffix] = { \\\"lat\\\" : float(value[0]), \\\"long\\\":\",\n \"in result: fields = [\\\"spatial\\\", \\\"agential\\\"] for field in fields: values = obj[field]\",\n \"in obj[\\\"descriptions\\\"]: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\"\",\n \"field == \\\"spatial\\\": uri = \\\"place:\\\"+value if uri not in uris: uris.append(uri) for\",\n \"URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix == \\\"type\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) #\",\n \"prefix == \\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\":\",\n \"open(\\\"data/dict.json\\\") as f: ln_map = json.load(f) st_path = \\\"../data/index.json\\\" with open(st_path) as f:\",\n \"if prefix == \\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix ==\",\n \"all.add(stmt) elif prefix == \\\"keyword\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Keyword\\\")) all.add(stmt) elif prefix\",\n \"for label in labels: value = label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\"\",\n \"URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if\",\n \"if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value =\",\n \"obj and prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri =\",\n \"label in labels: if label[\\\"lang\\\"] == \\\"ja\\\": stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt)\",\n \"import sys import urllib import ssl import csv import time import requests import\",\n \"ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path): with\",\n \"lang=label[\\\"lang\\\"])) all.add(stmt) if \\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels:\",\n \"open(st_path) as f: result = json.load(f) uris = [] for obj in result:\",\n \"f: result = json.load(f) uris = [] for obj in result: fields =\",\n \"\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt = (subject,\",\n \"urllib import ssl import csv import time import requests import json import csv\",\n \"wiki = json.load(f) # sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj =\",\n \"rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace all = Graph()\",\n \"\\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki = {} if os.path.exists(db_path): with open(db_path) as f:\",\n \"= (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\" in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"),\",\n \"from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace all =\",\n \"= \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki = {} if os.path.exists(db_path): with open(db_path) as\",\n \"= (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\": stmt = (subject, RDF.type,\",\n \"value: stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \\\"point\\\" in\",\n \"= (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \\\"point\\\" in obj and\",\n \"csv import time import requests import json import csv from rdflib import URIRef,\",\n \"with open(wiki_path) as f: wiki = json.load(f) # sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"),\",\n \"sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if\",\n \"suffix not in places: places[suffix] = { \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) }\",\n \"= { \\\"lat\\\" : float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) ''' # 正規化前 if\",\n \"位置情報 ''' if \\\"point\\\" in obj and prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\"\",\n \"in obj: stmt = (subject, URIRef(\\\"http://schema.org/image\\\"), URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels\",\n \"\\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\": stmt =\",\n \"values = obj[field] for value in values: uri = \\\"chname:\\\"+value if field ==\",\n \"= \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db = {} wiki = {} if os.path.exists(db_path):\",\n \"for value in values: uri = \\\"chname:\\\"+value if field == \\\"spatial\\\": uri =\",\n \"db_uri not in db: print(\\\"not\\\" , db_uri) continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln)\",\n \"== \\\"chname\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Agent\\\")) all.add(stmt) elif prefix == \\\"time\\\": stmt\",\n \"and prefix == \\\"place\\\": value = obj[\\\"point\\\"][\\\"value\\\"].split(\\\" \\\") # addGeo関数 geoUri = addGeo({\",\n \"sys import urllib import ssl import csv import time import requests import json\",\n \"(subject, URIRef(\\\"http://schema.org/geo\\\"), geoUri) if suffix not in places: places[suffix] = { \\\"lat\\\" :\",\n \"= wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt\",\n \"in db: print(\\\"not\\\" , db_uri) continue # ###### subject = URIRef(\\\"https://shibusawa-dlab.github.io/lab1/api/\\\"+prefix+\\\"/\\\"+ln) if prefix\",\n \"\\\"long\\\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \\\"\\\" and ln\",\n \"\\\"chname:\\\"+value if field == \\\"spatial\\\": uri = \\\"place:\\\"+value if uri not in uris:\",\n \"stmt = (subject, RDFS.label, Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"]\",\n \"URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(value)) all.add(stmt) # 位置情報 ''' if \\\"point\\\" in obj and prefix ==\",\n \"continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if\",\n \"== \\\"spatial\\\": uri = \\\"place:\\\"+value if uri not in uris: uris.append(uri) for uri\",\n \"all.add(stmt) elif prefix == \\\"time\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Time\\\")) all.add(stmt) elif prefix\",\n \"prefix == \\\"org\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\":\",\n \"> 20: continue # ln = obj[\\\"uri\\\"].split(\\\":\\\")[1] ''' wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki =\",\n \"Graph from rdflib.namespace import RDF, RDFS, FOAF, XSD from rdflib import Namespace all\",\n \"= (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Organization\\\")) all.add(stmt) elif prefix == \\\"keyword\\\": stmt = (subject, RDF.type,\",\n \"json import glob import yaml import sys import urllib import ssl import csv\",\n \"json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db: print(\\\"not\\\" , db_uri) continue\",\n \"wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]] # description if \\\"descriptions\\\" in obj and \\\"ja\\\" in obj[\\\"descriptions\\\"]: stmt =\",\n \"tmp[0] suffix = tmp[1] ln = suffix ln_org = \\\"\\\" if ln in\",\n \"\\\"http://www.w3.org/2002/07/owl#sameAs\\\" in obj: labels = obj[\\\"http://www.w3.org/2002/07/owl#sameAs\\\"] for label in labels: value = label[\\\"value\\\"]\",\n \"os.path.exists(wiki_path): with open(wiki_path) as f: wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri\",\n \"os import json import glob import yaml import sys import urllib import ssl\",\n \"# ###### obj = db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt) if \\\"http://dbpedia.org/ontology/thumbnail\\\"\",\n \"\\\"agential\\\"] for field in fields: values = obj[field] for value in values: uri\",\n \"obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels: stmt = (subject, URIRef(\\\"http://schema.org/description\\\"), Literal(label[\\\"value\\\"], lang=label[\\\"lang\\\"])) all.add(stmt) if\",\n \"(subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Event\\\"))\",\n \"= label[\\\"value\\\"] if \\\"http://dbpedia.org\\\" in value or \\\"http://ja.dbpedia.org\\\" in value or \\\"www.wikidata.org\\\" in\",\n \"field in fields: values = obj[field] for value in values: uri = \\\"chname:\\\"+value\",\n \"Literal(label[\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#comment\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#comment\\\"] for label in labels:\",\n \": float(value[0]), \\\"long\\\": float(value[1]) } all.add(stmt) ''' # 正規化前 if ln_org != \\\"\\\"\",\n \"all.add(stmt) ln = wiki_url.split(\\\"/\\\")[-1] ''' db_path = \\\"data/dbpedia_ja/\\\"+ln+\\\".json\\\" wiki_path = \\\"data/wikidata/\\\"+ln+\\\".json\\\" db =\",\n \"= json.load(f) # sameAs stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(wiki_url)) all.add(stmt) obj = wiki[\\\"entities\\\"][wiki_url.split(\\\"/\\\")[-1]]\",\n \"prefix == \\\"place\\\": stmt = (subject, RDF.type, URIRef(\\\"https://jpsearch.go.jp/term/type/Place\\\")) all.add(stmt) elif prefix == \\\"event\\\":\",\n \"URIRef(\\\"https://jpsearch.go.jp/term/type/Type\\\")) all.add(stmt) # ###### obj = db[db_uri] stmt = (subject, URIRef(\\\"http://www.w3.org/2002/07/owl#sameAs\\\"), URIRef(db_uri)) all.add(stmt)\",\n \"= obj[field] for value in values: uri = \\\"chname:\\\"+value if field == \\\"spatial\\\":\",\n \"URIRef(\\\"http://schema.org/description\\\"), Literal(obj[\\\"descriptions\\\"][\\\"ja\\\"][\\\"value\\\"], lang=\\\"ja\\\")) all.add(stmt) # label if \\\"labels\\\" in obj and \\\"ja\\\" in\",\n \"ln_org = \\\"\\\" if ln in ln_map: ln_org = ln ln = ln_map[ln]\",\n \"URIRef(obj[\\\"http://dbpedia.org/ontology/thumbnail\\\"][0][\\\"value\\\"])) all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels:\",\n \"wiki = json.load(f) db_uri = \\\"http://ja.dbpedia.org/resource/\\\"+ln if db_uri not in db: print(\\\"not\\\" ,\",\n \"import ssl import csv import time import requests import json import csv from\",\n \"= \\\"data/wikidata/\\\"+ln+\\\".json\\\" wiki = {} if os.path.exists(wiki_path): with open(wiki_path) as f: wiki =\",\n \"all.add(stmt) if \\\"http://www.w3.org/2000/01/rdf-schema#label\\\" in obj: labels = obj[\\\"http://www.w3.org/2000/01/rdf-schema#label\\\"] for label in labels: if\"\n]","isConversational":false}}},{"rowIdx":83,"cells":{"ngram":{"kind":"list like","value":["configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print')","bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i in","@patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks if we","} open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i:","[0, 1, 2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4,","@patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks if","print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks if we can perform a whole","= [{'id': i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for","import * import bootloader_read_config from commands import * import sys import json class","[None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in","= \"test.py -p /dev/ttyUSB0 --all\".split() # The first two board answers the ping","sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn,","open_conn, write_command, write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0 0 1 2\".split() configs =","open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i]","range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) } open_conn.return_value =","from msgpack import * import bootloader_read_config from commands import * import sys import","object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i","for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def","write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) } open_conn.return_value = object()","{ i: packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value,","discovery. \"\"\" sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split() # The first two board","-p /dev/ttyUSB0 --all\".split() # The first two board answers the ping board_answers =","mock import * from msgpack import * import bootloader_read_config from commands import *","print_mock, open_conn, write_command, write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0 0 1 2\".split() configs","first two board answers the ping board_answers = [(b'', [0], i) for i","bootloader_read_config from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command')","= {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command')","packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value, encode_ping(), list(range(1, 128)))","if we can perform a whole network discovery. \"\"\" sys.argv = \"test.py -p","/dev/ttyUSB0 --all\".split() # The first two board answers the ping board_answers = [(b'',","indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry,","sys.argv = \"test.py -p /dev/ttyUSB0 0 1 2\".split() configs = [{'id': i} for","write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i in range(3)}","2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection')","= [(b'', [0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value =","* except ImportError: from mock import * from msgpack import * import bootloader_read_config","@patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks if we can","we can perform a whole network discovery. \"\"\" sys.argv = \"test.py -p /dev/ttyUSB0","try: from unittest.mock import * except ImportError: from mock import * from msgpack","i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i:","range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs =","\"\"\" sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split() # The first two board answers","write_command_retry, open_conn): \"\"\" Checks if we can perform a whole network discovery. \"\"\"","= iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in range(1, 3)","@patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\"","commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print')","i) for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value =","encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs,","unittest.mock import * except ImportError: from mock import * from msgpack import *","in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id':","--all\".split() # The first two board answers the ping board_answers = [(b'', [0],","except ImportError: from mock import * from msgpack import * import bootloader_read_config from","perform a whole network discovery. \"\"\" sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split() #","1 2\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value = {","+ [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i","ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv =","class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv","import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command,","def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks if we can perform","ImportError: from mock import * from msgpack import * import bootloader_read_config from commands","network discovery. \"\"\" sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split() # The first two","[{'id': i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i","two board answers the ping board_answers = [(b'', [0], i) for i in","a whole network discovery. \"\"\" sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split() # The","2\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value = { i:","answers the ping board_answers = [(b'', [0], i) for i in range(1, 3)]","the ping board_answers = [(b'', [0], i) for i in range(1, 3)] +","unittest try: from unittest.mock import * except ImportError: from mock import * from","= { i: packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main()","0 1 2\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value =","test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks if we can perform a","iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in range(1, 3) }","from mock import * from msgpack import * import bootloader_read_config from commands import","read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in range(1,","i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value, encode_ping(), list(range(1,","{i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams')","@patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0","msgpack import * import bootloader_read_config from commands import * import sys import json","i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2])","can perform a whole network discovery. \"\"\" sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split()","packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0,","sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn):","@patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks","* import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self,","i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in","-p /dev/ttyUSB0 0 1 2\".split() configs = [{'id': i} for i in range(3)]","The first two board answers the ping board_answers = [(b'', [0], i) for","sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split() # The first two board answers the","i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) }","print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command,","write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0 0 1 2\".split() configs = [{'id': i}","/dev/ttyUSB0 0 1 2\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value","# The first two board answers the ping board_answers = [(b'', [0], i)","@patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \"test.py","import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock,","import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def","board_answers = [(b'', [0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value","\"test.py -p /dev/ttyUSB0 --all\".split() # The first two board answers the ping board_answers","for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = {","* from msgpack import * import bootloader_read_config from commands import * import sys","read_can_datagram, write_command, write_command_retry, open_conn): \"\"\" Checks if we can perform a whole network","from unittest.mock import * except ImportError: from mock import * from msgpack import","\"\"\" Checks if we can perform a whole network discovery. \"\"\" sys.argv =","whole network discovery. \"\"\" sys.argv = \"test.py -p /dev/ttyUSB0 --all\".split() # The first","from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection')","range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram,","in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs","Checks if we can perform a whole network discovery. \"\"\" sys.argv = \"test.py","import * from msgpack import * import bootloader_read_config from commands import * import","write_command_retry.return_value = { i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main()","= object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for","1, 2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True))","i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self,","import bootloader_read_config from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry')","for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3)","configs = [{'id': i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i])","ping board_answers = [(b'', [0], i) for i in range(1, 3)] + [None]","i: packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(),","= \"test.py -p /dev/ttyUSB0 0 1 2\".split() configs = [{'id': i} for i","[0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value","open_conn): \"\"\" Checks if we can perform a whole network discovery. \"\"\" sys.argv","3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for","@patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0 0","import * except ImportError: from mock import * from msgpack import * import","* import bootloader_read_config from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase):","[(b'', [0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers)","@patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \"test.py -p","for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1,","range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i})","\"test.py -p /dev/ttyUSB0 0 1 2\".split() configs = [{'id': i} for i in","import unittest try: from unittest.mock import * except ImportError: from mock import *","in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) } open_conn.return_value","in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock,","write_command, write_command_retry, open_conn): \"\"\" Checks if we can perform a whole network discovery.","all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry')","def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0 0 1","write_command, write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0 0 1 2\".split() configs = [{'id':","= { i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value,","board answers the ping board_answers = [(b'', [0], i) for i in range(1,","json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry):","test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \"test.py -p /dev/ttyUSB0 0 1 2\".split()","{ i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value, encode_ping(),"],"string":"[\n \"configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print')\",\n \"bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i in\",\n \"@patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if we\",\n \"} open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i:\",\n \"[0, 1, 2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4,\",\n \"@patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if\",\n \"print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if we can perform a whole\",\n \"= [{'id': i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for\",\n \"import * import bootloader_read_config from commands import * import sys import json class\",\n \"[None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in\",\n \"= \\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The first two board answers the ping\",\n \"sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn,\",\n \"open_conn, write_command, write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split() configs =\",\n \"open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i]\",\n \"range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) } open_conn.return_value =\",\n \"from msgpack import * import bootloader_read_config from commands import * import sys import\",\n \"object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i\",\n \"for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def\",\n \"write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) } open_conn.return_value = object()\",\n \"{ i: packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value,\",\n \"discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The first two board\",\n \"-p /dev/ttyUSB0 --all\\\".split() # The first two board answers the ping board_answers =\",\n \"mock import * from msgpack import * import bootloader_read_config from commands import *\",\n \"print_mock, open_conn, write_command, write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split() configs\",\n \"first two board answers the ping board_answers = [(b'', [0], i) for i\",\n \"bootloader_read_config from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command')\",\n \"= {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command')\",\n \"packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value, encode_ping(), list(range(1, 128)))\",\n \"if we can perform a whole network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p\",\n \"/dev/ttyUSB0 --all\\\".split() # The first two board answers the ping board_answers = [(b'',\",\n \"indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry,\",\n \"sys.argv = \\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split() configs = [{'id': i} for\",\n \"write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i in range(3)}\",\n \"2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection')\",\n \"= [(b'', [0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value =\",\n \"* except ImportError: from mock import * from msgpack import * import bootloader_read_config\",\n \"@patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if we can\",\n \"we can perform a whole network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0\",\n \"try: from unittest.mock import * except ImportError: from mock import * from msgpack\",\n \"i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i:\",\n \"range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs =\",\n \"\\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The first two board answers\",\n \"write_command_retry, open_conn): \\\"\\\"\\\" Checks if we can perform a whole network discovery. \\\"\\\"\\\"\",\n \"= iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in range(1, 3)\",\n \"@patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\"\",\n \"commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print')\",\n \"i) for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value =\",\n \"encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs,\",\n \"unittest.mock import * except ImportError: from mock import * from msgpack import *\",\n \"in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id':\",\n \"--all\\\".split() # The first two board answers the ping board_answers = [(b'', [0],\",\n \"except ImportError: from mock import * from msgpack import * import bootloader_read_config from\",\n \"perform a whole network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split() #\",\n \"1 2\\\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value = {\",\n \"+ [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i\",\n \"ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv =\",\n \"class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv\",\n \"import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command,\",\n \"def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if we can perform\",\n \"ImportError: from mock import * from msgpack import * import bootloader_read_config from commands\",\n \"network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The first two\",\n \"[{'id': i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i\",\n \"two board answers the ping board_answers = [(b'', [0], i) for i in\",\n \"a whole network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The\",\n \"2\\\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value = { i:\",\n \"answers the ping board_answers = [(b'', [0], i) for i in range(1, 3)]\",\n \"the ping board_answers = [(b'', [0], i) for i in range(1, 3)] +\",\n \"unittest try: from unittest.mock import * except ImportError: from mock import * from\",\n \"= { i: packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main()\",\n \"0 1 2\\\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value =\",\n \"test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if we can perform a\",\n \"iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in range(1, 3) }\",\n \"from mock import * from msgpack import * import bootloader_read_config from commands import\",\n \"read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for i in range(1,\",\n \"i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value, encode_ping(), list(range(1,\",\n \"{i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams')\",\n \"@patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0\",\n \"msgpack import * import bootloader_read_config from commands import * import sys import json\",\n \"i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2])\",\n \"can perform a whole network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split()\",\n \"packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0,\",\n \"sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn):\",\n \"@patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks\",\n \"* import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self,\",\n \"i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in\",\n \"-p /dev/ttyUSB0 0 1 2\\\".split() configs = [{'id': i} for i in range(3)]\",\n \"The first two board answers the ping board_answers = [(b'', [0], i) for\",\n \"sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The first two board answers the\",\n \"i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) }\",\n \"print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram, write_command,\",\n \"write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split() configs = [{'id': i}\",\n \"/dev/ttyUSB0 0 1 2\\\".split() configs = [{'id': i} for i in range(3)] write_command_retry.return_value\",\n \"# The first two board answers the ping board_answers = [(b'', [0], i)\",\n \"@patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \\\"test.py\",\n \"import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock,\",\n \"import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def\",\n \"board_answers = [(b'', [0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value\",\n \"\\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The first two board answers the ping board_answers\",\n \"for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = {\",\n \"* from msgpack import * import bootloader_read_config from commands import * import sys\",\n \"read_can_datagram, write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if we can perform a whole network\",\n \"from unittest.mock import * except ImportError: from mock import * from msgpack import\",\n \"\\\"\\\"\\\" Checks if we can perform a whole network discovery. \\\"\\\"\\\" sys.argv =\",\n \"whole network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py -p /dev/ttyUSB0 --all\\\".split() # The first\",\n \"from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection')\",\n \"range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock, read_can_datagram,\",\n \"in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs\",\n \"Checks if we can perform a whole network discovery. \\\"\\\"\\\" sys.argv = \\\"test.py\",\n \"import * from msgpack import * import bootloader_read_config from commands import * import\",\n \"write_command_retry.return_value = { i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main()\",\n \"= object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1, 2]) all_configs = {i: configs[i] for\",\n \"1, 2]) all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True))\",\n \"i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self,\",\n \"import bootloader_read_config from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry')\",\n \"for i in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3)\",\n \"configs = [{'id': i} for i in range(3)] write_command_retry.return_value = { i: packb(configs[i])\",\n \"ping board_answers = [(b'', [0], i) for i in range(1, 3)] + [None]\",\n \"i: packb(configs[i]) for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(),\",\n \"= \\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split() configs = [{'id': i} for i\",\n \"[0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value\",\n \"open_conn): \\\"\\\"\\\" Checks if we can perform a whole network discovery. \\\"\\\"\\\" sys.argv\",\n \"3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i}) for\",\n \"@patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0 0\",\n \"import * except ImportError: from mock import * from msgpack import * import\",\n \"* import bootloader_read_config from commands import * import sys import json class ReadConfigToolTestCase(unittest.TestCase):\",\n \"[(b'', [0], i) for i in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers)\",\n \"@patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \\\"test.py -p\",\n \"for i in range(3) } open_conn.return_value = object() bootloader_read_config.main() write_command_retry.assert_any_call(open_conn.return_value, encode_read_config(), [0, 1,\",\n \"range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value = { i: packb({'id': i})\",\n \"\\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split() configs = [{'id': i} for i in\",\n \"import unittest try: from unittest.mock import * except ImportError: from mock import *\",\n \"in range(3)] write_command_retry.return_value = { i: packb(configs[i]) for i in range(3) } open_conn.return_value\",\n \"in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_network_discovery(self, print_mock,\",\n \"write_command, write_command_retry, open_conn): \\\"\\\"\\\" Checks if we can perform a whole network discovery.\",\n \"all_configs = {i: configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry')\",\n \"def test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0 0 1\",\n \"write_command, write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split() configs = [{'id':\",\n \"= { i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value,\",\n \"board answers the ping board_answers = [(b'', [0], i) for i in range(1,\",\n \"json class ReadConfigToolTestCase(unittest.TestCase): @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.open_connection') @patch('builtins.print') def test_integration(self, print_mock, open_conn, write_command, write_command_retry):\",\n \"test_integration(self, print_mock, open_conn, write_command, write_command_retry): sys.argv = \\\"test.py -p /dev/ttyUSB0 0 1 2\\\".split()\",\n \"{ i: packb({'id': i}) for i in range(1, 3) } bootloader_read_config.main() write_command.assert_any_call(open_conn.return_value, encode_ping(),\"\n]","isConversational":false}}},{"rowIdx":84,"cells":{"ngram":{"kind":"list like","value":["in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException):","ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54,","requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username,","async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message","*args): try: msg = await review_embed(username, ' '.join(str(i) for i in args)) except","'') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {}","def on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats())","in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await film_embed(arg) except","permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif","msg = await diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx,","= discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664',","await ctx.send('This command requires the {} permission.'.format( ', '.join(err for err in error.missing_perms)))","'.join(str(i) for i in args)) except LetterboxdError as err: msg = err await","await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format(","from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot =","break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await","msg = await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as","send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd","from film import film_embed from helpers import LetterboxdError from list_ import list_embed from",":/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg)","except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def","await film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx, msg) async","msg = await film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx,","await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg =","(commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry,","@bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message)","ctx.send('This command requires the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif","% (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’',","{} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return","discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed","= await diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg)","username, *args): try: msg = await review_embed(username, ' '.join(str(i) for i in args))","for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if","await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings","def film(ctx, *, arg): try: # eiga.me ratings for specific servers if ctx.guild","bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for","text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description","review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d","3: await ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args)","def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list()","the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg,","as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def","False cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name) for alias","as err: msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username):","elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed.","= True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word","log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True","err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx,","check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2","+ alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not","arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg =","isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err for err","list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i) for i in","command requires the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error,","review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i) for i in","on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error,","*, arg): try: # eiga.me ratings for specific servers if ctx.guild and ctx.guild.id","activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if","= err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg)","@bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False","'').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb -","parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try:","in args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del')","i in args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg)","msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await review_embed(username,","cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id ==","await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires","@bot.event async def on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds),","command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {}","discord from discord.ext import commands from config import SETTINGS from crew import crew_embed","inline=False) help_embed.description = 'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async","logging from asyncio import sleep import discord from discord.ext import commands from config","username): try: msg = await user_embed(username) except LetterboxdError as err: msg = err","error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return","in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias) async","from crew import crew_embed from diary import diary_embed from film import film_embed from","async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg')","LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async","' '.join(str(i) for i in args)) except LetterboxdError as err: msg = err","async def review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i) for","requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format(","send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg =","async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list =","from list_ import list_embed from review import review_embed from user import user_embed logging.basicConfig(","cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for log_message","def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands","log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return","case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers as %s'","found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd","isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx):","commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers as","msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async","import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True)","commands from config import SETTINGS from crew import crew_embed from diary import diary_embed","= commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers","bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error):","async def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as err:","film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as err: msg =","import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S')","%H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in","except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command() async def","= log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else:","ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg =","name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items():","user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!',","import LetterboxdError from list_ import list_embed from review import review_embed from user import","by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description =","try: # eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']:","film_embed from helpers import LetterboxdError from list_ import list_embed from review import review_embed","discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async","await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed =","def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif","True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in","if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg","*args): try: msg = await list_embed(username, ' '.join(str(i) for i in args)) except","isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error","asyncio import sleep import discord from discord.ext import commands from config import SETTINGS","continue if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break if","and not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content:","command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30):","SETTINGS from crew import crew_embed from diary import diary_embed from film import film_embed","msg = await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as","@bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot',","ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await","LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def","2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args):","command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx,","diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress',","True) else: msg = await film_embed(arg) except LetterboxdError as err: msg = err","crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await","'actress', 'director']) async def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with)","== bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg:","'\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg =","async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) #","return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command","alias in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id","await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3:","57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for","from discord.ext import commands from config import SETTINGS from crew import crew_embed from","= await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err:","62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key,","found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word =","True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def","from config import SETTINGS from crew import crew_embed from diary import diary_embed from","for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg,","msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This","msg = await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as","send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await","await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as err: msg","not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word","= False cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name) for","elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err for","help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value","command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias)","and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await","False found_usr_cmd = False cmd_list = list() for command in bot.commands: cmd_list.append('!' +","as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx):","await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list() for command","= err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: #","bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '')","if len(msg) < 3: await ctx.send('This command requires 2 parameters.') return len(msg) >","servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await","err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg","ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError","+ command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for log_message in","ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg =","for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message =","= err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg","icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value,","except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async","= log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message =","value=value, inline=False) help_embed.description = 'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command()","await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg","(len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘',","parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err","err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try:","try: msg = await user_embed(username) except LetterboxdError as err: msg = err await","try: msg = await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError","LetterboxdError as err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg","ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def","- {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error,","'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def","if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await","first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if","err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) <","msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg = await","def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900)","= 'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx,","'[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await user_embed(username)","err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me","servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'):","await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg):","format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def","logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else:","LetterboxdError from list_ import list_embed from review import review_embed from user import user_embed","as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx,","else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx,","= await film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx, msg)","bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0]","command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed):","try: msg = await diary_embed(username) except LetterboxdError as err: msg = err await","async def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError","await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62))","'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username):","bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await","%d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if","True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id","found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete() await","# eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg","msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *,","help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False)","LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def","args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args)","as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content","found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if","help_embed.description = 'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def","import film_embed from helpers import LetterboxdError from list_ import list_embed from review import","import SETTINGS from crew import crew_embed from diary import diary_embed from film import","ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png')","= await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx,","except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async","= err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg):","%s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content =","err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await","def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer(","import list_embed from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s","cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name) for alias in","= await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as err:","@commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i)","= await user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg)","from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s',","requires the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound,","async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await","await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await user_embed(username) except","> 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await","first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message","import logging from asyncio import sleep import discord from discord.ext import commands from","if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete()","msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if","%(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info(","for command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' +","bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d","else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57,","def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as err: msg","def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def","', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error,","diary import diary_embed from film import film_embed from helpers import LetterboxdError from list_","alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg:","return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def","await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx,","username, *args): try: msg = await list_embed(username, ' '.join(str(i) for i in args))","list_ import list_embed from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO,","discord.ext import commands from config import SETTINGS from crew import crew_embed from diary","on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event","import sleep import discord from discord.ext import commands from config import SETTINGS from","crew import crew_embed from diary import diary_embed from film import film_embed from helpers","cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages:","bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds))))","@bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await list_embed(username, '","elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list:","discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png')","Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite","msg = await user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx,","bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers as %s' %","send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command()","in args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry'])","log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True elif","msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try:","helpers import LetterboxdError from list_ import list_embed from review import review_embed from user","if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise","async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async","msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd =","@commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list","def review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i) for i","if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd:","found_usr_cmd = False cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name)","import diary_embed from film import film_embed from helpers import LetterboxdError from list_ import","try: msg = await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError","message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await","servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else:","@bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg = await crew_embed(arg,","Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd","review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg =","msg) @bot.command() async def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError","await user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command()","if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True","icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot","if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd =","in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id ==","len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg =","crew_embed from diary import diary_embed from film import film_embed from helpers import LetterboxdError","| '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg","value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\ +","err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg =","send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await","user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command() async","raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await","@bot.command() async def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as","< 3: await ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list')","crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err:","found_bot_msg = False found_usr_cmd = False cmd_list = list() for command in bot.commands:","else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break","in cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if not","isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await","while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async","film(ctx, *, arg): try: # eiga.me ratings for specific servers if ctx.guild and","+ '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await","user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help')","crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie'])","= log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id:","specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True)","helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created","help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in","for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot |","config import SETTINGS from crew import crew_embed from diary import diary_embed from film","level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async","if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def","err: msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try:","message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb","async def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as err:","ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await film_embed(arg)","@bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await review_embed(username, '","review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot","cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and","else: msg = await film_embed(arg) except LetterboxdError as err: msg = err await","err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username,","commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command","for alias in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if","async def on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name))","logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async","def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires","import crew_embed from diary import diary_embed from film import film_embed from helpers import","send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings for","= False found_usr_cmd = False cmd_list = list() for command in bot.commands: cmd_list.append('!'","ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the","msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args):","delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list() for","if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete() await bot_message.delete()","on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats():","from helpers import LetterboxdError from list_ import list_embed from review import review_embed from","isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This","user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as err: msg =","list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg =","for i in args)) except LetterboxdError as err: msg = err await send_msg(ctx,","@commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i)","ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async","= ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2 parameters.') return","'.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError):","SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError","| %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready():","in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message):","await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg","commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the","ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2 parameters.') return len(msg)","Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key,","in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)'","try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err","log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message","= err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try:","await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg","datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged","len(msg) < 3: await ctx.send('This command requires 2 parameters.') return len(msg) > 2","= await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err:","msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2 parameters.')","2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await list_embed(username,","list() for command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!'","diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as err: msg =","error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg)","@bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a","= list() for command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases:","logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event","ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list() for command in","username): try: msg = await diary_embed(username) except LetterboxdError as err: msg = err","not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete() await bot_message.delete() bot.run(SETTINGS['discord'])","return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg","error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions):","# Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author(","Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try:","the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)):","def list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i) for i","await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx, msg)","'director']) async def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except","command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id","await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command","update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event","await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False","found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if","except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director'])","help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed)","err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original,","*, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg","as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *,","log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue","from diary import diary_embed from film import film_embed from helpers import LetterboxdError from","err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg):","isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/')","msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg","a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ',","SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await","= message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence(","len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This","async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command","{} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument):","err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg = await","def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as err: msg","key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\","sleep import discord from discord.ext import commands from config import SETTINGS from crew","async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.')","err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split()","from asyncio import sleep import discord from discord.ext import commands from config import","bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if","as err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg =","eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg =","if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while","async def film(ctx, *, arg): try: # eiga.me ratings for specific servers if","msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings for specific","= True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not","= err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg =","except LetterboxdError as err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx):","args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True)","log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message","LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx,","ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if","film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx, msg) async def","await ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async","def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as","message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True:","async def list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i) for","LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx,","diary_embed from film import film_embed from helpers import LetterboxdError from list_ import list_embed","commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content)","in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg","import discord from discord.ext import commands from config import SETTINGS from crew import","list_embed from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s |","await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg = await diary_embed(username)","msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete()","import commands from config import SETTINGS from crew import crew_embed from diary import","commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err for err in","send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg = await diary_embed(username) except","arg): try: # eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in","await diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor',","@bot.command() async def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as","help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by","msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await","film import film_embed from helpers import LetterboxdError from list_ import list_embed from review","sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires","elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else:","@bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings for specific servers"],"string":"[\n \"in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException):\",\n \"ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54,\",\n \"requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username,\",\n \"async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message\",\n \"*args): try: msg = await review_embed(username, ' '.join(str(i) for i in args)) except\",\n \"'') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {}\",\n \"def on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats())\",\n \"in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await film_embed(arg) except\",\n \"permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif\",\n \"msg = await diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx,\",\n \"= discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664',\",\n \"await ctx.send('This command requires the {} permission.'.format( ', '.join(err for err in error.missing_perms)))\",\n \"'.join(str(i) for i in args)) except LetterboxdError as err: msg = err await\",\n \"await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format(\",\n \"from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot =\",\n \"break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await\",\n \"msg = await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as\",\n \"send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd\",\n \"from film import film_embed from helpers import LetterboxdError from list_ import list_embed from\",\n \":/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg)\",\n \"except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def\",\n \"await film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx, msg) async\",\n \"msg = await film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx,\",\n \"await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg =\",\n \"(commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry,\",\n \"@bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message)\",\n \"ctx.send('This command requires the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif\",\n \"% (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’',\",\n \"{} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return\",\n \"discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed\",\n \"= await diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg)\",\n \"username, *args): try: msg = await review_embed(username, ' '.join(str(i) for i in args))\",\n \"for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if\",\n \"await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings\",\n \"def film(ctx, *, arg): try: # eiga.me ratings for specific servers if ctx.guild\",\n \"bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for\",\n \"text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description\",\n \"review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d\",\n \"3: await ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args)\",\n \"def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list()\",\n \"the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg,\",\n \"as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def\",\n \"False cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name) for alias\",\n \"as err: msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username):\",\n \"elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed.\",\n \"= True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word\",\n \"log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True\",\n \"err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx,\",\n \"check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2\",\n \"+ alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not\",\n \"arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg =\",\n \"isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err for err\",\n \"list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i) for i in\",\n \"command requires the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error,\",\n \"review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i) for i in\",\n \"on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error,\",\n \"*, arg): try: # eiga.me ratings for specific servers if ctx.guild and ctx.guild.id\",\n \"activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if\",\n \"= err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg)\",\n \"@bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False\",\n \"'').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb -\",\n \"parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try:\",\n \"in args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del')\",\n \"i in args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg)\",\n \"msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await review_embed(username,\",\n \"cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id ==\",\n \"await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires\",\n \"@bot.event async def on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds),\",\n \"command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {}\",\n \"discord from discord.ext import commands from config import SETTINGS from crew import crew_embed\",\n \"inline=False) help_embed.description = 'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async\",\n \"logging from asyncio import sleep import discord from discord.ext import commands from config\",\n \"username): try: msg = await user_embed(username) except LetterboxdError as err: msg = err\",\n \"error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return\",\n \"in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias) async\",\n \"from crew import crew_embed from diary import diary_embed from film import film_embed from\",\n \"async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg')\",\n \"LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async\",\n \"' '.join(str(i) for i in args)) except LetterboxdError as err: msg = err\",\n \"async def review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i) for\",\n \"requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format(\",\n \"send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg =\",\n \"async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list =\",\n \"from list_ import list_embed from review import review_embed from user import user_embed logging.basicConfig(\",\n \"cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for log_message\",\n \"def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands\",\n \"log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return\",\n \"case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers as %s'\",\n \"found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd\",\n \"isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx):\",\n \"commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers as\",\n \"msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async\",\n \"import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True)\",\n \"commands from config import SETTINGS from crew import crew_embed from diary import diary_embed\",\n \"= commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers\",\n \"bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error):\",\n \"async def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as err:\",\n \"film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as err: msg =\",\n \"import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S')\",\n \"%H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in\",\n \"except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command() async def\",\n \"= log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else:\",\n \"ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg =\",\n \"name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items():\",\n \"user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!',\",\n \"import LetterboxdError from list_ import list_embed from review import review_embed from user import\",\n \"by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description =\",\n \"try: # eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']:\",\n \"film_embed from helpers import LetterboxdError from list_ import list_embed from review import review_embed\",\n \"discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async\",\n \"await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed =\",\n \"def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif\",\n \"True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in\",\n \"if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg\",\n \"*args): try: msg = await list_embed(username, ' '.join(str(i) for i in args)) except\",\n \"isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error\",\n \"asyncio import sleep import discord from discord.ext import commands from config import SETTINGS\",\n \"continue if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break if\",\n \"and not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content:\",\n \"command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30):\",\n \"SETTINGS from crew import crew_embed from diary import diary_embed from film import film_embed\",\n \"msg = await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as\",\n \"@bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot',\",\n \"ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await\",\n \"LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def\",\n \"2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args):\",\n \"command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx,\",\n \"diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress',\",\n \"True) else: msg = await film_embed(arg) except LetterboxdError as err: msg = err\",\n \"crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await\",\n \"'actress', 'director']) async def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with)\",\n \"== bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg:\",\n \"'\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg =\",\n \"async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) #\",\n \"return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command\",\n \"alias in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id\",\n \"await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3:\",\n \"57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for\",\n \"from discord.ext import commands from config import SETTINGS from crew import crew_embed from\",\n \"= await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err:\",\n \"62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key,\",\n \"found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word =\",\n \"True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def\",\n \"from config import SETTINGS from crew import crew_embed from diary import diary_embed from\",\n \"for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg,\",\n \"msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This\",\n \"msg = await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as\",\n \"send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await\",\n \"await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as err: msg\",\n \"not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word\",\n \"= False cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name) for\",\n \"elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err for\",\n \"help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value\",\n \"command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' + alias)\",\n \"and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await\",\n \"False found_usr_cmd = False cmd_list = list() for command in bot.commands: cmd_list.append('!' +\",\n \"as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx):\",\n \"await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list() for command\",\n \"= err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: #\",\n \"bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '')\",\n \"if len(msg) < 3: await ctx.send('This command requires 2 parameters.') return len(msg) >\",\n \"servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await\",\n \"err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg\",\n \"ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError\",\n \"+ command.name) for alias in command.aliases: cmd_list.append('!' + alias) async for log_message in\",\n \"ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg =\",\n \"for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message =\",\n \"= err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg\",\n \"icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value,\",\n \"except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async\",\n \"= log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message =\",\n \"value=value, inline=False) help_embed.description = 'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command()\",\n \"await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg\",\n \"(len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘',\",\n \"parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err\",\n \"err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try:\",\n \"try: msg = await user_embed(username) except LetterboxdError as err: msg = err await\",\n \"try: msg = await list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError\",\n \"LetterboxdError as err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg\",\n \"ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def\",\n \"- {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error,\",\n \"'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def\",\n \"if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await\",\n \"first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if\",\n \"err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) <\",\n \"msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg = await\",\n \"def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900)\",\n \"= 'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx,\",\n \"'[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await user_embed(username)\",\n \"err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me\",\n \"servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'):\",\n \"await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg):\",\n \"format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def\",\n \"logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else:\",\n \"LetterboxdError from list_ import list_embed from review import review_embed from user import user_embed\",\n \"as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx,\",\n \"else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx,\",\n \"= await film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx, msg)\",\n \"bot_message = log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0]\",\n \"command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed):\",\n \"try: msg = await diary_embed(username) except LetterboxdError as err: msg = err await\",\n \"async def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError\",\n \"await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62))\",\n \"'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username):\",\n \"bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await\",\n \"%d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if\",\n \"True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id\",\n \"found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete() await\",\n \"# eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg\",\n \"msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *,\",\n \"help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False)\",\n \"LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def\",\n \"args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args)\",\n \"as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content\",\n \"found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if\",\n \"help_embed.description = 'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def\",\n \"import film_embed from helpers import LetterboxdError from list_ import list_embed from review import\",\n \"import SETTINGS from crew import crew_embed from diary import diary_embed from film import\",\n \"ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png')\",\n \"= await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx,\",\n \"except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async\",\n \"= err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg):\",\n \"%s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message): if message.content.startswith('!'): message.content =\",\n \"err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await\",\n \"def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer(\",\n \"import list_embed from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s\",\n \"cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name) for alias in\",\n \"= await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError as err:\",\n \"@commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i)\",\n \"= await user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg)\",\n \"from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s',\",\n \"requires the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound,\",\n \"async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await\",\n \"await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await user_embed(username) except\",\n \"> 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await\",\n \"first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message\",\n \"import logging from asyncio import sleep import discord from discord.ext import commands from\",\n \"if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete()\",\n \"msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if\",\n \"%(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info(\",\n \"for command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!' +\",\n \"bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d\",\n \"else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57,\",\n \"def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as err: msg\",\n \"def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def\",\n \"', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error,\",\n \"diary import diary_embed from film import film_embed from helpers import LetterboxdError from list_\",\n \"alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg:\",\n \"return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def\",\n \"await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx,\",\n \"username, *args): try: msg = await list_embed(username, ' '.join(str(i) for i in args))\",\n \"list_ import list_embed from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO,\",\n \"discord.ext import commands from config import SETTINGS from crew import crew_embed from diary\",\n \"on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event\",\n \"import sleep import discord from discord.ext import commands from config import SETTINGS from\",\n \"crew import crew_embed from diary import diary_embed from film import film_embed from helpers\",\n \"cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages:\",\n \"bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds))))\",\n \"@bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await list_embed(username, '\",\n \"elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list:\",\n \"discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png')\",\n \"Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite\",\n \"msg = await user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx,\",\n \"bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged in %d servers as %s' %\",\n \"send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command()\",\n \"in args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry'])\",\n \"log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True elif\",\n \"msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try:\",\n \"helpers import LetterboxdError from list_ import list_embed from review import review_embed from user\",\n \"if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise\",\n \"async def on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async\",\n \"msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd =\",\n \"@commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list\",\n \"def review(ctx, username, *args): try: msg = await review_embed(username, ' '.join(str(i) for i\",\n \"if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd:\",\n \"found_usr_cmd = False cmd_list = list() for command in bot.commands: cmd_list.append('!' + command.name)\",\n \"import diary_embed from film import film_embed from helpers import LetterboxdError from list_ import\",\n \"try: msg = await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError\",\n \"message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await\",\n \"servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else:\",\n \"@bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg = await crew_embed(arg,\",\n \"Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd\",\n \"review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg =\",\n \"msg) @bot.command() async def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError\",\n \"await user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command()\",\n \"if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True\",\n \"icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot\",\n \"if log_message.content: first_word = log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd =\",\n \"in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id ==\",\n \"len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg =\",\n \"crew_embed from diary import diary_embed from film import film_embed from helpers import LetterboxdError\",\n \"| '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg\",\n \"value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\\\ +\",\n \"err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg =\",\n \"send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await\",\n \"user_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command() async\",\n \"raise error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await\",\n \"@bot.command() async def diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as\",\n \"< 3: await ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list')\",\n \"crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err:\",\n \"found_bot_msg = False found_usr_cmd = False cmd_list = list() for command in bot.commands:\",\n \"else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message break\",\n \"in cmd_list: found_usr_cmd = True cmd_message = log_message break if found_usr_cmd: if not\",\n \"isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await\",\n \"while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async\",\n \"film(ctx, *, arg): try: # eiga.me ratings for specific servers if ctx.guild and\",\n \"+ '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try: msg = await\",\n \"user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help')\",\n \"crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie'])\",\n \"= log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id:\",\n \"specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True)\",\n \"helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created\",\n \"help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in\",\n \"for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot |\",\n \"config import SETTINGS from crew import crew_embed from diary import diary_embed from film\",\n \"level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async\",\n \"if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def\",\n \"err: msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try:\",\n \"message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb\",\n \"async def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as err:\",\n \"ctx.guild.id in SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await film_embed(arg)\",\n \"@bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try: msg = await review_embed(username, '\",\n \"review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot\",\n \"cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and\",\n \"else: msg = await film_embed(arg) except LetterboxdError as err: msg = err await\",\n \"err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username,\",\n \"commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command\",\n \"for alias in command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if\",\n \"async def on_ready(): logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name))\",\n \"logging.info( 'Logged in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async\",\n \"def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires\",\n \"import crew_embed from diary import diary_embed from film import film_embed from helpers import\",\n \"send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings for\",\n \"= False found_usr_cmd = False cmd_list = list() for command in bot.commands: cmd_list.append('!'\",\n \"ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the\",\n \"msg = err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args):\",\n \"delete(ctx): await ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list() for\",\n \"if not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete() await bot_message.delete()\",\n \"on_message(message): if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats():\",\n \"from helpers import LetterboxdError from list_ import list_embed from review import review_embed from\",\n \"isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This\",\n \"user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as err: msg =\",\n \"list_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg =\",\n \"for i in args)) except LetterboxdError as err: msg = err await send_msg(ctx,\",\n \"@commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i)\",\n \"ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async\",\n \"= ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2 parameters.') return\",\n \"'.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError):\",\n \"SETTINGS['mkdb_servers']: msg = await film_embed(arg, True) else: msg = await film_embed(arg) except LetterboxdError\",\n \"| %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready():\",\n \"in %d servers as %s' % (len(bot.guilds), bot.user.name)) bot.loop.create_task(update_stats()) @bot.event async def on_message(message):\",\n \"await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director']) async def crew(ctx, *, arg): try: msg\",\n \"commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the\",\n \"ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2 parameters.') return len(msg)\",\n \"Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by Porkepik#2664', icon_url='https://i.imgur.com/li4cLpd.png') for key, value in SETTINGS['help'].items(): help_embed.add_field(name=key,\",\n \"in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)'\",\n \"try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err\",\n \"log_message.content.split()[0] else: continue if first_word in cmd_list: found_usr_cmd = True cmd_message = log_message\",\n \"= err await send_msg(ctx, msg) @bot.command(aliases=['entry']) @commands.check(check_if_two_args) async def review(ctx, username, *args): try:\",\n \"await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err: msg\",\n \"datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event async def on_ready(): logging.info( 'Logged\",\n \"len(msg) < 3: await ctx.send('This command requires 2 parameters.') return len(msg) > 2\",\n \"= await review_embed(username, ' '.join(str(i) for i in args)) except LetterboxdError as err:\",\n \"msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command requires 2 parameters.')\",\n \"2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg = await list_embed(username,\",\n \"list() for command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases: cmd_list.append('!'\",\n \"diary(ctx, username): try: msg = await diary_embed(username) except LetterboxdError as err: msg =\",\n \"error async def send_msg(ctx, msg): if isinstance(msg, discord.Embed): await ctx.send(embed=msg) else: await ctx.send(msg)\",\n \"@bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a\",\n \"= list() for command in bot.commands: cmd_list.append('!' + command.name) for alias in command.aliases:\",\n \"logging.basicConfig( level=logging.INFO, format='%(asctime)s | %(message)s', datefmt='%m/%d %H:%M:%S') bot = commands.Bot(command_prefix='!', case_insensitive=True) bot.remove_command('help') @bot.event\",\n \"ctx.message.delete() found_bot_msg = False found_usr_cmd = False cmd_list = list() for command in\",\n \"username): try: msg = await diary_embed(username) except LetterboxdError as err: msg = err\",\n \"not ctx.author.permissions_in(ctx.channel).manage_messages: if not cmd_message.author.id == ctx.author.id: return await cmd_message.delete() await bot_message.delete() bot.run(SETTINGS['discord'])\",\n \"return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async def list_(ctx, username, *args): try: msg\",\n \"error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.') elif isinstance(error, commands.BotMissingPermissions):\",\n \"# Commands @bot.command() async def helplb(ctx): help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author(\",\n \"Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed) @bot.command() async def user(ctx, username): try:\",\n \"the {} permission.'.format( ', '.join(err for err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)):\",\n \"def list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i) for i\",\n \"await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await send_msg(ctx, msg)\",\n \"'director']) async def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except\",\n \"command.aliases: cmd_list.append('!' + alias) async for log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id\",\n \"await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command\",\n \"update_stats(): while True: await bot.change_presence( activity=discord.Game('!helplb - {} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event\",\n \"await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete() found_bot_msg = False\",\n \"found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue if\",\n \"except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor', 'actress', 'director'])\",\n \"help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await ctx.send(embed=help_embed)\",\n \"err in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original,\",\n \"*, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg\",\n \"as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *,\",\n \"log_message found_bot_msg = True elif found_bot_msg: if log_message.content: first_word = log_message.content.split()[0] else: continue\",\n \"from diary import diary_embed from film import film_embed from helpers import LetterboxdError from\",\n \"err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg):\",\n \"isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/')\",\n \"msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg\",\n \"a parameter.') elif isinstance(error, commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ',\",\n \"SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\\\ + '[GitHub](https://github.com/Porkepik/Letterboxd-Bot)' await\",\n \"= message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True: await bot.change_presence(\",\n \"len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This\",\n \"async def check_if_two_args(ctx): msg = ctx.message.content.split() if len(msg) < 3: await ctx.send('This command\",\n \"{} servers'.format( len(bot.guilds)))) await sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument):\",\n \"err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg = await\",\n \"def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as err: msg\",\n \"key, value in SETTINGS['help'].items(): help_embed.add_field(name=key, value=value, inline=False) help_embed.description = 'Invite Bot | '\\\\\",\n \"sleep import discord from discord.ext import commands from config import SETTINGS from crew\",\n \"async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires a parameter.')\",\n \"err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split()\",\n \"from asyncio import sleep import discord from discord.ext import commands from config import\",\n \"bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg = True elif found_bot_msg: if\",\n \"as err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg =\",\n \"eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in SETTINGS['mkdb_servers']: msg =\",\n \"if message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while\",\n \"async def film(ctx, *, arg): try: # eiga.me ratings for specific servers if\",\n \"msg) @bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings for specific\",\n \"= True cmd_message = log_message break if found_usr_cmd: if not ctx.author.permissions_in(ctx.channel).manage_messages: if not\",\n \"= err await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg =\",\n \"except LetterboxdError as err: msg = err await send_msg(ctx, msg) async def check_if_two_args(ctx):\",\n \"args)) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True)\",\n \"log_message in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message\",\n \"LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['movie']) async def film(ctx,\",\n \"ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content) raise error async def send_msg(ctx, msg): if\",\n \"film_embed(arg) except LetterboxdError as err: msg = err await send_msg(ctx, msg) async def\",\n \"await ctx.send('This command requires 2 parameters.') return len(msg) > 2 @bot.command(name='list') @commands.check(check_if_two_args) async\",\n \"def crew(ctx, *, arg): try: msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as\",\n \"message.content.startswith('!'): message.content = message.content.replace('’', '').replace('‘', '') await bot.process_commands(message) async def update_stats(): while True:\",\n \"async def list_(ctx, username, *args): try: msg = await list_embed(username, ' '.join(str(i) for\",\n \"LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command() async def diary(ctx,\",\n \"diary_embed from film import film_embed from helpers import LetterboxdError from list_ import list_embed\",\n \"commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else: await ctx.send('Sorry, the command crashed. :/') logging.error(ctx.message.content)\",\n \"in ctx.channel.history(limit=30): if log_message.author.id == bot.user.id and not found_bot_msg: bot_message = log_message found_bot_msg\",\n \"import discord from discord.ext import commands from config import SETTINGS from crew import\",\n \"list_embed from review import review_embed from user import user_embed logging.basicConfig( level=logging.INFO, format='%(asctime)s |\",\n \"await send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg = await diary_embed(username)\",\n \"msg = err await send_msg(ctx, msg) @bot.command(name='del') @commands.bot_has_permissions(manage_messages=True) async def delete(ctx): await ctx.message.delete()\",\n \"import commands from config import SETTINGS from crew import crew_embed from diary import\",\n \"commands.BotMissingPermissions): await ctx.send('This command requires the {} permission.'.format( ', '.join(err for err in\",\n \"send_msg(ctx, msg) @bot.command() async def diary(ctx, username): try: msg = await diary_embed(username) except\",\n \"arg): try: # eiga.me ratings for specific servers if ctx.guild and ctx.guild.id in\",\n \"await diary_embed(username) except LetterboxdError as err: msg = err await send_msg(ctx, msg) @bot.command(aliases=['actor',\",\n \"@bot.command() async def user(ctx, username): try: msg = await user_embed(username) except LetterboxdError as\",\n \"help_embed = discord.Embed(colour=discord.Color.from_rgb(54, 57, 62)) help_embed.set_thumbnail(url='https://i.imgur.com/Kr1diFu.png') help_embed.set_author( name='Letterboxd Bot', icon_url='https://i.imgur.com/5VALKVy.jpg') help_embed.set_footer( text='Created by\",\n \"msg = await crew_embed(arg, ctx.invoked_with) except LetterboxdError as err: msg = err await\",\n \"film import film_embed from helpers import LetterboxdError from list_ import list_embed from review\",\n \"sleep(900) @bot.event async def on_command_error(ctx, error): if isinstance(error, commands.MissingRequiredArgument): await ctx.send('This command requires\",\n \"elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException): return else:\",\n \"@bot.command(aliases=['movie']) async def film(ctx, *, arg): try: # eiga.me ratings for specific servers\"\n]","isConversational":false}}},{"rowIdx":85,"cells":{"ngram":{"kind":"list like","value":["result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id,","such workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try:","try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id:","need to fix this later. \"\"\" store = get_global_storage() assert ray.is_initialized() if workflow_id","-> ray.ObjectRef: \"\"\"Get the output of a running workflow. See \"api.get_output()\" for details.","== StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery","workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\"No such workflow_id {workflow_id}\")","import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor","= get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to","_) in all_failed])) return [(wid, obj) for (wid, obj) in ret if obj","{workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get","workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to","this later. \"\"\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None: #","(k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings:","runnings = set(runnings) # Here we don't have workflow id, so use empty","result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def","See \"api.get_output()\" for details. \"\"\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError","in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret","def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError:","except ValueError: workflow_manager = None if workflow_manager is None: runnings = [] else:","import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step","ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger","if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark):","ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id:","ValueError( \"Failed to connect to the workflow management \" \"actor. The workflow could","e: raise ValueError( \"Failed to connect to the workflow management \" \"actor. The","\"api.get_output()\" for details. \"\"\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as","result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id,","-> ray.ObjectRef: \"\"\"Run a workflow asynchronously. # TODO(suquark): The current \"run\" always overwrite","already failed. You can use \" \"workflow.resume() to resume the workflow.\") from e","except Exception: logger.error(f\"Failed to resume workflow {wid}\") return (wid, None) ret = workflow_storage.asyncio_run(","fix this later. \"\"\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None:","None, overwrite: bool = True) -> ray.ObjectRef: \"\"\"Run a workflow asynchronously. # TODO(suquark):","TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage","we don't have workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\"\")","workflow management \" \"actor. The workflow could have already failed. You can use","k not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s))","-> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try:","entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support","logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) ->","assert ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix","fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type","[] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not","async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = ( await","resume the workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def","# checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor()","= get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned output. This","ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job","storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get' the","the output of a running workflow. See \"api.get_output()\" for details. \"\"\" assert ray.is_initialized()","list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager","= False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if","[] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1:","use empty one instead store = workflow_storage.get_workflow_storage(\"\") ret = [] for (k, s)","import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import","ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import","workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None: runnings","UUID}.{Unix time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\")","obj except Exception: logger.error(f\"Failed to resume workflow {wid}\") return (wid, None) ret =","ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import","result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef:","workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager","meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except","empty one instead store = workflow_storage.get_workflow_storage(\"\") ret = [] for (k, s) in","output of a running workflow. See \"api.get_output()\" for details. \"\"\" assert ray.is_initialized() try:","running workflow. See \"api.get_output()\" for details. \"\"\" assert ray.is_initialized() try: workflow_manager = get_management_actor()","except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager","ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str])","filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor()","get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned output. This #","have workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\"\") ret =","get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except","import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import","time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray","ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor,","name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the output of a running workflow. See \"api.get_output()\"","s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]:","\" \"workflow.resume() to resume the workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return","WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) ->","Otherwise if the actor removes the reference of the # workflow output, the","meta is None: raise ValueError(f\"No such workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus]","workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if","= get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None: runnings =","raise RuntimeError(\"Failed to get management actor\") from e async def _resume_one(wid: str) ->","ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\"","and k not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k,","# result. Otherwise if the actor removes the reference of the # workflow","ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from","the reference of the # workflow output, the caller may fail to resolve","of the # workflow output, the caller may fail to resolve the result.","storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE:","try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None:","str) -> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\" for details. \"\"\" storage","ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type !=","workflow UUID}.{Unix time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\"","except Exception: running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta","the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing =","logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE: It is important","logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) ->","list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\"Failed to get","a workflow asynchronously. See \"api.resume()\" for details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow","get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None: runnings = []","= workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for (wid,","existing workflow. # We need to fix this later. \"\"\" store = get_global_storage()","\"run\" always overwrite existing workflow. # We need to fix this later. \"\"\"","Exception: logger.error(f\"Failed to resume workflow {wid}\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid)","# TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume","to 'ray.get' the returned output. This # ensures caller of 'run()' holds the","None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj)","is None: # Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id","NOTE: It is important to 'ray.get' the returned output. This # ensures caller","1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here","(wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid,","import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger =","from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING:","can use \" \"workflow.resume() to resume the workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id,","wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor()","\"\"\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID","def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef:","\"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() #","= workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running","runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def","if workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix time to","reference to the workflow # result. Otherwise if the actor removes the reference","resume workflow {wid}\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _)","None if workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if","in all_failed])) return [(wid, obj) for (wid, obj) in ret if obj is","with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow)","import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor)","Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return","to get management actor\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]:","ValueError(f\"No such workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]:","# ensures caller of 'run()' holds the reference to the workflow # result.","= get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) ->","workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id)","{WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception","-> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if","= ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def","== WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if s in","Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output)","get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import","WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in","storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws,","WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import","workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager","result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj","Optional[str]) -> ray.ObjectRef: \"\"\"Get the output of a running workflow. See \"api.get_output()\" for","for (wid, _) in all_failed])) return [(wid, obj) for (wid, obj) in ret","overwrite existing workflow. # We need to fix this later. \"\"\" store =","ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE}","workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str)","= get_management_actor() except ValueError as e: raise ValueError( \"Failed to connect to the","commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE:","bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set)","to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job","management actor\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result:","get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow:","True) -> ray.ObjectRef: \"\"\"Run a workflow asynchronously. # TODO(suquark): The current \"run\" always","all_failed])) return [(wid, obj) for (wid, obj) in ret if obj is not","-> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED))","try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\"Failed to get management","List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager","f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned","the workflow # result. Otherwise if the actor removes the reference of the","def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\" for details.","= ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING store","ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for","ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id,","workflow_storage.get_workflow_storage(\"\") ret = [] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING","support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a workflow","s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if","except ValueError as e: raise ValueError( \"Failed to connect to the workflow management","as e: raise RuntimeError(\"Failed to get management actor\") from e async def _resume_one(wid:","id, so use empty one instead store = workflow_storage.get_workflow_storage(\"\") ret = [] for","= set(runnings) # Here we don't have workflow id, so use empty one","\"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It","resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the","meta = store.load_workflow_meta() if meta is None: raise ValueError(f\"No such workflow_id {workflow_id}\") return","Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow","the returned output. This # ensures caller of 'run()' holds the reference to","to resume workflow {wid}\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid,","ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try:","if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id:","None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def","the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\")","logging import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid","WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access","workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running =","Here we don't have workflow id, so use empty one instead store =","Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager =","resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id}","wid, obj except Exception: logger.error(f\"Failed to resume workflow {wid}\") return (wid, None) ret","List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager","raise ValueError( \"Failed to connect to the workflow management \" \"actor. The workflow","= workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION)","'run()' holds the reference to the workflow # result. Otherwise if the actor","try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \"Failed to connect","None: raise ValueError(f\"No such workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) ->","flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\"Failed to resume workflow {wid}\") return","to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id,","store = get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID format:","workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in","workflow_manager = None if workflow_manager is None: runnings = [] else: runnings =","logger.error(f\"Failed to resume workflow {wid}\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for","status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set =","return [(wid, obj) for (wid, obj) in ret if obj is not None]","output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try:","returned output. This # ensures caller of 'run()' holds the reference to the","[id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id)","import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import","WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool","TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str]","It is important to 'ray.get' the returned output. This # ensures caller of","store.load_workflow_meta() if meta is None: raise ValueError(f\"No such workflow_id {workflow_id}\") return meta.status def","return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return","= workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\"No such workflow_id","ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\" for details. \"\"\" storage = get_global_storage()","f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\",","if meta is None: raise ValueError(f\"No such workflow_id {workflow_id}\") return meta.status def list_all(status_filter:","for r in runnings] runnings = set(runnings) # Here we don't have workflow","workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for (wid, obj)","recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a workflow asynchronously.","in runnings] runnings = set(runnings) # Here we don't have workflow id, so","len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings)","StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import (","if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as","result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return","def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed","workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): #","created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws =","s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed:","uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common","return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise","set(runnings) # Here we don't have workflow id, so use empty one instead","= get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry","else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id:","return wid, obj except Exception: logger.error(f\"Failed to resume workflow {wid}\") return (wid, None)","job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef:","ValueError as e: raise ValueError( \"Failed to connect to the workflow management \"","_resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj","\"\"\"Resume a workflow asynchronously. See \"api.resume()\" for details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming","to the workflow management \" \"actor. The workflow could have already failed. You","str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception:","Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \"\"\"Run a workflow asynchronously.","return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef","result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the output of a","flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except","result. Otherwise if the actor removes the reference of the # workflow output,","asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for (wid, obj) in","f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the","ray.ObjectRef: \"\"\"Run a workflow asynchronously. # TODO(suquark): The current \"run\" always overwrite existing","in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set","ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING store =","get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the output of a running workflow.","details. \"\"\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise","ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager =","caller may fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing))","entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is","= workflow_storage.get_workflow_storage(\"\") ret = [] for (k, s) in store.list_workflow(): if s ==","ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager =","cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store =","This # ensures caller of 'run()' holds the reference to the workflow #","\"workflow.resume() to resume the workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id,","if the actor removes the reference of the # workflow output, the caller","= True) -> ray.ObjectRef: \"\"\"Run a workflow asynchronously. # TODO(suquark): The current \"run\"","from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult","workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \"\"\"Run a workflow","to resume the workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output)","ray.ObjectRef: \"\"\"Get the output of a running workflow. See \"api.get_output()\" for details. \"\"\"","store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager =","= ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return","try: result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid,","logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool =","\"\"\"Run a workflow asynchronously. # TODO(suquark): The current \"run\" always overwrite existing workflow.","workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important","raise ValueError(f\"No such workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str,","None: # Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id =","workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds}","wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get(","output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError:","ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow,","flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) ->","workflow {wid}\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in","a workflow asynchronously. # TODO(suquark): The current \"run\" always overwrite existing workflow. #","import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite:","from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from","from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] =","await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\"Failed to","str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the output of a running workflow. See","import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from","def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id))","import asyncio import logging import time from typing import Set, List, Tuple, Optional,","except Exception as e: raise RuntimeError(\"Failed to get management actor\") from e async","if s == WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if","str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj =","output. This # ensures caller of 'run()' holds the reference to the workflow","Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \"\"\"Run a","status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings","# NOTE: It is important to 'ray.get' the returned output. This # ensures","ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData,","r in runnings] runnings = set(runnings) # Here we don't have workflow id,","ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED)","flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs.","workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \"Failed to connect to","if workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING","if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r","failed. You can use \" \"workflow.resume() to resume the workflow.\") from e output","runnings] runnings = set(runnings) # Here we don't have workflow id, so use","commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if","and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings =","ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) #","\"api.resume()\" for details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager","e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None:","# Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\"","logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow","s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings: s","time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with","def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store","asyncio import logging import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING","inputs. def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\" for","workflow. # We need to fix this later. \"\"\" store = get_global_storage() assert","return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor()","the caller may fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id,","is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter","workflow could have already failed. You can use \" \"workflow.resume() to resume the","None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and","caller may fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id,","\"Failed to connect to the workflow management \" \"actor. The workflow could have","import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType)","= {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except","-> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid,","the workflow management \" \"actor. The workflow could have already failed. You can","with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See","to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type ==","= None, overwrite: bool = True) -> ray.ObjectRef: \"\"\"Run a workflow asynchronously. #","Exception: running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta =","use \" \"workflow.resume() to resume the workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name))","is important to 'ray.get' the returned output. This # ensures caller of 'run()'","typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow","workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from","later. \"\"\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow","nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url):","= ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager","don't have workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\"\") ret","current \"run\" always overwrite existing workflow. # We need to fix this later.","a running workflow. See \"api.get_output()\" for details. \"\"\" assert ray.is_initialized() try: workflow_manager =","# workflow output, the caller may fail to resolve the result. result: \"WorkflowExecutionResult\"","format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created.","= get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running:","workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) #","\"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output)","return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the output","get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return","try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False","from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage","ValueError: workflow_manager = None if workflow_manager is None: runnings = [] else: runnings","WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager is","name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor()","return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here we","get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE: It is","from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" =","workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name:","e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = (","the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return","== 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) #","List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from","workflow asynchronously. # TODO(suquark): The current \"run\" always overwrite existing workflow. # We","WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here we don't have","Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import","ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get' the","to fix this later. \"\"\" store = get_global_storage() assert ray.is_initialized() if workflow_id is","actor removes the reference of the # workflow output, the caller may fail","WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter:","<gh_stars>0 import asyncio import logging import time from typing import Set, List, Tuple,","[(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here we don't","store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\"No such","{Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\",","WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\"No","if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str,","TODO(suquark): The current \"run\" always overwrite existing workflow. # We need to fix","to connect to the workflow management \" \"actor. The workflow could have already","filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise","assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \"Failed","\"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else:","ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None,","# TODO(suquark): The current \"run\" always overwrite existing workflow. # We need to","return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str)","= get_management_actor() except Exception as e: raise RuntimeError(\"Failed to get management actor\") from","= ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING)","workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned output.","management \" \"actor. The workflow could have already failed. You can use \"","asynchronously. # TODO(suquark): The current \"run\" always overwrite existing workflow. # We need","for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in","the # workflow output, the caller may fail to resolve the result. result:","runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter)",") -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None","(entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned output.","as e: raise ValueError( \"Failed to connect to the workflow management \" \"actor.","store = workflow_storage.get_workflow_storage(\"\") ret = [] for (k, s) in store.list_workflow(): if s","str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id)","workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output)","= None if workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote())","the actor removes the reference of the # workflow output, the caller may","(Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from","TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a","(wid, _) in all_failed])) return [(wid, obj) for (wid, obj) in ret if","-> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running","get_management_actor() except Exception as e: raise RuntimeError(\"Failed to get management actor\") from e","is None: raise ValueError(f\"No such workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus] )","all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\"Failed","overwrite: bool = True) -> ray.ObjectRef: \"\"\"Run a workflow asynchronously. # TODO(suquark): The","import logging import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import","= f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint","get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get'","job created. [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{store.storage_url}\\\"].\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws","the reference to the workflow # result. Otherwise if the actor removes the","not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return","one instead store = workflow_storage.get_workflow_storage(\"\") ret = [] for (k, s) in store.list_workflow():","actor\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\"","resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION:","= get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE: It","= (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned","workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\"\") ret = []","result.persisted_output) return wid, obj except Exception: logger.error(f\"Failed to resume workflow {wid}\") return (wid,","get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry workflow","in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings: s =","caller of 'run()' holds the reference to the workflow # result. Otherwise if","run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \"\"\"Run","workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from","get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow,","return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed:","from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output,","s == WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if s","= [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) ==","instead store = workflow_storage.get_workflow_storage(\"\") ret = [] for (k, s) in store.list_workflow(): if","-> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\" for details. \"\"\" storage =","important to 'ray.get' the returned output. This # ensures caller of 'run()' holds","RuntimeError(\"Failed to get management actor\") from e async def _resume_one(wid: str) -> Tuple[str,","resume(workflow_id: str) -> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\" for details. \"\"\"","ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager =","{wid}\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed]))","e: raise RuntimeError(\"Failed to get management actor\") from e async def _resume_one(wid: str)","ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \"Failed to","may fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False))","ret = [] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and","fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow","resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed =","'ray.get' the returned output. This # ensures caller of 'run()' holds the reference","\" \"actor. The workflow could have already failed. You can use \" \"workflow.resume()","removes the reference of the # workflow output, the caller may fail to","holds the reference to the workflow # result. Otherwise if the actor removes","for details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager =","have already failed. You can use \" \"workflow.resume() to resume the workflow.\") from","workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str)","= logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True)","= store.load_workflow_meta() if meta is None: raise ValueError(f\"No such workflow_id {workflow_id}\") return meta.status","may fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if","( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__)","We need to fix this later. \"\"\" store = get_global_storage() assert ray.is_initialized() if","Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\"{str(uuid.uuid4())}.{time.time():.9f}\" logger.info(f\"Workflow","from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor","ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for","The workflow could have already failed. You can use \" \"workflow.resume() to resume","StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with","details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor()","import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage","workflow output, the caller may fail to resolve the result. result: \"WorkflowExecutionResult\" =","flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the output of","connect to the workflow management \" \"actor. The workflow could have already failed.","running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None:","running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING","the workflow.\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id:","= ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception:","if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is","( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\"Failed","Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context","[id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get'","workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\"Failed to resume","could have already failed. You can use \" \"workflow.resume() to resume the workflow.\")","asynchronously. See \"api.resume()\" for details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\"","with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e:","reference of the # workflow output, the caller may fail to resolve the","{workflow_id}\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager =","!= StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned output. This","runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r,","StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned output. This #","\"\"\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError(","else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return","of a running workflow. See \"api.get_output()\" for details. \"\"\" assert ray.is_initialized() try: workflow_manager","\"\"\"Get the output of a running workflow. See \"api.get_output()\" for details. \"\"\" assert","Exception as e: raise RuntimeError(\"Failed to get management actor\") from e async def","result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output)","from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) ->","# Here we don't have workflow id, so use empty one instead store","store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE","\"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except","= list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\"Failed to","output, the caller may fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get(","See \"api.resume()\" for details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\", storage_url=\" f\"\\\"{storage.storage_url}\\\"].\")","def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \"WorkflowExecutionResult\" = ( await workflow_manager.run_or_resume.remote(wid))","to the workflow # result. Otherwise if the actor removes the reference of","workflow # result. Otherwise if the actor removes the reference of the #","in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings]","False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta","so use empty one instead store = workflow_storage.get_workflow_storage(\"\") ret = [] for (k,","get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]:","flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def","workflow. See \"api.get_output()\" for details. \"\"\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except","ensures caller of 'run()' holds the reference to the workflow # result. Otherwise","workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str,","get management actor\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try:","of 'run()' holds the reference to the workflow # result. Otherwise if the","def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \"\"\"Get the output of a running","from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus,","= [] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k","checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing","Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running =","bool = True) -> ray.ObjectRef: \"\"\"Run a workflow asynchronously. # TODO(suquark): The current","workflow asynchronously. See \"api.resume()\" for details. \"\"\" storage = get_global_storage() logger.info(f\"Resuming workflow [id=\\\"{workflow_id}\\\",","always overwrite existing workflow. # We need to fix this later. \"\"\" store","the caller may fail to resolve the result. result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote(","= WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool)","for details. \"\"\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e:","workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\"Failed to get management actor\")","return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id))","# We need to fix this later. \"\"\" store = get_global_storage() assert ray.is_initialized()","\"actor. The workflow could have already failed. You can use \" \"workflow.resume() to","obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\"Failed to resume workflow","running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta()","The current \"run\" always overwrite existing workflow. # We need to fix this","You can use \" \"workflow.resume() to resume the workflow.\") from e output =","ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix time","workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \"\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type","get_management_actor() except ValueError as e: raise ValueError( \"Failed to connect to the workflow","= flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\"Failed to resume workflow {wid}\")"],"string":"[\n \"result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id,\",\n \"such workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try:\",\n \"try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id:\",\n \"need to fix this later. \\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized() if workflow_id\",\n \"-> ray.ObjectRef: \\\"\\\"\\\"Get the output of a running workflow. See \\\"api.get_output()\\\" for details.\",\n \"== StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery\",\n \"workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\")\",\n \"import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor\",\n \"= get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to\",\n \"_) in all_failed])) return [(wid, obj) for (wid, obj) in ret if obj\",\n \"{workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get\",\n \"workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to\",\n \"this later. \\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None: #\",\n \"(k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings:\",\n \"runnings = set(runnings) # Here we don't have workflow id, so use empty\",\n \"result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def\",\n \"See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError\",\n \"in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret\",\n \"def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError:\",\n \"except ValueError: workflow_manager = None if workflow_manager is None: runnings = [] else:\",\n \"import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step\",\n \"ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger\",\n \"if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark):\",\n \"ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id:\",\n \"ValueError( \\\"Failed to connect to the workflow management \\\" \\\"actor. The workflow could\",\n \"e: raise ValueError( \\\"Failed to connect to the workflow management \\\" \\\"actor. The\",\n \"\\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as\",\n \"result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id,\",\n \"-> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark): The current \\\"run\\\" always overwrite\",\n \"already failed. You can use \\\" \\\"workflow.resume() to resume the workflow.\\\") from e\",\n \"except Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\") return (wid, None) ret = workflow_storage.asyncio_run(\",\n \"fix this later. \\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None:\",\n \"None, overwrite: bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark):\",\n \"TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage\",\n \"we don't have workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\")\",\n \"workflow management \\\" \\\"actor. The workflow could have already failed. You can use\",\n \"k not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s))\",\n \"-> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try:\",\n \"entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support\",\n \"logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) ->\",\n \"assert ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix\",\n \"fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type\",\n \"[] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not\",\n \"async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = ( await\",\n \"resume the workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def\",\n \"# checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor()\",\n \"= get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned output. This\",\n \"ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job\",\n \"storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get' the\",\n \"the output of a running workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized()\",\n \"list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager\",\n \"= False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if\",\n \"[] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1:\",\n \"use empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k, s)\",\n \"import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import\",\n \"ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import\",\n \"workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None: runnings\",\n \"UUID}.{Unix time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\")\",\n \"obj except Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\") return (wid, None) ret =\",\n \"ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import\",\n \"result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef:\",\n \"workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager\",\n \"meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except\",\n \"empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k, s) in\",\n \"output of a running workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized() try:\",\n \"running workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager = get_management_actor()\",\n \"except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager\",\n \"ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str])\",\n \"filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor()\",\n \"get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned output. This #\",\n \"have workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret =\",\n \"get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except\",\n \"import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import\",\n \"time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray\",\n \"ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor,\",\n \"name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output of a running workflow. See \\\"api.get_output()\\\"\",\n \"s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]:\",\n \"\\\" \\\"workflow.resume() to resume the workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return\",\n \"WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) ->\",\n \"Otherwise if the actor removes the reference of the # workflow output, the\",\n \"meta is None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus]\",\n \"workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if\",\n \"= get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None: runnings =\",\n \"raise RuntimeError(\\\"Failed to get management actor\\\") from e async def _resume_one(wid: str) ->\",\n \"ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\"\",\n \"and k not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k,\",\n \"# result. Otherwise if the actor removes the reference of the # workflow\",\n \"ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from\",\n \"the reference of the # workflow output, the caller may fail to resolve\",\n \"of the # workflow output, the caller may fail to resolve the result.\",\n \"storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE:\",\n \"try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None:\",\n \"str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage\",\n \"ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type !=\",\n \"workflow UUID}.{Unix time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\"\",\n \"except Exception: running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta\",\n \"the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing =\",\n \"logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE: It is important\",\n \"logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) ->\",\n \"list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\\\"Failed to get\",\n \"a workflow asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow\",\n \"get_management_actor() except ValueError: workflow_manager = None if workflow_manager is None: runnings = []\",\n \"= workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for (wid,\",\n \"existing workflow. # We need to fix this later. \\\"\\\"\\\" store = get_global_storage()\",\n \"\\\"run\\\" always overwrite existing workflow. # We need to fix this later. \\\"\\\"\\\"\",\n \"Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid)\",\n \"# TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume\",\n \"to 'ray.get' the returned output. This # ensures caller of 'run()' holds the\",\n \"None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj)\",\n \"is None: # Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id\",\n \"NOTE: It is important to 'ray.get' the returned output. This # ensures caller\",\n \"1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here\",\n \"(wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid,\",\n \"import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger =\",\n \"from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING:\",\n \"can use \\\" \\\"workflow.resume() to resume the workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id,\",\n \"wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor()\",\n \"\\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID\",\n \"def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef:\",\n \"\\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() #\",\n \"= workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running\",\n \"runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def\",\n \"if workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix time to\",\n \"reference to the workflow # result. Otherwise if the actor removes the reference\",\n \"resume workflow {wid}\\\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _)\",\n \"None if workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if\",\n \"in all_failed])) return [(wid, obj) for (wid, obj) in ret if obj is\",\n \"with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow)\",\n \"import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor)\",\n \"Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return\",\n \"to get management actor\\\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]:\",\n \"ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]:\",\n \"# ensures caller of 'run()' holds the reference to the workflow # result.\",\n \"= get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) ->\",\n \"workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id)\",\n \"{WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception\",\n \"-> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if\",\n \"= ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def\",\n \"== WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if s in\",\n \"Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output)\",\n \"get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import\",\n \"WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in\",\n \"storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws,\",\n \"WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import\",\n \"workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager\",\n \"result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj\",\n \"Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output of a running workflow. See \\\"api.get_output()\\\" for\",\n \"for (wid, _) in all_failed])) return [(wid, obj) for (wid, obj) in ret\",\n \"overwrite existing workflow. # We need to fix this later. \\\"\\\"\\\" store =\",\n \"ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE}\",\n \"workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str)\",\n \"= get_management_actor() except ValueError as e: raise ValueError( \\\"Failed to connect to the\",\n \"commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE:\",\n \"bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set)\",\n \"to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job\",\n \"management actor\\\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result:\",\n \"get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow:\",\n \"True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark): The current \\\"run\\\" always\",\n \"all_failed])) return [(wid, obj) for (wid, obj) in ret if obj is not\",\n \"-> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED))\",\n \"try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\\\"Failed to get management\",\n \"List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager\",\n \"f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned\",\n \"the workflow # result. Otherwise if the actor removes the reference of the\",\n \"def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\" for details.\",\n \"= ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING store\",\n \"ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for\",\n \"ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id,\",\n \"workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING\",\n \"support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow\",\n \"s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if\",\n \"except ValueError as e: raise ValueError( \\\"Failed to connect to the workflow management\",\n \"as e: raise RuntimeError(\\\"Failed to get management actor\\\") from e async def _resume_one(wid:\",\n \"id, so use empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for\",\n \"= set(runnings) # Here we don't have workflow id, so use empty one\",\n \"\\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It\",\n \"resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the\",\n \"meta = store.load_workflow_meta() if meta is None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return\",\n \"Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow\",\n \"the returned output. This # ensures caller of 'run()' holds the reference to\",\n \"to resume workflow {wid}\\\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid,\",\n \"ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try:\",\n \"if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id:\",\n \"None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def\",\n \"the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\")\",\n \"logging import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid\",\n \"WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access\",\n \"workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running =\",\n \"Here we don't have workflow id, so use empty one instead store =\",\n \"Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager =\",\n \"resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id}\",\n \"wid, obj except Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\") return (wid, None) ret\",\n \"List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager\",\n \"raise ValueError( \\\"Failed to connect to the workflow management \\\" \\\"actor. The workflow\",\n \"= workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION)\",\n \"'run()' holds the reference to the workflow # result. Otherwise if the actor\",\n \"try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \\\"Failed to connect\",\n \"None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) ->\",\n \"flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\") return\",\n \"to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id,\",\n \"store = get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID format:\",\n \"workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in\",\n \"workflow_manager = None if workflow_manager is None: runnings = [] else: runnings =\",\n \"logger.error(f\\\"Failed to resume workflow {wid}\\\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for\",\n \"status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set =\",\n \"return [(wid, obj) for (wid, obj) in ret if obj is not None]\",\n \"output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try:\",\n \"returned output. This # ensures caller of 'run()' holds the reference to the\",\n \"[id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id)\",\n \"import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import\",\n \"WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool\",\n \"TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str]\",\n \"It is important to 'ray.get' the returned output. This # ensures caller of\",\n \"store.load_workflow_meta() if meta is None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status def\",\n \"return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return\",\n \"= workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\\\"No such workflow_id\",\n \"ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage = get_global_storage()\",\n \"f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\",\",\n \"if meta is None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter:\",\n \"for r in runnings] runnings = set(runnings) # Here we don't have workflow\",\n \"workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for (wid, obj)\",\n \"recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously.\",\n \"in runnings] runnings = set(runnings) # Here we don't have workflow id, so\",\n \"len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings)\",\n \"StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import (\",\n \"if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as\",\n \"result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return\",\n \"def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed\",\n \"workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): #\",\n \"created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws =\",\n \"s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed:\",\n \"uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common\",\n \"return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise\",\n \"set(runnings) # Here we don't have workflow id, so use empty one instead\",\n \"= get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry\",\n \"else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id:\",\n \"return wid, obj except Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\") return (wid, None)\",\n \"job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef:\",\n \"ValueError as e: raise ValueError( \\\"Failed to connect to the workflow management \\\"\",\n \"_resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj\",\n \"\\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming\",\n \"to the workflow management \\\" \\\"actor. The workflow could have already failed. You\",\n \"str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception:\",\n \"Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously.\",\n \"return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef\",\n \"result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output of a\",\n \"flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except\",\n \"result. Otherwise if the actor removes the reference of the # workflow output,\",\n \"asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for (wid, obj) in\",\n \"f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the\",\n \"ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark): The current \\\"run\\\" always overwrite existing\",\n \"in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set\",\n \"ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING store =\",\n \"get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output of a running workflow.\",\n \"details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise\",\n \"ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager =\",\n \"caller may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing))\",\n \"entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is\",\n \"= workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k, s) in store.list_workflow(): if s ==\",\n \"ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager =\",\n \"cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store =\",\n \"This # ensures caller of 'run()' holds the reference to the workflow #\",\n \"\\\"workflow.resume() to resume the workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id,\",\n \"if the actor removes the reference of the # workflow output, the caller\",\n \"= True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark): The current \\\"run\\\"\",\n \"from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult\",\n \"workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow\",\n \"to resume the workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output)\",\n \"ray.ObjectRef: \\\"\\\"\\\"Get the output of a running workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\"\",\n \"store.storage_url): # checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager =\",\n \"= ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return\",\n \"try: result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid,\",\n \"logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool =\",\n \"\\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark): The current \\\"run\\\" always overwrite existing workflow.\",\n \"workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important\",\n \"raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str,\",\n \"None: # Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id =\",\n \"workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds}\",\n \"wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get(\",\n \"output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError:\",\n \"ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow,\",\n \"flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) ->\",\n \"workflow {wid}\\\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in\",\n \"a workflow asynchronously. # TODO(suquark): The current \\\"run\\\" always overwrite existing workflow. #\",\n \"import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite:\",\n \"from typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from\",\n \"from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] =\",\n \"await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\\\"Failed to\",\n \"str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output of a running workflow. See\",\n \"import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from\",\n \"def get_status(workflow_id: str) -> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id))\",\n \"import asyncio import logging import time from typing import Set, List, Tuple, Optional,\",\n \"except Exception as e: raise RuntimeError(\\\"Failed to get management actor\\\") from e async\",\n \"if s == WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if\",\n \"str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj =\",\n \"output. This # ensures caller of 'run()' holds the reference to the workflow\",\n \"Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run a\",\n \"status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings\",\n \"# NOTE: It is important to 'ray.get' the returned output. This # ensures\",\n \"ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData,\",\n \"r in runnings] runnings = set(runnings) # Here we don't have workflow id,\",\n \"ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED)\",\n \"flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs.\",\n \"workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \\\"Failed to connect to\",\n \"if workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING\",\n \"if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r\",\n \"failed. You can use \\\" \\\"workflow.resume() to resume the workflow.\\\") from e output\",\n \"runnings] runnings = set(runnings) # Here we don't have workflow id, so use\",\n \"commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if\",\n \"and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings =\",\n \"ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) #\",\n \"\\\"api.resume()\\\" for details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager\",\n \"e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None:\",\n \"# Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\"\",\n \"logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow\",\n \"s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings: s\",\n \"time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with\",\n \"def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store\",\n \"asyncio import logging import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING\",\n \"inputs. def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\" for\",\n \"workflow. # We need to fix this later. \\\"\\\"\\\" store = get_global_storage() assert\",\n \"return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor()\",\n \"the caller may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id,\",\n \"is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter\",\n \"workflow could have already failed. You can use \\\" \\\"workflow.resume() to resume the\",\n \"None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and\",\n \"caller may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id,\",\n \"\\\"Failed to connect to the workflow management \\\" \\\"actor. The workflow could have\",\n \"import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType)\",\n \"= {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except\",\n \"-> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid,\",\n \"the workflow management \\\" \\\"actor. The workflow could have already failed. You can\",\n \"with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See\",\n \"to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type ==\",\n \"= None, overwrite: bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. #\",\n \"Exception: running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta =\",\n \"use \\\" \\\"workflow.resume() to resume the workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name))\",\n \"is important to 'ray.get' the returned output. This # ensures caller of 'run()'\",\n \"typing import Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow\",\n \"workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from\",\n \"later. \\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow\",\n \"nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url):\",\n \"= ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager\",\n \"don't have workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret\",\n \"current \\\"run\\\" always overwrite existing workflow. # We need to fix this later.\",\n \"a running workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager =\",\n \"# workflow output, the caller may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\"\",\n \"format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created.\",\n \"= get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running:\",\n \"workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) #\",\n \"\\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output)\",\n \"return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output\",\n \"get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return\",\n \"try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False\",\n \"from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage\",\n \"ValueError: workflow_manager = None if workflow_manager is None: runnings = [] else: runnings\",\n \"WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None if workflow_manager is\",\n \"name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor()\",\n \"return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here we\",\n \"get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE: It is\",\n \"from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" =\",\n \"workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name:\",\n \"e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = (\",\n \"the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return\",\n \"== 1: return [(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) #\",\n \"List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from\",\n \"workflow asynchronously. # TODO(suquark): The current \\\"run\\\" always overwrite existing workflow. # We\",\n \"WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here we don't have\",\n \"Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context from ray.experimental.workflow import\",\n \"ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get' the\",\n \"to fix this later. \\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized() if workflow_id is\",\n \"actor removes the reference of the # workflow output, the caller may fail\",\n \"WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter:\",\n \"<gh_stars>0 import asyncio import logging import time from typing import Set, List, Tuple,\",\n \"[(r, WorkflowStatus.RUNNING) for r in runnings] runnings = set(runnings) # Here we don't\",\n \"store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\\\"No such\",\n \"{Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\",\",\n \"WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None: raise ValueError(f\\\"No\",\n \"if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool) -> List[Tuple[str,\",\n \"TODO(suquark): The current \\\"run\\\" always overwrite existing workflow. # We need to fix\",\n \"to connect to the workflow management \\\" \\\"actor. The workflow could have already\",\n \"filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise\",\n \"assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \\\"Failed\",\n \"\\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else:\",\n \"ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None,\",\n \"# TODO(suquark): The current \\\"run\\\" always overwrite existing workflow. # We need to\",\n \"return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str)\",\n \"= get_management_actor() except Exception as e: raise RuntimeError(\\\"Failed to get management actor\\\") from\",\n \"= ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING)\",\n \"workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get' the returned output.\",\n \"management \\\" \\\"actor. The workflow could have already failed. You can use \\\"\",\n \"asynchronously. # TODO(suquark): The current \\\"run\\\" always overwrite existing workflow. # We need\",\n \"for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in\",\n \"the # workflow output, the caller may fail to resolve the result. result:\",\n \"runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter)\",\n \") -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager = get_management_actor() except ValueError: workflow_manager = None\",\n \"(entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned output.\",\n \"as e: raise ValueError( \\\"Failed to connect to the workflow management \\\" \\\"actor.\",\n \"store = workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k, s) in store.list_workflow(): if s\",\n \"str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id)\",\n \"workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output)\",\n \"= None if workflow_manager is None: runnings = [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote())\",\n \"the actor removes the reference of the # workflow output, the caller may\",\n \"(Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from\",\n \"TODO(suquark): support recovery with ObjectRef inputs. def resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a\",\n \"(wid, _) in all_failed])) return [(wid, obj) for (wid, obj) in ret if\",\n \"-> Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running\",\n \"get_management_actor() except Exception as e: raise RuntimeError(\\\"Failed to get management actor\\\") from e\",\n \"is None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus] )\",\n \"all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\\\"Failed\",\n \"overwrite: bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark): The\",\n \"import logging import time from typing import Set, List, Tuple, Optional, TYPE_CHECKING import\",\n \"= f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint\",\n \"get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get'\",\n \"job created. [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{store.storage_url}\\\\\\\"].\\\") with workflow_context.workflow_step_context(workflow_id, store.storage_url): # checkpoint the workflow ws\",\n \"the reference to the workflow # result. Otherwise if the actor removes the\",\n \"not in runnings: s = WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return\",\n \"one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k, s) in store.list_workflow():\",\n \"actor\\\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\"\",\n \"resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION:\",\n \"= get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE: It\",\n \"= (entry_workflow.data.step_type != StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned\",\n \"workflow id, so use empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret = []\",\n \"result.persisted_output) return wid, obj except Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\") return (wid,\",\n \"get_global_storage() assert ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry workflow\",\n \"in store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings: s =\",\n \"caller of 'run()' holds the reference to the workflow # result. Otherwise if\",\n \"run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run\",\n \"workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from\",\n \"get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def run(entry_workflow: Workflow,\",\n \"return ret def resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed:\",\n \"from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage from ray.experimental.workflow.workflow_access import ( flatten_workflow_output,\",\n \"s == WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE if s\",\n \"= [] else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) ==\",\n \"instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k, s) in store.list_workflow(): if\",\n \"-> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage =\",\n \"important to 'ray.get' the returned output. This # ensures caller of 'run()' holds\",\n \"RuntimeError(\\\"Failed to get management actor\\\") from e async def _resume_one(wid: str) -> Tuple[str,\",\n \"resume(workflow_id: str) -> ray.ObjectRef: \\\"\\\"\\\"Resume a workflow asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\"\",\n \"ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager =\",\n \"{wid}\\\") return (wid, None) ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed]))\",\n \"e: raise RuntimeError(\\\"Failed to get management actor\\\") from e async def _resume_one(wid: str)\",\n \"ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError( \\\"Failed to\",\n \"may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False))\",\n \"ret = [] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and\",\n \"fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow\",\n \"resume_all(with_failed: bool) -> List[Tuple[str, ray.ObjectRef]]: filter_set = {WorkflowStatus.RESUMABLE} if with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed =\",\n \"'ray.get' the returned output. This # ensures caller of 'run()' holds the reference\",\n \"\\\" \\\"actor. The workflow could have already failed. You can use \\\" \\\"workflow.resume()\",\n \"removes the reference of the # workflow output, the caller may fail to\",\n \"holds the reference to the workflow # result. Otherwise if the actor removes\",\n \"for details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager =\",\n \"have already failed. You can use \\\" \\\"workflow.resume() to resume the workflow.\\\") from\",\n \"workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str)\",\n \"= logging.getLogger(__name__) def run(entry_workflow: Workflow, workflow_id: Optional[str] = None, overwrite: bool = True)\",\n \"= store.load_workflow_meta() if meta is None: raise ValueError(f\\\"No such workflow_id {workflow_id}\\\") return meta.status\",\n \"may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if\",\n \"( flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__)\",\n \"We need to fix this later. \\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized() if\",\n \"Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds} workflow_id = f\\\"{str(uuid.uuid4())}.{time.time():.9f}\\\" logger.info(f\\\"Workflow\",\n \"from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor\",\n \"ret = workflow_storage.asyncio_run( asyncio.gather(*[_resume_one(wid) for (wid, _) in all_failed])) return [(wid, obj) for\",\n \"The workflow could have already failed. You can use \\\" \\\"workflow.resume() to resume\",\n \"StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output) else: return flatten_workflow_output(workflow_id, result.volatile_output) # TODO(suquark): support recovery with\",\n \"details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor()\",\n \"import (Workflow, WorkflowStatus, WorkflowMetaData, StepType) from ray.experimental.workflow.step_executor import commit_step from ray.experimental.workflow.storage import get_global_storage\",\n \"workflow output, the caller may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" =\",\n \"flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output of\",\n \"connect to the workflow management \\\" \\\"actor. The workflow could have already failed.\",\n \"running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is None:\",\n \"running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running = False if running: return WorkflowStatus.RUNNING\",\n \"the workflow.\\\") from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id:\",\n \"= ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception:\",\n \"if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta is\",\n \"( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\\\"Failed\",\n \"Set, List, Tuple, Optional, TYPE_CHECKING import uuid import ray from ray.experimental.workflow import workflow_context\",\n \"[id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\") workflow_manager = get_or_create_management_actor() # NOTE: It is important to 'ray.get'\",\n \"workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\\\"Failed to resume\",\n \"could have already failed. You can use \\\" \\\"workflow.resume() to resume the workflow.\\\")\",\n \"asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\"\",\n \"with_failed: filter_set.add(WorkflowStatus.FAILED) all_failed = list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e:\",\n \"reference of the # workflow output, the caller may fail to resolve the\",\n \"{workflow_id}\\\") return meta.status def list_all(status_filter: Set[WorkflowStatus] ) -> List[Tuple[str, WorkflowStatus]]: try: workflow_manager =\",\n \"!= StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned output. This\",\n \"runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return [(r,\",\n \"StepType.FUNCTION) # NOTE: It is important to 'ray.get' the returned output. This #\",\n \"\\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e: raise ValueError(\",\n \"else: runnings = ray.get(workflow_manager.list_running_workflow.remote()) if WorkflowStatus.RUNNING in status_filter and len(status_filter) == 1: return\",\n \"of a running workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager\",\n \"\\\"\\\"\\\"Get the output of a running workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert\",\n \"Exception as e: raise RuntimeError(\\\"Failed to get management actor\\\") from e async def\",\n \"result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(workflow_id, ignore_existing)) if entry_workflow.data.step_type == StepType.FUNCTION: return flatten_workflow_output(workflow_id, result.persisted_output)\",\n \"from e output = ray.get(workflow_manager.get_output.remote(workflow_id, name)) return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) ->\",\n \"# Here we don't have workflow id, so use empty one instead store\",\n \"store.list_workflow(): if s == WorkflowStatus.RUNNING and k not in runnings: s = WorkflowStatus.RESUMABLE\",\n \"\\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid)) obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except\",\n \"= list_all(filter_set) try: workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\\\"Failed to\",\n \"output, the caller may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get(\",\n \"See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\", storage_url=\\\" f\\\"\\\\\\\"{storage.storage_url}\\\\\\\"].\\\")\",\n \"def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try: result: \\\"WorkflowExecutionResult\\\" = ( await workflow_manager.run_or_resume.remote(wid))\",\n \"to the workflow # result. Otherwise if the actor removes the reference of\",\n \"workflow # result. Otherwise if the actor removes the reference of the #\",\n \"in status_filter and len(status_filter) == 1: return [(r, WorkflowStatus.RUNNING) for r in runnings]\",\n \"False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta() if meta\",\n \"so use empty one instead store = workflow_storage.get_workflow_storage(\\\"\\\") ret = [] for (k,\",\n \"get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id)) except ValueError: wf_store = workflow_storage.get_workflow_storage(workflow_id) wf_store.save_workflow_meta(WorkflowMetaData(WorkflowStatus.CANCELED)) def get_status(workflow_id: str) -> Optional[WorkflowStatus]:\",\n \"flatten_workflow_output, get_or_create_management_actor, get_management_actor) if TYPE_CHECKING: from ray.experimental.workflow.step_executor import WorkflowExecutionResult logger = logging.getLogger(__name__) def\",\n \"workflow. See \\\"api.get_output()\\\" for details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except\",\n \"ensures caller of 'run()' holds the reference to the workflow # result. Otherwise\",\n \"workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\\\"Workflow job {workflow_id} resumed.\\\") return flatten_workflow_output(workflow_id, result.persisted_output) def get_output(workflow_id: str,\",\n \"get management actor\\\") from e async def _resume_one(wid: str) -> Tuple[str, Optional[ray.ObjectRef]]: try:\",\n \"of 'run()' holds the reference to the workflow # result. Otherwise if the\",\n \"def get_output(workflow_id: str, name: Optional[str]) -> ray.ObjectRef: \\\"\\\"\\\"Get the output of a running\",\n \"from ray.experimental.workflow import workflow_context from ray.experimental.workflow import workflow_storage from ray.experimental.workflow.common import (Workflow, WorkflowStatus,\",\n \"= [] for (k, s) in store.list_workflow(): if s == WorkflowStatus.RUNNING and k\",\n \"checkpoint the workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing\",\n \"Optional[WorkflowStatus]: try: workflow_manager = get_management_actor() running = ray.get( workflow_manager.is_workflow_running.remote(workflow_id)) except Exception: running =\",\n \"bool = True) -> ray.ObjectRef: \\\"\\\"\\\"Run a workflow asynchronously. # TODO(suquark): The current\",\n \"workflow asynchronously. See \\\"api.resume()\\\" for details. \\\"\\\"\\\" storage = get_global_storage() logger.info(f\\\"Resuming workflow [id=\\\\\\\"{workflow_id}\\\\\\\",\",\n \"always overwrite existing workflow. # We need to fix this later. \\\"\\\"\\\" store\",\n \"the caller may fail to resolve the result. result: \\\"WorkflowExecutionResult\\\" = ray.get( workflow_manager.run_or_resume.remote(\",\n \"= WorkflowStatus.RESUMABLE if s in status_filter: ret.append((k, s)) return ret def resume_all(with_failed: bool)\",\n \"for details. \\\"\\\"\\\" assert ray.is_initialized() try: workflow_manager = get_management_actor() except ValueError as e:\",\n \"workflow_manager = get_management_actor() except Exception as e: raise RuntimeError(\\\"Failed to get management actor\\\")\",\n \"return flatten_workflow_output(workflow_id, output) def cancel(workflow_id: str) -> None: try: workflow_manager = get_management_actor() ray.get(workflow_manager.cancel_workflow.remote(workflow_id))\",\n \"# We need to fix this later. \\\"\\\"\\\" store = get_global_storage() assert ray.is_initialized()\",\n \"\\\"actor. The workflow could have already failed. You can use \\\" \\\"workflow.resume() to\",\n \"obj = flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\\\"Failed to resume workflow\",\n \"running = False if running: return WorkflowStatus.RUNNING store = workflow_storage.get_workflow_storage(workflow_id) meta = store.load_workflow_meta()\",\n \"The current \\\"run\\\" always overwrite existing workflow. # We need to fix this\",\n \"You can use \\\" \\\"workflow.resume() to resume the workflow.\\\") from e output =\",\n \"ray.is_initialized() if workflow_id is None: # Workflow ID format: {Entry workflow UUID}.{Unix time\",\n \"workflow ws = workflow_storage.get_workflow_storage(workflow_id) commit_step(ws, \\\"\\\", entry_workflow) workflow_manager = get_or_create_management_actor() ignore_existing = (entry_workflow.data.step_type\",\n \"get_management_actor() except ValueError as e: raise ValueError( \\\"Failed to connect to the workflow\",\n \"= flatten_workflow_output(wid, result.persisted_output) return wid, obj except Exception: logger.error(f\\\"Failed to resume workflow {wid}\\\")\"\n]","isConversational":false}}},{"rowIdx":86,"cells":{"ngram":{"kind":"list like","value":["from .compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature #",".compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature # noqa","from .signature import BinarySignature, Signature, MemorySignature # noqa from .username import UsernameToken #","Compose # noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from .username","noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from .username import UsernameToken","<reponame>bertonha/python-zeep from .compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature","# noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from .username import","import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from",".signature import BinarySignature, Signature, MemorySignature # noqa from .username import UsernameToken # noqa"],"string":"[\n \"from .compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature #\",\n \".compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature # noqa\",\n \"from .signature import BinarySignature, Signature, MemorySignature # noqa from .username import UsernameToken #\",\n \"Compose # noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from .username\",\n \"noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from .username import UsernameToken\",\n \"<reponame>bertonha/python-zeep from .compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature\",\n \"# noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from .username import\",\n \"import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature # noqa from\",\n \".signature import BinarySignature, Signature, MemorySignature # noqa from .username import UsernameToken # noqa\"\n]","isConversational":false}}},{"rowIdx":87,"cells":{"ngram":{"kind":"list like","value":["1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return","y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T","= u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt","f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan):","(1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10,","k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)):","return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:]","import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11","<reponame>peteboi/Python-Scripts<gh_stars>0 # -*- coding: utf-8 -*- import numpy as np import matplotlib.pyplot as","RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for","dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T plt.grid()","orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def","-*- coding: utf-8 -*- import numpy as np import matplotlib.pyplot as plt def","M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def","u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] =","for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t =","def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0","-*- import numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y =","return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y =","x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt):","numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y)","np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:]","k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt)","utf-8 -*- import numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y","= RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t)","y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1","=y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t","y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10])","as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3","k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range","RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y","import numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u","matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110","def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1])","y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y","r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt","#r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt","as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r=","k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k","= np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T plt.grid() plt.plot(x,y) plt.show()","coding: utf-8 -*- import numpy as np import matplotlib.pyplot as plt def orbit(u):","return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)])","t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T plt.grid() plt.plot(x,y)","plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return","in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10,","range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0,","def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y])","RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return","np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06","u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt","# -*- coding: utf-8 -*- import numpy as np import matplotlib.pyplot as plt","#M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6","k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in"],"string":"[\n \"1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return\",\n \"y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T\",\n \"= u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt\",\n \"f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan):\",\n \"(1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10,\",\n \"k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)):\",\n \"return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:]\",\n \"import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11\",\n \"<reponame>peteboi/Python-Scripts<gh_stars>0 # -*- coding: utf-8 -*- import numpy as np import matplotlib.pyplot as\",\n \"RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for\",\n \"dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T plt.grid()\",\n \"orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def\",\n \"-*- coding: utf-8 -*- import numpy as np import matplotlib.pyplot as plt def\",\n \"M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def\",\n \"u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] =\",\n \"for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t =\",\n \"def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0\",\n \"-*- import numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y =\",\n \"return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y =\",\n \"x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt):\",\n \"numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y)\",\n \"np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:]\",\n \"k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt)\",\n \"utf-8 -*- import numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y\",\n \"= RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t)\",\n \"y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1\",\n \"=y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t\",\n \"y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10])\",\n \"as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3\",\n \"k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range\",\n \"RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y\",\n \"import numpy as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u\",\n \"matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110\",\n \"def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1])\",\n \"y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y\",\n \"r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt\",\n \"#r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt\",\n \"as np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r=\",\n \"k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k\",\n \"= np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T plt.grid() plt.plot(x,y) plt.show()\",\n \"coding: utf-8 -*- import numpy as np import matplotlib.pyplot as plt def orbit(u):\",\n \"return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)])\",\n \"t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T plt.grid() plt.plot(x,y)\",\n \"plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return\",\n \"in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10,\",\n \"range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0,\",\n \"def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y])\",\n \"RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range (1,len(tspan)): y[k,:] = RK4(f,y[k-1],tspan[k]-tspan[k-1]) return\",\n \"np import matplotlib.pyplot as plt def orbit(u): x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06\",\n \"u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt\",\n \"# -*- coding: utf-8 -*- import numpy as np import matplotlib.pyplot as plt\",\n \"#M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6\",\n \"k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in\"\n]","isConversational":false}}},{"rowIdx":88,"cells":{"ngram":{"kind":"list like","value":["factories for all installed apps' def handle(self, *args, **options): created_files = [] for","apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in","<reponame>gamabounty/django-factory-generator import os from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator","import os from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import","factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all installed","= FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('-","+= factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('- ' + created_file))","FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all installed apps' def","FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('- '","installed apps' def handle(self, *args, **options): created_files = [] for app in apps.get_app_configs():","created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files()","for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:'))","'Create model factories for all installed apps' def handle(self, *args, **options): created_files =","= [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully","django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand):","all installed apps' def handle(self, *args, **options): created_files = [] for app in","import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all installed apps'","from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all","app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for","factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files:","help = 'Create model factories for all installed apps' def handle(self, *args, **options):","apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help =","Command(BaseCommand): help = 'Create model factories for all installed apps' def handle(self, *args,","for all installed apps' def handle(self, *args, **options): created_files = [] for app","class Command(BaseCommand): help = 'Create model factories for all installed apps' def handle(self,","def handle(self, *args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator =","*args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files","[] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created","handle(self, *args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app)","django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model","in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file","created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('- ' +","**options): created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files +=","import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help","from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create","from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class","import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories","model factories for all installed apps' def handle(self, *args, **options): created_files = []","BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for","= 'Create model factories for all installed apps' def handle(self, *args, **options): created_files","apps' def handle(self, *args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator","os from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator"],"string":"[\n \"factories for all installed apps' def handle(self, *args, **options): created_files = [] for\",\n \"apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in\",\n \"<reponame>gamabounty/django-factory-generator import os from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator\",\n \"import os from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import\",\n \"factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all installed\",\n \"= FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('-\",\n \"+= factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('- ' + created_file))\",\n \"FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all installed apps' def\",\n \"FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('- '\",\n \"installed apps' def handle(self, *args, **options): created_files = [] for app in apps.get_app_configs():\",\n \"created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files()\",\n \"for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:'))\",\n \"'Create model factories for all installed apps' def handle(self, *args, **options): created_files =\",\n \"= [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully\",\n \"django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand):\",\n \"all installed apps' def handle(self, *args, **options): created_files = [] for app in\",\n \"import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all installed apps'\",\n \"from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for all\",\n \"app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for\",\n \"factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files:\",\n \"help = 'Create model factories for all installed apps' def handle(self, *args, **options):\",\n \"apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help =\",\n \"Command(BaseCommand): help = 'Create model factories for all installed apps' def handle(self, *args,\",\n \"for all installed apps' def handle(self, *args, **options): created_files = [] for app\",\n \"class Command(BaseCommand): help = 'Create model factories for all installed apps' def handle(self,\",\n \"def handle(self, *args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator =\",\n \"*args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files\",\n \"[] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created\",\n \"handle(self, *args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app)\",\n \"django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model\",\n \"in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file\",\n \"created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file in created_files: self.stdout.write(self.style.SUCCESS('- ' +\",\n \"**options): created_files = [] for app in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files +=\",\n \"import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help\",\n \"from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create\",\n \"from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator class\",\n \"import BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories\",\n \"model factories for all installed apps' def handle(self, *args, **options): created_files = []\",\n \"BaseCommand from factory_generator.generator import FactoryAppGenerator class Command(BaseCommand): help = 'Create model factories for\",\n \"= 'Create model factories for all installed apps' def handle(self, *args, **options): created_files\",\n \"apps' def handle(self, *args, **options): created_files = [] for app in apps.get_app_configs(): factory_app_generator\",\n \"os from django.apps import apps from django.core.management.base import BaseCommand from factory_generator.generator import FactoryAppGenerator\"\n]","isConversational":false}}},{"rowIdx":89,"cells":{"ngram":{"kind":"list like","value":["chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix =","lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes > 1","h5 diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using ( in","NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb,","{'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) #","def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out","= [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in","in h5 clustering_h5, in bool skip, in int random_seed, in int max_clusters, out","cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants","big jobs more threads in order to avoid overloading a node threads =","'__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs):","= matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as","for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) #","as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as","cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants","( in string clustering_key, ) \"\"\" def split(args): if args.skip: return {'chunks': [{'__mem_gb':","one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB))","split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add","cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE)","= [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs]","4 #TODO Not clear why this stage takes > 1 thread. Martian thinks","in string clustering_key, ) \"\"\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]}","threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key':","chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP,","Copyright (c) 2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as","skip, in int random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv,",") \"\"\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = []","in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks,","- give big jobs more threads in order to avoid overloading a node","# # Copyright (c) 2017 10X Genomics, Inc. All rights reserved. # import","using ( in string clustering_key, ) \"\"\" def split(args): if args.skip: return {'chunks':","src py \"stages/analyzer/run_differential_expression\", ) split using ( in string clustering_key, ) \"\"\" def","return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons","def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only","in h5 matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed, in","4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, })","as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as","cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io","out h5 diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using (","overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in","cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if","more threads in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN)","chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in","import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import","cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants","h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io","NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes > 1 thread.","= cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features matrix =","{'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons unknown","stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip, in int","outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for","as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4","= [] # FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 *","if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv","clustering_h5, in bool skip, in int random_seed, in int max_clusters, out h5 diffexp_h5,","Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io","# FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb","{'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix","avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key","= \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip,","import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import","threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if","int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split","= int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in order","cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv)","diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return","#!/usr/bin/env python # # Copyright (c) 2017 10X Genomics, Inc. All rights reserved.","and kills it on long jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5","main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute","does and kills it on long jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in","analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs,","}) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip:","out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using ( in string clustering_key,","= cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix,","2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import","#TODO Not clear why this stage takes > 1 thread. Martian thinks it","it does and kills it on long jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION(","rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome","matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features matrix","import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not","max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using","as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why","cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix","= 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big","in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads =","'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5)","For now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering =","import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import","split using ( in string clustering_key, ) \"\"\" def split(args): if args.skip: return","return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return","1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs","f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs):","python # # Copyright (c) 2017 10X Genomics, Inc. All rights reserved. #","min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb':","HACK - give big jobs more threads in order to avoid overloading a","SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp)","import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import","diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using ( in string clustering_key, ) \"\"\"","(c) 2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp","random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\",","h5 clustering_h5, in bool skip, in int random_seed, in int max_clusters, out h5","= 4 #TODO Not clear why this stage takes > 1 thread. Martian","as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes >","outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs]","threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads':","__MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool","analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants",") split using ( in string clustering_key, ) \"\"\" def split(args): if args.skip:","takes > 1 thread. Martian thinks it does and kills it on long","chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in","Not clear why this stage takes > 1 thread. Martian thinks it does","'__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def","why this stage takes > 1 thread. Martian thinks it does and kills","\"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip, in","matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5","in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs: cr_io.copytree(csv_dir, outs.diffexp_csv, allow_existing=True)","thread. Martian thinks it does and kills it on long jobs __MRO__ =","\"\"\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] #","args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for","# For now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering","Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as","for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return","outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for","h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in order to avoid","long jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5,","args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for","= min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key,","<reponame>qiangli/cellranger<filename>mro/stages/analyzer/run_differential_expression/__init__.py #!/usr/bin/env python # # Copyright (c) 2017 10X Genomics, Inc. All rights","matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give","# HACK - give big jobs more threads in order to avoid overloading","chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs: cr_io.copytree(csv_dir, outs.diffexp_csv,","return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features","# Copyright (c) 2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp","import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage","[{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons unknown matrix_mem_gb","= 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads,","args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression","matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f:","cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN =","path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using ( in string clustering_key, )","if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one","in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", )","chunks = [] # FIXME: Add one for reasons unknown matrix_mem_gb = 1.8","matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5)","in int random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src","[chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s,","node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({","for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs: cr_io.copytree(csv_dir,","clustering_key, ) \"\"\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks =","SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join':","def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME:","a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5):","[] # FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5)","import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN","All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from","RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed,","jobs more threads in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb),","as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs,","analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants","chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs =","reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import","kills it on long jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5,","= SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key,","SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix","chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for","args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip:","as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as","if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene","py \"stages/analyzer/run_differential_expression\", ) split using ( in string clustering_key, ) \"\"\" def split(args):","order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4","int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in order to","unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK -","> 1 thread. Martian thinks it does and kills it on long jobs","clear why this stage takes > 1 thread. Martian thinks it does and","* cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more","give big jobs more threads in order to avoid overloading a node threads","reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK","diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s =",": 1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For","cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads","1 thread. Martian thinks it does and kills it on long jobs __MRO__","compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp","diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp,","# import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis","diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using ( in string","clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f,","import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as","cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear","cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants","as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as","in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP])","h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons unknown matrix_mem_gb =","1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now,","\"stages/analyzer/run_differential_expression\", ) split using ( in string clustering_key, ) \"\"\" def split(args): if","cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO","cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s","from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import","string clustering_key, ) \"\"\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks","with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args,","for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5,","only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key)","return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out","bool skip, in int random_seed, in int max_clusters, out h5 diffexp_h5, out path","FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb =","threads in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads","to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for","expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters)","features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with","chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs","jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in","'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' :","for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp =","10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io","[chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs:","h5 matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed, in int","on long jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5","in bool skip, in int random_seed, in int max_clusters, out h5 diffexp_h5, out","cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this","join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in","chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir","chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args,","Martian thinks it does and kills it on long jobs __MRO__ = \"\"\"","chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb'","stage takes > 1 thread. Martian thinks it does and kills it on","int random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py","cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes","it on long jobs __MRO__ = \"\"\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in","thinks it does and kills it on long jobs __MRO__ = \"\"\" stage","this stage takes > 1 thread. Martian thinks it does and kills it","key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}}","now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5,","matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed, in int max_clusters,","key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks':","args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key,","gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix,","clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def","Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb,"],"string":"[\n \"chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix =\",\n \"lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes > 1\",\n \"h5 diffexp_h5, out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split using ( in\",\n \"NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb,\",\n \"{'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) #\",\n \"def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out\",\n \"= [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in\",\n \"in h5 clustering_h5, in bool skip, in int random_seed, in int max_clusters, out\",\n \"cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants\",\n \"big jobs more threads in order to avoid overloading a node threads =\",\n \"'__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs):\",\n \"= matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as\",\n \"for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) #\",\n \"as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as\",\n \"cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants\",\n \"( in string clustering_key, ) \\\"\\\"\\\" def split(args): if args.skip: return {'chunks': [{'__mem_gb':\",\n \"one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB))\",\n \"split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add\",\n \"cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE)\",\n \"= [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs]\",\n \"4 #TODO Not clear why this stage takes > 1 thread. Martian thinks\",\n \"in string clustering_key, ) \\\"\\\"\\\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]}\",\n \"threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key':\",\n \"chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP,\",\n \"Copyright (c) 2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as\",\n \"skip, in int random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv,\",\n \") \\\"\\\"\\\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = []\",\n \"in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks,\",\n \"- give big jobs more threads in order to avoid overloading a node\",\n \"# # Copyright (c) 2017 10X Genomics, Inc. All rights reserved. # import\",\n \"using ( in string clustering_key, ) \\\"\\\"\\\" def split(args): if args.skip: return {'chunks':\",\n \"src py \\\"stages/analyzer/run_differential_expression\\\", ) split using ( in string clustering_key, ) \\\"\\\"\\\" def\",\n \"return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons\",\n \"def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only\",\n \"in h5 matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed, in\",\n \"4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, })\",\n \"as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as\",\n \"cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io\",\n \"out h5 diffexp_h5, out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split using (\",\n \"overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in\",\n \"cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if\",\n \"more threads in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN)\",\n \"chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in\",\n \"import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import\",\n \"cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants\",\n \"h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io\",\n \"NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes > 1 thread.\",\n \"= cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features matrix =\",\n \"{'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons unknown\",\n \"stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip, in int\",\n \"outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for\",\n \"as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4\",\n \"= [] # FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 *\",\n \"if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv\",\n \"clustering_h5, in bool skip, in int random_seed, in int max_clusters, out h5 diffexp_h5,\",\n \"Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io\",\n \"# FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb\",\n \"{'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix\",\n \"avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key\",\n \"= \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip,\",\n \"import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import\",\n \"threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if\",\n \"int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split\",\n \"= int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in order\",\n \"cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv)\",\n \"diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return\",\n \"#!/usr/bin/env python # # Copyright (c) 2017 10X Genomics, Inc. All rights reserved.\",\n \"and kills it on long jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5\",\n \"main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute\",\n \"does and kills it on long jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in\",\n \"analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs,\",\n \"}) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip:\",\n \"out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split using ( in string clustering_key,\",\n \"= cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix,\",\n \"2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import\",\n \"#TODO Not clear why this stage takes > 1 thread. Martian thinks it\",\n \"it does and kills it on long jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION(\",\n \"rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome\",\n \"matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features matrix\",\n \"import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not\",\n \"max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split using\",\n \"as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why\",\n \"cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix\",\n \"= 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big\",\n \"in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads =\",\n \"'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5)\",\n \"For now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering =\",\n \"import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import\",\n \"split using ( in string clustering_key, ) \\\"\\\"\\\" def split(args): if args.skip: return\",\n \"return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return\",\n \"1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs\",\n \"f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs):\",\n \"python # # Copyright (c) 2017 10X Genomics, Inc. All rights reserved. #\",\n \"min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb':\",\n \"HACK - give big jobs more threads in order to avoid overloading a\",\n \"SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp)\",\n \"import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import\",\n \"diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split using ( in string clustering_key, ) \\\"\\\"\\\"\",\n \"(c) 2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp\",\n \"random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\",\",\n \"h5 clustering_h5, in bool skip, in int random_seed, in int max_clusters, out h5\",\n \"= 4 #TODO Not clear why this stage takes > 1 thread. Martian\",\n \"as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes >\",\n \"outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs]\",\n \"threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads':\",\n \"__MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool\",\n \"analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants\",\n \") split using ( in string clustering_key, ) \\\"\\\"\\\" def split(args): if args.skip:\",\n \"takes > 1 thread. Martian thinks it does and kills it on long\",\n \"chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in\",\n \"Not clear why this stage takes > 1 thread. Martian thinks it does\",\n \"'__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def\",\n \"why this stage takes > 1 thread. Martian thinks it does and kills\",\n \"\\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip, in\",\n \"matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5\",\n \"in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs: cr_io.copytree(csv_dir, outs.diffexp_csv, allow_existing=True)\",\n \"thread. Martian thinks it does and kills it on long jobs __MRO__ =\",\n \"\\\"\\\"\\\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] #\",\n \"args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for\",\n \"# For now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering\",\n \"Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as\",\n \"for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return\",\n \"outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for\",\n \"h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in order to avoid\",\n \"long jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5,\",\n \"args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for\",\n \"= min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key,\",\n \"<reponame>qiangli/cellranger<filename>mro/stages/analyzer/run_differential_expression/__init__.py #!/usr/bin/env python # # Copyright (c) 2017 10X Genomics, Inc. All rights\",\n \"matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give\",\n \"# HACK - give big jobs more threads in order to avoid overloading\",\n \"chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs: cr_io.copytree(csv_dir, outs.diffexp_csv,\",\n \"return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression features\",\n \"# Copyright (c) 2017 10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp\",\n \"import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage\",\n \"[{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons unknown matrix_mem_gb\",\n \"= 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads,\",\n \"args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene expression\",\n \"matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f:\",\n \"cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN =\",\n \"path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split using ( in string clustering_key, )\",\n \"if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one\",\n \"in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", )\",\n \"chunks = [] # FIXME: Add one for reasons unknown matrix_mem_gb = 1.8\",\n \"matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5)\",\n \"in int random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src\",\n \"[chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s,\",\n \"node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({\",\n \"for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs: cr_io.copytree(csv_dir,\",\n \"clustering_key, ) \\\"\\\"\\\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks =\",\n \"SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join':\",\n \"def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME:\",\n \"a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5):\",\n \"[] # FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5)\",\n \"import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN\",\n \"All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from\",\n \"RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed,\",\n \"jobs more threads in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb),\",\n \"as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs,\",\n \"analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants\",\n \"chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs =\",\n \"reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import\",\n \"kills it on long jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5,\",\n \"= SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key,\",\n \"SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix\",\n \"chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for\",\n \"args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip:\",\n \"as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as\",\n \"if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now, only compute for gene\",\n \"py \\\"stages/analyzer/run_differential_expression\\\", ) split using ( in string clustering_key, ) \\\"\\\"\\\" def split(args):\",\n \"order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4\",\n \"int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads in order to\",\n \"unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK -\",\n \"> 1 thread. Martian thinks it does and kills it on long jobs\",\n \"clear why this stage takes > 1 thread. Martian thinks it does and\",\n \"* cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more\",\n \"give big jobs more threads in order to avoid overloading a node threads\",\n \"reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK\",\n \"diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s =\",\n \": 1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For\",\n \"cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb, h5_constants.MIN_MEM_GB)) # HACK - give big jobs more threads\",\n \"1 thread. Martian thinks it does and kills it on long jobs __MRO__\",\n \"compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp\",\n \"diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp,\",\n \"# import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis\",\n \"diffexp_h5, out path diffexp_csv, src py \\\"stages/analyzer/run_differential_expression\\\", ) split using ( in string\",\n \"clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f,\",\n \"import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as\",\n \"cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear\",\n \"cr_diffexp import cellranger.analysis.io as analysis_io from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants\",\n \"as h5_constants import cellranger.analysis.constants as analysis_constants import cellranger.matrix as cr_matrix import cellranger.io as\",\n \"in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP])\",\n \"h5_constants.MIN_MEM_GB}]} chunks = [] # FIXME: Add one for reasons unknown matrix_mem_gb =\",\n \"1}} def main(args, outs): if args.skip: return matrix = cr_matrix.CountMatrix.load_h5_file(args.matrix_h5) # For now,\",\n \"\\\"stages/analyzer/run_differential_expression\\\", ) split using ( in string clustering_key, ) \\\"\\\"\\\" def split(args): if\",\n \"cr_matrix import cellranger.io as cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO\",\n \"cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s\",\n \"from cellranger.analysis.singlegenome import SingleGenomeAnalysis import cellranger.h5_constants as h5_constants import cellranger.analysis.constants as analysis_constants import\",\n \"string clustering_key, ) \\\"\\\"\\\" def split(args): if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks\",\n \"with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def join(args,\",\n \"for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5,\",\n \"only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key)\",\n \"return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out\",\n \"bool skip, in int random_seed, in int max_clusters, out h5 diffexp_h5, out path\",\n \"FIXME: Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb =\",\n \"threads in order to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads\",\n \"to avoid overloading a node threads = min(cr_io.get_thread_request_from_mem_gb(chunk_mem_gb), NUM_THREADS_MIN) threads = 4 for\",\n \"expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters)\",\n \"features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with\",\n \"chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in chunk_outs] chunk_csv_dirs\",\n \"jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5 clustering_h5, in\",\n \"'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' :\",\n \"for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp =\",\n \"10X Genomics, Inc. All rights reserved. # import cellranger.analysis.diffexp as cr_diffexp import cellranger.analysis.io\",\n \"[chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_csv_dirs:\",\n \"h5 matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed, in int\",\n \"on long jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in h5\",\n \"in bool skip, in int random_seed, in int max_clusters, out h5 diffexp_h5, out\",\n \"cr_io import cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this\",\n \"join(args, outs, chunk_defs, chunk_outs): if args.skip: return chunk_h5s = [chunk_out.diffexp_h5 for chunk_out in\",\n \"chunk_csv_dirs = [chunk_out.diffexp_csv for chunk_out in chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir\",\n \"chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}} def main(args,\",\n \"Martian thinks it does and kills it on long jobs __MRO__ = \\\"\\\"\\\"\",\n \"chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb'\",\n \"stage takes > 1 thread. Martian thinks it does and kills it on\",\n \"int random_seed, in int max_clusters, out h5 diffexp_h5, out path diffexp_csv, src py\",\n \"cellranger.library_constants as lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes\",\n \"it on long jobs __MRO__ = \\\"\\\"\\\" stage RUN_DIFFERENTIAL_EXPRESSION( in h5 matrix_h5, in\",\n \"thinks it does and kills it on long jobs __MRO__ = \\\"\\\"\\\" stage\",\n \"this stage takes > 1 thread. Martian thinks it does and kills it\",\n \"key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks': chunks, 'join': {'__mem_gb' : 1}}\",\n \"now, only compute for gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5,\",\n \"matrix_h5, in h5 clustering_h5, in bool skip, in int random_seed, in int max_clusters,\",\n \"key in SingleGenomeAnalysis.load_clustering_keys_from_h5(args.clustering_h5): chunks.append({ 'clustering_key': key, '__mem_gb': chunk_mem_gb, '__threads': threads, }) return {'chunks':\",\n \"args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix, clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key,\",\n \"gene expression features matrix = matrix.select_features_by_type(lib_constants.GENE_EXPRESSION_LIBRARY_TYPE) clustering = SingleGenomeAnalysis.load_clustering_from_h5(args.clustering_h5, args.clustering_key) diffexp = cr_diffexp.run_differential_expression(matrix,\",\n \"clustering.clusters) with analysis_io.open_h5_for_writing(outs.diffexp_h5) as f: cr_diffexp.save_differential_expression_h5(f, args.clustering_key, diffexp) cr_diffexp.save_differential_expression_csv(args.clustering_key, diffexp, matrix, outs.diffexp_csv) def\",\n \"Add one for reasons unknown matrix_mem_gb = 1.8 * cr_matrix.CountMatrix.get_mem_gb_from_matrix_h5(args.matrix_h5) chunk_mem_gb = int(max(matrix_mem_gb,\"\n]","isConversational":false}}},{"rowIdx":90,"cells":{"ngram":{"kind":"list like","value":["not hashable and cannot be put into a set. Examples ======== >>> from","a certificate for the graph gr adjacency list The graph is assumed to",">>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is",">>> b = Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4,","from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S","= current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg,","from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form","= _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i])","2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 =","two component tensors of type `i` None no symmetry 0 commuting 1 anticommuting","else return the array form of the permutation representing the canonical form of","candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if","This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup,",">>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A =","gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in","for tensors of type `i` base_i, gens_i BSGS for tensors of this type","of the graph. The canonical form of the tensor gives a certificate for","This is a brute force implementation that goes over all elements of the","a naive implementation using the definition of a base and a strong generating","size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies] sym = [sym]","for testing purposes. Since the array form of a permutation is currently a","of elements for the centralizer of a subgroup/set/element. This is a brute force","2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3],","{tuple(a) for a in first} == \\ {tuple(a) for a in second} def","2, 1, 3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import","2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3,","return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \"\"\" Verify the correctness of","= tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for h","[0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v = [] for i","it. There are other procedures for verifying a base and strong generating set,","3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4],","contracted when they correspond to the same line of the graph. The canonical","0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0, *v) return can","= set() for s in S.generate(af=True): h = _af_rmul(g, s) for d in","using the definition of a base and a strong generating set relative to","symmetry 0 commuting 1 anticommuting Return 0 if the tensor is zero, else","_verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A)","if h[-1] != prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr):","Since the array form of a permutation is currently a list, Permutation is","True \"\"\" return {tuple(a) for a in first} == \\ {tuple(a) for a","sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices:","is a brute force implementation that goes over all elements of the group","commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other,","\\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import","return 0 prev = h return list(a[0]) def graph_certificate(gr): \"\"\" Return a certificate","dummies list of dummy indices msym symmetry of the metric v is a","over all elements of the group and checks for membership in the centralizer.",">>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3,","sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for","8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17,","5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3,","[a, b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True","!= candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False","for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\"","return the array form of the permutation representing the canonical form of the","v is a list of (base_i, gens_i, n_i, sym_i) for tensors of type","number of lines of the graph num_indices = 0 for v, neigh in","i in range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base,","items] i = 0 for v, neigh in items: for v2 in neigh:","prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h return list(a[0]) def","# the odd index to the other vertex vertices = [[] for i","_af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in","is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import","def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a list of","centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group,","g = [] for v in vertices: g.extend(v) assert len(g) == num_indices g","elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af)","tensors of type `i` None no symmetry 0 commuting 1 anticommuting Return 0","= PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize tensor formed","from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = []","3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0,","``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup","= [] if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else:","sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>>","True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None: closure = group.normal_closure(arg)","graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10, 12, 3, 14,","2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh","sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None: closure = group.normal_closure(arg) conjugates = set() if","and a strong generating set relative to it. There are other procedures for","tensor is zero, else return the array form of the permutation representing the","list of (base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i","[dummies] sym = [sym] else: num_types = len(sym) dgens = [] for i","ot tensors of type `i` sym_i symmetry under exchange of two component tensors","g = g.array_form st = set() for s in S.generate(af=True): h = _af_rmul(g,","closure of a subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure","_distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if","sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1,","centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from","base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0))","0 for v, neigh in items: num_indices += len(neigh) # associate to each","from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the normal closure of a subgroup/subset/element in","Return 0 if the tensor is zero, else return the array form of","h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for h in a:","- 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist","sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in","gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS for tensors","of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can","c2 True \"\"\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items","arg, centr=None): \"\"\" Verify the centralizer of a group/set/element inside another group. This","the group and checks for membership in the centralizer. It is used to","PermutationGroup \"\"\" Verify the normal closure of a subgroup/subset/element in a group. This","3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1,","a group/set/element inside another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups``","'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen","======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure","correspond to the same line of the graph. The canonical form of the","which comes first in items, # the odd index to the other vertex","for a in first} == \\ {tuple(a) for a in second} def _naive_list_centralizer(self,","... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>>","symmetry under exchange of two component tensors of type `i` None no symmetry","None no symmetry 0 commuting 1 anticommuting Return 0 if the tensor is","naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize tensor","False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def","else: num_types = len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i],","1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer,","= graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1,","procedures for verifying a base and strong generating set, but this one will","centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is None:","a list, Permutation is not hashable and cannot be put into a set.","1 v = [] for i in range(len(vlen)): n = vlen[i] if n:","prev = h return list(a[0]) def graph_certificate(gr): \"\"\" Return a certificate for the","3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 =","of (base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS","num_types = len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size","_naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a list of elements","list(D.generate(af=True)) g = g.array_form st = set() for s in S.generate(af=True): h =","4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2,","the graph num_indices = 0 for v, neigh in items: num_indices += len(neigh)","2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5],","_naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base,","= v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens =","centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See","each vertex its indices; for each line # between two vertices assign the","return True def _verify_centralizer(group, arg, centr=None): \"\"\" Verify the centralizer of a group/set/element","n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS for tensors of","= SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3,","brute force implementation that goes over all elements of the group and checks","used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer","import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]),","5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations","<reponame>ethankward/sympy<filename>sympy/combinatorics/testutil.py from sympy.combinatorics import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def","the array form of the permutation representing the canonical form of the tensor.","a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1,","of a base and a strong generating set relative to it. There are","for tensors of this type n_i number ot tensors of type `i` sym_i","the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>>","gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4],","if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group,","def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the normal closure","of the graph num_indices = 0 for v, neigh in items: num_indices +=","generating set, but this one will serve for more robust testing. Examples ========","used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup)","st = set() for s in S.generate(af=True): h = _af_rmul(g, s) for d","sym_i symmetry under exchange of two component tensors of type `i` None no","in items: num_indices += len(neigh) # associate to each vertex its indices; for","in items, # the odd index to the other vertex vertices = [[]","the centralizer of a group/set/element inside another group. This is used for testing","n_i number ot tensors of type `i` sym_i symmetry under exchange of two","< pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in","= h return list(a[0]) def graph_certificate(gr): \"\"\" Return a certificate for the graph","lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if not","indices msym symmetry of the metric v is a list of (base_i, gens_i,","dummies = [dummies] sym = [sym] else: num_types = len(sym) dgens = []","algorithm to get the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil","def graph_certificate(gr): \"\"\" Return a certificate for the graph gr adjacency list The","if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for","gens) current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order()","v, neigh in items: num_indices += len(neigh) # associate to each vertex its","x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens)","centr=None): \"\"\" Verify the centralizer of a group/set/element inside another group. This is","to get the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import","# associate to each vertex its indices; for each line # between two","4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2,","the normal closure of a subgroup/subset/element in a group. This is used to","return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify","PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize tensor formed by","items: num_indices += len(neigh) # associate to each vertex its indices; for each","1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3,","component tensors of type `i` None no symmetry 0 commuting 1 anticommuting Return","for s in S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q","4, 3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1 =","_af_rmul v1 = [] for i in range(len(v)): base_i, gens_i, n_i, sym_i =","for each line # between two vertices assign the # even index to","= Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare two lists of permutations as sets.","currently a list, Permutation is not hashable and cannot be put into a","4, 0, 1, 2]) >>> ls1 = [a, b, c] >>> ls2 =","AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\"","Canonicalize tensor formed by tensors of the different types g permutation representing the","sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in","group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from","a subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ========","0 if the tensor is zero, else return the array form of the","from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i","num_indices = 0 for v, neigh in items: num_indices += len(neigh) # associate","sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True))","hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen in subgr_gens:","`i` None no symmetry 0 commuting 1 anticommuting Return 0 if the tensor","isinstance(sym, int): num_types = 1 dummies = [dummies] sym = [sym] else: num_types","S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True))","v in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices +","graph a symmetric tensor with number of indices equal to the degree of","a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a) for a in first} ==","AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>>","between two vertices assign the # even index to the vertex which comes","sym, *v): \"\"\" Canonicalize tensor formed by tensors of the different types g","tensor formed by tensors of the different types g permutation representing the tensor","import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims()","gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g,","a certificate for the graph. This is not an efficient algorithm to get","3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with if","from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5)","graph. The canonical form of the tensor gives a certificate for the graph.","True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is None: centr","3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]}","Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i, gens_i, n_i, sym_i","to the other vertex vertices = [[] for i in items] i =","are contracted when they correspond to the same line of the graph. The","and strong generating set. This is a naive implementation using the definition of","b = Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4, 0,","is currently a list, Permutation is not hashable and cannot be put into","sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>>","PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() !=","g.array_form st = set() for s in S.generate(af=True): h = _af_rmul(g, s) for","checks for membership in the centralizer. It is used to test ``.centralizer()`` from","======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D","A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S,","======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5],","S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h))","items, # the odd index to the other vertex vertices = [[] for","inside another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ========","This is not an efficient algorithm to get the certificate of a graph.","number ot tensors of type `i` sym_i symmetry under exchange of two component","testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup)","= SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also","import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup","size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens])","assign the # even index to the vertex which comes first in items,","+= [num_indices, num_indices + 1] size = num_indices + 2 assert sorted(g) ==","as sets. This is used for testing purposes. Since the array form of","= [a, b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2)","BSGS for tensors of this type n_i number ot tensors of type `i`","def _cmp_perm_lists(first, second): \"\"\" Compare two lists of permutations as sets. This is","dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size","of a base and strong generating set. This is a naive implementation using","i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer","_cmp_perm_lists(first, second): \"\"\" Compare two lists of permutations as sets. This is used","size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int):","the metric v is a list of (base_i, gens_i, n_i, sym_i) for tensors","conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens","len(g) == num_indices g += [num_indices, num_indices + 1] size = num_indices +","A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ========","el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize","True \"\"\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items =","= PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st","in gens) centralizer_list = [] if not af: for element in elements: if","be unoriented and without external lines. Associate to each vertex of the graph","12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19,","line # between two vertices assign the # even index to the vertex","in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element)","return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group,","in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x)","5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2)","This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups","the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>>","two vertices assign the # even index to the vertex which comes first","import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr =","_verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup","group/set/element inside another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples","(base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS for","representing the canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import","= [] for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i,","4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2,","= list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in items]","vertex; indices are contracted when they correspond to the same line of the","dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies] sym","5, 9, 15, 7, 11, 17, 13, 19, 20, 21] >>> c1 ==","exchange of two component tensors of type `i` None no symmetry 0 commuting","canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4,","4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2","g += [num_indices, num_indices + 1] size = num_indices + 2 assert sorted(g)","_naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import","D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0,","else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'):","for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False","the vertex which comes first in items, # the odd index to the","AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr)","af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a list of elements for the","elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen in","get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1,","of a permutation is currently a list, Permutation is not hashable and cannot",">>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if","import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x","if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif","[] if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for","for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from","1 anticommuting Return 0 if the tensor is zero, else return the array","sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for","Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4,","def _verify_centralizer(group, arg, centr=None): \"\"\" Verify the centralizer of a group/set/element inside another","for membership in the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``.","type `i` None no symmetry 0 commuting 1 anticommuting Return 0 if the","1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3,","naive implementation using the definition of a base and a strong generating set","for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort()","indices are contracted when they correspond to the same line of the graph.","9, 15, 7, 11, 17, 13, 19, 20, 21] >>> c1 == c2","af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\"","of the metric v is a list of (base_i, gens_i, n_i, sym_i) for","dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x","4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0,","num_indices += len(neigh) # associate to each vertex its indices; for each line","commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif","not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in","sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens","put into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from",">>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True","= Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2, 0, 4,","2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist =","without external lines. Associate to each vertex of the graph a symmetric tensor","vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in vertices: g.extend(v) assert","the definition of a base and a strong generating set relative to it.",">>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also","elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for","no symmetry 0 commuting 1 anticommuting Return 0 if the tensor is zero,","gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2)","line of the graph. The canonical form of the tensor gives a certificate","neigh in items: num_indices += len(neigh) # associate to each vertex its indices;","_verify_bsgs(group, base, gens): \"\"\" Verify the correctness of a base and strong generating","= _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a","items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in","Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3,","0)) [0, 2, 1, 3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from","strong generating set. This is a naive implementation using the definition of a","from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import","i in items] i = 0 for v, neigh in items: for v2","pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v","for the graph gr adjacency list The graph is assumed to be unoriented","certificate for the graph gr adjacency list The graph is assumed to be","from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2,","tensor gives a certificate for the graph. This is not an efficient algorithm","0 for v, neigh in items: for v2 in neigh: if pvert[v] <","len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2))","relative to it. There are other procedures for verifying a base and strong","range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n,","if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1:","gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can =","size = num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen","= list(D.generate(af=True)) g = g.array_form st = set() for s in S.generate(af=True): h","for i in items] i = 0 for v, neigh in items: for","_verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See",">>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4,","st.add(q) a = list(st) a.sort() prev = (0,)*size for h in a: if","= g.array_form st = set() for s in S.generate(af=True): h = _af_rmul(g, s)","closure is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens","sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2,","= lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if","array form of the permutation representing the canonical form of the tensor. Examples","PermutationGroup \"\"\" Return a list of elements for the centralizer of a subgroup/set/element.","(base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups","from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a list of elements for the centralizer","set() for s in S.generate(af=True): h = _af_rmul(g, s) for d in dlist:","It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil","sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S =","PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 =","+ 1] size = num_indices + 2 assert sorted(g) == list(range(size)) g =","Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v =","def _verify_bsgs(group, base, gens): \"\"\" Verify the correctness of a base and strong","num_indices g += [num_indices, num_indices + 1] size = num_indices + 2 assert","return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize tensor formed by tensors","sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr",">>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0,","_verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None:","from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i,","tensors of the different types g permutation representing the tensor dummies list of","indices; for each line # between two vertices assign the # even index","\"\"\" Return a list of elements for the centralizer of a subgroup/set/element. This","sympy.combinatorics import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second):","v1 = [] for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i]","generating set relative to it. There are other procedures for verifying a base","even index to the vertex which comes first in items, # the odd","the same line of the graph. The canonical form of the tensor gives","graph is assumed to be unoriented and without external lines. Associate to each","base_i, gens_i BSGS for tensors of this type n_i number ot tensors of","a subgroup/set/element. This is a brute force implementation that goes over all elements","from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base,","the different types g permutation representing the tensor dummies list of dummy indices",">>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D =","form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from","for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D","tensor dummies list of dummy indices msym symmetry of the metric v is","list The graph is assumed to be unoriented and without external lines. Associate","\"\"\" Compare two lists of permutations as sets. This is used for testing",">>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3,","af) def _verify_bsgs(group, base, gens): \"\"\" Verify the correctness of a base and","the correctness of a base and strong generating set. This is a naive","= set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens =","import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]),","types g permutation representing the tensor dummies list of dummy indices msym symmetry","graph gr adjacency list The graph is assumed to be unoriented and without","sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4],","lines of the graph num_indices = 0 for v, neigh in items: num_indices","PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S","tensors of type `i` sym_i symmetry under exchange of two component tensors of","arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup","the # even index to the vertex which comes first in items, #",">>> ls1 = [a, b, c] >>> ls2 = [b, c, a] >>>","of lines of the graph num_indices = 0 for v, neigh in items:","_naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \"\"\" Verify the correctness of a","centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list,","from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from","{0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5],","= [] for v in vertices: g.extend(v) assert len(g) == num_indices g +=","generating set. This is a naive implementation using the definition of a base","from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g =","a base and strong generating set, but this one will serve for more","from sympy.combinatorics import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first,","5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1,","of the tensor are twice the number of lines of the graph num_indices","closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif","of the graph a symmetric tensor with number of indices equal to the","hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af)","strong generating set relative to it. There are other procedures for verifying a","vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices + 1] size","\"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import","force implementation that goes over all elements of the group and checks for","goes over all elements of the group and checks for membership in the","range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase,","n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1)","ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a) for","conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v):","this type n_i number ot tensors of type `i` sym_i symmetry under exchange","in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev","sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert =","of a subgroup/set/element. This is a brute force implementation that goes over all","(SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation","in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev =","dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S","======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None: closure = group.normal_closure(arg) conjugates = set()","4, 1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>> c =","return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True","centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other,","purposes. Since the array form of a permutation is currently a list, Permutation","canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>>","canonical form of the tensor gives a certificate for the graph. This is","7, 11, 17, 13, 19, 20, 21] >>> c1 == c2 True \"\"\"","symmetric tensor with number of indices equal to the degree of the vertex;","they correspond to the same line of the graph. The canonical form of","2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]}","pvert = [x[0] for x in items] pvert = _af_invert(pvert) # the indices","comes first in items, # the odd index to the other vertex vertices","n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0, *v) return","permutation is currently a list, Permutation is not hashable and cannot be put","This is used for testing purposes. Since the array form of a permutation","gens = [x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen)","element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element):","another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>>","gens_i BSGS for tensors of this type n_i number ot tensors of type","= Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b, c] >>>","af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \"\"\"","this one will serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups","to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>>","*v): \"\"\" Canonicalize tensor formed by tensors of the different types g permutation","= gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1","x in items] pvert = _af_invert(pvert) # the indices of the tensor are","set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists","a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups","+= 1 v = [] for i in range(len(vlen)): n = vlen[i] if","import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A","certificate for the graph. This is not an efficient algorithm to get the","A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\"","Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2,","= DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])]","neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = []","= vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse()","This is a naive implementation using the definition of a base and a",">>> _cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a) for a in first} == \\","the array form of a permutation is currently a list, Permutation is not","for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return","sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>> b","sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group",">>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S =","elements of the group and checks for membership in the centralizer. It is","(SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>>","gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0,","sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types","0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0,","4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0,","20, 21] >>> c1 == c2 True \"\"\" from sympy.combinatorics.permutations import _af_invert from","from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda","`i` base_i, gens_i BSGS for tensors of this type n_i number ot tensors","of type `i` base_i, gens_i BSGS for tensors of this type n_i number","== prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h return list(a[0])","Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer",">>> c1 == c2 True \"\"\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import","1, 2]) >>> ls1 = [a, b, c] >>> ls2 = [b, c,","[sym] else: num_types = len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i],","in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size,","h in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0","from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert","dummies, sym, *v): \"\"\" Canonicalize tensor formed by tensors of the different types","Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements =","for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set()","a brute force implementation that goes over all elements of the group and","centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg,","of the group and checks for membership in the centralizer. It is used","elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens = lambda","msym symmetry of the metric v is a list of (base_i, gens_i, n_i,","the canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive","sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation,","base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens","from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from","num_types = 1 dummies = [dummies] sym = [sym] else: num_types = len(sym)","odd index to the other vertex vertices = [[] for i in items]","list of dummy indices msym symmetry of the metric v is a list","is a list of (base_i, gens_i, n_i, sym_i) for tensors of type `i`","indices equal to the degree of the vertex; indices are contracted when they","reverse=True) pvert = [x[0] for x in items] pvert = _af_invert(pvert) # the","that goes over all elements of the group and checks for membership in","5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>>","D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer","base, gens): \"\"\" Verify the correctness of a base and strong generating set.","import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3)","each vertex of the graph a symmetric tensor with number of indices equal","for the graph. This is not an efficient algorithm to get the certificate","c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\" return","sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil","unoriented and without external lines. Associate to each vertex of the graph a","list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] +=","current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return","\"\"\" Return a certificate for the graph gr adjacency list The graph is","to the vertex which comes first in items, # the odd index to","if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element","set, but this one will serve for more robust testing. Examples ======== >>>","vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)): n = vlen[i]","implementation using the definition of a base and a strong generating set relative","dummy indices msym symmetry of the metric v is a list of (base_i,","'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'):","== list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)]","A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None: closure","3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2,","test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from","is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ...","= AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims","'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \"\"\" Verify the correctness","definition of a base and a strong generating set relative to it. There","= PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g","None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators","import Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i, gens_i, n_i,","n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0))","centralizer of a group/set/element inside another group. This is used for testing ``.centralizer()``",">>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import","arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the normal closure of a","adjacency list The graph is assumed to be unoriented and without external lines.","for the centralizer of a subgroup/set/element. This is a brute force implementation that","D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form",">>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1,","to be unoriented and without external lines. Associate to each vertex of the","from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4)","strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate =","more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil","dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies =","sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x:",">>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3)","2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4],","of type `i` sym_i symmetry under exchange of two component tensors of type","A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups","in range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens,","n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices))","commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = []","PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2","18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21] >>> c1","======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer =","of two component tensors of type `i` None no symmetry 0 commuting 1","get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for","arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen","type n_i number ot tensors of type `i` sym_i symmetry under exchange of","sym_i) for tensors of type `i` base_i, gens_i BSGS for tensors of this","v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym,","centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from","A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is","graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1,","3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import","= len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size -","1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11,","14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21]","canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>>","1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>>","PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens):","are twice the number of lines of the graph num_indices = 0 for","elements for the centralizer of a subgroup/set/element. This is a brute force implementation","4, 5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from","two lists of permutations as sets. This is used for testing purposes. Since","testing purposes. Since the array form of a permutation is currently a list,","vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies","+= len(neigh) # associate to each vertex its indices; for each line #","= arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens =","vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v = []","1] size = num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g)","c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6,","g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1","for x in items] pvert = _af_invert(pvert) # the indices of the tensor","h return list(a[0]) def graph_certificate(gr): \"\"\" Return a certificate for the graph gr","type `i` sym_i symmetry under exchange of two component tensors of type `i`","the other vertex vertices = [[] for i in items] i = 0","from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare two","all elements of the group and checks for membership in the centralizer. It","a.sort() prev = (0,)*size for h in a: if h[:-2] == prev[:-2]: if","int): num_types = 1 dummies = [dummies] sym = [sym] else: num_types =","= [x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for","import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import","2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5],","21] >>> c1 == c2 True \"\"\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can","'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def","permutation representing the canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil","= get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g,","4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 =","= AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A,","PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g =","4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1)","indices of the tensor are twice the number of lines of the graph","elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]),","``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups","current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group,","AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from",">>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2,","neigh in items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1)","import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D,",">>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from","[arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure","\"\"\" Verify the centralizer of a group/set/element inside another group. This is used","2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1","1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'):","6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7,","c1 == c2 True \"\"\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs,","for verifying a base and strong generating set, but this one will serve","!= prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr): \"\"\" Return","if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg, centr=None): \"\"\"","to it. There are other procedures for verifying a base and strong generating","serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>>","import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A,","other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a list of elements for","for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure =","2, 0)) [0, 2, 1, 3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup","10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13,","= Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v","[Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\"","\"\"\" Canonicalize tensor formed by tensors of the different types g permutation representing","gens) centralizer_list = [] if not af: for element in elements: if commutes_with_gens(element):","robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import","in the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ========","\"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for","from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import","b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\"","is assumed to be unoriented and without external lines. Associate to each vertex","second): \"\"\" Compare two lists of permutations as sets. This is used for","dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set() for s in","+= 2 g = [] for v in vertices: g.extend(v) assert len(g) ==","subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens","sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym,","import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>>","= [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S =","permutation representing the tensor dummies list of dummy indices msym symmetry of the","representing the tensor dummies list of dummy indices msym symmetry of the metric","of type `i` None no symmetry 0 commuting 1 anticommuting Return 0 if","4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5],","= group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive)","gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups import","items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert =","for v, neigh in items: num_indices += len(neigh) # associate to each vertex","vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in vertices: g.extend(v)","= [x[0] for x in items] pvert = _af_invert(pvert) # the indices of","Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with","list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None):","2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3,","= group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg,","sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>>","sets. This is used for testing purposes. Since the array form of a","for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in","c1 [0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18,","current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg, centr=None):","prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr): \"\"\" Return a","in first} == \\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False):","= num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen =","centralizer of a subgroup/set/element. This is a brute force implementation that goes over","c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10, 12,","s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st)","vertex which comes first in items, # the odd index to the other","equal to the degree of the vertex; indices are contracted when they correspond","i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i))","centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'):","15, 7, 11, 17, 13, 19, 20, 21] >>> c1 == c2 True","2, 3, 4, 1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>>","_verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0,","pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in vertices:","in S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d,","implementation that goes over all elements of the group and checks for membership","\"\"\" Verify the normal closure of a subgroup/subset/element in a group. This is",">>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0,","PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \"\"\" Verify the correctness of a base","5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>>","the centralizer of a subgroup/set/element. This is a brute force implementation that goes","gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies","for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def","is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import","5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2,","in items] pvert = _af_invert(pvert) # the indices of the tensor are twice","See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is None: centr =","Return a list of elements for the centralizer of a subgroup/set/element. This is",">>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True","for neigh in vertices: vlen[len(neigh)] += 1 v = [] for i in","\"\"\" return {tuple(a) for a in first} == \\ {tuple(a) for a in","each line # between two vertices assign the # even index to the","_verify_centralizer(group, arg, centr=None): \"\"\" Verify the centralizer of a group/set/element inside another group.","subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino():","Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>>","Compare two lists of permutations as sets. This is used for testing purposes.","17, 13, 19, 20, 21] >>> c1 == c2 True \"\"\" from sympy.combinatorics.permutations","testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs","will serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup","= group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order():","= _af_invert(pvert) # the indices of the tensor are twice the number of","PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ========","0, 1, 2]) >>> ls1 = [a, b, c] >>> ls2 = [b,","of a subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples","3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0,","from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>>","is zero, else return the array form of the permutation representing the canonical","index to the other vertex vertices = [[] for i in items] i","= 0 for v, neigh in items: for v2 in neigh: if pvert[v]","in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices + 1]",">>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil","if the tensor is zero, else return the array form of the permutation",">>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b,","See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None: closure = group.normal_closure(arg) conjugates","zero, else return the array form of the permutation representing the canonical form","tensor with number of indices equal to the degree of the vertex; indices","vertices: vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)): n =","======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A","# between two vertices assign the # even index to the vertex which","test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from","cannot be put into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation","element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self,","canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x","set relative to it. There are other procedures for verifying a base and","3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20,","3, 4, 1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>> c","an efficient algorithm to get the certificate of a graph. Examples ======== >>>","list(a[0]) def graph_certificate(gr): \"\"\" Return a certificate for the graph gr adjacency list","sym, size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies] sym =","i = 0 for v, neigh in items: for v2 in neigh: if","neigh in vertices: vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)):","# even index to the vertex which comes first in items, # the","graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2,","subgr_gens = [arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^","in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return","and without external lines. Associate to each vertex of the graph a symmetric","sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer","is used for testing purposes. Since the array form of a permutation is","A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr","closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the normal closure of a subgroup/subset/element","= [sym] else: num_types = len(sym) dgens = [] for i in range(num_types):","h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h return","``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups","closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize tensor formed by tensors of","tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs","d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev","return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return","gr adjacency list The graph is assumed to be unoriented and without external","list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert","g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2)",">>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics","0 prev = h return list(a[0]) def graph_certificate(gr): \"\"\" Return a certificate for","list, Permutation is not hashable and cannot be put into a set. Examples","in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer =","with number of indices equal to the degree of the vertex; indices are","sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare two lists","graph. This is not an efficient algorithm to get the certificate of a","by tensors of the different types g permutation representing the tensor dummies list","sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S,","_cmp_perm_lists \"\"\" if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive","from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4,","for gen in gens) centralizer_list = [] if not af: for element in","gen in gens) centralizer_list = [] if not af: for element in elements:","if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list","into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil","_cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1,","[x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen","in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from",">>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5)","q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for","the tensor are twice the number of lines of the graph num_indices =","centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self,","def canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize tensor formed by tensors of the","g permutation representing the tensor dummies list of dummy indices msym symmetry of","len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert = _af_invert(pvert) #","subgroup/set/element. This is a brute force implementation that goes over all elements of","True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base,","if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators]","base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can","import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \"\"\"","0, 4, 3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1","= [] for i in range(len(vlen)): n = vlen[i] if n: base, gens","None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return","base and strong generating set. This is a naive implementation using the definition","See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens)","of permutations as sets. This is used for testing purposes. Since the array","= arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for","formed by tensors of the different types g permutation representing the tensor dummies","of a group/set/element inside another group. This is used for testing ``.centralizer()`` from","efficient algorithm to get the certificate of a graph. Examples ======== >>> from","correctness of a base and strong generating set. This is a naive implementation","the vertex; indices are contracted when they correspond to the same line of","to each vertex of the graph a symmetric tensor with number of indices","subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym,","current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() !=","if closure is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'):","import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i","a symmetric tensor with number of indices equal to the degree of the","v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies,","get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies,","in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set() for s","base and a strong generating set relative to it. There are other procedures","h = _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q)","s in S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q =","2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5],","normal closure of a subgroup/subset/element in a group. This is used to test","Return a certificate for the graph gr adjacency list The graph is assumed","of this type n_i number ot tensors of type `i` sym_i symmetry under","Verify the centralizer of a group/set/element inside another group. This is used for","= dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies]","is not hashable and cannot be put into a set. Examples ======== >>>","the degree of the vertex; indices are contracted when they correspond to the","3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2","for v in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices","{0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2,","4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2,","2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations","_cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the","AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A =","3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1","i += 2 g = [] for v in vertices: g.extend(v) assert len(g)","2]) >>> ls1 = [a, b, c] >>> ls2 = [b, c, a]",">>> a = Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2,","graph_certificate(gr): \"\"\" Return a certificate for the graph gr adjacency list The graph","dlist = list(D.generate(af=True)) g = g.array_form st = set() for s in S.generate(af=True):","in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a","candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return","the tensor gives a certificate for the graph. This is not an efficient","[] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens)","not an efficient algorithm to get the certificate of a graph. Examples ========","Verify the normal closure of a subgroup/subset/element in a group. This is used","= graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10, 12, 3,","for v, neigh in items: for v2 in neigh: if pvert[v] < pvert[v2]:","the odd index to the other vertex vertices = [[] for i in","num_indices + 1] size = num_indices + 2 assert sorted(g) == list(range(size)) g","= 1 dummies = [dummies] sym = [sym] else: num_types = len(sym) dgens","_distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare two lists of permutations",">>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure","_verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the normal closure of","There are other procedures for verifying a base and strong generating set, but","See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements","3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \"\"\"","======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is None: centr = group.centralizer(arg) centr_list","assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in","list(st) a.sort() prev = (0,)*size for h in a: if h[:-2] == prev[:-2]:","array form of a permutation is currently a list, Permutation is not hashable","elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \"\"\" Verify","======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup",">>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a =","vertex its indices; for each line # between two vertices assign the #","and cannot be put into a set. Examples ======== >>> from sympy.combinatorics.permutations import","metric v is a list of (base_i, gens_i, n_i, sym_i) for tensors of","x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set() for","elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return","_cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a) for a in first} == \\ {tuple(a)","c, a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a) for a in first}","x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if not af:","SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ========",">>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0,","a base and strong generating set. This is a naive implementation using the","of the vertex; indices are contracted when they correspond to the same line","items] pvert = _af_invert(pvert) # the indices of the tensor are twice the","of dummy indices msym symmetry of the metric v is a list of","True def _verify_centralizer(group, arg, centr=None): \"\"\" Verify the centralizer of a group/set/element inside","in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list","S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See","Permutation is not hashable and cannot be put into a set. Examples ========","3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1,","to the degree of the vertex; indices are contracted when they correspond to","the graph. The canonical form of the tensor gives a certificate for the","0 commuting 1 anticommuting Return 0 if the tensor is zero, else return","= PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order()","======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from","the tensor is zero, else return the array form of the permutation representing","11, 17, 13, 19, 20, 21] >>> c1 == c2 True \"\"\" from","\"\"\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens =","anticommuting Return 0 if the tensor is zero, else return the array form","pvert = _af_invert(pvert) # the indices of the tensor are twice the number","permutations as sets. This is used for testing purposes. Since the array form","the tensor dummies list of dummy indices msym symmetry of the metric v","\"\"\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items())","+ 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for","for i in range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i)","gens): \"\"\" Verify the correctness of a base and strong generating set. This","[[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if","# the indices of the tensor are twice the number of lines of","the permutation representing the canonical form of the tensor. Examples ======== >>> from","[num_indices, num_indices + 1] size = num_indices + 2 assert sorted(g) == list(range(size))","group and checks for membership in the centralizer. It is used to test","and checks for membership in the centralizer. It is used to test ``.centralizer()``","strong generating set, but this one will serve for more robust testing. Examples","sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2,","3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a,","to each vertex its indices; for each line # between two vertices assign","dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in range(len(v)):","degree of the vertex; indices are contracted when they correspond to the same","======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True))","hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \"\"\" Verify the","== num_indices g += [num_indices, num_indices + 1] size = num_indices + 2","= list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg,","[0, 2, 1, 3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can","Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare","1: return False return True def _verify_centralizer(group, arg, centr=None): \"\"\" Verify the centralizer","group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def","sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the normal closure of a subgroup/subset/element in a","a list of (base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i,","tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for h in","prev = (0,)*size for h in a: if h[:-2] == prev[:-2]: if h[-1]","The canonical form of the tensor gives a certificate for the graph. This","a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev =","its indices; for each line # between two vertices assign the # even","of indices equal to the degree of the vertex; indices are contracted when","4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\"","[0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5,","and strong generating set, but this one will serve for more robust testing.","Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>>","list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x,","all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if not af: for","tensors of this type n_i number ot tensors of type `i` sym_i symmetry","= Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>>","twice the number of lines of the graph num_indices = 0 for v,","= list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens = lambda x:","sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a list of elements for the centralizer of","x: len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert = _af_invert(pvert)","other procedures for verifying a base and strong generating set, but this one",">>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>>","for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if","``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>>","= _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups","group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return","the graph gr adjacency list The graph is assumed to be unoriented and","form of the tensor gives a certificate for the graph. This is not","group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure)","sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens","get the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate","= [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v = [] for","v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0,","gen) for gen in gens) centralizer_list = [] if not af: for element","the number of lines of the graph num_indices = 0 for v, neigh","set. This is a naive implementation using the definition of a base and","[b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a) for a in","current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg, centr=None): \"\"\" Verify","lines. Associate to each vertex of the graph a symmetric tensor with number","gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens =","gives a certificate for the graph. This is not an efficient algorithm to","ls1 = [a, b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1,","are other procedures for verifying a base and strong generating set, but this","list of elements for the centralizer of a subgroup/set/element. This is a brute","== \\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups","= AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if","range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for",">>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>>","arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg]","19, 20, 21] >>> c1 == c2 True \"\"\" from sympy.combinatorics.permutations import _af_invert","external lines. Associate to each vertex of the graph a symmetric tensor with","import PermutationGroup \"\"\" Return a list of elements for the centralizer of a","!= 1: return False return True def _verify_centralizer(group, arg, centr=None): \"\"\" Verify the","3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists",">>> g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 =","= (0,)*size for h in a: if h[:-2] == prev[:-2]: if h[-1] !=","[] for i in range(len(vlen)): n = vlen[i] if n: base, gens =","symmetry of the metric v is a list of (base_i, gens_i, n_i, sym_i)","different types g permutation representing the tensor dummies list of dummy indices msym","Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare two lists of permutations as sets. This","a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import","return {tuple(a) for a in first} == \\ {tuple(a) for a in second}","under exchange of two component tensors of type `i` None no symmetry 0","to the same line of the graph. The canonical form of the tensor","h[-1] != prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr): \"\"\"","of the tensor gives a certificate for the graph. This is not an","= Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4, 0, 1,","v, neigh in items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i)","if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies =","(0,)*size for h in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]:","subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>>",">>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10,","======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a","1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3,","a permutation is currently a list, Permutation is not hashable and cannot be","a = list(st) a.sort() prev = (0,)*size for h in a: if h[:-2]","commuting 1 anticommuting Return 0 if the tensor is zero, else return the","from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation,","import PermutationGroup \"\"\" Verify the normal closure of a subgroup/subset/element in a group.","5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1,","5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>>","DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2,",">>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A,","PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate","set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg","^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \"\"\"","sym = [sym] else: num_types = len(sym) dgens = [] for i in","if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h","0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other,","associate to each vertex its indices; for each line # between two vertices","vertices assign the # even index to the vertex which comes first in","{tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup","for h in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return","import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3,","import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>> b =","AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure","closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None: closure =","\"\"\" if closure is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg,","the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import","i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D =","assumed to be unoriented and without external lines. Associate to each vertex of","= {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4,","= [[] for i in items] i = 0 for v, neigh in","num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1)","hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el","Verify the correctness of a base and strong generating set. This is a","Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import","other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list =","a strong generating set relative to it. There are other procedures for verifying","hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens","same line of the graph. The canonical form of the tensor gives a","= [dummies] sym = [sym] else: num_types = len(sym) dgens = [] for","= list(st) a.sort() prev = (0,)*size for h in a: if h[:-2] ==","membership in the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples",">>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g","graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8,","The graph is assumed to be unoriented and without external lines. Associate to","a base and a strong generating set relative to it. There are other","verifying a base and strong generating set, but this one will serve for","2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer,","rmul = Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare two lists of permutations as","'__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in","= [arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el)","but this one will serve for more robust testing. Examples ======== >>> from","A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr =","of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 =","el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates))","sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5])","Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g,","= get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2,","if isinstance(sym, int): num_types = 1 dummies = [dummies] sym = [sym] else:","a list of elements for the centralizer of a subgroup/set/element. This is a","Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>>","tensor are twice the number of lines of the graph num_indices = 0","if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif","is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True)","hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg,","import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \"\"\" Compare two lists of","\"\"\" if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive =","group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import","False return True def _verify_centralizer(group, arg, centr=None): \"\"\" Verify the centralizer of a","of the permutation representing the canonical form of the tensor. Examples ======== >>>","5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2,","used for testing purposes. Since the array form of a permutation is currently","lists of permutations as sets. This is used for testing purposes. Since the","is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens =","get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2,","used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup,","a in first} == \\ {tuple(a) for a in second} def _naive_list_centralizer(self, other,","= PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also","DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See",">>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>>","[2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5]","the graph a symmetric tensor with number of indices equal to the degree","len(neigh) # associate to each vertex its indices; for each line # between","af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements:","[[] for i in items] i = 0 for v, neigh in items:","items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i +=","2 g = [] for v in vertices: g.extend(v) assert len(g) == num_indices","form of the permutation representing the canonical form of the tensor. Examples ========","sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types =","a = Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2, 0,","import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1","from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>>","for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ...","sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul","centralizer_list = [] if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element))","graph num_indices = 0 for v, neigh in items: num_indices += len(neigh) #",">>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also","from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4)","one will serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import","in items] i = 0 for v, neigh in items: for v2 in","_naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is None: centr = group.centralizer(arg) centr_list =",">>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3,","= 0 for v, neigh in items: num_indices += len(neigh) # associate to","index to the vertex which comes first in items, # the odd index","range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i])","return False return True def _verify_centralizer(group, arg, centr=None): \"\"\" Verify the centralizer of","0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \"\"\" from","sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i, gens_i,","... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A","first in items, # the odd index to the other vertex vertices =","Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2, 0, 4, 3])","Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr is None: centr = group.centralizer(arg)","centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Verify the normal","v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g","assert len(g) == num_indices g += [num_indices, num_indices + 1] size = num_indices","of the different types g permutation representing the tensor dummies list of dummy","vertex vertices = [[] for i in items] i = 0 for v,","the graph. This is not an efficient algorithm to get the certificate of",">>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1,","Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import","import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)):","other vertex vertices = [[] for i in items] i = 0 for",">>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a)","_naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D)",">>> c1 [0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16,","gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2,","4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15,","in vertices: vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)): n","to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>>","import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3,","_af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a =","PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st =","_af_invert(pvert) # the indices of the tensor are twice the number of lines","in items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i","gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0, *v)","import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5]) >>>","vertex of the graph a symmetric tensor with number of indices equal to","v = [] for i in range(len(vlen)): n = vlen[i] if n: base,","group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'):","second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return a list","return list(a[0]) def graph_certificate(gr): \"\"\" Return a certificate for the graph gr adjacency","import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0]","SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])])","[x[0] for x in items] pvert = _af_invert(pvert) # the indices of the","\"\"\" Verify the correctness of a base and strong generating set. This is","type `i` base_i, gens_i BSGS for tensors of this type n_i number ot","1 dummies = [dummies] sym = [sym] else: num_types = len(sym) dgens =","= [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \"\"\" return {tuple(a) for a","in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other),","2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9,","sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations","2, 0, 4, 3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>>","first} == \\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from","13, 19, 20, 21] >>> c1 == c2 True \"\"\" from sympy.combinatorics.permutations import","the indices of the tensor are twice the number of lines of the","g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices + 1] size =","in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g =","1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \"\"\" from","c = Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b, c]","'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens =","import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0,","base and strong generating set, but this one will serve for more robust","canonicalize_naive(g, dummies, sym, *v): \"\"\" Canonicalize tensor formed by tensors of the different","a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \"\"\" Return","== c2 True \"\"\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize","3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs","[] for v in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices,","Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is None: closure = group.normal_closure(arg) conjugates =","_naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ========","Associate to each vertex of the graph a symmetric tensor with number of","16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21] >>>","number of indices equal to the degree of the vertex; indices are contracted","be put into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>>","Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4, 0, 1, 2])","from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import","for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i,","vertices = [[] for i in items] i = 0 for v, neigh","for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2","sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens)","hashable and cannot be put into a set. Examples ======== >>> from sympy.combinatorics.permutations","when they correspond to the same line of the graph. The canonical form","from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>>","= {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0,","`i` sym_i symmetry under exchange of two component tensors of type `i` None","ls2) True \"\"\" return {tuple(a) for a in first} == \\ {tuple(a) for","Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>>","from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1,","[] for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i,","is not an efficient algorithm to get the certificate of a graph. Examples","_af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True)",">>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1])","is a naive implementation using the definition of a base and a strong","Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b, c] >>> ls2","from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0,","form of a permutation is currently a list, Permutation is not hashable and","Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A =","1, 3, 4, 5] \"\"\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products,","in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies,","certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1","S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2,","import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True","_verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \"\"\" if centr","tensors of type `i` base_i, gens_i BSGS for tensors of this type n_i"],"string":"[\n \"not hashable and cannot be put into a set. Examples ======== >>> from\",\n \"a certificate for the graph gr adjacency list The graph is assumed to\",\n \">>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is\",\n \">>> b = Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4,\",\n \"from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S\",\n \"= current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg,\",\n \"from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form\",\n \"= _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i])\",\n \"2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 =\",\n \"two component tensors of type `i` None no symmetry 0 commuting 1 anticommuting\",\n \"else return the array form of the permutation representing the canonical form of\",\n \"candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if\",\n \"This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup,\",\n \">>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A =\",\n \"gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in\",\n \"for tensors of type `i` base_i, gens_i BSGS for tensors of this type\",\n \"of the graph. The canonical form of the tensor gives a certificate for\",\n \"This is a brute force implementation that goes over all elements of the\",\n \"a naive implementation using the definition of a base and a strong generating\",\n \"size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies] sym = [sym]\",\n \"for testing purposes. Since the array form of a permutation is currently a\",\n \"of elements for the centralizer of a subgroup/set/element. This is a brute force\",\n \"2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3],\",\n \"{tuple(a) for a in first} == \\\\ {tuple(a) for a in second} def\",\n \"2, 1, 3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import\",\n \"2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3,\",\n \"return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the correctness of\",\n \"= tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for h\",\n \"[0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v = [] for i\",\n \"it. There are other procedures for verifying a base and strong generating set,\",\n \"3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4],\",\n \"contracted when they correspond to the same line of the graph. The canonical\",\n \"0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0, *v) return can\",\n \"= set() for s in S.generate(af=True): h = _af_rmul(g, s) for d in\",\n \"using the definition of a base and a strong generating set relative to\",\n \"symmetry 0 commuting 1 anticommuting Return 0 if the tensor is zero, else\",\n \"_verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A)\",\n \"if h[-1] != prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr):\",\n \"Since the array form of a permutation is currently a list, Permutation is\",\n \"True \\\"\\\"\\\" return {tuple(a) for a in first} == \\\\ {tuple(a) for a\",\n \"sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices:\",\n \"is a brute force implementation that goes over all elements of the group\",\n \"commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other,\",\n \"\\\\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import\",\n \"return 0 prev = h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a certificate\",\n \"dummies list of dummy indices msym symmetry of the metric v is a\",\n \"over all elements of the group and checks for membership in the centralizer.\",\n \">>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3,\",\n \"sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for\",\n \"8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17,\",\n \"5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3,\",\n \"[a, b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True\",\n \"!= candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False\",\n \"for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\"\",\n \"return the array form of the permutation representing the canonical form of the\",\n \"v is a list of (base_i, gens_i, n_i, sym_i) for tensors of type\",\n \"number of lines of the graph num_indices = 0 for v, neigh in\",\n \"i in range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base,\",\n \"items] i = 0 for v, neigh in items: for v2 in neigh:\",\n \"prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h return list(a[0]) def\",\n \"# the odd index to the other vertex vertices = [[] for i\",\n \"_af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in\",\n \"is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import\",\n \"def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a list of\",\n \"centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group,\",\n \"g = [] for v in vertices: g.extend(v) assert len(g) == num_indices g\",\n \"elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af)\",\n \"tensors of type `i` None no symmetry 0 commuting 1 anticommuting Return 0\",\n \"= PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor formed\",\n \"from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = []\",\n \"3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0,\",\n \"``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup\",\n \"= [] if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else:\",\n \"sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>>\",\n \"True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None: closure = group.normal_closure(arg)\",\n \"graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10, 12, 3, 14,\",\n \"2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh\",\n \"sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None: closure = group.normal_closure(arg) conjugates = set() if\",\n \"and a strong generating set relative to it. There are other procedures for\",\n \"tensor is zero, else return the array form of the permutation representing the\",\n \"list of (base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i\",\n \"[dummies] sym = [sym] else: num_types = len(sym) dgens = [] for i\",\n \"ot tensors of type `i` sym_i symmetry under exchange of two component tensors\",\n \"g = g.array_form st = set() for s in S.generate(af=True): h = _af_rmul(g,\",\n \"closure of a subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure\",\n \"_distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if\",\n \"sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1,\",\n \"centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from\",\n \"base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0))\",\n \"0 for v, neigh in items: num_indices += len(neigh) # associate to each\",\n \"from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the normal closure of a subgroup/subset/element in\",\n \"Return 0 if the tensor is zero, else return the array form of\",\n \"h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for h in a:\",\n \"- 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist\",\n \"sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in\",\n \"gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS for tensors\",\n \"of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can\",\n \"c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items\",\n \"arg, centr=None): \\\"\\\"\\\" Verify the centralizer of a group/set/element inside another group. This\",\n \"the group and checks for membership in the centralizer. It is used to\",\n \"PermutationGroup \\\"\\\"\\\" Verify the normal closure of a subgroup/subset/element in a group. This\",\n \"3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1,\",\n \"a group/set/element inside another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups``\",\n \"'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen\",\n \"======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure\",\n \"correspond to the same line of the graph. The canonical form of the\",\n \"which comes first in items, # the odd index to the other vertex\",\n \"for a in first} == \\\\ {tuple(a) for a in second} def _naive_list_centralizer(self,\",\n \"... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>>\",\n \"symmetry under exchange of two component tensors of type `i` None no symmetry\",\n \"None no symmetry 0 commuting 1 anticommuting Return 0 if the tensor is\",\n \"naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor\",\n \"False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def\",\n \"else: num_types = len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i],\",\n \"1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer,\",\n \"= graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1,\",\n \"procedures for verifying a base and strong generating set, but this one will\",\n \"centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is None:\",\n \"a list, Permutation is not hashable and cannot be put into a set.\",\n \"1 v = [] for i in range(len(vlen)): n = vlen[i] if n:\",\n \"prev = h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a certificate for the\",\n \"3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 =\",\n \"of (base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS\",\n \"num_types = len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size\",\n \"_naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a list of elements\",\n \"list(D.generate(af=True)) g = g.array_form st = set() for s in S.generate(af=True): h =\",\n \"4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2,\",\n \"the graph num_indices = 0 for v, neigh in items: num_indices += len(neigh)\",\n \"2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5],\",\n \"_naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base,\",\n \"= v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens =\",\n \"centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See\",\n \"each vertex its indices; for each line # between two vertices assign the\",\n \"return True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the centralizer of a group/set/element\",\n \"n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS for tensors of\",\n \"= SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3,\",\n \"brute force implementation that goes over all elements of the group and checks\",\n \"used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer\",\n \"import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]),\",\n \"5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations\",\n \"<reponame>ethankward/sympy<filename>sympy/combinatorics/testutil.py from sympy.combinatorics import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def\",\n \"the array form of the permutation representing the canonical form of the tensor.\",\n \"a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1,\",\n \"of a base and a strong generating set relative to it. There are\",\n \"for tensors of this type n_i number ot tensors of type `i` sym_i\",\n \"the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>>\",\n \"gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4],\",\n \"if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group,\",\n \"def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the normal closure\",\n \"of the graph num_indices = 0 for v, neigh in items: num_indices +=\",\n \"generating set, but this one will serve for more robust testing. Examples ========\",\n \"used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup)\",\n \"st = set() for s in S.generate(af=True): h = _af_rmul(g, s) for d\",\n \"sym_i symmetry under exchange of two component tensors of type `i` None no\",\n \"in items: num_indices += len(neigh) # associate to each vertex its indices; for\",\n \"in items, # the odd index to the other vertex vertices = [[]\",\n \"the centralizer of a group/set/element inside another group. This is used for testing\",\n \"n_i number ot tensors of type `i` sym_i symmetry under exchange of two\",\n \"< pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in\",\n \"= h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a certificate for the graph\",\n \"lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if not\",\n \"indices msym symmetry of the metric v is a list of (base_i, gens_i,\",\n \"dummies = [dummies] sym = [sym] else: num_types = len(sym) dgens = []\",\n \"algorithm to get the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil\",\n \"def graph_certificate(gr): \\\"\\\"\\\" Return a certificate for the graph gr adjacency list The\",\n \"if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for\",\n \"gens) current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order()\",\n \"v, neigh in items: num_indices += len(neigh) # associate to each vertex its\",\n \"x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens)\",\n \"centr=None): \\\"\\\"\\\" Verify the centralizer of a group/set/element inside another group. This is\",\n \"to get the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import\",\n \"# associate to each vertex its indices; for each line # between two\",\n \"4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2,\",\n \"the normal closure of a subgroup/subset/element in a group. This is used to\",\n \"return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify\",\n \"PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor formed by\",\n \"items: num_indices += len(neigh) # associate to each vertex its indices; for each\",\n \"1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3,\",\n \"component tensors of type `i` None no symmetry 0 commuting 1 anticommuting Return\",\n \"for s in S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q\",\n \"4, 3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1 =\",\n \"_af_rmul v1 = [] for i in range(len(v)): base_i, gens_i, n_i, sym_i =\",\n \"for each line # between two vertices assign the # even index to\",\n \"= Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists of permutations as sets.\",\n \"currently a list, Permutation is not hashable and cannot be put into a\",\n \"4, 0, 1, 2]) >>> ls1 = [a, b, c] >>> ls2 =\",\n \"AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\"\",\n \"Canonicalize tensor formed by tensors of the different types g permutation representing the\",\n \"sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in\",\n \"group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from\",\n \"a subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ========\",\n \"0 if the tensor is zero, else return the array form of the\",\n \"from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i\",\n \"num_indices = 0 for v, neigh in items: num_indices += len(neigh) # associate\",\n \"sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True))\",\n \"hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen in subgr_gens:\",\n \"`i` None no symmetry 0 commuting 1 anticommuting Return 0 if the tensor\",\n \"isinstance(sym, int): num_types = 1 dummies = [dummies] sym = [sym] else: num_types\",\n \"S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True))\",\n \"v in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices +\",\n \"graph a symmetric tensor with number of indices equal to the degree of\",\n \"a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a) for a in first} ==\",\n \"AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>>\",\n \"between two vertices assign the # even index to the vertex which comes\",\n \"sym, *v): \\\"\\\"\\\" Canonicalize tensor formed by tensors of the different types g\",\n \"tensor formed by tensors of the different types g permutation representing the tensor\",\n \"import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims()\",\n \"gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g,\",\n \"a certificate for the graph. This is not an efficient algorithm to get\",\n \"3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if\",\n \"from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5)\",\n \"graph. The canonical form of the tensor gives a certificate for the graph.\",\n \"True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is None: centr\",\n \"3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]}\",\n \"Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i, gens_i, n_i, sym_i\",\n \"to the other vertex vertices = [[] for i in items] i =\",\n \"are contracted when they correspond to the same line of the graph. The\",\n \"and strong generating set. This is a naive implementation using the definition of\",\n \"b = Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4, 0,\",\n \"is currently a list, Permutation is not hashable and cannot be put into\",\n \"sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>>\",\n \"PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() !=\",\n \"g.array_form st = set() for s in S.generate(af=True): h = _af_rmul(g, s) for\",\n \"checks for membership in the centralizer. It is used to test ``.centralizer()`` from\",\n \"======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D\",\n \"A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S,\",\n \"======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5],\",\n \"S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h))\",\n \"items, # the odd index to the other vertex vertices = [[] for\",\n \"inside another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ========\",\n \"This is not an efficient algorithm to get the certificate of a graph.\",\n \"number ot tensors of type `i` sym_i symmetry under exchange of two component\",\n \"testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup)\",\n \"= SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also\",\n \"import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup\",\n \"size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens])\",\n \"assign the # even index to the vertex which comes first in items,\",\n \"+= [num_indices, num_indices + 1] size = num_indices + 2 assert sorted(g) ==\",\n \"as sets. This is used for testing purposes. Since the array form of\",\n \"= [a, b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2)\",\n \"BSGS for tensors of this type n_i number ot tensors of type `i`\",\n \"def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists of permutations as sets. This is\",\n \"dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size\",\n \"of a base and strong generating set. This is a naive implementation using\",\n \"i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer\",\n \"_cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists of permutations as sets. This is used\",\n \"size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int):\",\n \"the metric v is a list of (base_i, gens_i, n_i, sym_i) for tensors\",\n \"conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens\",\n \"len(g) == num_indices g += [num_indices, num_indices + 1] size = num_indices +\",\n \"A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ========\",\n \"el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize\",\n \"True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items =\",\n \"= PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st\",\n \"in gens) centralizer_list = [] if not af: for element in elements: if\",\n \"be unoriented and without external lines. Associate to each vertex of the graph\",\n \"12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19,\",\n \"line # between two vertices assign the # even index to the vertex\",\n \"in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element)\",\n \"return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group,\",\n \"in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x)\",\n \"5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2)\",\n \"This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups\",\n \"the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>>\",\n \"two vertices assign the # even index to the vertex which comes first\",\n \"import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr =\",\n \"_verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup\",\n \"group/set/element inside another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples\",\n \"(base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i, gens_i BSGS for\",\n \"representing the canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import\",\n \"= [] for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i,\",\n \"4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2,\",\n \"= list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in items]\",\n \"vertex; indices are contracted when they correspond to the same line of the\",\n \"dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies] sym\",\n \"5, 9, 15, 7, 11, 17, 13, 19, 20, 21] >>> c1 ==\",\n \"exchange of two component tensors of type `i` None no symmetry 0 commuting\",\n \"canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4,\",\n \"4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2\",\n \"g += [num_indices, num_indices + 1] size = num_indices + 2 assert sorted(g)\",\n \"_naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import\",\n \"D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0,\",\n \"else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'):\",\n \"for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False\",\n \"the vertex which comes first in items, # the odd index to the\",\n \"AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr)\",\n \"af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a list of elements for the\",\n \"elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen in\",\n \"get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1,\",\n \"of a permutation is currently a list, Permutation is not hashable and cannot\",\n \">>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if\",\n \"import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x\",\n \"if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif\",\n \"[] if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for\",\n \"for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from\",\n \"1 anticommuting Return 0 if the tensor is zero, else return the array\",\n \"sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for\",\n \"Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4,\",\n \"def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the centralizer of a group/set/element inside another\",\n \"for membership in the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``.\",\n \"type `i` None no symmetry 0 commuting 1 anticommuting Return 0 if the\",\n \"1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3,\",\n \"naive implementation using the definition of a base and a strong generating set\",\n \"for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort()\",\n \"indices are contracted when they correspond to the same line of the graph.\",\n \"9, 15, 7, 11, 17, 13, 19, 20, 21] >>> c1 == c2\",\n \"af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\"\",\n \"of the metric v is a list of (base_i, gens_i, n_i, sym_i) for\",\n \"dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x\",\n \"4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0,\",\n \"num_indices += len(neigh) # associate to each vertex its indices; for each line\",\n \"commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif\",\n \"not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in\",\n \"sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens\",\n \"put into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from\",\n \">>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True\",\n \"= Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2, 0, 4,\",\n \"2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist =\",\n \"without external lines. Associate to each vertex of the graph a symmetric tensor\",\n \"vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in vertices: g.extend(v) assert\",\n \"the definition of a base and a strong generating set relative to it.\",\n \">>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also\",\n \"elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for\",\n \"no symmetry 0 commuting 1 anticommuting Return 0 if the tensor is zero,\",\n \"gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2)\",\n \"line of the graph. The canonical form of the tensor gives a certificate\",\n \"neigh in items: num_indices += len(neigh) # associate to each vertex its indices;\",\n \"_verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the correctness of a base and strong generating\",\n \"= _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a\",\n \"items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in\",\n \"Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3,\",\n \"0)) [0, 2, 1, 3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from\",\n \"strong generating set. This is a naive implementation using the definition of a\",\n \"from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import\",\n \"i in items] i = 0 for v, neigh in items: for v2\",\n \"pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v\",\n \"for the graph gr adjacency list The graph is assumed to be unoriented\",\n \"certificate for the graph gr adjacency list The graph is assumed to be\",\n \"from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2,\",\n \"tensor gives a certificate for the graph. This is not an efficient algorithm\",\n \"0 for v, neigh in items: for v2 in neigh: if pvert[v] <\",\n \"len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2))\",\n \"relative to it. There are other procedures for verifying a base and strong\",\n \"range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n,\",\n \"if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1:\",\n \"gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can =\",\n \"size = num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen\",\n \"= list(D.generate(af=True)) g = g.array_form st = set() for s in S.generate(af=True): h\",\n \"for i in items] i = 0 for v, neigh in items: for\",\n \"_verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See\",\n \">>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4,\",\n \"st.add(q) a = list(st) a.sort() prev = (0,)*size for h in a: if\",\n \"= g.array_form st = set() for s in S.generate(af=True): h = _af_rmul(g, s)\",\n \"closure is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens\",\n \"sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2,\",\n \"= lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if\",\n \"array form of the permutation representing the canonical form of the tensor. Examples\",\n \"PermutationGroup \\\"\\\"\\\" Return a list of elements for the centralizer of a subgroup/set/element.\",\n \"(base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups\",\n \"from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a list of elements for the centralizer\",\n \"set() for s in S.generate(af=True): h = _af_rmul(g, s) for d in dlist:\",\n \"It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil\",\n \"sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S =\",\n \"PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 =\",\n \"+ 1] size = num_indices + 2 assert sorted(g) == list(range(size)) g =\",\n \"Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v =\",\n \"def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the correctness of a base and strong\",\n \"num_indices g += [num_indices, num_indices + 1] size = num_indices + 2 assert\",\n \"return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor formed by tensors\",\n \"sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr\",\n \">>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0,\",\n \"_verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None:\",\n \"from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i,\",\n \"tensors of the different types g permutation representing the tensor dummies list of\",\n \"indices; for each line # between two vertices assign the # even index\",\n \"\\\"\\\"\\\" Return a list of elements for the centralizer of a subgroup/set/element. This\",\n \"sympy.combinatorics import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second):\",\n \"v1 = [] for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i]\",\n \"generating set relative to it. There are other procedures for verifying a base\",\n \"even index to the vertex which comes first in items, # the odd\",\n \"the same line of the graph. The canonical form of the tensor gives\",\n \"graph is assumed to be unoriented and without external lines. Associate to each\",\n \"base_i, gens_i BSGS for tensors of this type n_i number ot tensors of\",\n \"a subgroup/set/element. This is a brute force implementation that goes over all elements\",\n \"from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base,\",\n \"the different types g permutation representing the tensor dummies list of dummy indices\",\n \">>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D =\",\n \"form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from\",\n \"for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D\",\n \"tensor dummies list of dummy indices msym symmetry of the metric v is\",\n \"list The graph is assumed to be unoriented and without external lines. Associate\",\n \"\\\"\\\"\\\" Compare two lists of permutations as sets. This is used for testing\",\n \">>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3,\",\n \"af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the correctness of a base and\",\n \"the correctness of a base and strong generating set. This is a naive\",\n \"= set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens =\",\n \"import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]),\",\n \"types g permutation representing the tensor dummies list of dummy indices msym symmetry\",\n \"graph gr adjacency list The graph is assumed to be unoriented and without\",\n \"sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4],\",\n \"lines of the graph num_indices = 0 for v, neigh in items: num_indices\",\n \"PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S\",\n \"tensors of type `i` sym_i symmetry under exchange of two component tensors of\",\n \"arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup\",\n \"the # even index to the vertex which comes first in items, #\",\n \">>> ls1 = [a, b, c] >>> ls2 = [b, c, a] >>>\",\n \"of lines of the graph num_indices = 0 for v, neigh in items:\",\n \"_naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the correctness of a\",\n \"centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list,\",\n \"from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from\",\n \"{0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5],\",\n \"= [] for v in vertices: g.extend(v) assert len(g) == num_indices g +=\",\n \"generating set. This is a naive implementation using the definition of a base\",\n \"from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g =\",\n \"a base and strong generating set, but this one will serve for more\",\n \"from sympy.combinatorics import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first,\",\n \"5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1,\",\n \"of the tensor are twice the number of lines of the graph num_indices\",\n \"closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif\",\n \"of the graph a symmetric tensor with number of indices equal to the\",\n \"hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af)\",\n \"strong generating set relative to it. There are other procedures for verifying a\",\n \"vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices + 1] size\",\n \"\\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import\",\n \"force implementation that goes over all elements of the group and checks for\",\n \"goes over all elements of the group and checks for membership in the\",\n \"range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase,\",\n \"n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1)\",\n \"ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a) for\",\n \"conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v):\",\n \"this type n_i number ot tensors of type `i` sym_i symmetry under exchange\",\n \"in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev\",\n \"sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert =\",\n \"of a subgroup/set/element. This is a brute force implementation that goes over all\",\n \"(SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation\",\n \"in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev =\",\n \"dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S\",\n \"======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None: closure = group.normal_closure(arg) conjugates = set()\",\n \"4, 1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>> c =\",\n \"return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True\",\n \"centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other,\",\n \"purposes. Since the array form of a permutation is currently a list, Permutation\",\n \"canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>>\",\n \"canonical form of the tensor gives a certificate for the graph. This is\",\n \"7, 11, 17, 13, 19, 20, 21] >>> c1 == c2 True \\\"\\\"\\\"\",\n \"symmetric tensor with number of indices equal to the degree of the vertex;\",\n \"they correspond to the same line of the graph. The canonical form of\",\n \"2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]}\",\n \"pvert = [x[0] for x in items] pvert = _af_invert(pvert) # the indices\",\n \"comes first in items, # the odd index to the other vertex vertices\",\n \"n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0, *v) return\",\n \"permutation is currently a list, Permutation is not hashable and cannot be put\",\n \"This is used for testing purposes. Since the array form of a permutation\",\n \"gens = [x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen)\",\n \"element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element):\",\n \"another group. This is used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>>\",\n \"gens_i BSGS for tensors of this type n_i number ot tensors of type\",\n \"= Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b, c] >>>\",\n \"af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\"\",\n \"this one will serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups\",\n \"to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>>\",\n \"*v): \\\"\\\"\\\" Canonicalize tensor formed by tensors of the different types g permutation\",\n \"= gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1\",\n \"x in items] pvert = _af_invert(pvert) # the indices of the tensor are\",\n \"set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists\",\n \"a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups\",\n \"+= 1 v = [] for i in range(len(vlen)): n = vlen[i] if\",\n \"import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A\",\n \"certificate for the graph. This is not an efficient algorithm to get the\",\n \"A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\"\",\n \"Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2,\",\n \"= DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])]\",\n \"neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = []\",\n \"= vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse()\",\n \"This is a naive implementation using the definition of a base and a\",\n \">>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a) for a in first} == \\\\\",\n \"the array form of a permutation is currently a list, Permutation is not\",\n \"for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return\",\n \"sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>> b\",\n \"sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group\",\n \">>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S =\",\n \"elements of the group and checks for membership in the centralizer. It is\",\n \"(SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>>\",\n \"gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0,\",\n \"sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types\",\n \"0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0,\",\n \"4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0,\",\n \"20, 21] >>> c1 == c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from\",\n \"from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda\",\n \"`i` base_i, gens_i BSGS for tensors of this type n_i number ot tensors\",\n \"of type `i` base_i, gens_i BSGS for tensors of this type n_i number\",\n \"== prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h return list(a[0])\",\n \"Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer\",\n \">>> c1 == c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import\",\n \"1, 2]) >>> ls1 = [a, b, c] >>> ls2 = [b, c,\",\n \"[sym] else: num_types = len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i],\",\n \"in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size,\",\n \"h in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0\",\n \"from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert\",\n \"dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor formed by tensors of the different types\",\n \"Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements =\",\n \"for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set()\",\n \"a brute force implementation that goes over all elements of the group and\",\n \"centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg,\",\n \"of the group and checks for membership in the centralizer. It is used\",\n \"elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens = lambda\",\n \"msym symmetry of the metric v is a list of (base_i, gens_i, n_i,\",\n \"the canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive\",\n \"sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation,\",\n \"base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens\",\n \"from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from\",\n \"num_types = 1 dummies = [dummies] sym = [sym] else: num_types = len(sym)\",\n \"odd index to the other vertex vertices = [[] for i in items]\",\n \"list of dummy indices msym symmetry of the metric v is a list\",\n \"is a list of (base_i, gens_i, n_i, sym_i) for tensors of type `i`\",\n \"indices equal to the degree of the vertex; indices are contracted when they\",\n \"reverse=True) pvert = [x[0] for x in items] pvert = _af_invert(pvert) # the\",\n \"that goes over all elements of the group and checks for membership in\",\n \"5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>>\",\n \"D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer\",\n \"base, gens): \\\"\\\"\\\" Verify the correctness of a base and strong generating set.\",\n \"import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3)\",\n \"each vertex of the graph a symmetric tensor with number of indices equal\",\n \"for the graph. This is not an efficient algorithm to get the certificate\",\n \"c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return\",\n \"sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil\",\n \"unoriented and without external lines. Associate to each vertex of the graph a\",\n \"list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] +=\",\n \"current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return\",\n \"\\\"\\\"\\\" Return a certificate for the graph gr adjacency list The graph is\",\n \"to the vertex which comes first in items, # the odd index to\",\n \"if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element\",\n \"set, but this one will serve for more robust testing. Examples ======== >>>\",\n \"vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)): n = vlen[i]\",\n \"implementation using the definition of a base and a strong generating set relative\",\n \"dummy indices msym symmetry of the metric v is a list of (base_i,\",\n \"'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'):\",\n \"== list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)]\",\n \"A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None: closure\",\n \"3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2,\",\n \"test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from\",\n \"is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ...\",\n \"= AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims\",\n \"'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the correctness\",\n \"definition of a base and a strong generating set relative to it. There\",\n \"= PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g\",\n \"None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators\",\n \"import Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i, gens_i, n_i,\",\n \"n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0))\",\n \"centralizer of a group/set/element inside another group. This is used for testing ``.centralizer()``\",\n \">>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import\",\n \"arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the normal closure of a\",\n \"adjacency list The graph is assumed to be unoriented and without external lines.\",\n \"for the centralizer of a subgroup/set/element. This is a brute force implementation that\",\n \"D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form\",\n \">>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1,\",\n \"to be unoriented and without external lines. Associate to each vertex of the\",\n \"from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4)\",\n \"strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate =\",\n \"more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil\",\n \"dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies =\",\n \"sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x:\",\n \">>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3)\",\n \"2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4],\",\n \"of type `i` sym_i symmetry under exchange of two component tensors of type\",\n \"A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups\",\n \"in range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens,\",\n \"n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices))\",\n \"commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = []\",\n \"PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2\",\n \"18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21] >>> c1\",\n \"======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer =\",\n \"of two component tensors of type `i` None no symmetry 0 commuting 1\",\n \"get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for\",\n \"arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for gen\",\n \"type n_i number ot tensors of type `i` sym_i symmetry under exchange of\",\n \"sym_i) for tensors of type `i` base_i, gens_i BSGS for tensors of this\",\n \"v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym,\",\n \"centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from\",\n \"A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is\",\n \"graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1,\",\n \"3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import\",\n \"= len(sym) dgens = [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size -\",\n \"1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11,\",\n \"14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21]\",\n \"canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>>\",\n \"1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>>\",\n \"PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens):\",\n \"are twice the number of lines of the graph num_indices = 0 for\",\n \"elements for the centralizer of a subgroup/set/element. This is a brute force implementation\",\n \"4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from\",\n \"two lists of permutations as sets. This is used for testing purposes. Since\",\n \"testing purposes. Since the array form of a permutation is currently a list,\",\n \"vlen[i] if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies\",\n \"+= len(neigh) # associate to each vertex its indices; for each line #\",\n \"= arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens =\",\n \"vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v = []\",\n \"1] size = num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g)\",\n \"c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6,\",\n \"g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1\",\n \"for x in items] pvert = _af_invert(pvert) # the indices of the tensor\",\n \"h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a certificate for the graph gr\",\n \"type `i` sym_i symmetry under exchange of two component tensors of type `i`\",\n \"the other vertex vertices = [[] for i in items] i = 0\",\n \"from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two\",\n \"all elements of the group and checks for membership in the centralizer. It\",\n \"a.sort() prev = (0,)*size for h in a: if h[:-2] == prev[:-2]: if\",\n \"int): num_types = 1 dummies = [dummies] sym = [sym] else: num_types =\",\n \"= [x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for\",\n \"import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import\",\n \"2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5],\",\n \"21] >>> c1 == c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can\",\n \"'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def\",\n \"permutation representing the canonical form of the tensor. Examples ======== >>> from sympy.combinatorics.testutil\",\n \"= get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g,\",\n \"4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2 =\",\n \"= AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A,\",\n \"PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g =\",\n \"4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1)\",\n \"indices of the tensor are twice the number of lines of the graph\",\n \"elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]),\",\n \"``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups\",\n \"current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group,\",\n \"AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from\",\n \">>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2,\",\n \"neigh in items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1)\",\n \"import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D,\",\n \">>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from\",\n \"[arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure\",\n \"\\\"\\\"\\\" Verify the centralizer of a group/set/element inside another group. This is used\",\n \"2, 3, 4]} >>> c1 = graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1\",\n \"1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'):\",\n \"6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7,\",\n \"c1 == c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs,\",\n \"for verifying a base and strong generating set, but this one will serve\",\n \"!= prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return\",\n \"if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\"\",\n \"to it. There are other procedures for verifying a base and strong generating\",\n \"serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>>\",\n \"import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A,\",\n \"other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a list of elements for\",\n \"for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure =\",\n \"2, 0)) [0, 2, 1, 3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup\",\n \"10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13,\",\n \"= Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v\",\n \"[Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" Canonicalize tensor formed by tensors of the different types g permutation representing\",\n \"gens) centralizer_list = [] if not af: for element in elements: if commutes_with_gens(element):\",\n \"robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import\",\n \"in the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ========\",\n \"\\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for\",\n \"from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import\",\n \"b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\"\",\n \"is assumed to be unoriented and without external lines. Associate to each vertex\",\n \"second): \\\"\\\"\\\" Compare two lists of permutations as sets. This is used for\",\n \"dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set() for s in\",\n \"+= 2 g = [] for v in vertices: g.extend(v) assert len(g) ==\",\n \"subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens\",\n \"sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym,\",\n \"import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>>\",\n \"= [] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S =\",\n \"permutation representing the tensor dummies list of dummy indices msym symmetry of the\",\n \"representing the tensor dummies list of dummy indices msym symmetry of the metric\",\n \"of type `i` None no symmetry 0 commuting 1 anticommuting Return 0 if\",\n \"4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5],\",\n \"= group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive)\",\n \"gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import\",\n \"items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert =\",\n \"for v, neigh in items: num_indices += len(neigh) # associate to each vertex\",\n \"vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in vertices: g.extend(v)\",\n \"= [x[0] for x in items] pvert = _af_invert(pvert) # the indices of\",\n \"Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with\",\n \"list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None):\",\n \"2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3,\",\n \"= group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg,\",\n \"sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>>\",\n \"sets. This is used for testing purposes. Since the array form of a\",\n \"for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in\",\n \"c1 [0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18,\",\n \"current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg, centr=None):\",\n \"prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a\",\n \"in first} == \\\\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False):\",\n \"= num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen =\",\n \"centralizer of a subgroup/set/element. This is a brute force implementation that goes over\",\n \"c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10, 12,\",\n \"s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st)\",\n \"vertex which comes first in items, # the odd index to the other\",\n \"equal to the degree of the vertex; indices are contracted when they correspond\",\n \"i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i))\",\n \"centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'):\",\n \"15, 7, 11, 17, 13, 19, 20, 21] >>> c1 == c2 True\",\n \"2, 3, 4, 1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>>\",\n \"_verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0,\",\n \"pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g = [] for v in vertices:\",\n \"in S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d,\",\n \"implementation that goes over all elements of the group and checks for membership\",\n \"\\\"\\\"\\\" Verify the normal closure of a subgroup/subset/element in a group. This is\",\n \">>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0,\",\n \"PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the correctness of a base\",\n \"5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>>\",\n \"the centralizer of a subgroup/set/element. This is a brute force implementation that goes\",\n \"gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies\",\n \"for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def\",\n \"is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import\",\n \"5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2,\",\n \"in items] pvert = _af_invert(pvert) # the indices of the tensor are twice\",\n \"See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is None: centr =\",\n \"Return a list of elements for the centralizer of a subgroup/set/element. This is\",\n \">>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True\",\n \"for neigh in vertices: vlen[len(neigh)] += 1 v = [] for i in\",\n \"\\\"\\\"\\\" return {tuple(a) for a in first} == \\\\ {tuple(a) for a in\",\n \"each line # between two vertices assign the # even index to the\",\n \"_verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the centralizer of a group/set/element inside another group.\",\n \"subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino():\",\n \"Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>>\",\n \"Compare two lists of permutations as sets. This is used for testing purposes.\",\n \"17, 13, 19, 20, 21] >>> c1 == c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations\",\n \"testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs\",\n \"will serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import AlternatingGroup\",\n \"= group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order():\",\n \"= _af_invert(pvert) # the indices of the tensor are twice the number of\",\n \"PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ========\",\n \"0, 1, 2]) >>> ls1 = [a, b, c] >>> ls2 = [b,\",\n \"of a subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples\",\n \"3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0,\",\n \"from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>>\",\n \"is zero, else return the array form of the permutation representing the canonical\",\n \"index to the other vertex vertices = [[] for i in items] i\",\n \"= 0 for v, neigh in items: for v2 in neigh: if pvert[v]\",\n \"in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices + 1]\",\n \">>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil\",\n \"if the tensor is zero, else return the array form of the permutation\",\n \">>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b,\",\n \"See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None: closure = group.normal_closure(arg) conjugates\",\n \"zero, else return the array form of the permutation representing the canonical form\",\n \"tensor with number of indices equal to the degree of the vertex; indices\",\n \"vertices: vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)): n =\",\n \"======== >>> from sympy.combinatorics.named_groups import AlternatingGroup >>> from sympy.combinatorics.testutil import _verify_bsgs >>> A\",\n \"# between two vertices assign the # even index to the vertex which\",\n \"test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from\",\n \"cannot be put into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation\",\n \"element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self,\",\n \"canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x\",\n \"set relative to it. There are other procedures for verifying a base and\",\n \"3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20,\",\n \"3, 4, 1]) >>> b = Permutation([1, 2, 0, 4, 3]) >>> c\",\n \"an efficient algorithm to get the certificate of a graph. Examples ======== >>>\",\n \"list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a certificate for the graph gr adjacency list\",\n \"sym, size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies] sym =\",\n \"i = 0 for v, neigh in items: for v2 in neigh: if\",\n \"neigh in vertices: vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)):\",\n \"# even index to the vertex which comes first in items, # the\",\n \"graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 = {0:[1, 2,\",\n \"subgr_gens = [arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^\",\n \"in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return\",\n \"and without external lines. Associate to each vertex of the graph a symmetric\",\n \"sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer\",\n \"is used for testing purposes. Since the array form of a permutation is\",\n \"A.base, A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr\",\n \"closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the normal closure of a subgroup/subset/element\",\n \"= [sym] else: num_types = len(sym) dgens = [] for i in range(num_types):\",\n \"h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h return\",\n \"``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups\",\n \"closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor formed by tensors of\",\n \"tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs\",\n \"d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev\",\n \"return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return\",\n \"gr adjacency list The graph is assumed to be unoriented and without external\",\n \"list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert\",\n \"g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2)\",\n \">>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics\",\n \"0 prev = h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a certificate for\",\n \"list, Permutation is not hashable and cannot be put into a set. Examples\",\n \"in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer =\",\n \"with number of indices equal to the degree of the vertex; indices are\",\n \"sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists\",\n \"graph. This is not an efficient algorithm to get the certificate of a\",\n \"by tensors of the different types g permutation representing the tensor dummies list\",\n \"sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S,\",\n \"_cmp_perm_lists \\\"\\\"\\\" if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive\",\n \"from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4,\",\n \"for gen in gens) centralizer_list = [] if not af: for element in\",\n \"gen in gens) centralizer_list = [] if not af: for element in elements:\",\n \"if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list\",\n \"into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil\",\n \"_cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1,\",\n \"[x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen\",\n \"in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from\",\n \">>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5)\",\n \"q = tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for\",\n \"the tensor are twice the number of lines of the graph num_indices =\",\n \"centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other), af) elif hasattr(other, 'array_form'): return _naive_list_centralizer(self,\",\n \"def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor formed by tensors of the\",\n \"g permutation representing the tensor dummies list of dummy indices msym symmetry of\",\n \"len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert = _af_invert(pvert) #\",\n \"subgroup/set/element. This is a brute force implementation that goes over all elements of\",\n \"True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base,\",\n \"if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators]\",\n \"base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can\",\n \"import Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\"\",\n \"0, 4, 3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1\",\n \"= [] for i in range(len(vlen)): n = vlen[i] if n: base, gens\",\n \"None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return\",\n \"base and strong generating set. This is a naive implementation using the definition\",\n \"See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens)\",\n \"of permutations as sets. This is used for testing purposes. Since the array\",\n \"= arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in group.generate_dimino(): for\",\n \"formed by tensors of the different types g permutation representing the tensor dummies\",\n \"of a group/set/element inside another group. This is used for testing ``.centralizer()`` from\",\n \"efficient algorithm to get the certificate of a graph. Examples ======== >>> from\",\n \"correctness of a base and strong generating set. This is a naive implementation\",\n \"the vertex; indices are contracted when they correspond to the same line of\",\n \"to each vertex of the graph a symmetric tensor with number of indices\",\n \"subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym,\",\n \"current_stabilizer = group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() !=\",\n \"if closure is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'):\",\n \"import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i\",\n \"a symmetric tensor with number of indices equal to the degree of the\",\n \"v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies,\",\n \"get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies,\",\n \"in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set() for s\",\n \"base and a strong generating set relative to it. There are other procedures\",\n \"h = _af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q)\",\n \"s in S.generate(af=True): h = _af_rmul(g, s) for d in dlist: q =\",\n \"2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5],\",\n \"normal closure of a subgroup/subset/element in a group. This is used to test\",\n \"Return a certificate for the graph gr adjacency list The graph is assumed\",\n \"of this type n_i number ot tensors of type `i` sym_i symmetry under\",\n \"Verify the centralizer of a group/set/element inside another group. This is used for\",\n \"= dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types = 1 dummies = [dummies]\",\n \"is not hashable and cannot be put into a set. Examples ======== >>>\",\n \"the degree of the vertex; indices are contracted when they correspond to the\",\n \"3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} >>> gr2\",\n \"for v in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices\",\n \"{0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2,\",\n \"4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2,\",\n \"2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations\",\n \"_cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the\",\n \"AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A =\",\n \"3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1\",\n \"i += 2 g = [] for v in vertices: g.extend(v) assert len(g)\",\n \"2]) >>> ls1 = [a, b, c] >>> ls2 = [b, c, a]\",\n \">>> a = Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2,\",\n \"graph_certificate(gr): \\\"\\\"\\\" Return a certificate for the graph gr adjacency list The graph\",\n \"dlist = list(D.generate(af=True)) g = g.array_form st = set() for s in S.generate(af=True):\",\n \"in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a\",\n \"candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order() != 1: return False return\",\n \"the tensor gives a certificate for the graph. This is not an efficient\",\n \"[] for i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens)\",\n \"not an efficient algorithm to get the certificate of a graph. Examples ========\",\n \"Verify the normal closure of a subgroup/subset/element in a group. This is used\",\n \"= graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10, 12, 3,\",\n \"for v, neigh in items: for v2 in neigh: if pvert[v] < pvert[v2]:\",\n \"the odd index to the other vertex vertices = [[] for i in\",\n \"num_indices + 1] size = num_indices + 2 assert sorted(g) == list(range(size)) g\",\n \"= 1 dummies = [dummies] sym = [sym] else: num_types = len(sym) dgens\",\n \"_distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists of permutations\",\n \">>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure\",\n \"_verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the normal closure of\",\n \"There are other procedures for verifying a base and strong generating set, but\",\n \"See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements\",\n \"3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \\\"\\\"\\\"\",\n \"======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is None: centr = group.centralizer(arg) centr_list\",\n \"assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for neigh in\",\n \"list(st) a.sort() prev = (0,)*size for h in a: if h[:-2] == prev[:-2]:\",\n \"array form of a permutation is currently a list, Permutation is not hashable\",\n \"elif hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify\",\n \"======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup\",\n \">>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a =\",\n \"vertex its indices; for each line # between two vertices assign the #\",\n \"and cannot be put into a set. Examples ======== >>> from sympy.combinatorics.permutations import\",\n \"metric v is a list of (base_i, gens_i, n_i, sym_i) for tensors of\",\n \"x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st = set() for\",\n \"elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if commutes_with_gens(element): centralizer_list.append(element) return\",\n \"_cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a) for a in first} == \\\\ {tuple(a)\",\n \"c, a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a) for a in first}\",\n \"x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if not af:\",\n \"SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ========\",\n \">>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0,\",\n \"a base and strong generating set. This is a naive implementation using the\",\n \"of the vertex; indices are contracted when they correspond to the same line\",\n \"items] pvert = _af_invert(pvert) # the indices of the tensor are twice the\",\n \"of dummy indices msym symmetry of the metric v is a list of\",\n \"True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the centralizer of a group/set/element inside\",\n \"in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list\",\n \"S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See\",\n \"Permutation is not hashable and cannot be put into a set. Examples ========\",\n \"3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1,\",\n \"to the degree of the vertex; indices are contracted when they correspond to\",\n \"the graph. The canonical form of the tensor gives a certificate for the\",\n \"0 commuting 1 anticommuting Return 0 if the tensor is zero, else return\",\n \"= PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i]) if current_stabilizer.order()\",\n \"======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from\",\n \"the tensor is zero, else return the array form of the permutation representing\",\n \"11, 17, 13, 19, 20, 21] >>> c1 == c2 True \\\"\\\"\\\" from\",\n \"\\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens =\",\n \"anticommuting Return 0 if the tensor is zero, else return the array form\",\n \"pvert = _af_invert(pvert) # the indices of the tensor are twice the number\",\n \"permutations as sets. This is used for testing purposes. Since the array form\",\n \"the tensor dummies list of dummy indices msym symmetry of the metric v\",\n \"\\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items())\",\n \"+ 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1) for\",\n \"for i in range(len(vlen)): n = vlen[i] if n: base, gens = get_symmetric_group_sgs(i)\",\n \"gens): \\\"\\\"\\\" Verify the correctness of a base and strong generating set. This\",\n \"[[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if\",\n \"# the indices of the tensor are twice the number of lines of\",\n \"the permutation representing the canonical form of the tensor. Examples ======== >>> from\",\n \"[num_indices, num_indices + 1] size = num_indices + 2 assert sorted(g) == list(range(size))\",\n \"group and checks for membership in the centralizer. It is used to test\",\n \"and checks for membership in the centralizer. It is used to test ``.centralizer()``\",\n \"strong generating set, but this one will serve for more robust testing. Examples\",\n \"sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2,\",\n \"3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a,\",\n \"to each vertex its indices; for each line # between two vertices assign\",\n \"dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in range(len(v)):\",\n \"degree of the vertex; indices are contracted when they correspond to the same\",\n \"======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True))\",\n \"hasattr(other, 'array_form'): return _naive_list_centralizer(self, PermutationGroup([other]), af) def _verify_bsgs(group, base, gens): \\\"\\\"\\\" Verify the\",\n \"== num_indices g += [num_indices, num_indices + 1] size = num_indices + 2\",\n \"= list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg,\",\n \"[0, 2, 1, 3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can\",\n \"Permutation from sympy.combinatorics.util import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare\",\n \"1: return False return True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the centralizer\",\n \"group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def\",\n \"sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the normal closure of a subgroup/subset/element in a\",\n \"a list of (base_i, gens_i, n_i, sym_i) for tensors of type `i` base_i,\",\n \"tuple(_af_rmul(d, h)) st.add(q) a = list(st) a.sort() prev = (0,)*size for h in\",\n \"prev = (0,)*size for h in a: if h[:-2] == prev[:-2]: if h[-1]\",\n \"The canonical form of the tensor gives a certificate for the graph. This\",\n \"a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev =\",\n \"its indices; for each line # between two vertices assign the # even\",\n \"of indices equal to the degree of the vertex; indices are contracted when\",\n \"4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\"\",\n \"[0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5,\",\n \"and strong generating set, but this one will serve for more robust testing.\",\n \"Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>>\",\n \"list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x,\",\n \"all(_af_commutes_with(x, gen) for gen in gens) centralizer_list = [] if not af: for\",\n \"tensors of this type n_i number ot tensors of type `i` sym_i symmetry\",\n \"= Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>>\",\n \"twice the number of lines of the graph num_indices = 0 for v,\",\n \"= list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens = lambda x:\",\n \"sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a list of elements for the centralizer of\",\n \"x: len(x[1]), reverse=True) pvert = [x[0] for x in items] pvert = _af_invert(pvert)\",\n \"other procedures for verifying a base and strong generating set, but this one\",\n \">>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>>\",\n \"for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements: if\",\n \"``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>>\",\n \"= _naive_list_centralizer(group, arg, af=True) return _cmp_perm_lists(centr_list, centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups\",\n \"group for i in range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return\",\n \"the graph gr adjacency list The graph is assumed to be unoriented and\",\n \"form of the tensor gives a certificate for the graph. This is not\",\n \"group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure)\",\n \"sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens = gens_products(*v1) dgens\",\n \"get the certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate\",\n \"= [0]*(len(vertices[0])+1) for neigh in vertices: vlen[len(neigh)] += 1 v = [] for\",\n \"v.append((base, gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0,\",\n \"gen) for gen in gens) centralizer_list = [] if not af: for element\",\n \"the number of lines of the graph num_indices = 0 for v, neigh\",\n \"set. This is a naive implementation using the definition of a base and\",\n \"[b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a) for a in\",\n \"current_stabilizer.order() != 1: return False return True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify\",\n \"lines. Associate to each vertex of the graph a symmetric tensor with number\",\n \"gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) size, sbase, sgens =\",\n \"gives a certificate for the graph. This is not an efficient algorithm to\",\n \"ls1 = [a, b, c] >>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1,\",\n \"are other procedures for verifying a base and strong generating set, but this\",\n \"list of elements for the centralizer of a subgroup/set/element. This is a brute\",\n \"== \\\\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups\",\n \"= AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if\",\n \"range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for\",\n \">>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>>\",\n \"arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg]\",\n \"19, 20, 21] >>> c1 == c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert\",\n \"external lines. Associate to each vertex of the graph a symmetric tensor with\",\n \"import PermutationGroup \\\"\\\"\\\" Return a list of elements for the centralizer of a\",\n \"!= 1: return False return True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the\",\n \"3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists\",\n \">>> g = Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 =\",\n \"= (0,)*size for h in a: if h[:-2] == prev[:-2]: if h[-1] !=\",\n \"[] for i in range(len(vlen)): n = vlen[i] if n: base, gens =\",\n \"symmetry of the metric v is a list of (base_i, gens_i, n_i, sym_i)\",\n \"different types g permutation representing the tensor dummies list of dummy indices msym\",\n \"Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists of permutations as sets. This\",\n \"a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import\",\n \"return {tuple(a) for a in first} == \\\\ {tuple(a) for a in second}\",\n \"under exchange of two component tensors of type `i` None no symmetry 0\",\n \"to the same line of the graph. The canonical form of the tensor\",\n \"h[-1] != prev[-1]: return 0 prev = h return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\"\",\n \"of the tensor gives a certificate for the graph. This is not an\",\n \"= Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4, 0, 1,\",\n \"v, neigh in items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i)\",\n \"if n: base, gens = get_symmetric_group_sgs(i) v.append((base, gens, n, 0)) v.reverse() dummies =\",\n \"(0,)*size for h in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]:\",\n \"subgroup/subset/element in a group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>>\",\n \">>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8, 10,\",\n \"======== >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a\",\n \"1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3,\",\n \"a permutation is currently a list, Permutation is not hashable and cannot be\",\n \"a = list(st) a.sort() prev = (0,)*size for h in a: if h[:-2]\",\n \"commuting 1 anticommuting Return 0 if the tensor is zero, else return the\",\n \"from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation,\",\n \"import PermutationGroup \\\"\\\"\\\" Verify the normal closure of a subgroup/subset/element in a group.\",\n \"5], 5:[0, 4]} >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1,\",\n \"5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} >>> c1 = graph_certificate(gr1) >>>\",\n \"DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2,\",\n \">>> from sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A,\",\n \"PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)): candidate\",\n \"set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg\",\n \"^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\"\",\n \"sym = [sym] else: num_types = len(sym) dgens = [] for i in\",\n \"if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return 0 prev = h\",\n \"0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_commutes_with if hasattr(other,\",\n \"associate to each vertex its indices; for each line # between two vertices\",\n \"vertices assign the # even index to the vertex which comes first in\",\n \"{tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup\",\n \"for h in a: if h[:-2] == prev[:-2]: if h[-1] != prev[-1]: return\",\n \"import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3,\",\n \"import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>> b =\",\n \"AlternatingGroup(3) >>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure\",\n \"closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None: closure =\",\n \"\\\"\\\"\\\" if closure is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg,\",\n \"the tensor. Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import\",\n \"i in range(num_types): dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) S = PermutationGroup(sgens) D =\",\n \"assumed to be unoriented and without external lines. Associate to each vertex of\",\n \"= {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4,\",\n \"= [[] for i in items] i = 0 for v, neigh in\",\n \"num_indices + 2 assert sorted(g) == list(range(size)) g = Permutation(g) vlen = [0]*(len(vertices[0])+1)\",\n \"hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el\",\n \"Verify the correctness of a base and strong generating set. This is a\",\n \"Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import\",\n \"other.generators] commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens) centralizer_list =\",\n \"a strong generating set relative to it. There are other procedures for verifying\",\n \"hasattr(other, 'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens\",\n \"same line of the graph. The canonical form of the tensor gives a\",\n \"= [dummies] sym = [sym] else: num_types = len(sym) dgens = [] for\",\n \"= list(st) a.sort() prev = (0,)*size for h in a: if h[:-2] ==\",\n \"membership in the centralizer. It is used to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples\",\n \">>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g\",\n \"graph_certificate(gr1) >>> c2 = graph_certificate(gr2) >>> c1 [0, 2, 4, 6, 1, 8,\",\n \"The graph is assumed to be unoriented and without external lines. Associate to\",\n \"a base and a strong generating set relative to it. There are other\",\n \"verifying a base and strong generating set, but this one will serve for\",\n \"2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer,\",\n \"rmul = Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists of permutations as\",\n \"'__getitem__'): subgr_gens = arg elif hasattr(arg, 'array_form'): subgr_gens = [arg] for el in\",\n \"= [arg] for el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el)\",\n \"but this one will serve for more robust testing. Examples ======== >>> from\",\n \"A.strong_gens) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup strong_gens_distr =\",\n \"of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1 =\",\n \"el in group.generate_dimino(): for gen in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates))\",\n \"sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5])\",\n \"Permutation([1, 3, 2, 0, 4, 5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g,\",\n \"= get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2,\",\n \"if isinstance(sym, int): num_types = 1 dummies = [dummies] sym = [sym] else:\",\n \"a list of elements for the centralizer of a subgroup/set/element. This is a\",\n \"Examples ======== >>> from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>>\",\n \"tensor are twice the number of lines of the graph num_indices = 0\",\n \"if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif\",\n \"is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive = _naive_list_centralizer(group, arg, af=True)\",\n \"hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'): subgr_gens = arg elif hasattr(arg,\",\n \"import _distribute_gens_by_base rmul = Permutation.rmul def _cmp_perm_lists(first, second): \\\"\\\"\\\" Compare two lists of\",\n \"\\\"\\\"\\\" if centr is None: centr = group.centralizer(arg) centr_list = list(centr.generate_dimino(af=True)) centr_list_naive =\",\n \"group. This is used to test sympy.combinatorics.perm_groups.PermutationGroup.normal_closure Examples ======== >>> from sympy.combinatorics.named_groups import\",\n \"False return True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the centralizer of a\",\n \"of the permutation representing the canonical form of the tensor. Examples ======== >>>\",\n \"5]) >>> base2, gens2 = get_symmetric_group_sgs(2) >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2,\",\n \"used for testing purposes. Since the array form of a permutation is currently\",\n \"lists of permutations as sets. This is used for testing purposes. Since the\",\n \"is None: closure = group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens =\",\n \"get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2,\",\n \"used for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup,\",\n \"a in first} == \\\\ {tuple(a) for a in second} def _naive_list_centralizer(self, other,\",\n \"= PermutationGroup([Permutation([0, 1, 2, 3, 4])]) >>> _verify_centralizer(S, A, centr) True See Also\",\n \"DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See\",\n \">>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>>\",\n \"[2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5]\",\n \"the graph a symmetric tensor with number of indices equal to the degree\",\n \"len(neigh) # associate to each vertex its indices; for each line # between\",\n \"af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element)) else: for element in elements:\",\n \"[[] for i in items] i = 0 for v, neigh in items:\",\n \"items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i +=\",\n \"2 g = [] for v in vertices: g.extend(v) assert len(g) == num_indices\",\n \"form of the permutation representing the canonical form of the tensor. Examples ========\",\n \"sgens = gens_products(*v1) dgens = dummy_sgs(dummies, sym, size-2) if isinstance(sym, int): num_types =\",\n \"a = Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2, 0,\",\n \"import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul v1\",\n \"from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1]) >>>\",\n \"for testing ``.centralizer()`` from ``sympy.combinatorics.perm_groups`` Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ...\",\n \"sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs from sympy.combinatorics.permutations import Permutation, _af_rmul\",\n \"centralizer_list = [] if not af: for element in elements: if commutes_with_gens(element): centralizer_list.append(Permutation._af_new(element))\",\n \"graph num_indices = 0 for v, neigh in items: num_indices += len(neigh) #\",\n \">>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True See Also\",\n \"from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4)\",\n \"one will serve for more robust testing. Examples ======== >>> from sympy.combinatorics.named_groups import\",\n \"in items] i = 0 for v, neigh in items: for v2 in\",\n \"_naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is None: centr = group.centralizer(arg) centr_list =\",\n \">>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) [0, 2, 1, 3,\",\n \"= 0 for v, neigh in items: num_indices += len(neigh) # associate to\",\n \"index to the vertex which comes first in items, # the odd index\",\n \"range(len(base)): candidate = PermutationGroup(strong_gens_distr[i]) if current_stabilizer.order() != candidate.order(): return False current_stabilizer = current_stabilizer.stabilizer(base[i])\",\n \"return False return True def _verify_centralizer(group, arg, centr=None): \\\"\\\"\\\" Verify the centralizer of\",\n \"0, (base2, gens2, 2, 0)) [0, 2, 1, 3, 4, 5] \\\"\\\"\\\" from\",\n \"sympy.combinatorics.permutations import Permutation, _af_rmul v1 = [] for i in range(len(v)): base_i, gens_i,\",\n \"... AlternatingGroup) >>> from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A\",\n \"first in items, # the odd index to the other vertex vertices =\",\n \"Permutation([0, 2, 3, 4, 1]) >>> b = Permutation([1, 2, 0, 4, 3])\",\n \"Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr is None: centr = group.centralizer(arg)\",\n \"centr_list_naive) def _verify_normal_closure(group, arg, closure=None): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Verify the normal\",\n \"v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g\",\n \"assert len(g) == num_indices g += [num_indices, num_indices + 1] size = num_indices\",\n \"of the different types g permutation representing the tensor dummies list of dummy\",\n \"vertex vertices = [[] for i in items] i = 0 for v,\",\n \"the graph. This is not an efficient algorithm to get the certificate of\",\n \">>> S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1,\",\n \"Examples ======== >>> from sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.testutil import\",\n \"import PermutationGroup strong_gens_distr = _distribute_gens_by_base(base, gens) current_stabilizer = group for i in range(len(base)):\",\n \"other vertex vertices = [[] for i in items] i = 0 for\",\n \">>> ls2 = [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a)\",\n \"_naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D)\",\n \">>> c1 [0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16,\",\n \"gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2,\",\n \"4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15,\",\n \"in vertices: vlen[len(neigh)] += 1 v = [] for i in range(len(vlen)): n\",\n \"to test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>>\",\n \"import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g = Permutation([1, 3,\",\n \"_af_rmul(g, s) for d in dlist: q = tuple(_af_rmul(d, h)) st.add(q) a =\",\n \"PermutationGroup([Permutation(x) for x in dgens]) dlist = list(D.generate(af=True)) g = g.array_form st =\",\n \"_af_invert(pvert) # the indices of the tensor are twice the number of lines\",\n \"in items: for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i\",\n \"gens, n, 0)) v.reverse() dummies = list(range(num_indices)) can = canonicalize(g, dummies, 0, *v)\",\n \"import Permutation, PermutationGroup >>> g = Permutation([1, 3, 2, 0, 4, 5]) >>>\",\n \"vertex of the graph a symmetric tensor with number of indices equal to\",\n \"v = [] for i in range(len(vlen)): n = vlen[i] if n: base,\",\n \"group.normal_closure(arg) conjugates = set() if hasattr(arg, 'generators'): subgr_gens = arg.generators elif hasattr(arg, '__getitem__'):\",\n \"second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return a list\",\n \"return list(a[0]) def graph_certificate(gr): \\\"\\\"\\\" Return a certificate for the graph gr adjacency\",\n \"import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True) pvert = [x[0]\",\n \"SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])])\",\n \"[x[0] for x in items] pvert = _af_invert(pvert) # the indices of the\",\n \"\\\"\\\"\\\" Verify the correctness of a base and strong generating set. This is\",\n \"type `i` base_i, gens_i BSGS for tensors of this type n_i number ot\",\n \"1 dummies = [dummies] sym = [sym] else: num_types = len(sym) dgens =\",\n \"= [b, c, a] >>> _cmp_perm_lists(ls1, ls2) True \\\"\\\"\\\" return {tuple(a) for a\",\n \"in elements: if commutes_with_gens(element): centralizer_list.append(element) return centralizer_list elif hasattr(other, 'getitem'): return _naive_list_centralizer(self, PermutationGroup(other),\",\n \"2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9,\",\n \"sympy.combinatorics.named_groups import (SymmetricGroup, ... AlternatingGroup) >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.permutations\",\n \"2, 0, 4, 3]) >>> c = Permutation([3, 4, 0, 1, 2]) >>>\",\n \"first} == \\\\ {tuple(a) for a in second} def _naive_list_centralizer(self, other, af=False): from\",\n \"13, 19, 20, 21] >>> c1 == c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import\",\n \"the indices of the tensor are twice the number of lines of the\",\n \"g.extend(v) assert len(g) == num_indices g += [num_indices, num_indices + 1] size =\",\n \"in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2 g =\",\n \"1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ======== sympy.combinatorics.perm_groups.centralizer \\\"\\\"\\\" from\",\n \"c = Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b, c]\",\n \"'generators'): elements = list(self.generate_dimino(af=True)) gens = [x._array_form for x in other.generators] commutes_with_gens =\",\n \"import graph_certificate >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0,\",\n \"base and strong generating set, but this one will serve for more robust\",\n \"canonicalize_naive(g, dummies, sym, *v): \\\"\\\"\\\" Canonicalize tensor formed by tensors of the different\",\n \"a in second} def _naive_list_centralizer(self, other, af=False): from sympy.combinatorics.perm_groups import PermutationGroup \\\"\\\"\\\" Return\",\n \"== c2 True \\\"\\\"\\\" from sympy.combinatorics.permutations import _af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize\",\n \"3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products, dummy_sgs\",\n \"[] for v in vertices: g.extend(v) assert len(g) == num_indices g += [num_indices,\",\n \"Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \\\"\\\"\\\" if closure is None: closure = group.normal_closure(arg) conjugates =\",\n \"_naive_list_centralizer(D, D) [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] See Also ========\",\n \"Associate to each vertex of the graph a symmetric tensor with number of\",\n \"16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21] >>>\",\n \"number of indices equal to the degree of the vertex; indices are contracted\",\n \"be put into a set. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>>\",\n \"Permutation([1, 2, 0, 4, 3]) >>> c = Permutation([3, 4, 0, 1, 2])\",\n \"from sympy.combinatorics.testutil import canonicalize_naive >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs >>> from sympy.combinatorics import\",\n \"for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i, [[]]*n_i,\",\n \"vertices = [[] for i in items] i = 0 for v, neigh\",\n \"for v2 in neigh: if pvert[v] < pvert[v2]: vertices[pvert[v]].append(i) vertices[pvert[v2]].append(i+1) i += 2\",\n \"sympy.combinatorics.testutil import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens)\",\n \"hashable and cannot be put into a set. Examples ======== >>> from sympy.combinatorics.permutations\",\n \"when they correspond to the same line of the graph. The canonical form\",\n \"from sympy.combinatorics.testutil import _verify_normal_closure >>> S = SymmetricGroup(3) >>> A = AlternatingGroup(3) >>>\",\n \"= {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0,\",\n \"`i` sym_i symmetry under exchange of two component tensors of type `i` None\",\n \"ls2) True \\\"\\\"\\\" return {tuple(a) for a in first} == \\\\ {tuple(a) for\",\n \"Examples ======== >>> from sympy.combinatorics.testutil import _naive_list_centralizer >>> from sympy.combinatorics.named_groups import DihedralGroup >>>\",\n \"from sympy.combinatorics.named_groups import DihedralGroup >>> D = DihedralGroup(4) >>> _naive_list_centralizer(D, D) [Permutation([0, 1,\",\n \"[] for i in range(len(v)): base_i, gens_i, n_i, sym_i = v[i] v1.append((base_i, gens_i,\",\n \"is not an efficient algorithm to get the certificate of a graph. Examples\",\n \"_af_invert from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize items = list(gr.items()) items.sort(key=lambda x: len(x[1]), reverse=True)\",\n \">>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0, 2, 3, 4, 1])\",\n \"is a naive implementation using the definition of a base and a strong\",\n \"Permutation([3, 4, 0, 1, 2]) >>> ls1 = [a, b, c] >>> ls2\",\n \"from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.testutil import _cmp_perm_lists >>> a = Permutation([0,\",\n \"form of a permutation is currently a list, Permutation is not hashable and\",\n \"Permutation >>> from sympy.combinatorics.testutil import _verify_centralizer >>> S = SymmetricGroup(5) >>> A =\",\n \"1, 3, 4, 5] \\\"\\\"\\\" from sympy.combinatorics.perm_groups import PermutationGroup from sympy.combinatorics.tensor_can import gens_products,\",\n \"in subgr_gens: conjugates.add(gen ^ el) naive_closure = PermutationGroup(list(conjugates)) return closure.is_subgroup(naive_closure) def canonicalize_naive(g, dummies,\",\n \"certificate of a graph. Examples ======== >>> from sympy.combinatorics.testutil import graph_certificate >>> gr1\",\n \"S = SymmetricGroup(5) >>> A = AlternatingGroup(5) >>> centr = PermutationGroup([Permutation([0, 1, 2,\",\n \"import _verify_bsgs >>> A = AlternatingGroup(4) >>> A.schreier_sims() >>> _verify_bsgs(A, A.base, A.strong_gens) True\",\n \"_verify_centralizer(S, A, centr) True See Also ======== _naive_list_centralizer, sympy.combinatorics.perm_groups.PermutationGroup.centralizer, _cmp_perm_lists \\\"\\\"\\\" if centr\",\n \"tensors of type `i` base_i, gens_i BSGS for tensors of this type n_i\"\n]","isConversational":false}}},{"rowIdx":91,"cells":{"ngram":{"kind":"list like","value":["recaptcha_secret = \"\" # recaptcha secret for verification duplicate_annotations = False # Should","training videos to be considered recaptcha_secret = \"\" # recaptcha secret for verification","annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os","Should the server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) #","to be considered recaptcha_secret = \"\" # recaptcha secret for verification duplicate_annotations =","= 2 # the minimum number of training videos to be considered recaptcha_secret","= \"http://localhost/\" # your local host database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training =","\"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number of training videos","= \"\" # recaptcha secret for verification duplicate_annotations = False # Should the","of training videos to be considered recaptcha_secret = \"\" # recaptcha secret for","\"http://localhost/\" # your local host database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2","minimum number of training videos to be considered recaptcha_secret = \"\" # recaptcha","# your local host database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2 #","False # Should the server allow for duplicate annotations? import os.path import sys","= False # Should the server allow for duplicate annotations? import os.path import","considered recaptcha_secret = \"\" # recaptcha secret for verification duplicate_annotations = False #","duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import","host database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number","# recaptcha secret for verification duplicate_annotations = False # Should the server allow","number of training videos to be considered recaptcha_secret = \"\" # recaptcha secret","2 # the minimum number of training videos to be considered recaptcha_secret =","server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove","local host database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2 # the minimum","videos to be considered recaptcha_secret = \"\" # recaptcha secret for verification duplicate_annotations","import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os os.environ['PYTHON_EGG_CACHE'] = '/tmp/apache'","import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os os.environ['PYTHON_EGG_CACHE']","= \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number of training","for verification duplicate_annotations = False # Should the server allow for duplicate annotations?","be considered recaptcha_secret = \"\" # recaptcha secret for verification duplicate_annotations = False","# Should the server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__)))","localhost = \"http://localhost/\" # your local host database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training","min_training = 2 # the minimum number of training videos to be considered","\"\" # recaptcha secret for verification duplicate_annotations = False # Should the server","for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server","os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os os.environ['PYTHON_EGG_CACHE'] =","the server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO:","# the minimum number of training videos to be considered recaptcha_secret = \"\"","allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on","server://user:pass@localhost/dbname min_training = 2 # the minimum number of training videos to be","verification duplicate_annotations = False # Should the server allow for duplicate annotations? import","your local host database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2 # the","recaptcha secret for verification duplicate_annotations = False # Should the server allow for","# server://user:pass@localhost/dbname min_training = 2 # the minimum number of training videos to","secret for verification duplicate_annotations = False # Should the server allow for duplicate","duplicate_annotations = False # Should the server allow for duplicate annotations? import os.path","the minimum number of training videos to be considered recaptcha_secret = \"\" #","database = \"mysql://root@localhost/vaticChecker\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number of"],"string":"[\n \"recaptcha_secret = \\\"\\\" # recaptcha secret for verification duplicate_annotations = False # Should\",\n \"training videos to be considered recaptcha_secret = \\\"\\\" # recaptcha secret for verification\",\n \"annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os\",\n \"Should the server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) #\",\n \"to be considered recaptcha_secret = \\\"\\\" # recaptcha secret for verification duplicate_annotations =\",\n \"= 2 # the minimum number of training videos to be considered recaptcha_secret\",\n \"= \\\"http://localhost/\\\" # your local host database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training =\",\n \"\\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number of training videos\",\n \"= \\\"\\\" # recaptcha secret for verification duplicate_annotations = False # Should the\",\n \"of training videos to be considered recaptcha_secret = \\\"\\\" # recaptcha secret for\",\n \"\\\"http://localhost/\\\" # your local host database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2\",\n \"minimum number of training videos to be considered recaptcha_secret = \\\"\\\" # recaptcha\",\n \"# your local host database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2 #\",\n \"False # Should the server allow for duplicate annotations? import os.path import sys\",\n \"= False # Should the server allow for duplicate annotations? import os.path import\",\n \"considered recaptcha_secret = \\\"\\\" # recaptcha secret for verification duplicate_annotations = False #\",\n \"duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import\",\n \"host database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number\",\n \"# recaptcha secret for verification duplicate_annotations = False # Should the server allow\",\n \"number of training videos to be considered recaptcha_secret = \\\"\\\" # recaptcha secret\",\n \"2 # the minimum number of training videos to be considered recaptcha_secret =\",\n \"server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove\",\n \"local host database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2 # the minimum\",\n \"videos to be considered recaptcha_secret = \\\"\\\" # recaptcha secret for verification duplicate_annotations\",\n \"import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os os.environ['PYTHON_EGG_CACHE'] = '/tmp/apache'\",\n \"import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os os.environ['PYTHON_EGG_CACHE']\",\n \"= \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number of training\",\n \"for verification duplicate_annotations = False # Should the server allow for duplicate annotations?\",\n \"be considered recaptcha_secret = \\\"\\\" # recaptcha secret for verification duplicate_annotations = False\",\n \"# Should the server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__)))\",\n \"localhost = \\\"http://localhost/\\\" # your local host database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training\",\n \"min_training = 2 # the minimum number of training videos to be considered\",\n \"\\\"\\\" # recaptcha secret for verification duplicate_annotations = False # Should the server\",\n \"for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server\",\n \"os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on server import os os.environ['PYTHON_EGG_CACHE'] =\",\n \"the server allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO:\",\n \"# the minimum number of training videos to be considered recaptcha_secret = \\\"\\\"\",\n \"allow for duplicate annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove on\",\n \"server://user:pass@localhost/dbname min_training = 2 # the minimum number of training videos to be\",\n \"verification duplicate_annotations = False # Should the server allow for duplicate annotations? import\",\n \"your local host database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2 # the\",\n \"recaptcha secret for verification duplicate_annotations = False # Should the server allow for\",\n \"# server://user:pass@localhost/dbname min_training = 2 # the minimum number of training videos to\",\n \"secret for verification duplicate_annotations = False # Should the server allow for duplicate\",\n \"duplicate_annotations = False # Should the server allow for duplicate annotations? import os.path\",\n \"the minimum number of training videos to be considered recaptcha_secret = \\\"\\\" #\",\n \"database = \\\"mysql://root@localhost/vaticChecker\\\" # server://user:pass@localhost/dbname min_training = 2 # the minimum number of\"\n]","isConversational":false}}},{"rowIdx":92,"cells":{"ngram":{"kind":"list like","value":["inaccurate. If you're having trouble with this class, don't waste your time, just","function and cache the result. _localtime = None def get_default_timezone(): \"\"\" Returns the","of the currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns","This function is designed for use by the template engine. \"\"\" should_convert =","implementation taken from Python's docs. Used only when pytz isn't available, and most","available, and most likely inaccurate. If you're having trouble with this class, don't","def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day,","time zone name, pytz is required. \"\"\" if isinstance(timezone, tzinfo): _active.value = timezone","from Python's docs. Used only when pytz isn't available. \"\"\" def __repr__(self): return","\"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self,","is not None: _active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value,","_time try: import pytz except ImportError: pytz = None from django.conf import settings","or a time zone name. If it is a time zone name, pytz","caller should ensure that they don't receive an invalid value like None. def","described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not None and value.tzinfo.utcoffset(value)","``None``, Django enables the default time zone. \"\"\" def __init__(self, timezone): self.timezone =","is None def make_aware(value, timezone): \"\"\" Makes a naive datetime.datetime in a given","thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone","a time zone name. If it is a time zone name, pytz is","``timezone``. \"\"\" try: # for pytz timezones return timezone.zone except AttributeError: # for","\"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the name of ``timezone``. \"\"\" try:","\"\"\" Checks if value is a datetime and converts it to local time","time, just install pytz. \"\"\" def __init__(self): # This code is moved in","self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt","time zone as a tzinfo instance. This is the time zone defined by","and value.tzinfo.utcoffset(value) is not None def is_naive(value): \"\"\" Determines if a given datetime.datetime","function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the name of","(settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time',","else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return","\"\"\" try: # for pytz timezones return timezone.zone except AttributeError: # for regular","else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert","pytz isn't available, and most likely inaccurate. If you're having trouble with this","zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the name of ``timezone``. \"\"\"","time implementation taken from Python's docs. Used only when pytz isn't available, and","deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None:","timezone.localize(value, is_dst=None) else: # may be wrong around DST changes return value.replace(tzinfo=timezone) def","timezone.normalize(value) return value def now(): \"\"\" Returns an aware or naive datetime.datetime, depending","= pytz.utc if pytz else UTC() \"\"\"UTC time zone as a tzinfo instance.\"\"\"","time.tzset() # because it isn't thread safe. def activate(timezone): \"\"\" Sets the time","self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return","is_aware(value): \"\"\" Determines if a given datetime.datetime is aware. The logic is described","# timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now()","tzinfo subclass or a time zone name. If it is a time zone","is designed for use by the template engine. \"\"\" should_convert = (isinstance(value, datetime)","a time zone name, pytz is required. If it is ``None``, Django enables","return datetime.now() # By design, these four functions don't perform any checks on","_time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC() \"\"\"UTC","override(object): \"\"\" Temporarily set the time zone for the current thread. This is","'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local","functions. # These functions don't change os.environ['TZ'] and call time.tzset() # because it","LocalTimezone(tzinfo): \"\"\" Local time implementation taken from Python's docs. Used only when pytz","\"\"\" from datetime import datetime, timedelta, tzinfo from threading import local import time","self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF","= timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def","UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation","entry, and restores the previously active timezone on exit. The ``timezone`` argument must","= timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is None:","and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities def","time zone, unless another time zone is specified. \"\"\" if timezone is None:","like None. def is_aware(value): \"\"\" Determines if a given datetime.datetime is aware. The","local time. Local time is defined by the current time zone, unless another","may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes","= timezone.normalize(value) return value def now(): \"\"\" Returns an aware or naive datetime.datetime,","is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo","pytz is required. If it is ``None``, Django enables the default time zone.","return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second,","http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone):","None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if","pytz = None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone',","a datetime and converts it to local time if necessary. If use_tz is","dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst >","by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value class override(object): \"\"\" Temporarily set","Returns the currently active time zone as a tzinfo instance. \"\"\" return getattr(_active,","a tzinfo subclass or a time zone name. If it is a time","in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None","zone for the current thread. The ``timezone`` argument must be an instance of","in a function and cache the result. _localtime = None def get_default_timezone(): \"\"\"","time zones return timezone.localize(value, is_dst=None) else: # may be wrong around DST changes","def get_current_timezone_name(): \"\"\" Returns the name of the currently active time zone. \"\"\"","_localtime # This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns","manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the","not None def is_naive(value): \"\"\" Determines if a given datetime.datetime is naive. The","dt): return ZERO def tzname(self, dt): return \"UTC\" def dst(self, dt): return ZERO","dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)]","Local time is defined by the current time zone, unless another time zone","available and fallbacks when it isn't. \"\"\" from datetime import datetime, timedelta, tzinfo","This is a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on","self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone","timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation taken from Python's docs. Used only when","default time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \"\"\" Returns","# This code is moved in __init__ to execute it as late as","tzinfo from threading import local import time as _time try: import pytz except","\"\"\" Unsets the time zone for the current thread. Django will then use","of ``timezone``. \"\"\" try: # for pytz timezones return timezone.zone except AttributeError: #","datetime, timedelta, tzinfo from threading import local import time as _time try: import","If it is a time zone name, pytz is required. \"\"\" if isinstance(timezone,","is not None def is_naive(value): \"\"\" Determines if a given datetime.datetime is naive.","as _time try: import pytz except ImportError: pytz = None from django.conf import","when it's available and fallbacks when it isn't. \"\"\" from datetime import datetime,","be an instance of a tzinfo subclass or a time zone name. If","if necessary. If use_tz is provided and is not None, that will force","a naive datetime.datetime in a given time zone aware. \"\"\" if hasattr(timezone, 'localize'):","for the current thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to","expression in a function and cache the result. _localtime = None def get_default_timezone():","= local() def get_current_timezone(): \"\"\" Returns the currently active time zone as a","functions don't perform any checks on their arguments. # The caller should ensure",":func:`get_current_timezone`. \"\"\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz","if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if","aware. \"\"\" if hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value,","it a time zone name, pytz is required. If it is ``None``, Django","_active.value class override(object): \"\"\" Temporarily set the time zone for the current thread.","code is moved in __init__ to execute it as late as possible #","you're having trouble with this class, don't waste your time, just install pytz.","\"\"\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \"\"\"","and converts it to local time if necessary. If use_tz is provided and","value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \"\"\" Determines","utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if","ImportError: pytz = None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone',","it isn't. \"\"\" from datetime import datetime, timedelta, tzinfo from threading import local","else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO","'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None) else: # may","an aware datetime.datetime naive in a given time zone. \"\"\" value = value.astimezone(timezone)","If use_tz is provided and is not None, that will force the value","try: # for pytz timezones return timezone.zone except AttributeError: # for regular tzinfo","# These functions don't change os.environ['TZ'] and call time.tzset() # because it isn't","= LocalTimezone() return _localtime # This function exists for consistency with get_current_timezone_name def","def get_default_timezone_name(): \"\"\" Returns the name of the default time zone. \"\"\" return","provided and is not None, that will force the value to be converted","checks on their arguments. # The caller should ensure that they don't receive","as a tzinfo instance.\"\"\" # In order to avoid accessing the settings at","force the value to be converted (or not), overriding the value of settings.USE_TZ.","= self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \"\"\" Checks if","timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET","timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate()","avoid accessing the settings at compile time, # wrap the expression in a","zone for the current thread. Django will then use the time zone defined","return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else:","def is_aware(value): \"\"\" Determines if a given datetime.datetime is aware. The logic is","hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None) else: #","pytz when it's available and fallbacks when it isn't. \"\"\" from datetime import","dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0","= self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt): if","return ZERO class LocalTimezone(tzinfo): \"\"\" Local time implementation taken from Python's docs. Used","Timezone selection functions. # These functions don't change os.environ['TZ'] and call time.tzset() #","return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \"\"\"","is_naive(value): \"\"\" Determines if a given datetime.datetime is naive. The logic is described","converts it to local time if necessary. If use_tz is provided and is","ZERO = timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation taken from Python's docs. Used","exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone else: del","taken from Python's docs. Used only when pytz isn't available. \"\"\" def __repr__(self):","else: # may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone):","= (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt)","\"\"\" Returns the name of the currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone())","if a given datetime.datetime is aware. The logic is described in Python's docs:","\"\"\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \"\"\" Returns the currently active","isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid","def now(): \"\"\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \"\"\"","the template engine. \"\"\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is","isn't thread safe. def activate(timezone): \"\"\" Sets the time zone for the current","and restores the previously active timezone on exit. The ``timezone`` argument must be","any checks on their arguments. # The caller should ensure that they don't","they don't receive an invalid value like None. def is_aware(value): \"\"\" Determines if","in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is","zones return timezone.localize(value, is_dst=None) else: # may be wrong around DST changes return","\"\"\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def","zone aware. \"\"\" if hasattr(timezone, 'localize'): # available for pytz time zones return","import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware',","return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions don't perform","None def get_default_timezone(): \"\"\" Returns the default time zone as a tzinfo instance.","is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\" % timezone)","zone is specified. \"\"\" if timezone is None: timezone = get_current_timezone() value =","value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value)","Python's docs. Used only when pytz isn't available, and most likely inaccurate. If","of settings.USE_TZ. This function is designed for use by the template engine. \"\"\"","the timezone on entry, and restores the previously active timezone on exit. The","accessing the settings at compile time, # wrap the expression in a function","in __init__ to execute it as late as possible # See get_default_timezone(). self.STDOFFSET","time zone defined by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value class override(object):","pytz.utc if pytz else UTC() \"\"\"UTC time zone as a tzinfo instance.\"\"\" #","settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value class override(object): \"\"\" Temporarily set the","required. If it is ``None``, Django enables the default time zone. \"\"\" def","subclass or a time zone name. If it is a time zone name,","and is not None, that will force the value to be converted (or","value.tzinfo.utcoffset(value) is not None def is_naive(value): \"\"\" Determines if a given datetime.datetime is","wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes an aware","AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone","\"\"\" Converts an aware datetime.datetime to local time. Local time is defined by","dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst","name. If it is a time zone name, pytz is required. \"\"\" if","Sets the time zone for the current thread. The ``timezone`` argument must be","\"\"\" UTC implementation taken from Python's docs. Used only when pytz isn't available.","import datetime, timedelta, tzinfo from threading import local import time as _time try:","ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month,","a time zone name, pytz is required. \"\"\" if isinstance(timezone, tzinfo): _active.value =","datetime.datetime to local time. Local time is defined by the current time zone,","default time zone. \"\"\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active,","\"\"\" Makes a naive datetime.datetime in a given time zone aware. \"\"\" if","set the time zone for the current thread. This is a context manager","instance of a ``tzinfo`` subclass, a time zone name, or ``None``. If is","is ``None``, Django enables the default time zone. \"\"\" def __init__(self, timezone): self.timezone","use the time zone defined by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value","else: return datetime.now() # By design, these four functions don't perform any checks","= timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF =","template engine. \"\"\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None","Local time implementation taken from Python's docs. Used only when pytz isn't available,","by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global _localtime if _localtime is None: if","_localtime = None def get_default_timezone(): \"\"\" Returns the default time zone as a","most likely inaccurate. If you're having trouble with this class, don't waste your","safe. def activate(timezone): \"\"\" Sets the time zone for the current thread. The","return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt):","the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global _localtime if","See also :func:`get_current_timezone`. \"\"\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring)","return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \"\"\" Returns the currently active time","is a time zone name, pytz is required. \"\"\" if isinstance(timezone, tzinfo): _active.value","not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\" % timezone) def","def deactivate(): \"\"\" Unsets the time zone for the current thread. Django will","The ``timezone`` argument must be an instance of a tzinfo subclass or a","arguments. # The caller should ensure that they don't receive an invalid value","aware datetime.datetime naive in a given time zone. \"\"\" value = value.astimezone(timezone) if","of a ``tzinfo`` subclass, a time zone name, or ``None``. If is it","not None: _active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None):","The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None","is not None, that will force the value to be converted (or not),","at compile time, # wrap the expression in a function and cache the","from threading import local import time as _time try: import pytz except ImportError:","that they don't receive an invalid value like None. def is_aware(value): \"\"\" Determines","naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is","\"\"\" Determines if a given datetime.datetime is aware. The logic is described in","make_naive(value, timezone): \"\"\" Makes an aware datetime.datetime naive in a given time zone.","settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return","and local time zones ZERO = timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation taken","# UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo): \"\"\" UTC","return \"UTC\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \"\"\" Local time implementation","if pytz else UTC() \"\"\"UTC time zone as a tzinfo instance.\"\"\" # In","isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is not None:","or naive datetime.datetime, depending on settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit shows that","a given datetime.datetime is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo","dst(self, dt): return ZERO class LocalTimezone(tzinfo): \"\"\" Local time implementation taken from Python's","from Python's docs. Used only when pytz isn't available, and most likely inaccurate.","an invalid value like None. def is_aware(value): \"\"\" Determines if a given datetime.datetime","on exit. The ``timezone`` argument must be an instance of a ``tzinfo`` subclass,","dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt =","helper functions. This module uses pytz when it's available and fallbacks when it","functions don't change os.environ['TZ'] and call time.tzset() # because it isn't thread safe.","(or not), overriding the value of settings.USE_TZ. This function is designed for use","= value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones value =","time zones value = timezone.normalize(value) return value def now(): \"\"\" Returns an aware","'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time","if hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None) else:","return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes an aware datetime.datetime naive in a","# See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET","not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This","available. \"\"\" def __repr__(self): return \"<UTC>\" def utcoffset(self, dt): return ZERO def tzname(self,","None, that will force the value to be converted (or not), overriding the","None def make_aware(value, timezone): \"\"\" Makes a naive datetime.datetime in a given time","perform any checks on their arguments. # The caller should ensure that they","\"\"\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is","result. _localtime = None def get_default_timezone(): \"\"\" Returns the default time zone as","basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone()","time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the name of ``timezone``.","Checks if value is a datetime and converts it to local time if","should ensure that they don't receive an invalid value like None. def is_aware(value):","invalid value like None. def is_aware(value): \"\"\" Determines if a given datetime.datetime is","and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return","'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones","is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None or value.tzinfo.utcoffset(value)","a given time zone aware. \"\"\" if hasattr(timezone, 'localize'): # available for pytz","def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt):","design, these four functions don't perform any checks on their arguments. # The","don't change os.environ['TZ'] and call time.tzset() # because it isn't thread safe. def","else: _localtime = LocalTimezone() return _localtime # This function exists for consistency with","# Timezone selection functions. # These functions don't change os.environ['TZ'] and call time.tzset()","thread safe. def activate(timezone): \"\"\" Sets the time zone for the current thread.","it is ``None``, Django enables the default time zone. \"\"\" def __init__(self, timezone):","unless another time zone is specified. \"\"\" if timezone is None: timezone =","current thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to set the","\"\"\" if hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None)","another time zone is specified. \"\"\" if timezone is None: timezone = get_current_timezone()","_time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz","is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is","True)) return localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None): \"\"\"","\"value\"): del _active.value class override(object): \"\"\" Temporarily set the time zone for the","use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else","In order to avoid accessing the settings at compile time, # wrap the","or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \"\"\" Makes a naive datetime.datetime in","current time zone, unless another time zone is specified. \"\"\" if timezone is","raise ValueError(\"Invalid timezone: %r\" % timezone) def deactivate(): \"\"\" Unsets the time zone","described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is","engine. \"\"\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else","an aware datetime.datetime to local time. Local time is defined by the current","None: _active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \"\"\"","thread. The ``timezone`` argument must be an instance of a tzinfo subclass or","tzinfo instance. \"\"\" return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the name","zone as a tzinfo instance.\"\"\" # In order to avoid accessing the settings","= None def get_default_timezone(): \"\"\" Returns the default time zone as a tzinfo","name, pytz is required. \"\"\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone,","thread. Django will then use the time zone defined by settings.TIME_ZONE. \"\"\" if","def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0,","from datetime import datetime, timedelta, tzinfo from threading import local import time as","instance.\"\"\" # In order to avoid accessing the settings at compile time, #","Determines if a given datetime.datetime is aware. The logic is described in Python's","else: raise ValueError(\"Invalid timezone: %r\" % timezone) def deactivate(): \"\"\" Unsets the time","possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else:","argument must be an instance of a ``tzinfo`` subclass, a time zone name,","not None, that will force the value to be converted (or not), overriding","time as _time try: import pytz except ImportError: pytz = None from django.conf","ZERO def tzname(self, dt): return \"UTC\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo):","def template_localtime(value, use_tz=None): \"\"\" Checks if value is a datetime and converts it","specified. \"\"\" if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if","value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \"\"\" Makes a naive datetime.datetime in a","UTC(tzinfo): \"\"\" UTC implementation taken from Python's docs. Used only when pytz isn't","time zone name, or ``None``. If is it a time zone name, pytz","pytz else UTC() \"\"\"UTC time zone as a tzinfo instance.\"\"\" # In order","# Utilities def localtime(value, timezone=None): \"\"\" Converts an aware datetime.datetime to local time.","cache the result. _localtime = None def get_default_timezone(): \"\"\" Returns the default time","late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET =","to local time if necessary. If use_tz is provided and is not None,","\"\"\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is","don't perform any checks on their arguments. # The caller should ensure that","class, don't waste your time, just install pytz. \"\"\" def __init__(self): # This","name of ``timezone``. \"\"\" try: # for pytz timezones return timezone.zone except AttributeError:","now(): \"\"\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \"\"\" if","is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime #","naive datetime.datetime, depending on settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc)","instance. \"\"\" return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the name of","traceback): if self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value #","0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc =","make_aware(value, timezone): \"\"\" Makes a naive datetime.datetime in a given time zone aware.","return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year,","also :func:`get_current_timezone`. \"\"\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and","def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone","# for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection","is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value)","and most likely inaccurate. If you're having trouble with this class, don't waste","is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE)","is a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry,","datetime.datetime is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return","else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt =","tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp =","(dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt","time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \"\"\" Returns the","available for pytz time zones value = timezone.normalize(value) return value def now(): \"\"\"","available for pytz time zones return timezone.localize(value, is_dst=None) else: # may be wrong","pytz isn't available. \"\"\" def __repr__(self): return \"<UTC>\" def utcoffset(self, dt): return ZERO","# This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the","If it is ``None``, Django enables the default time zone. \"\"\" def __init__(self,","changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes an aware datetime.datetime naive in","datetime) and (settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value) and","don't receive an invalid value like None. def is_aware(value): \"\"\" Determines if a","dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute,","UTC() \"\"\"UTC time zone as a tzinfo instance.\"\"\" # In order to avoid","[ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] #","active time zone as a tzinfo instance. \"\"\" return getattr(_active, \"value\", get_default_timezone()) def","del _active.value class override(object): \"\"\" Temporarily set the time zone for the current","self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \"\"\" Checks if value","Converts an aware datetime.datetime to local time. Local time is defined by the","except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) #","\"\"\" if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone,","Django will then use the time zone defined by settings.TIME_ZONE. \"\"\" if hasattr(_active,","def activate(timezone): \"\"\" Sets the time zone for the current thread. The ``timezone``","self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self,","return tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC() \"\"\"UTC time","time if necessary. If use_tz is provided and is not None, that will","return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the name of the currently","of a tzinfo subclass or a time zone name. If it is a","moved in __init__ to execute it as late as possible # See get_default_timezone().","aware datetime.datetime to local time. Local time is defined by the current time","= None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate',","if value is a datetime and converts it to local time if necessary.","Returns the name of ``timezone``. \"\"\" try: # for pytz timezones return timezone.zone","the value to be converted (or not), overriding the value of settings.USE_TZ. This","\"<UTC>\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return \"UTC\" def dst(self,","os.environ['TZ'] and call time.tzset() # because it isn't thread safe. def activate(timezone): \"\"\"","This code is moved in __init__ to execute it as late as possible","timezone.zone except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now)","_active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\" % timezone) def deactivate(): \"\"\"","function is designed for use by the template engine. \"\"\" should_convert = (isinstance(value,","the time zone for the current thread. This is a context manager that","timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz","timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone","is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four","uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the previously active","wrap the expression in a function and cache the result. _localtime = None","class LocalTimezone(tzinfo): \"\"\" Local time implementation taken from Python's docs. Used only when","naive datetime.datetime in a given time zone aware. \"\"\" if hasattr(timezone, 'localize'): #","tzinfo instance. This is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`.","the current thread. The ``timezone`` argument must be an instance of a tzinfo","The caller should ensure that they don't receive an invalid value like None.","datetime.datetime is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return","currently active time zone as a tzinfo instance. \"\"\" return getattr(_active, \"value\", get_default_timezone())","deactivate(): \"\"\" Unsets the time zone for the current thread. Django will then","for the current thread. The ``timezone`` argument must be an instance of a","0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc","context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores","current thread. Django will then use the time zone defined by settings.TIME_ZONE. \"\"\"","pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\" %","value to be converted (or not), overriding the value of settings.USE_TZ. This function","by the current time zone, unless another time zone is specified. \"\"\" if","time zone for the current thread. The ``timezone`` argument must be an instance","time. Local time is defined by the current time zone, unless another time","'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones ZERO =","This is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global","in a given time zone. \"\"\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): #","timedelta, tzinfo from threading import local import time as _time try: import pytz","datetime import datetime, timedelta, tzinfo from threading import local import time as _time","def _get_timezone_name(timezone): \"\"\" Returns the name of ``timezone``. \"\"\" try: # for pytz","utc = pytz.utc if pytz else UTC() \"\"\"UTC time zone as a tzinfo","_localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None:","an instance of a ``tzinfo`` subclass, a time zone name, or ``None``. If","local() def get_current_timezone(): \"\"\" Returns the currently active time zone as a tzinfo","datetime.datetime naive in a given time zone. \"\"\" value = value.astimezone(timezone) if hasattr(timezone,","on their arguments. # The caller should ensure that they don't receive an","a function and cache the result. _localtime = None def get_default_timezone(): \"\"\" Returns","def is_naive(value): \"\"\" Determines if a given datetime.datetime is naive. The logic is","time zone name. If it is a time zone name, pytz is required.","# for pytz timezones return timezone.zone except AttributeError: # for regular tzinfo objects","zone. \"\"\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None)","def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value,","is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities","module uses pytz when it's available and fallbacks when it isn't. \"\"\" from","\"\"\" Makes an aware datetime.datetime naive in a given time zone. \"\"\" value","on settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower","time zone. \"\"\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz","time zone is specified. \"\"\" if timezone is None: timezone = get_current_timezone() value","None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type,","get_current_timezone_name(): \"\"\" Returns the name of the currently active time zone. \"\"\" return","] # UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo): \"\"\"","Temporarily set the time zone for the current thread. This is a context","docs. Used only when pytz isn't available. \"\"\" def __repr__(self): return \"<UTC>\" def","_active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \"\"\" Checks","a ``tzinfo`` subclass, a time zone name, or ``None``. If is it a","\"\"\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones","If is it a time zone name, pytz is required. If it is","current thread. The ``timezone`` argument must be an instance of a tzinfo subclass","the time zone defined by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value class","use_tz is provided and is not None, that will force the value to","get_current_timezone(): \"\"\" Returns the currently active time zone as a tzinfo instance. \"\"\"","Django enables the default time zone. \"\"\" def __init__(self, timezone): self.timezone = timezone","timezone=None): \"\"\" Converts an aware datetime.datetime to local time. Local time is defined","as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone)","# available for pytz time zones value = timezone.normalize(value) return value def now():","as a tzinfo instance. This is the time zone defined by settings.TIME_ZONE. See","use_tz=None): \"\"\" Checks if value is a datetime and converts it to local","else UTC() \"\"\"UTC time zone as a tzinfo instance.\"\"\" # In order to","threading import local import time as _time try: import pytz except ImportError: pytz","four functions don't perform any checks on their arguments. # The caller should","def make_naive(value, timezone): \"\"\" Makes an aware datetime.datetime naive in a given time","Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not","when pytz isn't available, and most likely inaccurate. If you're having trouble with","as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET","_localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function exists","value = timezone.normalize(value) return value def now(): \"\"\" Returns an aware or naive","defined by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value class override(object): \"\"\" Temporarily","= [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ]","is required. If it is ``None``, Django enables the default time zone. \"\"\"","time zones ZERO = timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation taken from Python's","functions. This module uses pytz when it's available and fallbacks when it isn't.","'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones ZERO = timedelta(0)","is specified. \"\"\" if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone)","__exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone else:","by the template engine. \"\"\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz","local import time as _time try: import pytz except ImportError: pytz = None","uses pytz when it's available and fallbacks when it isn't. \"\"\" from datetime","these four functions don't perform any checks on their arguments. # The caller","the result. _localtime = None def get_default_timezone(): \"\"\" Returns the default time zone","docs. Used only when pytz isn't available, and most likely inaccurate. If you're","activate(timezone): \"\"\" Sets the time zone for the current thread. The ``timezone`` argument","consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the name of the default time","argument must be an instance of a tzinfo subclass or a time zone","is required. \"\"\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and","is_dst=None) else: # may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value,","timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self):","isn't. \"\"\" from datetime import datetime, timedelta, tzinfo from threading import local import","%r\" % timezone) def deactivate(): \"\"\" Unsets the time zone for the current","set the timezone on entry, and restores the previously active timezone on exit.","datetime.datetime, depending on settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is","not), overriding the value of settings.USE_TZ. This function is designed for use by","a given datetime.datetime is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo","instance of a tzinfo subclass or a time zone name. If it is","return value def now(): \"\"\" Returns an aware or naive datetime.datetime, depending on","the default time zone. \"\"\" def __init__(self, timezone): self.timezone = timezone self.old_timezone =","is provided and is not None, that will force the value to be","and fallbacks when it isn't. \"\"\" from datetime import datetime, timedelta, tzinfo from","overriding the value of settings.USE_TZ. This function is designed for use by the","\"\"\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \"\"\" if settings.USE_TZ:","datetime.datetime in a given time zone aware. \"\"\" if hasattr(timezone, 'localize'): # available","pytz time zones return timezone.localize(value, is_dst=None) else: # may be wrong around DST","dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return","the currently active time zone as a tzinfo instance. \"\"\" return getattr(_active, \"value\",","\"\"\" Returns the default time zone as a tzinfo instance. This is the","if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'):","Unsets the time zone for the current thread. Django will then use the","pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime","self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET","def localtime(value, timezone=None): \"\"\" Converts an aware datetime.datetime to local time. Local time","for pytz time zones value = timezone.normalize(value) return value def now(): \"\"\" Returns","timezone) def deactivate(): \"\"\" Unsets the time zone for the current thread. Django","for consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the name of the default","it isn't thread safe. def activate(timezone): \"\"\" Sets the time zone for the","__init__ to execute it as late as possible # See get_default_timezone(). self.STDOFFSET =","tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz else","with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the name of the default time zone.","and (settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value) and getattr(value,","> 0 utc = pytz.utc if pytz else UTC() \"\"\"UTC time zone as","naive in a given time zone. \"\"\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'):","try: import pytz except ImportError: pytz = None from django.conf import settings __all__","None: _active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\" % timezone) def deactivate():","ValueError(\"Invalid timezone: %r\" % timezone) def deactivate(): \"\"\" Unsets the time zone for","= pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\" % timezone) def deactivate(): \"\"\" Unsets","= get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time","# wrap the expression in a function and cache the result. _localtime =","docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None","http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def","if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def","_localtime = LocalTimezone() return _localtime # This function exists for consistency with get_current_timezone_name","import local import time as _time try: import pytz except ImportError: pytz =","See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET =","self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt):","compile time, # wrap the expression in a function and cache the result.","\"\"\" def __init__(self): # This code is moved in __init__ to execute it","must be an instance of a ``tzinfo`` subclass, a time zone name, or","localtime(value, timezone=None): \"\"\" Converts an aware datetime.datetime to local time. Local time is","# The caller should ensure that they don't receive an invalid value like","that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the previously","# may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\"","Returns the name of the currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def","if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return","Python's docs. Used only when pytz isn't available. \"\"\" def __repr__(self): return \"<UTC>\"","DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes an aware datetime.datetime naive","class override(object): \"\"\" Temporarily set the time zone for the current thread. This","If you're having trouble with this class, don't waste your time, just install","localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None): \"\"\" Converts an","\"\"\" Temporarily set the time zone for the current thread. This is a","global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not","as a tzinfo instance. \"\"\" return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns","self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\"","exists for consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the name of the","having trouble with this class, don't waste your time, just install pytz. \"\"\"","# available for pytz time zones return timezone.localize(value, is_dst=None) else: # may be","the default time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \"\"\"","def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt):","ensure that they don't receive an invalid value like None. def is_aware(value): \"\"\"","\"\"\" if hasattr(_active, \"value\"): del _active.value class override(object): \"\"\" Temporarily set the time","if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET -","value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \"\"\" Makes a","required. \"\"\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz","else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value","waste your time, just install pytz. \"\"\" def __init__(self): # This code is","a tzinfo instance. \"\"\" return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the","value # Utilities def localtime(value, timezone=None): \"\"\" Converts an aware datetime.datetime to local","timezone): \"\"\" Makes an aware datetime.datetime naive in a given time zone. \"\"\"","pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\" % timezone) def deactivate(): \"\"\" Unsets the","exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value","def get_default_timezone(): \"\"\" Returns the default time zone as a tzinfo instance. This","value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes an aware datetime.datetime naive in a given","only when pytz isn't available, and most likely inaccurate. If you're having trouble","getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities def localtime(value,","and call time.tzset() # because it isn't thread safe. def activate(timezone): \"\"\" Sets","given datetime.datetime is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\"","the current thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to set","'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones ZERO","the name of the default time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active = local()","and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value","get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones","is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo","only when pytz isn't available. \"\"\" def __repr__(self): return \"<UTC>\" def utcoffset(self, dt):","zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \"\"\" Returns the currently","# because it isn't thread safe. def activate(timezone): \"\"\" Sets the time zone","\"\"\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz)","datetime and converts it to local time if necessary. If use_tz is provided","in a given time zone aware. \"\"\" if hasattr(timezone, 'localize'): # available for","self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self,","logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not None","(isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value)","get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the name of the currently active time zone.","_get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the name of ``timezone``. \"\"\" try: # for","this class, don't waste your time, just install pytz. \"\"\" def __init__(self): #","__repr__(self): return \"<UTC>\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return \"UTC\"","name of the currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\"","then use the time zone defined by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del","zone as a tzinfo instance. This is the time zone defined by settings.TIME_ZONE.","\"\"\" Returns the name of the default time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active","def get_current_timezone(): \"\"\" Returns the currently active time zone as a tzinfo instance.","the name of the currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone):","zone defined by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value class override(object): \"\"\"","value def now(): \"\"\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ.","settings at compile time, # wrap the expression in a function and cache","the time zone for the current thread. Django will then use the time","return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \"\"\" Makes","\"\"\" Sets the time zone for the current thread. The ``timezone`` argument must","timezone on exit. The ``timezone`` argument must be an instance of a ``tzinfo``","given datetime.datetime is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\"","zone name, or ``None``. If is it a time zone name, pytz is","the default time zone as a tzinfo instance. This is the time zone","if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is not","_active.value # Templates def template_localtime(value, use_tz=None): \"\"\" Checks if value is a datetime","hasattr(_active, \"value\"): del _active.value class override(object): \"\"\" Temporarily set the time zone for","24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions","except ImportError: pytz = None from django.conf import settings __all__ = [ 'utc',","= pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function exists for","'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC","don't waste your time, just install pytz. \"\"\" def __init__(self): # This code","None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not","Templates def template_localtime(value, use_tz=None): \"\"\" Checks if value is a datetime and converts","if a given datetime.datetime is naive. The logic is described in Python's docs:","when pytz isn't available. \"\"\" def __repr__(self): return \"<UTC>\" def utcoffset(self, dt): return","ZERO class LocalTimezone(tzinfo): \"\"\" Local time implementation taken from Python's docs. Used only","order to avoid accessing the settings at compile time, # wrap the expression","pytz time zones value = timezone.normalize(value) return value def now(): \"\"\" Returns an","implementation taken from Python's docs. Used only when pytz isn't available. \"\"\" def","'make_naive', ] # UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo):","for use by the template engine. \"\"\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ","zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global _localtime if _localtime is","activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value =","the currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the","Returns the default time zone as a tzinfo instance. This is the time","The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not","zones ZERO = timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation taken from Python's docs.","self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is","def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \"\"\" Local time implementation taken from","\"\"\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc)","it is a time zone name, pytz is required. \"\"\" if isinstance(timezone, tzinfo):","aware or naive datetime.datetime, depending on settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit shows","None def is_naive(value): \"\"\" Determines if a given datetime.datetime is naive. The logic","datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions don't change os.environ['TZ']","logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None or","zones value = timezone.normalize(value) return value def now(): \"\"\" Returns an aware or","return ZERO def tzname(self, dt): return \"UTC\" def dst(self, dt): return ZERO class","if use_tz is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True))","These functions don't change os.environ['TZ'] and call time.tzset() # because it isn't thread","get_default_timezone_name(): \"\"\" Returns the name of the default time zone. \"\"\" return _get_timezone_name(get_default_timezone())","UTC implementation taken from Python's docs. Used only when pytz isn't available. \"\"\"","# In order to avoid accessing the settings at compile time, # wrap","\"\"\"Timezone helper functions. This module uses pytz when it's available and fallbacks when","use by the template engine. \"\"\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if","likely inaccurate. If you're having trouble with this class, don't waste your time,","it as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight:","dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp","This module uses pytz when it's available and fallbacks when it isn't. \"\"\"","depending on settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24%","isn't available, and most likely inaccurate. If you're having trouble with this class,","\"\"\" Local time implementation taken from Python's docs. Used only when pytz isn't","if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime","return timezone.zone except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return","def make_aware(value, timezone): \"\"\" Makes a naive datetime.datetime in a given time zone","= timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone)","must be an instance of a tzinfo subclass or a time zone name.","``timezone`` argument must be an instance of a ``tzinfo`` subclass, a time zone","_get_timezone_name(timezone): \"\"\" Returns the name of ``timezone``. \"\"\" try: # for pytz timezones","converted (or not), overriding the value of settings.USE_TZ. This function is designed for","given time zone. \"\"\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for","Makes an aware datetime.datetime naive in a given time zone. \"\"\" value =","settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE,","a given time zone. \"\"\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available","= getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone)","def utcoffset(self, dt): return ZERO def tzname(self, dt): return \"UTC\" def dst(self, dt):","active timezone on exit. The ``timezone`` argument must be an instance of a","just install pytz. \"\"\" def __init__(self): # This code is moved in __init__","_time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(),","LocalTimezone() return _localtime # This function exists for consistency with get_current_timezone_name def get_default_timezone_name():","utcoffset(self, dt): return ZERO def tzname(self, dt): return \"UTC\" def dst(self, dt): return","datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these","for the current thread. Django will then use the time zone defined by","By design, these four functions don't perform any checks on their arguments. #","is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is not None and","to avoid accessing the settings at compile time, # wrap the expression in","= timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation taken from Python's docs. Used only","a time zone name, or ``None``. If is it a time zone name,","to be converted (or not), overriding the value of settings.USE_TZ. This function is","django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive',","around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes an aware datetime.datetime","taken from Python's docs. Used only when pytz isn't available, and most likely","None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \"\"\" Determines if a given","\"UTC\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \"\"\" Local time implementation taken","defined by the current time zone, unless another time zone is specified. \"\"\"","when it isn't. \"\"\" from datetime import datetime, timedelta, tzinfo from threading import","dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt):","None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function","dt): return \"UTC\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \"\"\" Local time","dt): return ZERO class LocalTimezone(tzinfo): \"\"\" Local time implementation taken from Python's docs.","if should_convert else value # Utilities def localtime(value, timezone=None): \"\"\" Converts an aware","the settings at compile time, # wrap the expression in a function and","time zone as a tzinfo instance.\"\"\" # In order to avoid accessing the","hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value) return value.replace(tzinfo=None)","local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions don't","timezone.tzname(local_now) # Timezone selection functions. # These functions don't change os.environ['TZ'] and call","timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() #","default time zone as a tzinfo instance. This is the time zone defined","if self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value # Templates","datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions don't perform any","zone for the current thread. This is a context manager that uses ``~django.utils.timezone.activate()``","tzname(self, dt): return \"UTC\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \"\"\" Local","to set the timezone on entry, and restores the previously active timezone on","instance. This is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\"","\"\"\" Determines if a given datetime.datetime is naive. The logic is described in","restores the previously active timezone on exit. The ``timezone`` argument must be an","get_default_timezone(): \"\"\" Returns the default time zone as a tzinfo instance. This is","time zone for the current thread. Django will then use the time zone","= (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz) and not","if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime","time zone. \"\"\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value',","value like None. def is_aware(value): \"\"\" Determines if a given datetime.datetime is aware.","shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By","'make_aware', 'make_naive', ] # UTC and local time zones ZERO = timedelta(0) class","that will force the value to be converted (or not), overriding the value","and pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone: %r\"","will then use the time zone defined by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"):","The ``timezone`` argument must be an instance of a ``tzinfo`` subclass, a time","timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): #","= _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC()","for pytz time zones return timezone.localize(value, is_dst=None) else: # may be wrong around","# By design, these four functions don't perform any checks on their arguments.","execute it as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if","your time, just install pytz. \"\"\" def __init__(self): # This code is moved","zone, unless another time zone is specified. \"\"\" if timezone is None: timezone","be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \"\"\" Makes an","\"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the name of the currently active time","to local time. Local time is defined by the current time zone, unless","Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def","% timezone) def deactivate(): \"\"\" Unsets the time zone for the current thread.","defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global _localtime if _localtime is None:","\"\"\" def __repr__(self): return \"<UTC>\" def utcoffset(self, dt): return ZERO def tzname(self, dt):","to execute it as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone)","timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else:","name of the default time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active = local() def","_get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \"\"\" Returns the currently active time zone","self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF","time, # wrap the expression in a function and cache the result. _localtime","should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz) and","dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp)","__repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET","self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value # Templates def","self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self,","an instance of a tzinfo subclass or a time zone name. If it","template_localtime(value, use_tz=None): \"\"\" Checks if value is a datetime and converts it to","if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else:","the name of ``timezone``. \"\"\" try: # for pytz timezones return timezone.zone except","'value', None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self,","aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is","timezone on entry, and restores the previously active timezone on exit. The ``timezone``","pytz timezones return timezone.zone except AttributeError: # for regular tzinfo objects local_now =","pytz. \"\"\" def __init__(self): # This code is moved in __init__ to execute","dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return","active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the name of","not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \"\"\" Determines if a","Used only when pytz isn't available, and most likely inaccurate. If you're having","a tzinfo instance.\"\"\" # In order to avoid accessing the settings at compile","with this class, don't waste your time, just install pytz. \"\"\" def __init__(self):","_active.value = timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value =","Used only when pytz isn't available. \"\"\" def __repr__(self): return \"<UTC>\" def utcoffset(self,","for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions.","None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else:","be an instance of a ``tzinfo`` subclass, a time zone name, or ``None``.","# Templates def template_localtime(value, use_tz=None): \"\"\" Checks if value is a datetime and","is defined by the current time zone, unless another time zone is specified.","enables the default time zone. \"\"\" def __init__(self, timezone): self.timezone = timezone self.old_timezone","for pytz timezones return timezone.zone except AttributeError: # for regular tzinfo objects local_now","``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the previously active timezone","__init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if","docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \"\"\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value,","0 utc = pytz.utc if pytz else UTC() \"\"\"UTC time zone as a","def tzname(self, dt): return \"UTC\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \"\"\"","_localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime =","settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware',","local time if necessary. If use_tz is provided and is not None, that","the current time zone, unless another time zone is specified. \"\"\" if timezone","Makes a naive datetime.datetime in a given time zone aware. \"\"\" if hasattr(timezone,","zone name, pytz is required. If it is ``None``, Django enables the default","the expression in a function and cache the result. _localtime = None def","return \"<UTC>\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return \"UTC\" def","previously active timezone on exit. The ``timezone`` argument must be an instance of","\"\"\" Returns the currently active time zone as a tzinfo instance. \"\"\" return","basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\"Invalid timezone:","it to local time if necessary. If use_tz is provided and is not","slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions don't","if hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value) return","self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate() else:","def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return","timezone): \"\"\" Makes a naive datetime.datetime in a given time zone aware. \"\"\"","value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones value","necessary. If use_tz is provided and is not None, that will force the","time zone as a tzinfo instance. \"\"\" return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name():","None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \"\"\" Makes a naive datetime.datetime","``tzinfo`` subclass, a time zone name, or ``None``. If is it a time","Utilities def localtime(value, timezone=None): \"\"\" Converts an aware datetime.datetime to local time. Local","zone. \"\"\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time","currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the name","tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC() \"\"\"UTC time zone","get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET","the previously active timezone on exit. The ``timezone`` argument must be an instance","should_convert else value # Utilities def localtime(value, timezone=None): \"\"\" Converts an aware datetime.datetime","__enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback):","local time zones ZERO = timedelta(0) class UTC(tzinfo): \"\"\" UTC implementation taken from","and cache the result. _localtime = None def get_default_timezone(): \"\"\" Returns the default","is a datetime and converts it to local time if necessary. If use_tz","settings.USE_TZ. This function is designed for use by the template engine. \"\"\" should_convert","an aware or naive datetime.datetime, depending on settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit","value is a datetime and converts it to local time if necessary. If","settings.USE_TZ. \"\"\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return","_active = local() def get_current_timezone(): \"\"\" Returns the currently active time zone as","return localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None): \"\"\" Converts","tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else:","isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime =","datetime.now() # By design, these four functions don't perform any checks on their","def __repr__(self): return \"<UTC>\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return","Determines if a given datetime.datetime is naive. The logic is described in Python's","``timezone`` argument must be an instance of a tzinfo subclass or a time","= _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if","receive an invalid value like None. def is_aware(value): \"\"\" Determines if a given","return \"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def","del _active.value # Templates def template_localtime(value, use_tz=None): \"\"\" Checks if value is a","tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These","= datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions don't change","tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value","value of settings.USE_TZ. This function is designed for use by the template engine.","stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc","the current thread. Django will then use the time zone defined by settings.TIME_ZONE.","self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt):","'normalize'): # available for pytz time zones value = timezone.normalize(value) return value def","designed for use by the template engine. \"\"\" should_convert = (isinstance(value, datetime) and","pytz except ImportError: pytz = None from django.conf import settings __all__ = [","getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def","\"\"\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value):","trouble with this class, don't waste your time, just install pytz. \"\"\" def","is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available","the value of settings.USE_TZ. This function is designed for use by the template","pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function exists for consistency","zone name, pytz is required. \"\"\" if isinstance(timezone, tzinfo): _active.value = timezone elif","not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value #","the time zone for the current thread. The ``timezone`` argument must be an","return _localtime # This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\"","def __init__(self): # This code is moved in __init__ to execute it as","is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global _localtime","exit. The ``timezone`` argument must be an instance of a ``tzinfo`` subclass, a","This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the name","get_current_timezone_name def get_default_timezone_name(): \"\"\" Returns the name of the default time zone. \"\"\"","tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour,","__init__(self): # This code is moved in __init__ to execute it as late","\"\"\" Returns the name of ``timezone``. \"\"\" try: # for pytz timezones return","time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \"\"\" global _localtime if _localtime","zone as a tzinfo instance. \"\"\" return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\"","- self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def utcoffset(self, dt): if self._isdst(dt): return","time zone aware. \"\"\" if hasattr(timezone, 'localize'): # available for pytz time zones","return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \"\"\" Returns the name of ``timezone``. \"\"\" try: #","tzinfo instance.\"\"\" # In order to avoid accessing the settings at compile time,","hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value) return value","is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \"\"\" Makes a naive","return timezone.localize(value, is_dst=None) else: # may be wrong around DST changes return value.replace(tzinfo=timezone)","is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \"\"\" Determines if","time zone name, pytz is required. If it is ``None``, Django enables the","change os.environ['TZ'] and call time.tzset() # because it isn't thread safe. def activate(timezone):","or ``None``. If is it a time zone name, pytz is required. If","import pytz except ImportError: pytz = None from django.conf import settings __all__ =","of the default time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone():","Returns the name of the default time zone. \"\"\" return _get_timezone_name(get_default_timezone()) _active =","timezones return timezone.zone except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone)","= self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \"<LocalTimezone>\" def","pytz is required. \"\"\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring)","return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def","'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None):","class UTC(tzinfo): \"\"\" UTC implementation taken from Python's docs. Used only when pytz","subclass, a time zone name, or ``None``. If is it a time zone","timezone: %r\" % timezone) def deactivate(): \"\"\" Unsets the time zone for the","Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \"\"\" if settings.USE_TZ: #","regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. #","\"\"\" return getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the name of the","is moved in __init__ to execute it as late as possible # See","return timezone.tzname(local_now) # Timezone selection functions. # These functions don't change os.environ['TZ'] and","selection functions. # These functions don't change os.environ['TZ'] and call time.tzset() # because","from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override',","elif isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else: raise","a tzinfo instance. This is the time zone defined by settings.TIME_ZONE. See also","if hasattr(_active, \"value\"): del _active.value class override(object): \"\"\" Temporarily set the time zone","time is defined by the current time zone, unless another time zone is","import time as _time try: import pytz except ImportError: pytz = None from","'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and","__all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive',","None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate',","that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design,","will force the value to be converted (or not), overriding the value of","None. def is_aware(value): \"\"\" Determines if a given datetime.datetime is aware. The logic","call time.tzset() # because it isn't thread safe. def activate(timezone): \"\"\" Sets the","None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for","else value # Utilities def localtime(value, timezone=None): \"\"\" Converts an aware datetime.datetime to","def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self):","self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self)","zone name. If it is a time zone name, pytz is required. \"\"\"","be converted (or not), overriding the value of settings.USE_TZ. This function is designed","_time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET","\"\"\"UTC time zone as a tzinfo instance.\"\"\" # In order to avoid accessing","on entry, and restores the previously active timezone on exit. The ``timezone`` argument","objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions","a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and","_isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0)","is it a time zone name, pytz is required. If it is ``None``,","their arguments. # The caller should ensure that they don't receive an invalid","use_tz is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return","else: del _active.value # Templates def template_localtime(value, use_tz=None): \"\"\" Checks if value is","install pytz. \"\"\" def __init__(self): # This code is moved in __init__ to","given time zone aware. \"\"\" if hasattr(timezone, 'localize'): # available for pytz time","it's available and fallbacks when it isn't. \"\"\" from datetime import datetime, timedelta,","fallbacks when it isn't. \"\"\" from datetime import datetime, timedelta, tzinfo from threading","isn't available. \"\"\" def __repr__(self): return \"<UTC>\" def utcoffset(self, dt): return ZERO def","time zone for the current thread. This is a context manager that uses","getattr(_active, \"value\", get_default_timezone()) def get_current_timezone_name(): \"\"\" Returns the name of the currently active","name, pytz is required. If it is ``None``, Django enables the default time","because it isn't thread safe. def activate(timezone): \"\"\" Sets the time zone for","``None``. If is it a time zone name, pytz is required. If it","name, or ``None``. If is it a time zone name, pytz is required."],"string":"[\n \"inaccurate. If you're having trouble with this class, don't waste your time, just\",\n \"function and cache the result. _localtime = None def get_default_timezone(): \\\"\\\"\\\" Returns the\",\n \"of the currently active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns\",\n \"This function is designed for use by the template engine. \\\"\\\"\\\" should_convert =\",\n \"implementation taken from Python's docs. Used only when pytz isn't available, and most\",\n \"available, and most likely inaccurate. If you're having trouble with this class, don't\",\n \"def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day,\",\n \"time zone name, pytz is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value = timezone\",\n \"from Python's docs. Used only when pytz isn't available. \\\"\\\"\\\" def __repr__(self): return\",\n \"\\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self,\",\n \"is not None: _active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value,\",\n \"_time try: import pytz except ImportError: pytz = None from django.conf import settings\",\n \"or a time zone name. If it is a time zone name, pytz\",\n \"caller should ensure that they don't receive an invalid value like None. def\",\n \"described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not None and value.tzinfo.utcoffset(value)\",\n \"``None``, Django enables the default time zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone =\",\n \"is None def make_aware(value, timezone): \\\"\\\"\\\" Makes a naive datetime.datetime in a given\",\n \"thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone\",\n \"a time zone name. If it is a time zone name, pytz is\",\n \"``timezone``. \\\"\\\"\\\" try: # for pytz timezones return timezone.zone except AttributeError: # for\",\n \"\\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of ``timezone``. \\\"\\\"\\\" try:\",\n \"\\\"\\\"\\\" Checks if value is a datetime and converts it to local time\",\n \"time, just install pytz. \\\"\\\"\\\" def __init__(self): # This code is moved in\",\n \"self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt\",\n \"time zone as a tzinfo instance. This is the time zone defined by\",\n \"and value.tzinfo.utcoffset(value) is not None def is_naive(value): \\\"\\\"\\\" Determines if a given datetime.datetime\",\n \"function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the name of\",\n \"(settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time',\",\n \"else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return\",\n \"\\\"\\\"\\\" try: # for pytz timezones return timezone.zone except AttributeError: # for regular\",\n \"else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert\",\n \"pytz isn't available, and most likely inaccurate. If you're having trouble with this\",\n \"zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of ``timezone``. \\\"\\\"\\\"\",\n \"time implementation taken from Python's docs. Used only when pytz isn't available, and\",\n \"deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None:\",\n \"timezone.localize(value, is_dst=None) else: # may be wrong around DST changes return value.replace(tzinfo=timezone) def\",\n \"timezone.normalize(value) return value def now(): \\\"\\\"\\\" Returns an aware or naive datetime.datetime, depending\",\n \"= pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC time zone as a tzinfo instance.\\\"\\\"\\\"\",\n \"time.tzset() # because it isn't thread safe. def activate(timezone): \\\"\\\"\\\" Sets the time\",\n \"self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return\",\n \"is_aware(value): \\\"\\\"\\\" Determines if a given datetime.datetime is aware. The logic is described\",\n \"# timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now()\",\n \"tzinfo subclass or a time zone name. If it is a time zone\",\n \"is designed for use by the template engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime)\",\n \"a time zone name, pytz is required. If it is ``None``, Django enables\",\n \"return datetime.now() # By design, these four functions don't perform any checks on\",\n \"_time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC\",\n \"override(object): \\\"\\\"\\\" Temporarily set the time zone for the current thread. This is\",\n \"'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local\",\n \"functions. # These functions don't change os.environ['TZ'] and call time.tzset() # because it\",\n \"LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken from Python's docs. Used only when pytz\",\n \"\\\"\\\"\\\" from datetime import datetime, timedelta, tzinfo from threading import local import time\",\n \"self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF\",\n \"= timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def\",\n \"UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation\",\n \"entry, and restores the previously active timezone on exit. The ``timezone`` argument must\",\n \"= timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is None:\",\n \"and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities def\",\n \"time zone, unless another time zone is specified. \\\"\\\"\\\" if timezone is None:\",\n \"like None. def is_aware(value): \\\"\\\"\\\" Determines if a given datetime.datetime is aware. The\",\n \"local time. Local time is defined by the current time zone, unless another\",\n \"may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes\",\n \"= timezone.normalize(value) return value def now(): \\\"\\\"\\\" Returns an aware or naive datetime.datetime,\",\n \"is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo\",\n \"pytz is required. If it is ``None``, Django enables the default time zone.\",\n \"return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second,\",\n \"http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone):\",\n \"None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if\",\n \"pytz = None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone',\",\n \"a datetime and converts it to local time if necessary. If use_tz is\",\n \"dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst >\",\n \"by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\" Temporarily set\",\n \"Returns the currently active time zone as a tzinfo instance. \\\"\\\"\\\" return getattr(_active,\",\n \"a tzinfo subclass or a time zone name. If it is a time\",\n \"in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None\",\n \"zone for the current thread. The ``timezone`` argument must be an instance of\",\n \"in a function and cache the result. _localtime = None def get_default_timezone(): \\\"\\\"\\\"\",\n \"time zones return timezone.localize(value, is_dst=None) else: # may be wrong around DST changes\",\n \"def get_current_timezone_name(): \\\"\\\"\\\" Returns the name of the currently active time zone. \\\"\\\"\\\"\",\n \"_localtime # This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns\",\n \"manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the\",\n \"not None def is_naive(value): \\\"\\\"\\\" Determines if a given datetime.datetime is naive. The\",\n \"dt): return ZERO def tzname(self, dt): return \\\"UTC\\\" def dst(self, dt): return ZERO\",\n \"dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)]\",\n \"Local time is defined by the current time zone, unless another time zone\",\n \"available and fallbacks when it isn't. \\\"\\\"\\\" from datetime import datetime, timedelta, tzinfo\",\n \"This is a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on\",\n \"self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone\",\n \"timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from Python's docs. Used only when\",\n \"default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \\\"\\\"\\\" Returns\",\n \"# This code is moved in __init__ to execute it as late as\",\n \"tzinfo from threading import local import time as _time try: import pytz except\",\n \"\\\"\\\"\\\" Unsets the time zone for the current thread. Django will then use\",\n \"of ``timezone``. \\\"\\\"\\\" try: # for pytz timezones return timezone.zone except AttributeError: #\",\n \"datetime, timedelta, tzinfo from threading import local import time as _time try: import\",\n \"If it is a time zone name, pytz is required. \\\"\\\"\\\" if isinstance(timezone,\",\n \"is not None def is_naive(value): \\\"\\\"\\\" Determines if a given datetime.datetime is naive.\",\n \"as _time try: import pytz except ImportError: pytz = None from django.conf import\",\n \"when it's available and fallbacks when it isn't. \\\"\\\"\\\" from datetime import datetime,\",\n \"be an instance of a tzinfo subclass or a time zone name. If\",\n \"if necessary. If use_tz is provided and is not None, that will force\",\n \"a naive datetime.datetime in a given time zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'):\",\n \"for the current thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to\",\n \"expression in a function and cache the result. _localtime = None def get_default_timezone():\",\n \"= local() def get_current_timezone(): \\\"\\\"\\\" Returns the currently active time zone as a\",\n \"functions don't perform any checks on their arguments. # The caller should ensure\",\n \":func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz\",\n \"if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if\",\n \"aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value,\",\n \"it a time zone name, pytz is required. If it is ``None``, Django\",\n \"_active.value class override(object): \\\"\\\"\\\" Temporarily set the time zone for the current thread.\",\n \"code is moved in __init__ to execute it as late as possible #\",\n \"you're having trouble with this class, don't waste your time, just install pytz.\",\n \"\\\"\\\"\\\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \\\"\\\"\\\"\",\n \"and converts it to local time if necessary. If use_tz is provided and\",\n \"value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \\\"\\\"\\\" Determines\",\n \"utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if\",\n \"ImportError: pytz = None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone',\",\n \"it isn't. \\\"\\\"\\\" from datetime import datetime, timedelta, tzinfo from threading import local\",\n \"else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO\",\n \"'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None) else: # may\",\n \"an aware datetime.datetime naive in a given time zone. \\\"\\\"\\\" value = value.astimezone(timezone)\",\n \"If use_tz is provided and is not None, that will force the value\",\n \"try: # for pytz timezones return timezone.zone except AttributeError: # for regular tzinfo\",\n \"# These functions don't change os.environ['TZ'] and call time.tzset() # because it isn't\",\n \"= LocalTimezone() return _localtime # This function exists for consistency with get_current_timezone_name def\",\n \"def get_default_timezone_name(): \\\"\\\"\\\" Returns the name of the default time zone. \\\"\\\"\\\" return\",\n \"provided and is not None, that will force the value to be converted\",\n \"checks on their arguments. # The caller should ensure that they don't receive\",\n \"as a tzinfo instance.\\\"\\\"\\\" # In order to avoid accessing the settings at\",\n \"force the value to be converted (or not), overriding the value of settings.USE_TZ.\",\n \"= self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if\",\n \"timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET\",\n \"timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate()\",\n \"avoid accessing the settings at compile time, # wrap the expression in a\",\n \"zone for the current thread. Django will then use the time zone defined\",\n \"return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else:\",\n \"def is_aware(value): \\\"\\\"\\\" Determines if a given datetime.datetime is aware. The logic is\",\n \"hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None) else: #\",\n \"pytz when it's available and fallbacks when it isn't. \\\"\\\"\\\" from datetime import\",\n \"dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0\",\n \"= self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if\",\n \"return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken from Python's docs. Used\",\n \"Timezone selection functions. # These functions don't change os.environ['TZ'] and call time.tzset() #\",\n \"return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \\\"\\\"\\\"\",\n \"is_naive(value): \\\"\\\"\\\" Determines if a given datetime.datetime is naive. The logic is described\",\n \"converts it to local time if necessary. If use_tz is provided and is\",\n \"ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from Python's docs. Used\",\n \"exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone else: del\",\n \"taken from Python's docs. Used only when pytz isn't available. \\\"\\\"\\\" def __repr__(self):\",\n \"else: # may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone):\",\n \"= (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt)\",\n \"\\\"\\\"\\\" Returns the name of the currently active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone())\",\n \"if a given datetime.datetime is aware. The logic is described in Python's docs:\",\n \"\\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \\\"\\\"\\\" Returns the currently active\",\n \"isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid\",\n \"def now(): \\\"\\\"\\\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\"\",\n \"the template engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is\",\n \"isn't thread safe. def activate(timezone): \\\"\\\"\\\" Sets the time zone for the current\",\n \"and restores the previously active timezone on exit. The ``timezone`` argument must be\",\n \"any checks on their arguments. # The caller should ensure that they don't\",\n \"they don't receive an invalid value like None. def is_aware(value): \\\"\\\"\\\" Determines if\",\n \"in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is\",\n \"zones return timezone.localize(value, is_dst=None) else: # may be wrong around DST changes return\",\n \"\\\"\\\"\\\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def\",\n \"zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): # available for pytz time zones return\",\n \"import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware',\",\n \"return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions don't perform\",\n \"None def get_default_timezone(): \\\"\\\"\\\" Returns the default time zone as a tzinfo instance.\",\n \"is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\" % timezone)\",\n \"zone is specified. \\\"\\\"\\\" if timezone is None: timezone = get_current_timezone() value =\",\n \"value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value)\",\n \"Python's docs. Used only when pytz isn't available, and most likely inaccurate. If\",\n \"of settings.USE_TZ. This function is designed for use by the template engine. \\\"\\\"\\\"\",\n \"the timezone on entry, and restores the previously active timezone on exit. The\",\n \"accessing the settings at compile time, # wrap the expression in a function\",\n \"in __init__ to execute it as late as possible # See get_default_timezone(). self.STDOFFSET\",\n \"time zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value class override(object):\",\n \"pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC time zone as a tzinfo instance.\\\"\\\"\\\" #\",\n \"settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\" Temporarily set the\",\n \"required. If it is ``None``, Django enables the default time zone. \\\"\\\"\\\" def\",\n \"subclass or a time zone name. If it is a time zone name,\",\n \"and is not None, that will force the value to be converted (or\",\n \"value.tzinfo.utcoffset(value) is not None def is_naive(value): \\\"\\\"\\\" Determines if a given datetime.datetime is\",\n \"wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes an aware\",\n \"AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone\",\n \"\\\"\\\"\\\" Converts an aware datetime.datetime to local time. Local time is defined by\",\n \"dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst\",\n \"name. If it is a time zone name, pytz is required. \\\"\\\"\\\" if\",\n \"Sets the time zone for the current thread. The ``timezone`` argument must be\",\n \"\\\"\\\"\\\" UTC implementation taken from Python's docs. Used only when pytz isn't available.\",\n \"import datetime, timedelta, tzinfo from threading import local import time as _time try:\",\n \"ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month,\",\n \"a time zone name, pytz is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value =\",\n \"datetime.datetime to local time. Local time is defined by the current time zone,\",\n \"default time zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active,\",\n \"\\\"\\\"\\\" Makes a naive datetime.datetime in a given time zone aware. \\\"\\\"\\\" if\",\n \"set the time zone for the current thread. This is a context manager\",\n \"instance of a ``tzinfo`` subclass, a time zone name, or ``None``. If is\",\n \"is ``None``, Django enables the default time zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone\",\n \"use the time zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value\",\n \"else: return datetime.now() # By design, these four functions don't perform any checks\",\n \"= timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF =\",\n \"template engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None\",\n \"Local time implementation taken from Python's docs. Used only when pytz isn't available,\",\n \"by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime is None: if\",\n \"_localtime = None def get_default_timezone(): \\\"\\\"\\\" Returns the default time zone as a\",\n \"most likely inaccurate. If you're having trouble with this class, don't waste your\",\n \"safe. def activate(timezone): \\\"\\\"\\\" Sets the time zone for the current thread. The\",\n \"return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt):\",\n \"the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if\",\n \"See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring)\",\n \"return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \\\"\\\"\\\" Returns the currently active time\",\n \"is a time zone name, pytz is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value\",\n \"not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\" % timezone) def\",\n \"def deactivate(): \\\"\\\"\\\" Unsets the time zone for the current thread. Django will\",\n \"The ``timezone`` argument must be an instance of a tzinfo subclass or a\",\n \"arguments. # The caller should ensure that they don't receive an invalid value\",\n \"aware datetime.datetime naive in a given time zone. \\\"\\\"\\\" value = value.astimezone(timezone) if\",\n \"of a ``tzinfo`` subclass, a time zone name, or ``None``. If is it\",\n \"not None: _active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None):\",\n \"The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None\",\n \"is not None, that will force the value to be converted (or not),\",\n \"at compile time, # wrap the expression in a function and cache the\",\n \"from threading import local import time as _time try: import pytz except ImportError:\",\n \"that they don't receive an invalid value like None. def is_aware(value): \\\"\\\"\\\" Determines\",\n \"naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is\",\n \"\\\"\\\"\\\" Determines if a given datetime.datetime is aware. The logic is described in\",\n \"make_naive(value, timezone): \\\"\\\"\\\" Makes an aware datetime.datetime naive in a given time zone.\",\n \"settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return\",\n \"and local time zones ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken\",\n \"# UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC\",\n \"return \\\"UTC\\\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation\",\n \"if pytz else UTC() \\\"\\\"\\\"UTC time zone as a tzinfo instance.\\\"\\\"\\\" # In\",\n \"isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is not None:\",\n \"or naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit shows that\",\n \"a given datetime.datetime is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo\",\n \"dst(self, dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken from Python's\",\n \"from Python's docs. Used only when pytz isn't available, and most likely inaccurate.\",\n \"an invalid value like None. def is_aware(value): \\\"\\\"\\\" Determines if a given datetime.datetime\",\n \"on exit. The ``timezone`` argument must be an instance of a ``tzinfo`` subclass,\",\n \"dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt =\",\n \"helper functions. This module uses pytz when it's available and fallbacks when it\",\n \"functions don't change os.environ['TZ'] and call time.tzset() # because it isn't thread safe.\",\n \"(or not), overriding the value of settings.USE_TZ. This function is designed for use\",\n \"= value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones value =\",\n \"time zones value = timezone.normalize(value) return value def now(): \\\"\\\"\\\" Returns an aware\",\n \"'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time\",\n \"if hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None) else:\",\n \"return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes an aware datetime.datetime naive in a\",\n \"# See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET\",\n \"not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This\",\n \"available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt): return ZERO def tzname(self,\",\n \"None, that will force the value to be converted (or not), overriding the\",\n \"None def make_aware(value, timezone): \\\"\\\"\\\" Makes a naive datetime.datetime in a given time\",\n \"perform any checks on their arguments. # The caller should ensure that they\",\n \"\\\"\\\"\\\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is\",\n \"result. _localtime = None def get_default_timezone(): \\\"\\\"\\\" Returns the default time zone as\",\n \"basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone()\",\n \"time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of ``timezone``.\",\n \"Checks if value is a datetime and converts it to local time if\",\n \"should ensure that they don't receive an invalid value like None. def is_aware(value):\",\n \"invalid value like None. def is_aware(value): \\\"\\\"\\\" Determines if a given datetime.datetime is\",\n \"and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return\",\n \"'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones\",\n \"is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None or value.tzinfo.utcoffset(value)\",\n \"a given time zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): # available for pytz\",\n \"def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt):\",\n \"design, these four functions don't perform any checks on their arguments. # The\",\n \"don't change os.environ['TZ'] and call time.tzset() # because it isn't thread safe. def\",\n \"else: _localtime = LocalTimezone() return _localtime # This function exists for consistency with\",\n \"# Timezone selection functions. # These functions don't change os.environ['TZ'] and call time.tzset()\",\n \"thread safe. def activate(timezone): \\\"\\\"\\\" Sets the time zone for the current thread.\",\n \"it is ``None``, Django enables the default time zone. \\\"\\\"\\\" def __init__(self, timezone):\",\n \"unless another time zone is specified. \\\"\\\"\\\" if timezone is None: timezone =\",\n \"current thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to set the\",\n \"\\\"\\\"\\\" if hasattr(timezone, 'localize'): # available for pytz time zones return timezone.localize(value, is_dst=None)\",\n \"another time zone is specified. \\\"\\\"\\\" if timezone is None: timezone = get_current_timezone()\",\n \"_time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz\",\n \"is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is\",\n \"True)) return localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None): \\\"\\\"\\\"\",\n \"\\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\" Temporarily set the time zone for the\",\n \"use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else\",\n \"In order to avoid accessing the settings at compile time, # wrap the\",\n \"or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \\\"\\\"\\\" Makes a naive datetime.datetime in\",\n \"current time zone, unless another time zone is specified. \\\"\\\"\\\" if timezone is\",\n \"raise ValueError(\\\"Invalid timezone: %r\\\" % timezone) def deactivate(): \\\"\\\"\\\" Unsets the time zone\",\n \"described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is\",\n \"engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else\",\n \"an aware datetime.datetime to local time. Local time is defined by the current\",\n \"None: _active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\"\",\n \"thread. The ``timezone`` argument must be an instance of a tzinfo subclass or\",\n \"tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the name\",\n \"zone as a tzinfo instance.\\\"\\\"\\\" # In order to avoid accessing the settings\",\n \"= None def get_default_timezone(): \\\"\\\"\\\" Returns the default time zone as a tzinfo\",\n \"name, pytz is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone,\",\n \"thread. Django will then use the time zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if\",\n \"def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0,\",\n \"from datetime import datetime, timedelta, tzinfo from threading import local import time as\",\n \"instance.\\\"\\\"\\\" # In order to avoid accessing the settings at compile time, #\",\n \"Determines if a given datetime.datetime is aware. The logic is described in Python's\",\n \"else: raise ValueError(\\\"Invalid timezone: %r\\\" % timezone) def deactivate(): \\\"\\\"\\\" Unsets the time\",\n \"possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else:\",\n \"argument must be an instance of a ``tzinfo`` subclass, a time zone name,\",\n \"not None, that will force the value to be converted (or not), overriding\",\n \"time as _time try: import pytz except ImportError: pytz = None from django.conf\",\n \"ZERO def tzname(self, dt): return \\\"UTC\\\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo):\",\n \"def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value is a datetime and converts it\",\n \"specified. \\\"\\\"\\\" if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if\",\n \"value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \\\"\\\"\\\" Makes a naive datetime.datetime in a\",\n \"UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from Python's docs. Used only when pytz isn't\",\n \"time zone name, or ``None``. If is it a time zone name, pytz\",\n \"pytz else UTC() \\\"\\\"\\\"UTC time zone as a tzinfo instance.\\\"\\\"\\\" # In order\",\n \"# Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime to local time.\",\n \"cache the result. _localtime = None def get_default_timezone(): \\\"\\\"\\\" Returns the default time\",\n \"late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET =\",\n \"to local time if necessary. If use_tz is provided and is not None,\",\n \"\\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is\",\n \"don't perform any checks on their arguments. # The caller should ensure that\",\n \"class, don't waste your time, just install pytz. \\\"\\\"\\\" def __init__(self): # This\",\n \"name of ``timezone``. \\\"\\\"\\\" try: # for pytz timezones return timezone.zone except AttributeError:\",\n \"now(): \\\"\\\"\\\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if\",\n \"is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime #\",\n \"naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc)\",\n \"instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the name of\",\n \"traceback): if self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value #\",\n \"0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc =\",\n \"make_aware(value, timezone): \\\"\\\"\\\" Makes a naive datetime.datetime in a given time zone aware.\",\n \"return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year,\",\n \"also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and\",\n \"def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone\",\n \"# for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection\",\n \"is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value)\",\n \"and most likely inaccurate. If you're having trouble with this class, don't waste\",\n \"is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE)\",\n \"is a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry,\",\n \"datetime.datetime is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return\",\n \"else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt =\",\n \"tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp =\",\n \"(dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt\",\n \"time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \\\"\\\"\\\" Returns the\",\n \"available for pytz time zones value = timezone.normalize(value) return value def now(): \\\"\\\"\\\"\",\n \"available for pytz time zones return timezone.localize(value, is_dst=None) else: # may be wrong\",\n \"pytz isn't available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt): return ZERO\",\n \"# This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the\",\n \"If it is ``None``, Django enables the default time zone. \\\"\\\"\\\" def __init__(self,\",\n \"changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes an aware datetime.datetime naive in\",\n \"datetime) and (settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value) and\",\n \"don't receive an invalid value like None. def is_aware(value): \\\"\\\"\\\" Determines if a\",\n \"dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute,\",\n \"UTC() \\\"\\\"\\\"UTC time zone as a tzinfo instance.\\\"\\\"\\\" # In order to avoid\",\n \"[ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] #\",\n \"active time zone as a tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def\",\n \"del _active.value class override(object): \\\"\\\"\\\" Temporarily set the time zone for the current\",\n \"self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value\",\n \"Converts an aware datetime.datetime to local time. Local time is defined by the\",\n \"except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) #\",\n \"\\\"\\\"\\\" if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone,\",\n \"Django will then use the time zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active,\",\n \"def activate(timezone): \\\"\\\"\\\" Sets the time zone for the current thread. The ``timezone``\",\n \"self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self,\",\n \"return tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC time\",\n \"time if necessary. If use_tz is provided and is not None, that will\",\n \"return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the name of the currently\",\n \"of a tzinfo subclass or a time zone name. If it is a\",\n \"moved in __init__ to execute it as late as possible # See get_default_timezone().\",\n \"aware datetime.datetime to local time. Local time is defined by the current time\",\n \"= None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate',\",\n \"if value is a datetime and converts it to local time if necessary.\",\n \"Returns the name of ``timezone``. \\\"\\\"\\\" try: # for pytz timezones return timezone.zone\",\n \"the value to be converted (or not), overriding the value of settings.USE_TZ. This\",\n \"\\\"<UTC>\\\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return \\\"UTC\\\" def dst(self,\",\n \"os.environ['TZ'] and call time.tzset() # because it isn't thread safe. def activate(timezone): \\\"\\\"\\\"\",\n \"This code is moved in __init__ to execute it as late as possible\",\n \"timezone.zone except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now)\",\n \"_active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\" % timezone) def deactivate(): \\\"\\\"\\\"\",\n \"function is designed for use by the template engine. \\\"\\\"\\\" should_convert = (isinstance(value,\",\n \"the time zone for the current thread. This is a context manager that\",\n \"timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz\",\n \"timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone\",\n \"is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four\",\n \"uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the previously active\",\n \"wrap the expression in a function and cache the result. _localtime = None\",\n \"class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken from Python's docs. Used only when\",\n \"naive datetime.datetime in a given time zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): #\",\n \"tzinfo instance. This is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`.\",\n \"the current thread. The ``timezone`` argument must be an instance of a tzinfo\",\n \"The caller should ensure that they don't receive an invalid value like None.\",\n \"datetime.datetime is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return\",\n \"currently active time zone as a tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone())\",\n \"deactivate(): \\\"\\\"\\\" Unsets the time zone for the current thread. Django will then\",\n \"for the current thread. The ``timezone`` argument must be an instance of a\",\n \"0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc\",\n \"context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores\",\n \"current thread. Django will then use the time zone defined by settings.TIME_ZONE. \\\"\\\"\\\"\",\n \"pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\" %\",\n \"value to be converted (or not), overriding the value of settings.USE_TZ. This function\",\n \"by the current time zone, unless another time zone is specified. \\\"\\\"\\\" if\",\n \"time zone for the current thread. The ``timezone`` argument must be an instance\",\n \"time. Local time is defined by the current time zone, unless another time\",\n \"'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones ZERO =\",\n \"This is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global\",\n \"in a given time zone. \\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): #\",\n \"timedelta, tzinfo from threading import local import time as _time try: import pytz\",\n \"datetime import datetime, timedelta, tzinfo from threading import local import time as _time\",\n \"def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of ``timezone``. \\\"\\\"\\\" try: # for pytz\",\n \"utc = pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC time zone as a tzinfo\",\n \"_localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None:\",\n \"an instance of a ``tzinfo`` subclass, a time zone name, or ``None``. If\",\n \"local() def get_current_timezone(): \\\"\\\"\\\" Returns the currently active time zone as a tzinfo\",\n \"datetime.datetime naive in a given time zone. \\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone,\",\n \"on their arguments. # The caller should ensure that they don't receive an\",\n \"a function and cache the result. _localtime = None def get_default_timezone(): \\\"\\\"\\\" Returns\",\n \"def is_naive(value): \\\"\\\"\\\" Determines if a given datetime.datetime is naive. The logic is\",\n \"time zone name. If it is a time zone name, pytz is required.\",\n \"# for pytz timezones return timezone.zone except AttributeError: # for regular tzinfo objects\",\n \"zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None)\",\n \"def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value,\",\n \"is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities\",\n \"module uses pytz when it's available and fallbacks when it isn't. \\\"\\\"\\\" from\",\n \"\\\"\\\"\\\" Makes an aware datetime.datetime naive in a given time zone. \\\"\\\"\\\" value\",\n \"on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower\",\n \"time zone. \\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz\",\n \"time zone is specified. \\\"\\\"\\\" if timezone is None: timezone = get_current_timezone() value\",\n \"None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type,\",\n \"get_current_timezone_name(): \\\"\\\"\\\" Returns the name of the currently active time zone. \\\"\\\"\\\" return\",\n \"] # UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\"\",\n \"Temporarily set the time zone for the current thread. This is a context\",\n \"docs. Used only when pytz isn't available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def\",\n \"_active.value = self.old_timezone else: del _active.value # Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks\",\n \"a ``tzinfo`` subclass, a time zone name, or ``None``. If is it a\",\n \"\\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones\",\n \"If is it a time zone name, pytz is required. If it is\",\n \"current thread. The ``timezone`` argument must be an instance of a tzinfo subclass\",\n \"the time zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value class\",\n \"use_tz is provided and is not None, that will force the value to\",\n \"get_current_timezone(): \\\"\\\"\\\" Returns the currently active time zone as a tzinfo instance. \\\"\\\"\\\"\",\n \"Django enables the default time zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone = timezone\",\n \"timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime to local time. Local time is defined\",\n \"as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone)\",\n \"# available for pytz time zones value = timezone.normalize(value) return value def now():\",\n \"as a tzinfo instance. This is the time zone defined by settings.TIME_ZONE. See\",\n \"use_tz=None): \\\"\\\"\\\" Checks if value is a datetime and converts it to local\",\n \"else UTC() \\\"\\\"\\\"UTC time zone as a tzinfo instance.\\\"\\\"\\\" # In order to\",\n \"threading import local import time as _time try: import pytz except ImportError: pytz\",\n \"four functions don't perform any checks on their arguments. # The caller should\",\n \"def make_naive(value, timezone): \\\"\\\"\\\" Makes an aware datetime.datetime naive in a given time\",\n \"Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not\",\n \"when pytz isn't available, and most likely inaccurate. If you're having trouble with\",\n \"as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET\",\n \"_localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function exists\",\n \"value = timezone.normalize(value) return value def now(): \\\"\\\"\\\" Returns an aware or naive\",\n \"defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\" Temporarily\",\n \"= [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ]\",\n \"is required. If it is ``None``, Django enables the default time zone. \\\"\\\"\\\"\",\n \"time zones ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from Python's\",\n \"functions. This module uses pytz when it's available and fallbacks when it isn't.\",\n \"'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones ZERO = timedelta(0)\",\n \"is specified. \\\"\\\"\\\" if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone)\",\n \"__exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone else:\",\n \"by the template engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz\",\n \"local import time as _time try: import pytz except ImportError: pytz = None\",\n \"uses pytz when it's available and fallbacks when it isn't. \\\"\\\"\\\" from datetime\",\n \"these four functions don't perform any checks on their arguments. # The caller\",\n \"the result. _localtime = None def get_default_timezone(): \\\"\\\"\\\" Returns the default time zone\",\n \"docs. Used only when pytz isn't available, and most likely inaccurate. If you're\",\n \"activate(timezone): \\\"\\\"\\\" Sets the time zone for the current thread. The ``timezone`` argument\",\n \"consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the name of the default time\",\n \"argument must be an instance of a tzinfo subclass or a time zone\",\n \"is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and\",\n \"is_dst=None) else: # may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value,\",\n \"timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self):\",\n \"isn't. \\\"\\\"\\\" from datetime import datetime, timedelta, tzinfo from threading import local import\",\n \"%r\\\" % timezone) def deactivate(): \\\"\\\"\\\" Unsets the time zone for the current\",\n \"set the timezone on entry, and restores the previously active timezone on exit.\",\n \"datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is\",\n \"not), overriding the value of settings.USE_TZ. This function is designed for use by\",\n \"a given datetime.datetime is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo\",\n \"instance of a tzinfo subclass or a time zone name. If it is\",\n \"return value def now(): \\\"\\\"\\\" Returns an aware or naive datetime.datetime, depending on\",\n \"the default time zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone = timezone self.old_timezone =\",\n \"is provided and is not None, that will force the value to be\",\n \"and fallbacks when it isn't. \\\"\\\"\\\" from datetime import datetime, timedelta, tzinfo from\",\n \"overriding the value of settings.USE_TZ. This function is designed for use by the\",\n \"\\\"\\\"\\\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ:\",\n \"datetime.datetime in a given time zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): # available\",\n \"pytz time zones return timezone.localize(value, is_dst=None) else: # may be wrong around DST\",\n \"dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp) return\",\n \"the currently active time zone as a tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\",\",\n \"\\\"\\\"\\\" Returns the default time zone as a tzinfo instance. This is the\",\n \"if timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'):\",\n \"Unsets the time zone for the current thread. Django will then use the\",\n \"pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime\",\n \"self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET\",\n \"def localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime to local time. Local time\",\n \"for pytz time zones value = timezone.normalize(value) return value def now(): \\\"\\\"\\\" Returns\",\n \"timezone) def deactivate(): \\\"\\\"\\\" Unsets the time zone for the current thread. Django\",\n \"for consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the name of the default\",\n \"it isn't thread safe. def activate(timezone): \\\"\\\"\\\" Sets the time zone for the\",\n \"__init__ to execute it as late as possible # See get_default_timezone(). self.STDOFFSET =\",\n \"tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz else\",\n \"with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the name of the default time zone.\",\n \"and (settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value) and getattr(value,\",\n \"> 0 utc = pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC time zone as\",\n \"naive in a given time zone. \\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'):\",\n \"try: import pytz except ImportError: pytz = None from django.conf import settings __all__\",\n \"None: _active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\" % timezone) def deactivate():\",\n \"ValueError(\\\"Invalid timezone: %r\\\" % timezone) def deactivate(): \\\"\\\"\\\" Unsets the time zone for\",\n \"= pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\" % timezone) def deactivate(): \\\"\\\"\\\" Unsets\",\n \"= get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time\",\n \"# wrap the expression in a function and cache the result. _localtime =\",\n \"docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None\",\n \"http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def\",\n \"if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def\",\n \"_localtime = LocalTimezone() return _localtime # This function exists for consistency with get_current_timezone_name\",\n \"import local import time as _time try: import pytz except ImportError: pytz =\",\n \"See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET =\",\n \"self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt):\",\n \"compile time, # wrap the expression in a function and cache the result.\",\n \"\\\"\\\"\\\" def __init__(self): # This code is moved in __init__ to execute it\",\n \"must be an instance of a ``tzinfo`` subclass, a time zone name, or\",\n \"localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime to local time. Local time is\",\n \"# The caller should ensure that they don't receive an invalid value like\",\n \"that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the previously\",\n \"# may be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\"\",\n \"Returns the name of the currently active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def\",\n \"if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return\",\n \"Python's docs. Used only when pytz isn't available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\"\",\n \"DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes an aware datetime.datetime naive\",\n \"class override(object): \\\"\\\"\\\" Temporarily set the time zone for the current thread. This\",\n \"If you're having trouble with this class, don't waste your time, just install\",\n \"localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts an\",\n \"\\\"\\\"\\\" Temporarily set the time zone for the current thread. This is a\",\n \"global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not\",\n \"as a tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns\",\n \"self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\"\",\n \"exists for consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the name of the\",\n \"having trouble with this class, don't waste your time, just install pytz. \\\"\\\"\\\"\",\n \"# available for pytz time zones return timezone.localize(value, is_dst=None) else: # may be\",\n \"the default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \\\"\\\"\\\"\",\n \"def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt):\",\n \"ensure that they don't receive an invalid value like None. def is_aware(value): \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\" Temporarily set the time\",\n \"if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET -\",\n \"value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \\\"\\\"\\\" Makes a\",\n \"required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz\",\n \"else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value\",\n \"waste your time, just install pytz. \\\"\\\"\\\" def __init__(self): # This code is\",\n \"a tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the\",\n \"value # Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime to local\",\n \"timezone): \\\"\\\"\\\" Makes an aware datetime.datetime naive in a given time zone. \\\"\\\"\\\"\",\n \"pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\" % timezone) def deactivate(): \\\"\\\"\\\" Unsets the\",\n \"exc_value, traceback): if self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value\",\n \"def get_default_timezone(): \\\"\\\"\\\" Returns the default time zone as a tzinfo instance. This\",\n \"value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes an aware datetime.datetime naive in a given\",\n \"only when pytz isn't available, and most likely inaccurate. If you're having trouble\",\n \"getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities def localtime(value,\",\n \"and call time.tzset() # because it isn't thread safe. def activate(timezone): \\\"\\\"\\\" Sets\",\n \"given datetime.datetime is naive. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\"\",\n \"the current thread. This is a context manager that uses ``~django.utils.timezone.activate()`` to set\",\n \"'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and local time zones ZERO\",\n \"the name of the default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local()\",\n \"and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value\",\n \"get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones\",\n \"is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo\",\n \"only when pytz isn't available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt):\",\n \"zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \\\"\\\"\\\" Returns the currently\",\n \"# because it isn't thread safe. def activate(timezone): \\\"\\\"\\\" Sets the time zone\",\n \"\\\"\\\"\\\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz)\",\n \"datetime and converts it to local time if necessary. If use_tz is provided\",\n \"in a given time zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): # available for\",\n \"self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self,\",\n \"logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not None\",\n \"(isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz) and not is_naive(value)\",\n \"get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the name of the currently active time zone.\",\n \"_get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of ``timezone``. \\\"\\\"\\\" try: # for\",\n \"this class, don't waste your time, just install pytz. \\\"\\\"\\\" def __init__(self): #\",\n \"__repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return \\\"UTC\\\"\",\n \"name of the currently active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\"\",\n \"then use the time zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del\",\n \"zone as a tzinfo instance. This is the time zone defined by settings.TIME_ZONE.\",\n \"\\\"\\\"\\\" Returns the name of the default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active\",\n \"def get_current_timezone(): \\\"\\\"\\\" Returns the currently active time zone as a tzinfo instance.\",\n \"the name of the currently active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone):\",\n \"zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\"\",\n \"value def now(): \\\"\\\"\\\" Returns an aware or naive datetime.datetime, depending on settings.USE_TZ.\",\n \"settings at compile time, # wrap the expression in a function and cache\",\n \"the time zone for the current thread. Django will then use the time\",\n \"return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \\\"\\\"\\\" Makes\",\n \"\\\"\\\"\\\" Sets the time zone for the current thread. The ``timezone`` argument must\",\n \"timezone on exit. The ``timezone`` argument must be an instance of a ``tzinfo``\",\n \"given datetime.datetime is aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\"\",\n \"zone name, or ``None``. If is it a time zone name, pytz is\",\n \"the default time zone as a tzinfo instance. This is the time zone\",\n \"if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is not\",\n \"_active.value # Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value is a datetime\",\n \"hasattr(_active, \\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\" Temporarily set the time zone for\",\n \"24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions\",\n \"except ImportError: pytz = None from django.conf import settings __all__ = [ 'utc',\",\n \"= pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function exists for\",\n \"'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC\",\n \"don't waste your time, just install pytz. \\\"\\\"\\\" def __init__(self): # This code\",\n \"None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not\",\n \"Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value is a datetime and converts\",\n \"if a given datetime.datetime is naive. The logic is described in Python's docs:\",\n \"when pytz isn't available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt): return\",\n \"ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken from Python's docs. Used only\",\n \"order to avoid accessing the settings at compile time, # wrap the expression\",\n \"pytz time zones value = timezone.normalize(value) return value def now(): \\\"\\\"\\\" Returns an\",\n \"implementation taken from Python's docs. Used only when pytz isn't available. \\\"\\\"\\\" def\",\n \"'make_naive', ] # UTC and local time zones ZERO = timedelta(0) class UTC(tzinfo):\",\n \"for use by the template engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ\",\n \"zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime is\",\n \"activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback): if self.old_timezone is not None: _active.value =\",\n \"the currently active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the\",\n \"Returns the default time zone as a tzinfo instance. This is the time\",\n \"The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not\",\n \"zones ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from Python's docs.\",\n \"self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is\",\n \"def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken from\",\n \"\\\"\\\"\\\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc)\",\n \"it is a time zone name, pytz is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo):\",\n \"aware or naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit shows\",\n \"None def is_naive(value): \\\"\\\"\\\" Determines if a given datetime.datetime is naive. The logic\",\n \"datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions don't change os.environ['TZ']\",\n \"logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None or\",\n \"zones value = timezone.normalize(value) return value def now(): \\\"\\\"\\\" Returns an aware or\",\n \"return ZERO def tzname(self, dt): return \\\"UTC\\\" def dst(self, dt): return ZERO class\",\n \"if use_tz is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True))\",\n \"These functions don't change os.environ['TZ'] and call time.tzset() # because it isn't thread\",\n \"get_default_timezone_name(): \\\"\\\"\\\" Returns the name of the default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone())\",\n \"UTC implementation taken from Python's docs. Used only when pytz isn't available. \\\"\\\"\\\"\",\n \"# In order to avoid accessing the settings at compile time, # wrap\",\n \"\\\"\\\"\\\"Timezone helper functions. This module uses pytz when it's available and fallbacks when\",\n \"use by the template engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime) and (settings.USE_TZ if\",\n \"likely inaccurate. If you're having trouble with this class, don't waste your time,\",\n \"it as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight:\",\n \"dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp\",\n \"This module uses pytz when it's available and fallbacks when it isn't. \\\"\\\"\\\"\",\n \"depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24%\",\n \"isn't available, and most likely inaccurate. If you're having trouble with this class,\",\n \"\\\"\\\"\\\" Local time implementation taken from Python's docs. Used only when pytz isn't\",\n \"if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime\",\n \"return timezone.zone except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone) return\",\n \"def make_aware(value, timezone): \\\"\\\"\\\" Makes a naive datetime.datetime in a given time zone\",\n \"= timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone)\",\n \"must be an instance of a tzinfo subclass or a time zone name.\",\n \"``timezone`` argument must be an instance of a ``tzinfo`` subclass, a time zone\",\n \"_get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of ``timezone``. \\\"\\\"\\\" try: # for pytz timezones\",\n \"converted (or not), overriding the value of settings.USE_TZ. This function is designed for\",\n \"given time zone. \\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for\",\n \"Makes an aware datetime.datetime naive in a given time zone. \\\"\\\"\\\" value =\",\n \"settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime is None: if isinstance(settings.TIME_ZONE,\",\n \"a given time zone. \\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available\",\n \"= getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone)\",\n \"def utcoffset(self, dt): return ZERO def tzname(self, dt): return \\\"UTC\\\" def dst(self, dt):\",\n \"active timezone on exit. The ``timezone`` argument must be an instance of a\",\n \"just install pytz. \\\"\\\"\\\" def __init__(self): # This code is moved in __init__\",\n \"_time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(),\",\n \"LocalTimezone() return _localtime # This function exists for consistency with get_current_timezone_name def get_default_timezone_name():\",\n \"utcoffset(self, dt): return ZERO def tzname(self, dt): return \\\"UTC\\\" def dst(self, dt): return\",\n \"datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these\",\n \"for the current thread. Django will then use the time zone defined by\",\n \"By design, these four functions don't perform any checks on their arguments. #\",\n \"is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is not None and\",\n \"to avoid accessing the settings at compile time, # wrap the expression in\",\n \"= timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from Python's docs. Used only\",\n \"a time zone name, or ``None``. If is it a time zone name,\",\n \"to be converted (or not), overriding the value of settings.USE_TZ. This function is\",\n \"django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive',\",\n \"around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes an aware datetime.datetime\",\n \"taken from Python's docs. Used only when pytz isn't available, and most likely\",\n \"None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \\\"\\\"\\\" Determines if a given\",\n \"\\\"UTC\\\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken\",\n \"defined by the current time zone, unless another time zone is specified. \\\"\\\"\\\"\",\n \"when it isn't. \\\"\\\"\\\" from datetime import datetime, timedelta, tzinfo from threading import\",\n \"dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def dst(self, dt): if self._isdst(dt):\",\n \"None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function\",\n \"dt): return \\\"UTC\\\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time\",\n \"dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local time implementation taken from Python's docs.\",\n \"if should_convert else value # Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware\",\n \"the settings at compile time, # wrap the expression in a function and\",\n \"time zone as a tzinfo instance.\\\"\\\"\\\" # In order to avoid accessing the\",\n \"hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value) return value.replace(tzinfo=None)\",\n \"local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions don't\",\n \"timezone.tzname(local_now) # Timezone selection functions. # These functions don't change os.environ['TZ'] and call\",\n \"timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() #\",\n \"default time zone as a tzinfo instance. This is the time zone defined\",\n \"if self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value # Templates\",\n \"datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions don't perform any\",\n \"zone for the current thread. This is a context manager that uses ``~django.utils.timezone.activate()``\",\n \"tzname(self, dt): return \\\"UTC\\\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\" Local\",\n \"to set the timezone on entry, and restores the previously active timezone on\",\n \"instance. This is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" Determines if a given datetime.datetime is naive. The logic is described in\",\n \"restores the previously active timezone on exit. The ``timezone`` argument must be an\",\n \"get_default_timezone(): \\\"\\\"\\\" Returns the default time zone as a tzinfo instance. This is\",\n \"time zone for the current thread. Django will then use the time zone\",\n \"= (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz) and not\",\n \"if _localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime\",\n \"time zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value',\",\n \"value like None. def is_aware(value): \\\"\\\"\\\" Determines if a given datetime.datetime is aware.\",\n \"shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By\",\n \"'make_aware', 'make_naive', ] # UTC and local time zones ZERO = timedelta(0) class\",\n \"that will force the value to be converted (or not), overriding the value\",\n \"and pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone: %r\\\"\",\n \"will then use the time zone defined by settings.TIME_ZONE. \\\"\\\"\\\" if hasattr(_active, \\\"value\\\"):\",\n \"The ``timezone`` argument must be an instance of a ``tzinfo`` subclass, a time\",\n \"timezone is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): #\",\n \"= _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC()\",\n \"for pytz time zones return timezone.localize(value, is_dst=None) else: # may be wrong around\",\n \"# By design, these four functions don't perform any checks on their arguments.\",\n \"execute it as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if\",\n \"your time, just install pytz. \\\"\\\"\\\" def __init__(self): # This code is moved\",\n \"zone, unless another time zone is specified. \\\"\\\"\\\" if timezone is None: timezone\",\n \"be wrong around DST changes return value.replace(tzinfo=timezone) def make_naive(value, timezone): \\\"\\\"\\\" Makes an\",\n \"\\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the name of the currently active time\",\n \"to local time. Local time is defined by the current time zone, unless\",\n \"Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def\",\n \"% timezone) def deactivate(): \\\"\\\"\\\" Unsets the time zone for the current thread.\",\n \"defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime is None:\",\n \"\\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt): return ZERO def tzname(self, dt):\",\n \"to execute it as late as possible # See get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone)\",\n \"timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else:\",\n \"name of the default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local() def\",\n \"_get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone(): \\\"\\\"\\\" Returns the currently active time zone\",\n \"self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF\",\n \"time, # wrap the expression in a function and cache the result. _localtime\",\n \"should_convert = (isinstance(value, datetime) and (settings.USE_TZ if use_tz is None else use_tz) and\",\n \"dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0) stamp = _time.mktime(tt) tt = _time.localtime(stamp)\",\n \"__repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET\",\n \"self.old_timezone is not None: _active.value = self.old_timezone else: del _active.value # Templates def\",\n \"self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self,\",\n \"an instance of a tzinfo subclass or a time zone name. If it\",\n \"template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value is a datetime and converts it to\",\n \"if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else:\",\n \"the name of ``timezone``. \\\"\\\"\\\" try: # for pytz timezones return timezone.zone except\",\n \"'value', None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self,\",\n \"aware. The logic is described in Python's docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is\",\n \"timezone on entry, and restores the previously active timezone on exit. The ``timezone``\",\n \"pytz timezones return timezone.zone except AttributeError: # for regular tzinfo objects local_now =\",\n \"pytz. \\\"\\\"\\\" def __init__(self): # This code is moved in __init__ to execute\",\n \"dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def tzname(self, dt): return\",\n \"active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of\",\n \"not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \\\"\\\"\\\" Determines if a\",\n \"Used only when pytz isn't available, and most likely inaccurate. If you're having\",\n \"a tzinfo instance.\\\"\\\"\\\" # In order to avoid accessing the settings at compile\",\n \"with this class, don't waste your time, just install pytz. \\\"\\\"\\\" def __init__(self):\",\n \"_active.value = timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value =\",\n \"Used only when pytz isn't available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self,\",\n \"for regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions.\",\n \"None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else:\",\n \"be an instance of a ``tzinfo`` subclass, a time zone name, or ``None``.\",\n \"# Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value is a datetime and\",\n \"is defined by the current time zone, unless another time zone is specified.\",\n \"enables the default time zone. \\\"\\\"\\\" def __init__(self, timezone): self.timezone = timezone self.old_timezone\",\n \"for pytz timezones return timezone.zone except AttributeError: # for regular tzinfo objects local_now\",\n \"``~django.utils.timezone.activate()`` to set the timezone on entry, and restores the previously active timezone\",\n \"__init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if\",\n \"docs: http://docs.python.org/library/datetime.html#datetime.tzinfo \\\"\\\"\\\" return value.tzinfo is None or value.tzinfo.utcoffset(value) is None def make_aware(value,\",\n \"0 utc = pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC time zone as a\",\n \"def tzname(self, dt): return \\\"UTC\\\" def dst(self, dt): return ZERO class LocalTimezone(tzinfo): \\\"\\\"\\\"\",\n \"_localtime is None: if isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime =\",\n \"settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware',\",\n \"local time if necessary. If use_tz is provided and is not None, that\",\n \"the current time zone, unless another time zone is specified. \\\"\\\"\\\" if timezone\",\n \"Makes a naive datetime.datetime in a given time zone aware. \\\"\\\"\\\" if hasattr(timezone,\",\n \"zone name, pytz is required. If it is ``None``, Django enables the default\",\n \"the expression in a function and cache the result. _localtime = None def\",\n \"return \\\"<UTC>\\\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return \\\"UTC\\\" def\",\n \"previously active timezone on exit. The ``timezone`` argument must be an instance of\",\n \"\\\"\\\"\\\" Returns the currently active time zone as a tzinfo instance. \\\"\\\"\\\" return\",\n \"basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else: raise ValueError(\\\"Invalid timezone:\",\n \"it to local time if necessary. If use_tz is provided and is not\",\n \"slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design, these four functions don't\",\n \"if hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value) return\",\n \"self.old_timezone = getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate() else:\",\n \"def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return\",\n \"timezone): \\\"\\\"\\\" Makes a naive datetime.datetime in a given time zone aware. \\\"\\\"\\\"\",\n \"value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time zones value\",\n \"necessary. If use_tz is provided and is not None, that will force the\",\n \"time zone as a tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name():\",\n \"None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \\\"\\\"\\\" Makes a naive datetime.datetime\",\n \"``tzinfo`` subclass, a time zone name, or ``None``. If is it a time\",\n \"Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime to local time. Local\",\n \"zone. \\\"\\\"\\\" value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for pytz time\",\n \"currently active time zone. \\\"\\\"\\\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name\",\n \"tt.tm_isdst > 0 utc = pytz.utc if pytz else UTC() \\\"\\\"\\\"UTC time zone\",\n \"get_default_timezone(). self.STDOFFSET = timedelta(seconds=-_time.timezone) if _time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET\",\n \"the previously active timezone on exit. The ``timezone`` argument must be an instance\",\n \"should_convert else value # Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime\",\n \"__enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def __exit__(self, exc_type, exc_value, traceback):\",\n \"local time zones ZERO = timedelta(0) class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from\",\n \"and cache the result. _localtime = None def get_default_timezone(): \\\"\\\"\\\" Returns the default\",\n \"is a datetime and converts it to local time if necessary. If use_tz\",\n \"settings.USE_TZ. This function is designed for use by the template engine. \\\"\\\"\\\" should_convert\",\n \"an aware or naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit\",\n \"value is a datetime and converts it to local time if necessary. If\",\n \"settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: # timeit shows that datetime.now(tz=utc) is 24% slower return\",\n \"_active = local() def get_current_timezone(): \\\"\\\"\\\" Returns the currently active time zone as\",\n \"return localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts\",\n \"tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else:\",\n \"isinstance(settings.TIME_ZONE, basestring) and pytz is not None: _localtime = pytz.timezone(settings.TIME_ZONE) else: _localtime =\",\n \"datetime.now() # By design, these four functions don't perform any checks on their\",\n \"def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt): return ZERO def tzname(self, dt): return\",\n \"Determines if a given datetime.datetime is naive. The logic is described in Python's\",\n \"``timezone`` argument must be an instance of a tzinfo subclass or a time\",\n \"= _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc if\",\n \"receive an invalid value like None. def is_aware(value): \\\"\\\"\\\" Determines if a given\",\n \"return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt): return self.DSTOFFSET else: return self.STDOFFSET def\",\n \"del _active.value # Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value is a\",\n \"tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These\",\n \"= datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions don't change\",\n \"tzinfo): _active.value = timezone elif isinstance(timezone, basestring) and pytz is not None: _active.value\",\n \"value of settings.USE_TZ. This function is designed for use by the template engine.\",\n \"stamp = _time.mktime(tt) tt = _time.localtime(stamp) return tt.tm_isdst > 0 utc = pytz.utc\",\n \"the current thread. Django will then use the time zone defined by settings.TIME_ZONE.\",\n \"self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt):\",\n \"'normalize'): # available for pytz time zones value = timezone.normalize(value) return value def\",\n \"designed for use by the template engine. \\\"\\\"\\\" should_convert = (isinstance(value, datetime) and\",\n \"pytz except ImportError: pytz = None from django.conf import settings __all__ = [\",\n \"getattr(_active, 'value', None) def __enter__(self): if self.timezone is None: deactivate() else: activate(self.timezone) def\",\n \"\\\"\\\"\\\" return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value):\",\n \"trouble with this class, don't waste your time, just install pytz. \\\"\\\"\\\" def\",\n \"is None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available\",\n \"the value of settings.USE_TZ. This function is designed for use by the template\",\n \"pytz.timezone(settings.TIME_ZONE) else: _localtime = LocalTimezone() return _localtime # This function exists for consistency\",\n \"zone name, pytz is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value = timezone elif\",\n \"not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return localtime(value) if should_convert else value #\",\n \"the time zone for the current thread. The ``timezone`` argument must be an\",\n \"return _localtime # This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\"\",\n \"def __init__(self): # This code is moved in __init__ to execute it as\",\n \"is the time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime\",\n \"exit. The ``timezone`` argument must be an instance of a ``tzinfo`` subclass, a\",\n \"This function exists for consistency with get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the name\",\n \"get_current_timezone_name def get_default_timezone_name(): \\\"\\\"\\\" Returns the name of the default time zone. \\\"\\\"\\\"\",\n \"tzname(self, dt): return _time.tzname[self._isdst(dt)] def _isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour,\",\n \"__init__(self): # This code is moved in __init__ to execute it as late\",\n \"\\\"\\\"\\\" Returns the name of ``timezone``. \\\"\\\"\\\" try: # for pytz timezones return\",\n \"time zone defined by settings.TIME_ZONE. See also :func:`get_current_timezone`. \\\"\\\"\\\" global _localtime if _localtime\",\n \"zone as a tzinfo instance. \\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\"\",\n \"- self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def utcoffset(self, dt): if self._isdst(dt): return\",\n \"time zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): # available for pytz time zones\",\n \"return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \\\"\\\"\\\" Returns the name of ``timezone``. \\\"\\\"\\\" try: #\",\n \"tzinfo instance.\\\"\\\"\\\" # In order to avoid accessing the settings at compile time,\",\n \"hasattr(timezone, 'normalize'): # available for pytz time zones value = timezone.normalize(value) return value\",\n \"is None or value.tzinfo.utcoffset(value) is None def make_aware(value, timezone): \\\"\\\"\\\" Makes a naive\",\n \"return timezone.localize(value, is_dst=None) else: # may be wrong around DST changes return value.replace(tzinfo=timezone)\",\n \"is not None and value.tzinfo.utcoffset(value) is not None def is_naive(value): \\\"\\\"\\\" Determines if\",\n \"time zone name, pytz is required. If it is ``None``, Django enables the\",\n \"change os.environ['TZ'] and call time.tzset() # because it isn't thread safe. def activate(timezone):\",\n \"or ``None``. If is it a time zone name, pytz is required. If\",\n \"import pytz except ImportError: pytz = None from django.conf import settings __all__ =\",\n \"of the default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active = local() def get_current_timezone():\",\n \"Returns the name of the default time zone. \\\"\\\"\\\" return _get_timezone_name(get_default_timezone()) _active =\",\n \"timezones return timezone.zone except AttributeError: # for regular tzinfo objects local_now = datetime.now(timezone)\",\n \"= self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self) def __repr__(self): return \\\"<LocalTimezone>\\\" def\",\n \"pytz is required. \\\"\\\"\\\" if isinstance(timezone, tzinfo): _active.value = timezone elif isinstance(timezone, basestring)\",\n \"return self.STDOFFSET def dst(self, dt): if self._isdst(dt): return self.DSTDIFF else: return ZERO def\",\n \"'convert_to_local_time', True)) return localtime(value) if should_convert else value # Utilities def localtime(value, timezone=None):\",\n \"class UTC(tzinfo): \\\"\\\"\\\" UTC implementation taken from Python's docs. Used only when pytz\",\n \"subclass, a time zone name, or ``None``. If is it a time zone\",\n \"timezone: %r\\\" % timezone) def deactivate(): \\\"\\\"\\\" Unsets the time zone for the\",\n \"Returns an aware or naive datetime.datetime, depending on settings.USE_TZ. \\\"\\\"\\\" if settings.USE_TZ: #\",\n \"regular tzinfo objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. #\",\n \"\\\"\\\"\\\" return getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the name of the\",\n \"is moved in __init__ to execute it as late as possible # See\",\n \"return timezone.tzname(local_now) # Timezone selection functions. # These functions don't change os.environ['TZ'] and\",\n \"selection functions. # These functions don't change os.environ['TZ'] and call time.tzset() # because\",\n \"from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override',\",\n \"elif isinstance(timezone, basestring) and pytz is not None: _active.value = pytz.timezone(timezone) else: raise\",\n \"a tzinfo instance. This is the time zone defined by settings.TIME_ZONE. See also\",\n \"if hasattr(_active, \\\"value\\\"): del _active.value class override(object): \\\"\\\"\\\" Temporarily set the time zone\",\n \"time is defined by the current time zone, unless another time zone is\",\n \"import time as _time try: import pytz except ImportError: pytz = None from\",\n \"'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive', ] # UTC and\",\n \"__all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate', 'override', 'is_naive', 'is_aware', 'make_aware', 'make_naive',\",\n \"None from django.conf import settings __all__ = [ 'utc', 'get_default_timezone', 'get_current_timezone', 'activate', 'deactivate',\",\n \"that datetime.now(tz=utc) is 24% slower return datetime.utcnow().replace(tzinfo=utc) else: return datetime.now() # By design,\",\n \"will force the value to be converted (or not), overriding the value of\",\n \"None. def is_aware(value): \\\"\\\"\\\" Determines if a given datetime.datetime is aware. The logic\",\n \"call time.tzset() # because it isn't thread safe. def activate(timezone): \\\"\\\"\\\" Sets the\",\n \"None: timezone = get_current_timezone() value = value.astimezone(timezone) if hasattr(timezone, 'normalize'): # available for\",\n \"else value # Utilities def localtime(value, timezone=None): \\\"\\\"\\\" Converts an aware datetime.datetime to\",\n \"def __init__(self, timezone): self.timezone = timezone self.old_timezone = getattr(_active, 'value', None) def __enter__(self):\",\n \"self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET tzinfo.__init__(self)\",\n \"zone name. If it is a time zone name, pytz is required. \\\"\\\"\\\"\",\n \"be converted (or not), overriding the value of settings.USE_TZ. This function is designed\",\n \"_time.daylight: self.DSTOFFSET = timedelta(seconds=-_time.altzone) else: self.DSTOFFSET = self.STDOFFSET self.DSTDIFF = self.DSTOFFSET - self.STDOFFSET\",\n \"\\\"\\\"\\\"UTC time zone as a tzinfo instance.\\\"\\\"\\\" # In order to avoid accessing\",\n \"on entry, and restores the previously active timezone on exit. The ``timezone`` argument\",\n \"objects local_now = datetime.now(timezone) return timezone.tzname(local_now) # Timezone selection functions. # These functions\",\n \"a context manager that uses ``~django.utils.timezone.activate()`` to set the timezone on entry, and\",\n \"_isdst(self, dt): tt = (dt.year, dt.month, dt.day, dt.hour, dt.minute, dt.second, dt.weekday(), 0, 0)\",\n \"is it a time zone name, pytz is required. If it is ``None``,\",\n \"their arguments. # The caller should ensure that they don't receive an invalid\",\n \"use_tz is None else use_tz) and not is_naive(value) and getattr(value, 'convert_to_local_time', True)) return\",\n \"else: del _active.value # Templates def template_localtime(value, use_tz=None): \\\"\\\"\\\" Checks if value is\",\n \"install pytz. \\\"\\\"\\\" def __init__(self): # This code is moved in __init__ to\",\n \"given time zone aware. \\\"\\\"\\\" if hasattr(timezone, 'localize'): # available for pytz time\",\n \"it's available and fallbacks when it isn't. \\\"\\\"\\\" from datetime import datetime, timedelta,\",\n \"fallbacks when it isn't. \\\"\\\"\\\" from datetime import datetime, timedelta, tzinfo from threading\",\n \"isn't available. \\\"\\\"\\\" def __repr__(self): return \\\"<UTC>\\\" def utcoffset(self, dt): return ZERO def\",\n \"time zone for the current thread. This is a context manager that uses\",\n \"getattr(_active, \\\"value\\\", get_default_timezone()) def get_current_timezone_name(): \\\"\\\"\\\" Returns the name of the currently active\",\n \"name, pytz is required. If it is ``None``, Django enables the default time\",\n \"because it isn't thread safe. def activate(timezone): \\\"\\\"\\\" Sets the time zone for\",\n \"``None``. If is it a time zone name, pytz is required. If it\",\n \"name, or ``None``. If is it a time zone name, pytz is required.\"\n]","isConversational":false}}},{"rowIdx":93,"cells":{"ngram":{"kind":"list like","value":["import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names","= resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch', 'thredds_download', 'workflow'","resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch', 'thredds_download', 'workflow' ]","Service from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import processes","test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings'","= client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) ==","import Service from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import","from pywps import Service from pywps.tests import assert_response_success from .common import client_for from","pywps import Service from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes","pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import processes def test_wps_caps():","import assert_response_success from .common import client_for from malleefowl.processes import processes def test_wps_caps(): client","client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps',","version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch',","import client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp =","names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch', 'thredds_download',","from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities',","processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names =","client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process'","from .common import client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes))","client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert","<gh_stars>0 import pytest from pywps import Service from pywps.tests import assert_response_success from .common","from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import processes def","request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download',","assert_response_success from .common import client_for from malleefowl.processes import processes def test_wps_caps(): client =","def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities'","client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [","pytest from pywps import Service from pywps.tests import assert_response_success from .common import client_for","malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0')","resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split())","import pytest from pywps import Service from pywps.tests import assert_response_success from .common import","= client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier')",".common import client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp"],"string":"[\n \"import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names\",\n \"= resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch', 'thredds_download', 'workflow'\",\n \"resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch', 'thredds_download', 'workflow' ]\",\n \"Service from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import processes\",\n \"test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings'\",\n \"= client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) ==\",\n \"import Service from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import\",\n \"from pywps import Service from pywps.tests import assert_response_success from .common import client_for from\",\n \"pywps import Service from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes\",\n \"pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import processes def test_wps_caps():\",\n \"import assert_response_success from .common import client_for from malleefowl.processes import processes def test_wps_caps(): client\",\n \"client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps',\",\n \"version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch',\",\n \"import client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp =\",\n \"names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch', 'thredds_download',\",\n \"from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities',\",\n \"processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names =\",\n \"client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process'\",\n \"from .common import client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes))\",\n \"client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert\",\n \"<gh_stars>0 import pytest from pywps import Service from pywps.tests import assert_response_success from .common\",\n \"from pywps.tests import assert_response_success from .common import client_for from malleefowl.processes import processes def\",\n \"request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download',\",\n \"assert_response_success from .common import client_for from malleefowl.processes import processes def test_wps_caps(): client =\",\n \"def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities'\",\n \"client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [\",\n \"pytest from pywps import Service from pywps.tests import assert_response_success from .common import client_for\",\n \"malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0')\",\n \"resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split())\",\n \"import pytest from pywps import Service from pywps.tests import assert_response_success from .common import\",\n \"= client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier')\",\n \".common import client_for from malleefowl.processes import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp\"\n]","isConversational":false}}},{"rowIdx":94,"cells":{"ngram":{"kind":"list like","value":["- Production/Stable\", \"License :: OSI Approved :: MIT License\", \"Operating System :: MacOS\",",":: 3.5\", \"Programming Language :: Python :: 3.6\", \"Programming Language :: Python ::","\"Programming Language :: Python :: Implementation :: PyPy\", \"Topic :: Software Development ::","Language :: Python :: 3.7\", \"Programming Language :: Python :: Implementation :: CPython\",","Web Environment\", \"Intended Audience :: Developers\", \"Intended Audience :: Education\", \"Development Status ::","Language :: Python :: 2.7\", \"Programming Language :: Python :: 3.4\", \"Programming Language",":: Implementation :: CPython\", \"Programming Language :: Python :: Implementation :: PyPy\", \"Topic","= f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\",",":: Python :: Implementation :: PyPy\", \"Topic :: Software Development :: Libraries ::","\"Environment :: Console\", \"Environment :: Web Environment\", \"Intended Audience :: Developers\", \"Intended Audience","setuptools import setup __author__ = \"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\" __version__ =","!=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for","install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for Ngrok.\",","Language :: Python :: Implementation :: CPython\", \"Programming Language :: Python :: Implementation","\"Programming Language :: Python :: 3.6\", \"Programming Language :: Python :: 3.7\", \"Programming","\"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language :: Python :: 2.7\", \"Programming Language :: Python","description=\"A Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\",","\"Programming Language :: Python :: 3.5\", \"Programming Language :: Python :: 3.6\", \"Programming",":: Developers\", \"Intended Audience :: Education\", \"Development Status :: 5 - Production/Stable\", \"License","\"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\",","f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\"",":: 3.4\", \"Programming Language :: Python :: 3.5\", \"Programming Language :: Python ::","\"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language :: Python :: 2.7\", \"Programming Language ::",":: 3.6\", \"Programming Language :: Python :: 3.7\", \"Programming Language :: Python ::","License\", \"Operating System :: MacOS\", \"Operating System :: Microsoft :: Windows\", \"Operating System","!=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python","<NAME>\" __version__ = \"1.4.0\" with open(\"README.md\", \"r\") as f: long_description = f.read() setup(",":: Python :: 3.4\", \"Programming Language :: Python :: 3.5\", \"Programming Language ::","long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming","Audience :: Education\", \"Development Status :: 5 - Production/Stable\", \"License :: OSI Approved","[console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\",",":: MacOS\", \"Operating System :: Microsoft :: Windows\", \"Operating System :: POSIX\", \"Operating","\"Intended Audience :: Education\", \"Development Status :: 5 - Production/Stable\", \"License :: OSI","\"Development Status :: 5 - Production/Stable\", \"License :: OSI Approved :: MIT License\",","], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\",","for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"],","Implementation :: PyPy\", \"Topic :: Software Development :: Libraries :: Python Modules\", \"Environment","long_description = f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[","!=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A","python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\",","Python :: 3.7\", \"Programming Language :: Python :: Implementation :: CPython\", \"Programming Language","\"Intended Audience :: Developers\", \"Intended Audience :: Education\", \"Development Status :: 5 -",":: Web Environment\", \"Intended Audience :: Developers\", \"Intended Audience :: Education\", \"Development Status","Language :: Python :: 3.6\", \"Programming Language :: Python :: 3.7\", \"Programming Language","Language :: Python :: Implementation :: PyPy\", \"Topic :: Software Development :: Libraries","\"Operating System :: Microsoft :: Windows\", \"Operating System :: POSIX\", \"Operating System ::",":: Python :: 2.7\", \"Programming Language :: Python :: 3.4\", \"Programming Language ::","MacOS\", \"Operating System :: Microsoft :: Windows\", \"Operating System :: POSIX\", \"Operating System","setup __author__ = \"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\" __version__ = \"1.4.0\" with","3.7\", \"Programming Language :: Python :: Implementation :: CPython\", \"Programming Language :: Python","\"Environment :: Web Environment\", \"Intended Audience :: Developers\", \"Intended Audience :: Education\", \"Development","\"Programming Language :: Python :: 2.7\", \"Programming Language :: Python :: 3.4\", \"Programming","3.4\", \"Programming Language :: Python :: 3.5\", \"Programming Language :: Python :: 3.6\",","Python :: 3.5\", \"Programming Language :: Python :: 3.6\", \"Programming Language :: Python","f: long_description = f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\",","\"\"\", description=\"A Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\",","\"Operating System :: MacOS\", \"Operating System :: Microsoft :: Windows\", \"Operating System ::","import setup __author__ = \"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\" __version__ = \"1.4.0\"","\"1.4.0\" with open(\"README.md\", \"r\") as f: long_description = f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"],",":: Console\", \"Environment :: Web Environment\", \"Intended Audience :: Developers\", \"Intended Audience ::",":: Python Modules\", \"Environment :: Console\", \"Environment :: Web Environment\", \"Intended Audience ::","\"Programming Language :: Python :: Implementation :: CPython\", \"Programming Language :: Python ::","license=\"MIT\", classifiers=[ \"Programming Language :: Python :: 2.7\", \"Programming Language :: Python ::","CPython\", \"Programming Language :: Python :: Implementation :: PyPy\", \"Topic :: Software Development","2019, <NAME>\" __version__ = \"1.4.0\" with open(\"README.md\", \"r\") as f: long_description = f.read()","\"Programming Language :: Python :: 3.4\", \"Programming Language :: Python :: 3.5\", \"Programming","Status :: 5 - Production/Stable\", \"License :: OSI Approved :: MIT License\", \"Operating","MIT License\", \"Operating System :: MacOS\", \"Operating System :: Microsoft :: Windows\", \"Operating",":: PyPy\", \"Topic :: Software Development :: Libraries :: Python Modules\", \"Environment ::","= \"1.4.0\" with open(\"README.md\", \"r\") as f: long_description = f.read() setup( name=\"pyngrok\", version=__version__,","3.6\", \"Programming Language :: Python :: 3.7\", \"Programming Language :: Python :: Implementation","<filename>setup.py from setuptools import setup __author__ = \"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\"",":: Python :: 3.7\", \"Programming Language :: Python :: Implementation :: CPython\", \"Programming","Implementation :: CPython\", \"Programming Language :: Python :: Implementation :: PyPy\", \"Topic ::",":: MIT License\", \"Operating System :: MacOS\", \"Operating System :: Microsoft :: Windows\",","url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language :: Python",":: 5 - Production/Stable\", \"License :: OSI Approved :: MIT License\", \"Operating System","\"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language :: Python :: 2.7\", \"Programming Language","Python :: 3.4\", \"Programming Language :: Python :: 3.5\", \"Programming Language :: Python","__author__ = \"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\" __version__ = \"1.4.0\" with open(\"README.md\",","Audience :: Developers\", \"Intended Audience :: Education\", \"Development Status :: 5 - Production/Stable\",","Libraries :: Python Modules\", \"Environment :: Console\", \"Environment :: Web Environment\", \"Intended Audience","OSI Approved :: MIT License\", \"Operating System :: MacOS\", \"Operating System :: Microsoft","Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\",","packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run",":: Software Development :: Libraries :: Python Modules\", \"Environment :: Console\", \"Environment ::","setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ],","\"Copyright 2019, <NAME>\" __version__ = \"1.4.0\" with open(\"README.md\", \"r\") as f: long_description =",":: Python :: 3.5\", \"Programming Language :: Python :: 3.6\", \"Programming Language ::",":: Python :: 3.6\", \"Programming Language :: Python :: 3.7\", \"Programming Language ::","from setuptools import setup __author__ = \"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\" __version__","__copyright__ = \"Copyright 2019, <NAME>\" __version__ = \"1.4.0\" with open(\"README.md\", \"r\") as f:","Python Modules\", \"Environment :: Console\", \"Environment :: Web Environment\", \"Intended Audience :: Developers\",","long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[",":: Implementation :: PyPy\", \"Topic :: Software Development :: Libraries :: Python Modules\",",":: Libraries :: Python Modules\", \"Environment :: Console\", \"Environment :: Web Environment\", \"Intended","\"Topic :: Software Development :: Libraries :: Python Modules\", \"Environment :: Console\", \"Environment",":: Education\", \"Development Status :: 5 - Production/Stable\", \"License :: OSI Approved ::","Production/Stable\", \"License :: OSI Approved :: MIT License\", \"Operating System :: MacOS\", \"Operating","Python :: 2.7\", \"Programming Language :: Python :: 3.4\", \"Programming Language :: Python","Python :: Implementation :: CPython\", \"Programming Language :: Python :: Implementation :: PyPy\",","\"Programming Language :: Python :: 3.7\", \"Programming Language :: Python :: Implementation ::","Approved :: MIT License\", \"Operating System :: MacOS\", \"Operating System :: Microsoft ::","Console\", \"Environment :: Web Environment\", \"Intended Audience :: Developers\", \"Intended Audience :: Education\",","\"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language :: Python :: 2.7\", \"Programming","\"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for Ngrok.\", long_description=long_description,","Language :: Python :: 3.5\", \"Programming Language :: Python :: 3.6\", \"Programming Language","\"License :: OSI Approved :: MIT License\", \"Operating System :: MacOS\", \"Operating System","= \"Copyright 2019, <NAME>\" __version__ = \"1.4.0\" with open(\"README.md\", \"r\") as f: long_description","entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\",","Python :: 3.6\", \"Programming Language :: Python :: 3.7\", \"Programming Language :: Python","!=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts] ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper","author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language",":: 2.7\", \"Programming Language :: Python :: 3.4\", \"Programming Language :: Python ::","keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language :: Python :: 2.7\",","with open(\"README.md\", \"r\") as f: long_description = f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7,","wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\",","Software Development :: Libraries :: Python Modules\", \"Environment :: Console\", \"Environment :: Web","\"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\" __version__ = \"1.4.0\" with open(\"README.md\", \"r\") as","__version__ = \"1.4.0\" with open(\"README.md\", \"r\") as f: long_description = f.read() setup( name=\"pyngrok\",","Microsoft :: Windows\", \"Operating System :: POSIX\", \"Operating System :: Unix\" ] )","Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\",",":: Python :: Implementation :: CPython\", \"Programming Language :: Python :: Implementation ::","Python :: Implementation :: PyPy\", \"Topic :: Software Development :: Libraries :: Python","System :: MacOS\", \"Operating System :: Microsoft :: Windows\", \"Operating System :: POSIX\",","classifiers=[ \"Programming Language :: Python :: 2.7\", \"Programming Language :: Python :: 3.4\",","author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language ::","version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\" [console_scripts]",":: CPython\", \"Programming Language :: Python :: Implementation :: PyPy\", \"Topic :: Software","name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\", install_requires=[ \"future\", \"pyyaml\" ], entry_points=\"\"\"","5 - Production/Stable\", \"License :: OSI Approved :: MIT License\", \"Operating System ::","\"r\") as f: long_description = f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*,","System :: Microsoft :: Windows\", \"Operating System :: POSIX\", \"Operating System :: Unix\"",":: Microsoft :: Windows\", \"Operating System :: POSIX\", \"Operating System :: Unix\" ]","= \"<NAME>\" __copyright__ = \"Copyright 2019, <NAME>\" __version__ = \"1.4.0\" with open(\"README.md\", \"r\")","Education\", \"Development Status :: 5 - Production/Stable\", \"License :: OSI Approved :: MIT","Language :: Python :: 3.4\", \"Programming Language :: Python :: 3.5\", \"Programming Language","Developers\", \"Intended Audience :: Education\", \"Development Status :: 5 - Production/Stable\", \"License ::",":: OSI Approved :: MIT License\", \"Operating System :: MacOS\", \"Operating System ::","ngrok=pyngrok.ngrok:run \"\"\", description=\"A Python wrapper for Ngrok.\", long_description=long_description, long_description_content_type=\"text/markdown\", author=\"<NAME>\", author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__),","download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost\"], license=\"MIT\", classifiers=[ \"Programming Language :: Python ::","2.7\", \"Programming Language :: Python :: 3.4\", \"Programming Language :: Python :: 3.5\",","open(\"README.md\", \"r\") as f: long_description = f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*,","as f: long_description = f.read() setup( name=\"pyngrok\", version=__version__, packages=[\"pyngrok\"], python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*,","PyPy\", \"Topic :: Software Development :: Libraries :: Python Modules\", \"Environment :: Console\",","3.5\", \"Programming Language :: Python :: 3.6\", \"Programming Language :: Python :: 3.7\",","Modules\", \"Environment :: Console\", \"Environment :: Web Environment\", \"Intended Audience :: Developers\", \"Intended","Environment\", \"Intended Audience :: Developers\", \"Intended Audience :: Education\", \"Development Status :: 5",":: 3.7\", \"Programming Language :: Python :: Implementation :: CPython\", \"Programming Language ::","Development :: Libraries :: Python Modules\", \"Environment :: Console\", \"Environment :: Web Environment\","],"string":"[\n \"- Production/Stable\\\", \\\"License :: OSI Approved :: MIT License\\\", \\\"Operating System :: MacOS\\\",\",\n \":: 3.5\\\", \\\"Programming Language :: Python :: 3.6\\\", \\\"Programming Language :: Python ::\",\n \"\\\"Programming Language :: Python :: Implementation :: PyPy\\\", \\\"Topic :: Software Development ::\",\n \"Language :: Python :: 3.7\\\", \\\"Programming Language :: Python :: Implementation :: CPython\\\",\",\n \"Web Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development Status ::\",\n \"Language :: Python :: 2.7\\\", \\\"Programming Language :: Python :: 3.4\\\", \\\"Programming Language\",\n \":: Implementation :: CPython\\\", \\\"Programming Language :: Python :: Implementation :: PyPy\\\", \\\"Topic\",\n \"= f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\",\",\n \":: Python :: Implementation :: PyPy\\\", \\\"Topic :: Software Development :: Libraries ::\",\n \"\\\"Environment :: Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended Audience\",\n \"setuptools import setup __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__ =\",\n \"!=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for\",\n \"install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\",\",\n \"Language :: Python :: Implementation :: CPython\\\", \\\"Programming Language :: Python :: Implementation\",\n \"\\\"Programming Language :: Python :: 3.6\\\", \\\"Programming Language :: Python :: 3.7\\\", \\\"Programming\",\n \"\\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python :: 2.7\\\", \\\"Programming Language :: Python\",\n \"description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\",\",\n \"\\\"Programming Language :: Python :: 3.5\\\", \\\"Programming Language :: Python :: 3.6\\\", \\\"Programming\",\n \":: Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development Status :: 5 - Production/Stable\\\", \\\"License\",\n \"\\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\",\",\n \"f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\"\",\n \":: 3.4\\\", \\\"Programming Language :: Python :: 3.5\\\", \\\"Programming Language :: Python ::\",\n \"\\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python :: 2.7\\\", \\\"Programming Language ::\",\n \":: 3.6\\\", \\\"Programming Language :: Python :: 3.7\\\", \\\"Programming Language :: Python ::\",\n \"License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating System :: Microsoft :: Windows\\\", \\\"Operating System\",\n \"!=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python\",\n \"<NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f: long_description = f.read() setup(\",\n \":: Python :: 3.4\\\", \\\"Programming Language :: Python :: 3.5\\\", \\\"Programming Language ::\",\n \"long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming\",\n \"Audience :: Education\\\", \\\"Development Status :: 5 - Production/Stable\\\", \\\"License :: OSI Approved\",\n \"[console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\",\",\n \":: MacOS\\\", \\\"Operating System :: Microsoft :: Windows\\\", \\\"Operating System :: POSIX\\\", \\\"Operating\",\n \"\\\"Intended Audience :: Education\\\", \\\"Development Status :: 5 - Production/Stable\\\", \\\"License :: OSI\",\n \"\\\"Development Status :: 5 - Production/Stable\\\", \\\"License :: OSI Approved :: MIT License\\\",\",\n \"], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\",\",\n \"for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"],\",\n \"Implementation :: PyPy\\\", \\\"Topic :: Software Development :: Libraries :: Python Modules\\\", \\\"Environment\",\n \"long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[\",\n \"!=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A\",\n \"python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\",\",\n \"Python :: 3.7\\\", \\\"Programming Language :: Python :: Implementation :: CPython\\\", \\\"Programming Language\",\n \"\\\"Intended Audience :: Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development Status :: 5 -\",\n \":: Web Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development Status\",\n \"Language :: Python :: 3.6\\\", \\\"Programming Language :: Python :: 3.7\\\", \\\"Programming Language\",\n \"Language :: Python :: Implementation :: PyPy\\\", \\\"Topic :: Software Development :: Libraries\",\n \"\\\"Operating System :: Microsoft :: Windows\\\", \\\"Operating System :: POSIX\\\", \\\"Operating System ::\",\n \":: Python :: 2.7\\\", \\\"Programming Language :: Python :: 3.4\\\", \\\"Programming Language ::\",\n \"MacOS\\\", \\\"Operating System :: Microsoft :: Windows\\\", \\\"Operating System :: POSIX\\\", \\\"Operating System\",\n \"setup __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with\",\n \"3.7\\\", \\\"Programming Language :: Python :: Implementation :: CPython\\\", \\\"Programming Language :: Python\",\n \"\\\"Environment :: Web Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development\",\n \"\\\"Programming Language :: Python :: 2.7\\\", \\\"Programming Language :: Python :: 3.4\\\", \\\"Programming\",\n \"3.4\\\", \\\"Programming Language :: Python :: 3.5\\\", \\\"Programming Language :: Python :: 3.6\\\",\",\n \"Python :: 3.5\\\", \\\"Programming Language :: Python :: 3.6\\\", \\\"Programming Language :: Python\",\n \"f: long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\",\",\n \"\\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\",\",\n \"\\\"Operating System :: MacOS\\\", \\\"Operating System :: Microsoft :: Windows\\\", \\\"Operating System ::\",\n \"import setup __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\"\",\n \"\\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f: long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"],\",\n \":: Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended Audience ::\",\n \":: Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended Audience ::\",\n \"\\\"Programming Language :: Python :: Implementation :: CPython\\\", \\\"Programming Language :: Python ::\",\n \"license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python :: 2.7\\\", \\\"Programming Language :: Python ::\",\n \"CPython\\\", \\\"Programming Language :: Python :: Implementation :: PyPy\\\", \\\"Topic :: Software Development\",\n \"2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f: long_description = f.read()\",\n \"\\\"Programming Language :: Python :: 3.4\\\", \\\"Programming Language :: Python :: 3.5\\\", \\\"Programming\",\n \"Status :: 5 - Production/Stable\\\", \\\"License :: OSI Approved :: MIT License\\\", \\\"Operating\",\n \"MIT License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating System :: Microsoft :: Windows\\\", \\\"Operating\",\n \":: PyPy\\\", \\\"Topic :: Software Development :: Libraries :: Python Modules\\\", \\\"Environment ::\",\n \"= \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f: long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__,\",\n \"3.6\\\", \\\"Programming Language :: Python :: 3.7\\\", \\\"Programming Language :: Python :: Implementation\",\n \"<filename>setup.py from setuptools import setup __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\"\",\n \":: Python :: 3.7\\\", \\\"Programming Language :: Python :: Implementation :: CPython\\\", \\\"Programming\",\n \"Implementation :: CPython\\\", \\\"Programming Language :: Python :: Implementation :: PyPy\\\", \\\"Topic ::\",\n \":: MIT License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating System :: Microsoft :: Windows\\\",\",\n \"url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python\",\n \":: 5 - Production/Stable\\\", \\\"License :: OSI Approved :: MIT License\\\", \\\"Operating System\",\n \"\\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python :: 2.7\\\", \\\"Programming Language\",\n \"Python :: 3.4\\\", \\\"Programming Language :: Python :: 3.5\\\", \\\"Programming Language :: Python\",\n \"__author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\",\",\n \"Audience :: Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development Status :: 5 - Production/Stable\\\",\",\n \"Libraries :: Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended Audience\",\n \"OSI Approved :: MIT License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating System :: Microsoft\",\n \"Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\",\",\n \"packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run\",\n \":: Software Development :: Libraries :: Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment ::\",\n \"setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ],\",\n \"\\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f: long_description =\",\n \":: Python :: 3.5\\\", \\\"Programming Language :: Python :: 3.6\\\", \\\"Programming Language ::\",\n \":: Python :: 3.6\\\", \\\"Programming Language :: Python :: 3.7\\\", \\\"Programming Language ::\",\n \"from setuptools import setup __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__\",\n \"__copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f:\",\n \"Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended Audience :: Developers\\\",\",\n \"long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[\",\n \":: Implementation :: PyPy\\\", \\\"Topic :: Software Development :: Libraries :: Python Modules\\\",\",\n \":: Libraries :: Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended\",\n \"\\\"Topic :: Software Development :: Libraries :: Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment\",\n \":: Education\\\", \\\"Development Status :: 5 - Production/Stable\\\", \\\"License :: OSI Approved ::\",\n \"Production/Stable\\\", \\\"License :: OSI Approved :: MIT License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating\",\n \"Python :: 2.7\\\", \\\"Programming Language :: Python :: 3.4\\\", \\\"Programming Language :: Python\",\n \"Python :: Implementation :: CPython\\\", \\\"Programming Language :: Python :: Implementation :: PyPy\\\",\",\n \"\\\"Programming Language :: Python :: 3.7\\\", \\\"Programming Language :: Python :: Implementation ::\",\n \"Approved :: MIT License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating System :: Microsoft ::\",\n \"Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended Audience :: Education\\\",\",\n \"\\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python :: 2.7\\\", \\\"Programming\",\n \"\\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description,\",\n \"Language :: Python :: 3.5\\\", \\\"Programming Language :: Python :: 3.6\\\", \\\"Programming Language\",\n \"\\\"License :: OSI Approved :: MIT License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating System\",\n \"= \\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f: long_description\",\n \"entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\",\",\n \"Python :: 3.6\\\", \\\"Programming Language :: Python :: 3.7\\\", \\\"Programming Language :: Python\",\n \"!=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts] ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper\",\n \"author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language\",\n \":: 2.7\\\", \\\"Programming Language :: Python :: 3.4\\\", \\\"Programming Language :: Python ::\",\n \"keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python :: 2.7\\\",\",\n \"with open(\\\"README.md\\\", \\\"r\\\") as f: long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7,\",\n \"wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\",\",\n \"Software Development :: Libraries :: Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment :: Web\",\n \"\\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as\",\n \"__version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\") as f: long_description = f.read() setup( name=\\\"pyngrok\\\",\",\n \"Microsoft :: Windows\\\", \\\"Operating System :: POSIX\\\", \\\"Operating System :: Unix\\\" ] )\",\n \"Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\",\",\n \":: Python :: Implementation :: CPython\\\", \\\"Programming Language :: Python :: Implementation ::\",\n \"Python :: Implementation :: PyPy\\\", \\\"Topic :: Software Development :: Libraries :: Python\",\n \"System :: MacOS\\\", \\\"Operating System :: Microsoft :: Windows\\\", \\\"Operating System :: POSIX\\\",\",\n \"classifiers=[ \\\"Programming Language :: Python :: 2.7\\\", \\\"Programming Language :: Python :: 3.4\\\",\",\n \"author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language ::\",\n \"version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\" [console_scripts]\",\n \":: CPython\\\", \\\"Programming Language :: Python :: Implementation :: PyPy\\\", \\\"Topic :: Software\",\n \"name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*\\\", install_requires=[ \\\"future\\\", \\\"pyyaml\\\" ], entry_points=\\\"\\\"\\\"\",\n \"5 - Production/Stable\\\", \\\"License :: OSI Approved :: MIT License\\\", \\\"Operating System ::\",\n \"\\\"r\\\") as f: long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*,\",\n \"System :: Microsoft :: Windows\\\", \\\"Operating System :: POSIX\\\", \\\"Operating System :: Unix\\\"\",\n \":: Microsoft :: Windows\\\", \\\"Operating System :: POSIX\\\", \\\"Operating System :: Unix\\\" ]\",\n \"= \\\"<NAME>\\\" __copyright__ = \\\"Copyright 2019, <NAME>\\\" __version__ = \\\"1.4.0\\\" with open(\\\"README.md\\\", \\\"r\\\")\",\n \"Education\\\", \\\"Development Status :: 5 - Production/Stable\\\", \\\"License :: OSI Approved :: MIT\",\n \"Language :: Python :: 3.4\\\", \\\"Programming Language :: Python :: 3.5\\\", \\\"Programming Language\",\n \"Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development Status :: 5 - Production/Stable\\\", \\\"License ::\",\n \":: OSI Approved :: MIT License\\\", \\\"Operating System :: MacOS\\\", \\\"Operating System ::\",\n \"ngrok=pyngrok.ngrok:run \\\"\\\"\\\", description=\\\"A Python wrapper for Ngrok.\\\", long_description=long_description, long_description_content_type=\\\"text/markdown\\\", author=\\\"<NAME>\\\", author_email=\\\"<EMAIL>\\\", url=\\\"https://github.com/alexdlaird/pyngrok\\\", download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__),\",\n \"download_url=\\\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\\\".format(__version__), keywords=[\\\"ngrok\\\", \\\"tunnel\\\", \\\"tunneling\\\", \\\"webhook\\\", \\\"localhost\\\"], license=\\\"MIT\\\", classifiers=[ \\\"Programming Language :: Python ::\",\n \"2.7\\\", \\\"Programming Language :: Python :: 3.4\\\", \\\"Programming Language :: Python :: 3.5\\\",\",\n \"open(\\\"README.md\\\", \\\"r\\\") as f: long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*,\",\n \"as f: long_description = f.read() setup( name=\\\"pyngrok\\\", version=__version__, packages=[\\\"pyngrok\\\"], python_requires=\\\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*,\",\n \"PyPy\\\", \\\"Topic :: Software Development :: Libraries :: Python Modules\\\", \\\"Environment :: Console\\\",\",\n \"3.5\\\", \\\"Programming Language :: Python :: 3.6\\\", \\\"Programming Language :: Python :: 3.7\\\",\",\n \"Modules\\\", \\\"Environment :: Console\\\", \\\"Environment :: Web Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended\",\n \"Environment\\\", \\\"Intended Audience :: Developers\\\", \\\"Intended Audience :: Education\\\", \\\"Development Status :: 5\",\n \":: 3.7\\\", \\\"Programming Language :: Python :: Implementation :: CPython\\\", \\\"Programming Language ::\",\n \"Development :: Libraries :: Python Modules\\\", \\\"Environment :: Console\\\", \\\"Environment :: Web Environment\\\",\"\n]","isConversational":false}}},{"rowIdx":95,"cells":{"ngram":{"kind":"list like","value":["\"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE,","= \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(): return dsl.ContainerOp( name='train',","command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def","= serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler","\"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE,","dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION","arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\",","variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\"","tracks' ) def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen =","@dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def trackml(): train =","description='A pipeline that predicts particle tracks' ) def trackml(): train = train_op() serve","particle tracks' ) def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen","serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler",").apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml',","image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks'","name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret())","= \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"],",").apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def trackml(): train","import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION =","image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def","TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[","kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\"","name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle","import kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE",")#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\",","Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION","KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(): return dsl.ContainerOp(","train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__':","gcp # Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE =","that predicts particle tracks' ) def trackml(): train = train_op() serve = serve_op()","#!/usr/bin/env python3 import kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input","resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml, __file__ +","= train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ ==","image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION),","as gcp # Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE","\"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"],","\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(): return","TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' )","def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op():","def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve)","trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if","dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ]",") def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op()","TRACKML_IMAGE_VERSION = \"1\" def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret()","arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return","resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline","command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\",","def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply","pipeline that predicts particle tracks' ) def trackml(): train = train_op() serve =","resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml, __file__ + '.tar.gz')","resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml,","-f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"],","input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION =","serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f","] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline(","name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE,","= \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op():","arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def trackml():","name='trackml', description='A pipeline that predicts particle tracks' ) def trackml(): train = train_op()","KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op():","train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__","\"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp(","dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve',","serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import","\"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen',","as dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\"","TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION),","= resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml, __file__","kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE =","\"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION),",").apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\",","train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return","predicts particle tracks' ) def trackml(): train = train_op() serve = serve_op() serve.after(train)","def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A","serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as","return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \"/src/set_kubectl.sh\", \"--namespace\", \"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\",","return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that","= \"1\" def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1)","python3 import kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input variables.","\"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"],","return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp(","KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def","dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts","# Pipeline input variables. KUBECTL_IMAGE = \"gcr.io/mcas-195423/trackml_master_kfp_kubectl\" KUBECTL_IMAGE_VERSION = \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\"","\"1\" def train_op(): return dsl.ContainerOp( name='train', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def","/src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\"python\"], arguments=[\"resultsgen.py\"], ).apply(gcp.use_gcp_secret())"],"string":"[\n \"\\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE,\",\n \"= \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return dsl.ContainerOp( name='train',\",\n \"command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def\",\n \"= serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler\",\n \"\\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE,\",\n \"dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION\",\n \"arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\",\",\n \"variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\"\",\n \"tracks' ) def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen =\",\n \"@dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def trackml(): train =\",\n \"description='A pipeline that predicts particle tracks' ) def trackml(): train = train_op() serve\",\n \"particle tracks' ) def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen\",\n \"serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler\",\n \").apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml',\",\n \"image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks'\",\n \"name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret())\",\n \"= \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"],\",\n \").apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def trackml(): train\",\n \"import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION =\",\n \"image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def\",\n \"TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[\",\n \"kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\"\",\n \"name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle\",\n \"import kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE\",\n \")#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\",\",\n \"Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION\",\n \"KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return dsl.ContainerOp(\",\n \"train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__':\",\n \"gcp # Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE =\",\n \"that predicts particle tracks' ) def trackml(): train = train_op() serve = serve_op()\",\n \"#!/usr/bin/env python3 import kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input\",\n \"resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml, __file__ +\",\n \"= train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ ==\",\n \"image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION),\",\n \"as gcp # Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE\",\n \"\\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"],\",\n \"\\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return\",\n \"TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' )\",\n \"def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op():\",\n \"def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve)\",\n \"trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if\",\n \"dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ]\",\n \") def trackml(): train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op()\",\n \"TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret()\",\n \"arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return\",\n \"resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline\",\n \"command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\",\",\n \"def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply\",\n \"pipeline that predicts particle tracks' ) def trackml(): train = train_op() serve =\",\n \"resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml, __file__ + '.tar.gz')\",\n \"resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml,\",\n \"-f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"],\",\n \"input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION =\",\n \"serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f\",\n \"] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline(\",\n \"name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE,\",\n \"= \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op():\",\n \"arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts particle tracks' ) def trackml():\",\n \"name='trackml', description='A pipeline that predicts particle tracks' ) def trackml(): train = train_op()\",\n \"KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op():\",\n \"train = train_op() serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__\",\n \"\\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp(\",\n \"dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve',\",\n \"serve = serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import\",\n \"\\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen',\",\n \"as dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\"\",\n \"TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION),\",\n \"= resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as compiler compiler.Compiler().compile(trackml, __file__\",\n \"kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input variables. KUBECTL_IMAGE =\",\n \"\\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION),\",\n \").apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\",\",\n \"train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return\",\n \"predicts particle tracks' ) def trackml(): train = train_op() serve = serve_op() serve.after(train)\",\n \"def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A\",\n \"serve_op() serve.after(train) resultsgen = resultsgen_op() resultsgen.after(serve) if __name__ == '__main__': import kfp.compiler as\",\n \"return dsl.ContainerOp( name='serve', image=\\\"{}:{}\\\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION), arguments=[ \\\"/src/set_kubectl.sh\\\", \\\"--namespace\\\", \\\"kubeflow\\\", \\\"--command\\\", \\\"apply -f /src/k8s/serve.yaml\\\",\",\n \"return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that\",\n \"= \\\"1\\\" def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1)\",\n \"python3 import kfp.dsl as dsl import kfp.gcp as gcp # Pipeline input variables.\",\n \"\\\"apply -f /src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"],\",\n \"return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp(\",\n \"KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\" TRACKML_IMAGE_VERSION = \\\"1\\\" def\",\n \"dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret()) @dsl.pipeline( name='trackml', description='A pipeline that predicts\",\n \"# Pipeline input variables. KUBECTL_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_kfp_kubectl\\\" KUBECTL_IMAGE_VERSION = \\\"1\\\" TRACKML_IMAGE = \\\"gcr.io/mcas-195423/trackml_master_trackml\\\"\",\n \"\\\"1\\\" def train_op(): return dsl.ContainerOp( name='train', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"train.py\\\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def\",\n \"/src/k8s/serve.yaml\\\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\\\"{}:{}\\\".format(TRACKML_IMAGE, TRACKML_IMAGE_VERSION), command=[\\\"python\\\"], arguments=[\\\"resultsgen.py\\\"], ).apply(gcp.use_gcp_secret())\"\n]","isConversational":false}}},{"rowIdx":96,"cells":{"ngram":{"kind":"list like","value":["__name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name","= infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,)","= argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args =","'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0","<reponame>aleasoluciones/infrabbitmq<filename>bin/ticker.py # -*- coding: utf-8 -*- import time import puka import argparse import","utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser","main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError,","TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\"publish event","= 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1","= 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2","network, secs, mins): logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins':","0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 ==","TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,","if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins)","puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network,","import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from","2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins %","True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if","( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins):","-*- coding: utf-8 -*- import time import puka import argparse import logging from","secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs","+= 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60","secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network,","TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,","from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event,","% 60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,","try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)')","utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 == 0:","publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,","utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0:","import puka import argparse import logging from infcommon import utils from infrabbitmq import","publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs =",") def publish_event(publisher, event, network, secs, mins): logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event,","TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n',","0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs","publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 == 0: mins +=","rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,","0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 ==","mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs,","network, secs, mins) if secs % 60 == 0: mins += 1 secs","args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc: logging.critical(\"Ticker Fails:","infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import (","-*- import time import puka import argparse import logging from infcommon import utils","{}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer()","network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES,","infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError","mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs +=","coding: utf-8 -*- import time import puka import argparse import logging from infcommon","0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 ==","(ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as","from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import","publish_event(publisher, event, network, secs, mins): logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event, network, data={'tick':","logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network):","TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\"publish event {} {}\".format(event, secs))","1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 ==","help='Network name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except","infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, )","= 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1)","publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser =","mins) if secs % 60 == 0: mins += 1 secs = 0","secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs %","secs, mins): logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins})","c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc:","event, network, secs, mins): logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs,","publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,","TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\"publish event {} {}\".format(event,","publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 == 0: mins","secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network,","% 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__","if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins)","'__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k,","required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network)","infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network,","TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,","mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs,","...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc: logging.critical(\"Ticker","infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES,","% 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins","def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions =","publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,","parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network","publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError,","if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network","+= 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if","mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True,","network, secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network',","from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES,","import time import puka import argparse import logging from infcommon import utils from","60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ ==","utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0:","def publish_event(publisher, event, network, secs, mins): logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event, network,","== '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo,","name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception","publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,","network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES,","parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args","= parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc: logging.critical(\"Ticker Fails: {}\".format(exc))","TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\"publish","RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher,","time import puka import argparse import logging from infcommon import utils from infrabbitmq","utf-8 -*- import time import puka import argparse import logging from infcommon import","network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0","event {} {}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher","if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins)","publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser()","'--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network =","== 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5","infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while","% 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins","secs, mins) if secs % 60 == 0: mins += 1 secs =","secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network,","publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,","secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store',","action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0]","== 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__':","0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs,","5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins %","argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args()","= (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,","argparse import logging from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory","if secs % 60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,","data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins","utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names","mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs,","mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions","== 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network,","time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs","secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins %","mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if","import argparse import logging from infcommon import utils from infrabbitmq import factory as","mins): logging.info(\"publish event {} {}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def","publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,","1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins","0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try:","factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE,","import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def","secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True:","import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND,","as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES,","60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE,","from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import","mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if","TICK_1_SECOND, network, secs, mins) if secs % 60 == 0: mins += 1","secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins =","== 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60","secs % 60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,","import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs,","import logging from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from","KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs,","mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins)","mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if","network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES,","0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,","puka import argparse import logging from infcommon import utils from infrabbitmq import factory","(RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND,","TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\"publish event {}","while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins)","{} {}\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher =","# -*- coding: utf-8 -*- import time import puka import argparse import logging","utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0:","logging from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq"],"string":"[\n \"__name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name\",\n \"= infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,)\",\n \"= argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args =\",\n \"'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0\",\n \"<reponame>aleasoluciones/infrabbitmq<filename>bin/ticker.py # -*- coding: utf-8 -*- import time import puka import argparse import\",\n \"utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser\",\n \"main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError,\",\n \"TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish event\",\n \"= 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1\",\n \"= 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2\",\n \"network, secs, mins): logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins':\",\n \"0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 ==\",\n \"TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,\",\n \"if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins)\",\n \"puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network,\",\n \"import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from\",\n \"2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins %\",\n \"True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if\",\n \"( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins):\",\n \"-*- coding: utf-8 -*- import time import puka import argparse import logging from\",\n \"secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs\",\n \"+= 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60\",\n \"secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network,\",\n \"TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,\",\n \"from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event,\",\n \"% 60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,\",\n \"try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)')\",\n \"utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 == 0:\",\n \"publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,\",\n \"utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0:\",\n \"import puka import argparse import logging from infcommon import utils from infrabbitmq import\",\n \"publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs =\",\n \") def publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event,\",\n \"TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n',\",\n \"0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs\",\n \"publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 == 0: mins +=\",\n \"rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,\",\n \"0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 ==\",\n \"mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs,\",\n \"network, secs, mins) if secs % 60 == 0: mins += 1 secs\",\n \"args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc: logging.critical(\\\"Ticker Fails:\",\n \"infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import (\",\n \"-*- import time import puka import argparse import logging from infcommon import utils\",\n \"{}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer()\",\n \"network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES,\",\n \"infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError\",\n \"mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs +=\",\n \"coding: utf-8 -*- import time import puka import argparse import logging from infcommon\",\n \"0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 ==\",\n \"(ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as\",\n \"from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import\",\n \"publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick':\",\n \"logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network):\",\n \"TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish event {} {}\\\".format(event, secs))\",\n \"1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 ==\",\n \"help='Network name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except\",\n \"infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, )\",\n \"= 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1)\",\n \"publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser =\",\n \"mins) if secs % 60 == 0: mins += 1 secs = 0\",\n \"secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs %\",\n \"secs, mins): logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins})\",\n \"c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc:\",\n \"event, network, secs, mins): logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs,\",\n \"publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,\",\n \"TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish event {} {}\\\".format(event,\",\n \"publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs % 60 == 0: mins\",\n \"secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network,\",\n \"% 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__\",\n \"if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins)\",\n \"'__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k,\",\n \"required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network)\",\n \"infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network,\",\n \"TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,\",\n \"mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs,\",\n \"...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc: logging.critical(\\\"Ticker\",\n \"infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES,\",\n \"% 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins\",\n \"def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions =\",\n \"publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,\",\n \"parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network\",\n \"publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError,\",\n \"if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network\",\n \"+= 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if\",\n \"mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True,\",\n \"network, secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network',\",\n \"from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES,\",\n \"import time import puka import argparse import logging from infcommon import utils from\",\n \"60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ ==\",\n \"utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0:\",\n \"def publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event, network,\",\n \"== '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo,\",\n \"name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0] main(network) except Exception\",\n \"publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,\",\n \"network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES,\",\n \"parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args\",\n \"= parser.parse_args() network = args.network.split('-')[0] main(network) except Exception as exc: logging.critical(\\\"Ticker Fails: {}\\\".format(exc))\",\n \"TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish\",\n \"RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher,\",\n \"time import puka import argparse import logging from infcommon import utils from infrabbitmq\",\n \"utf-8 -*- import time import puka import argparse import logging from infcommon import\",\n \"network, data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0\",\n \"event {} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher\",\n \"if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins)\",\n \"publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser()\",\n \"'--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network =\",\n \"== 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5\",\n \"infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while\",\n \"% 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins\",\n \"secs, mins) if secs % 60 == 0: mins += 1 secs =\",\n \"secs, mins) if mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network,\",\n \"publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,\",\n \"secs, mins) if __name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store',\",\n \"action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args() network = args.network.split('-')[0]\",\n \"== 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__':\",\n \"0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs,\",\n \"5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins %\",\n \"argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name (ilo, c2k, ...)') args = parser.parse_args()\",\n \"= (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher,\",\n \"argparse import logging from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory\",\n \"if secs % 60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,\",\n \"data={'tick': secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins\",\n \"utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names\",\n \"mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs,\",\n \"mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions\",\n \"== 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network,\",\n \"time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins) if secs\",\n \"secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins %\",\n \"mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if\",\n \"import argparse import logging from infcommon import utils from infrabbitmq import factory as\",\n \"mins): logging.info(\\\"publish event {} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def\",\n \"publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,\",\n \"1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins) if mins\",\n \"0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_60_MINUTES, network, secs, mins) if __name__ == '__main__': try:\",\n \"factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE,\",\n \"import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def\",\n \"secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True:\",\n \"import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND,\",\n \"as infrabbitmq_factory from infrabbitmq.rabbitmq import RabbitMQError from infrabbitmq.events_names import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES,\",\n \"60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE,\",\n \"from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq import\",\n \"mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if\",\n \"TICK_1_SECOND, network, secs, mins) if secs % 60 == 0: mins += 1\",\n \"secs, 'mins': mins}) def main(network): publisher = infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins =\",\n \"== 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if mins % 60\",\n \"secs % 60 == 0: mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,\",\n \"import ( TICK_1_SECOND, TICK_1_MINUTE, TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs,\",\n \"import logging from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from\",\n \"KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs,\",\n \"mins += 1 secs = 0 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_MINUTE, network, secs, mins)\",\n \"mins % 5 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_5_MINUTES, network, secs, mins) if\",\n \"network, secs, mins) if mins % 2 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES,\",\n \"0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions,\",\n \"puka import argparse import logging from infcommon import utils from infrabbitmq import factory\",\n \"(RabbitMQError, puka.AMQPError, KeyError,) while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND,\",\n \"TICK_2_MINUTES, TICK_5_MINUTES, TICK_60_MINUTES, ) def publish_event(publisher, event, network, secs, mins): logging.info(\\\"publish event {}\",\n \"while True: time.sleep(1) secs += 1 utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_1_SECOND, network, secs, mins)\",\n \"{} {}\\\".format(event, secs)) publisher.publish(event, network, data={'tick': secs, 'mins': mins}) def main(network): publisher =\",\n \"# -*- coding: utf-8 -*- import time import puka import argparse import logging\",\n \"utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5 == 0:\",\n \"logging from infcommon import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq\"\n]","isConversational":false}}},{"rowIdx":97,"cells":{"ngram":{"kind":"list like","value":["Unless required by applicable law or agreed to in writing, software # distributed","by a model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def","To train the model, you need to first set it back in training","use instead of a state dictionary loaded from saved weights file. This option","prediction, we perform one forward pass through the encoder, and then perform several","loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either:","used to override said attribute with the supplied ``kwargs`` value. Remaining keys that","vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \"\"\" # keyword arguments come","are of the same family. If the name of or that path to","`tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set","method. \"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder =","the encoder if an argument named `encoder_hidden_state` is passed to this function. Params:","``__init__`` function. You can specify kwargs sepcific for the encoder and decoder by","(e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True and a","``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the vocabulary. kwargs: (`optional`)","override the cached versions if they exists. proxies: (`optional`) dict, default None: A",":class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an automatically loaded configuation.","- the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the","this case, ``from_tf`` should be set to True and a configuration object should","- RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings -","option can be used if you want to create a model from a","the name of or that path to a pretrained model is specified the","in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \"\"\" # keyword","decoder-specific (prefixed by `decoder_`) and those # that apply to the model as","# Copyright 2018 The HuggingFace Inc. team. # # Licensed under the Apache","def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None) is None: # We will create","can specify kwargs sepcific for the encoder and decoder by prefixing the key","} ) # Load and initialize the encoder and decoder # The distinction","and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used","the embedding weights. However the different model classes are inconsistent to that respect:","a decoder from one or two base classes of the library from pre-trained","encoder_outputs[ 0 ] # output the last layer hidden state else: encoder_outputs =","containing missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of","input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices","pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder)","randomly initilized LSTM model as decoder if \"decoder_config\" not in kwargs: raise ValueError(","IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or","\" \" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\"))","using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two separate directories.","the different model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings -","cached versions if they exists. proxies: (`optional`) dict, default None: A dictionary of","def save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq model and its configuration file in","initilized LSTM model as decoder if \"decoder_config\" not in kwargs: raise ValueError( \"To","decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates","and not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\")","suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json`","with the `shortcut name` of a pre-trained model to load from cache or","If the name of or that path to a pretrained model is specified","*args, **kwargs): if ( \"bert\" not in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or","argument. This loading path is slower than converting the TensorFlow checkpoint in a","the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional","to use instead of an automatically loaded configuation. Configuration can be automatically loaded","that we need to set correctly. encoder = kwargs_encoder.pop(\"model\", None) if encoder is","using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow index","be used to initialize a\" \" torch.nn.LSTM model as `decoder_config` keyword argument. \"","been done) - If a configuration is not provided, ``kwargs`` will be first","parameter (`decoder_model=lstm_model`), or\" \" - a dictionary of configuration parameters that will be","instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use","the encoder and decoder # The distinction between encoder and decoder at the","in kwargs.items() if argument.startswith(\"decoder_\") } ) # Encode if needed (training, first prediction","be instantiated as a transformer architecture with one of the base model classes","default False: Force to (re-)download the model weights and configuration files and override","(training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None: encoder_outputs","if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ]","to any configuration attribute will be passed to the underlying model's ``__init__`` function.","\"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only the Bert model is currently supported.\") model","{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`)","and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both","Tying the encoder and decoders' embeddings together. We need for each to get","software # distributed under the License is distributed on an \"AS IS\" BASIS,","positional arguments will be passed to the underlying model's ``__init__`` method config: (`optional`)","``output_attention=True``). Behave differently depending on whether a `config` is provided or automatically loaded:","] # output the last layer hidden state else: encoder_outputs = () #","to a pretrained model is specified the encoder and the decoder will be","@classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates an encoder","model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings","and configuration files and override the cached versions if they exists. proxies: (`optional`)","load from cache or download, e.g.: ``bert-base-uncased``. - a path to a `directory`","class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an","that corresponds to a configuration attribute will be used to override said attribute","sequence_length)`` Indices of decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining","'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\")) model = super(Model2LSTM, cls).from_pretrained(*args, **kwargs)","using `model.eval()` (Dropout modules are deactivated) To train the model, you need to","to also return a dictionnary containing missing keys, unexpected keys and error messages.","kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for argument,","model, but it is \"blocked\" by a model-specific keyword (bert, )... \"\"\" #","the flag `is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\"model\", None)","possible to override this behavior and initialize, say, the decoder randomly by creating","supply either: \" \" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\"","the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law","``./my_model_directory/encoder``. - a path or url to a `tensorflow index checkpoint file` (e.g.","keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args,","by the library (loaded with the ``shortcut-name`` string of a pretrained model), or","one forward pass through the encoder, and then perform several forward passes with","on whether a `config` is provided or automatically loaded: - If a configuration","return model def save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq model and its configuration","are used on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also","value for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Load and","Sequence of positional arguments: All remaning positional arguments will be passed to the","not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]:","come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`)","specific kwargs override the common ones in case of conflict. kwargs_common = {","# that apply to the model as a whole. # We let the","or\" \" - a dictionary of configuration parameters that will be used to","conflict. kwargs_common = { argument: value for argument, value in kwargs.items() if not","is \"blocked\" by a model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass","relevant updates to the configuration have already been done) - If a configuration","of the encoder and decoder are of the same family. If the name","to update the configuration object (after it being loaded) and initiate the model.","optional state dictionnary for the model to use instead of a state dictionary","PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated as","a seq2eq depends what we are performing: - During training we perform one","value for argument, value in kwargs.items() if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") }","forward passes with the encoder's hidden state through the decoder to decode a","class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder","AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model","for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Encode if needed","2018 The HuggingFace Inc. team. # # Licensed under the Apache License, Version","please supply either: \" \" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`),","\"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder","# The distinction between encoder and decoder at the model level is made","decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder)","to the configuration have already been done) - If a configuration is not","apply to the model as a whole. # We let the specific kwargs","decoder; - During prediction, we perform one forward pass through the encoder, and","The remaining kwargs will be passed to both encoders and decoders. Examples:: model","Each key of ``kwargs`` that corresponds to a configuration attribute will be used","a configuration JSON file named `config.json` is found in the directory. state_dict: (`optional`)","an optional state dictionnary for the model to use instead of a state","self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\" not","model from a pretrained configuration but load your own weights. In this case","or \"roberta\" in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only the Bert","argument, value in kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\") :]: value","configuration parameters that will be used to initialize a\" \" torch.nn.LSTM model as","from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None) is None: # We will create a","of an automatically loaded configuation. Configuration can be automatically loaded when: - the","Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape","say, the decoder randomly by creating it beforehand as follows config = BertConfig.from_pretrained()","`directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or","): r\"\"\" Instantiates an encoder and a decoder from one or two base","using the provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information","a randomly initilized LSTM model as decoder if \"decoder_config\" not in kwargs: raise","model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq","initialize a\" \" torch.nn.LSTM model as `decoder_config` keyword argument. \" \" E.g. `decoder_config={'input_size':","@classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\" not in pretrained_model_name_or_path or","print_function, unicode_literals import logging import os import torch from torch import nn from","and decoder; - During prediction, we perform one forward pass through the encoder,","encoder and decoder at the model level is made # by the value","argument.startswith(\"decoder_\") } ) # Load and initialize the encoder and decoder # The","model using the provided conversion scripts and loading the PyTorch model afterwards. model_args:","= self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer","directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The","not use this file except in compliance with the License. # You may","the value of the flag `is_decoder` that we need to set correctly. encoder","PyTorch model using the provided conversion scripts and loading the PyTorch model afterwards.","XEmbedding layer for each model, but it is \"blocked\" by a model-specific keyword","the encoder, and then perform several forward passes with the encoder's hidden state","(prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply","directory. state_dict: (`optional`) dict: an optional state dictionnary for the model to use","in kwargs.items() if argument.startswith(\"decoder_\") } ) # Load and initialize the encoder and","suppling the save directory. - the model is loaded by suppling a local","one of the base model classes of the library as encoder and (optionally)","distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY","modules are deactivated) To train the model, you need to first set it","to first set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information","arguments. \"\"\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by #","encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args,","to a configuration attribute will be used to override said attribute with the","a transformer architecture with one of the base model classes of the library","`directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or","tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \"\"\" #","agreed to in writing, software # distributed under the License is distributed on","state_dict: (`optional`) dict: an optional state dictionnary for the model to use instead","argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Load and initialize the","*args, **kwargs): if kwargs.get(\"decoder_model\", None) is None: # We will create a randomly","are deactivated) To train the model, you need to first set it back","is None: # We will create a randomly initilized LSTM model as decoder","model is specified the encoder and the decoder will be initialized with the","want to create a model from a pretrained configuration but load your own","also return a dictionnary containing missing keys, unexpected keys and error messages. kwargs:","``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor``","*model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\", None) if decoder is","weights are not present). It is possible to override this behavior and initialize,","kwargs.get(\"decoder_model\", None) is None: # We will create a randomly initilized LSTM model","be initialized with the pretrained weight (the cross-attention will be intialized randomly if","dictionnary for the model to use instead of a state dictionary loaded from","input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments.","not present). It is possible to override this behavior and initialize, say, the","decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs):","configuration but load your own weights. In this case though, you should check","as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\"","loaded: - If a configuration is provided with ``config``, ``**kwargs`` will be directly","check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`)","Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder and","instead of an automatically loaded configuation. Configuration can be automatically loaded when: -","be passed to the underlying model's ``__init__`` function. You can specify kwargs sepcific","forward pass on a seq2eq depends what we are performing: - During training","'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`) boolean: Set","model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to","saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow","output the last layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"]","): raise ValueError(\"Only the Bert model is currently supported.\") model = super(Model2Model, cls).from_pretrained(","ValueError( \"To load an LSTM in Encoder-Decoder model, please supply either: \" \"","of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size,","with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder","to in writing, software # distributed under the License is distributed on an","= super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod","instantiated as a transformer architecture with one of the base model classes of","default None: A dictionary of proxy servers to use by protocol or endpoint,","implied. # See the License for the specific language governing permissions and #","from __future__ import absolute_import, division, print_function, unicode_literals import logging import os import torch","not a simpler option. cache_dir: (`optional`) string: Path to a directory in which","override said attribute with the supplied ``kwargs`` value. Remaining keys that do not","``__init__`` method (we assume all relevant updates to the configuration have already been","or \"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only the Bert model is currently supported.\")","argument[len(\"encoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update(","create a model from a pretrained configuration but load your own weights. In","HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the","attribute with the supplied ``kwargs`` value. Remaining keys that do not correspond to","case, ``from_tf`` should be set to True and a configuration object should be","**kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\",","pass on a seq2eq depends what we are performing: - During training we","pre-trained model configuration should be cached if the standard cache should not be",") # Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None)","configuration attribute will be used to override said attribute with the supplied ``kwargs``","Apache License, Version 2.0 (the \"License\"); # you may not use this file","specific language governing permissions and # limitations under the License. \"\"\" Classes to","Classes to support Encoder-Decoder architectures \"\"\" from __future__ import absolute_import, division, print_function, unicode_literals","In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is","or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case,","value of the flag `is_decoder` that we need to set correctly. encoder =","on a seq2eq depends what we are performing: - During training we perform","encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\",","TensorFlow checkpoint in a PyTorch model using the provided conversion scripts and loading","need for each to get down to the embedding weights. However the different","# See the License for the specific language governing permissions and # limitations","the License is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR","in a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save","it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on","(`decoder_model=lstm_model`), or\" \" - a dictionary of configuration parameters that will be used","be used. force_download: (`optional`) boolean, default False: Force to (re-)download the model weights","initialize, say, the decoder randomly by creating it beforehand as follows config =","the same family. If the name of or that path to a pretrained","any configuration attribute will be passed to the underlying model's ``__init__`` function. You","the Apache License, Version 2.0 (the \"License\"); # you may not use this","you may not use this file except in compliance with the License. #","- a path or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`).","need to set correctly. encoder = kwargs_encoder.pop(\"model\", None) if encoder is None: encoder","Set to ``True`` to also return a dictionnary containing missing keys, unexpected keys","pretrained configuration but load your own weights. In this case though, you should","(prefixed by `decoder_`) and those # that apply to the model as a","use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are","`:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two separate directories. \"\"\"","automatically loaded configuation. Configuration can be automatically loaded when: - the model is","Copyright 2018 The HuggingFace Inc. team. # # Licensed under the Apache License,","( \"bert\" not in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path","from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class","files and override the cached versions if they exists. proxies: (`optional`) dict, default","configuration is provided with ``config``, ``**kwargs`` will be directly passed to the underlying","from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an automatically loaded","to use instead of a state dictionary loaded from saved weights file. This","model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path,","and (optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method.","\"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward pass on","# Licensed under the Apache License, Version 2.0 (the \"License\"); # you may","decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a string with the","several forward passes with the encoder's hidden state through the decoder to decode","(e.g. ``output_attention=True``). Behave differently depending on whether a `config` is provided or automatically","You can specify kwargs sepcific for the encoder and decoder by prefixing the","own weights. In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and","model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\" # keyword arguments come in","roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but it is \"blocked\"","model's ``__init__`` method (we assume all relevant updates to the configuration have already","provided by the library (loaded with the ``shortcut-name`` string of a pretrained model),","the provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary","encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ):","the configuration object (after it being loaded) and initiate the model. (e.g. ``output_attention=True``).",")... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if","This option can be used if you want to create a model from","Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None) is None: # We","= encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return","passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize","= Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def","protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on","a configuration is provided with ``config``, ``**kwargs`` will be directly passed to the","We will create a randomly initilized LSTM model as decoder if \"decoder_config\" not","weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a","of or that path to a pretrained model is specified the encoder and","= BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args,","loading path is slower than converting the TensorFlow checkpoint in a PyTorch model","if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy()","encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward pass on a seq2eq depends what we","need to first set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path:","argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Encode if needed (training,",") kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"decoder_\")","by suppling the save directory. - the model is loaded by suppling a","directory in which a downloaded pre-trained model configuration should be cached if the","**kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\", None) if decoder is None:","to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder","last layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states","*args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying the encoder and","the library as encoder and (optionally) another one as decoder when created with","encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs","*model_args, **kwargs ): r\"\"\" Instantiates an encoder and a decoder from one or","two base classes of the library from pre-trained model checkpoints. The model is","should be cached if the standard cache should not be used. force_download: (`optional`)","@classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None) is None: # We will","- a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.:","self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args,","Either: - a string with the `shortcut name` of a pre-trained model to",":class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated as a transformer","layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"]","self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward pass","string with the `shortcut name` of a pre-trained model to load from cache","PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\" # keyword arguments come in 3 flavors:","# keyword arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific","model, please supply either: \" \" - a torch.nn.LSTM model as `decoder_model` parameter","created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__()","`encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``","encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer hidden state else:","permissions and # limitations under the License. \"\"\" Classes to support Encoder-Decoder architectures","**kwargs ): r\"\"\" Instantiates an encoder and a decoder from one or two","a downloaded pre-trained model configuration should be cached if the standard cache should","the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save","not provided, ``kwargs`` will be first passed to the configuration class initialization function","to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should","``**kwargs`` will be directly passed to the underlying model's ``__init__`` method (we assume","information necessary to initiate the encoder. Either: - a string with the `shortcut","is a generic model class that will be instantiated as a transformer architecture","encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``","reloaded by suppling the save directory. - the model is loaded by suppling","model's ``__init__`` function. You can specify kwargs sepcific for the encoder and decoder","remaining kwargs will be passed to both encoders and decoders. Examples:: model =","model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None) is None:","to get down to the embedding weights. However the different model classes are","} kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for","forward pass on the encoder if an argument named `encoder_hidden_state` is passed to","on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,","deactivated) To train the model, you need to first set it back in","a configuration object should be provided as ``config`` argument. This loading path is","and a configuration object should be provided as ``config`` argument. This loading path","provided with ``config``, ``**kwargs`` will be directly passed to the underlying model's ``__init__``","decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self, encoder, decoder):","both of the encoder and decoder are of the same family. If the","cache should not be used. force_download: (`optional`) boolean, default False: Force to (re-)download","directly passed to the underlying model's ``__init__`` method (we assume all relevant updates","will be instantiated as a transformer architecture with one of the base model","None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder =","load an LSTM in Encoder-Decoder model, please supply either: \" \" - a","encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a string with the","of keyword arguments. Can be used to update the configuration object (after it","boolean: Set to ``True`` to also return a dictionnary containing missing keys, unexpected","(:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration attribute will be","the common ones in case of conflict. kwargs_common = { argument: value for","path or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this","See the License for the specific language governing permissions and # limitations under","already been done) - If a configuration is not provided, ``kwargs`` will be","(after it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending","pass through the encoder, and then perform several forward passes with the encoder's","the model to use instead of a state dictionary loaded from saved weights","decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both","done) - If a configuration is not provided, ``kwargs`` will be first passed","``__init__`` method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for","of keyword arguments. \"\"\" # keyword arguments come in 3 flavors: encoder-specific (prefixed","kwargs.items() if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder =","We need for each to get down to the embedding weights. However the","# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in","it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased',","model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by","RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM:","directory. - the model is loaded by suppling a local directory as ``pretrained_model_name_or_path``","model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments will","def tie_weights(self): \"\"\" Tying the encoder and decoders' embeddings together. We need for","the provided conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence","# limitations under the License. \"\"\" Classes to support Encoder-Decoder architectures \"\"\" from","**kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model","the pretrained weight (the cross-attention will be intialized randomly if its weights are","let the specific kwargs override the common ones in case of conflict. kwargs_common","are performing: - During training we perform one forward pass through both the","error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used to","assume all relevant updates to the configuration have already been done) - If","decoder's parameters in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self,","**kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying the encoder and decoders' embeddings together. We","at the model level is made # by the value of the flag","an LSTM in Encoder-Decoder model, please supply either: \" \" - a torch.nn.LSTM","\" torch.nn.LSTM model as `decoder_config` keyword argument. \" \" E.g. `decoder_config={'input_size': 768, 'hidden_size':","# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0","(`optional`) dict, default None: A dictionary of proxy servers to use by protocol","was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. -","file. This option can be used if you want to create a model","if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string:","in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder.","state dictionary loaded from saved weights file. This option can be used if","save_directory): \"\"\" Save a Seq2Seq model and its configuration file in a format","the last layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"] =","the underlying model's ``__init__`` method config: (`optional`) instance of a class derived from","arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by","super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None,","encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates an encoder and a decoder from","# Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs =","be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of","bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but","are not present). It is possible to override this behavior and initialize, say,","torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__)","Force to (re-)download the model weights and configuration files and override the cached","__init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def","randomly if its weights are not present). It is possible to override this","pass through both the encoder and decoder; - During prediction, we perform one","currently supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model","is a model provided by the library (loaded with the ``shortcut-name`` string of","model weights and configuration files and override the cached versions if they exists.","you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option.","model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights()","messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used to update","pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded","to the underlying model's ``__init__`` method (we assume all relevant updates to the","to initiate the decoder. Either: - a string with the `shortcut name` of","KIND, either express or implied. # See the License for the specific language","but load your own weights. In this case though, you should check if","override this behavior and initialize, say, the decoder randomly by creating it beforehand","to override said attribute with the supplied ``kwargs`` value. Remaining keys that do","level is made # by the value of the flag `is_decoder` that we","load your own weights. In this case though, you should check if using","of a pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``. -","to ``True`` to also return a dictionnary containing missing keys, unexpected keys and","to the embedding weights. However the different model classes are inconsistent to that","containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url","None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder =","LSTM in Encoder-Decoder model, please supply either: \" \" - a torch.nn.LSTM model","This loading path is slower than converting the TensorFlow checkpoint in a PyTorch","through both the encoder and decoder; - During prediction, we perform one forward","ANY KIND, either express or implied. # See the License for the specific","\"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if (","of ``kwargs`` that corresponds to a configuration attribute will be used to override","tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder","the cached versions if they exists. proxies: (`optional`) dict, default None: A dictionary","necessary to initiate the decoder. Either: - a string with the `shortcut name`","instead of a state dictionary loaded from saved weights file. This option can","argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape","initialize Bert2Bert \"\"\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by","be set to True and a configuration object should be provided as ``config``","WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See","one or two base classes of the library from pre-trained model checkpoints. The","PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a","sequence. Therefore, we skip the forward pass on the encoder if an argument","decoder from one or two base classes of the library from pre-trained model","between encoder and decoder at the model level is made # by the","of decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of","= kwargs_decoder.pop(\"model\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder )","of positional arguments: All remaning positional arguments will be passed to the underlying","necessary to initiate the encoder. Either: - a string with the `shortcut name`","path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. -","a pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``. - a","encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\", None) if decoder is None: decoder =","\"\"\" Save a Seq2Seq model and its configuration file in a format such","with one of the base model classes of the library as encoder and","the encoder and decoder; - During prediction, we perform one forward pass through","``kwargs`` will be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each","from pre-trained model checkpoints. The model is set in evaluation mode by default",":func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. - the model is","language governing permissions and # limitations under the License. \"\"\" Classes to support","encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the","a pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is","each model, but it is \"blocked\" by a model-specific keyword (bert, )... \"\"\"","PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments","{ argument: value for argument, value in kwargs.items() if not argument.startswith(\"encoder_\") and not","to override this behavior and initialize, say, the decoder randomly by creating it","by default using `model.eval()` (Dropout modules are deactivated) To train the model, you","a pretrained model is specified the encoder and the decoder will be initialized","= encoder_outputs[ 0 ] # output the last layer hidden state else: encoder_outputs","else: encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\",","- BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each","not be used. force_download: (`optional`) boolean, default False: Force to (re-)download the model","we skip the forward pass on the encoder if an argument named `encoder_hidden_state`","by creating it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model","under the License is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES","BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs)","is slower than converting the TensorFlow checkpoint in a PyTorch model using the","get down to the embedding weights. However the different model classes are inconsistent","\"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express","r\"\"\" Instantiates an encoder and a decoder from one or two base classes","= logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will","update the configuration object (after it being loaded) and initiate the model. (e.g.","proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.","seq2eq depends what we are performing: - During training we perform one forward","a full sequence. Therefore, we skip the forward pass on the encoder if","hidden state else: encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] =","applicable law or agreed to in writing, software # distributed under the License","`config.json` is found in the directory. state_dict: (`optional`) dict: an optional state dictionnary","__future__ import absolute_import, division, print_function, unicode_literals import logging import os import torch from","and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder.","simpler option. cache_dir: (`optional`) string: Path to a directory in which a downloaded","not correspond to any configuration attribute will be passed to the underlying model's","found in the directory. state_dict: (`optional`) dict: an optional state dictionnary for the","weight (the cross-attention will be intialized randomly if its weights are not present).","kwargs override the common ones in case of conflict. kwargs_common = { argument:","keyword arguments. Can be used to update the configuration object (after it being","CONDITIONS OF ANY KIND, either express or implied. # See the License for","model configuration should be cached if the standard cache should not be used.","= AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\", None)","the decoder will be initialized with the pretrained weight (the cross-attention will be","loaded from saved weights file. This option can be used if you want","cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates an encoder and a decoder","self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer hidden","Encoder-Decoder model, please supply either: \" \" - a torch.nn.LSTM model as `decoder_model`","writing, software # distributed under the License is distributed on an \"AS IS\"","# that apply to the model as whole. # We let the specific","specified the encoder and the decoder will be initialized with the pretrained weight","sequence_length)`` Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of","a simpler option. cache_dir: (`optional`) string: Path to a directory in which a","'bert-base-uncased') # initialize Bert2Bert \"\"\" # keyword arguments come in 3 flavors: encoder-specific","and decoder # The distinction between encoder and decoder at the model level","Instantiates an encoder and a decoder from one or two base classes of","first set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary","\"roberta\" in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only the Bert model","and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All","decoder at the model level is made # by the value of the","provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to","specify kwargs sepcific for the encoder and decoder by prefixing the key with","= False decoder = kwargs_decoder.pop(\"model\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained(","compliance with the License. # You may obtain a copy of the License","RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but it is","True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \"\"\" Save a","ones in case of conflict. kwargs_common = { argument: value for argument, value","= { argument: value for argument, value in kwargs.items() if not argument.startswith(\"encoder_\") and","such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and","`decoder_`) and those # that apply to the model as a whole. #","sepcific for the encoder and decoder by prefixing the key with `encoder_` and","architecture with one of the base model classes of the library as encoder","method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the","provided, ``kwargs`` will be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`).","vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens","be automatically loaded when: - the model is a model provided by the","it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters","\"bert\" not in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ):","performing: - During training we perform one forward pass through both the encoder","of configuration parameters that will be used to initialize a\" \" torch.nn.LSTM model","is provided with ``config``, ``**kwargs`` will be directly passed to the underlying model's","+ encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of","the base model classes of the library as encoder and (optionally) another one","kwargs_common = { argument: value for argument, value in kwargs.items() if not argument.startswith(\"encoder_\")","that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2:","**kwargs): \"\"\" The forward pass on a seq2eq depends what we are performing:","in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and","from saved weights file. This option can be used if you want to","kwargs_decoder.pop(\"model\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder","path is slower than converting the TensorFlow checkpoint in a PyTorch model using","kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[","boolean, default False: Force to (re-)download the model weights and configuration files and","Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a string with","standard cache should not be used. force_download: (`optional`) boolean, default False: Force to","and initialize, say, the decoder randomly by creating it beforehand as follows config","local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found","if the standard cache should not be used. force_download: (`optional`) boolean, default False:","proxies: (`optional`) dict, default None: A dictionary of proxy servers to use by","should not be used. force_download: (`optional`) boolean, default False: Force to (re-)download the","= () # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None )","encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] #","pretrained weight (the cross-attention will be intialized randomly if its weights are not","if its weights are not present). It is possible to override this behavior",":class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder and decoder are","(the \"License\"); # you may not use this file except in compliance with","model, you need to first set it back in training mode with `model.train()`","the save directory. - the model is loaded by suppling a local directory","be used to update the configuration object (after it being loaded) and initiate","set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated) To","`decoder_`) and those # that apply to the model as whole. # We","for the model to use instead of a state dictionary loaded from saved","a string with the `shortcut name` of a pre-trained model to load from","The distinction between encoder and decoder at the model level is made #","# Unless required by applicable law or agreed to in writing, software #","Bert2Bert \"\"\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by #","by applicable law or agreed to in writing, software # distributed under the","= kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for argument, value in kwargs.items() if","perform one forward pass through the encoder, and then perform several forward passes","'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`) boolean:","from a pretrained configuration but load your own weights. In this case though,","to decode a full sequence. Therefore, we skip the forward pass on the","(optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\"","supplied ``kwargs`` value. Remaining keys that do not correspond to any configuration attribute","768, 'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\")) model = super(Model2LSTM, cls).from_pretrained(*args,","one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self,","file except in compliance with the License. # You may obtain a copy","those # that apply to the model as whole. # We let the","encoder' and decoder's parameters in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\"))","= AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return","passed to the underlying model's ``__init__`` function. You can specify kwargs sepcific for","key of ``kwargs`` that corresponds to a configuration attribute will be used to","an argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of","function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration attribute will","torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \" - a dictionary of configuration","None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the","if an argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor``","your own weights. In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained`","r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder and decoder","not in kwargs: raise ValueError( \"To load an LSTM in Encoder-Decoder model, please","model to use instead of a state dictionary loaded from saved weights file.","the encoder. Either: - a string with the `shortcut name` of a pre-trained","apply to the model as whole. # We let the specific kwargs override","Remaining dictionary of keyword arguments. Can be used to update the configuration object","import os import torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead","logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that","forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward pass on a seq2eq depends what","initialize the encoder and decoder # The distinction between encoder and decoder at","OR CONDITIONS OF ANY KIND, either express or implied. # See the License","may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #","the encoder and decoder are of the same family. If the name of","(prefixed by `decoder_`) and those # that apply to the model as whole.","checkpoints. The model is set in evaluation mode by default using `model.eval()` (Dropout","a pretrained configuration but load your own weights. In this case though, you","decoders' embeddings together. We need for each to get down to the embedding","and those # that apply to the model as whole. # We let","Remaining keys that do not correspond to any configuration attribute will be passed","and # limitations under the License. \"\"\" Classes to support Encoder-Decoder architectures \"\"\"","function. You can specify kwargs sepcific for the encoder and decoder by prefixing","return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where","scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the","loaded when: - the model is a model provided by the library (loaded","where both of the encoder and decoder are of the same family. If","training we perform one forward pass through both the encoder and decoder; -","\"\"\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`),","correctly. encoder = kwargs_encoder.pop(\"model\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path,","model def save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq model and its configuration file","the underlying model's ``__init__`` method (we assume all relevant updates to the configuration","by the value of the flag `is_decoder` that we need to set correctly.","- During training we perform one forward pass through both the encoder and","`model.eval()` (Dropout modules are deactivated) To train the model, you need to first","is set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated)","pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``. - a path","for the specific language governing permissions and # limitations under the License. \"\"\"","model as a whole. # We let the specific kwargs override the common","``kwargs`` that corresponds to a configuration attribute will be used to override said","``kwargs`` value. Remaining keys that do not correspond to any configuration attribute will","kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class","checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True","library as encoder and (optionally) another one as decoder when created with the","encoder and a decoder from one or two base classes of the library","`shortcut name` of a pre-trained model to load from cache or download, e.g.:","used to initialize a\" \" torch.nn.LSTM model as `decoder_config` keyword argument. \" \"","model where both of the encoder and decoder are of the same family.","encoder = kwargs_encoder.pop(\"model\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args,","randomly by creating it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config)","to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies","mode by default using `model.eval()` (Dropout modules are deactivated) To train the model,","or that path to a pretrained model is specified the encoder and the","if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is","decoder to decode a full sequence. Therefore, we skip the forward pass on","class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration","= kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for argument, value","base model classes of the library as encoder and (optionally) another one as","be cached if the standard cache should not be used. force_download: (`optional`) boolean,","The forward pass on a seq2eq depends what we are performing: - During","pass on the encoder if an argument named `encoder_hidden_state` is passed to this","case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a","def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward pass on a seq2eq depends","common ones in case of conflict. kwargs_common = { argument: value for argument,","have already been done) - If a configuration is not provided, ``kwargs`` will","Licensed under the Apache License, Version 2.0 (the \"License\"); # you may not","the encoder and decoder by prefixing the key with `encoder_` and `decoder_` respectively.","same family. If the name of or that path to a pretrained model","model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config` is provided or","architectures \"\"\" from __future__ import absolute_import, division, print_function, unicode_literals import logging import os","a Seq2Seq2 model where both of the encoder and decoder are of the","value in kwargs.items() if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy()","named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size,","self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\" not in","the configuration have already been done) - If a configuration is not provided,","a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path","``True`` to also return a dictionnary containing missing keys, unexpected keys and error","different model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa:","the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to","is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF","nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder`","the XEmbedding layer for each model, but it is \"blocked\" by a model-specific","if argument.startswith(\"decoder_\") } ) # Encode if needed (training, first prediction pass) encoder_hidden_states","or download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing model weights","It is possible to override this behavior and initialize, say, the decoder randomly","whole. # We let the specific kwargs override the common ones in case","with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed","for argument, value in kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\") :]:","**kwargs): if kwargs.get(\"decoder_model\", None) is None: # We will create a randomly initilized","as decoder if \"decoder_config\" not in kwargs: raise ValueError( \"To load an LSTM","classes of the library as encoder and (optionally) another one as decoder when","the supplied ``kwargs`` value. Remaining keys that do not correspond to any configuration","def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod","will create a randomly initilized LSTM model as decoder if \"decoder_config\" not in","from one or two base classes of the library from pre-trained model checkpoints.","that will be used to initialize a\" \" torch.nn.LSTM model as `decoder_config` keyword","initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration attribute","to the underlying model's ``__init__`` function. You can specify kwargs sepcific for the","if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder =","We save the encoder' and decoder's parameters in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory,","GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer","encoder, and then perform several forward passes with the encoder's hidden state through","dict, default None: A dictionary of proxy servers to use by protocol or","keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be",":]: value for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Encode","for each model, but it is \"blocked\" by a model-specific keyword (bert, )...","the License for the specific language governing permissions and # limitations under the","as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self, encoder,","value for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Encode if","model as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \" - a dictionary of configuration parameters","intialized randomly if its weights are not present). It is possible to override","keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments.","is currently supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return","flag `is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\"model\", None) if","either: \" \" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \"","dictionary loaded from saved weights file. This option can be used if you","- the model is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and","perform several forward passes with the encoder's hidden state through the decoder to","it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate","a\" \" torch.nn.LSTM model as `decoder_config` keyword argument. \" \" E.g. `decoder_config={'input_size': 768,","with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a","and decoder by prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``).","**kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return model def save_pretrained(self,","decoder. Either: - a string with the `shortcut name` of a pre-trained model","# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #","of the library from pre-trained model checkpoints. The model is set in evaluation","automatically loaded when: - the model is a model provided by the library","will be passed to the underlying model's ``__init__`` method config: (`optional`) instance of","correspond to any configuration attribute will be passed to the underlying model's ``__init__``","configuration JSON file named `config.json` is found in the directory. state_dict: (`optional`) dict:","then perform several forward passes with the encoder's hidden state through the decoder","Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states","- the model is a model provided by the library (loaded with the","differently depending on whether a `config` is provided or automatically loaded: - If","as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \" - a dictionary of configuration parameters that","a path or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In","and decoder's parameters in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def","encoder and decoder are of the same family. If the name of or","E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\")) model =","argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( {","``shortcut-name`` string of a pretrained model), or - the model was saved using","a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``.","if argument.startswith(\"decoder_\") } ) # Load and initialize the encoder and decoder #","inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings","} ) kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for argument, value in kwargs.items() if","and then perform several forward passes with the encoder's hidden state through the","(`optional`) boolean: Set to ``True`` to also return a dictionnary containing missing keys,","Version 2.0 (the \"License\"); # you may not use this file except in","None) is None: # We will create a randomly initilized LSTM model as","\"\"\" The forward pass on a seq2eq depends what we are performing: -","is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder","Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids,","e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow index checkpoint file`","on the encoder if an argument named `encoder_hidden_state` is passed to this function.","each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return a dictionnary","() # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs",") encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\", None) if decoder is None: decoder","0 ] # output the last layer hidden state else: encoder_outputs = ()","cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls,","to support Encoder-Decoder architectures \"\"\" from __future__ import absolute_import, division, print_function, unicode_literals import","a generic model class that will be instantiated as a transformer architecture with","to load from cache or download, e.g.: ``bert-base-uncased``. - a path to a","keyword arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed","a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \" - a dictionary of","default using `model.eval()` (Dropout modules are deactivated) To train the model, you need","will be used to override said attribute with the supplied ``kwargs`` value. Remaining","as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found in the","argument: value for argument, value in kwargs.items() if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\")","# self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\"","decoder will be initialized with the pretrained weight (the cross-attention will be intialized","weights. In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained`","config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self,","sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of","if kwargs.get(\"decoder_model\", None) is None: # We will create a randomly initilized LSTM","instantiates a Seq2Seq2 model where both of the encoder and decoder are of","though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler","AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return model","the model to use instead of an automatically loaded configuation. Configuration can be","configuration attribute will be passed to the underlying model's ``__init__`` function. You can","what we are performing: - During training we perform one forward pass through","decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in","(`optional`) Remaining dictionary of keyword arguments. Can be used to update the configuration","in case of conflict. kwargs_common = { argument: value for argument, value in","as whole. # We let the specific kwargs override the common ones in","provided as ``config`` argument. This loading path is slower than converting the TensorFlow","cross-attention will be intialized randomly if its weights are not present). It is","prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs","shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the vocabulary. kwargs:","`AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder","import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\"","encoder and decoder; - During prediction, we perform one forward pass through the","model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a string","= encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs","of the flag `is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\"model\",","that do not correspond to any configuration attribute will be passed to the","model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory.","initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config` is","follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def","will be used to initialize a\" \" torch.nn.LSTM model as `decoder_config` keyword argument.","Seq2Seq2 model where both of the encoder and decoder are of the same","AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class","as ``config`` argument. This loading path is slower than converting the TensorFlow checkpoint","tie_weights(self): \"\"\" Tying the encoder and decoders' embeddings together. We need for each","class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None) is None: #","e.g.: ``bert-base-uncased``. - a path to a `directory` containing model weights saved using","self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2","loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file","kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for argument, value","\"decoder_config\" not in kwargs: raise ValueError( \"To load an LSTM in Encoder-Decoder model,","keyword arguments. \"\"\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by","OF ANY KIND, either express or implied. # See the License for the","the model level is made # by the value of the flag `is_decoder`","to set correctly. encoder = kwargs_encoder.pop(\"model\", None) if encoder is None: encoder =","model's ``__init__`` method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration","\"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward pass on a seq2eq","be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two","model and its configuration file in a format such that it can be","the specific kwargs override the common ones in case of conflict. kwargs_common =","configuation. Configuration can be automatically loaded when: - the model is a model","afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments will be","encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states","in a PyTorch model using the provided conversion scripts and loading the PyTorch","in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids,","the model, you need to first set it back in training mode with",":]: value for argument, value in kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( {","embeddings together. We need for each to get down to the embedding weights.","is made # by the value of the flag `is_decoder` that we need","argument, value in kwargs.items() if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder =","Configuration for the model to use instead of an automatically loaded configuation. Configuration","**kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer hidden state","the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \"\"\" # keyword arguments","downloaded pre-trained model configuration should be cached if the standard cache should not","model is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration","to True and a configuration object should be provided as ``config`` argument. This","(`optional`) Sequence of positional arguments: All remaning positional arguments will be passed to","the forward pass on the encoder if an argument named `encoder_hidden_state` is passed","the decoder. Either: - a string with the `shortcut name` of a pre-trained","from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates an encoder and a","- During prediction, we perform one forward pass through the encoder, and then","cache or download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing model","Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\" # keyword arguments come","return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None) is",") # Load and initialize the encoder and decoder # The distinction between","LSTM model as decoder if \"decoder_config\" not in kwargs: raise ValueError( \"To load","`config` is provided or automatically loaded: - If a configuration is provided with","configuration object should be provided as ``config`` argument. This loading path is slower","{ argument[len(\"decoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } )","`decoder_config` keyword argument. \" \" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\" )","None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder,","used on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return","be used if you want to create a model from a pretrained configuration","Load and initialize the encoder and decoder # The distinction between encoder and","or agreed to in writing, software # distributed under the License is distributed","torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module):","the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder =","encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None","absolute_import, division, print_function, unicode_literals import logging import os import torch from torch import","decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model","weights and configuration files and override the cached versions if they exists. proxies:","- RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but it",":func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path to","will be directly passed to the underlying model's ``__init__`` method (we assume all","name` of a pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``.","prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids,","under the Apache License, Version 2.0 (the \"License\"); # you may not use","skip the forward pass on the encoder if an argument named `encoder_hidden_state` is","(`optional`) boolean, default False: Force to (re-)download the model weights and configuration files","model as `decoder_config` keyword argument. \" \" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers':","During training we perform one forward pass through both the encoder and decoder;","format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder'","of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the vocabulary.","if \"decoder_config\" not in kwargs: raise ValueError( \"To load an LSTM in Encoder-Decoder","underlying model's ``__init__`` method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`:","License. # You may obtain a copy of the License at # #","index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to","kwargs.items() if argument.startswith(\"decoder_\") } ) # Encode if needed (training, first prediction pass)","string of a pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained`","the standard cache should not be used. force_download: (`optional`) boolean, default False: Force","a Seq2Seq model and its configuration file in a format such that it","in which a downloaded pre-trained model configuration should be cached if the standard","Behave differently depending on whether a `config` is provided or automatically loaded: -","encoder and (optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class","of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable","Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens","arguments: All remaning positional arguments will be passed to the underlying model's ``__init__``","A dictionary of proxy servers to use by protocol or endpoint, e.g.: {'http':","support Encoder-Decoder architectures \"\"\" from __future__ import absolute_import, division, print_function, unicode_literals import logging","During prediction, we perform one forward pass through the encoder, and then perform","= PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\" # keyword arguments come in 3","together. We need for each to get down to the embedding weights. However","encoder's hidden state through the decoder to decode a full sequence. Therefore, we","not in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ): raise","model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder):","with the pretrained weight (the cross-attention will be intialized randomly if its weights","XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of","License, Version 2.0 (the \"License\"); # you may not use this file except","class that will be instantiated as a transformer architecture with one of the","is possible to override this behavior and initialize, say, the decoder randomly by","# initialize Bert2Bert \"\"\" # keyword arguments come in 3 flavors: encoder-specific (prefixed","BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM:",") return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\"decoder_model\", None)","kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used to update the","but it is \"blocked\" by a model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder,","However the different model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings","of conflict. kwargs_common = { argument: value for argument, value in kwargs.items() if","is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output","def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying the","(`optional`) Remaining dictionary of keyword arguments. \"\"\" # keyword arguments come in 3","logging import os import torch from torch import nn from .modeling_auto import AutoModel,","encoder and decoder # The distinction between encoder and decoder at the model","both the encoder and decoder; - During prediction, we perform one forward pass","and decoders' embeddings together. We need for each to get down to the","dictionary of keyword arguments. Can be used to update the configuration object (after","underlying model's ``__init__`` method (we assume all relevant updates to the configuration have","raise ValueError(\"Only the Bert model is currently supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path,","be intialized randomly if its weights are not present). It is possible to","of the base model classes of the library as encoder and (optionally) another","decoder by prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The","(the cross-attention will be intialized randomly if its weights are not present). It","or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each","copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by","that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's","when: - the model is a model provided by the library (loaded with","model to load from cache or download, e.g.: ``bert-base-uncased``. - a path to","to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a","in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input","model to use instead of an automatically loaded configuation. Configuration can be automatically","checkpoint in a PyTorch model using the provided conversion scripts and loading the","the specific language governing permissions and # limitations under the License. \"\"\" Classes",".modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a","(`optional`) string: Path to a directory in which a downloaded pre-trained model configuration","updates to the configuration have already been done) - If a configuration is","a model from a pretrained configuration but load your own weights. In this","or automatically loaded: - If a configuration is provided with ``config``, ``**kwargs`` will","configuration have already been done) - If a configuration is not provided, ``kwargs``","both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\"","AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\", None) if","state else: encoder_outputs = () # Decode kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get(","to create a model from a pretrained configuration but load your own weights.","two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs):","embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the","its configuration file in a format such that it can be loaded using","and its configuration file in a format such that it can be loaded","encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in","the model is a model provided by the library (loaded with the ``shortcut-name``","using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path","be used to override said attribute with the supplied ``kwargs`` value. Remaining keys","or implied. # See the License for the specific language governing permissions and","Can be used to update the configuration object (after it being loaded) and",":func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path to a directory","and a decoder from one or two base classes of the library from","a state dictionary loaded from saved weights file. This option can be used","kwargs_decoder[\"encoder_hidden_states\"] = encoder_hidden_states kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder)","\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\")) model","classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings -","of a state dictionary loaded from saved weights file. This option can be","respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders and","forward pass through the encoder, and then perform several forward passes with the","and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config`","weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a","division, print_function, unicode_literals import logging import os import torch from torch import nn","of the same family. If the name of or that path to a","or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling","and decoder are of the same family. If the name of or that","behavior and initialize, say, the decoder randomly by creating it beforehand as follows","a configuration attribute will be used to override said attribute with the supplied","Save a Seq2Seq model and its configuration file in a format such that","model level is made # by the value of the flag `is_decoder` that","model checkpoints. The model is set in evaluation mode by default using `model.eval()`","path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. -","'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`) boolean: Set to","in kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for argument,","the model as a whole. # We let the specific kwargs override the","a dictionary of configuration parameters that will be used to initialize a\" \"","Inc. team. # # Licensed under the Apache License, Version 2.0 (the \"License\");","if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True","the License. \"\"\" Classes to support Encoder-Decoder architectures \"\"\" from __future__ import absolute_import,","governing permissions and # limitations under the License. \"\"\" Classes to support Encoder-Decoder",") decoder.config.is_decoder = True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory):","using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow index",":]: value for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Load","- a string with the `shortcut name` of a pre-trained model to load","the ``shortcut-name`` string of a pretrained model), or - the model was saved","use this file except in compliance with the License. # You may obtain",":func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow index checkpoint","perform one forward pass through both the encoder and decoder; - During prediction,","with the ``shortcut-name`` string of a pretrained model), or - the model was","with the encoder's hidden state through the decoder to decode a full sequence.","``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders and decoders. Examples::","kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"decoder_\") }","encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\"model\", None) if decoder","if you want to create a model from a pretrained configuration but load","3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those","can be used if you want to create a model from a pretrained","`./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True and a configuration","to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds","should be set to True and a configuration object should be provided as","cached if the standard cache should not be used. force_download: (`optional`) boolean, default","pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only the","they exists. proxies: (`optional`) dict, default None: A dictionary of proxy servers to","provided or automatically loaded: - If a configuration is provided with ``config``, ``**kwargs``","override the common ones in case of conflict. kwargs_common = { argument: value","BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs):","argument.startswith(\"decoder_\") } ) # Encode if needed (training, first prediction pass) encoder_hidden_states =","decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls,","of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the vocabulary.","- BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte -","by prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining","url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf``","None: # We will create a randomly initilized LSTM model as decoder if","an automatically loaded configuation. Configuration can be automatically loaded when: - the model","a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is","afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a string with","We let the specific kwargs override the common ones in case of conflict.","configuration file in a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained`","by `decoder_`) and those # that apply to the model as a whole.","an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either","to a directory in which a downloaded pre-trained model configuration should be cached","that path to a pretrained model is specified the encoder and the decoder","def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates an encoder and","full sequence. Therefore, we skip the forward pass on the encoder if an","for argument, value in kwargs.items() if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder","a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``.","request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return a dictionnary containing","\"To load an LSTM in Encoder-Decoder model, please supply either: \" \" -","None: A dictionary of proxy servers to use by protocol or endpoint, e.g.:","in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only","a model provided by the library (loaded with the ``shortcut-name`` string of a","hidden state through the decoder to decode a full sequence. Therefore, we skip","None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\"","# distributed under the License is distributed on an \"AS IS\" BASIS, #","conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate","as a transformer architecture with one of the base model classes of the","argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value","that will be instantiated as a transformer architecture with one of the base","decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\" # keyword arguments","servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The","kwargs_encoder.pop(\"model\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder )","family. If the name of or that path to a pretrained model is","False: Force to (re-)download the model weights and configuration files and override the","# We will create a randomly initilized LSTM model as decoder if \"decoder_config\"","model is a model provided by the library (loaded with the ``shortcut-name`` string","pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\" not in pretrained_model_name_or_path","evaluation mode by default using `model.eval()` (Dropout modules are deactivated) To train the","all relevant updates to the configuration have already been done) - If a","and is reloaded by suppling the save directory. - the model is loaded","\" - a dictionary of configuration parameters that will be used to initialize","embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings","initiate the encoder. Either: - a string with the `shortcut name` of a","__init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying the encoder","with the License. # You may obtain a copy of the License at","``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found in the directory.","arguments will be passed to the underlying model's ``__init__`` method config: (`optional`) instance","kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"encoder_\")","train the model, you need to first set it back in training mode","not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update(","wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for","state through the decoder to decode a full sequence. Therefore, we skip the","embedding weights. However the different model classes are inconsistent to that respect: -","is not a simpler option. cache_dir: (`optional`) string: Path to a directory in","= True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \"\"\" Save","is reloaded by suppling the save directory. - the model is loaded by","encoder and decoder by prefixing the key with `encoder_` and `decoder_` respectively. (e.g.","argument of the XEmbedding layer for each model, but it is \"blocked\" by","a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be","will be intialized randomly if its weights are not present). It is possible","law or agreed to in writing, software # distributed under the License is","model as whole. # We let the specific kwargs override the common ones","and those # that apply to the model as a whole. # We","shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids:","the model is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a","needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None:","argument[len(\"decoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) #","`is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\"model\", None) if encoder","pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\" not in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path","dictionary of configuration parameters that will be used to initialize a\" \" torch.nn.LSTM","or two base classes of the library from pre-trained model checkpoints. The model","option. cache_dir: (`optional`) string: Path to a directory in which a downloaded pre-trained","a model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls,","containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url","flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those #","than converting the TensorFlow checkpoint in a PyTorch model using the provided conversion","decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs): super(Model2Model,","loaded configuation. Configuration can be automatically loaded when: - the model is a","in compliance with the License. # You may obtain a copy of the","is provided or automatically loaded: - If a configuration is provided with ``config``,","the encoder and decoders' embeddings together. We need for each to get down","License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or","# coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # Licensed under","said attribute with the supplied ``kwargs`` value. Remaining keys that do not correspond","and the decoder will be initialized with the pretrained weight (the cross-attention will","= cls(encoder, decoder) return model def save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq model","each to get down to the embedding weights. However the different model classes","BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.","download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing model weights saved","a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required","# `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply to the","string: Path to a directory in which a downloaded pre-trained model configuration should","raise ValueError( \"To load an LSTM in Encoder-Decoder model, please supply either: \"","we are performing: - During training we perform one forward pass through both","by `decoder_`) and those # that apply to the model as whole. #","the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence","the model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config` is provided","creating it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model =","= BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args,","and initialize the encoder and decoder # The distinction between encoder and decoder","cls(encoder, decoder) return model def save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq model and","``config``, ``**kwargs`` will be directly passed to the underlying model's ``__init__`` method (we","initialized with the pretrained weight (the cross-attention will be intialized randomly if its","file named `config.json` is found in the directory. state_dict: (`optional`) dict: an optional","the TensorFlow checkpoint in a PyTorch model using the provided conversion scripts and","down to the embedding weights. However the different model classes are inconsistent to","with the supplied ``kwargs`` value. Remaining keys that do not correspond to any","(Dropout modules are deactivated) To train the model, you need to first set","first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs``","- If a configuration is not provided, ``kwargs`` will be first passed to","will be passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased')","passed to the underlying model's ``__init__`` method config: (`optional`) instance of a class","model as decoder if \"decoder_config\" not in kwargs: raise ValueError( \"To load an","forward pass through both the encoder and decoder; - During prediction, we perform","the encoder' and decoder's parameters in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory,","super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying the encoder and decoders' embeddings","# Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if","decoder are of the same family. If the name of or that path","set to True and a configuration object should be provided as ``config`` argument.","config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model","def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\" not in pretrained_model_name_or_path or \"roberta\"","configuration is not provided, ``kwargs`` will be first passed to the configuration class","kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for argument, value in","key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be","will be passed to the underlying model's ``__init__`` function. You can specify kwargs","by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used","arguments. Can be used to update the configuration object (after it being loaded)","dictionary of keyword arguments. \"\"\" # keyword arguments come in 3 flavors: encoder-specific","as `decoder_config` keyword argument. \" \" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\"","can be automatically loaded when: - the model is a model provided by","a directory in which a downloaded pre-trained model configuration should be cached if","one forward pass through both the encoder and decoder; - During prediction, we","model class that will be instantiated as a transformer architecture with one of","be passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') #","encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False","do not correspond to any configuration attribute will be passed to the underlying","is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON","\" \" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \" -","(`optional`) dict: an optional state dictionnary for the model to use instead of","through the decoder to decode a full sequence. Therefore, we skip the forward","`decoder_model` parameter (`decoder_model=lstm_model`), or\" \" - a dictionary of configuration parameters that will","pretrained_model_name_or_path ): raise ValueError(\"Only the Bert model is currently supported.\") model = super(Model2Model,","distributed under the License is distributed on an \"AS IS\" BASIS, # WITHOUT","\"\"\" Tying the encoder and decoders' embeddings together. We need for each to","super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def","of a pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and","(re-)download the model weights and configuration files and override the cached versions if","to initiate the encoder. Either: - a string with the `shortcut name` of","self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None,","= kwargs_encoder.pop(\"model\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder","classes of the library from pre-trained model checkpoints. The model is set in","by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply to","made # by the value of the flag `is_decoder` that we need to","The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0","loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two separate","of the library as encoder and (optionally) another one as decoder when created","class method. \"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder","you want to create a model from a pretrained configuration but load your","present). It is possible to override this behavior and initialize, say, the decoder","attribute will be used to override said attribute with the supplied ``kwargs`` value.","weights file. This option can be used if you want to create a","encoder if an argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids:","this file except in compliance with the License. # You may obtain a","`decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders","is found in the directory. state_dict: (`optional`) dict: an optional state dictionnary for","} ) # Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\",","be directly passed to the underlying model's ``__init__`` method (we assume all relevant","- If a configuration is provided with ``config``, ``**kwargs`` will be directly passed","dict: an optional state dictionnary for the model to use instead of a","state dictionnary for the model to use instead of a state dictionary loaded","it is \"blocked\" by a model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder)","versions if they exists. proxies: (`optional`) dict, default None: A dictionary of proxy","slower than converting the TensorFlow checkpoint in a PyTorch model using the provided","the directory. state_dict: (`optional`) dict: an optional state dictionnary for the model to","the decoder randomly by creating it beforehand as follows config = BertConfig.from_pretrained() decoder","remaning positional arguments will be passed to the underlying model's ``__init__`` method config:","Path to a directory in which a downloaded pre-trained model configuration should be","dictionary of proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128',","# Load and initialize the encoder and decoder # The distinction between encoder","derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an automatically","save directory. - the model is loaded by suppling a local directory as","from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is","{ argument[len(\"encoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"encoder_\") } )","import torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger =","= self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model` instantiates a","e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info:","respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte","``from_tf`` should be set to True and a configuration object should be provided","missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword","configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a","of the XEmbedding layer for each model, but it is \"blocked\" by a","configuration should be cached if the standard cache should not be used. force_download:","distinction between encoder and decoder at the model level is made # by","self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying the encoder and decoders' embeddings together.","``./my_model_directory/decoder``. - a path or url to a `tensorflow index checkpoint file` (e.g.","decoder_input_ids, **kwargs): \"\"\" The forward pass on a seq2eq depends what we are","in pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only the Bert model is","in kwargs.items() if not argument.startswith(\"encoder_\") and not argument.startswith(\"decoder_\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder","the `shortcut name` of a pre-trained model to load from cache or download,","and override the cached versions if they exists. proxies: (`optional`) dict, default None:","under the License. \"\"\" Classes to support Encoder-Decoder architectures \"\"\" from __future__ import","License. \"\"\" Classes to support Encoder-Decoder architectures \"\"\" from __future__ import absolute_import, division,","a PyTorch model using the provided conversion scripts and loading the PyTorch model","passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that","# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to","= decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates","a whole. # We let the specific kwargs override the common ones in","a configuration is not provided, ``kwargs`` will be first passed to the configuration","used to update the configuration object (after it being loaded) and initiate the","the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: -","will be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key","self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward pass on a","JSON file named `config.json` is found in the directory. state_dict: (`optional`) dict: an","pretrained_model_name_or_path or \"distilbert\" in pretrained_model_name_or_path ): raise ValueError(\"Only the Bert model is currently",":func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow index checkpoint","beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder)","`decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\")) model = super(Model2LSTM,","for argument, value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Load and initialize","saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow","automatically loaded: - If a configuration is provided with ``config``, ``**kwargs`` will be","in pretrained_model_name_or_path ): raise ValueError(\"Only the Bert model is currently supported.\") model =","and a configuration JSON file named `config.json` is found in the directory. state_dict:","required by applicable law or agreed to in writing, software # distributed under","logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be","save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq model and its configuration file in a","set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to","model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments will be passed","- a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \" - a dictionary","# by the value of the flag `is_decoder` that we need to set","separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\"","True and a configuration object should be provided as ``config`` argument. This loading","decoder if \"decoder_config\" not in kwargs: raise ValueError( \"To load an LSTM in","the encoder and the decoder will be initialized with the pretrained weight (the","import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic","model classes of the library as encoder and (optionally) another one as decoder","as encoder and (optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)`","the model weights and configuration files and override the cached versions if they","e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow index checkpoint file`","You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #","and decoder at the model level is made # by the value of","conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional","\" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\" \" - a","should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir:","exists. proxies: (`optional`) dict, default None: A dictionary of proxy servers to use","kwargs will be passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased',","is not provided, ``kwargs`` will be first passed to the configuration class initialization","\"\"\" from __future__ import absolute_import, division, print_function, unicode_literals import logging import os import","kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for argument, value in kwargs.items() if argument.startswith(\"encoder_\") }","BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model,","function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence","Encoder-Decoder architectures \"\"\" from __future__ import absolute_import, division, print_function, unicode_literals import logging import","= kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states =","method (we assume all relevant updates to the configuration have already been done)","proxies are used on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to","'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\")) model = super(Model2LSTM, cls).from_pretrained(*args, **kwargs) return model","encoder. Either: - a string with the `shortcut name` of a pre-trained model","kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\"encoder_\") :]: value for argument, value in kwargs.items()","is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices","endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request.","this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input","on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return a","force_download: (`optional`) boolean, default False: Force to (re-)download the model weights and configuration","in the directory. state_dict: (`optional`) dict: an optional state dictionnary for the model","pre-trained model checkpoints. The model is set in evaluation mode by default using","from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \"bert\" not in pretrained_model_name_or_path or \"roberta\" in","in evaluation mode by default using `model.eval()` (Dropout modules are deactivated) To train","loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether a","# you may not use this file except in compliance with the License.","library from pre-trained model checkpoints. The model is set in evaluation mode by","those # that apply to the model as a whole. # We let","that apply to the model as a whole. # We let the specific","Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self):","converting the TensorFlow checkpoint in a PyTorch model using the provided conversion scripts","using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. - the model","decoder) return model def save_pretrained(self, save_directory): \"\"\" Save a Seq2Seq model and its","encoder and the decoder will be initialized with the pretrained weight (the cross-attention",") decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\"\"\" :class:`~transformers.Model2Model`","and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path to a","from cache or download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing","output_loading_info: (`optional`) boolean: Set to ``True`` to also return a dictionnary containing missing","Remaining dictionary of keyword arguments. \"\"\" # keyword arguments come in 3 flavors:","value in kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for","model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to","value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Encode if needed (training, first","for each to get down to the embedding weights. However the different model","(we assume all relevant updates to the configuration have already been done) -","to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a","to the underlying model's ``__init__`` method config: (`optional`) instance of a class derived","decoder.config.is_decoder = True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \"\"\"","should be provided as ``config`` argument. This loading path is slower than converting","back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the","whether a `config` is provided or automatically loaded: - If a configuration is","model is currently supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs )","for the encoder and decoder by prefixing the key with `encoder_` and `decoder_`","\"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \"\"\" The forward","License for the specific language governing permissions and # limitations under the License.","the encoder's hidden state through the decoder to decode a full sequence. Therefore,","file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True and","(e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders and decoders.","# We let the specific kwargs override the common ones in case of","can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in","\"License\"); # you may not use this file except in compliance with the","obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless","to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings -","768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] = torch.nn.LSTM(kwargs.pop(\"decoder_config\")) model = super(Model2LSTM, cls).from_pretrained(*args, **kwargs) return","to the model as whole. # We let the specific kwargs override the","to initialize a\" \" torch.nn.LSTM model as `decoder_config` keyword argument. \" \" E.g.","decoder randomly by creating it beforehand as follows config = BertConfig.from_pretrained() decoder =","team. # # Licensed under the Apache License, Version 2.0 (the \"License\"); #","Indices of decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary","If a configuration is provided with ``config``, ``**kwargs`` will be directly passed to","http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing,","saved weights file. This option can be used if you want to create","in writing, software # distributed under the License is distributed on an \"AS","used if you want to create a model from a pretrained configuration but","\"\"\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying","you need to first set it back in training mode with `model.train()` Params:","base classes of the library from pre-trained model checkpoints. The model is set","import absolute_import, division, print_function, unicode_literals import logging import os import torch from torch","argument. \" \" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"] =","decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates an encoder and a decoder from one","`encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply to the model","the Bert model is currently supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args,","kwargs.items() if argument.startswith(\"decoder_\") } ) # Load and initialize the encoder and decoder","- XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument","unicode_literals import logging import os import torch from torch import nn from .modeling_auto","\"blocked\" by a model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod","be provided as ``config`` argument. This loading path is slower than converting the","to the model as a whole. # We let the specific kwargs override","we perform one forward pass through both the encoder and decoder; - During","value for argument, value in kwargs.items() if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\")","decode a full sequence. Therefore, we skip the forward pass on the encoder","decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\" Instantiates an","file in a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We","None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0","configuration object (after it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave","decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword","(`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to","generic model class that will be instantiated as a transformer architecture with one","loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning","**kwargs): if ( \"bert\" not in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or \"distilbert\"","`encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to","limitations under the License. \"\"\" Classes to support Encoder-Decoder architectures \"\"\" from __future__","is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model =","as a whole. # We let the specific kwargs override the common ones","the model as whole. # We let the specific kwargs override the common","underlying model's ``__init__`` function. You can specify kwargs sepcific for the encoder and","- GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding","\"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder):","2.0 (the \"License\"); # you may not use this file except in compliance","depends what we are performing: - During training we perform one forward pass","initiate the decoder. Either: - a string with the `shortcut name` of a","Seq2Seq model and its configuration file in a format such that it can","The model is set in evaluation mode by default using `model.eval()` (Dropout modules","WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the","a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of","encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\" #","mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: -","information necessary to initiate the decoder. Either: - a string with the `shortcut","kwargs sepcific for the encoder and decoder by prefixing the key with `encoder_`","# # Unless required by applicable law or agreed to in writing, software","(bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs):","express or implied. # See the License for the specific language governing permissions","value. Remaining keys that do not correspond to any configuration attribute will be","``bert-base-uncased``. - a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`,","through the encoder, and then perform several forward passes with the encoder's hidden","ValueError(\"Only the Bert model is currently supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path,","corresponds to a configuration attribute will be used to override said attribute with","a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the","either express or implied. # See the License for the specific language governing","Configuration can be automatically loaded when: - the model is a model provided","r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated as a","use instead of an automatically loaded configuation. Configuration can be automatically loaded when:","# output the last layer hidden state else: encoder_outputs = () # Decode","``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the","supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class","transformer architecture with one of the base model classes of the library as","*args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if","with ``config``, ``**kwargs`` will be directly passed to the underlying model's ``__init__`` method","weights. However the different model classes are inconsistent to that respect: - BertModel:","a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path","name of or that path to a pretrained model is specified the encoder","model is set in evaluation mode by default using `model.eval()` (Dropout modules are","the License. # You may obtain a copy of the License at #","unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can","import logging import os import torch from torch import nn from .modeling_auto import","in Encoder-Decoder model, please supply either: \" \" - a torch.nn.LSTM model as","scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments:","a dictionnary containing missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining","Bert model is currently supported.\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs","encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last","and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \"\"\" # keyword","be passed to the underlying model's ``__init__`` method config: (`optional`) instance of a","this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not","that apply to the model as whole. # We let the specific kwargs","an encoder and a decoder from one or two base classes of the","a `config` is provided or automatically loaded: - If a configuration is provided","is specified the encoder and the decoder will be initialized with the pretrained","in kwargs: raise ValueError( \"To load an LSTM in Encoder-Decoder model, please supply","are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel:","``config`` argument. This loading path is slower than converting the TensorFlow checkpoint in","(loaded with the ``shortcut-name`` string of a pretrained model), or - the model","depending on whether a `config` is provided or automatically loaded: - If a","= kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs","\"\"\" Classes to support Encoder-Decoder architectures \"\"\" from __future__ import absolute_import, division, print_function,","object (after it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently","self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\"\"\"","passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of","by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named","another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def","kwargs_decoder[\"encoder_attention_mask\"] = kwargs_encoder.get( \"attention_mask\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs +","# # Licensed under the Apache License, Version 2.0 (the \"License\"); # you","saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. - the","The proxies are used on each request. output_loading_info: (`optional`) boolean: Set to ``True``","decoder # The distinction between encoder and decoder at the model level is","pretrained model is specified the encoder and the decoder will be initialized with","being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether","class PreTrainedEncoderDecoder(nn.Module): r\"\"\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated","positional arguments: All remaning positional arguments will be passed to the underlying model's","will be initialized with the pretrained weight (the cross-attention will be intialized randomly","of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead","encoder and decoders' embeddings together. We need for each to get down to","model using the provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path:","self.tie_weights() def tie_weights(self): \"\"\" Tying the encoder and decoders' embeddings together. We need","layer for each model, but it is \"blocked\" by a model-specific keyword (bert,","``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the","decoder = kwargs_decoder.pop(\"model\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder","None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder","keyword argument. \" \" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\" ) kwargs[\"decoder_model\"]","model provided by the library (loaded with the ``shortcut-name`` string of a pretrained","argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for argument, value in kwargs.items()","sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \"\"\"","attribute will be passed to the underlying model's ``__init__`` function. You can specify","value in kwargs.items() if argument.startswith(\"decoder_\") } ) # Load and initialize the encoder","at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed","parameters in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\")) self.decoder.save_pretrained(os.path.join(save_directory, \"decoder\")) def forward(self, encoder_input_ids,","the library (loaded with the ``shortcut-name`` string of a pretrained model), or -","using the provided conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`)","dictionnary containing missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary","path to a pretrained model is specified the encoder and the decoder will","used. force_download: (`optional`) boolean, default False: Force to (re-)download the model weights and","`model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a string","kwargs: raise ValueError( \"To load an LSTM in Encoder-Decoder model, please supply either:","**kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\" Tying the encoder and decoders'","named `config.json` is found in the directory. state_dict: (`optional`) dict: an optional state","case of conflict. kwargs_common = { argument: value for argument, value in kwargs.items()","if argument.startswith(\"encoder_\") } ) kwargs_decoder.update( { argument[len(\"decoder_\") :]: value for argument, value in","passes with the encoder's hidden state through the decoder to decode a full","provided conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of","this behavior and initialize, say, the decoder randomly by creating it beforehand as","we need to set correctly. encoder = kwargs_encoder.pop(\"model\", None) if encoder is None:","library (loaded with the ``shortcut-name`` string of a pretrained model), or - the","kwargs: (`optional`) Remaining dictionary of keyword arguments. \"\"\" # keyword arguments come in","configuration files and override the cached versions if they exists. proxies: (`optional`) dict,","which a downloaded pre-trained model configuration should be cached if the standard cache","False decoder = kwargs_decoder.pop(\"model\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path,","embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings","os import torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger","except in compliance with the License. # You may obtain a copy of","All remaning positional arguments will be passed to the underlying model's ``__init__`` method","save the encoder' and decoder's parameters in two separate directories. \"\"\" self.encoder.save_pretrained(os.path.join(save_directory, \"encoder\"))","In this case, ``from_tf`` should be set to True and a configuration object","the decoder to decode a full sequence. Therefore, we skip the forward pass","to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert","for the model to use instead of an automatically loaded configuation. Configuration can","If a configuration is not provided, ``kwargs`` will be first passed to the","when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \"\"\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder,","may not use this file except in compliance with the License. # You","License is distributed on an \"AS IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS","passed to the underlying model's ``__init__`` method (we assume all relevant updates to","object should be provided as ``config`` argument. This loading path is slower than","parameters that will be used to initialize a\" \" torch.nn.LSTM model as `decoder_config`","Therefore, we skip the forward pass on the encoder if an argument named","create a randomly initilized LSTM model as decoder if \"decoder_config\" not in kwargs:","keys that do not correspond to any configuration attribute will be passed to","the underlying model's ``__init__`` function. You can specify kwargs sepcific for the encoder","of proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname':","decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return model def","torch.nn.LSTM model as `decoder_config` keyword argument. \" \" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768,","coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # Licensed under the","to (re-)download the model weights and configuration files and override the cached versions","decoder_model=decoder) \"\"\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \"\"\"","training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either:","its weights are not present). It is possible to override this behavior and","if they exists. proxies: (`optional`) dict, default None: A dictionary of proxy servers","first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\"hidden_states\", None) if encoder_hidden_states is None: encoder_outputs =","return a dictionnary containing missing keys, unexpected keys and error messages. kwargs: (`optional`)","the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will","if ( \"bert\" not in pretrained_model_name_or_path or \"roberta\" in pretrained_model_name_or_path or \"distilbert\" in","- a dictionary of configuration parameters that will be used to initialize a\"","encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained(","cache_dir: (`optional`) string: Path to a directory in which a downloaded pre-trained model","we perform one forward pass through the encoder, and then perform several forward","the library from pre-trained model checkpoints. The model is set in evaluation mode","set correctly. encoder = kwargs_encoder.pop(\"model\", None) if encoder is None: encoder = AutoModel.from_pretrained(","encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that","directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found in"],"string":"[\n \"Unless required by applicable law or agreed to in writing, software # distributed\",\n \"by a model-specific keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def\",\n \"To train the model, you need to first set it back in training\",\n \"use instead of a state dictionary loaded from saved weights file. This option\",\n \"prediction, we perform one forward pass through the encoder, and then perform several\",\n \"loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either:\",\n \"used to override said attribute with the supplied ``kwargs`` value. Remaining keys that\",\n \"vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \\\"\\\"\\\" # keyword arguments come\",\n \"are of the same family. If the name of or that path to\",\n \"`tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set\",\n \"method. \\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder =\",\n \"the encoder if an argument named `encoder_hidden_state` is passed to this function. Params:\",\n \"``__init__`` function. You can specify kwargs sepcific for the encoder and decoder by\",\n \"(e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True and a\",\n \"``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the vocabulary. kwargs: (`optional`)\",\n \"override the cached versions if they exists. proxies: (`optional`) dict, default None: A\",\n \":class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an automatically loaded configuation.\",\n \"- the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the\",\n \"this case, ``from_tf`` should be set to True and a configuration object should\",\n \"- RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings -\",\n \"option can be used if you want to create a model from a\",\n \"the name of or that path to a pretrained model is specified the\",\n \"in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \\\"\\\"\\\" # keyword\",\n \"decoder-specific (prefixed by `decoder_`) and those # that apply to the model as\",\n \"# Copyright 2018 The HuggingFace Inc. team. # # Licensed under the Apache\",\n \"def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None: # We will create\",\n \"can specify kwargs sepcific for the encoder and decoder by prefixing the key\",\n \"} ) # Load and initialize the encoder and decoder # The distinction\",\n \"and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used\",\n \"the embedding weights. However the different model classes are inconsistent to that respect:\",\n \"a decoder from one or two base classes of the library from pre-trained\",\n \"encoder_outputs[ 0 ] # output the last layer hidden state else: encoder_outputs =\",\n \"containing missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of\",\n \"input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices\",\n \"pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder)\",\n \"randomly initilized LSTM model as decoder if \\\"decoder_config\\\" not in kwargs: raise ValueError(\",\n \"IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or\",\n \"\\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\"))\",\n \"using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two separate directories.\",\n \"the different model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings -\",\n \"cached versions if they exists. proxies: (`optional`) dict, default None: A dictionary of\",\n \"def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq model and its configuration file in\",\n \"initilized LSTM model as decoder if \\\"decoder_config\\\" not in kwargs: raise ValueError( \\\"To\",\n \"decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates\",\n \"and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\")\",\n \"suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json`\",\n \"with the `shortcut name` of a pre-trained model to load from cache or\",\n \"If the name of or that path to a pretrained model is specified\",\n \"*args, **kwargs): if ( \\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or\",\n \"argument. This loading path is slower than converting the TensorFlow checkpoint in a\",\n \"the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional\",\n \"to use instead of an automatically loaded configuation. Configuration can be automatically loaded\",\n \"that we need to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder is\",\n \"using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow index\",\n \"be used to initialize a\\\" \\\" torch.nn.LSTM model as `decoder_config` keyword argument. \\\"\",\n \"been done) - If a configuration is not provided, ``kwargs`` will be first\",\n \"parameter (`decoder_model=lstm_model`), or\\\" \\\" - a dictionary of configuration parameters that will be\",\n \"instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use\",\n \"the encoder and decoder # The distinction between encoder and decoder at the\",\n \"in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Encode if needed (training, first prediction\",\n \"be instantiated as a transformer architecture with one of the base model classes\",\n \"default False: Force to (re-)download the model weights and configuration files and override\",\n \"(training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None: encoder_outputs\",\n \"if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ]\",\n \"to any configuration attribute will be passed to the underlying model's ``__init__`` function.\",\n \"\\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert model is currently supported.\\\") model\",\n \"{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`)\",\n \"and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both\",\n \"Tying the encoder and decoders' embeddings together. We need for each to get\",\n \"software # distributed under the License is distributed on an \\\"AS IS\\\" BASIS,\",\n \"positional arguments will be passed to the underlying model's ``__init__`` method config: (`optional`)\",\n \"``output_attention=True``). Behave differently depending on whether a `config` is provided or automatically loaded:\",\n \"] # output the last layer hidden state else: encoder_outputs = () #\",\n \"to a pretrained model is specified the encoder and the decoder will be\",\n \"@classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an encoder\",\n \"model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings\",\n \"and configuration files and override the cached versions if they exists. proxies: (`optional`)\",\n \"load from cache or download, e.g.: ``bert-base-uncased``. - a path to a `directory`\",\n \"class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an\",\n \"that corresponds to a configuration attribute will be used to override said attribute\",\n \"sequence_length)`` Indices of decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining\",\n \"'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\")) model = super(Model2LSTM, cls).from_pretrained(*args, **kwargs)\",\n \"using `model.eval()` (Dropout modules are deactivated) To train the model, you need to\",\n \"to also return a dictionnary containing missing keys, unexpected keys and error messages.\",\n \"kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for argument,\",\n \"model, but it is \\\"blocked\\\" by a model-specific keyword (bert, )... \\\"\\\"\\\" #\",\n \"the flag `is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None)\",\n \"possible to override this behavior and initialize, say, the decoder randomly by creating\",\n \"supply either: \\\" \\\" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\"\",\n \"the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law\",\n \"``./my_model_directory/encoder``. - a path or url to a `tensorflow index checkpoint file` (e.g.\",\n \"keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args,\",\n \"by the library (loaded with the ``shortcut-name`` string of a pretrained model), or\",\n \"one forward pass through the encoder, and then perform several forward passes with\",\n \"on whether a `config` is provided or automatically loaded: - If a configuration\",\n \"return model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq model and its configuration\",\n \"are used on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also\",\n \"value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Load and\",\n \"Sequence of positional arguments: All remaning positional arguments will be passed to the\",\n \"not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]:\",\n \"come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`)\",\n \"specific kwargs override the common ones in case of conflict. kwargs_common = {\",\n \"# that apply to the model as a whole. # We let the\",\n \"or\\\" \\\" - a dictionary of configuration parameters that will be used to\",\n \"conflict. kwargs_common = { argument: value for argument, value in kwargs.items() if not\",\n \"is \\\"blocked\\\" by a model-specific keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass\",\n \"relevant updates to the configuration have already been done) - If a configuration\",\n \"of the encoder and decoder are of the same family. If the name\",\n \"to update the configuration object (after it being loaded) and initiate the model.\",\n \"optional state dictionnary for the model to use instead of a state dictionary\",\n \"PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated as\",\n \"a seq2eq depends what we are performing: - During training we perform one\",\n \"value for argument, value in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") }\",\n \"forward passes with the encoder's hidden state through the decoder to decode a\",\n \"class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder\",\n \"AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model\",\n \"for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Encode if needed\",\n \"2018 The HuggingFace Inc. team. # # Licensed under the Apache License, Version\",\n \"please supply either: \\\" \\\" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`),\",\n \"\\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder\",\n \"# The distinction between encoder and decoder at the model level is made\",\n \"decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder)\",\n \"to the configuration have already been done) - If a configuration is not\",\n \"apply to the model as a whole. # We let the specific kwargs\",\n \"decoder; - During prediction, we perform one forward pass through the encoder, and\",\n \"The remaining kwargs will be passed to both encoders and decoders. Examples:: model\",\n \"Each key of ``kwargs`` that corresponds to a configuration attribute will be used\",\n \"a configuration JSON file named `config.json` is found in the directory. state_dict: (`optional`)\",\n \"an optional state dictionnary for the model to use instead of a state\",\n \"self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\" not\",\n \"model from a pretrained configuration but load your own weights. In this case\",\n \"or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert\",\n \"argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value\",\n \"configuration parameters that will be used to initialize a\\\" \\\" torch.nn.LSTM model as\",\n \"from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None: # We will create a\",\n \"of an automatically loaded configuation. Configuration can be automatically loaded when: - the\",\n \"Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape\",\n \"say, the decoder randomly by creating it beforehand as follows config = BertConfig.from_pretrained()\",\n \"`directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or\",\n \"): r\\\"\\\"\\\" Instantiates an encoder and a decoder from one or two base\",\n \"using the provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information\",\n \"a randomly initilized LSTM model as decoder if \\\"decoder_config\\\" not in kwargs: raise\",\n \"model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq\",\n \"initialize a\\\" \\\" torch.nn.LSTM model as `decoder_config` keyword argument. \\\" \\\" E.g. `decoder_config={'input_size':\",\n \"@classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\" not in pretrained_model_name_or_path or\",\n \"print_function, unicode_literals import logging import os import torch from torch import nn from\",\n \"and decoder; - During prediction, we perform one forward pass through the encoder,\",\n \"encoder and decoder at the model level is made # by the value\",\n \"argument.startswith(\\\"decoder_\\\") } ) # Load and initialize the encoder and decoder # The\",\n \"model using the provided conversion scripts and loading the PyTorch model afterwards. model_args:\",\n \"= self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer\",\n \"directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The\",\n \"not use this file except in compliance with the License. # You may\",\n \"the value of the flag `is_decoder` that we need to set correctly. encoder\",\n \"PyTorch model using the provided conversion scripts and loading the PyTorch model afterwards.\",\n \"XEmbedding layer for each model, but it is \\\"blocked\\\" by a model-specific keyword\",\n \"the encoder, and then perform several forward passes with the encoder's hidden state\",\n \"(prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply\",\n \"directory. state_dict: (`optional`) dict: an optional state dictionnary for the model to use\",\n \"in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Load and initialize the encoder and\",\n \"suppling the save directory. - the model is loaded by suppling a local\",\n \"one of the base model classes of the library as encoder and (optionally)\",\n \"distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY\",\n \"modules are deactivated) To train the model, you need to first set it\",\n \"to first set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information\",\n \"arguments. \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by #\",\n \"encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args,\",\n \"to a configuration attribute will be used to override said attribute with the\",\n \"a transformer architecture with one of the base model classes of the library\",\n \"`directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or\",\n \"tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \\\"\\\"\\\" #\",\n \"agreed to in writing, software # distributed under the License is distributed on\",\n \"state_dict: (`optional`) dict: an optional state dictionnary for the model to use instead\",\n \"argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Load and initialize the\",\n \"*args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None: # We will create a randomly\",\n \"are deactivated) To train the model, you need to first set it back\",\n \"is None: # We will create a randomly initilized LSTM model as decoder\",\n \"model is specified the encoder and the decoder will be initialized with the\",\n \"want to create a model from a pretrained configuration but load your own\",\n \"also return a dictionnary containing missing keys, unexpected keys and error messages. kwargs:\",\n \"``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor``\",\n \"*model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder is\",\n \"weights are not present). It is possible to override this behavior and initialize,\",\n \"kwargs.get(\\\"decoder_model\\\", None) is None: # We will create a randomly initilized LSTM model\",\n \"be initialized with the pretrained weight (the cross-attention will be intialized randomly if\",\n \"dictionnary for the model to use instead of a state dictionary loaded from\",\n \"input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments.\",\n \"not present). It is possible to override this behavior and initialize, say, the\",\n \"decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs):\",\n \"configuration but load your own weights. In this case though, you should check\",\n \"as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\"\",\n \"loaded: - If a configuration is provided with ``config``, ``**kwargs`` will be directly\",\n \"check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`)\",\n \"Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder and\",\n \"instead of an automatically loaded configuation. Configuration can be automatically loaded when: -\",\n \"be passed to the underlying model's ``__init__`` function. You can specify kwargs sepcific\",\n \"forward pass on a seq2eq depends what we are performing: - During training\",\n \"'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`) boolean: Set\",\n \"model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to\",\n \"saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow\",\n \"output the last layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"]\",\n \"): raise ValueError(\\\"Only the Bert model is currently supported.\\\") model = super(Model2Model, cls).from_pretrained(\",\n \"ValueError( \\\"To load an LSTM in Encoder-Decoder model, please supply either: \\\" \\\"\",\n \"of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size,\",\n \"with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder\",\n \"to in writing, software # distributed under the License is distributed on an\",\n \"= super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod\",\n \"instantiated as a transformer architecture with one of the base model classes of\",\n \"default None: A dictionary of proxy servers to use by protocol or endpoint,\",\n \"implied. # See the License for the specific language governing permissions and #\",\n \"from __future__ import absolute_import, division, print_function, unicode_literals import logging import os import torch\",\n \"not a simpler option. cache_dir: (`optional`) string: Path to a directory in which\",\n \"override said attribute with the supplied ``kwargs`` value. Remaining keys that do not\",\n \"``__init__`` method (we assume all relevant updates to the configuration have already been\",\n \"or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert model is currently supported.\\\")\",\n \"argument[len(\\\"encoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update(\",\n \"create a model from a pretrained configuration but load your own weights. In\",\n \"HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the\",\n \"attribute with the supplied ``kwargs`` value. Remaining keys that do not correspond to\",\n \"case, ``from_tf`` should be set to True and a configuration object should be\",\n \"**kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\",\",\n \"pass on a seq2eq depends what we are performing: - During training we\",\n \"pre-trained model configuration should be cached if the standard cache should not be\",\n \") # Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None)\",\n \"configuration attribute will be used to override said attribute with the supplied ``kwargs``\",\n \"Apache License, Version 2.0 (the \\\"License\\\"); # you may not use this file\",\n \"specific language governing permissions and # limitations under the License. \\\"\\\"\\\" Classes to\",\n \"Classes to support Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import absolute_import, division, print_function, unicode_literals\",\n \"In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is\",\n \"or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case,\",\n \"value of the flag `is_decoder` that we need to set correctly. encoder =\",\n \"on a seq2eq depends what we are performing: - During training we perform\",\n \"encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\",\",\n \"TensorFlow checkpoint in a PyTorch model using the provided conversion scripts and loading\",\n \"need for each to get down to the embedding weights. However the different\",\n \"# See the License for the specific language governing permissions and # limitations\",\n \"the License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR\",\n \"in a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save\",\n \"it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on\",\n \"(`decoder_model=lstm_model`), or\\\" \\\" - a dictionary of configuration parameters that will be used\",\n \"be used. force_download: (`optional`) boolean, default False: Force to (re-)download the model weights\",\n \"initialize, say, the decoder randomly by creating it beforehand as follows config =\",\n \"the same family. If the name of or that path to a pretrained\",\n \"any configuration attribute will be passed to the underlying model's ``__init__`` function. You\",\n \"the Apache License, Version 2.0 (the \\\"License\\\"); # you may not use this\",\n \"you may not use this file except in compliance with the License. #\",\n \"- a path or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`).\",\n \"need to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder is None: encoder\",\n \"Set to ``True`` to also return a dictionnary containing missing keys, unexpected keys\",\n \"pretrained configuration but load your own weights. In this case though, you should\",\n \"(prefixed by `decoder_`) and those # that apply to the model as a\",\n \"use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are\",\n \"`:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two separate directories. \\\"\\\"\\\"\",\n \"automatically loaded configuation. Configuration can be automatically loaded when: - the model is\",\n \"Copyright 2018 The HuggingFace Inc. team. # # Licensed under the Apache License,\",\n \"( \\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path\",\n \"from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class\",\n \"files and override the cached versions if they exists. proxies: (`optional`) dict, default\",\n \"configuration is provided with ``config``, ``**kwargs`` will be directly passed to the underlying\",\n \"from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an automatically loaded\",\n \"to use instead of a state dictionary loaded from saved weights file. This\",\n \"model-specific keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path,\",\n \"and (optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method.\",\n \"\\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass on\",\n \"# Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you may\",\n \"decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a string with the\",\n \"several forward passes with the encoder's hidden state through the decoder to decode\",\n \"(e.g. ``output_attention=True``). Behave differently depending on whether a `config` is provided or automatically\",\n \"You can specify kwargs sepcific for the encoder and decoder by prefixing the\",\n \"own weights. In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and\",\n \"model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" # keyword arguments come in\",\n \"roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but it is \\\"blocked\\\"\",\n \"model's ``__init__`` method (we assume all relevant updates to the configuration have already\",\n \"provided by the library (loaded with the ``shortcut-name`` string of a pretrained model),\",\n \"the provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary\",\n \"encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ):\",\n \"the configuration object (after it being loaded) and initiate the model. (e.g. ``output_attention=True``).\",\n \")... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if\",\n \"This option can be used if you want to create a model from\",\n \"Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None: # We\",\n \"= encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return\",\n \"passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize\",\n \"= Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def\",\n \"protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on\",\n \"a configuration is provided with ``config``, ``**kwargs`` will be directly passed to the\",\n \"We will create a randomly initilized LSTM model as decoder if \\\"decoder_config\\\" not\",\n \"weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a\",\n \"of or that path to a pretrained model is specified the encoder and\",\n \"= BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args,\",\n \"loading path is slower than converting the TensorFlow checkpoint in a PyTorch model\",\n \"if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy()\",\n \"encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass on a seq2eq depends what we\",\n \"need to first set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path:\",\n \"argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Encode if needed (training,\",\n \") kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\")\",\n \"by suppling the save directory. - the model is loaded by suppling a\",\n \"directory in which a downloaded pre-trained model configuration should be cached if the\",\n \"**kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder is None:\",\n \"to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder\",\n \"last layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states\",\n \"*args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the encoder and\",\n \"the library as encoder and (optionally) another one as decoder when created with\",\n \"encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs\",\n \"*model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an encoder and a decoder from one or\",\n \"two base classes of the library from pre-trained model checkpoints. The model is\",\n \"should be cached if the standard cache should not be used. force_download: (`optional`)\",\n \"@classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None: # We will\",\n \"- a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.:\",\n \"self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args,\",\n \"Either: - a string with the `shortcut name` of a pre-trained model to\",\n \":class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated as a transformer\",\n \"layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"]\",\n \"self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass\",\n \"string with the `shortcut name` of a pre-trained model to load from cache\",\n \"PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" # keyword arguments come in 3 flavors:\",\n \"# keyword arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific\",\n \"model, please supply either: \\\" \\\" - a torch.nn.LSTM model as `decoder_model` parameter\",\n \"created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__()\",\n \"`encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``\",\n \"encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer hidden state else:\",\n \"permissions and # limitations under the License. \\\"\\\"\\\" Classes to support Encoder-Decoder architectures\",\n \"**kwargs ): r\\\"\\\"\\\" Instantiates an encoder and a decoder from one or two\",\n \"a downloaded pre-trained model configuration should be cached if the standard cache should\",\n \"the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save\",\n \"not provided, ``kwargs`` will be first passed to the configuration class initialization function\",\n \"to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should\",\n \"``**kwargs`` will be directly passed to the underlying model's ``__init__`` method (we assume\",\n \"information necessary to initiate the encoder. Either: - a string with the `shortcut\",\n \"is a generic model class that will be instantiated as a transformer architecture\",\n \"encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``\",\n \"reloaded by suppling the save directory. - the model is loaded by suppling\",\n \"model's ``__init__`` function. You can specify kwargs sepcific for the encoder and decoder\",\n \"remaining kwargs will be passed to both encoders and decoders. Examples:: model =\",\n \"model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None:\",\n \"to get down to the embedding weights. However the different model classes are\",\n \"} kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for\",\n \"forward pass on the encoder if an argument named `encoder_hidden_state` is passed to\",\n \"on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,\",\n \"deactivated) To train the model, you need to first set it back in\",\n \"a configuration object should be provided as ``config`` argument. This loading path is\",\n \"and a configuration object should be provided as ``config`` argument. This loading path\",\n \"provided with ``config``, ``**kwargs`` will be directly passed to the underlying model's ``__init__``\",\n \"decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self, encoder, decoder):\",\n \"both of the encoder and decoder are of the same family. If the\",\n \"cache should not be used. force_download: (`optional`) boolean, default False: Force to (re-)download\",\n \"directly passed to the underlying model's ``__init__`` method (we assume all relevant updates\",\n \"will be instantiated as a transformer architecture with one of the base model\",\n \"None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder =\",\n \"load an LSTM in Encoder-Decoder model, please supply either: \\\" \\\" - a\",\n \"encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a string with the\",\n \"of keyword arguments. Can be used to update the configuration object (after it\",\n \"boolean: Set to ``True`` to also return a dictionnary containing missing keys, unexpected\",\n \"(:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration attribute will be\",\n \"the common ones in case of conflict. kwargs_common = { argument: value for\",\n \"path or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this\",\n \"See the License for the specific language governing permissions and # limitations under\",\n \"already been done) - If a configuration is not provided, ``kwargs`` will be\",\n \"(after it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending\",\n \"pass through the encoder, and then perform several forward passes with the encoder's\",\n \"the model to use instead of a state dictionary loaded from saved weights\",\n \"decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both\",\n \"done) - If a configuration is not provided, ``kwargs`` will be first passed\",\n \"``__init__`` method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for\",\n \"of keyword arguments. \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific (prefixed\",\n \"kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder =\",\n \"We need for each to get down to the embedding weights. However the\",\n \"# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in\",\n \"it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased',\",\n \"model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by\",\n \"RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM:\",\n \"directory. - the model is loaded by suppling a local directory as ``pretrained_model_name_or_path``\",\n \"model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments will\",\n \"def tie_weights(self): \\\"\\\"\\\" Tying the encoder and decoders' embeddings together. We need for\",\n \"the provided conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence\",\n \"# limitations under the License. \\\"\\\"\\\" Classes to support Encoder-Decoder architectures \\\"\\\"\\\" from\",\n \"**kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model\",\n \"the pretrained weight (the cross-attention will be intialized randomly if its weights are\",\n \"let the specific kwargs override the common ones in case of conflict. kwargs_common\",\n \"are performing: - During training we perform one forward pass through both the\",\n \"error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used to\",\n \"assume all relevant updates to the configuration have already been done) - If\",\n \"decoder's parameters in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self,\",\n \"**kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the encoder and decoders' embeddings together. We\",\n \"at the model level is made # by the value of the flag\",\n \"an LSTM in Encoder-Decoder model, please supply either: \\\" \\\" - a torch.nn.LSTM\",\n \"\\\" torch.nn.LSTM model as `decoder_config` keyword argument. \\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size':\",\n \"# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0\",\n \"(`optional`) dict, default None: A dictionary of proxy servers to use by protocol\",\n \"was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. -\",\n \"file. This option can be used if you want to create a model\",\n \"if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string:\",\n \"in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder.\",\n \"state dictionary loaded from saved weights file. This option can be used if\",\n \"save_directory): \\\"\\\"\\\" Save a Seq2Seq model and its configuration file in a format\",\n \"the last layer hidden state else: encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] =\",\n \"the underlying model's ``__init__`` method config: (`optional`) instance of a class derived from\",\n \"arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by\",\n \"super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None,\",\n \"encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an encoder and a decoder from\",\n \"# Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs =\",\n \"be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of\",\n \"bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but\",\n \"are not present). It is possible to override this behavior and initialize, say,\",\n \"torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__)\",\n \"Force to (re-)download the model weights and configuration files and override the cached\",\n \"__init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def\",\n \"randomly if its weights are not present). It is possible to override this\",\n \"pass through both the encoder and decoder; - During prediction, we perform one\",\n \"currently supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model\",\n \"is a model provided by the library (loaded with the ``shortcut-name`` string of\",\n \"model weights and configuration files and override the cached versions if they exists.\",\n \"you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option.\",\n \"model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights()\",\n \"messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used to update\",\n \"pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded\",\n \"to the underlying model's ``__init__`` method (we assume all relevant updates to the\",\n \"to initiate the decoder. Either: - a string with the `shortcut name` of\",\n \"KIND, either express or implied. # See the License for the specific language\",\n \"but load your own weights. In this case though, you should check if\",\n \"override this behavior and initialize, say, the decoder randomly by creating it beforehand\",\n \"to override said attribute with the supplied ``kwargs`` value. Remaining keys that do\",\n \"level is made # by the value of the flag `is_decoder` that we\",\n \"load your own weights. In this case though, you should check if using\",\n \"of a pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``. -\",\n \"to ``True`` to also return a dictionnary containing missing keys, unexpected keys and\",\n \"to the embedding weights. However the different model classes are inconsistent to that\",\n \"containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url\",\n \"None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder =\",\n \"LSTM in Encoder-Decoder model, please supply either: \\\" \\\" - a torch.nn.LSTM model\",\n \"This loading path is slower than converting the TensorFlow checkpoint in a PyTorch\",\n \"through both the encoder and decoder; - During prediction, we perform one forward\",\n \"ANY KIND, either express or implied. # See the License for the specific\",\n \"\\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if (\",\n \"of ``kwargs`` that corresponds to a configuration attribute will be used to override\",\n \"tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder\",\n \"the cached versions if they exists. proxies: (`optional`) dict, default None: A dictionary\",\n \"necessary to initiate the decoder. Either: - a string with the `shortcut name`\",\n \"instead of a state dictionary loaded from saved weights file. This option can\",\n \"argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape\",\n \"initialize Bert2Bert \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by\",\n \"be set to True and a configuration object should be provided as ``config``\",\n \"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See\",\n \"one or two base classes of the library from pre-trained model checkpoints. The\",\n \"PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a\",\n \"sequence. Therefore, we skip the forward pass on the encoder if an argument\",\n \"decoder from one or two base classes of the library from pre-trained model\",\n \"between encoder and decoder at the model level is made # by the\",\n \"of decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of\",\n \"= kwargs_decoder.pop(\\\"model\\\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder )\",\n \"of positional arguments: All remaning positional arguments will be passed to the underlying\",\n \"necessary to initiate the encoder. Either: - a string with the `shortcut name`\",\n \"path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. -\",\n \"a pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``. - a\",\n \"encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder is None: decoder =\",\n \"\\\"\\\"\\\" Save a Seq2Seq model and its configuration file in a format such\",\n \"with one of the base model classes of the library as encoder and\",\n \"the encoder and decoder; - During prediction, we perform one forward pass through\",\n \"``kwargs`` will be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each\",\n \"from pre-trained model checkpoints. The model is set in evaluation mode by default\",\n \":func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. - the model is\",\n \"language governing permissions and # limitations under the License. \\\"\\\"\\\" Classes to support\",\n \"encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the\",\n \"a pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is\",\n \"each model, but it is \\\"blocked\\\" by a model-specific keyword (bert, )... \\\"\\\"\\\"\",\n \"PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments\",\n \"{ argument: value for argument, value in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not\",\n \"to override this behavior and initialize, say, the decoder randomly by creating it\",\n \"by default using `model.eval()` (Dropout modules are deactivated) To train the model, you\",\n \"a pretrained model is specified the encoder and the decoder will be initialized\",\n \"= encoder_outputs[ 0 ] # output the last layer hidden state else: encoder_outputs\",\n \"else: encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\",\",\n \"- BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each\",\n \"not be used. force_download: (`optional`) boolean, default False: Force to (re-)download the model\",\n \"we skip the forward pass on the encoder if an argument named `encoder_hidden_state`\",\n \"by creating it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model\",\n \"under the License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES\",\n \"BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs)\",\n \"is slower than converting the TensorFlow checkpoint in a PyTorch model using the\",\n \"get down to the embedding weights. However the different model classes are inconsistent\",\n \"\\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express\",\n \"r\\\"\\\"\\\" Instantiates an encoder and a decoder from one or two base classes\",\n \"= logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will\",\n \"update the configuration object (after it being loaded) and initiate the model. (e.g.\",\n \"proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.\",\n \"seq2eq depends what we are performing: - During training we perform one forward\",\n \"a full sequence. Therefore, we skip the forward pass on the encoder if\",\n \"hidden state else: encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] =\",\n \"applicable law or agreed to in writing, software # distributed under the License\",\n \"`config.json` is found in the directory. state_dict: (`optional`) dict: an optional state dictionnary\",\n \"__future__ import absolute_import, division, print_function, unicode_literals import logging import os import torch from\",\n \"and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder.\",\n \"simpler option. cache_dir: (`optional`) string: Path to a directory in which a downloaded\",\n \"not correspond to any configuration attribute will be passed to the underlying model's\",\n \"found in the directory. state_dict: (`optional`) dict: an optional state dictionnary for the\",\n \"weight (the cross-attention will be intialized randomly if its weights are not present).\",\n \"kwargs override the common ones in case of conflict. kwargs_common = { argument:\",\n \"keyword arguments. Can be used to update the configuration object (after it being\",\n \"CONDITIONS OF ANY KIND, either express or implied. # See the License for\",\n \"model configuration should be cached if the standard cache should not be used.\",\n \"= AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\", None)\",\n \"the decoder will be initialized with the pretrained weight (the cross-attention will be\",\n \"loaded from saved weights file. This option can be used if you want\",\n \"cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an encoder and a decoder\",\n \"self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer hidden\",\n \"Encoder-Decoder model, please supply either: \\\" \\\" - a torch.nn.LSTM model as `decoder_model`\",\n \"writing, software # distributed under the License is distributed on an \\\"AS IS\\\"\",\n \"# that apply to the model as whole. # We let the specific\",\n \"specified the encoder and the decoder will be initialized with the pretrained weight\",\n \"sequence_length)`` Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of\",\n \"a simpler option. cache_dir: (`optional`) string: Path to a directory in which a\",\n \"'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific\",\n \"and decoder # The distinction between encoder and decoder at the model level\",\n \"Instantiates an encoder and a decoder from one or two base classes of\",\n \"first set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary\",\n \"\\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert model\",\n \"and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All\",\n \"decoder at the model level is made # by the value of the\",\n \"provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to\",\n \"specify kwargs sepcific for the encoder and decoder by prefixing the key with\",\n \"= False decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained(\",\n \"compliance with the License. # You may obtain a copy of the License\",\n \"RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but it is\",\n \"True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a\",\n \"ones in case of conflict. kwargs_common = { argument: value for argument, value\",\n \"= { argument: value for argument, value in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and\",\n \"such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and\",\n \"`decoder_`) and those # that apply to the model as a whole. #\",\n \"sepcific for the encoder and decoder by prefixing the key with `encoder_` and\",\n \"architecture with one of the base model classes of the library as encoder\",\n \"method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the\",\n \"provided, ``kwargs`` will be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`).\",\n \"vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens\",\n \"be automatically loaded when: - the model is a model provided by the\",\n \"it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters\",\n \"\\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ):\",\n \"performing: - During training we perform one forward pass through both the encoder\",\n \"of configuration parameters that will be used to initialize a\\\" \\\" torch.nn.LSTM model\",\n \"is provided with ``config``, ``**kwargs`` will be directly passed to the underlying model's\",\n \"+ encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of\",\n \"the base model classes of the library as encoder and (optionally) another one\",\n \"kwargs_common = { argument: value for argument, value in kwargs.items() if not argument.startswith(\\\"encoder_\\\")\",\n \"that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2:\",\n \"**kwargs): \\\"\\\"\\\" The forward pass on a seq2eq depends what we are performing:\",\n \"in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and\",\n \"from saved weights file. This option can be used if you want to\",\n \"kwargs_decoder.pop(\\\"model\\\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder\",\n \"path is slower than converting the TensorFlow checkpoint in a PyTorch model using\",\n \"kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[\",\n \"boolean, default False: Force to (re-)download the model weights and configuration files and\",\n \"Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a string with\",\n \"standard cache should not be used. force_download: (`optional`) boolean, default False: Force to\",\n \"and initialize, say, the decoder randomly by creating it beforehand as follows config\",\n \"local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found\",\n \"if the standard cache should not be used. force_download: (`optional`) boolean, default False:\",\n \"proxies: (`optional`) dict, default None: A dictionary of proxy servers to use by\",\n \"should not be used. force_download: (`optional`) boolean, default False: Force to (re-)download the\",\n \"= () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None )\",\n \"encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] #\",\n \"pretrained weight (the cross-attention will be intialized randomly if its weights are not\",\n \"if its weights are not present). It is possible to override this behavior\",\n \":class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder and decoder are\",\n \"(the \\\"License\\\"); # you may not use this file except in compliance with\",\n \"model, you need to first set it back in training mode with `model.train()`\",\n \"the save directory. - the model is loaded by suppling a local directory\",\n \"be used to update the configuration object (after it being loaded) and initiate\",\n \"set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated) To\",\n \"`decoder_`) and those # that apply to the model as whole. # We\",\n \"for the model to use instead of a state dictionary loaded from saved\",\n \"a string with the `shortcut name` of a pre-trained model to load from\",\n \"The distinction between encoder and decoder at the model level is made #\",\n \"# Unless required by applicable law or agreed to in writing, software #\",\n \"Bert2Bert \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by #\",\n \"by applicable law or agreed to in writing, software # distributed under the\",\n \"= kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for argument, value in kwargs.items() if\",\n \"perform one forward pass through the encoder, and then perform several forward passes\",\n \"'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`) boolean:\",\n \"from a pretrained configuration but load your own weights. In this case though,\",\n \"to decode a full sequence. Therefore, we skip the forward pass on the\",\n \"(optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\"\",\n \"supplied ``kwargs`` value. Remaining keys that do not correspond to any configuration attribute\",\n \"768, 'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\")) model = super(Model2LSTM, cls).from_pretrained(*args,\",\n \"one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self,\",\n \"file except in compliance with the License. # You may obtain a copy\",\n \"those # that apply to the model as whole. # We let the\",\n \"encoder' and decoder's parameters in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\"))\",\n \"= AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return\",\n \"passed to the underlying model's ``__init__`` function. You can specify kwargs sepcific for\",\n \"key of ``kwargs`` that corresponds to a configuration attribute will be used to\",\n \"an argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of\",\n \"function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration attribute will\",\n \"torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" - a dictionary of configuration\",\n \"None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the\",\n \"if an argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor``\",\n \"your own weights. In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained`\",\n \"r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where both of the encoder and decoder\",\n \"not in kwargs: raise ValueError( \\\"To load an LSTM in Encoder-Decoder model, please\",\n \"model to use instead of a state dictionary loaded from saved weights file.\",\n \"the encoder. Either: - a string with the `shortcut name` of a pre-trained\",\n \"apply to the model as whole. # We let the specific kwargs override\",\n \"Remaining dictionary of keyword arguments. Can be used to update the configuration object\",\n \"import os import torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead\",\n \"logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that\",\n \"forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass on a seq2eq depends what\",\n \"initialize the encoder and decoder # The distinction between encoder and decoder at\",\n \"OR CONDITIONS OF ANY KIND, either express or implied. # See the License\",\n \"may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #\",\n \"the encoder and decoder are of the same family. If the name of\",\n \"(prefixed by `decoder_`) and those # that apply to the model as whole.\",\n \"checkpoints. The model is set in evaluation mode by default using `model.eval()` (Dropout\",\n \"a pretrained configuration but load your own weights. In this case though, you\",\n \"decoders' embeddings together. We need for each to get down to the embedding\",\n \"and those # that apply to the model as whole. # We let\",\n \"Remaining keys that do not correspond to any configuration attribute will be passed\",\n \"and # limitations under the License. \\\"\\\"\\\" Classes to support Encoder-Decoder architectures \\\"\\\"\\\"\",\n \"function. You can specify kwargs sepcific for the encoder and decoder by prefixing\",\n \"return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2 model where\",\n \"scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the\",\n \"loaded when: - the model is a model provided by the library (loaded\",\n \"where both of the encoder and decoder are of the same family. If\",\n \"training we perform one forward pass through both the encoder and decoder; -\",\n \"\\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`),\",\n \"correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path,\",\n \"model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq model and its configuration file\",\n \"the underlying model's ``__init__`` method (we assume all relevant updates to the configuration\",\n \"by the value of the flag `is_decoder` that we need to set correctly.\",\n \"- During training we perform one forward pass through both the encoder and\",\n \"`model.eval()` (Dropout modules are deactivated) To train the model, you need to first\",\n \"is set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated)\",\n \"pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``. - a path\",\n \"for the specific language governing permissions and # limitations under the License. \\\"\\\"\\\"\",\n \"model as a whole. # We let the specific kwargs override the common\",\n \"``kwargs`` that corresponds to a configuration attribute will be used to override said\",\n \"``kwargs`` value. Remaining keys that do not correspond to any configuration attribute will\",\n \"kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class\",\n \"checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True\",\n \"library as encoder and (optionally) another one as decoder when created with the\",\n \"encoder and a decoder from one or two base classes of the library\",\n \"`shortcut name` of a pre-trained model to load from cache or download, e.g.:\",\n \"used to initialize a\\\" \\\" torch.nn.LSTM model as `decoder_config` keyword argument. \\\" \\\"\",\n \"model where both of the encoder and decoder are of the same family.\",\n \"encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args,\",\n \"randomly by creating it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config)\",\n \"to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies\",\n \"mode by default using `model.eval()` (Dropout modules are deactivated) To train the model,\",\n \"or that path to a pretrained model is specified the encoder and the\",\n \"if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is\",\n \"decoder to decode a full sequence. Therefore, we skip the forward pass on\",\n \"class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration\",\n \"= kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for argument, value\",\n \"base model classes of the library as encoder and (optionally) another one as\",\n \"be cached if the standard cache should not be used. force_download: (`optional`) boolean,\",\n \"The forward pass on a seq2eq depends what we are performing: - During\",\n \"pass on the encoder if an argument named `encoder_hidden_state` is passed to this\",\n \"case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a\",\n \"def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass on a seq2eq depends\",\n \"common ones in case of conflict. kwargs_common = { argument: value for argument,\",\n \"have already been done) - If a configuration is not provided, ``kwargs`` will\",\n \"Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you may not\",\n \"the encoder and decoder by prefixing the key with `encoder_` and `decoder_` respectively.\",\n \"same family. If the name of or that path to a pretrained model\",\n \"model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config` is provided or\",\n \"architectures \\\"\\\"\\\" from __future__ import absolute_import, division, print_function, unicode_literals import logging import os\",\n \"a Seq2Seq2 model where both of the encoder and decoder are of the\",\n \"value in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy()\",\n \"named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size,\",\n \"self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\" not in\",\n \"the configuration have already been done) - If a configuration is not provided,\",\n \"a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path\",\n \"``True`` to also return a dictionnary containing missing keys, unexpected keys and error\",\n \"different model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa:\",\n \"the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to\",\n \"is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF\",\n \"nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder`\",\n \"the XEmbedding layer for each model, but it is \\\"blocked\\\" by a model-specific\",\n \"if argument.startswith(\\\"decoder_\\\") } ) # Encode if needed (training, first prediction pass) encoder_hidden_states\",\n \"or download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing model weights\",\n \"It is possible to override this behavior and initialize, say, the decoder randomly\",\n \"whole. # We let the specific kwargs override the common ones in case\",\n \"with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed\",\n \"for argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]:\",\n \"**kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None: # We will create a randomly initilized\",\n \"as decoder if \\\"decoder_config\\\" not in kwargs: raise ValueError( \\\"To load an LSTM\",\n \"classes of the library as encoder and (optionally) another one as decoder when\",\n \"the supplied ``kwargs`` value. Remaining keys that do not correspond to any configuration\",\n \"def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod\",\n \"will create a randomly initilized LSTM model as decoder if \\\"decoder_config\\\" not in\",\n \"from one or two base classes of the library from pre-trained model checkpoints.\",\n \"that will be used to initialize a\\\" \\\" torch.nn.LSTM model as `decoder_config` keyword\",\n \"initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration attribute\",\n \"to the underlying model's ``__init__`` function. You can specify kwargs sepcific for the\",\n \"if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder =\",\n \"We save the encoder' and decoder's parameters in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory,\",\n \"GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer\",\n \"encoder, and then perform several forward passes with the encoder's hidden state through\",\n \"dict, default None: A dictionary of proxy servers to use by protocol or\",\n \"keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be\",\n \":]: value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Encode\",\n \"for each model, but it is \\\"blocked\\\" by a model-specific keyword (bert, )...\",\n \"the License for the specific language governing permissions and # limitations under the\",\n \"as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self, encoder,\",\n \"value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Encode if\",\n \"model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" - a dictionary of configuration parameters\",\n \"intialized randomly if its weights are not present). It is possible to override\",\n \"keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments.\",\n \"is currently supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return\",\n \"flag `is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if\",\n \"either: \\\" \\\" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\"\",\n \"dictionary loaded from saved weights file. This option can be used if you\",\n \"- the model is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and\",\n \"perform several forward passes with the encoder's hidden state through the decoder to\",\n \"it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate\",\n \"a\\\" \\\" torch.nn.LSTM model as `decoder_config` keyword argument. \\\" \\\" E.g. `decoder_config={'input_size': 768,\",\n \"with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a\",\n \"and decoder by prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``).\",\n \"**kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return model def save_pretrained(self,\",\n \"decoder. Either: - a string with the `shortcut name` of a pre-trained model\",\n \"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #\",\n \"of the library from pre-trained model checkpoints. The model is set in evaluation\",\n \"automatically loaded when: - the model is a model provided by the library\",\n \"will be passed to the underlying model's ``__init__`` method config: (`optional`) instance of\",\n \"correspond to any configuration attribute will be passed to the underlying model's ``__init__``\",\n \"configuration JSON file named `config.json` is found in the directory. state_dict: (`optional`) dict:\",\n \"then perform several forward passes with the encoder's hidden state through the decoder\",\n \"Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states\",\n \"- the model is a model provided by the library (loaded with the\",\n \"differently depending on whether a `config` is provided or automatically loaded: - If\",\n \"as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" - a dictionary of configuration parameters that\",\n \"a path or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In\",\n \"and decoder's parameters in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def\",\n \"encoder and decoder are of the same family. If the name of or\",\n \"E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\")) model =\",\n \"argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( {\",\n \"``shortcut-name`` string of a pretrained model), or - the model was saved using\",\n \"a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``.\",\n \"if argument.startswith(\\\"decoder_\\\") } ) # Load and initialize the encoder and decoder #\",\n \"inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings\",\n \"} ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for argument, value in kwargs.items() if\",\n \"and then perform several forward passes with the encoder's hidden state through the\",\n \"(`optional`) boolean: Set to ``True`` to also return a dictionnary containing missing keys,\",\n \"Version 2.0 (the \\\"License\\\"); # you may not use this file except in\",\n \"None) is None: # We will create a randomly initilized LSTM model as\",\n \"\\\"\\\"\\\" The forward pass on a seq2eq depends what we are performing: -\",\n \"is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder\",\n \"Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids,\",\n \"e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow index checkpoint file`\",\n \"on the encoder if an argument named `encoder_hidden_state` is passed to this function.\",\n \"each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return a dictionnary\",\n \"() # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs\",\n \") encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder is None: decoder\",\n \"0 ] # output the last layer hidden state else: encoder_outputs = ()\",\n \"cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls,\",\n \"to support Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import absolute_import, division, print_function, unicode_literals import\",\n \"a generic model class that will be instantiated as a transformer architecture with\",\n \"to load from cache or download, e.g.: ``bert-base-uncased``. - a path to a\",\n \"keyword arguments come in 3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed\",\n \"a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" - a dictionary of\",\n \"default using `model.eval()` (Dropout modules are deactivated) To train the model, you need\",\n \"will be used to override said attribute with the supplied ``kwargs`` value. Remaining\",\n \"as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found in the\",\n \"argument: value for argument, value in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\")\",\n \"# self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\"\",\n \"decoder will be initialized with the pretrained weight (the cross-attention will be intialized\",\n \"weights. In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained`\",\n \"config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self,\",\n \"sequence tokens in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of\",\n \"if kwargs.get(\\\"decoder_model\\\", None) is None: # We will create a randomly initilized LSTM\",\n \"instantiates a Seq2Seq2 model where both of the encoder and decoder are of\",\n \"though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler\",\n \"AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return model\",\n \"the model to use instead of an automatically loaded configuation. Configuration can be\",\n \"configuration attribute will be passed to the underlying model's ``__init__`` function. You can\",\n \"what we are performing: - During training we perform one forward pass through\",\n \"decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in\",\n \"(`optional`) Remaining dictionary of keyword arguments. Can be used to update the configuration\",\n \"in case of conflict. kwargs_common = { argument: value for argument, value in\",\n \"as whole. # We let the specific kwargs override the common ones in\",\n \"provided as ``config`` argument. This loading path is slower than converting the TensorFlow\",\n \"cross-attention will be intialized randomly if its weights are not present). It is\",\n \"prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs\",\n \"shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the vocabulary. kwargs:\",\n \"`AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder\",\n \"import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\"\",\n \"encoder and decoder; - During prediction, we perform one forward pass through the\",\n \"model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a string\",\n \"= encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs\",\n \"of the flag `is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\",\",\n \"that do not correspond to any configuration attribute will be passed to the\",\n \"model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory.\",\n \"initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config` is\",\n \"follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def\",\n \"will be used to initialize a\\\" \\\" torch.nn.LSTM model as `decoder_config` keyword argument.\",\n \"Seq2Seq2 model where both of the encoder and decoder are of the same\",\n \"AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class\",\n \"as ``config`` argument. This loading path is slower than converting the TensorFlow checkpoint\",\n \"tie_weights(self): \\\"\\\"\\\" Tying the encoder and decoders' embeddings together. We need for each\",\n \"class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is None: #\",\n \"e.g.: ``bert-base-uncased``. - a path to a `directory` containing model weights saved using\",\n \"self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a Seq2Seq2\",\n \"loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file\",\n \"kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for argument, value\",\n \"\\\"decoder_config\\\" not in kwargs: raise ValueError( \\\"To load an LSTM in Encoder-Decoder model,\",\n \"keyword arguments. \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific (prefixed by\",\n \"OF ANY KIND, either express or implied. # See the License for the\",\n \"the model level is made # by the value of the flag `is_decoder`\",\n \"to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder is None: encoder =\",\n \"model's ``__init__`` method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration\",\n \"\\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass on a seq2eq\",\n \"be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two\",\n \"model and its configuration file in a format such that it can be\",\n \"the specific kwargs override the common ones in case of conflict. kwargs_common =\",\n \"configuation. Configuration can be automatically loaded when: - the model is a model\",\n \"afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments will be\",\n \"encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states\",\n \"in a PyTorch model using the provided conversion scripts and loading the PyTorch\",\n \"in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids,\",\n \"the model, you need to first set it back in training mode with\",\n \":]: value for argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( {\",\n \"embeddings together. We need for each to get down to the embedding weights.\",\n \"is made # by the value of the flag `is_decoder` that we need\",\n \"argument, value in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder =\",\n \"Configuration for the model to use instead of an automatically loaded configuation. Configuration\",\n \"**kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last layer hidden state\",\n \"the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \\\"\\\"\\\" # keyword arguments\",\n \"downloaded pre-trained model configuration should be cached if the standard cache should not\",\n \"model is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration\",\n \"to True and a configuration object should be provided as ``config`` argument. This\",\n \"(`optional`) Sequence of positional arguments: All remaning positional arguments will be passed to\",\n \"the forward pass on the encoder if an argument named `encoder_hidden_state` is passed\",\n \"the decoder. Either: - a string with the `shortcut name` of a pre-trained\",\n \"from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an encoder and a\",\n \"- During prediction, we perform one forward pass through the encoder, and then\",\n \"cache or download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing model\",\n \"Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" # keyword arguments come\",\n \"return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None) is\",\n \") # Load and initialize the encoder and decoder # The distinction between\",\n \"LSTM model as decoder if \\\"decoder_config\\\" not in kwargs: raise ValueError( \\\"To load\",\n \"`config` is provided or automatically loaded: - If a configuration is provided with\",\n \"configuration object should be provided as ``config`` argument. This loading path is slower\",\n \"{ argument[len(\\\"decoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } )\",\n \"`decoder_config` keyword argument. \\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\" )\",\n \"None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder,\",\n \"used on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return\",\n \"be used if you want to create a model from a pretrained configuration\",\n \"Load and initialize the encoder and decoder # The distinction between encoder and\",\n \"or agreed to in writing, software # distributed under the License is distributed\",\n \"torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module):\",\n \"the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder =\",\n \"encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None\",\n \"absolute_import, division, print_function, unicode_literals import logging import os import torch from torch import\",\n \"decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model\",\n \"weights and configuration files and override the cached versions if they exists. proxies:\",\n \"- RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model, but it\",\n \":func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path to\",\n \"will be directly passed to the underlying model's ``__init__`` method (we assume all\",\n \"name` of a pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``.\",\n \"prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids,\",\n \"under the Apache License, Version 2.0 (the \\\"License\\\"); # you may not use\",\n \"skip the forward pass on the encoder if an argument named `encoder_hidden_state` is\",\n \"(`optional`) boolean, default False: Force to (re-)download the model weights and configuration files\",\n \"model as `decoder_config` keyword argument. \\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers':\",\n \"During training we perform one forward pass through both the encoder and decoder;\",\n \"format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder'\",\n \"of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the vocabulary.\",\n \"if \\\"decoder_config\\\" not in kwargs: raise ValueError( \\\"To load an LSTM in Encoder-Decoder\",\n \"underlying model's ``__init__`` method config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`:\",\n \"License. # You may obtain a copy of the License at # #\",\n \"index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to\",\n \"kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Encode if needed (training, first prediction pass)\",\n \"string of a pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained`\",\n \"the standard cache should not be used. force_download: (`optional`) boolean, default False: Force\",\n \"a Seq2Seq model and its configuration file in a format such that it\",\n \"in which a downloaded pre-trained model configuration should be cached if the standard\",\n \"Behave differently depending on whether a `config` is provided or automatically loaded: -\",\n \"encoder and (optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class\",\n \"of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable\",\n \"Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens\",\n \"arguments: All remaning positional arguments will be passed to the underlying model's ``__init__``\",\n \"A dictionary of proxy servers to use by protocol or endpoint, e.g.: {'http':\",\n \"support Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import absolute_import, division, print_function, unicode_literals import logging\",\n \"During prediction, we perform one forward pass through the encoder, and then perform\",\n \"= PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" # keyword arguments come in 3\",\n \"together. We need for each to get down to the embedding weights. However\",\n \"encoder's hidden state through the decoder to decode a full sequence. Therefore, we\",\n \"not in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise\",\n \"model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder):\",\n \"with the pretrained weight (the cross-attention will be intialized randomly if its weights\",\n \"XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of\",\n \"License, Version 2.0 (the \\\"License\\\"); # you may not use this file except\",\n \"class that will be instantiated as a transformer architecture with one of the\",\n \"is possible to override this behavior and initialize, say, the decoder randomly by\",\n \"# initialize Bert2Bert \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific (prefixed\",\n \"BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM:\",\n \") return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if kwargs.get(\\\"decoder_model\\\", None)\",\n \"kwargs: (`optional`) Remaining dictionary of keyword arguments. Can be used to update the\",\n \"but it is \\\"blocked\\\" by a model-specific keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder,\",\n \"However the different model classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings\",\n \"of conflict. kwargs_common = { argument: value for argument, value in kwargs.items() if\",\n \"is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output\",\n \"def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the\",\n \"(`optional`) Remaining dictionary of keyword arguments. \\\"\\\"\\\" # keyword arguments come in 3\",\n \"logging import os import torch from torch import nn from .modeling_auto import AutoModel,\",\n \"encoder and decoder # The distinction between encoder and decoder at the model\",\n \"both the encoder and decoder; - During prediction, we perform one forward pass\",\n \"and decoders' embeddings together. We need for each to get down to the\",\n \"dictionary of keyword arguments. Can be used to update the configuration object (after\",\n \"underlying model's ``__init__`` method (we assume all relevant updates to the configuration have\",\n \"raise ValueError(\\\"Only the Bert model is currently supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path,\",\n \"be intialized randomly if its weights are not present). It is possible to\",\n \"of the base model classes of the library as encoder and (optionally) another\",\n \"decoder by prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The\",\n \"(the cross-attention will be intialized randomly if its weights are not present). It\",\n \"or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each\",\n \"copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by\",\n \"that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's\",\n \"when: - the model is a model provided by the library (loaded with\",\n \"model to load from cache or download, e.g.: ``bert-base-uncased``. - a path to\",\n \"to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a\",\n \"in the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input\",\n \"model to use instead of an automatically loaded configuation. Configuration can be automatically\",\n \"checkpoint in a PyTorch model using the provided conversion scripts and loading the\",\n \"the specific language governing permissions and # limitations under the License. \\\"\\\"\\\" Classes\",\n \".modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a\",\n \"(`optional`) string: Path to a directory in which a downloaded pre-trained model configuration\",\n \"updates to the configuration have already been done) - If a configuration is\",\n \"a model from a pretrained configuration but load your own weights. In this\",\n \"or automatically loaded: - If a configuration is provided with ``config``, ``**kwargs`` will\",\n \"configuration have already been done) - If a configuration is not provided, ``kwargs``\",\n \"both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\"\",\n \"AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\", None) if\",\n \"state else: encoder_outputs = () # Decode kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get(\",\n \"to create a model from a pretrained configuration but load your own weights.\",\n \"two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs):\",\n \"embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the\",\n \"its configuration file in a format such that it can be loaded using\",\n \"and its configuration file in a format such that it can be loaded\",\n \"encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in\",\n \"the model is a model provided by the library (loaded with the ``shortcut-name``\",\n \"using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path\",\n \"be used to override said attribute with the supplied ``kwargs`` value. Remaining keys\",\n \"or implied. # See the License for the specific language governing permissions and\",\n \"Can be used to update the configuration object (after it being loaded) and\",\n \":func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path to a directory\",\n \"and a decoder from one or two base classes of the library from\",\n \"a state dictionary loaded from saved weights file. This option can be used\",\n \"kwargs_decoder[\\\"encoder_hidden_states\\\"] = encoder_hidden_states kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder)\",\n \"\\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\")) model\",\n \"classes are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings -\",\n \"of a state dictionary loaded from saved weights file. This option can be\",\n \"respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders and\",\n \"forward pass through the encoder, and then perform several forward passes with the\",\n \"and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config`\",\n \"weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a\",\n \"division, print_function, unicode_literals import logging import os import torch from torch import nn\",\n \"of the same family. If the name of or that path to a\",\n \"or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling\",\n \"and decoder are of the same family. If the name of or that\",\n \"behavior and initialize, say, the decoder randomly by creating it beforehand as follows\",\n \"a configuration attribute will be used to override said attribute with the supplied\",\n \"Save a Seq2Seq model and its configuration file in a format such that\",\n \"model level is made # by the value of the flag `is_decoder` that\",\n \"model checkpoints. The model is set in evaluation mode by default using `model.eval()`\",\n \"path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. -\",\n \"'foo.bar:4012'}. The proxies are used on each request. output_loading_info: (`optional`) boolean: Set to\",\n \"in kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for argument,\",\n \"the model as a whole. # We let the specific kwargs override the\",\n \"a dictionary of configuration parameters that will be used to initialize a\\\" \\\"\",\n \"Inc. team. # # Licensed under the Apache License, Version 2.0 (the \\\"License\\\");\",\n \"if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True\",\n \"the License. \\\"\\\"\\\" Classes to support Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import absolute_import,\",\n \"governing permissions and # limitations under the License. \\\"\\\"\\\" Classes to support Encoder-Decoder\",\n \") decoder.config.is_decoder = True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory):\",\n \"using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow index\",\n \":]: value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Load\",\n \"- a string with the `shortcut name` of a pre-trained model to load\",\n \"the ``shortcut-name`` string of a pretrained model), or - the model was saved\",\n \"use this file except in compliance with the License. # You may obtain\",\n \":func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow index checkpoint\",\n \"perform one forward pass through both the encoder and decoder; - During prediction,\",\n \"with the ``shortcut-name`` string of a pretrained model), or - the model was\",\n \"with the encoder's hidden state through the decoder to decode a full sequence.\",\n \"``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders and decoders. Examples::\",\n \"kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") }\",\n \"encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder\",\n \"if you want to create a model from a pretrained configuration but load\",\n \"3 flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those\",\n \"can be used if you want to create a model from a pretrained\",\n \"`./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True and a configuration\",\n \"to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds\",\n \"should be set to True and a configuration object should be provided as\",\n \"cached if the standard cache should not be used. force_download: (`optional`) boolean, default\",\n \"pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only the\",\n \"they exists. proxies: (`optional`) dict, default None: A dictionary of proxy servers to\",\n \"provided or automatically loaded: - If a configuration is provided with ``config``, ``**kwargs``\",\n \"override the common ones in case of conflict. kwargs_common = { argument: value\",\n \"BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs):\",\n \"argument.startswith(\\\"decoder_\\\") } ) # Encode if needed (training, first prediction pass) encoder_hidden_states =\",\n \"decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls,\",\n \"of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the vocabulary.\",\n \"- BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte -\",\n \"by prefixing the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining\",\n \"url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf``\",\n \"None: # We will create a randomly initilized LSTM model as decoder if\",\n \"an automatically loaded configuation. Configuration can be automatically loaded when: - the model\",\n \"a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is\",\n \"afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: - a string with\",\n \"We let the specific kwargs override the common ones in case of conflict.\",\n \"configuration file in a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained`\",\n \"by `decoder_`) and those # that apply to the model as a whole.\",\n \"an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either\",\n \"to a directory in which a downloaded pre-trained model configuration should be cached\",\n \"that path to a pretrained model is specified the encoder and the decoder\",\n \"def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an encoder and\",\n \"full sequence. Therefore, we skip the forward pass on the encoder if an\",\n \"for argument, value in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder\",\n \"a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``.\",\n \"request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return a dictionnary containing\",\n \"\\\"To load an LSTM in Encoder-Decoder model, please supply either: \\\" \\\" -\",\n \"None: A dictionary of proxy servers to use by protocol or endpoint, e.g.:\",\n \"in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only\",\n \"a model provided by the library (loaded with the ``shortcut-name`` string of a\",\n \"hidden state through the decoder to decode a full sequence. Therefore, we skip\",\n \"None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\"\",\n \"# distributed under the License is distributed on an \\\"AS IS\\\" BASIS, #\",\n \"conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate\",\n \"as a transformer architecture with one of the base model classes of the\",\n \"argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value\",\n \"that will be instantiated as a transformer architecture with one of the base\",\n \"decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" # keyword arguments\",\n \"servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The\",\n \"kwargs_encoder.pop(\\\"model\\\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder )\",\n \"family. If the name of or that path to a pretrained model is\",\n \"False: Force to (re-)download the model weights and configuration files and override the\",\n \"# We will create a randomly initilized LSTM model as decoder if \\\"decoder_config\\\"\",\n \"model is a model provided by the library (loaded with the ``shortcut-name`` string\",\n \"pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\" not in pretrained_model_name_or_path\",\n \"evaluation mode by default using `model.eval()` (Dropout modules are deactivated) To train the\",\n \"all relevant updates to the configuration have already been done) - If a\",\n \"and is reloaded by suppling the save directory. - the model is loaded\",\n \"\\\" - a dictionary of configuration parameters that will be used to initialize\",\n \"embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings\",\n \"initiate the encoder. Either: - a string with the `shortcut name` of a\",\n \"__init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the encoder\",\n \"with the License. # You may obtain a copy of the License at\",\n \"``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found in the directory.\",\n \"arguments will be passed to the underlying model's ``__init__`` method config: (`optional`) instance\",\n \"kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\")\",\n \"train the model, you need to first set it back in training mode\",\n \"not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update(\",\n \"wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for\",\n \"state through the decoder to decode a full sequence. Therefore, we skip the\",\n \"embedding weights. However the different model classes are inconsistent to that respect: -\",\n \"is not a simpler option. cache_dir: (`optional`) string: Path to a directory in\",\n \"= True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save\",\n \"is reloaded by suppling the save directory. - the model is loaded by\",\n \"encoder and decoder by prefixing the key with `encoder_` and `decoder_` respectively. (e.g.\",\n \"argument of the XEmbedding layer for each model, but it is \\\"blocked\\\" by\",\n \"a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be\",\n \"will be intialized randomly if its weights are not present). It is possible\",\n \"law or agreed to in writing, software # distributed under the License is\",\n \"model as whole. # We let the specific kwargs override the common ones\",\n \"and those # that apply to the model as a whole. # We\",\n \"shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the vocabulary. decoder_input_ids:\",\n \"the model is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a\",\n \"needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None:\",\n \"argument[len(\\\"decoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) #\",\n \"`is_decoder` that we need to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder\",\n \"pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path\",\n \"dictionary of configuration parameters that will be used to initialize a\\\" \\\" torch.nn.LSTM\",\n \"or two base classes of the library from pre-trained model checkpoints. The model\",\n \"option. cache_dir: (`optional`) string: Path to a directory in which a downloaded pre-trained\",\n \"a model-specific keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls,\",\n \"containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url\",\n \"flavors: encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those #\",\n \"than converting the TensorFlow checkpoint in a PyTorch model using the provided conversion\",\n \"decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model,\",\n \"loaded configuation. Configuration can be automatically loaded when: - the model is a\",\n \"in compliance with the License. # You may obtain a copy of the\",\n \"is provided or automatically loaded: - If a configuration is provided with ``config``,\",\n \"the encoder and decoders' embeddings together. We need for each to get down\",\n \"License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or\",\n \"# coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # Licensed under\",\n \"said attribute with the supplied ``kwargs`` value. Remaining keys that do not correspond\",\n \"and the decoder will be initialized with the pretrained weight (the cross-attention will\",\n \"= cls(encoder, decoder) return model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq model\",\n \"each to get down to the embedding weights. However the different model classes\",\n \"BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\",\n \"download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing model weights saved\",\n \"a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required\",\n \"# `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply to the\",\n \"string: Path to a directory in which a downloaded pre-trained model configuration should\",\n \"raise ValueError( \\\"To load an LSTM in Encoder-Decoder model, please supply either: \\\"\",\n \"we are performing: - During training we perform one forward pass through both\",\n \"by `decoder_`) and those # that apply to the model as whole. #\",\n \"the vocabulary. decoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence\",\n \"the model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config` is provided\",\n \"creating it beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model =\",\n \"= BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args,\",\n \"and initialize the encoder and decoder # The distinction between encoder and decoder\",\n \"cls(encoder, decoder) return model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq model and\",\n \"``config``, ``**kwargs`` will be directly passed to the underlying model's ``__init__`` method (we\",\n \"initialized with the pretrained weight (the cross-attention will be intialized randomly if its\",\n \"file named `config.json` is found in the directory. state_dict: (`optional`) dict: an optional\",\n \"the TensorFlow checkpoint in a PyTorch model using the provided conversion scripts and\",\n \"down to the embedding weights. However the different model classes are inconsistent to\",\n \"with the supplied ``kwargs`` value. Remaining keys that do not correspond to any\",\n \"(Dropout modules are deactivated) To train the model, you need to first set\",\n \"first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs``\",\n \"- If a configuration is not provided, ``kwargs`` will be first passed to\",\n \"will be passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased')\",\n \"passed to the underlying model's ``__init__`` method config: (`optional`) instance of a class\",\n \"model as decoder if \\\"decoder_config\\\" not in kwargs: raise ValueError( \\\"To load an\",\n \"forward pass through both the encoder and decoder; - During prediction, we perform\",\n \"the encoder' and decoder's parameters in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory,\",\n \"super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the encoder and decoders' embeddings\",\n \"# Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if\",\n \"decoder are of the same family. If the name of or that path\",\n \"set to True and a configuration object should be provided as ``config`` argument.\",\n \"config: (`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model\",\n \"def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\"\",\n \"configuration is not provided, ``kwargs`` will be first passed to the configuration class\",\n \"kwargs_common.copy() kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for argument, value in\",\n \"key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be\",\n \"will be passed to the underlying model's ``__init__`` function. You can specify kwargs\",\n \"by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used\",\n \"arguments. Can be used to update the configuration object (after it being loaded)\",\n \"dictionary of keyword arguments. \\\"\\\"\\\" # keyword arguments come in 3 flavors: encoder-specific\",\n \"as `decoder_config` keyword argument. \\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\"\",\n \"can be automatically loaded when: - the model is a model provided by\",\n \"a directory in which a downloaded pre-trained model configuration should be cached if\",\n \"one forward pass through both the encoder and decoder; - During prediction, we\",\n \"model class that will be instantiated as a transformer architecture with one of\",\n \"be passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') #\",\n \"encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder = False\",\n \"do not correspond to any configuration attribute will be passed to the underlying\",\n \"is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON\",\n \"\\\" \\\" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" -\",\n \"(`optional`) dict: an optional state dictionnary for the model to use instead of\",\n \"through the decoder to decode a full sequence. Therefore, we skip the forward\",\n \"`decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" - a dictionary of configuration parameters that will\",\n \"pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert model is currently supported.\\\") model = super(Model2Model,\",\n \"distributed under the License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT\",\n \"\\\"\\\"\\\" Tying the encoder and decoders' embeddings together. We need for each to\",\n \"super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def\",\n \"of a pretrained model), or - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and\",\n \"(re-)download the model weights and configuration files and override the cached versions if\",\n \"to initiate the encoder. Either: - a string with the `shortcut name` of\",\n \"self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None,\",\n \"= kwargs_encoder.pop(\\\"model\\\", None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder\",\n \"classes of the library from pre-trained model checkpoints. The model is set in\",\n \"by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply to\",\n \"made # by the value of the flag `is_decoder` that we need to\",\n \"The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0\",\n \"loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in two separate\",\n \"of the library as encoder and (optionally) another one as decoder when created\",\n \"class method. \\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder\",\n \"you want to create a model from a pretrained configuration but load your\",\n \"present). It is possible to override this behavior and initialize, say, the decoder\",\n \"attribute will be used to override said attribute with the supplied ``kwargs`` value.\",\n \"weights file. This option can be used if you want to create a\",\n \"encoder if an argument named `encoder_hidden_state` is passed to this function. Params: encoder_input_ids:\",\n \"this file except in compliance with the License. # You may obtain a\",\n \"`decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders\",\n \"is found in the directory. state_dict: (`optional`) dict: an optional state dictionnary for\",\n \"} ) # Encode if needed (training, first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\",\",\n \"be directly passed to the underlying model's ``__init__`` method (we assume all relevant\",\n \"- If a configuration is provided with ``config``, ``**kwargs`` will be directly passed\",\n \"dict: an optional state dictionnary for the model to use instead of a\",\n \"state dictionnary for the model to use instead of a state dictionary loaded\",\n \"it is \\\"blocked\\\" by a model-specific keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder)\",\n \"versions if they exists. proxies: (`optional`) dict, default None: A dictionary of proxy\",\n \"slower than converting the TensorFlow checkpoint in a PyTorch model using the provided\",\n \"the directory. state_dict: (`optional`) dict: an optional state dictionnary for the model to\",\n \"the decoder randomly by creating it beforehand as follows config = BertConfig.from_pretrained() decoder\",\n \"remaning positional arguments will be passed to the underlying model's ``__init__`` method config:\",\n \"Path to a directory in which a downloaded pre-trained model configuration should be\",\n \"dictionary of proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128',\",\n \"# Load and initialize the encoder and decoder # The distinction between encoder\",\n \"derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of an automatically\",\n \"save directory. - the model is loaded by suppling a local directory as\",\n \"from .modeling_auto import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is\",\n \"{ argument[len(\\\"encoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\") } )\",\n \"import torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger =\",\n \"= self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model` instantiates a\",\n \"e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request. output_loading_info:\",\n \"respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte\",\n \"``from_tf`` should be set to True and a configuration object should be provided\",\n \"missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword\",\n \"configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a\",\n \"of the XEmbedding layer for each model, but it is \\\"blocked\\\" by a\",\n \"configuration should be cached if the standard cache should not be used. force_download:\",\n \"distinction between encoder and decoder at the model level is made # by\",\n \"self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the encoder and decoders' embeddings together.\",\n \"``./my_model_directory/decoder``. - a path or url to a `tensorflow index checkpoint file` (e.g.\",\n \"decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass on a seq2eq depends what we are\",\n \"in pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert model is\",\n \"in kwargs.items() if not argument.startswith(\\\"encoder_\\\") and not argument.startswith(\\\"decoder_\\\") } kwargs_decoder = kwargs_common.copy() kwargs_encoder\",\n \"the `shortcut name` of a pre-trained model to load from cache or download,\",\n \"and override the cached versions if they exists. proxies: (`optional`) dict, default None:\",\n \"under the License. \\\"\\\"\\\" Classes to support Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import\",\n \"License. \\\"\\\"\\\" Classes to support Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import absolute_import, division,\",\n \"a PyTorch model using the provided conversion scripts and loading the PyTorch model\",\n \"passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that\",\n \"# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to\",\n \"= decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates\",\n \"a whole. # We let the specific kwargs override the common ones in\",\n \"a configuration is not provided, ``kwargs`` will be first passed to the configuration\",\n \"used to update the configuration object (after it being loaded) and initiate the\",\n \"the PyTorch model afterwards. decoder_pretrained_model_name_or_path: information necessary to initiate the decoder. Either: -\",\n \"will be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key\",\n \"self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward pass on a\",\n \"JSON file named `config.json` is found in the directory. state_dict: (`optional`) dict: an\",\n \"pretrained_model_name_or_path or \\\"distilbert\\\" in pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert model is currently\",\n \":func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to a `tensorflow index checkpoint\",\n \"beforehand as follows config = BertConfig.from_pretrained() decoder = BertForMaskedLM(config) model = Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder)\",\n \"`decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\")) model = super(Model2LSTM,\",\n \"for argument, value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Load and initialize\",\n \"saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow\",\n \"automatically loaded: - If a configuration is provided with ``config``, ``**kwargs`` will be\",\n \"in pretrained_model_name_or_path ): raise ValueError(\\\"Only the Bert model is currently supported.\\\") model =\",\n \"and a configuration JSON file named `config.json` is found in the directory. state_dict:\",\n \"required by applicable law or agreed to in writing, software # distributed under\",\n \"logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be\",\n \"save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq model and its configuration file in a\",\n \"set it back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to\",\n \"model_args: (`optional`) Sequence of positional arguments: All remaning positional arguments will be passed\",\n \"- a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" - a dictionary\",\n \"# by the value of the flag `is_decoder` that we need to set\",\n \"separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\"\",\n \"True and a configuration object should be provided as ``config`` argument. This loading\",\n \"decoder if \\\"decoder_config\\\" not in kwargs: raise ValueError( \\\"To load an LSTM in\",\n \"the encoder and the decoder will be initialized with the pretrained weight (the\",\n \"import AutoModel, AutoModelWithLMHead logger = logging.getLogger(__name__) class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic\",\n \"model classes of the library as encoder and (optionally) another one as decoder\",\n \"as encoder and (optionally) another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)`\",\n \"the model weights and configuration files and override the cached versions if they\",\n \"e.g.: ``./my_model_directory/encoder``. - a path or url to a `tensorflow index checkpoint file`\",\n \"You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #\",\n \"and decoder at the model level is made # by the value of\",\n \"conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional\",\n \"\\\" - a torch.nn.LSTM model as `decoder_model` parameter (`decoder_model=lstm_model`), or\\\" \\\" - a\",\n \"should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir:\",\n \"exists. proxies: (`optional`) dict, default None: A dictionary of proxy servers to use\",\n \"kwargs will be passed to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased',\",\n \"is not provided, ``kwargs`` will be first passed to the configuration class initialization\",\n \"\\\"\\\"\\\" from __future__ import absolute_import, division, print_function, unicode_literals import logging import os import\",\n \"kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\") }\",\n \"BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding layer for each model,\",\n \"function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence\",\n \"Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import absolute_import, division, print_function, unicode_literals import logging import\",\n \"= kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states =\",\n \"method (we assume all relevant updates to the configuration have already been done)\",\n \"proxies are used on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to\",\n \"'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\")) model = super(Model2LSTM, cls).from_pretrained(*args, **kwargs) return model\",\n \"encoder. Either: - a string with the `shortcut name` of a pre-trained model\",\n \"kwargs_encoder = kwargs_common.copy() kwargs_encoder.update( { argument[len(\\\"encoder_\\\") :]: value for argument, value in kwargs.items()\",\n \"is passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices\",\n \"endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request.\",\n \"this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input\",\n \"on each request. output_loading_info: (`optional`) boolean: Set to ``True`` to also return a\",\n \"force_download: (`optional`) boolean, default False: Force to (re-)download the model weights and configuration\",\n \"in the directory. state_dict: (`optional`) dict: an optional state dictionnary for the model\",\n \"pre-trained model checkpoints. The model is set in evaluation mode by default using\",\n \"from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): if ( \\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\" in\",\n \"in evaluation mode by default using `model.eval()` (Dropout modules are deactivated) To train\",\n \"loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether a\",\n \"# you may not use this file except in compliance with the License.\",\n \"library from pre-trained model checkpoints. The model is set in evaluation mode by\",\n \"those # that apply to the model as a whole. # We let\",\n \"that apply to the model as a whole. # We let the specific\",\n \"Model2Model.from_pretrained('bert-base-uncased', decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self):\",\n \"converting the TensorFlow checkpoint in a PyTorch model using the provided conversion scripts\",\n \"using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. - the model\",\n \"decoder) return model def save_pretrained(self, save_directory): \\\"\\\"\\\" Save a Seq2Seq model and its\",\n \"encoder and the decoder will be initialized with the pretrained weight (the cross-attention\",\n \") decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder): r\\\"\\\"\\\" :class:`~transformers.Model2Model`\",\n \"and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. cache_dir: (`optional`) string: Path to a\",\n \"from cache or download, e.g.: ``bert-base-uncased``. - a path to a `directory` containing\",\n \"output_loading_info: (`optional`) boolean: Set to ``True`` to also return a dictionnary containing missing\",\n \"Remaining dictionary of keyword arguments. \\\"\\\"\\\" # keyword arguments come in 3 flavors:\",\n \"value in kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for\",\n \"model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path or url to\",\n \"value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Encode if needed (training, first\",\n \"for each to get down to the embedding weights. However the different model\",\n \"(we assume all relevant updates to the configuration have already been done) -\",\n \"to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/encoder``. - a\",\n \"to the underlying model's ``__init__`` method config: (`optional`) instance of a class derived\",\n \"decoder.config.is_decoder = True model = cls(encoder, decoder) return model def save_pretrained(self, save_directory): \\\"\\\"\\\"\",\n \"should be provided as ``config`` argument. This loading path is slower than converting\",\n \"back in training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the\",\n \"whether a `config` is provided or automatically loaded: - If a configuration is\",\n \"model is currently supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs )\",\n \"for the encoder and decoder by prefixing the key with `encoder_` and `decoder_`\",\n \"\\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids, decoder_input_ids, **kwargs): \\\"\\\"\\\" The forward\",\n \"License for the specific language governing permissions and # limitations under the License.\",\n \"the encoder's hidden state through the decoder to decode a full sequence. Therefore,\",\n \"file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True and\",\n \"(e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to both encoders and decoders.\",\n \"# We let the specific kwargs override the common ones in case of\",\n \"can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the encoder' and decoder's parameters in\",\n \"\\\"License\\\"); # you may not use this file except in compliance with the\",\n \"obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless\",\n \"to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings -\",\n \"768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] = torch.nn.LSTM(kwargs.pop(\\\"decoder_config\\\")) model = super(Model2LSTM, cls).from_pretrained(*args, **kwargs) return\",\n \"to the model as whole. # We let the specific kwargs override the\",\n \"to initialize a\\\" \\\" torch.nn.LSTM model as `decoder_config` keyword argument. \\\" \\\" E.g.\",\n \"decoder randomly by creating it beforehand as follows config = BertConfig.from_pretrained() decoder =\",\n \"team. # # Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); #\",\n \"Indices of decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary\",\n \"If a configuration is provided with ``config``, ``**kwargs`` will be directly passed to\",\n \"http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing,\",\n \"saved weights file. This option can be used if you want to create\",\n \"in writing, software # distributed under the License is distributed on an \\\"AS\",\n \"used if you want to create a model from a pretrained configuration but\",\n \"\\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying\",\n \"you need to first set it back in training mode with `model.train()` Params:\",\n \"base classes of the library from pre-trained model checkpoints. The model is set\",\n \"import absolute_import, division, print_function, unicode_literals import logging import os import torch from torch\",\n \"argument. \\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"] =\",\n \"decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an encoder and a decoder from one\",\n \"`encoder_`), decoder-specific (prefixed by `decoder_`) and those # that apply to the model\",\n \"the Bert model is currently supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args,\",\n \"kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Load and initialize the encoder and decoder\",\n \"- XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument\",\n \"unicode_literals import logging import os import torch from torch import nn from .modeling_auto\",\n \"\\\"blocked\\\" by a model-specific keyword (bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod\",\n \"be provided as ``config`` argument. This loading path is slower than converting the\",\n \"to the model as a whole. # We let the specific kwargs override\",\n \"we perform one forward pass through both the encoder and decoder; - During\",\n \"value for argument, value in kwargs.items() if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\")\",\n \"decode a full sequence. Therefore, we skip the forward pass on the encoder\",\n \"decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\" Instantiates an\",\n \"file in a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We\",\n \"None) if encoder_hidden_states is None: encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0\",\n \"configuration object (after it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave\",\n \"decoder input sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword\",\n \"(`optional`) instance of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to\",\n \"generic model class that will be instantiated as a transformer architecture with one\",\n \"loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments: All remaning\",\n \"**kwargs): if ( \\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\"\",\n \"`encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will be passed to\",\n \"limitations under the License. \\\"\\\"\\\" Classes to support Encoder-Decoder architectures \\\"\\\"\\\" from __future__\",\n \"is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model =\",\n \"as a whole. # We let the specific kwargs override the common ones\",\n \"the model as whole. # We let the specific kwargs override the common\",\n \"underlying model's ``__init__`` function. You can specify kwargs sepcific for the encoder and\",\n \"- GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings - RobertaForMaskedLM: roberta.embeddings.word_embeddings argument of the XEmbedding\",\n \"\\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs class Model2Model(PreTrainedEncoderDecoder):\",\n \"2.0 (the \\\"License\\\"); # you may not use this file except in compliance\",\n \"depends what we are performing: - During training we perform one forward pass\",\n \"initiate the decoder. Either: - a string with the `shortcut name` of a\",\n \"Seq2Seq model and its configuration file in a format such that it can\",\n \"The model is set in evaluation mode by default using `model.eval()` (Dropout modules\",\n \"WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the\",\n \"a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead of\",\n \"encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" #\",\n \"mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: -\",\n \"information necessary to initiate the decoder. Either: - a string with the `shortcut\",\n \"kwargs sepcific for the encoder and decoder by prefixing the key with `encoder_`\",\n \"# # Unless required by applicable law or agreed to in writing, software\",\n \"(bert, )... \\\"\\\"\\\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs):\",\n \"express or implied. # See the License for the specific language governing permissions\",\n \"value. Remaining keys that do not correspond to any configuration attribute will be\",\n \"``bert-base-uncased``. - a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`,\",\n \"through the encoder, and then perform several forward passes with the encoder's hidden\",\n \"ValueError(\\\"Only the Bert model is currently supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path,\",\n \"corresponds to a configuration attribute will be used to override said attribute with\",\n \"a format such that it can be loaded using `:func:`~transformers.PreTrainedEncoderDecoder.from_pretrained` We save the\",\n \"either express or implied. # See the License for the specific language governing\",\n \"Configuration can be automatically loaded when: - the model is a model provided\",\n \"r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated as a\",\n \"use instead of an automatically loaded configuation. Configuration can be automatically loaded when:\",\n \"# output the last layer hidden state else: encoder_outputs = () # Decode\",\n \"``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of encoder input sequence tokens in the\",\n \"supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs ) return model class\",\n \"transformer architecture with one of the base model classes of the library as\",\n \"*args, **kwargs ) return model class Model2LSTM(PreTrainedEncoderDecoder): @classmethod def from_pretrained(cls, *args, **kwargs): if\",\n \"with ``config``, ``**kwargs`` will be directly passed to the underlying model's ``__init__`` method\",\n \"weights. However the different model classes are inconsistent to that respect: - BertModel:\",\n \"a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/decoder``. - a path\",\n \"name of or that path to a pretrained model is specified the encoder\",\n \"model is set in evaluation mode by default using `model.eval()` (Dropout modules are\",\n \"the License. # You may obtain a copy of the License at #\",\n \"unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary of keyword arguments. Can\",\n \"import logging import os import torch from torch import nn from .modeling_auto import\",\n \"in Encoder-Decoder model, please supply either: \\\" \\\" - a torch.nn.LSTM model as\",\n \"scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of positional arguments:\",\n \"a dictionnary containing missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining\",\n \"Bert model is currently supported.\\\") model = super(Model2Model, cls).from_pretrained( encoder_pretrained_model_name_or_path=pretrained_model_name_or_path, decoder_pretrained_model_name_or_path=pretrained_model_name_or_path, *args, **kwargs\",\n \"encoder_outputs = self.encoder(encoder_input_ids, **kwargs_encoder) encoder_hidden_states = encoder_outputs[ 0 ] # output the last\",\n \"and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert \\\"\\\"\\\" # keyword\",\n \"be passed to the underlying model's ``__init__`` method config: (`optional`) instance of a\",\n \"this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not\",\n \"that apply to the model as whole. # We let the specific kwargs\",\n \"an encoder and a decoder from one or two base classes of the\",\n \"a `config` is provided or automatically loaded: - If a configuration is provided\",\n \"is specified the encoder and the decoder will be initialized with the pretrained\",\n \"in kwargs: raise ValueError( \\\"To load an LSTM in Encoder-Decoder model, please supply\",\n \"are inconsistent to that respect: - BertModel: embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel:\",\n \"``config`` argument. This loading path is slower than converting the TensorFlow checkpoint in\",\n \"(loaded with the ``shortcut-name`` string of a pretrained model), or - the model\",\n \"depending on whether a `config` is provided or automatically loaded: - If a\",\n \"= kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs + encoder_outputs\",\n \"\\\"\\\"\\\" Classes to support Encoder-Decoder architectures \\\"\\\"\\\" from __future__ import absolute_import, division, print_function,\",\n \"object (after it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently\",\n \"self.decoder = decoder @classmethod def from_pretrained( cls, encoder_pretrained_model_name_or_path=None, decoder_pretrained_model_name_or_path=None, *model_args, **kwargs ): r\\\"\\\"\\\"\",\n \"passed to this function. Params: encoder_input_ids: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of\",\n \"by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named\",\n \"another one as decoder when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def\",\n \"kwargs_decoder[\\\"encoder_attention_mask\\\"] = kwargs_encoder.get( \\\"attention_mask\\\", None ) decoder_outputs = self.decoder(decoder_input_ids, **kwargs_decoder) return decoder_outputs +\",\n \"# # Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you\",\n \"saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. - the\",\n \"The proxies are used on each request. output_loading_info: (`optional`) boolean: Set to ``True``\",\n \"decoder # The distinction between encoder and decoder at the model level is\",\n \"pretrained model is specified the encoder and the decoder will be initialized with\",\n \"being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether\",\n \"class PreTrainedEncoderDecoder(nn.Module): r\\\"\\\"\\\" :class:`~transformers.PreTrainedEncoderDecoder` is a generic model class that will be instantiated\",\n \"positional arguments: All remaning positional arguments will be passed to the underlying model's\",\n \"will be initialized with the pretrained weight (the cross-attention will be intialized randomly\",\n \"of a class derived from :class:`~transformers.PretrainedConfig`: Configuration for the model to use instead\",\n \"encoder and decoders' embeddings together. We need for each to get down to\",\n \"model using the provided conversion scripts and loading the PyTorch model afterwards. decoder_pretrained_model_name_or_path:\",\n \"self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the encoder and decoders' embeddings together. We need\",\n \"layer for each model, but it is \\\"blocked\\\" by a model-specific keyword (bert,\",\n \"``torch.LongTensor`` of shape ``(batch_size, sequence_length)`` Indices of decoder input sequence tokens in the\",\n \"decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path, **kwargs_decoder\",\n \"None) if encoder is None: encoder = AutoModel.from_pretrained( encoder_pretrained_model_name_or_path, *model_args, **kwargs_encoder ) encoder.config.is_decoder\",\n \"keyword argument. \\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768, 'num_layers': 2}`\\\" ) kwargs[\\\"decoder_model\\\"]\",\n \"model provided by the library (loaded with the ``shortcut-name`` string of a pretrained\",\n \"argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for argument, value in kwargs.items()\",\n \"sequence tokens in the vocabulary. kwargs: (`optional`) Remaining dictionary of keyword arguments. \\\"\\\"\\\"\",\n \"attribute will be passed to the underlying model's ``__init__`` function. You can specify\",\n \"value in kwargs.items() if argument.startswith(\\\"decoder_\\\") } ) # Load and initialize the encoder\",\n \"at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed\",\n \"parameters in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\")) self.decoder.save_pretrained(os.path.join(save_directory, \\\"decoder\\\")) def forward(self, encoder_input_ids,\",\n \"the library (loaded with the ``shortcut-name`` string of a pretrained model), or -\",\n \"using the provided conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`)\",\n \"dictionnary containing missing keys, unexpected keys and error messages. kwargs: (`optional`) Remaining dictionary\",\n \"path to a pretrained model is specified the encoder and the decoder will\",\n \"used. force_download: (`optional`) boolean, default False: Force to (re-)download the model weights and\",\n \"`model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either: - a string\",\n \"kwargs: raise ValueError( \\\"To load an LSTM in Encoder-Decoder model, please supply either:\",\n \"**kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\" Tying the encoder and decoders'\",\n \"named `config.json` is found in the directory. state_dict: (`optional`) dict: an optional state\",\n \"case of conflict. kwargs_common = { argument: value for argument, value in kwargs.items()\",\n \"if argument.startswith(\\\"encoder_\\\") } ) kwargs_decoder.update( { argument[len(\\\"decoder_\\\") :]: value for argument, value in\",\n \"passes with the encoder's hidden state through the decoder to decode a full\",\n \"provided conversion scripts and loading the PyTorch model afterwards. model_args: (`optional`) Sequence of\",\n \"this behavior and initialize, say, the decoder randomly by creating it beforehand as\",\n \"we need to set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder is None:\",\n \"library (loaded with the ``shortcut-name`` string of a pretrained model), or - the\",\n \"kwargs: (`optional`) Remaining dictionary of keyword arguments. \\\"\\\"\\\" # keyword arguments come in\",\n \"configuration files and override the cached versions if they exists. proxies: (`optional`) dict,\",\n \"which a downloaded pre-trained model configuration should be cached if the standard cache\",\n \"False decoder = kwargs_decoder.pop(\\\"model\\\", None) if decoder is None: decoder = AutoModelWithLMHead.from_pretrained( decoder_pretrained_model_name_or_path,\",\n \"embeddings.word_embeddings - RoBERTa: embeddings.word_embeddings - XLMModel: embeddings - GPT2: wte - BertForMaskedLM: bert.embeddings.word_embeddings\",\n \"os import torch from torch import nn from .modeling_auto import AutoModel, AutoModelWithLMHead logger\",\n \"except in compliance with the License. # You may obtain a copy of\",\n \"All remaning positional arguments will be passed to the underlying model's ``__init__`` method\",\n \"save the encoder' and decoder's parameters in two separate directories. \\\"\\\"\\\" self.encoder.save_pretrained(os.path.join(save_directory, \\\"encoder\\\"))\",\n \"In this case, ``from_tf`` should be set to True and a configuration object\",\n \"the decoder to decode a full sequence. Therefore, we skip the forward pass\",\n \"to both encoders and decoders. Examples:: model = PreTrainedEncoderDecoder.from_pretained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert\",\n \"for the model to use instead of an automatically loaded configuation. Configuration can\",\n \"If a configuration is not provided, ``kwargs`` will be first passed to the\",\n \"when created with the `AutoModel.from_pretrained(pretrained_model_name_or_path)` class method. \\\"\\\"\\\" def __init__(self, encoder, decoder): super(PreTrainedEncoderDecoder,\",\n \"may not use this file except in compliance with the License. # You\",\n \"License is distributed on an \\\"AS IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS\",\n \"passed to the underlying model's ``__init__`` method (we assume all relevant updates to\",\n \"object should be provided as ``config`` argument. This loading path is slower than\",\n \"parameters that will be used to initialize a\\\" \\\" torch.nn.LSTM model as `decoder_config`\",\n \"Therefore, we skip the forward pass on the encoder if an argument named\",\n \"create a randomly initilized LSTM model as decoder if \\\"decoder_config\\\" not in kwargs:\",\n \"keys that do not correspond to any configuration attribute will be passed to\",\n \"the underlying model's ``__init__`` function. You can specify kwargs sepcific for the encoder\",\n \"of proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname':\",\n \"decoder_pretrained_model_name_or_path, **kwargs_decoder ) decoder.config.is_decoder = True model = cls(encoder, decoder) return model def\",\n \"torch.nn.LSTM model as `decoder_config` keyword argument. \\\" \\\" E.g. `decoder_config={'input_size': 768, 'hidden_size': 768,\",\n \"coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # Licensed under the\",\n \"to (re-)download the model weights and configuration files and override the cached versions\",\n \"decoder_model=decoder) \\\"\\\"\\\" def __init__(self, *args, **kwargs): super(Model2Model, self).__init__(*args, **kwargs) self.tie_weights() def tie_weights(self): \\\"\\\"\\\"\",\n \"training mode with `model.train()` Params: encoder_pretrained_model_name_or_path: information necessary to initiate the encoder. Either:\",\n \"its weights are not present). It is possible to override this behavior and\",\n \"if they exists. proxies: (`optional`) dict, default None: A dictionary of proxy servers\",\n \"first prediction pass) encoder_hidden_states = kwargs_encoder.pop(\\\"hidden_states\\\", None) if encoder_hidden_states is None: encoder_outputs =\",\n \"return a dictionnary containing missing keys, unexpected keys and error messages. kwargs: (`optional`)\",\n \"the key with `encoder_` and `decoder_` respectively. (e.g. ``decoder_output_attention=True``). The remaining kwargs will\",\n \"if ( \\\"bert\\\" not in pretrained_model_name_or_path or \\\"roberta\\\" in pretrained_model_name_or_path or \\\"distilbert\\\" in\",\n \"- a dictionary of configuration parameters that will be used to initialize a\\\"\",\n \"encoder, decoder): super(PreTrainedEncoderDecoder, self).__init__() self.encoder = encoder self.decoder = decoder @classmethod def from_pretrained(\",\n \"cache_dir: (`optional`) string: Path to a directory in which a downloaded pre-trained model\",\n \"we perform one forward pass through the encoder, and then perform several forward\",\n \"the library from pre-trained model checkpoints. The model is set in evaluation mode\",\n \"set correctly. encoder = kwargs_encoder.pop(\\\"model\\\", None) if encoder is None: encoder = AutoModel.from_pretrained(\",\n \"encoder-specific (prefixed by # `encoder_`), decoder-specific (prefixed by `decoder_`) and those # that\",\n \"directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found in\"\n]","isConversational":false}}},{"rowIdx":98,"cells":{"ngram":{"kind":"list like","value":["= default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl","PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem, branch_mulher]","18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1)","'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag","/usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m,","timedelta import pandas as pd import random # Default args definition default_args =","dag = DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula idade media para","homens ou mulheres\", default_args = default_args, schedule_interval='*/20 * * * *' ) get_data","as pd import random # Default args definition default_args = { 'owner': 'Rafael',","1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\"Extrai dados","def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def","'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False,","{med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv')","datetime, timedelta import pandas as pd import random # Default args definition default_args","definition dag = DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula idade media","= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no","['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag","Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11,","{ 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>',","'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'],","pandas as pd import random # Default args definition default_args = { 'owner':","from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime,","BranchPythonOperator from datetime import datetime, timedelta import pandas as pd import random #","schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o","python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==","get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return","default_args = default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data',","from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as","import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as pd import","task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem'","== 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator(","'<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition","import random # Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False,","import pandas as pd import random # Default args definition default_args = {","mulheres\", default_args = default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator(","= df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher","False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry':","df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres","PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as pd import random","no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m","de idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag","value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator(","-o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m',","= PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem,","'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value","Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df =","from datetime import datetime, timedelta import pandas as pd import random # Default","False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03',","df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens","mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das","= BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med","dados do Titanic e calcula idade media para homens ou mulheres\", default_args =",") def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de","df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher =","print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher,","BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =","de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag","'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG(","random # Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date':","'treino-03', description=\"Extrai dados do Titanic e calcula idade media para homens ou mulheres\",","do Titanic e calcula idade media para homens ou mulheres\", default_args = default_args,","if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional',","pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic:","default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv","Titanic e calcula idade media para homens ou mulheres\", default_args = default_args, schedule_interval='*/20","task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m","df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem =","datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries':","'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def","BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female'])","pd import random # Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past':","= DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula idade media para homens","'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df =","def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female","print(f'Media de idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem,","20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) }","random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if","def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade","# Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020,","dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media","media para homens ou mulheres\", default_args = default_args, schedule_interval='*/20 * * * *'","== 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True,","# Dag definition dag = DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula","args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29,","PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return","return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df","'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False,","airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as pd","return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag )","dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag","med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}')","task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex","= PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male':","else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem():","* * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv',","= df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem","False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag =","*' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def","return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m')","= { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email':","import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import","29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay':","= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no","BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas","11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1,","para homens ou mulheres\", default_args = default_args, schedule_interval='*/20 * * * *' )","MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female =","no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df","* *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag )","'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure':","= BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male',","'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag","datetime import datetime, timedelta import pandas as pd import random # Default args","'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem',","bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m =","airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from","'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } #","DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula idade media para homens ou","escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value ==","branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >>","} # Dag definition dag = DAG( 'treino-03', description=\"Extrai dados do Titanic e","python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean()","dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media","mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >>",") def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag )","value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF,","mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos","PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex","== 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem = PythonOperator(","{med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female","pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic:","homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher():","e calcula idade media para homens ou mulheres\", default_args = default_args, schedule_interval='*/20 *","branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med","male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv')","airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta","'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher',","import datetime, timedelta import pandas as pd import random # Default args definition","def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade","Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >>","Dag definition dag = DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula idade","definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18,","sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context):","from airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator","python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else:","'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\"Extrai dados do","med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}')","timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\"Extrai dados do Titanic","provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean()","description=\"Extrai dados do Titanic e calcula idade media para homens ou mulheres\", default_args","ou mulheres\", default_args = default_args, schedule_interval='*/20 * * * *' ) get_data =","idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag )","idade media para homens ou mulheres\", default_args = default_args, schedule_interval='*/20 * * *","default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20),",") def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de","dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return","= PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =","'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\"Extrai","dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def","https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator(",") get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m():",") def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher'","idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag )","das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data","DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import","task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==","* * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag","calcula idade media para homens ou mulheres\", default_args = default_args, schedule_interval='*/20 * *","import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime"],"string":"[\n \"= default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl\",\n \"PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem, branch_mulher]\",\n \"18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1)\",\n \"'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag\",\n \"/usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m,\",\n \"timedelta import pandas as pd import random # Default args definition default_args =\",\n \"dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula idade media para\",\n \"homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * * * *' ) get_data\",\n \"as pd import random # Default args definition default_args = { 'owner': 'Rafael',\",\n \"1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados\",\n \"def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def\",\n \"'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False,\",\n \"{med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv')\",\n \"datetime, timedelta import pandas as pd import random # Default args definition default_args\",\n \"definition dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula idade media\",\n \"= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no\",\n \"['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag\",\n \"Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11,\",\n \"{ 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>',\",\n \"'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'],\",\n \"pandas as pd import random # Default args definition default_args = { 'owner':\",\n \"from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime,\",\n \"BranchPythonOperator from datetime import datetime, timedelta import pandas as pd import random #\",\n \"schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o\",\n \"python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==\",\n \"get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return\",\n \"default_args = default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data',\",\n \"from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as\",\n \"import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as pd import\",\n \"task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem'\",\n \"== 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator(\",\n \"'<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition\",\n \"import random # Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False,\",\n \"import pandas as pd import random # Default args definition default_args = {\",\n \"mulheres\\\", default_args = default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator(\",\n \"= df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher\",\n \"False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry':\",\n \"df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres\",\n \"PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as pd import random\",\n \"no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m\",\n \"de idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag\",\n \"value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator(\",\n \"-o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m',\",\n \"= PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem,\",\n \"'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value\",\n \"Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df =\",\n \"from datetime import datetime, timedelta import pandas as pd import random # Default\",\n \"False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03',\",\n \"df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens\",\n \"mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das\",\n \"= BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med\",\n \"dados do Titanic e calcula idade media para homens ou mulheres\\\", default_args =\",\n \") def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de\",\n \"df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher =\",\n \"print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher,\",\n \"BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =\",\n \"de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag\",\n \"'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG(\",\n \"random # Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date':\",\n \"'treino-03', description=\\\"Extrai dados do Titanic e calcula idade media para homens ou mulheres\\\",\",\n \"do Titanic e calcula idade media para homens ou mulheres\\\", default_args = default_args,\",\n \"if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional',\",\n \"pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic:\",\n \"default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv\",\n \"Titanic e calcula idade media para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20\",\n \"task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m\",\n \"df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem =\",\n \"datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries':\",\n \"'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def\",\n \"BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female'])\",\n \"pd import random # Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past':\",\n \"= DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula idade media para homens\",\n \"'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df =\",\n \"def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female\",\n \"print(f'Media de idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem,\",\n \"20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) }\",\n \"random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if\",\n \"def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade\",\n \"# Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020,\",\n \"dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media\",\n \"media para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * * * *'\",\n \"== 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True,\",\n \"# Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula\",\n \"args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29,\",\n \"PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return\",\n \"return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df\",\n \"'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False,\",\n \"airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as pd\",\n \"return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag )\",\n \"dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag\",\n \"med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}')\",\n \"task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex\",\n \"= PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male':\",\n \"else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem():\",\n \"* * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv',\",\n \"= df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem\",\n \"False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag =\",\n \"*' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def\",\n \"return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m')\",\n \"= { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email':\",\n \"import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import\",\n \"29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay':\",\n \"= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no\",\n \"BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas\",\n \"11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1,\",\n \"para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * * * *' )\",\n \"MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female =\",\n \"no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df\",\n \"* *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag )\",\n \"'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure':\",\n \"= BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male',\",\n \"'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag\",\n \"datetime import datetime, timedelta import pandas as pd import random # Default args\",\n \"'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem',\",\n \"bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m =\",\n \"airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from\",\n \"'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } #\",\n \"DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula idade media para homens ou\",\n \"escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value ==\",\n \"branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >>\",\n \"} # Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic e\",\n \"python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean()\",\n \"dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media\",\n \"mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >>\",\n \") def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag )\",\n \"value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF,\",\n \"mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos\",\n \"PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex\",\n \"== 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem = PythonOperator(\",\n \"{med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female\",\n \"pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic:\",\n \"homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher():\",\n \"e calcula idade media para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 *\",\n \"branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med\",\n \"male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv')\",\n \"airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta\",\n \"'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher',\",\n \"import datetime, timedelta import pandas as pd import random # Default args definition\",\n \"def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade\",\n \"Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >>\",\n \"Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula idade\",\n \"definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18,\",\n \"sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context):\",\n \"from airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator\",\n \"python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else:\",\n \"'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados do\",\n \"med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}')\",\n \"timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic\",\n \"provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean()\",\n \"description=\\\"Extrai dados do Titanic e calcula idade media para homens ou mulheres\\\", default_args\",\n \"ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * * * *' ) get_data =\",\n \"idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag )\",\n \"idade media para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * * *\",\n \"default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20),\",\n \") def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de\",\n \"dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return\",\n \"= PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =\",\n \"'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\\\"Extrai\",\n \"dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def\",\n \"https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator(\",\n \") get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m():\",\n \") def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher'\",\n \"idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag )\",\n \"das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data\",\n \"DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import\",\n \"task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==\",\n \"* * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag\",\n \"calcula idade media para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * *\",\n \"import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime\"\n]","isConversational":false}}},{"rowIdx":99,"cells":{"ngram":{"kind":"list like","value":["description = '%s %s' % (\"--\", \"Outputs in Tcl Shell the list with","args: argument = args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else:","# Dictionary of types from Tcl command, needs to be ordered arg_names =","Tcl command, needs to be ordered , this is for options like -optionname","'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\" :param","Tcl Shell the list with the names of system variables.\") # Dictionary of","= '%s %s' % (\"--\", \"Outputs in Tcl Shell the list with the","'%s %s' % (\"--\", \"Outputs in Tcl Shell the list with the names","-optionname value option_types = collections.OrderedDict([ ]) # array of mandatory options for current","or excellon or geometry or cncjob or global.\\n\" \"Note: Use 'get_sys system variable'","variable' to get the value and 'set_sys system variable value' to set it.\\n\",","the list of system variables example: list_sys \"\"\" # List of all command","current command, args needs to be ordered help = { 'main': \"Returns the",":param unnamed_args: :return: \"\"\" if 'selection' in args: argument = args['selection'] return str([k","\"Outputs in Tcl Shell the list with the names of system variables.\") #","with that string.\\n\" \"Main categories start with: gerber or excellon or geometry or","MIT Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl","with the names of system variables.\") # Dictionary of types from Tcl command,","to get the list of system variables example: list_sys \"\"\" # List of","(add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' % (\"--\", \"Outputs","letters from the name \" \"of the system variable.\\n\" \"In that case it","of types from Tcl command, needs to be ordered , this is for","]) # array of mandatory options for current Tcl command: required = {'name','outname'}","structured help for current command, args needs to be ordered help = {","an argument use first letter or first letters from the name \" \"of","value and 'set_sys system variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples':","= { 'main': \"Returns the list of the names of system variables.\\n\" \"Without","str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val)","system variable.\\n\" \"In that case it will list only the system variables that","needs to be ordered , this is for options like -optionname value option_types","Dictionary of types from Tcl command, needs to be ordered , this is","<NAME> (c) # # Date: 8/17/2019 # # MIT Licence # # ##########################################################","value option_types = collections.OrderedDict([ ]) # array of mandatory options for current Tcl","# Date: 8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand import","collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl command, needs to","the list of the names of system variables.\\n\" \"Without an argument it will","variables.\") # Dictionary of types from Tcl command, needs to be ordered arg_names","of the names of system variables.\\n\" \"Without an argument it will list all","or cncjob or global.\\n\" \"Note: Use 'get_sys system variable' to get the value","the value and 'set_sys system variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]),","in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return str([*self.app.defaults])","value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber',","%s' % (\"--\", \"Outputs in Tcl Shell the list with the names of","of mandatory options for current Tcl command: required = {'name','outname'} required = []","with: gerber or excellon or geometry or cncjob or global.\\n\" \"Note: Use 'get_sys","\"of the system variable.\\n\" \"In that case it will list only the system","'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\" :param args: :param","Tcl command: required = {'name','outname'} required = [] # structured help for current","for current Tcl command: required = {'name','outname'} required = [] # structured help","cncj'] } def execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\"","the list with the names of system variables.\") # Dictionary of types from","of types from Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection',","shell command to get the list of system variables example: list_sys \"\"\" #","excellon or geometry or cncjob or global.\\n\" \"Note: Use 'get_sys system variable' to","\"In that case it will list only the system variables that starts with","# MIT Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\"","command: required = {'name','outname'} required = [] # structured help for current command,","Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) #","options for current Tcl command: required = {'name','outname'} required = [] # structured","the names of system variables.\\n\" \"Without an argument it will list all the","'main': \"Returns the list of the names of system variables.\\n\" \"Without an argument","the system variable.\\n\" \"In that case it will list only the system variables","global.\\n\" \"Note: Use 'get_sys system variable' to get the value and 'set_sys system","backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' %","'selection' in args: argument = args['selection'] return str([k for k in self.app.defaults.keys() if","# # Date: 8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand","is for options like -optionname value option_types = collections.OrderedDict([ ]) # array of","list with the names of system variables.\") # Dictionary of types from Tcl","Post-processing for Manufacturing # # File Author: <NAME> (c) # # Date: 8/17/2019","that case it will list only the system variables that starts with that","Use 'get_sys system variable' to get the value and 'set_sys system variable value'","list all the system parameters. \" \"As an argument use first letter or","be ordered , this is for options like -optionname value option_types = collections.OrderedDict([","list_sys \"\"\" # List of all command aliases, to be able use old","starts with that string.\\n\" \"Main categories start with: gerber or excellon or geometry","system variable' to get the value and 'set_sys system variable value' to set","\"As an argument use first letter or first letters from the name \"","categories start with: gerber or excellon or geometry or cncjob or global.\\n\" \"Note:","Tcl shell command to get the list of system variables example: list_sys \"\"\"","gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args:","from Tcl command, needs to be ordered , this is for options like","help for current command, args needs to be ordered help = { 'main':","command, needs to be ordered , this is for options like -optionname value","only the system variables that starts with that string.\\n\" \"Main categories start with:","ordered help = { 'main': \"Returns the list of the names of system","to be ordered help = { 'main': \"Returns the list of the names","use old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description","= collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl command, needs","array of mandatory options for current Tcl command: required = {'name','outname'} required =","unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\" if 'selection' in args: argument","collections.OrderedDict([ ]) # array of mandatory options for current Tcl command: required =","or geometry or cncjob or global.\\n\" \"Note: Use 'get_sys system variable' to get","# array of mandatory options for current Tcl command: required = {'name','outname'} required","use first letter or first letters from the name \" \"of the system","and 'set_sys system variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys',","arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl command,","variables that starts with that string.\\n\" \"Main categories start with: gerber or excellon","<filename>tclCommands/TclCommandListSys.py # ########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File Author:","# structured help for current command, args needs to be ordered help =","name \" \"of the system variable.\\n\" \"In that case it will list only","it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] }","args: :param unnamed_args: :return: \"\"\" if 'selection' in args: argument = args['selection'] return","'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def","system parameters. \" \"As an argument use first letter or first letters from","the system parameters. \" \"As an argument use first letter or first letters","command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary","list only the system variables that starts with that string.\\n\" \"Main categories start","it will list all the system parameters. \" \"As an argument use first",":param args: :param unnamed_args: :return: \"\"\" if 'selection' in args: argument = args['selection']","Date: 8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand import *","tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the list","variables example: list_sys \"\"\" # List of all command aliases, to be able","Dictionary of types from Tcl command, needs to be ordered arg_names = collections.OrderedDict([","(\"--\", \"Outputs in Tcl Shell the list with the names of system variables.\")","argument it will list all the system parameters. \" \"As an argument use","########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME> (c)","# # File Author: <NAME> (c) # # Date: 8/17/2019 # # MIT","execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\" if 'selection' in","the system variables that starts with that string.\\n\" \"Main categories start with: gerber","[] # structured help for current command, args needs to be ordered help","{ 'main': \"Returns the list of the names of system variables.\\n\" \"Without an","def execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\" if 'selection'","get the list of system variables example: list_sys \"\"\" # List of all","['list_sys', 'listsys'] description = '%s %s' % (\"--\", \"Outputs in Tcl Shell the","an argument it will list all the system parameters. \" \"As an argument","will list all the system parameters. \" \"As an argument use first letter","the name \" \"of the system variable.\\n\" \"In that case it will list","of system variables.\") # Dictionary of types from Tcl command, needs to be","this is for options like -optionname value option_types = collections.OrderedDict([ ]) # array","= [] # structured help for current command, args needs to be ordered","aliases, to be able use old names for backward compatibility (add_poly, add_polygon) aliases","variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys","in args: argument = args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))])","k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return","types from Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str),","]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args,","letter or first letters from the name \" \"of the system variable.\\n\" \"In","= ['list_sys', 'listsys'] description = '%s %s' % (\"--\", \"Outputs in Tcl Shell","types from Tcl command, needs to be ordered , this is for options","all the system parameters. \" \"As an argument use first letter or first","# Dictionary of types from Tcl command, needs to be ordered , this","or global.\\n\" \"Note: Use 'get_sys system variable' to get the value and 'set_sys","system variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser',","('selection', str), ]) # Dictionary of types from Tcl command, needs to be","File Author: <NAME> (c) # # Date: 8/17/2019 # # MIT Licence #","collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self,","for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) #","for current command, args needs to be ordered help = { 'main': \"Returns","start with: gerber or excellon or geometry or cncjob or global.\\n\" \"Note: Use",", this is for options like -optionname value option_types = collections.OrderedDict([ ]) #","= collections.OrderedDict([ ]) # array of mandatory options for current Tcl command: required","that starts with that string.\\n\" \"Main categories start with: gerber or excellon or","unnamed_args: :return: \"\"\" if 'selection' in args: argument = args['selection'] return str([k for","\"Main categories start with: gerber or excellon or geometry or cncjob or global.\\n\"","string.\\n\" \"Main categories start with: gerber or excellon or geometry or cncjob or","set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj']","system variables example: list_sys \"\"\" # List of all command aliases, to be","that string.\\n\" \"Main categories start with: gerber or excellon or geometry or cncjob","['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\"","} def execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\" if","args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys())","needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of","options like -optionname value option_types = collections.OrderedDict([ ]) # array of mandatory options","gerber or excellon or geometry or cncjob or global.\\n\" \"Note: Use 'get_sys system","(c) # # Date: 8/17/2019 # # MIT Licence # # ########################################################## from","command to get the list of system variables example: list_sys \"\"\" # List","will list only the system variables that starts with that string.\\n\" \"Main categories","2D Post-processing for Manufacturing # # File Author: <NAME> (c) # # Date:","example: list_sys \"\"\" # List of all command aliases, to be able use","import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the list of","'set_sys system variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys","or first letters from the name \" \"of the system variable.\\n\" \"In that","mandatory options for current Tcl command: required = {'name','outname'} required = [] #","\"Returns the list of the names of system variables.\\n\" \"Without an argument it","system variables.\\n\" \"Without an argument it will list all the system parameters. \"","cncjob or global.\\n\" \"Note: Use 'get_sys system variable' to get the value and","\"\"\" :param args: :param unnamed_args: :return: \"\"\" if 'selection' in args: argument =","= {'name','outname'} required = [] # structured help for current command, args needs","Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell","be ordered help = { 'main': \"Returns the list of the names of","ordered , this is for options like -optionname value option_types = collections.OrderedDict([ ])","ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl","to be ordered , this is for options like -optionname value option_types =","get the value and 'set_sys system variable value' to set it.\\n\", 'args': collections.OrderedDict([","for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s'","# # MIT Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand):","'get_sys system variable' to get the value and 'set_sys system variable value' to","add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' % (\"--\", \"Outputs in","required = [] # structured help for current command, args needs to be","help = { 'main': \"Returns the list of the names of system variables.\\n\"","argument use first letter or first letters from the name \" \"of the","from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the","system variables.\") # Dictionary of types from Tcl command, needs to be ordered","aliases = ['list_sys', 'listsys'] description = '%s %s' % (\"--\", \"Outputs in Tcl","current Tcl command: required = {'name','outname'} required = [] # structured help for","to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys","= args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val =","argument = args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val","TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the list of system variables example:","FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME> (c) # #","names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s","required = {'name','outname'} required = [] # structured help for current command, args","for options like -optionname value option_types = collections.OrderedDict([ ]) # array of mandatory","'listsys'] description = '%s %s' % (\"--\", \"Outputs in Tcl Shell the list","it will list only the system variables that starts with that string.\\n\" \"Main","to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types","system variables that starts with that string.\\n\" \"Main categories start with: gerber or","of all command aliases, to be able use old names for backward compatibility","be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from","for Manufacturing # # File Author: <NAME> (c) # # Date: 8/17/2019 #","Manufacturing # # File Author: <NAME> (c) # # Date: 8/17/2019 # #","names of system variables.\") # Dictionary of types from Tcl command, needs to","option_types = collections.OrderedDict([ ]) # array of mandatory options for current Tcl command:","# ########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME>","variable.\\n\" \"In that case it will list only the system variables that starts","# # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command","case it will list only the system variables that starts with that string.\\n\"","\"\"\" if 'selection' in args: argument = args['selection'] return str([k for k in","]) # Dictionary of types from Tcl command, needs to be ordered ,","needs to be ordered help = { 'main': \"Returns the list of the","like -optionname value option_types = collections.OrderedDict([ ]) # array of mandatory options for","list of the names of system variables.\\n\" \"Without an argument it will list","of system variables.\\n\" \"Without an argument it will list all the system parameters.","Shell the list with the names of system variables.\") # Dictionary of types","\" \"of the system variable.\\n\" \"In that case it will list only the","% (\"--\", \"Outputs in Tcl Shell the list with the names of system","be able use old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys',","return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return","compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' % (\"--\",","variables.\\n\" \"Without an argument it will list all the system parameters. \" \"As","parameters. \" \"As an argument use first letter or first letters from the","\"Note: Use 'get_sys system variable' to get the value and 'set_sys system variable","\"\"\" Tcl shell command to get the list of system variables example: list_sys","'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args):","ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\" :param args:","first letters from the name \" \"of the system variable.\\n\" \"In that case",":return: \"\"\" if 'selection' in args: argument = args['selection'] return str([k for k","\"Without an argument it will list all the system parameters. \" \"As an","the names of system variables.\") # Dictionary of types from Tcl command, needs","{'name','outname'} required = [] # structured help for current command, args needs to","\"\"\" # List of all command aliases, to be able use old names","# File Author: <NAME> (c) # # Date: 8/17/2019 # # MIT Licence","str), ]) # Dictionary of types from Tcl command, needs to be ordered","command, args needs to be ordered help = { 'main': \"Returns the list","to get the value and 'set_sys system variable value' to set it.\\n\", 'args':","in Tcl Shell the list with the names of system variables.\") # Dictionary","names of system variables.\\n\" \"Without an argument it will list all the system","geometry or cncjob or global.\\n\" \"Note: Use 'get_sys system variable' to get the","args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\" if 'selection' in args:","# FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME> (c) #","of system variables example: list_sys \"\"\" # List of all command aliases, to","first letter or first letters from the name \" \"of the system variable.\\n\"","class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the list of system variables","########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get","old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description =","list of system variables example: list_sys \"\"\" # List of all command aliases,","List of all command aliases, to be able use old names for backward","command aliases, to be able use old names for backward compatibility (add_poly, add_polygon)","args needs to be ordered help = { 'main': \"Returns the list of","'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return:","\" \"As an argument use first letter or first letters from the name","able use old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys']","from the name \" \"of the system variable.\\n\" \"In that case it will","8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand import * class","* class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the list of system","from Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ])","Author: <NAME> (c) # # Date: 8/17/2019 # # MIT Licence # #","all command aliases, to be able use old names for backward compatibility (add_poly,","# List of all command aliases, to be able use old names for","# ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to","if 'selection' in args: argument = args['selection'] return str([k for k in self.app.defaults.keys()","to be able use old names for backward compatibility (add_poly, add_polygon) aliases ="],"string":"[\n \"description = '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the list with\",\n \"args: argument = args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else:\",\n \"# Dictionary of types from Tcl command, needs to be ordered arg_names =\",\n \"Tcl command, needs to be ordered , this is for options like -optionname\",\n \"'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param\",\n \"Tcl Shell the list with the names of system variables.\\\") # Dictionary of\",\n \"= '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the list with the\",\n \"'%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the list with the names\",\n \"-optionname value option_types = collections.OrderedDict([ ]) # array of mandatory options for current\",\n \"or excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable'\",\n \"variable' to get the value and 'set_sys system variable value' to set it.\\\\n\\\",\",\n \"the list of system variables example: list_sys \\\"\\\"\\\" # List of all command\",\n \"current command, args needs to be ordered help = { 'main': \\\"Returns the\",\n \":param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument = args['selection'] return str([k\",\n \"\\\"Outputs in Tcl Shell the list with the names of system variables.\\\") #\",\n \"with that string.\\\\n\\\" \\\"Main categories start with: gerber or excellon or geometry or\",\n \"MIT Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl\",\n \"with the names of system variables.\\\") # Dictionary of types from Tcl command,\",\n \"to get the list of system variables example: list_sys \\\"\\\"\\\" # List of\",\n \"(add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs\",\n \"letters from the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that case it\",\n \"of types from Tcl command, needs to be ordered , this is for\",\n \"]) # array of mandatory options for current Tcl command: required = {'name','outname'}\",\n \"structured help for current command, args needs to be ordered help = {\",\n \"an argument use first letter or first letters from the name \\\" \\\"of\",\n \"value and 'set_sys system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples':\",\n \"= { 'main': \\\"Returns the list of the names of system variables.\\\\n\\\" \\\"Without\",\n \"str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val)\",\n \"system variable.\\\\n\\\" \\\"In that case it will list only the system variables that\",\n \"needs to be ordered , this is for options like -optionname value option_types\",\n \"Dictionary of types from Tcl command, needs to be ordered , this is\",\n \"<NAME> (c) # # Date: 8/17/2019 # # MIT Licence # # ##########################################################\",\n \"value option_types = collections.OrderedDict([ ]) # array of mandatory options for current Tcl\",\n \"# Date: 8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand import\",\n \"collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl command, needs to\",\n \"the list of the names of system variables.\\\\n\\\" \\\"Without an argument it will\",\n \"variables.\\\") # Dictionary of types from Tcl command, needs to be ordered arg_names\",\n \"of the names of system variables.\\\\n\\\" \\\"Without an argument it will list all\",\n \"or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get the value\",\n \"the value and 'set_sys system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]),\",\n \"in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return str([*self.app.defaults])\",\n \"value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber',\",\n \"%s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the list with the names of\",\n \"of mandatory options for current Tcl command: required = {'name','outname'} required = []\",\n \"with: gerber or excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys\",\n \"\\\"of the system variable.\\\\n\\\" \\\"In that case it will list only the system\",\n \"'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param\",\n \"Tcl command: required = {'name','outname'} required = [] # structured help for current\",\n \"for current Tcl command: required = {'name','outname'} required = [] # structured help\",\n \"cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\"\",\n \"the list with the names of system variables.\\\") # Dictionary of types from\",\n \"of types from Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection',\",\n \"shell command to get the list of system variables example: list_sys \\\"\\\"\\\" #\",\n \"excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to\",\n \"\\\"In that case it will list only the system variables that starts with\",\n \"# MIT Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\"\",\n \"command: required = {'name','outname'} required = [] # structured help for current command,\",\n \"Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) #\",\n \"options for current Tcl command: required = {'name','outname'} required = [] # structured\",\n \"the names of system variables.\\\\n\\\" \\\"Without an argument it will list all the\",\n \"'main': \\\"Returns the list of the names of system variables.\\\\n\\\" \\\"Without an argument\",\n \"the system variable.\\\\n\\\" \\\"In that case it will list only the system variables\",\n \"global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get the value and 'set_sys system\",\n \"backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' %\",\n \"'selection' in args: argument = args['selection'] return str([k for k in self.app.defaults.keys() if\",\n \"# # Date: 8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand\",\n \"is for options like -optionname value option_types = collections.OrderedDict([ ]) # array of\",\n \"list with the names of system variables.\\\") # Dictionary of types from Tcl\",\n \"Post-processing for Manufacturing # # File Author: <NAME> (c) # # Date: 8/17/2019\",\n \"that case it will list only the system variables that starts with that\",\n \"Use 'get_sys system variable' to get the value and 'set_sys system variable value'\",\n \"list all the system parameters. \\\" \\\"As an argument use first letter or\",\n \"be ordered , this is for options like -optionname value option_types = collections.OrderedDict([\",\n \"list_sys \\\"\\\"\\\" # List of all command aliases, to be able use old\",\n \"starts with that string.\\\\n\\\" \\\"Main categories start with: gerber or excellon or geometry\",\n \"system variable' to get the value and 'set_sys system variable value' to set\",\n \"\\\"As an argument use first letter or first letters from the name \\\"\",\n \"categories start with: gerber or excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note:\",\n \"Tcl shell command to get the list of system variables example: list_sys \\\"\\\"\\\"\",\n \"gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args:\",\n \"from Tcl command, needs to be ordered , this is for options like\",\n \"help for current command, args needs to be ordered help = { 'main':\",\n \"command, needs to be ordered , this is for options like -optionname value\",\n \"only the system variables that starts with that string.\\\\n\\\" \\\"Main categories start with:\",\n \"ordered help = { 'main': \\\"Returns the list of the names of system\",\n \"to be ordered help = { 'main': \\\"Returns the list of the names\",\n \"use old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description\",\n \"= collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl command, needs\",\n \"array of mandatory options for current Tcl command: required = {'name','outname'} required =\",\n \"unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument\",\n \"collections.OrderedDict([ ]) # array of mandatory options for current Tcl command: required =\",\n \"or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get\",\n \"# array of mandatory options for current Tcl command: required = {'name','outname'} required\",\n \"use first letter or first letters from the name \\\" \\\"of the system\",\n \"and 'set_sys system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys',\",\n \"arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl command,\",\n \"variables that starts with that string.\\\\n\\\" \\\"Main categories start with: gerber or excellon\",\n \"<filename>tclCommands/TclCommandListSys.py # ########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File Author:\",\n \"# structured help for current command, args needs to be ordered help =\",\n \"name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that case it will list only\",\n \"it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] }\",\n \"args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument = args['selection'] return\",\n \"'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def\",\n \"system parameters. \\\" \\\"As an argument use first letter or first letters from\",\n \"the system parameters. \\\" \\\"As an argument use first letter or first letters\",\n \"command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary\",\n \"list only the system variables that starts with that string.\\\\n\\\" \\\"Main categories start\",\n \"it will list all the system parameters. \\\" \\\"As an argument use first\",\n \":param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument = args['selection']\",\n \"Date: 8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand import *\",\n \"tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the list\",\n \"variables example: list_sys \\\"\\\"\\\" # List of all command aliases, to be able\",\n \"Dictionary of types from Tcl command, needs to be ordered arg_names = collections.OrderedDict([\",\n \"(\\\"--\\\", \\\"Outputs in Tcl Shell the list with the names of system variables.\\\")\",\n \"argument it will list all the system parameters. \\\" \\\"As an argument use\",\n \"########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME> (c)\",\n \"# # File Author: <NAME> (c) # # Date: 8/17/2019 # # MIT\",\n \"execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in\",\n \"the system variables that starts with that string.\\\\n\\\" \\\"Main categories start with: gerber\",\n \"[] # structured help for current command, args needs to be ordered help\",\n \"{ 'main': \\\"Returns the list of the names of system variables.\\\\n\\\" \\\"Without an\",\n \"def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection'\",\n \"get the list of system variables example: list_sys \\\"\\\"\\\" # List of all\",\n \"['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the\",\n \"an argument it will list all the system parameters. \\\" \\\"As an argument\",\n \"will list all the system parameters. \\\" \\\"As an argument use first letter\",\n \"the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that case it will list\",\n \"of system variables.\\\") # Dictionary of types from Tcl command, needs to be\",\n \"this is for options like -optionname value option_types = collections.OrderedDict([ ]) # array\",\n \"= [] # structured help for current command, args needs to be ordered\",\n \"aliases, to be able use old names for backward compatibility (add_poly, add_polygon) aliases\",\n \"variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys\",\n \"in args: argument = args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))])\",\n \"k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return\",\n \"types from Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str),\",\n \"]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args,\",\n \"letter or first letters from the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In\",\n \"= ['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell\",\n \"types from Tcl command, needs to be ordered , this is for options\",\n \"all the system parameters. \\\" \\\"As an argument use first letter or first\",\n \"# Dictionary of types from Tcl command, needs to be ordered , this\",\n \"or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get the value and 'set_sys\",\n \"system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser',\",\n \"('selection', str), ]) # Dictionary of types from Tcl command, needs to be\",\n \"File Author: <NAME> (c) # # Date: 8/17/2019 # # MIT Licence #\",\n \"collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self,\",\n \"for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) #\",\n \"for current command, args needs to be ordered help = { 'main': \\\"Returns\",\n \"start with: gerber or excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use\",\n \", this is for options like -optionname value option_types = collections.OrderedDict([ ]) #\",\n \"= collections.OrderedDict([ ]) # array of mandatory options for current Tcl command: required\",\n \"that starts with that string.\\\\n\\\" \\\"Main categories start with: gerber or excellon or\",\n \"unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument = args['selection'] return str([k for\",\n \"\\\"Main categories start with: gerber or excellon or geometry or cncjob or global.\\\\n\\\"\",\n \"string.\\\\n\\\" \\\"Main categories start with: gerber or excellon or geometry or cncjob or\",\n \"set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj']\",\n \"system variables example: list_sys \\\"\\\"\\\" # List of all command aliases, to be\",\n \"that string.\\\\n\\\" \\\"Main categories start with: gerber or excellon or geometry or cncjob\",\n \"['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\"\",\n \"} def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if\",\n \"args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys())\",\n \"needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of\",\n \"options like -optionname value option_types = collections.OrderedDict([ ]) # array of mandatory options\",\n \"gerber or excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system\",\n \"(c) # # Date: 8/17/2019 # # MIT Licence # # ########################################################## from\",\n \"command to get the list of system variables example: list_sys \\\"\\\"\\\" # List\",\n \"will list only the system variables that starts with that string.\\\\n\\\" \\\"Main categories\",\n \"2D Post-processing for Manufacturing # # File Author: <NAME> (c) # # Date:\",\n \"example: list_sys \\\"\\\"\\\" # List of all command aliases, to be able use\",\n \"import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the list of\",\n \"'set_sys system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys\",\n \"or first letters from the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that\",\n \"mandatory options for current Tcl command: required = {'name','outname'} required = [] #\",\n \"\\\"Returns the list of the names of system variables.\\\\n\\\" \\\"Without an argument it\",\n \"system variables.\\\\n\\\" \\\"Without an argument it will list all the system parameters. \\\"\",\n \"cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get the value and\",\n \"\\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument =\",\n \"= {'name','outname'} required = [] # structured help for current command, args needs\",\n \"Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell\",\n \"be ordered help = { 'main': \\\"Returns the list of the names of\",\n \"ordered , this is for options like -optionname value option_types = collections.OrderedDict([ ])\",\n \"ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl\",\n \"to be ordered , this is for options like -optionname value option_types =\",\n \"get the value and 'set_sys system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([\",\n \"for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s'\",\n \"# # MIT Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand):\",\n \"'get_sys system variable' to get the value and 'set_sys system variable value' to\",\n \"add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs in\",\n \"required = [] # structured help for current command, args needs to be\",\n \"help = { 'main': \\\"Returns the list of the names of system variables.\\\\n\\\"\",\n \"argument use first letter or first letters from the name \\\" \\\"of the\",\n \"from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the\",\n \"system variables.\\\") # Dictionary of types from Tcl command, needs to be ordered\",\n \"aliases = ['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl\",\n \"current Tcl command: required = {'name','outname'} required = [] # structured help for\",\n \"to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys\",\n \"= args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val =\",\n \"argument = args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val\",\n \"TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the list of system variables example:\",\n \"FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME> (c) # #\",\n \"names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s\",\n \"required = {'name','outname'} required = [] # structured help for current command, args\",\n \"for options like -optionname value option_types = collections.OrderedDict([ ]) # array of mandatory\",\n \"'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the list\",\n \"it will list only the system variables that starts with that string.\\\\n\\\" \\\"Main\",\n \"to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types\",\n \"system variables that starts with that string.\\\\n\\\" \\\"Main categories start with: gerber or\",\n \"of all command aliases, to be able use old names for backward compatibility\",\n \"be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from\",\n \"for Manufacturing # # File Author: <NAME> (c) # # Date: 8/17/2019 #\",\n \"Manufacturing # # File Author: <NAME> (c) # # Date: 8/17/2019 # #\",\n \"names of system variables.\\\") # Dictionary of types from Tcl command, needs to\",\n \"option_types = collections.OrderedDict([ ]) # array of mandatory options for current Tcl command:\",\n \"# ########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME>\",\n \"variable.\\\\n\\\" \\\"In that case it will list only the system variables that starts\",\n \"# # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command\",\n \"case it will list only the system variables that starts with that string.\\\\n\\\"\",\n \"\\\"\\\"\\\" if 'selection' in args: argument = args['selection'] return str([k for k in\",\n \"]) # Dictionary of types from Tcl command, needs to be ordered ,\",\n \"needs to be ordered help = { 'main': \\\"Returns the list of the\",\n \"like -optionname value option_types = collections.OrderedDict([ ]) # array of mandatory options for\",\n \"list of the names of system variables.\\\\n\\\" \\\"Without an argument it will list\",\n \"of system variables.\\\\n\\\" \\\"Without an argument it will list all the system parameters.\",\n \"Shell the list with the names of system variables.\\\") # Dictionary of types\",\n \"\\\" \\\"of the system variable.\\\\n\\\" \\\"In that case it will list only the\",\n \"% (\\\"--\\\", \\\"Outputs in Tcl Shell the list with the names of system\",\n \"be able use old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys',\",\n \"return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return\",\n \"compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\",\",\n \"variables.\\\\n\\\" \\\"Without an argument it will list all the system parameters. \\\" \\\"As\",\n \"parameters. \\\" \\\"As an argument use first letter or first letters from the\",\n \"\\\"Note: Use 'get_sys system variable' to get the value and 'set_sys system variable\",\n \"\\\"\\\"\\\" Tcl shell command to get the list of system variables example: list_sys\",\n \"'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args):\",\n \"ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args:\",\n \"first letters from the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that case\",\n \":return: \\\"\\\"\\\" if 'selection' in args: argument = args['selection'] return str([k for k\",\n \"\\\"Without an argument it will list all the system parameters. \\\" \\\"As an\",\n \"the names of system variables.\\\") # Dictionary of types from Tcl command, needs\",\n \"{'name','outname'} required = [] # structured help for current command, args needs to\",\n \"\\\"\\\"\\\" # List of all command aliases, to be able use old names\",\n \"# File Author: <NAME> (c) # # Date: 8/17/2019 # # MIT Licence\",\n \"str), ]) # Dictionary of types from Tcl command, needs to be ordered\",\n \"command, args needs to be ordered help = { 'main': \\\"Returns the list\",\n \"to get the value and 'set_sys system variable value' to set it.\\\\n\\\", 'args':\",\n \"in Tcl Shell the list with the names of system variables.\\\") # Dictionary\",\n \"names of system variables.\\\\n\\\" \\\"Without an argument it will list all the system\",\n \"geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get the\",\n \"args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args:\",\n \"# FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME> (c) #\",\n \"of system variables example: list_sys \\\"\\\"\\\" # List of all command aliases, to\",\n \"first letter or first letters from the name \\\" \\\"of the system variable.\\\\n\\\"\",\n \"class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the list of system variables\",\n \"########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get\",\n \"old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description =\",\n \"list of system variables example: list_sys \\\"\\\"\\\" # List of all command aliases,\",\n \"List of all command aliases, to be able use old names for backward\",\n \"command aliases, to be able use old names for backward compatibility (add_poly, add_polygon)\",\n \"args needs to be ordered help = { 'main': \\\"Returns the list of\",\n \"'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return:\",\n \"\\\" \\\"As an argument use first letter or first letters from the name\",\n \"able use old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys']\",\n \"from the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that case it will\",\n \"8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand import * class\",\n \"* class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the list of system\",\n \"from Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ])\",\n \"Author: <NAME> (c) # # Date: 8/17/2019 # # MIT Licence # #\",\n \"all command aliases, to be able use old names for backward compatibility (add_poly,\",\n \"# List of all command aliases, to be able use old names for\",\n \"# ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to\",\n \"if 'selection' in args: argument = args['selection'] return str([k for k in self.app.defaults.keys()\",\n \"to be able use old names for backward compatibility (add_poly, add_polygon) aliases =\"\n]","isConversational":false}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":0,"numItemsPerPage":100,"numTotalItems":12866649,"offset":0,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3MzM5NjE0NSwic3ViIjoiL2RhdGFzZXRzL3RlcnJ5eXovc3RhcmNvZGVyZGF0YV9uZ3JhbV8xMyIsImV4cCI6MTc3MzM5OTc0NSwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.4CeT--6ohgh5oHu7fWHXTVDLZL5EFiKeiCaUbhVZsNl78_geK-opzY3jvR87YjRyqZ4_sidGcF0ShJTJ6pkyBQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":12866649,"numBytesParquet":149232926747}]},"discussionsStats":{"closed":0,"open":0,"total":0},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
ngram listlengths 0 67.8k |
|---|
[
") geo_field = \"mpoly\" model = Ocsge class Renaturee2018to2015Serializer(serializers.GeoFeatureModelSerializer): usage_2015 = s.SerializerMethodField() usage_2018",
"label=obj.cs_2015_label) def get_couverture_2018(self, obj): return get_label(code=obj.cs_2018, label=obj.cs_2018_label) class Meta: fields = ( \"... |
[
".models import SearchResult # Register your models here. class SearchResultAdmin(admin.ModelAdmin): fields = [\"query\",",
"django.contrib import admin from .models import SearchResult # Register your models here. class",
"# Register your models here. class SearchResultAdmin(admin.ModelAdmin): fields = [\"quer... |
[
"output, train_path, fixed_model_name, persist_nlu_training_data, ) ) async def _train_nlu_async( config: Text, nlu_data: Text,",
"which supplies the training data. train_path: Directory in which to train the model.",
"= await asyncio.gather( file_importer.get_domain(), file_importer.get_config() ) await rasa.c... |
[
"for i in range(len(prices)): for j in range(i+1,len(prices)): if prices[j]<=prices[i]: res.append(prices[i]-prices[j]) break if",
"def finalPrices(self, prices: List[int]) -> List[int]: res = [] for i in range(len(prices)):",
"i in range(len(prices)): for j in range(i+1,len(prices)): if prices[j]<=prices[i]: r... |
[
"_move_to_prev_line(self) -> None: if self._cursor >= 1: self._cursor -= 1 def _move_to_first_line(self) ->",
"source_names != 'hide': terms.append(self._context['max_source_name_format'].format( self._get_display_source_name(candidate['source_name']))) encoding = self._context['encoding'] abbr = candidate.get('a... |
[
"= None try: if stdchannel is None: yield iter([None]) else: oldstdchannel = os.dup(stdchannel.fileno())",
"try: if stdchannel is None: yield iter([None]) else: oldstdchannel = os.dup(stdchannel.fileno()) dest_file =",
"= open(dest_filename, mode) os.dup2(dest_file.fileno(), stdchannel.fileno()) yield except (U... |
[
"See frappe.core.notifications.get_notification_config # notification_config = \"pos_kiosk.notifications.get_notification_config\" # Permissions # ----------- # Permissions evaluated",
"scripted ways # permission_query_conditions = { # \"Event\": \"frappe.desk.doctype.event.event.get_permission_query_conditions\"... |
[
"neural network \"\"\" @staticmethod def default_config(): config = KerasModel.default_config() config['hidden'] = 32 return",
"SimpleLSTM(KerasModel): \"\"\" Use a simple lstm neural network \"\"\" @staticmethod def default_config(): config",
"config = KerasModel.default_config() config['hidden'] = 32 return c... |
[] |
[
"import ConvBNActivationBlock from easyai.model.base_block.cls.pnasnet_block import CellA, CellB __all__ = ['pnasnet_A', 'pnasnet_B'] class PNASNet(BaseBackbone):",
"for _ in range(num_cells): temp_block = self.block(self.in_planes, planes, stride=1, bn_name=self.bn_name, activation_name=self.activation_name) sel... |
[
"self.download_done_signal.emit() except Exception as e: if self.logger is not None: self.logger.error(e) if __name__",
"not None: self.logger.exception(e) def run(self): try: self.generate_metadata() count = 0 bboxs = self.cut_bbox()",
"def generate_metadata(self): try: metadatas = { \"attribution\": \"© Analy... |
[
"PyPDF2 import PdfFileReader def download_file(pdf_url, mdir, filename, flag=False): if flag is True: context",
"= 1 return flag def getDriver(url): driver = webdriver.Chrome() driver.get(url) return driver def",
"numpages = pdf.numPages return (numpages > 0) except Exception as e: return False",
"= open(file... |
[
"confirmed = os.path.join( BASE_PATH, 'csse_covid_19_time_series', 'time_series_covid19_confirmed_global.csv') confirmed = data.load_csv_data(confirmed) features = [] targets",
"= [] fig = plt.figure(figsize=(12, 12)) ax = fig.add_subplot(111) cm = plt.get_cmap('jet') NUM_COLORS",
"data.load_csv_data(confirmed)... |
[
"* x^2 + ... + b_m * x^{m + 1}|) `C`: Q(x) =",
"= gpu() if cuda else cpu() # register and configure weights (numerator and",
"denominator (Q). Default ``(5, 4)`` cuda (bool): whether to execute on cuda device.",
"on cuda device. NOTE: THIS PARAMETER IS CURRENTLY NOT CONSIDERED. CUDA GPUS ARE",
"w_denominato... |
[
"= torch.pow(x, 2).sum(1, keepdim=True).expand(m, n) yy = torch.pow(x, 2).sum(1, keepdim=True).expand(m, m).t() dist =",
"return num / denom # Source : https://github.com/earhian/Humpback-Whale-Identification-1st-/blob/master/models/triplet_loss.py def euclidean_dist(x, y): \"\"\"Computes Euclidean",
"= dist.cl... |
[
"for the sbahn_munich integration\"\"\" line_dict = { \"name\": \"S3\", \"color\": \"#333333\", \"text_color\": \"#444444\",",
"the sbahn_munich integration\"\"\" line_dict = { \"name\": \"S3\", \"color\": \"#333333\", \"text_color\": \"#444444\", }",
"\"\"\"Tests for the sbahn_munich integration\"\"\" line_dic... |
[
"Blueprint from flask import current_app from flask import render_template from flask_login import login_required",
"flask_login import login_required homestack = Blueprint(\"homestack\", __name__, url_prefix=\"/homestack\") @homestack.route(\"/\", methods=[\"GET\"]) @login_required def home():",
"flask import ... |
[
"{ 'dollars': forms.HiddenInput(attrs={ 'data-bind': 'value: dollars' }), 'last_4_digits': forms.TextInput(attrs={ 'data-bind': 'valueInit: card_digits, value:",
"forms.TextInput(attrs={ 'data-bind': 'value: logo_url, enable: urls_enabled' }), 'site_url': forms.TextInput(attrs={ 'data-bind': 'value: site_url, ena... |
[
"d_cols = { \"a\": \"ask\", \"b\": \"bid\", \"c\": \"change\", \"cid\": \"identity code\", \"cp\":",
"= { 'q': symbol, 'type': typ, 'output': output, } data = self._get_content(url, params)",
"def _get_content(self, url, params): #response = requests.get(url, params=params) response = self.session.get(url, para... |
[
"np import os class PreprocessGenerator: \"\"\" 数据预处理, 输入为csv格式, [label,ques] \"\"\" def __init__(self): self.l2i_i2l",
"= np.array(x), np.array(y) cnt = 0 yield (x_all, y_) x, y =[], []",
"len_all += 1 if len_all > 1: # 第一条是标签'label,ques'，不选择 line_sp = line.split(\",\") label_org",
"keras_textclassification.... |
[
"self.Flaky('Pixel_OffscreenCanvasTransferAfterStyleResize', ['mac', 'linux', 'win', 'android'], bug=735171) # TODO(junov): update reference images self.Fail('Pixel_CSSFilterEffects', ['mac'],",
"Retina self.Fail('Pixel_CSS3DBlueBox', ['mac'], bug=533690) # TODO(vmiura) check / generate reference images for Andro... |
[
"django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations =",
"primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.Date... |
[
"import setuptools #enables develop setuptools.setup( name='pysvm', version='0.1', description='PySVM : A NumPy implementation of",
"implementation of SVM based on SMO algorithm', author_email=\"<EMAIL>\", packages=['pysvm'], license='MIT License', long_description=open('README.md', encoding='utf-8').read(),",
... |
[
"CWD_PATH = os.getcwd() # Path to frozen detection graph .pb file, which contains",
"that is used # for object detection. PATH_TO_CKPT = os.path.join(CWD_PATH,MODEL_NAME,'frozen_inference_graph.pb') # Path to",
"category names, so that when our convolution # network predicts `5`, we know",
"= fid.read() od_gr... |
[
"data_collection.management.commands import BaseXpressDemocracyClubCsvImporter class Command(BaseXpressDemocracyClubCsvImporter): council_id = 'E06000027' addresses_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv'",
"from data_collection.management.commands import BaseXpressDemocracyClubCs... |
[
"def get(self, request, format=None): products = Product.objects.all()[0:4] serializer = ProductSerializer(products,many=True) return Response(serializer.data) class",
"def search(request): query = request.data.get('query', '') if query: products = Product.objects.filter(Q(name__icontains=query) | Q(description__... |
[
"aday=None, amonth=None, ayear=None, secaddr=None, secphone=None, note=None, id =None): self.fname = fname self.mname =",
"work=None, fax=None, email1=None, email2=None, email3=None, homepage=None, bday=None, bmonth=None, byear=None, aday=None, amonth=None, ayear=None, secaddr=None,",
"self.nick = nick self.tit... |
[
") self.assertEqual( len( messageHandler.messages ), 0 ) self.assertTrue( p.applicableTo( testObj, testObj.parameters() ) )",
"tearDown( self ) : savePath = os.path.abspath( os.path.join( os.path.dirname( __file__ ), \"data\", \"basicPreset\"",
") classes2 = testObj2.parameters()[\"c\"].getClass( True ) self.as... |
[
"can be # eaten) for ghost in self.game_state.data.agentStates[1:]: statespace_limits.append([1, self.layout.width - 2]) statespace_limits.append([1,",
"Domain from .PacmanPackage import layout, pacman, game, ghostAgents from .PacmanPackage import graphicsDisplay import",
"= len(agent_states) - 1 s = np.zeros( ... |
[
"'online/$year/$volume/foo' If the respective collection does not exist, it will be created before",
"working directory. template: Template which will be filled with year and volume. In",
"def get_working_directory(template): \"\"\"Return the collection which is the main working directory. template: Template",
... |
[
"- j) else: j = (i - 2) // 2 print(M + 2",
"1): if i % 2 == 1: j = (i - 1) //",
"if i % 2 == 1: j = (i - 1) // 2",
"for i in range(1, M + 1): if i % 2 == 1:",
"i % 2 == 1: j = (i - 1) // 2 print(1",
"1) // 2 print(1 + j, M + 1 - j) else: j",
"// 2 print(1 + j, M + 1 - j) else: j =",
"M + 1 - j) else: ... |
[
"License is distributed on an \"AS IS\" BASIS, WITHOUT # WARRANTIES OR CONDITIONS",
"writing, software # distributed under the License is distributed on an \"AS IS\"",
"return [name.strip() for name in fd.readlines()] with open('README.rst', 'r') as fd: long_description =",
"Unless required by applicable law ... |
[
"affiliates. # Copyright (c) HuggingFace Inc. team. # # Licensed under the Apache",
"it as a regular PyTorch Module and refer to the PyTorch documentation for",
"Unless required by applicable law or agreed to in writing, software # distributed",
"head is **not masked**, - 0 indicates the head is **masked**. i... |
[
") from eth._utils.datatypes import ( Configurable, ) from eth.db.backends.base import ( BaseAtomicDB, )",
"validate_sm_configuration(self.sm_configuration) pass self.chaindb = self.get_chaindb_class()(base_db) # # Helpers # @classmethod def get_chaindb_class(cls) ->",
"bool=True ) -> Tuple[BaseBeaconBlock, Tup... |
[
"device_access.send(line) time.sleep(1) output = device_access.recv(55000).decode('ascii') f3.write(output) \"\"\" THIS CODE IS FOR SINGLE COMMAND,",
"line.split(\" \") # print(data) addr = data[0] user = data[1] pwd = data[2]",
"SSH Client client = paramiko.SSHClient() # check dir(client) to find available opt... |
[
"if not (i % 6): # print(i, end=\" \") # 第二道题(17) out_l1 =",
"10 # k = n % 10 # if n == i **",
"= s1.split(' ') # l2 = [] # for i in l1: #",
"# 第一道题(16) # input(\"请输入(第一次):\") # s1 = input(\"请输入(第二次):\") # l1 = s1.split(' ')",
"0 global out_l1 for i in l1(): he1 += int(i)**2 if he1 >",
"k = n % 10 # if n ... |
[
"{ return Object.keys(defaults).reduce(function(acc, key) { if(typeof list[key] != 'undefined') return acc acc[key] =",
"a note in case this assumption turns out to be false — a",
"binary search is much more time-optimal for long lists, but adds a little",
"a function that accepts a program and returns a prog... |
[
"# 任务执行开始 PROCESS = 110 POLLING = 120 CALLBACK = 130 SUCCESS =",
"= 110 POLLING = 120 CALLBACK = 130 SUCCESS = 200 # 任务执行成功",
"130 SUCCESS = 200 # 任务执行成功 RETRY = 300 # 任务重试 FAILURE =",
"CALLBACK = 130 SUCCESS = 200 # 任务执行成功 RETRY = 300 # 任务重试",
"<filename>yzcore/templates/project_template/src/const/_job.py ... |
[
"boletoDados.data_documento tpl_data['data_documento'] = data_documento.strftime('%d/%m/%Y') tpl_data['cedente_endereco'] = boletoDados.cedente_endereco valor_doc = self._formataValorParaExibir(boletoDados.valor_documento) tpl_data['valor_documento'] = valor_doc",
"erro de nao uso do zip_longest else: from iterto... |
[
"i = 0 while i < 5: summary = summary + i print(summary)",
"< 5: summary = summary + i print(summary) i = i + 1",
"0 i = 0 while i < 5: summary = summary + i",
"= 0 i = 0 while i < 5: summary = summary +",
"= 0 while i < 5: summary = summary + i print(summary) i",
"i < 5: summary = summary + i print(summa... |
[
"import imtreat img = imtreat.imageManagerClass.openImageFunction(\"../images/soleil.png\", 0) img = imtreat.definedModesClass.detailEnhanceFunction(img) imtreat.imageManagerClass.saveImageFunction(\"/Téléchargements/\", \"image_1\", \".png\", img)"
] |
[
"of a Windows share. Related options: * \"instances_path\": The directory which will be",
"Possible values: * Name of the qemu-img executable, in case it is in",
"min=0, help=\"\"\" Wait soft reboot seconds Number of seconds to wait for instance",
"Unless required by applicable law or agreed to in writing, so... |
[
"path = input(\"Chemin d'écriture ? (words.txt) \") if path == \"\": path =",
"\") if path == \"\": path = \"./words.txt\" with open(path, \"w\", encoding=\"utf-8\") as",
"d'écriture ? (words.txt) \") if path == \"\": path = \"./words.txt\" with open(path,",
"= filter(lambda x: len(x) > 4, words_list.split('\... |
[
"os import subprocess from testfixtures import TempDirectory from simplegallery.upload.uploader_factory import get_uploader class AWSUploaderTestCase(unittest.TestCase):",
"self.assertFalse(uploader.check_location('')) @mock.patch('subprocess.run') def test_upload_gallery(self, subprocess_run): subprocess_run.ret... |
[
"font.setWeight(75) self.label_add_subject.setFont(font) self.label_add_subject.setObjectName(_fromUtf8(\"label_add_subject\")) self.lineEdit_subject_name = QtGui.QLineEdit(Dialog_add_subject) self.lineEdit_subject_name.setGeometry(QtCore.QRect(190, 230, 321, 31)) font = QtGui.QFont()",
"generated from reading ui... |
[
"receiver for handle the fact that test runner calls syncdb for several databases",
"We connect receiver here and not in unit test code because we need",
"That is, sequence of # actions would be: # # 1. Test runner",
"['app', 'create_models', 'verbosity', 'interactive', 'db'] SYNCDB_DATABASE = 'default' SYNCD... |
[
"use default_port = os.environ.get(\"SLURM_JOB_ID\") if default_port: # use the last 4 numbers in",
"it in if \"MASTER_PORT\" in os.environ: default_port = os.environ[\"MASTER_PORT\"] else: os.environ[\"MASTER_PORT\"] = str(default_port)",
"KIND, either express or implied. # See the License for the specific lan... |
[
"import os import math from trackball import TrackBall print(\"\"\"Trackball: Mouse Use the trackball",
"right, switch, state = trackball.read() # Send movements and clicks to xte if",
"<filename>examples/mouse.py #!/usr/bin/env python import time import os import math from trackball import TrackBall",
"sudo ... |
[
"layer(s). The function should return a tf.Tensor. learn_std (bool): Is std trainable. init_std",
"Initial value for std. adaptive_std (bool): Is std a neural network. If False,",
"should return a tf.Tensor. hidden_b_init (callable): Initializer function for the bias of intermediate",
"is at most the value of... |
[
"%.3f | Acc: %.3f%% (%d/%d)' % (test_loss/(batch_idx+1), 100.*float(correct_1)/float(total), correct_1, total)) return 100.*float(correct_1)/float(total),100.*float(correct_5)/float(total),test_loss acc1,acc5,loss=test()",
"dataset') parser.add_argument('--inputdir', help='path to input model') args = parser.pars... |
[
"} OPTIMIZER_FACTORY = { 'adadelta': optim.Adadelta, 'adagrad': optim.Adagrad, 'adam': optim.Adam, 'adamax': optim.Adamax, 'rmsprop':",
"'greedy': GreedySearch, 'beam': BeamSearch, } OPTIMIZER_FACTORY = { 'adadelta': optim.Adadelta, 'adagrad': optim.Adagrad, 'adam':",
"GreedySearch, 'beam': BeamSearch, } OPTIMI... |
[
"return distributions ############ # Tests ############ @pytest.mark.parametrize(\"distribution, w_dim\", get_distributions_with_w_dim()) def test_local_kls(distribution, w_dim): lv",
"KIND, either express or implied. # See the License for the specific language",
"# Tests ############ @pytest.mark.parametrize(\... |
[
"retrieve trust relationships (auth: only creator and admins allowed) # POST /trust with",
"= config.config() relationships = myself.getTrustRelationships( relationship=relationship, peerid=peerid) if not relationships: self.response.set_status(404, 'Not found')",
"and admins allowed) # POST /trust with json bo... |
[
"___ | |_ 110011 00110110 | /| | | ___ \\/ _ \\|",
"in the GUI no longer breaks the config. \"\"\", '1.3.0': \"\"\" Accurate ball",
"10100 | ___ \\ | | ___ \\ | | 00101 110011 |",
"is missing - Loadout configuration is broken Thanks to ccman32 and dtracers for",
"now get information about the ball's status ... |
[
"nn.AdaptiveAvgPool2d((1, 1)) self.fc = None if num_classes is None else nn.Linear(in_plane, num_classes) if",
"the root directory of this source tree. from typing import Any, Dict import",
"Inc. and its affiliates. # # This source code is licensed under the",
"ClassyHead, register_head @register_head(\"fully... |
[
"print(entry[0].name,entry[1]) if __name__ == \"__main__\": print(\"*** Task 2C: CUED Part IA Flood Warning",
"= stations_highest_rel_level(stations,10) for entry in warning_stations: print(entry[0].name,entry[1]) if __name__ == \"__main__\": print(\"*** Task",
"if __name__ == \"__main__\": print(\"*** Task 2C:... |
[
"copied via the `__copy_create__()` method. All variables, that could not be set via",
"here. This method must be overridden, if the constructor takes parameters. Returns -------",
"__all__ = [\"Copyable\"] import abc class Copyable(metaclass=abc.ABCMeta): \"\"\" Base class for all objects,",
"are then copied... |
[
"} @property def available(self) -> bool: return self._available @property def name(self): \"\"\"Return the",
"import List from homeassistant.components.binary_sensor import ( BinarySensorEntity, DEVICE_CLASS_MOTION ) from homeassistant.config_entries import ConfigEntry",
"= self._client.get_info(self._device) ... |
[
"# ------------------------------------------------------------ for sds in self.SDS: if self.verb: print 'sds',self.SDS.index(sds) v = hfile.select(sds).get()",
"array(lon) lat = array(lat) # List of HDF files for a given date",
"--------------------------------- self.read_BRDF() # Result #--- def _findNearest(... |
[
"backend does not support TimeDistributed and RNN yet') def test_TimeDistributed_trainable(): # test layers",
"3 units = 3 X = [np.random.rand(samples, timesteps, dim)] if merge_mode == 'sum':",
"s_bk_np, c_np]) weights = model.get_weights() config = layer.get_config() with CustomObjectScope(custom_objects): la... |
[
"import absolute_import, division, print_function, with_statement import errno import socket from tornado.platform import interface",
"that port (\"Address already in # use\") despite that the OS picked it.",
"errno import socket from tornado.platform import interface class Waker(interface.Waker): \"\"\"Create ... |
[
"options.image_name # Some visual indication that it works, for headless setups (green tape)",
"next row by a given latitude, also specified by user 6) sleeps for",
"0))) longitude_index = min(cols - 1, max(0, (int)(((loc[1] - -180) / (180 -",
"options.num_leds i_name = options.image_name # Some visual indica... |
[
"in data: # flatten list values if isinstance(data[key], list): if len(data[key]) > 0:",
"FieldMaps.map_key_value(field_key, data[key]) # manually add Fire Rating and proposed Fire Rating if field_key",
"fields \"\"\" output = {} if data: data = self.set_pts_fields(data) for key in",
"csv elif isinstance(data... |
[
"def __init__(self): self.pred = TorchPredictor.from_checkpoint(result.checkpoint) def __call__(self, x): return self.pred.predict(x, dtype=torch.float) predictions =",
"1) ) def __call__(self, x): return self.pred.predict(x, dtype=torch.float) predict_dataset = ray.data.range(3) predictions =",
"pytest import ... |
[
"IxNetwork model allows for multiple method Signatures with the same name while python",
"value) @property def LearnSendMacOnly(self): # type: () -> bool \"\"\" Returns ------- -",
"the property is accessed. \"\"\" __slots__ = () _SDM_NAME = 'learnFrames' _SDM_ATT_MAP =",
"bool \"\"\" Returns ------- - bool: ... |
[
"from core import models class AssetSerializer(serializers.ModelSerializer): class Meta: model = models.Asset fields =",
"import serializers from core import models class AssetSerializer(serializers.ModelSerializer): class Meta: model = models.Asset",
"from rest_framework import serializers from core import mod... |
[
"a(2). d(2,2,1). okay(X):- c(X), #count{V:a(V),d(V,X,1)} = 1. ouch(X):- p(X), #count{V:a(V),d(V,X,1)} = 1. \"\"\"",
"#count{V:a(V),d(V,X,1)} = 1. \"\"\" output = \"\"\" {a(2), c(2), d(2,2,1), okay(2), p(1)} \"\"\"",
"\"\"\" c(2). p(1). a(2). d(2,2,1). okay(X):- c(X), #count{V:a(V),d(V,X,1)} = 1. ouch(X):- p(X),... |
[
"+ bot.config.BAIDUKey sign = hashlib.md5(sign.encode()).hexdigest() myurl = ( myurl + \"?appid=\" + bot.config.BAIDUAPI",
"import hmac import random, sys import hashlib import binascii import urllib bot =",
"urllib.parse.quote(q) + \"&from=\" + fromLang + \"&to=\" + toLang + \"&salt=\" + str(salt)",
"import ... |
[
"lib.set_add_rowmode.argtypes = [c_void_p, c_ubyte] lib.set_add_rowmode.restype = c_ubyte lib.set_maxim.argtypes = [c_void_p] lib.write_lp.argtypes = [c_void_p,",
"assert self.lp != 0, \"Can't construct a new LpSolve model\" self.colbuff = (c_int",
"new LpSolve model\" self.colbuff = (c_int * maxvars)() self.ro... |
[
"'TEST', AMP_ID, vrrp_ip=VRRP_IP, ha_ip=HA_IP, vrrp_port_id=VRRP_PORT_ID, ha_port_id=HA_PORT_ID, vrrp_id=VRRP_ID) @mock.patch('octavia.db.repositories.AmphoraRepository.associate') def test_associate_failover_amphora_with_lb_id( self, mock_associate, mock_generate_uuid,",
"mock_listener_repo_update, mock_amphora_... |
[
"'url': 'architect'} ] capitales_du_monde = [ {'id': '183', 'nom': 'akmeneje'},#Akmenė {'id': '184', 'nom':",
"if number_of_pages > 1: for i in range(2, number_of_pages + 1): url_of_one_page_of_results =",
"content of html_doc soup = BeautifulSoup(html.content, 'html.parser') if soup.find('a', {'itemprop': 'ema... |
[
"= DagsterInstance.from_ref(InstanceRef.from_dir(test_dir)) runs = instance.get_runs() with pytest.raises( DagsterInstanceMigrationRequired, match=re.escape( 'Instance is out of",
"'c7a6c4d7-6c88-46d0-8baa-d4937c3cefe5). Database is at revision None, head is ' '567bc23fd1ac. Please run `dagster",
"re import pyt... |
[
"By Category') p.get_legend().remove() plt.savefig('../charts/category.png') def group_by_time_of_day(df): grouped = df.groupby(['TIME_OF_DAY']).size().to_frame('Crimes') p = grouped.plot.pie(y='Crimes', labels=['Day',",
"Grouped By Category') p.get_legend().remove() plt.savefig('../charts/category.png') def grou... |
[
"\"rule-x\": [[0, 1, 4, 5], [0, 2, 4, 5], [0, 3, 4, 5],",
"= { \"seqpav\": [[0, 1, 3]], \"av\": [[0, 1, 2]], \"sav\": [[0, 1,",
"= [[0, 4, 5], [0], [1, 4, 5], [1], [2, 4, 5], [2],",
"test_mwrules_correct_advanced_1(self): from preferences import Profile self.longMessage = True committeesize = 4 profile =",
... |
[
"== ticker) try: t_13_price = merged_df.loc[ t_13_condtion & ticker_condition ]['close'].values[0] previous_month = me_months[me_months.index(month)",
"'139409', '139410', '139411', '139412', '139501', '139502', '139503', '139504', '139505', '139506', '139507', '139508', '139509',",
"'BL' ]['ticker_num'].tolist... |
[
"s3://{1}/{2}'.format( mmdb, s3bucket_name, s3obj)) def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): # https://docs.aws.amazon.com/ja_jp/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html",
"s3.Bucket(s3bucket_name) url = 'https://downl... |
[
"in this basis def calculateBasisOffset(self,x1,x2,basis): dx = [(x2[j] - x1[j]) for j in",
"Unless required by applicable law or agreed to in writing, software # distributed",
"Save the position offset # Calculate a new start time relativeSlaveTime = slaveTime[i]",
"export laws and regulations. # The user ha... |
[
"range(n): cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FULL_DECK:",
"cards.append(self.draw()) return cards def __str__(self): return Card.print_pretty_cards(self.cards) @staticmethod def GetFullDeck(): if Deck._FUL... |
[
"the current scopeset if we do not already have on. :rtype: string or",
"list): raise ValueError('Scopes must be a list') token = self._get_token_with_scopes(scopes) if token: #",
"by # the user! Also, even if it has expired, we might still",
"due to a server error or because the account or token was lacking"... |
[
"and this permission notice shall be included in all # copies of this",
"elem.append(NIL(\"Schema\", frmt.schema)) return elem #------------------------------------------------------------------------------- def _encode_bbox(prm, is_input): return NIL(\"BoundingBoxData\" if is_input else",
"or title_required: e... |
[
"Error uploading ' + archive_file + ' to ' + bucket + '",
"downloading ' + key + ' from ' + bucket + ' bucket.",
"data object to archive. This value is required. ''' if bucket is None",
"archive_key: The vp_save data's location (S3 bucket and file path). This value is",
"None or len(bucket) <= 0: raise Valu... |
[
"plt.figure(figsize=(5,2)) bax = brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x",
"= brokenaxes(xlims=((0, .1), (.4, .7)), ylims=((-1, .7), (.79, 1)), hspace=.05) x = np.linspace(0,",
"plt from brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax",... |
[
"suffix = tmp[1] ln = suffix ln_org = \"\" if ln in ln_map:",
"wiki_path = \"data/wikidata/\"+ln+\".json\" db = {} wiki = {} if os.path.exists(db_path): with open(db_path)",
"{} if os.path.exists(db_path): with open(db_path) as f: db = json.load(f) if os.path.exists(wiki_path): with",
"RDFS.label, Literal(lab... |
[
"configs[i] for i in range(3)} print_mock.assert_any_call(json.dumps(all_configs, indent=4, sort_keys=True)) @patch('utils.open_connection') @patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print')",
"bootloader_read_config.main() write_command_... |
[
"in error.missing_perms))) elif isinstance(error, (commands.CommandNotFound, commands.CheckFailure)): return elif isinstance(error, commands.CommandInvokeError): if isinstance(error.original, discord.HTTPException):",
"ctx.send(embed=msg) else: await ctx.send(msg) # Commands @bot.command() async def helplb(ctx): ... |
[
"result: \"WorkflowExecutionResult\" = ray.get( workflow_manager.run_or_resume.remote( workflow_id, ignore_existing=False)) logger.info(f\"Workflow job {workflow_id} resumed.\") return flatten_workflow_output(workflow_id,",
"such workflow_id {workflow_id}\") return meta.status def list_all(status_filter: Set[Work... |
[
"from .compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature #",
".compose import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature # noqa",
"from .signature import BinarySignature, Signature, MemorySignature # noqa from .username import... |
[
"1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return np.array([v_x,v_y,-f*x,-f*y]) def RK4(f,u,dt): k1=f(u)*dt k2=f(u+0.5*k1)*dt k3=f(u+0.5*k2)*dt k4=f(u+k3)*dt return",
"y dt=0.1 t = np.arange(0,10,dt) y0=np.array([10, 0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T",
"= u r=np.hypo... |
[
"factories for all installed apps' def handle(self, *args, **options): created_files = [] for",
"apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for created_file ... |
[
"chunks, 'join': {'__mem_gb' : 1}} def main(args, outs): if args.skip: return matrix =",
"lib_constants NUM_THREADS_MIN = 4 #TODO Not clear why this stage takes > 1",
"h5 diffexp_h5, out path diffexp_csv, src py \"stages/analyzer/run_differential_expression\", ) split using ( in",
"NUM_THREADS_MIN) threads = ... |
[
"not hashable and cannot be put into a set. Examples ======== >>> from",
"a certificate for the graph gr adjacency list The graph is assumed to",
">>> _verify_normal_closure(S, A, closure=A) True See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.normal_closure \"\"\" if closure is",
">>> b = ... |
[
"recaptcha_secret = \"\" # recaptcha secret for verification duplicate_annotations = False # Should",
"training videos to be considered recaptcha_secret = \"\" # recaptcha secret for verification",
"annotations? import os.path import sys sys.path.append(os.path.dirname(os.path.abspath(__file__))) # TODO: remove... |
[
"inaccurate. If you're having trouble with this class, don't waste your time, just",
"function and cache the result. _localtime = None def get_default_timezone(): \"\"\" Returns the",
"of the currently active time zone. \"\"\" return _get_timezone_name(get_current_timezone()) def _get_timezone_name(timezone): \... |
[
"import processes def test_wps_caps(): client = client_for(Service(processes=processes)) resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names",
"= resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download... |
[
"- Production/Stable\", \"License :: OSI Approved :: MIT License\", \"Operating System :: MacOS\",",
":: 3.5\", \"Programming Language :: Python :: 3.6\", \"Programming Language :: Python ::",
"\"Programming Language :: Python :: Implementation :: PyPy\", \"Topic :: Software Development ::",
"Language :: Pyth... |
[
"\"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): return dsl.ContainerOp( name='resultsgen', image=\"{}:{}\".format(TRACKML_IMAGE,",
"= \"1\" TRACKML_IMAGE = \"gcr.io/mcas-195423/trackml_master_trackml\" TRACKML_IMAGE_VERSION = \"1\" def train_op(... |
[
"__name__ == '__main__': try: parser = argparse.ArgumentParser() parser.add_argument('-n', '--network', action='store', required=True, help='Network name",
"= infrabbitmq_factory.event_publisher_json_serializer() secs = 0 mins = 0 rabbitmq_exceptions = (RabbitMQError, puka.AMQPError, KeyError,)",
"= argparse.Ar... |
[
"Unless required by applicable law or agreed to in writing, software # distributed",
"by a model-specific keyword (bert, )... \"\"\" # self._tie_or_clone_weights(self.encoder, self.decoder) pass @classmethod def",
"To train the model, you need to first set it back in training",
"use instead of a state diction... |
[
"= default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl",
"PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem, branch_mulher]",
"18, 20), 'email': ['<EMAIL>', '<EMAIL>... |
[
"description = '%s %s' % (\"--\", \"Outputs in Tcl Shell the list with",
"args: argument = args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else:",
"# Dictionary of types from Tcl command, needs to be ordered arg_names =",
"Tcl command, needs to be ordere... |