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pypyr/pypyr-cli
pypyr/parser/keyvaluepairs.py
get_parsed_context
def get_parsed_context(context_arg): """Parse input context string and returns context as dictionary.""" if not context_arg: logger.debug("pipeline invoked without context arg set. For " "this keyvaluepairs parser you're looking for " "something like: " "pypyr pipelinename 'key1=value1,key2=value2'.") return None logger.debug("starting") # for each comma-delimited element, project key=value return dict(element.split('=') for element in context_arg.split(','))
python
def get_parsed_context(context_arg): """Parse input context string and returns context as dictionary.""" if not context_arg: logger.debug("pipeline invoked without context arg set. For " "this keyvaluepairs parser you're looking for " "something like: " "pypyr pipelinename 'key1=value1,key2=value2'.") return None logger.debug("starting") # for each comma-delimited element, project key=value return dict(element.split('=') for element in context_arg.split(','))
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Parse input context string and returns context as dictionary.
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train
https://github.com/pypyr/pypyr-cli/blob/4003f999cd5eb030b4c7407317de728f5115a80f/pypyr/parser/keyvaluepairs.py#L18-L29
pypyr/pypyr-cli
pypyr/steps/fetchjson.py
run_step
def run_step(context): """Load a json file into the pypyr context. json parsed from the file will be merged into the pypyr context. This will overwrite existing values if the same keys are already in there. I.e if file json has {'eggs' : 'boiled'} and context {'eggs': 'fried'} already exists, returned context['eggs'] will be 'boiled'. The json should not be an array [] on the top level, but rather an Object. Args: context: pypyr.context.Context. Mandatory. The following context key must exist - fetchJson - path. path-like. Path to file on disk. - key. string. If exists, write json structure to this context key. Else json writes to context root. Also supports a passing path as string to fetchJson, but in this case you won't be able to specify a key. All inputs support formatting expressions. Returns: None. updates context arg. Raises: FileNotFoundError: take a guess pypyr.errors.KeyNotInContextError: fetchJson.path missing in context. pypyr.errors.KeyInContextHasNoValueError: fetchJson.path exists but is None. """ logger.debug("started") deprecated(context) context.assert_key_has_value(key='fetchJson', caller=__name__) fetch_json_input = context.get_formatted('fetchJson') if isinstance(fetch_json_input, str): file_path = fetch_json_input destination_key_expression = None else: context.assert_child_key_has_value(parent='fetchJson', child='path', caller=__name__) file_path = fetch_json_input['path'] destination_key_expression = fetch_json_input.get('key', None) logger.debug(f"attempting to open file: {file_path}") with open(file_path) as json_file: payload = json.load(json_file) if destination_key_expression: destination_key = context.get_formatted_iterable( destination_key_expression) logger.debug(f"json file loaded. Writing to context {destination_key}") context[destination_key] = payload else: if not isinstance(payload, MutableMapping): raise TypeError( 'json input should describe an object at the top ' 'level when fetchJsonKey isn\'t specified. You should have ' 'something like {"key1": "value1", "key2": "value2"} ' 'in the json top-level, not ["value1", "value2"]') logger.debug("json file loaded. Merging into pypyr context. . .") context.update(payload) logger.info(f"json file written into pypyr context. Count: {len(payload)}") logger.debug("done")
python
def run_step(context): """Load a json file into the pypyr context. json parsed from the file will be merged into the pypyr context. This will overwrite existing values if the same keys are already in there. I.e if file json has {'eggs' : 'boiled'} and context {'eggs': 'fried'} already exists, returned context['eggs'] will be 'boiled'. The json should not be an array [] on the top level, but rather an Object. Args: context: pypyr.context.Context. Mandatory. The following context key must exist - fetchJson - path. path-like. Path to file on disk. - key. string. If exists, write json structure to this context key. Else json writes to context root. Also supports a passing path as string to fetchJson, but in this case you won't be able to specify a key. All inputs support formatting expressions. Returns: None. updates context arg. Raises: FileNotFoundError: take a guess pypyr.errors.KeyNotInContextError: fetchJson.path missing in context. pypyr.errors.KeyInContextHasNoValueError: fetchJson.path exists but is None. """ logger.debug("started") deprecated(context) context.assert_key_has_value(key='fetchJson', caller=__name__) fetch_json_input = context.get_formatted('fetchJson') if isinstance(fetch_json_input, str): file_path = fetch_json_input destination_key_expression = None else: context.assert_child_key_has_value(parent='fetchJson', child='path', caller=__name__) file_path = fetch_json_input['path'] destination_key_expression = fetch_json_input.get('key', None) logger.debug(f"attempting to open file: {file_path}") with open(file_path) as json_file: payload = json.load(json_file) if destination_key_expression: destination_key = context.get_formatted_iterable( destination_key_expression) logger.debug(f"json file loaded. Writing to context {destination_key}") context[destination_key] = payload else: if not isinstance(payload, MutableMapping): raise TypeError( 'json input should describe an object at the top ' 'level when fetchJsonKey isn\'t specified. You should have ' 'something like {"key1": "value1", "key2": "value2"} ' 'in the json top-level, not ["value1", "value2"]') logger.debug("json file loaded. Merging into pypyr context. . .") context.update(payload) logger.info(f"json file written into pypyr context. Count: {len(payload)}") logger.debug("done")
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train
https://github.com/pypyr/pypyr-cli/blob/4003f999cd5eb030b4c7407317de728f5115a80f/pypyr/steps/fetchjson.py#L10-L82
pypyr/pypyr-cli
pypyr/steps/fetchjson.py
deprecated
def deprecated(context): """Create new style in params from deprecated.""" if 'fetchJsonPath' in context: context.assert_key_has_value(key='fetchJsonPath', caller=__name__) context['fetchJson'] = {'path': context['fetchJsonPath']} if 'fetchJsonKey' in context: context['fetchJson']['key'] = context.get('fetchJsonKey', None) logger.warning("fetchJsonPath and fetchJsonKey " "are deprecated. They will stop working upon the next " "major release. Use the new context key fetchJson " "instead. It's a lot better, promise! For the moment " "pypyr is creating the new fetchJson key for you " "under the hood.")
python
def deprecated(context): """Create new style in params from deprecated.""" if 'fetchJsonPath' in context: context.assert_key_has_value(key='fetchJsonPath', caller=__name__) context['fetchJson'] = {'path': context['fetchJsonPath']} if 'fetchJsonKey' in context: context['fetchJson']['key'] = context.get('fetchJsonKey', None) logger.warning("fetchJsonPath and fetchJsonKey " "are deprecated. They will stop working upon the next " "major release. Use the new context key fetchJson " "instead. It's a lot better, promise! For the moment " "pypyr is creating the new fetchJson key for you " "under the hood.")
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Create new style in params from deprecated.
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train
https://github.com/pypyr/pypyr-cli/blob/4003f999cd5eb030b4c7407317de728f5115a80f/pypyr/steps/fetchjson.py#L85-L100
bradmontgomery/django-querycount
querycount/middleware.py
QueryCountMiddleware._ignore_request
def _ignore_request(self, path): """Check to see if we should ignore the request.""" return any([ re.match(pattern, path) for pattern in QC_SETTINGS['IGNORE_REQUEST_PATTERNS'] ])
python
def _ignore_request(self, path): """Check to see if we should ignore the request.""" return any([ re.match(pattern, path) for pattern in QC_SETTINGS['IGNORE_REQUEST_PATTERNS'] ])
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Check to see if we should ignore the request.
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train
https://github.com/bradmontgomery/django-querycount/blob/61a380d98bc55e926c011367ecc2031102c3484c/querycount/middleware.py#L83-L87
bradmontgomery/django-querycount
querycount/middleware.py
QueryCountMiddleware._ignore_sql
def _ignore_sql(self, query): """Check to see if we should ignore the sql query.""" return any([ re.search(pattern, query.get('sql')) for pattern in QC_SETTINGS['IGNORE_SQL_PATTERNS'] ])
python
def _ignore_sql(self, query): """Check to see if we should ignore the sql query.""" return any([ re.search(pattern, query.get('sql')) for pattern in QC_SETTINGS['IGNORE_SQL_PATTERNS'] ])
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Check to see if we should ignore the sql query.
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train
https://github.com/bradmontgomery/django-querycount/blob/61a380d98bc55e926c011367ecc2031102c3484c/querycount/middleware.py#L89-L93
bradmontgomery/django-querycount
querycount/middleware.py
QueryCountMiddleware._duplicate_queries
def _duplicate_queries(self, output): """Appends the most common duplicate queries to the given output.""" if QC_SETTINGS['DISPLAY_DUPLICATES']: for query, count in self.queries.most_common(QC_SETTINGS['DISPLAY_DUPLICATES']): lines = ['\nRepeated {0} times.'.format(count)] lines += wrap(query) lines = "\n".join(lines) + "\n" output += self._colorize(lines, count) return output
python
def _duplicate_queries(self, output): """Appends the most common duplicate queries to the given output.""" if QC_SETTINGS['DISPLAY_DUPLICATES']: for query, count in self.queries.most_common(QC_SETTINGS['DISPLAY_DUPLICATES']): lines = ['\nRepeated {0} times.'.format(count)] lines += wrap(query) lines = "\n".join(lines) + "\n" output += self._colorize(lines, count) return output
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Appends the most common duplicate queries to the given output.
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train
https://github.com/bradmontgomery/django-querycount/blob/61a380d98bc55e926c011367ecc2031102c3484c/querycount/middleware.py#L142-L150
bradmontgomery/django-querycount
querycount/middleware.py
QueryCountMiddleware._calculate_num_queries
def _calculate_num_queries(self): """ Calculate the total number of request and response queries. Used for count header and count table. """ request_totals = self._totals("request") response_totals = self._totals("response") return request_totals[2] + response_totals[2]
python
def _calculate_num_queries(self): """ Calculate the total number of request and response queries. Used for count header and count table. """ request_totals = self._totals("request") response_totals = self._totals("response") return request_totals[2] + response_totals[2]
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Calculate the total number of request and response queries. Used for count header and count table.
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train
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bradmontgomery/django-querycount
querycount/qc_settings.py
_process_settings
def _process_settings(**kwargs): """ Apply user supplied settings. """ # If we are in this method due to a signal, only reload for our settings setting_name = kwargs.get('setting', None) if setting_name is not None and setting_name != 'QUERYCOUNT': return # Support the old-style settings if getattr(settings, 'QUERYCOUNT_THRESHOLDS', False): QC_SETTINGS['THRESHOLDS'] = settings.QUERYCOUNT_THRESHOLDS # Apply new-style settings if not getattr(settings, 'QUERYCOUNT', False): return # Duplicate display is a special case, configure it specifically if 'DISPLAY_DUPLICATES' in settings.QUERYCOUNT: duplicate_settings = settings.QUERYCOUNT['DISPLAY_DUPLICATES'] if duplicate_settings is not None: duplicate_settings = int(duplicate_settings) QC_SETTINGS['DISPLAY_DUPLICATES'] = duplicate_settings # Apply the rest of the setting overrides for key in ['THRESHOLDS', 'IGNORE_REQUEST_PATTERNS', 'IGNORE_SQL_PATTERNS', 'IGNORE_PATTERNS', 'RESPONSE_HEADER']: if key in settings.QUERYCOUNT: QC_SETTINGS[key] = settings.QUERYCOUNT[key]
python
def _process_settings(**kwargs): """ Apply user supplied settings. """ # If we are in this method due to a signal, only reload for our settings setting_name = kwargs.get('setting', None) if setting_name is not None and setting_name != 'QUERYCOUNT': return # Support the old-style settings if getattr(settings, 'QUERYCOUNT_THRESHOLDS', False): QC_SETTINGS['THRESHOLDS'] = settings.QUERYCOUNT_THRESHOLDS # Apply new-style settings if not getattr(settings, 'QUERYCOUNT', False): return # Duplicate display is a special case, configure it specifically if 'DISPLAY_DUPLICATES' in settings.QUERYCOUNT: duplicate_settings = settings.QUERYCOUNT['DISPLAY_DUPLICATES'] if duplicate_settings is not None: duplicate_settings = int(duplicate_settings) QC_SETTINGS['DISPLAY_DUPLICATES'] = duplicate_settings # Apply the rest of the setting overrides for key in ['THRESHOLDS', 'IGNORE_REQUEST_PATTERNS', 'IGNORE_SQL_PATTERNS', 'IGNORE_PATTERNS', 'RESPONSE_HEADER']: if key in settings.QUERYCOUNT: QC_SETTINGS[key] = settings.QUERYCOUNT[key]
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https://github.com/bradmontgomery/django-querycount/blob/61a380d98bc55e926c011367ecc2031102c3484c/querycount/qc_settings.py#L23-L55
xiyouMc/ncmbot
ncmbot/core.py
login
def login(password, phone=None, email=None, rememberLogin=True): """ 登录接口,返回 :class:'Response' 对象 :param password: 网易云音乐的密码 :param phone: (optional) 手机登录 :param email: (optional) 邮箱登录 :param rememberLogin: (optional) 是否记住密码,默认 True """ if (phone is None) and (email is None): raise ParamsError() if password is None: raise ParamsError() r = NCloudBot() # r.username = phone or email md5 = hashlib.md5() md5.update(password) password = md5.hexdigest() print password r.data = {'password': password, 'rememberLogin': rememberLogin} if phone is not None: r.data['phone'] = phone r.method = 'LOGIN' else: r.data['username'] = email r.method = 'EMAIL_LOGIN' r.send() return r.response
python
def login(password, phone=None, email=None, rememberLogin=True): """ 登录接口,返回 :class:'Response' 对象 :param password: 网易云音乐的密码 :param phone: (optional) 手机登录 :param email: (optional) 邮箱登录 :param rememberLogin: (optional) 是否记住密码,默认 True """ if (phone is None) and (email is None): raise ParamsError() if password is None: raise ParamsError() r = NCloudBot() # r.username = phone or email md5 = hashlib.md5() md5.update(password) password = md5.hexdigest() print password r.data = {'password': password, 'rememberLogin': rememberLogin} if phone is not None: r.data['phone'] = phone r.method = 'LOGIN' else: r.data['username'] = email r.method = 'EMAIL_LOGIN' r.send() return r.response
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L218-L245
xiyouMc/ncmbot
ncmbot/core.py
user_play_list
def user_play_list(uid, offset=0, limit=1000): """获取用户歌单,包含收藏的歌单 :param uid: 用户的ID,可通过登录或者其他接口获取 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 1000 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_PLAY_LIST' r.data = {'offset': offset, 'uid': uid, 'limit': limit, 'csrf_token': ''} r.send() return r.response
python
def user_play_list(uid, offset=0, limit=1000): """获取用户歌单,包含收藏的歌单 :param uid: 用户的ID,可通过登录或者其他接口获取 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 1000 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_PLAY_LIST' r.data = {'offset': offset, 'uid': uid, 'limit': limit, 'csrf_token': ''} r.send() return r.response
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L248-L261
xiyouMc/ncmbot
ncmbot/core.py
user_dj
def user_dj(uid, offset=0, limit=30): """获取用户电台数据 :param uid: 用户的ID,可通过登录或者其他接口获取 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 30 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_DJ' r.data = {'offset': offset, 'limit': limit, "csrf_token": ""} r.params = {'uid': uid} r.send() return r.response
python
def user_dj(uid, offset=0, limit=30): """获取用户电台数据 :param uid: 用户的ID,可通过登录或者其他接口获取 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 30 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_DJ' r.data = {'offset': offset, 'limit': limit, "csrf_token": ""} r.params = {'uid': uid} r.send() return r.response
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[ "获取用户电台数据" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L264-L279
xiyouMc/ncmbot
ncmbot/core.py
search
def search(keyword, type=1, offset=0, limit=30): """搜索歌曲,支持搜索歌曲、歌手、专辑等 :param keyword: 关键词 :param type: (optional) 搜索类型,1: 单曲, 100: 歌手, 1000: 歌单, 1002: 用户 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 30 """ if keyword is None: raise ParamsError() r = NCloudBot() r.method = 'SEARCH' r.data = { 's': keyword, 'limit': str(limit), 'type': str(type), 'offset': str(offset) } r.send() return r.response
python
def search(keyword, type=1, offset=0, limit=30): """搜索歌曲,支持搜索歌曲、歌手、专辑等 :param keyword: 关键词 :param type: (optional) 搜索类型,1: 单曲, 100: 歌手, 1000: 歌单, 1002: 用户 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 30 """ if keyword is None: raise ParamsError() r = NCloudBot() r.method = 'SEARCH' r.data = { 's': keyword, 'limit': str(limit), 'type': str(type), 'offset': str(offset) } r.send() return r.response
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[ "搜索歌曲,支持搜索歌曲、歌手、专辑等" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L282-L302
xiyouMc/ncmbot
ncmbot/core.py
user_follows
def user_follows(uid, offset='0', limit=30): """获取用户关注列表 :param uid: 用户的ID,可通过登录或者其他接口获取 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 30 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_FOLLOWS' r.params = {'uid': uid} r.data = {'offset': offset, 'limit': limit, 'order': True} r.send() return r.response
python
def user_follows(uid, offset='0', limit=30): """获取用户关注列表 :param uid: 用户的ID,可通过登录或者其他接口获取 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 30 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_FOLLOWS' r.params = {'uid': uid} r.data = {'offset': offset, 'limit': limit, 'order': True} r.send() return r.response
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[ "获取用户关注列表" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L305-L320
xiyouMc/ncmbot
ncmbot/core.py
user_event
def user_event(uid): """获取用户动态 :param uid: 用户的ID,可通过登录或者其他接口获取 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_EVENT' r.params = {'uid': uid} r.data = {'time': -1, 'getcounts': True, "csrf_token": ""} r.send() return r.response
python
def user_event(uid): """获取用户动态 :param uid: 用户的ID,可通过登录或者其他接口获取 """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_EVENT' r.params = {'uid': uid} r.data = {'time': -1, 'getcounts': True, "csrf_token": ""} r.send() return r.response
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获取用户动态 :param uid: 用户的ID,可通过登录或者其他接口获取
[ "获取用户动态" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L345-L358
xiyouMc/ncmbot
ncmbot/core.py
user_record
def user_record(uid, type=0): """获取用户的播放列表,必须登录 :param uid: 用户的ID,可通过登录或者其他接口获取 :param type: (optional) 数据类型,0:获取所有记录,1:获取 weekData """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_RECORD' r.data = {'type': type, 'uid': uid, "csrf_token": ""} r.send() return r.response
python
def user_record(uid, type=0): """获取用户的播放列表,必须登录 :param uid: 用户的ID,可通过登录或者其他接口获取 :param type: (optional) 数据类型,0:获取所有记录,1:获取 weekData """ if uid is None: raise ParamsError() r = NCloudBot() r.method = 'USER_RECORD' r.data = {'type': type, 'uid': uid, "csrf_token": ""} r.send() return r.response
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[ "获取用户的播放列表", "必须登录" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L361-L374
xiyouMc/ncmbot
ncmbot/core.py
event
def event(): """获取好友的动态,包括分享视频、音乐、动态等 """ r = NCloudBot() r.method = 'EVENT' r.data = {"csrf_token": ""} r.send() return r.response
python
def event(): """获取好友的动态,包括分享视频、音乐、动态等 """ r = NCloudBot() r.method = 'EVENT' r.data = {"csrf_token": ""} r.send() return r.response
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获取好友的动态,包括分享视频、音乐、动态等
[ "获取好友的动态,包括分享视频、音乐、动态等" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L377-L386
xiyouMc/ncmbot
ncmbot/core.py
top_playlist_highquality
def top_playlist_highquality(cat='全部', offset=0, limit=20): """获取网易云音乐的精品歌单 :param cat: (optional) 歌单类型,默认 ‘全部’,比如 华语、欧美等 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 20 """ r = NCloudBot() r.method = 'TOP_PLAYLIST_HIGHQUALITY' r.data = {'cat': cat, 'offset': offset, 'limit': limit} r.send() return r.response
python
def top_playlist_highquality(cat='全部', offset=0, limit=20): """获取网易云音乐的精品歌单 :param cat: (optional) 歌单类型,默认 ‘全部’,比如 华语、欧美等 :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 20 """ r = NCloudBot() r.method = 'TOP_PLAYLIST_HIGHQUALITY' r.data = {'cat': cat, 'offset': offset, 'limit': limit} r.send() return r.response
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[ "获取网易云音乐的精品歌单" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L390-L402
xiyouMc/ncmbot
ncmbot/core.py
play_list_detail
def play_list_detail(id, limit=20): """获取歌单中的所有音乐。由于获取精品中,只能看到歌单名字和 ID 并没有歌单的音乐,因此增加该接口传入歌单 ID 获取歌单中的所有音乐. :param id: 歌单的ID :param limit: (optional) 数据上限多少行,默认 20 """ if id is None: raise ParamsError() r = NCloudBot() r.method = 'PLAY_LIST_DETAIL' r.data = {'id': id, 'limit': limit, "csrf_token": ""} r.send() return r.response
python
def play_list_detail(id, limit=20): """获取歌单中的所有音乐。由于获取精品中,只能看到歌单名字和 ID 并没有歌单的音乐,因此增加该接口传入歌单 ID 获取歌单中的所有音乐. :param id: 歌单的ID :param limit: (optional) 数据上限多少行,默认 20 """ if id is None: raise ParamsError() r = NCloudBot() r.method = 'PLAY_LIST_DETAIL' r.data = {'id': id, 'limit': limit, "csrf_token": ""} r.send() return r.response
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获取歌单中的所有音乐。由于获取精品中,只能看到歌单名字和 ID 并没有歌单的音乐,因此增加该接口传入歌单 ID 获取歌单中的所有音乐. :param id: 歌单的ID :param limit: (optional) 数据上限多少行,默认 20
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L406-L420
xiyouMc/ncmbot
ncmbot/core.py
music_url
def music_url(ids=[]): """通过歌曲 ID 获取歌曲下载地址 :param ids: 歌曲 ID 的 list """ if not isinstance(ids, list): raise ParamsError() r = NCloudBot() r.method = 'MUSIC_URL' r.data = {'ids': ids, 'br': 999000, "csrf_token": ""} r.send() return r.response
python
def music_url(ids=[]): """通过歌曲 ID 获取歌曲下载地址 :param ids: 歌曲 ID 的 list """ if not isinstance(ids, list): raise ParamsError() r = NCloudBot() r.method = 'MUSIC_URL' r.data = {'ids': ids, 'br': 999000, "csrf_token": ""} r.send() return r.response
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通过歌曲 ID 获取歌曲下载地址 :param ids: 歌曲 ID 的 list
[ "通过歌曲", "ID", "获取歌曲下载地址" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L424-L436
xiyouMc/ncmbot
ncmbot/core.py
lyric
def lyric(id): """通过歌曲 ID 获取歌曲歌词地址 :param id: 歌曲ID """ if id is None: raise ParamsError() r = NCloudBot() r.method = 'LYRIC' r.params = {'id': id} r.send() return r.response
python
def lyric(id): """通过歌曲 ID 获取歌曲歌词地址 :param id: 歌曲ID """ if id is None: raise ParamsError() r = NCloudBot() r.method = 'LYRIC' r.params = {'id': id} r.send() return r.response
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通过歌曲 ID 获取歌曲歌词地址 :param id: 歌曲ID
[ "通过歌曲", "ID", "获取歌曲歌词地址" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L440-L452
xiyouMc/ncmbot
ncmbot/core.py
music_comment
def music_comment(id, offset=0, limit=20): """获取歌曲的评论列表 :param id: 歌曲 ID :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 20 """ if id is None: raise ParamsError() r = NCloudBot() r.method = 'MUSIC_COMMENT' r.params = {'id': id} r.data = {'offset': offset, 'limit': limit, 'rid': id, "csrf_token": ""} r.send() return r.response
python
def music_comment(id, offset=0, limit=20): """获取歌曲的评论列表 :param id: 歌曲 ID :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 20 """ if id is None: raise ParamsError() r = NCloudBot() r.method = 'MUSIC_COMMENT' r.params = {'id': id} r.data = {'offset': offset, 'limit': limit, 'rid': id, "csrf_token": ""} r.send() return r.response
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获取歌曲的评论列表 :param id: 歌曲 ID :param offset: (optional) 分段起始位置,默认 0 :param limit: (optional) 数据上限多少行,默认 20
[ "获取歌曲的评论列表" ]
train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L456-L471
xiyouMc/ncmbot
ncmbot/core.py
song_detail
def song_detail(ids): """通过歌曲 ID 获取歌曲的详细信息 :param ids: 歌曲 ID 的 list """ if not isinstance(ids, list): raise ParamsError() c = [] for id in ids: c.append({'id': id}) r = NCloudBot() r.method = 'SONG_DETAIL' r.data = {'c': json.dumps(c), 'ids': c, "csrf_token": ""} r.send() return r.response
python
def song_detail(ids): """通过歌曲 ID 获取歌曲的详细信息 :param ids: 歌曲 ID 的 list """ if not isinstance(ids, list): raise ParamsError() c = [] for id in ids: c.append({'id': id}) r = NCloudBot() r.method = 'SONG_DETAIL' r.data = {'c': json.dumps(c), 'ids': c, "csrf_token": ""} r.send() return r.response
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通过歌曲 ID 获取歌曲的详细信息 :param ids: 歌曲 ID 的 list
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L488-L503
xiyouMc/ncmbot
ncmbot/core.py
personal_fm
def personal_fm(): """ 个人的 FM ,必须在登录之后调用,即 login 之后调用 """ r = NCloudBot() r.method = 'PERSONAL_FM' r.data = {"csrf_token": ""} r.send() return r.response
python
def personal_fm(): """ 个人的 FM ,必须在登录之后调用,即 login 之后调用 """ r = NCloudBot() r.method = 'PERSONAL_FM' r.data = {"csrf_token": ""} r.send() return r.response
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个人的 FM ,必须在登录之后调用,即 login 之后调用
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L507-L514
xiyouMc/ncmbot
ncmbot/core.py
NCloudBot._get_webapi_requests
def _get_webapi_requests(self): """Update headers of webapi for Requests.""" headers = { 'Accept': '*/*', 'Accept-Language': 'zh-CN,zh;q=0.8,gl;q=0.6,zh-TW;q=0.4', 'Connection': 'keep-alive', 'Content-Type': 'application/x-www-form-urlencoded', 'Referer': 'http://music.163.com', 'Host': 'music.163.com', 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/33.0.1750.152 Safari/537.36' } NCloudBot.req.headers.update(headers) return NCloudBot.req
python
def _get_webapi_requests(self): """Update headers of webapi for Requests.""" headers = { 'Accept': '*/*', 'Accept-Language': 'zh-CN,zh;q=0.8,gl;q=0.6,zh-TW;q=0.4', 'Connection': 'keep-alive', 'Content-Type': 'application/x-www-form-urlencoded', 'Referer': 'http://music.163.com', 'Host': 'music.163.com', 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/33.0.1750.152 Safari/537.36' } NCloudBot.req.headers.update(headers) return NCloudBot.req
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Update headers of webapi for Requests.
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L104-L124
xiyouMc/ncmbot
ncmbot/core.py
NCloudBot._build_response
def _build_response(self, resp): """Build internal Response object from given response.""" # rememberLogin # if self.method is 'LOGIN' and resp.json().get('code') == 200: # cookiesJar.save_cookies(resp, NCloudBot.username) self.response.content = resp.content self.response.status_code = resp.status_code self.response.headers = resp.headers
python
def _build_response(self, resp): """Build internal Response object from given response.""" # rememberLogin # if self.method is 'LOGIN' and resp.json().get('code') == 200: # cookiesJar.save_cookies(resp, NCloudBot.username) self.response.content = resp.content self.response.status_code = resp.status_code self.response.headers = resp.headers
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Build internal Response object from given response.
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L141-L148
xiyouMc/ncmbot
ncmbot/core.py
NCloudBot.send
def send(self): """Sens the request.""" success = False if self.method is None: raise ParamsError() try: if self.method == 'SEARCH': req = self._get_requests() _url = self.__NETEAST_HOST + self._METHODS[self.method] resp = req.post(_url, data=self.data) self._build_response(resp) self.response.ok = True else: if isinstance(self.data, dict): data = encrypted_request(self.data) req = self._get_webapi_requests() _url = self.__NETEAST_HOST + self._METHODS[self.method] if self.method in ('USER_DJ', 'USER_FOLLOWS', 'USER_EVENT'): _url = _url % self.params['uid'] if self.method in ('LYRIC', 'MUSIC_COMMENT'): _url = _url % self.params['id'] # GET if self.method in ('LYRIC'): resp = req.get(_url) else: resp = req.post(_url, data=data) self._build_response(resp) self.response.ok = True except Exception as why: traceback.print_exc() print 'Requests Exception', why # self._build_response(why) self.response.error = why
python
def send(self): """Sens the request.""" success = False if self.method is None: raise ParamsError() try: if self.method == 'SEARCH': req = self._get_requests() _url = self.__NETEAST_HOST + self._METHODS[self.method] resp = req.post(_url, data=self.data) self._build_response(resp) self.response.ok = True else: if isinstance(self.data, dict): data = encrypted_request(self.data) req = self._get_webapi_requests() _url = self.__NETEAST_HOST + self._METHODS[self.method] if self.method in ('USER_DJ', 'USER_FOLLOWS', 'USER_EVENT'): _url = _url % self.params['uid'] if self.method in ('LYRIC', 'MUSIC_COMMENT'): _url = _url % self.params['id'] # GET if self.method in ('LYRIC'): resp = req.get(_url) else: resp = req.post(_url, data=data) self._build_response(resp) self.response.ok = True except Exception as why: traceback.print_exc() print 'Requests Exception', why # self._build_response(why) self.response.error = why
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L150-L185
xiyouMc/ncmbot
ncmbot/core.py
Response.json
def json(self): """Returns the json-encoded content of a response, if any.""" if not self.headers and len(self.content) > 3: encoding = get_encoding_from_headers(self.headers) if encoding is not None: return json.loads(self.content.decode(encoding)) return json.loads(self.content)
python
def json(self): """Returns the json-encoded content of a response, if any.""" if not self.headers and len(self.content) > 3: encoding = get_encoding_from_headers(self.headers) if encoding is not None: return json.loads(self.content.decode(encoding)) return json.loads(self.content)
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Returns the json-encoded content of a response, if any.
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train
https://github.com/xiyouMc/ncmbot/blob/c4832f3ee7630ba104a89559f09c1fc366d1547b/ncmbot/core.py#L208-L215
has2k1/plydata
plydata/options.py
set_option
def set_option(name, value): """ Set plydata option Parameters ---------- name : str Name of the option value : object New value of the option Returns ------- old : object Old value of the option See also -------- :class:`options` """ old = get_option(name) globals()[name] = value return old
python
def set_option(name, value): """ Set plydata option Parameters ---------- name : str Name of the option value : object New value of the option Returns ------- old : object Old value of the option See also -------- :class:`options` """ old = get_option(name) globals()[name] = value return old
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Set plydata option Parameters ---------- name : str Name of the option value : object New value of the option Returns ------- old : object Old value of the option See also -------- :class:`options`
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/options.py#L45-L67
has2k1/plydata
plydata/dataframe/two_table.py
_join
def _join(verb): """ Join helper """ data = pd.merge(verb.x, verb.y, **verb.kwargs) # Preserve x groups if isinstance(verb.x, GroupedDataFrame): data.plydata_groups = list(verb.x.plydata_groups) return data
python
def _join(verb): """ Join helper """ data = pd.merge(verb.x, verb.y, **verb.kwargs) # Preserve x groups if isinstance(verb.x, GroupedDataFrame): data.plydata_groups = list(verb.x.plydata_groups) return data
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Join helper
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/two_table.py#L50-L59
has2k1/plydata
plydata/types.py
GroupedDataFrame.groupby
def groupby(self, by=None, **kwargs): """ Group by and do not sort (unless specified) For plydata use cases, there is no need to specify group columns. """ if by is None: by = self.plydata_groups # Turn off sorting by groups messes with some verbs if 'sort' not in kwargs: kwargs['sort'] = False return super().groupby(by, **kwargs)
python
def groupby(self, by=None, **kwargs): """ Group by and do not sort (unless specified) For plydata use cases, there is no need to specify group columns. """ if by is None: by = self.plydata_groups # Turn off sorting by groups messes with some verbs if 'sort' not in kwargs: kwargs['sort'] = False return super().groupby(by, **kwargs)
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Group by and do not sort (unless specified) For plydata use cases, there is no need to specify group columns.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/types.py#L33-L47
has2k1/plydata
plydata/types.py
GroupedDataFrame.group_indices
def group_indices(self): """ Return group indices """ # No groups if not self.plydata_groups: return np.ones(len(self), dtype=int) grouper = self.groupby() indices = np.empty(len(self), dtype=int) for i, (_, idx) in enumerate(sorted(grouper.indices.items())): indices[idx] = i return indices
python
def group_indices(self): """ Return group indices """ # No groups if not self.plydata_groups: return np.ones(len(self), dtype=int) grouper = self.groupby() indices = np.empty(len(self), dtype=int) for i, (_, idx) in enumerate(sorted(grouper.indices.items())): indices[idx] = i return indices
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Return group indices
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train
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has2k1/plydata
plydata/dataframe/helpers.py
_make_verb_helper
def _make_verb_helper(verb_func, add_groups=False): """ Create function that prepares verb for the verb function The functions created add expressions to be evaluated to the verb, then call the core verb function Parameters ---------- verb_func : function Core verb function. This is the function called after expressions created and added to the verb. The core function should be one of those that implement verbs that evaluate expressions. add_groups : bool If True, a groups attribute is added to the verb. The groups are the columns created after evaluating the expressions. Returns ------- out : function A function that implements a helper verb. """ @wraps(verb_func) def _verb_func(verb): verb.expressions, new_columns = build_expressions(verb) if add_groups: verb.groups = new_columns return verb_func(verb) return _verb_func
python
def _make_verb_helper(verb_func, add_groups=False): """ Create function that prepares verb for the verb function The functions created add expressions to be evaluated to the verb, then call the core verb function Parameters ---------- verb_func : function Core verb function. This is the function called after expressions created and added to the verb. The core function should be one of those that implement verbs that evaluate expressions. add_groups : bool If True, a groups attribute is added to the verb. The groups are the columns created after evaluating the expressions. Returns ------- out : function A function that implements a helper verb. """ @wraps(verb_func) def _verb_func(verb): verb.expressions, new_columns = build_expressions(verb) if add_groups: verb.groups = new_columns return verb_func(verb) return _verb_func
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Create function that prepares verb for the verb function The functions created add expressions to be evaluated to the verb, then call the core verb function Parameters ---------- verb_func : function Core verb function. This is the function called after expressions created and added to the verb. The core function should be one of those that implement verbs that evaluate expressions. add_groups : bool If True, a groups attribute is added to the verb. The groups are the columns created after evaluating the expressions. Returns ------- out : function A function that implements a helper verb.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/helpers.py#L156-L188
has2k1/plydata
plydata/dataframe/common.py
_get_base_dataframe
def _get_base_dataframe(df): """ Remove all columns other than those grouped on """ if isinstance(df, GroupedDataFrame): base_df = GroupedDataFrame( df.loc[:, df.plydata_groups], df.plydata_groups, copy=True) else: base_df = pd.DataFrame(index=df.index) return base_df
python
def _get_base_dataframe(df): """ Remove all columns other than those grouped on """ if isinstance(df, GroupedDataFrame): base_df = GroupedDataFrame( df.loc[:, df.plydata_groups], df.plydata_groups, copy=True) else: base_df = pd.DataFrame(index=df.index) return base_df
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Remove all columns other than those grouped on
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L27-L37
has2k1/plydata
plydata/dataframe/common.py
_add_group_columns
def _add_group_columns(data, gdf): """ Add group columns to data with a value from the grouped dataframe It is assumed that the grouped dataframe contains a single group >>> data = pd.DataFrame({ ... 'x': [5, 6, 7]}) >>> gdf = GroupedDataFrame({ ... 'g': list('aaa'), ... 'x': range(3)}, groups=['g']) >>> _add_group_columns(data, gdf) g x 0 a 5 1 a 6 2 a 7 """ n = len(data) if isinstance(gdf, GroupedDataFrame): for i, col in enumerate(gdf.plydata_groups): if col not in data: group_values = [gdf[col].iloc[0]] * n # Need to be careful and maintain the dtypes # of the group columns if pdtypes.is_categorical_dtype(gdf[col]): col_values = pd.Categorical( group_values, categories=gdf[col].cat.categories, ordered=gdf[col].cat.ordered ) else: col_values = pd.Series( group_values, index=data.index, dtype=gdf[col].dtype ) # Group columns come first data.insert(i, col, col_values) return data
python
def _add_group_columns(data, gdf): """ Add group columns to data with a value from the grouped dataframe It is assumed that the grouped dataframe contains a single group >>> data = pd.DataFrame({ ... 'x': [5, 6, 7]}) >>> gdf = GroupedDataFrame({ ... 'g': list('aaa'), ... 'x': range(3)}, groups=['g']) >>> _add_group_columns(data, gdf) g x 0 a 5 1 a 6 2 a 7 """ n = len(data) if isinstance(gdf, GroupedDataFrame): for i, col in enumerate(gdf.plydata_groups): if col not in data: group_values = [gdf[col].iloc[0]] * n # Need to be careful and maintain the dtypes # of the group columns if pdtypes.is_categorical_dtype(gdf[col]): col_values = pd.Categorical( group_values, categories=gdf[col].cat.categories, ordered=gdf[col].cat.ordered ) else: col_values = pd.Series( group_values, index=data.index, dtype=gdf[col].dtype ) # Group columns come first data.insert(i, col, col_values) return data
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Add group columns to data with a value from the grouped dataframe It is assumed that the grouped dataframe contains a single group >>> data = pd.DataFrame({ ... 'x': [5, 6, 7]}) >>> gdf = GroupedDataFrame({ ... 'g': list('aaa'), ... 'x': range(3)}, groups=['g']) >>> _add_group_columns(data, gdf) g x 0 a 5 1 a 6 2 a 7
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L40-L78
has2k1/plydata
plydata/dataframe/common.py
_create_column
def _create_column(data, col, value): """ Create column in dataframe Helper method meant to deal with problematic column values. e.g When the series index does not match that of the data. Parameters ---------- data : pandas.DataFrame dataframe in which to insert value col : column label Column name value : object Value to assign to column Returns ------- data : pandas.DataFrame Modified original dataframe >>> df = pd.DataFrame({'x': [1, 2, 3]}) >>> y = pd.Series([11, 12, 13], index=[21, 22, 23]) Data index and value index do not match >>> _create_column(df, 'y', y) x y 0 1 11 1 2 12 2 3 13 Non-empty dataframe, scalar value >>> _create_column(df, 'z', 3) x y z 0 1 11 3 1 2 12 3 2 3 13 3 Empty dataframe, scalar value >>> df = pd.DataFrame() >>> _create_column(df, 'w', 3) w 0 3 >>> _create_column(df, 'z', 'abc') w z 0 3 abc """ with suppress(AttributeError): # If the index of a series and the dataframe # in which the series will be assigned to a # column do not match, missing values/NaNs # are created. We do not want that. if not value.index.equals(data.index): if len(value) == len(data): value.index = data.index else: value.reset_index(drop=True, inplace=True) # You cannot assign a scalar value to a dataframe # without an index. You need an interable value. if data.index.empty: try: len(value) except TypeError: scalar = True else: scalar = isinstance(value, str) if scalar: value = [value] data[col] = value return data
python
def _create_column(data, col, value): """ Create column in dataframe Helper method meant to deal with problematic column values. e.g When the series index does not match that of the data. Parameters ---------- data : pandas.DataFrame dataframe in which to insert value col : column label Column name value : object Value to assign to column Returns ------- data : pandas.DataFrame Modified original dataframe >>> df = pd.DataFrame({'x': [1, 2, 3]}) >>> y = pd.Series([11, 12, 13], index=[21, 22, 23]) Data index and value index do not match >>> _create_column(df, 'y', y) x y 0 1 11 1 2 12 2 3 13 Non-empty dataframe, scalar value >>> _create_column(df, 'z', 3) x y z 0 1 11 3 1 2 12 3 2 3 13 3 Empty dataframe, scalar value >>> df = pd.DataFrame() >>> _create_column(df, 'w', 3) w 0 3 >>> _create_column(df, 'z', 'abc') w z 0 3 abc """ with suppress(AttributeError): # If the index of a series and the dataframe # in which the series will be assigned to a # column do not match, missing values/NaNs # are created. We do not want that. if not value.index.equals(data.index): if len(value) == len(data): value.index = data.index else: value.reset_index(drop=True, inplace=True) # You cannot assign a scalar value to a dataframe # without an index. You need an interable value. if data.index.empty: try: len(value) except TypeError: scalar = True else: scalar = isinstance(value, str) if scalar: value = [value] data[col] = value return data
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Create column in dataframe Helper method meant to deal with problematic column values. e.g When the series index does not match that of the data. Parameters ---------- data : pandas.DataFrame dataframe in which to insert value col : column label Column name value : object Value to assign to column Returns ------- data : pandas.DataFrame Modified original dataframe >>> df = pd.DataFrame({'x': [1, 2, 3]}) >>> y = pd.Series([11, 12, 13], index=[21, 22, 23]) Data index and value index do not match >>> _create_column(df, 'y', y) x y 0 1 11 1 2 12 2 3 13 Non-empty dataframe, scalar value >>> _create_column(df, 'z', 3) x y z 0 1 11 3 1 2 12 3 2 3 13 3 Empty dataframe, scalar value >>> df = pd.DataFrame() >>> _create_column(df, 'w', 3) w 0 3 >>> _create_column(df, 'z', 'abc') w z 0 3 abc
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L81-L157
has2k1/plydata
plydata/dataframe/common.py
build_expressions
def build_expressions(verb): """ Build expressions for helper verbs Parameters ---------- verb : verb A verb with a *functions* attribute. Returns ------- out : tuple (List of Expressions, New columns). The expressions and the new columns in which the results of those expressions will be stored. Even when a result will stored in a column with an existing label, that column is still considered new, i.e An expression ``x='x+1'``, will create a new_column `x` to replace an old column `x`. """ def partial(func, col, *args, **kwargs): """ Make a function that acts on a column in a dataframe Parameters ---------- func : callable Function col : str Column args : tuple Arguments to pass to func kwargs : dict Keyword arguments to func Results ------- new_func : callable Function that takes a dataframe, and calls the original function on a column in the dataframe. """ def new_func(gdf): return func(gdf[col], *args, **kwargs) return new_func def make_statement(func, col): """ A statement of function called on a column in a dataframe Parameters ---------- func : str or callable Function to call on a dataframe column col : str Column """ if isinstance(func, str): expr = '{}({})'.format(func, col) elif callable(func): expr = partial(func, col, *verb.args, **verb.kwargs) else: raise TypeError("{} is not a function".format(func)) return expr def func_name(func): """ Return name of a function. If the function is `np.sin`, we return `sin`. """ if isinstance(func, str): return func try: return func.__name__ except AttributeError: return '' # Generate function names. They act as identifiers (postfixed # to the original columns) in the new_column names. if isinstance(verb.functions, (tuple, list)): names = (func_name(func) for func in verb.functions) names_and_functions = zip(names, verb.functions) else: names_and_functions = verb.functions.items() # Create statements for the expressions # and postfix identifiers columns = Selector.get(verb) # columns to act on postfixes = [] stmts = [] for name, func in names_and_functions: postfixes.append(name) for col in columns: stmts.append(make_statement(func, col)) if not stmts: stmts = columns # Names of the new columns # e.g col1_mean, col2_mean, col1_std, col2_std add_postfix = (isinstance(verb.functions, dict) or len(verb.functions) > 1) if add_postfix: fmt = '{}_{}'.format new_columns = [fmt(c, p) for p in postfixes for c in columns] else: new_columns = columns expressions = [Expression(stmt, col) for stmt, col in zip(stmts, new_columns)] return expressions, new_columns
python
def build_expressions(verb): """ Build expressions for helper verbs Parameters ---------- verb : verb A verb with a *functions* attribute. Returns ------- out : tuple (List of Expressions, New columns). The expressions and the new columns in which the results of those expressions will be stored. Even when a result will stored in a column with an existing label, that column is still considered new, i.e An expression ``x='x+1'``, will create a new_column `x` to replace an old column `x`. """ def partial(func, col, *args, **kwargs): """ Make a function that acts on a column in a dataframe Parameters ---------- func : callable Function col : str Column args : tuple Arguments to pass to func kwargs : dict Keyword arguments to func Results ------- new_func : callable Function that takes a dataframe, and calls the original function on a column in the dataframe. """ def new_func(gdf): return func(gdf[col], *args, **kwargs) return new_func def make_statement(func, col): """ A statement of function called on a column in a dataframe Parameters ---------- func : str or callable Function to call on a dataframe column col : str Column """ if isinstance(func, str): expr = '{}({})'.format(func, col) elif callable(func): expr = partial(func, col, *verb.args, **verb.kwargs) else: raise TypeError("{} is not a function".format(func)) return expr def func_name(func): """ Return name of a function. If the function is `np.sin`, we return `sin`. """ if isinstance(func, str): return func try: return func.__name__ except AttributeError: return '' # Generate function names. They act as identifiers (postfixed # to the original columns) in the new_column names. if isinstance(verb.functions, (tuple, list)): names = (func_name(func) for func in verb.functions) names_and_functions = zip(names, verb.functions) else: names_and_functions = verb.functions.items() # Create statements for the expressions # and postfix identifiers columns = Selector.get(verb) # columns to act on postfixes = [] stmts = [] for name, func in names_and_functions: postfixes.append(name) for col in columns: stmts.append(make_statement(func, col)) if not stmts: stmts = columns # Names of the new columns # e.g col1_mean, col2_mean, col1_std, col2_std add_postfix = (isinstance(verb.functions, dict) or len(verb.functions) > 1) if add_postfix: fmt = '{}_{}'.format new_columns = [fmt(c, p) for p in postfixes for c in columns] else: new_columns = columns expressions = [Expression(stmt, col) for stmt, col in zip(stmts, new_columns)] return expressions, new_columns
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Build expressions for helper verbs Parameters ---------- verb : verb A verb with a *functions* attribute. Returns ------- out : tuple (List of Expressions, New columns). The expressions and the new columns in which the results of those expressions will be stored. Even when a result will stored in a column with an existing label, that column is still considered new, i.e An expression ``x='x+1'``, will create a new_column `x` to replace an old column `x`.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L502-L613
has2k1/plydata
plydata/dataframe/common.py
Evaluator.process
def process(self): """ Run the expressions Returns ------- out : pandas.DataFrame Resulting data """ # Short cut if self._all_expressions_evaluated(): if self.drop: # Drop extra columns. They do not correspond to # any expressions. columns = [expr.column for expr in self.expressions] self.data = self.data.loc[:, columns] return self.data # group_by # evaluate expressions # combine columns # concat evalutated group data and clean up index and group gdfs = self._get_group_dataframes() egdfs = self._evaluate_expressions(gdfs) edata = self._concat(egdfs) return edata
python
def process(self): """ Run the expressions Returns ------- out : pandas.DataFrame Resulting data """ # Short cut if self._all_expressions_evaluated(): if self.drop: # Drop extra columns. They do not correspond to # any expressions. columns = [expr.column for expr in self.expressions] self.data = self.data.loc[:, columns] return self.data # group_by # evaluate expressions # combine columns # concat evalutated group data and clean up index and group gdfs = self._get_group_dataframes() egdfs = self._evaluate_expressions(gdfs) edata = self._concat(egdfs) return edata
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Run the expressions Returns ------- out : pandas.DataFrame Resulting data
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L195-L220
has2k1/plydata
plydata/dataframe/common.py
Evaluator._all_expressions_evaluated
def _all_expressions_evaluated(self): """ Return True all expressions match with the columns Saves some processor cycles """ def present(expr): return expr.stmt == expr.column and expr.column in self.data return all(present(expr) for expr in self.expressions)
python
def _all_expressions_evaluated(self): """ Return True all expressions match with the columns Saves some processor cycles """ def present(expr): return expr.stmt == expr.column and expr.column in self.data return all(present(expr) for expr in self.expressions)
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Return True all expressions match with the columns Saves some processor cycles
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L222-L230
has2k1/plydata
plydata/dataframe/common.py
Evaluator._get_group_dataframes
def _get_group_dataframes(self): """ Get group dataframes Returns ------- out : tuple or generator Group dataframes """ if isinstance(self.data, GroupedDataFrame): grouper = self.data.groupby() # groupby on categorical columns uses the categories # even if they are not present in the data. This # leads to empty groups. We exclude them. return (gdf for _, gdf in grouper if not gdf.empty) else: return (self.data, )
python
def _get_group_dataframes(self): """ Get group dataframes Returns ------- out : tuple or generator Group dataframes """ if isinstance(self.data, GroupedDataFrame): grouper = self.data.groupby() # groupby on categorical columns uses the categories # even if they are not present in the data. This # leads to empty groups. We exclude them. return (gdf for _, gdf in grouper if not gdf.empty) else: return (self.data, )
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Get group dataframes Returns ------- out : tuple or generator Group dataframes
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L232-L248
has2k1/plydata
plydata/dataframe/common.py
Evaluator._evaluate_group_dataframe
def _evaluate_group_dataframe(self, gdf): """ Evaluate a single group dataframe Parameters ---------- gdf : pandas.DataFrame Input group dataframe Returns ------- out : pandas.DataFrame Result data """ gdf._is_copy = None result_index = gdf.index if self.keep_index else [] data = pd.DataFrame(index=result_index) for expr in self.expressions: value = expr.evaluate(gdf, self.env) if isinstance(value, pd.DataFrame): data = value break else: _create_column(data, expr.column, value) data = _add_group_columns(data, gdf) return data
python
def _evaluate_group_dataframe(self, gdf): """ Evaluate a single group dataframe Parameters ---------- gdf : pandas.DataFrame Input group dataframe Returns ------- out : pandas.DataFrame Result data """ gdf._is_copy = None result_index = gdf.index if self.keep_index else [] data = pd.DataFrame(index=result_index) for expr in self.expressions: value = expr.evaluate(gdf, self.env) if isinstance(value, pd.DataFrame): data = value break else: _create_column(data, expr.column, value) data = _add_group_columns(data, gdf) return data
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Evaluate a single group dataframe Parameters ---------- gdf : pandas.DataFrame Input group dataframe Returns ------- out : pandas.DataFrame Result data
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L266-L291
has2k1/plydata
plydata/dataframe/common.py
Evaluator._concat
def _concat(self, egdfs): """ Concatenate evaluated group dataframes Parameters ---------- egdfs : iterable Evaluated dataframes Returns ------- edata : pandas.DataFrame Evaluated data """ egdfs = list(egdfs) edata = pd.concat(egdfs, axis=0, ignore_index=False, copy=False) # groupby can mixup the rows. We try to maintain the original # order, but we can only do that if the result has a one to # one relationship with the original one2one = ( self.keep_index and not any(edata.index.duplicated()) and len(edata.index) == len(self.data.index)) if one2one: edata = edata.sort_index() else: edata.reset_index(drop=True, inplace=True) # Maybe this should happen in the verb functions if self.keep_groups and self.groups: edata = GroupedDataFrame(edata, groups=self.groups) return edata
python
def _concat(self, egdfs): """ Concatenate evaluated group dataframes Parameters ---------- egdfs : iterable Evaluated dataframes Returns ------- edata : pandas.DataFrame Evaluated data """ egdfs = list(egdfs) edata = pd.concat(egdfs, axis=0, ignore_index=False, copy=False) # groupby can mixup the rows. We try to maintain the original # order, but we can only do that if the result has a one to # one relationship with the original one2one = ( self.keep_index and not any(edata.index.duplicated()) and len(edata.index) == len(self.data.index)) if one2one: edata = edata.sort_index() else: edata.reset_index(drop=True, inplace=True) # Maybe this should happen in the verb functions if self.keep_groups and self.groups: edata = GroupedDataFrame(edata, groups=self.groups) return edata
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Concatenate evaluated group dataframes Parameters ---------- egdfs : iterable Evaluated dataframes Returns ------- edata : pandas.DataFrame Evaluated data
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L293-L325
has2k1/plydata
plydata/dataframe/common.py
Selector._resolve_slices
def _resolve_slices(data_columns, names): """ Convert any slices into column names Parameters ---------- data_columns : pandas.Index Dataframe columns names : tuple Names (including slices) of columns in the dataframe. Returns ------- out : tuple Names of columns in the dataframe. Has no slices. """ def _get_slice_cols(sc): """ Convert slice to list of names """ # Just like pandas.DataFrame.loc the stop # column is included idx_start = data_columns.get_loc(sc.start) idx_stop = data_columns.get_loc(sc.stop) + 1 return data_columns[idx_start:idx_stop:sc.step] result = [] for col in names: if isinstance(col, slice): result.extend(_get_slice_cols(col)) else: result.append(col) return tuple(result)
python
def _resolve_slices(data_columns, names): """ Convert any slices into column names Parameters ---------- data_columns : pandas.Index Dataframe columns names : tuple Names (including slices) of columns in the dataframe. Returns ------- out : tuple Names of columns in the dataframe. Has no slices. """ def _get_slice_cols(sc): """ Convert slice to list of names """ # Just like pandas.DataFrame.loc the stop # column is included idx_start = data_columns.get_loc(sc.start) idx_stop = data_columns.get_loc(sc.stop) + 1 return data_columns[idx_start:idx_stop:sc.step] result = [] for col in names: if isinstance(col, slice): result.extend(_get_slice_cols(col)) else: result.append(col) return tuple(result)
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Convert any slices into column names Parameters ---------- data_columns : pandas.Index Dataframe columns names : tuple Names (including slices) of columns in the dataframe. Returns ------- out : tuple Names of columns in the dataframe. Has no slices.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L333-L367
has2k1/plydata
plydata/dataframe/common.py
Selector.select
def select(cls, verb): """ Return selected columns for the select verb Parameters ---------- verb : object verb with the column selection attributes: - names - startswith - endswith - contains - matches """ columns = verb.data.columns contains = verb.contains matches = verb.matches groups = _get_groups(verb) names = cls._resolve_slices(columns, verb.names) names_set = set(names) groups_set = set(groups) lst = [[]] if names or groups: # group variable missing from the selection are prepended missing = [g for g in groups if g not in names_set] missing_set = set(missing) c1 = missing + [x for x in names if x not in missing_set] lst.append(c1) if verb.startswith: c2 = [x for x in columns if isinstance(x, str) and x.startswith(verb.startswith)] lst.append(c2) if verb.endswith: c3 = [x for x in columns if isinstance(x, str) and x.endswith(verb.endswith)] lst.append(c3) if contains: c4 = [] for col in columns: if (isinstance(col, str) and any(s in col for s in contains)): c4.append(col) lst.append(c4) if matches: c5 = [] patterns = [x if hasattr(x, 'match') else re.compile(x) for x in matches] for col in columns: if isinstance(col, str): if any(bool(p.match(col)) for p in patterns): c5.append(col) lst.append(c5) selected = unique(list(itertools.chain(*lst))) if verb.drop: to_drop = [col for col in selected if col not in groups_set] selected = [col for col in columns if col not in to_drop] return selected
python
def select(cls, verb): """ Return selected columns for the select verb Parameters ---------- verb : object verb with the column selection attributes: - names - startswith - endswith - contains - matches """ columns = verb.data.columns contains = verb.contains matches = verb.matches groups = _get_groups(verb) names = cls._resolve_slices(columns, verb.names) names_set = set(names) groups_set = set(groups) lst = [[]] if names or groups: # group variable missing from the selection are prepended missing = [g for g in groups if g not in names_set] missing_set = set(missing) c1 = missing + [x for x in names if x not in missing_set] lst.append(c1) if verb.startswith: c2 = [x for x in columns if isinstance(x, str) and x.startswith(verb.startswith)] lst.append(c2) if verb.endswith: c3 = [x for x in columns if isinstance(x, str) and x.endswith(verb.endswith)] lst.append(c3) if contains: c4 = [] for col in columns: if (isinstance(col, str) and any(s in col for s in contains)): c4.append(col) lst.append(c4) if matches: c5 = [] patterns = [x if hasattr(x, 'match') else re.compile(x) for x in matches] for col in columns: if isinstance(col, str): if any(bool(p.match(col)) for p in patterns): c5.append(col) lst.append(c5) selected = unique(list(itertools.chain(*lst))) if verb.drop: to_drop = [col for col in selected if col not in groups_set] selected = [col for col in columns if col not in to_drop] return selected
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Return selected columns for the select verb Parameters ---------- verb : object verb with the column selection attributes: - names - startswith - endswith - contains - matches
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L370-L437
has2k1/plydata
plydata/dataframe/common.py
Selector._all
def _all(cls, verb): """ A verb """ groups = set(_get_groups(verb)) return [col for col in verb.data if col not in groups]
python
def _all(cls, verb): """ A verb """ groups = set(_get_groups(verb)) return [col for col in verb.data if col not in groups]
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A verb
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L440-L445
has2k1/plydata
plydata/dataframe/common.py
Selector._at
def _at(cls, verb): """ A verb with a select text match """ # Named (listed) columns are always included columns = cls.select(verb) final_columns_set = set(cls.select(verb)) groups_set = set(_get_groups(verb)) final_columns_set -= groups_set - set(verb.names) def pred(col): if col not in verb.data: raise KeyError( "Unknown column name, {!r}".format(col)) return col in final_columns_set return [col for col in columns if pred(col)]
python
def _at(cls, verb): """ A verb with a select text match """ # Named (listed) columns are always included columns = cls.select(verb) final_columns_set = set(cls.select(verb)) groups_set = set(_get_groups(verb)) final_columns_set -= groups_set - set(verb.names) def pred(col): if col not in verb.data: raise KeyError( "Unknown column name, {!r}".format(col)) return col in final_columns_set return [col for col in columns if pred(col)]
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A verb with a select text match
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L448-L464
has2k1/plydata
plydata/dataframe/common.py
Selector._if
def _if(cls, verb): """ A verb with a predicate function """ pred = verb.predicate data = verb.data groups = set(_get_groups(verb)) # force predicate if isinstance(pred, str): if not pred.endswith('_dtype'): pred = '{}_dtype'.format(pred) pred = getattr(pdtypes, pred) elif pdtypes.is_bool_dtype(np.array(pred)): # Turn boolean array into a predicate function it = iter(pred) def pred(col): return next(it) return [col for col in data if pred(data[col]) and col not in groups]
python
def _if(cls, verb): """ A verb with a predicate function """ pred = verb.predicate data = verb.data groups = set(_get_groups(verb)) # force predicate if isinstance(pred, str): if not pred.endswith('_dtype'): pred = '{}_dtype'.format(pred) pred = getattr(pdtypes, pred) elif pdtypes.is_bool_dtype(np.array(pred)): # Turn boolean array into a predicate function it = iter(pred) def pred(col): return next(it) return [col for col in data if pred(data[col]) and col not in groups]
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A verb with a predicate function
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train
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has2k1/plydata
plydata/operators.py
get_verb_function
def get_verb_function(data, verb): """ Return function that implements the verb for given data type """ try: module = type_lookup[type(data)] except KeyError: # Some guess work for subclasses for type_, mod in type_lookup.items(): if isinstance(data, type_): module = mod break try: return getattr(module, verb) except (NameError, AttributeError): msg = "Data source of type '{}' is not supported." raise TypeError(msg.format(type(data)))
python
def get_verb_function(data, verb): """ Return function that implements the verb for given data type """ try: module = type_lookup[type(data)] except KeyError: # Some guess work for subclasses for type_, mod in type_lookup.items(): if isinstance(data, type_): module = mod break try: return getattr(module, verb) except (NameError, AttributeError): msg = "Data source of type '{}' is not supported." raise TypeError(msg.format(type(data)))
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Return function that implements the verb for given data type
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/operators.py#L23-L39
has2k1/plydata
plydata/expressions.py
Expression
def Expression(*args, **kwargs): """ Return an appropriate Expression given the arguments Parameters ---------- args : tuple Positional arguments passed to the Expression class kwargs : dict Keyword arguments passed to the Expression class """ # dispatch if not hasattr(args[0], '_Expression'): return BaseExpression(*args, *kwargs) else: return args[0]._Expression(*args, **kwargs)
python
def Expression(*args, **kwargs): """ Return an appropriate Expression given the arguments Parameters ---------- args : tuple Positional arguments passed to the Expression class kwargs : dict Keyword arguments passed to the Expression class """ # dispatch if not hasattr(args[0], '_Expression'): return BaseExpression(*args, *kwargs) else: return args[0]._Expression(*args, **kwargs)
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Return an appropriate Expression given the arguments Parameters ---------- args : tuple Positional arguments passed to the Expression class kwargs : dict Keyword arguments passed to the Expression class
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/expressions.py#L176-L191
has2k1/plydata
plydata/expressions.py
BaseExpression.evaluate
def evaluate(self, data, env): """ Evaluate statement Parameters ---------- data : pandas.DataFrame Data in whose namespace the statement will be evaluated. Typically, this is a group dataframe. Returns ------- out : object Result of the evaluation.pandas.DataFrame """ def n(): """ Return number of rows in groups This function is part of the public API """ return len(data) if isinstance(self.stmt, str): # Add function n() that computes the # size of the group data to the inner namespace. if self._has_n_func: namespace = dict(data, n=n) else: namespace = data # Avoid obvious keywords e.g if a column # is named class if self.stmt not in KEYWORDS: value = env.eval( self.stmt, source_name='Expression.evaluate', inner_namespace=namespace) else: value = namespace[self.stmt] elif callable(self.stmt): value = self.stmt(data) else: value = self.stmt return value
python
def evaluate(self, data, env): """ Evaluate statement Parameters ---------- data : pandas.DataFrame Data in whose namespace the statement will be evaluated. Typically, this is a group dataframe. Returns ------- out : object Result of the evaluation.pandas.DataFrame """ def n(): """ Return number of rows in groups This function is part of the public API """ return len(data) if isinstance(self.stmt, str): # Add function n() that computes the # size of the group data to the inner namespace. if self._has_n_func: namespace = dict(data, n=n) else: namespace = data # Avoid obvious keywords e.g if a column # is named class if self.stmt not in KEYWORDS: value = env.eval( self.stmt, source_name='Expression.evaluate', inner_namespace=namespace) else: value = namespace[self.stmt] elif callable(self.stmt): value = self.stmt(data) else: value = self.stmt return value
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Evaluate statement Parameters ---------- data : pandas.DataFrame Data in whose namespace the statement will be evaluated. Typically, this is a group dataframe. Returns ------- out : object Result of the evaluation.pandas.DataFrame
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/expressions.py#L58-L101
has2k1/plydata
plydata/expressions.py
CaseWhenExpression.evaluate
def evaluate(self, data, env): """ Evaluate the predicates and values """ # For each predicate-value, we keep track of the positions # that have been copied to the result, so that the later # more general values do not overwrite the previous ones. result = np.repeat(None, len(data)) copied = np.repeat(False, len(data)) for pred_expr, value_expr in self.pv_expressions: bool_idx = pred_expr.evaluate(data, env) if not pdtypes.is_bool_dtype(np.asarray(bool_idx)): raise TypeError( "The predicate keys must return a boolean array, " "or a boolean value.") value = value_expr.evaluate(data, env) mask = (copied ^ bool_idx) & bool_idx copied |= bool_idx idx = np.where(mask)[0] result[idx] = self.nice_value(value, idx) return np.array(list(result))
python
def evaluate(self, data, env): """ Evaluate the predicates and values """ # For each predicate-value, we keep track of the positions # that have been copied to the result, so that the later # more general values do not overwrite the previous ones. result = np.repeat(None, len(data)) copied = np.repeat(False, len(data)) for pred_expr, value_expr in self.pv_expressions: bool_idx = pred_expr.evaluate(data, env) if not pdtypes.is_bool_dtype(np.asarray(bool_idx)): raise TypeError( "The predicate keys must return a boolean array, " "or a boolean value.") value = value_expr.evaluate(data, env) mask = (copied ^ bool_idx) & bool_idx copied |= bool_idx idx = np.where(mask)[0] result[idx] = self.nice_value(value, idx) return np.array(list(result))
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Evaluate the predicates and values
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/expressions.py#L130-L150
has2k1/plydata
plydata/expressions.py
IfElseExpression.evaluate
def evaluate(self, data, env): """ Evaluate the predicates and values """ bool_idx = self.predicate_expr.evaluate(data, env) true_value = self.true_value_expr.evaluate(data, env) false_value = self.false_value_expr.evaluate(data, env) true_idx = np.where(bool_idx)[0] false_idx = np.where(~bool_idx)[0] result = np.repeat(None, len(data)) result[true_idx] = self.nice_value(true_value, true_idx) result[false_idx] = self.nice_value(false_value, false_idx) return np.array(list(result))
python
def evaluate(self, data, env): """ Evaluate the predicates and values """ bool_idx = self.predicate_expr.evaluate(data, env) true_value = self.true_value_expr.evaluate(data, env) false_value = self.false_value_expr.evaluate(data, env) true_idx = np.where(bool_idx)[0] false_idx = np.where(~bool_idx)[0] result = np.repeat(None, len(data)) result[true_idx] = self.nice_value(true_value, true_idx) result[false_idx] = self.nice_value(false_value, false_idx) return np.array(list(result))
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Evaluate the predicates and values
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/expressions.py#L161-L173
has2k1/plydata
plydata/eval.py
EvalEnvironment.with_outer_namespace
def with_outer_namespace(self, outer_namespace): """Return a new EvalEnvironment with an extra namespace added. This namespace will be used only for variables that are not found in any existing namespace, i.e., it is "outside" them all.""" return self.__class__(self._namespaces + [outer_namespace], self.flags)
python
def with_outer_namespace(self, outer_namespace): """Return a new EvalEnvironment with an extra namespace added. This namespace will be used only for variables that are not found in any existing namespace, i.e., it is "outside" them all.""" return self.__class__(self._namespaces + [outer_namespace], self.flags)
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Return a new EvalEnvironment with an extra namespace added. This namespace will be used only for variables that are not found in any existing namespace, i.e., it is "outside" them all.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/eval.py#L81-L86
has2k1/plydata
plydata/eval.py
EvalEnvironment.eval
def eval(self, expr, source_name="<string>", inner_namespace={}): """Evaluate some Python code in the encapsulated environment. :arg expr: A string containing a Python expression. :arg source_name: A name for this string, for use in tracebacks. :arg inner_namespace: A dict-like object that will be checked first when `expr` attempts to access any variables. :returns: The value of `expr`. """ code = compile(expr, source_name, "eval", self.flags, False) return eval(code, {}, VarLookupDict([inner_namespace] + self._namespaces))
python
def eval(self, expr, source_name="<string>", inner_namespace={}): """Evaluate some Python code in the encapsulated environment. :arg expr: A string containing a Python expression. :arg source_name: A name for this string, for use in tracebacks. :arg inner_namespace: A dict-like object that will be checked first when `expr` attempts to access any variables. :returns: The value of `expr`. """ code = compile(expr, source_name, "eval", self.flags, False) return eval(code, {}, VarLookupDict([inner_namespace] + self._namespaces))
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Evaluate some Python code in the encapsulated environment. :arg expr: A string containing a Python expression. :arg source_name: A name for this string, for use in tracebacks. :arg inner_namespace: A dict-like object that will be checked first when `expr` attempts to access any variables. :returns: The value of `expr`.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/eval.py#L88-L98
has2k1/plydata
plydata/eval.py
EvalEnvironment.capture
def capture(cls, eval_env=0, reference=0): """Capture an execution environment from the stack. If `eval_env` is already an :class:`EvalEnvironment`, it is returned unchanged. Otherwise, we walk up the stack by ``eval_env + reference`` steps and capture that function's evaluation environment. For ``eval_env=0`` and ``reference=0``, the default, this captures the stack frame of the function that calls :meth:`capture`. If ``eval_env + reference`` is 1, then we capture that function's caller, etc. This somewhat complicated calling convention is designed to be convenient for functions which want to capture their caller's environment by default, but also allow explicit environments to be specified. See the second example. Example:: x = 1 this_env = EvalEnvironment.capture() assert this_env.namespace["x"] == 1 def child_func(): return EvalEnvironment.capture(1) this_env_from_child = child_func() assert this_env_from_child.namespace["x"] == 1 Example:: # This function can be used like: # my_model(formula_like, data) # -> evaluates formula_like in caller's environment # my_model(formula_like, data, eval_env=1) # -> evaluates formula_like in caller's caller's environment # my_model(formula_like, data, eval_env=my_env) # -> evaluates formula_like in environment 'my_env' def my_model(formula_like, data, eval_env=0): eval_env = EvalEnvironment.capture(eval_env, reference=1) return model_setup_helper(formula_like, data, eval_env) This is how :func:`dmatrix` works. .. versionadded: 0.2.0 The ``reference`` argument. """ if isinstance(eval_env, cls): return eval_env elif isinstance(eval_env, numbers.Integral): depth = eval_env + reference else: raise TypeError("Parameter 'eval_env' must be either an integer " "or an instance of patsy.EvalEnvironment.") frame = inspect.currentframe() try: for i in range(depth + 1): if frame is None: raise ValueError("call-stack is not that deep!") frame = frame.f_back return cls([frame.f_locals, frame.f_globals], frame.f_code.co_flags & _ALL_FUTURE_FLAGS) # The try/finally is important to avoid a potential reference cycle -- # any exception traceback will carry a reference to *our* frame, which # contains a reference to our local variables, which would otherwise # carry a reference to some parent frame, where the exception was # caught...: finally: del frame
python
def capture(cls, eval_env=0, reference=0): """Capture an execution environment from the stack. If `eval_env` is already an :class:`EvalEnvironment`, it is returned unchanged. Otherwise, we walk up the stack by ``eval_env + reference`` steps and capture that function's evaluation environment. For ``eval_env=0`` and ``reference=0``, the default, this captures the stack frame of the function that calls :meth:`capture`. If ``eval_env + reference`` is 1, then we capture that function's caller, etc. This somewhat complicated calling convention is designed to be convenient for functions which want to capture their caller's environment by default, but also allow explicit environments to be specified. See the second example. Example:: x = 1 this_env = EvalEnvironment.capture() assert this_env.namespace["x"] == 1 def child_func(): return EvalEnvironment.capture(1) this_env_from_child = child_func() assert this_env_from_child.namespace["x"] == 1 Example:: # This function can be used like: # my_model(formula_like, data) # -> evaluates formula_like in caller's environment # my_model(formula_like, data, eval_env=1) # -> evaluates formula_like in caller's caller's environment # my_model(formula_like, data, eval_env=my_env) # -> evaluates formula_like in environment 'my_env' def my_model(formula_like, data, eval_env=0): eval_env = EvalEnvironment.capture(eval_env, reference=1) return model_setup_helper(formula_like, data, eval_env) This is how :func:`dmatrix` works. .. versionadded: 0.2.0 The ``reference`` argument. """ if isinstance(eval_env, cls): return eval_env elif isinstance(eval_env, numbers.Integral): depth = eval_env + reference else: raise TypeError("Parameter 'eval_env' must be either an integer " "or an instance of patsy.EvalEnvironment.") frame = inspect.currentframe() try: for i in range(depth + 1): if frame is None: raise ValueError("call-stack is not that deep!") frame = frame.f_back return cls([frame.f_locals, frame.f_globals], frame.f_code.co_flags & _ALL_FUTURE_FLAGS) # The try/finally is important to avoid a potential reference cycle -- # any exception traceback will carry a reference to *our* frame, which # contains a reference to our local variables, which would otherwise # carry a reference to some parent frame, where the exception was # caught...: finally: del frame
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Capture an execution environment from the stack. If `eval_env` is already an :class:`EvalEnvironment`, it is returned unchanged. Otherwise, we walk up the stack by ``eval_env + reference`` steps and capture that function's evaluation environment. For ``eval_env=0`` and ``reference=0``, the default, this captures the stack frame of the function that calls :meth:`capture`. If ``eval_env + reference`` is 1, then we capture that function's caller, etc. This somewhat complicated calling convention is designed to be convenient for functions which want to capture their caller's environment by default, but also allow explicit environments to be specified. See the second example. Example:: x = 1 this_env = EvalEnvironment.capture() assert this_env.namespace["x"] == 1 def child_func(): return EvalEnvironment.capture(1) this_env_from_child = child_func() assert this_env_from_child.namespace["x"] == 1 Example:: # This function can be used like: # my_model(formula_like, data) # -> evaluates formula_like in caller's environment # my_model(formula_like, data, eval_env=1) # -> evaluates formula_like in caller's caller's environment # my_model(formula_like, data, eval_env=my_env) # -> evaluates formula_like in environment 'my_env' def my_model(formula_like, data, eval_env=0): eval_env = EvalEnvironment.capture(eval_env, reference=1) return model_setup_helper(formula_like, data, eval_env) This is how :func:`dmatrix` works. .. versionadded: 0.2.0 The ``reference`` argument.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/eval.py#L101-L157
has2k1/plydata
plydata/eval.py
EvalEnvironment.subset
def subset(self, names): """Creates a new, flat EvalEnvironment that contains only the variables specified.""" vld = VarLookupDict(self._namespaces) new_ns = dict((name, vld[name]) for name in names) return EvalEnvironment([new_ns], self.flags)
python
def subset(self, names): """Creates a new, flat EvalEnvironment that contains only the variables specified.""" vld = VarLookupDict(self._namespaces) new_ns = dict((name, vld[name]) for name in names) return EvalEnvironment([new_ns], self.flags)
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Creates a new, flat EvalEnvironment that contains only the variables specified.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/eval.py#L159-L164
has2k1/plydata
plydata/utils.py
temporary_key
def temporary_key(d, key, value): """ Context manager that removes key from dictionary on closing The dictionary will hold the key for the duration of the context. Parameters ---------- d : dict-like Dictionary in which to insert a temporary key. key : hashable Location at which to insert ``value``. value : object Value to insert in ``d`` at location ``key``. """ d[key] = value try: yield d finally: del d[key]
python
def temporary_key(d, key, value): """ Context manager that removes key from dictionary on closing The dictionary will hold the key for the duration of the context. Parameters ---------- d : dict-like Dictionary in which to insert a temporary key. key : hashable Location at which to insert ``value``. value : object Value to insert in ``d`` at location ``key``. """ d[key] = value try: yield d finally: del d[key]
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Context manager that removes key from dictionary on closing The dictionary will hold the key for the duration of the context. Parameters ---------- d : dict-like Dictionary in which to insert a temporary key. key : hashable Location at which to insert ``value``. value : object Value to insert in ``d`` at location ``key``.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/utils.py#L16-L36
has2k1/plydata
plydata/utils.py
temporary_attr
def temporary_attr(obj, name, value): """ Context manager that removes key from dictionary on closing The dictionary will hold the key for the duration of the context. Parameters ---------- obj : object Object onto which to add a temporary attribute. name : str Name of attribute to add to ``obj``. value : object Value of ``attr``. """ setattr(obj, name, value) try: yield obj finally: delattr(obj, name)
python
def temporary_attr(obj, name, value): """ Context manager that removes key from dictionary on closing The dictionary will hold the key for the duration of the context. Parameters ---------- obj : object Object onto which to add a temporary attribute. name : str Name of attribute to add to ``obj``. value : object Value of ``attr``. """ setattr(obj, name, value) try: yield obj finally: delattr(obj, name)
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Context manager that removes key from dictionary on closing The dictionary will hold the key for the duration of the context. Parameters ---------- obj : object Object onto which to add a temporary attribute. name : str Name of attribute to add to ``obj``. value : object Value of ``attr``.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/utils.py#L40-L60
has2k1/plydata
plydata/utils.py
Q
def Q(name): """ Quote a variable name A way to 'quote' variable names, especially ones that do not otherwise meet Python's variable name rules. Parameters ---------- name : str Name of variable Returns ------- value : object Value of variable Examples -------- >>> import pandas as pd >>> from plydata import define >>> df = pd.DataFrame({'class': [10, 20, 30]}) Since ``class`` is a reserved python keyword it cannot be a variable name, and therefore cannot be used in an expression without quoting it. >>> df >> define(y='class+1') Traceback (most recent call last): File "<string>", line 1 class+1 ^ SyntaxError: invalid syntax >>> df >> define(y='Q("class")+1') class y 0 10 11 1 20 21 2 30 31 Note that it is ``'Q("some name")'`` and not ``'Q(some name)'``. As in the above example, you do not need to ``import`` ``Q`` before you can use it. """ env = EvalEnvironment.capture(1) try: return env.namespace[name] except KeyError: raise NameError("No data named {!r} found".format(name))
python
def Q(name): """ Quote a variable name A way to 'quote' variable names, especially ones that do not otherwise meet Python's variable name rules. Parameters ---------- name : str Name of variable Returns ------- value : object Value of variable Examples -------- >>> import pandas as pd >>> from plydata import define >>> df = pd.DataFrame({'class': [10, 20, 30]}) Since ``class`` is a reserved python keyword it cannot be a variable name, and therefore cannot be used in an expression without quoting it. >>> df >> define(y='class+1') Traceback (most recent call last): File "<string>", line 1 class+1 ^ SyntaxError: invalid syntax >>> df >> define(y='Q("class")+1') class y 0 10 11 1 20 21 2 30 31 Note that it is ``'Q("some name")'`` and not ``'Q(some name)'``. As in the above example, you do not need to ``import`` ``Q`` before you can use it. """ env = EvalEnvironment.capture(1) try: return env.namespace[name] except KeyError: raise NameError("No data named {!r} found".format(name))
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Quote a variable name A way to 'quote' variable names, especially ones that do not otherwise meet Python's variable name rules. Parameters ---------- name : str Name of variable Returns ------- value : object Value of variable Examples -------- >>> import pandas as pd >>> from plydata import define >>> df = pd.DataFrame({'class': [10, 20, 30]}) Since ``class`` is a reserved python keyword it cannot be a variable name, and therefore cannot be used in an expression without quoting it. >>> df >> define(y='class+1') Traceback (most recent call last): File "<string>", line 1 class+1 ^ SyntaxError: invalid syntax >>> df >> define(y='Q("class")+1') class y 0 10 11 1 20 21 2 30 31 Note that it is ``'Q("some name")'`` and not ``'Q(some name)'``. As in the above example, you do not need to ``import`` ``Q`` before you can use it.
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/utils.py#L72-L119
has2k1/plydata
plydata/utils.py
regular_index
def regular_index(*dfs): """ Change & restore the indices of dataframes Dataframe with duplicate values can be hard to work with. When split and recombined, you cannot restore the row order. This can be the case even if the index has unique but irregular/unordered. This contextmanager resets the unordered indices of any dataframe passed to it, on exit it restores the original index. A regular index is of the form:: RangeIndex(start=0, stop=n, step=1) Parameters ---------- dfs : tuple Dataframes Yields ------ dfs : tuple Dataframe Examples -------- Create dataframes with different indices >>> df1 = pd.DataFrame([4, 3, 2, 1]) >>> df2 = pd.DataFrame([3, 2, 1], index=[3, 0, 0]) >>> df3 = pd.DataFrame([11, 12, 13], index=[11, 12, 13]) Within the contexmanager all frames have nice range indices >>> with regular_index(df1, df2, df3): ... print(df1.index) ... print(df2.index) ... print(df3.index) RangeIndex(start=0, stop=4, step=1) RangeIndex(start=0, stop=3, step=1) RangeIndex(start=0, stop=3, step=1) Indices restored >>> df1.index RangeIndex(start=0, stop=4, step=1) >>> df2.index Int64Index([3, 0, 0], dtype='int64') >>> df3.index Int64Index([11, 12, 13], dtype='int64') """ original_index = [df.index for df in dfs] have_bad_index = [not isinstance(df.index, pd.RangeIndex) for df in dfs] for df, bad in zip(dfs, have_bad_index): if bad: df.reset_index(drop=True, inplace=True) try: yield dfs finally: for df, bad, idx in zip(dfs, have_bad_index, original_index): if bad and len(df.index) == len(idx): df.index = idx
python
def regular_index(*dfs): """ Change & restore the indices of dataframes Dataframe with duplicate values can be hard to work with. When split and recombined, you cannot restore the row order. This can be the case even if the index has unique but irregular/unordered. This contextmanager resets the unordered indices of any dataframe passed to it, on exit it restores the original index. A regular index is of the form:: RangeIndex(start=0, stop=n, step=1) Parameters ---------- dfs : tuple Dataframes Yields ------ dfs : tuple Dataframe Examples -------- Create dataframes with different indices >>> df1 = pd.DataFrame([4, 3, 2, 1]) >>> df2 = pd.DataFrame([3, 2, 1], index=[3, 0, 0]) >>> df3 = pd.DataFrame([11, 12, 13], index=[11, 12, 13]) Within the contexmanager all frames have nice range indices >>> with regular_index(df1, df2, df3): ... print(df1.index) ... print(df2.index) ... print(df3.index) RangeIndex(start=0, stop=4, step=1) RangeIndex(start=0, stop=3, step=1) RangeIndex(start=0, stop=3, step=1) Indices restored >>> df1.index RangeIndex(start=0, stop=4, step=1) >>> df2.index Int64Index([3, 0, 0], dtype='int64') >>> df3.index Int64Index([11, 12, 13], dtype='int64') """ original_index = [df.index for df in dfs] have_bad_index = [not isinstance(df.index, pd.RangeIndex) for df in dfs] for df, bad in zip(dfs, have_bad_index): if bad: df.reset_index(drop=True, inplace=True) try: yield dfs finally: for df, bad, idx in zip(dfs, have_bad_index, original_index): if bad and len(df.index) == len(idx): df.index = idx
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Change & restore the indices of dataframes Dataframe with duplicate values can be hard to work with. When split and recombined, you cannot restore the row order. This can be the case even if the index has unique but irregular/unordered. This contextmanager resets the unordered indices of any dataframe passed to it, on exit it restores the original index. A regular index is of the form:: RangeIndex(start=0, stop=n, step=1) Parameters ---------- dfs : tuple Dataframes Yields ------ dfs : tuple Dataframe Examples -------- Create dataframes with different indices >>> df1 = pd.DataFrame([4, 3, 2, 1]) >>> df2 = pd.DataFrame([3, 2, 1], index=[3, 0, 0]) >>> df3 = pd.DataFrame([11, 12, 13], index=[11, 12, 13]) Within the contexmanager all frames have nice range indices >>> with regular_index(df1, df2, df3): ... print(df1.index) ... print(df2.index) ... print(df3.index) RangeIndex(start=0, stop=4, step=1) RangeIndex(start=0, stop=3, step=1) RangeIndex(start=0, stop=3, step=1) Indices restored >>> df1.index RangeIndex(start=0, stop=4, step=1) >>> df2.index Int64Index([3, 0, 0], dtype='int64') >>> df3.index Int64Index([11, 12, 13], dtype='int64')
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train
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/utils.py#L147-L212
has2k1/plydata
plydata/utils.py
unique
def unique(lst): """ Return unique elements :class:`pandas.unique` and :class:`numpy.unique` cast mixed type lists to the same type. They are faster, but some times we want to maintain the type. Parameters ---------- lst : list-like List of items Returns ------- out : list Unique items in the order that they appear in the input. Examples -------- >>> import pandas as pd >>> import numpy as np >>> lst = ['one', 'two', 123, 'three'] >>> pd.unique(lst) array(['one', 'two', '123', 'three'], dtype=object) >>> np.unique(lst) array(['123', 'one', 'three', 'two'], dtype='<U5') >>> unique(lst) ['one', 'two', 123, 'three'] pandas and numpy cast 123 to a string!, and numpy does not even maintain the order. """ seen = set() def make_seen(x): seen.add(x) return x return [make_seen(x) for x in lst if x not in seen]
python
def unique(lst): """ Return unique elements :class:`pandas.unique` and :class:`numpy.unique` cast mixed type lists to the same type. They are faster, but some times we want to maintain the type. Parameters ---------- lst : list-like List of items Returns ------- out : list Unique items in the order that they appear in the input. Examples -------- >>> import pandas as pd >>> import numpy as np >>> lst = ['one', 'two', 123, 'three'] >>> pd.unique(lst) array(['one', 'two', '123', 'three'], dtype=object) >>> np.unique(lst) array(['123', 'one', 'three', 'two'], dtype='<U5') >>> unique(lst) ['one', 'two', 123, 'three'] pandas and numpy cast 123 to a string!, and numpy does not even maintain the order. """ seen = set() def make_seen(x): seen.add(x) return x return [make_seen(x) for x in lst if x not in seen]
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Return unique elements :class:`pandas.unique` and :class:`numpy.unique` cast mixed type lists to the same type. They are faster, but some times we want to maintain the type. Parameters ---------- lst : list-like List of items Returns ------- out : list Unique items in the order that they appear in the input. Examples -------- >>> import pandas as pd >>> import numpy as np >>> lst = ['one', 'two', 123, 'three'] >>> pd.unique(lst) array(['one', 'two', '123', 'three'], dtype=object) >>> np.unique(lst) array(['123', 'one', 'three', 'two'], dtype='<U5') >>> unique(lst) ['one', 'two', 123, 'three'] pandas and numpy cast 123 to a string!, and numpy does not even maintain the order.
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has2k1/plydata
plydata/dataframe/one_table.py
_nth
def _nth(arr, n): """ Return the nth value of array If it is missing return NaN """ try: return arr.iloc[n] except (KeyError, IndexError): return np.nan
python
def _nth(arr, n): """ Return the nth value of array If it is missing return NaN """ try: return arr.iloc[n] except (KeyError, IndexError): return np.nan
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Return the nth value of array If it is missing return NaN
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train
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tkarabela/pysubs2
pysubs2/time.py
make_time
def make_time(h=0, m=0, s=0, ms=0, frames=None, fps=None): """ Convert time to milliseconds. See :func:`pysubs2.time.times_to_ms()`. When both frames and fps are specified, :func:`pysubs2.time.frames_to_ms()` is called instead. Raises: ValueError: Invalid fps, or one of frames/fps is missing. Example: >>> make_time(s=1.5) 1500 >>> make_time(frames=50, fps=25) 2000 """ if frames is None and fps is None: return times_to_ms(h, m, s, ms) elif frames is not None and fps is not None: return frames_to_ms(frames, fps) else: raise ValueError("Both fps and frames must be specified")
python
def make_time(h=0, m=0, s=0, ms=0, frames=None, fps=None): """ Convert time to milliseconds. See :func:`pysubs2.time.times_to_ms()`. When both frames and fps are specified, :func:`pysubs2.time.frames_to_ms()` is called instead. Raises: ValueError: Invalid fps, or one of frames/fps is missing. Example: >>> make_time(s=1.5) 1500 >>> make_time(frames=50, fps=25) 2000 """ if frames is None and fps is None: return times_to_ms(h, m, s, ms) elif frames is not None and fps is not None: return frames_to_ms(frames, fps) else: raise ValueError("Both fps and frames must be specified")
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tkarabela/pysubs2
pysubs2/time.py
timestamp_to_ms
def timestamp_to_ms(groups): """ Convert groups from :data:`pysubs2.time.TIMESTAMP` match to milliseconds. Example: >>> timestamp_to_ms(TIMESTAMP.match("0:00:00.42").groups()) 420 """ h, m, s, frac = map(int, groups) ms = frac * 10**(3 - len(groups[-1])) ms += s * 1000 ms += m * 60000 ms += h * 3600000 return ms
python
def timestamp_to_ms(groups): """ Convert groups from :data:`pysubs2.time.TIMESTAMP` match to milliseconds. Example: >>> timestamp_to_ms(TIMESTAMP.match("0:00:00.42").groups()) 420 """ h, m, s, frac = map(int, groups) ms = frac * 10**(3 - len(groups[-1])) ms += s * 1000 ms += m * 60000 ms += h * 3600000 return ms
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Convert groups from :data:`pysubs2.time.TIMESTAMP` match to milliseconds. Example: >>> timestamp_to_ms(TIMESTAMP.match("0:00:00.42").groups()) 420
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tkarabela/pysubs2
pysubs2/time.py
times_to_ms
def times_to_ms(h=0, m=0, s=0, ms=0): """ Convert hours, minutes, seconds to milliseconds. Arguments may be positive or negative, int or float, need not be normalized (``s=120`` is okay). Returns: Number of milliseconds (rounded to int). """ ms += s * 1000 ms += m * 60000 ms += h * 3600000 return int(round(ms))
python
def times_to_ms(h=0, m=0, s=0, ms=0): """ Convert hours, minutes, seconds to milliseconds. Arguments may be positive or negative, int or float, need not be normalized (``s=120`` is okay). Returns: Number of milliseconds (rounded to int). """ ms += s * 1000 ms += m * 60000 ms += h * 3600000 return int(round(ms))
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Convert hours, minutes, seconds to milliseconds. Arguments may be positive or negative, int or float, need not be normalized (``s=120`` is okay). Returns: Number of milliseconds (rounded to int).
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tkarabela/pysubs2
pysubs2/time.py
frames_to_ms
def frames_to_ms(frames, fps): """ Convert frame-based duration to milliseconds. Arguments: frames: Number of frames (should be int). fps: Framerate (must be a positive number, eg. 23.976). Returns: Number of milliseconds (rounded to int). Raises: ValueError: fps was negative or zero. """ if fps <= 0: raise ValueError("Framerate must be positive number (%f)." % fps) return int(round(frames * (1000 / fps)))
python
def frames_to_ms(frames, fps): """ Convert frame-based duration to milliseconds. Arguments: frames: Number of frames (should be int). fps: Framerate (must be a positive number, eg. 23.976). Returns: Number of milliseconds (rounded to int). Raises: ValueError: fps was negative or zero. """ if fps <= 0: raise ValueError("Framerate must be positive number (%f)." % fps) return int(round(frames * (1000 / fps)))
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Convert frame-based duration to milliseconds. Arguments: frames: Number of frames (should be int). fps: Framerate (must be a positive number, eg. 23.976). Returns: Number of milliseconds (rounded to int). Raises: ValueError: fps was negative or zero.
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tkarabela/pysubs2
pysubs2/time.py
ms_to_frames
def ms_to_frames(ms, fps): """ Convert milliseconds to number of frames. Arguments: ms: Number of milliseconds (may be int, float or other numeric class). fps: Framerate (must be a positive number, eg. 23.976). Returns: Number of frames (int). Raises: ValueError: fps was negative or zero. """ if fps <= 0: raise ValueError("Framerate must be positive number (%f)." % fps) return int(round((ms / 1000) * fps))
python
def ms_to_frames(ms, fps): """ Convert milliseconds to number of frames. Arguments: ms: Number of milliseconds (may be int, float or other numeric class). fps: Framerate (must be a positive number, eg. 23.976). Returns: Number of frames (int). Raises: ValueError: fps was negative or zero. """ if fps <= 0: raise ValueError("Framerate must be positive number (%f)." % fps) return int(round((ms / 1000) * fps))
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Convert milliseconds to number of frames. Arguments: ms: Number of milliseconds (may be int, float or other numeric class). fps: Framerate (must be a positive number, eg. 23.976). Returns: Number of frames (int). Raises: ValueError: fps was negative or zero.
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tkarabela/pysubs2
pysubs2/time.py
ms_to_times
def ms_to_times(ms): """ Convert milliseconds to normalized tuple (h, m, s, ms). Arguments: ms: Number of milliseconds (may be int, float or other numeric class). Should be non-negative. Returns: Named tuple (h, m, s, ms) of ints. Invariants: ``ms in range(1000) and s in range(60) and m in range(60)`` """ ms = int(round(ms)) h, ms = divmod(ms, 3600000) m, ms = divmod(ms, 60000) s, ms = divmod(ms, 1000) return Times(h, m, s, ms)
python
def ms_to_times(ms): """ Convert milliseconds to normalized tuple (h, m, s, ms). Arguments: ms: Number of milliseconds (may be int, float or other numeric class). Should be non-negative. Returns: Named tuple (h, m, s, ms) of ints. Invariants: ``ms in range(1000) and s in range(60) and m in range(60)`` """ ms = int(round(ms)) h, ms = divmod(ms, 3600000) m, ms = divmod(ms, 60000) s, ms = divmod(ms, 1000) return Times(h, m, s, ms)
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tkarabela/pysubs2
pysubs2/time.py
ms_to_str
def ms_to_str(ms, fractions=False): """ Prettyprint milliseconds to [-]H:MM:SS[.mmm] Handles huge and/or negative times. Non-negative times with ``fractions=True`` are matched by :data:`pysubs2.time.TIMESTAMP`. Arguments: ms: Number of milliseconds (int, float or other numeric class). fractions: Whether to print up to millisecond precision. Returns: str """ sgn = "-" if ms < 0 else "" h, m, s, ms = ms_to_times(abs(ms)) if fractions: return sgn + "{:01d}:{:02d}:{:02d}.{:03d}".format(h, m, s, ms) else: return sgn + "{:01d}:{:02d}:{:02d}".format(h, m, s)
python
def ms_to_str(ms, fractions=False): """ Prettyprint milliseconds to [-]H:MM:SS[.mmm] Handles huge and/or negative times. Non-negative times with ``fractions=True`` are matched by :data:`pysubs2.time.TIMESTAMP`. Arguments: ms: Number of milliseconds (int, float or other numeric class). fractions: Whether to print up to millisecond precision. Returns: str """ sgn = "-" if ms < 0 else "" h, m, s, ms = ms_to_times(abs(ms)) if fractions: return sgn + "{:01d}:{:02d}:{:02d}.{:03d}".format(h, m, s, ms) else: return sgn + "{:01d}:{:02d}:{:02d}".format(h, m, s)
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Prettyprint milliseconds to [-]H:MM:SS[.mmm] Handles huge and/or negative times. Non-negative times with ``fractions=True`` are matched by :data:`pysubs2.time.TIMESTAMP`. Arguments: ms: Number of milliseconds (int, float or other numeric class). fractions: Whether to print up to millisecond precision. Returns: str
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tkarabela/pysubs2
pysubs2/substation.py
ms_to_timestamp
def ms_to_timestamp(ms): """Convert ms to 'H:MM:SS.cc'""" # XXX throw on overflow/underflow? if ms < 0: ms = 0 if ms > MAX_REPRESENTABLE_TIME: ms = MAX_REPRESENTABLE_TIME h, m, s, ms = ms_to_times(ms) return "%01d:%02d:%02d.%02d" % (h, m, s, ms//10)
python
def ms_to_timestamp(ms): """Convert ms to 'H:MM:SS.cc'""" # XXX throw on overflow/underflow? if ms < 0: ms = 0 if ms > MAX_REPRESENTABLE_TIME: ms = MAX_REPRESENTABLE_TIME h, m, s, ms = ms_to_times(ms) return "%01d:%02d:%02d.%02d" % (h, m, s, ms//10)
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tkarabela/pysubs2
pysubs2/substation.py
parse_tags
def parse_tags(text, style=SSAStyle.DEFAULT_STYLE, styles={}): """ Split text into fragments with computed SSAStyles. Returns list of tuples (fragment, style), where fragment is a part of text between two brace-delimited override sequences, and style is the computed styling of the fragment, ie. the original style modified by all override sequences before the fragment. Newline and non-breakable space overrides are left as-is. Supported override tags: - i, b, u, s - r (with or without style name) """ fragments = SSAEvent.OVERRIDE_SEQUENCE.split(text) if len(fragments) == 1: return [(text, style)] def apply_overrides(all_overrides): s = style.copy() for tag in re.findall(r"\\[ibus][10]|\\r[a-zA-Z_0-9 ]*", all_overrides): if tag == r"\r": s = style.copy() # reset to original line style elif tag.startswith(r"\r"): name = tag[2:] if name in styles: s = styles[name].copy() # reset to named style else: if "i" in tag: s.italic = "1" in tag elif "b" in tag: s.bold = "1" in tag elif "u" in tag: s.underline = "1" in tag elif "s" in tag: s.strikeout = "1" in tag return s overrides = SSAEvent.OVERRIDE_SEQUENCE.findall(text) overrides_prefix_sum = ["".join(overrides[:i]) for i in range(len(overrides) + 1)] computed_styles = map(apply_overrides, overrides_prefix_sum) return list(zip(fragments, computed_styles))
python
def parse_tags(text, style=SSAStyle.DEFAULT_STYLE, styles={}): """ Split text into fragments with computed SSAStyles. Returns list of tuples (fragment, style), where fragment is a part of text between two brace-delimited override sequences, and style is the computed styling of the fragment, ie. the original style modified by all override sequences before the fragment. Newline and non-breakable space overrides are left as-is. Supported override tags: - i, b, u, s - r (with or without style name) """ fragments = SSAEvent.OVERRIDE_SEQUENCE.split(text) if len(fragments) == 1: return [(text, style)] def apply_overrides(all_overrides): s = style.copy() for tag in re.findall(r"\\[ibus][10]|\\r[a-zA-Z_0-9 ]*", all_overrides): if tag == r"\r": s = style.copy() # reset to original line style elif tag.startswith(r"\r"): name = tag[2:] if name in styles: s = styles[name].copy() # reset to named style else: if "i" in tag: s.italic = "1" in tag elif "b" in tag: s.bold = "1" in tag elif "u" in tag: s.underline = "1" in tag elif "s" in tag: s.strikeout = "1" in tag return s overrides = SSAEvent.OVERRIDE_SEQUENCE.findall(text) overrides_prefix_sum = ["".join(overrides[:i]) for i in range(len(overrides) + 1)] computed_styles = map(apply_overrides, overrides_prefix_sum) return list(zip(fragments, computed_styles))
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/substation.py#L89-L130
tkarabela/pysubs2
pysubs2/ssaevent.py
SSAEvent.plaintext
def plaintext(self): """ Subtitle text as multi-line string with no tags (read/write property). Writing to this property replaces :attr:`SSAEvent.text` with given plain text. Newlines are converted to ``\\N`` tags. """ text = self.text text = self.OVERRIDE_SEQUENCE.sub("", text) text = text.replace(r"\h", " ") text = text.replace(r"\n", "\n") text = text.replace(r"\N", "\n") return text
python
def plaintext(self): """ Subtitle text as multi-line string with no tags (read/write property). Writing to this property replaces :attr:`SSAEvent.text` with given plain text. Newlines are converted to ``\\N`` tags. """ text = self.text text = self.OVERRIDE_SEQUENCE.sub("", text) text = text.replace(r"\h", " ") text = text.replace(r"\n", "\n") text = text.replace(r"\N", "\n") return text
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Subtitle text as multi-line string with no tags (read/write property). Writing to this property replaces :attr:`SSAEvent.text` with given plain text. Newlines are converted to ``\\N`` tags.
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssaevent.py#L87-L99
tkarabela/pysubs2
pysubs2/ssaevent.py
SSAEvent.shift
def shift(self, h=0, m=0, s=0, ms=0, frames=None, fps=None): """ Shift start and end times. See :meth:`SSAFile.shift()` for full description. """ delta = make_time(h=h, m=m, s=s, ms=ms, frames=frames, fps=fps) self.start += delta self.end += delta
python
def shift(self, h=0, m=0, s=0, ms=0, frames=None, fps=None): """ Shift start and end times. See :meth:`SSAFile.shift()` for full description. """ delta = make_time(h=h, m=m, s=s, ms=ms, frames=frames, fps=fps) self.start += delta self.end += delta
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Shift start and end times. See :meth:`SSAFile.shift()` for full description.
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssaevent.py#L105-L114
tkarabela/pysubs2
pysubs2/ssaevent.py
SSAEvent.equals
def equals(self, other): """Field-based equality for SSAEvents.""" if isinstance(other, SSAEvent): return self.as_dict() == other.as_dict() else: raise TypeError("Cannot compare to non-SSAEvent object")
python
def equals(self, other): """Field-based equality for SSAEvents.""" if isinstance(other, SSAEvent): return self.as_dict() == other.as_dict() else: raise TypeError("Cannot compare to non-SSAEvent object")
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Field-based equality for SSAEvents.
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssaevent.py#L123-L128
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.load
def load(cls, path, encoding="utf-8", format_=None, fps=None, **kwargs): """ Load subtitle file from given path. Arguments: path (str): Path to subtitle file. encoding (str): Character encoding of input file. Defaults to UTF-8, you may need to change this. format_ (str): Optional, forces use of specific parser (eg. `"srt"`, `"ass"`). Otherwise, format is detected automatically from file contents. This argument should be rarely needed. fps (float): Framerate for frame-based formats (MicroDVD), for other formats this argument is ignored. Framerate might be detected from the file, in which case you don't need to specify it here (when given, this argument overrides autodetection). kwargs: Extra options for the parser. Returns: SSAFile Raises: IOError UnicodeDecodeError pysubs2.exceptions.UnknownFPSError pysubs2.exceptions.UnknownFormatIdentifierError pysubs2.exceptions.FormatAutodetectionError Note: pysubs2 may autodetect subtitle format and/or framerate. These values are set as :attr:`SSAFile.format` and :attr:`SSAFile.fps` attributes. Example: >>> subs1 = pysubs2.load("subrip-subtitles.srt") >>> subs2 = pysubs2.load("microdvd-subtitles.sub", fps=23.976) """ with open(path, encoding=encoding) as fp: return cls.from_file(fp, format_, fps=fps, **kwargs)
python
def load(cls, path, encoding="utf-8", format_=None, fps=None, **kwargs): """ Load subtitle file from given path. Arguments: path (str): Path to subtitle file. encoding (str): Character encoding of input file. Defaults to UTF-8, you may need to change this. format_ (str): Optional, forces use of specific parser (eg. `"srt"`, `"ass"`). Otherwise, format is detected automatically from file contents. This argument should be rarely needed. fps (float): Framerate for frame-based formats (MicroDVD), for other formats this argument is ignored. Framerate might be detected from the file, in which case you don't need to specify it here (when given, this argument overrides autodetection). kwargs: Extra options for the parser. Returns: SSAFile Raises: IOError UnicodeDecodeError pysubs2.exceptions.UnknownFPSError pysubs2.exceptions.UnknownFormatIdentifierError pysubs2.exceptions.FormatAutodetectionError Note: pysubs2 may autodetect subtitle format and/or framerate. These values are set as :attr:`SSAFile.format` and :attr:`SSAFile.fps` attributes. Example: >>> subs1 = pysubs2.load("subrip-subtitles.srt") >>> subs2 = pysubs2.load("microdvd-subtitles.sub", fps=23.976) """ with open(path, encoding=encoding) as fp: return cls.from_file(fp, format_, fps=fps, **kwargs)
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Load subtitle file from given path. Arguments: path (str): Path to subtitle file. encoding (str): Character encoding of input file. Defaults to UTF-8, you may need to change this. format_ (str): Optional, forces use of specific parser (eg. `"srt"`, `"ass"`). Otherwise, format is detected automatically from file contents. This argument should be rarely needed. fps (float): Framerate for frame-based formats (MicroDVD), for other formats this argument is ignored. Framerate might be detected from the file, in which case you don't need to specify it here (when given, this argument overrides autodetection). kwargs: Extra options for the parser. Returns: SSAFile Raises: IOError UnicodeDecodeError pysubs2.exceptions.UnknownFPSError pysubs2.exceptions.UnknownFormatIdentifierError pysubs2.exceptions.FormatAutodetectionError Note: pysubs2 may autodetect subtitle format and/or framerate. These values are set as :attr:`SSAFile.format` and :attr:`SSAFile.fps` attributes. Example: >>> subs1 = pysubs2.load("subrip-subtitles.srt") >>> subs2 = pysubs2.load("microdvd-subtitles.sub", fps=23.976)
[ "Load", "subtitle", "file", "from", "given", "path", "." ]
train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L52-L92
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.from_string
def from_string(cls, string, format_=None, fps=None, **kwargs): """ Load subtitle file from string. See :meth:`SSAFile.load()` for full description. Arguments: string (str): Subtitle file in a string. Note that the string must be Unicode (in Python 2). Returns: SSAFile Example: >>> text = ''' ... 1 ... 00:00:00,000 --> 00:00:05,000 ... An example SubRip file. ... ''' >>> subs = SSAFile.from_string(text) """ fp = io.StringIO(string) return cls.from_file(fp, format_, fps=fps, **kwargs)
python
def from_string(cls, string, format_=None, fps=None, **kwargs): """ Load subtitle file from string. See :meth:`SSAFile.load()` for full description. Arguments: string (str): Subtitle file in a string. Note that the string must be Unicode (in Python 2). Returns: SSAFile Example: >>> text = ''' ... 1 ... 00:00:00,000 --> 00:00:05,000 ... An example SubRip file. ... ''' >>> subs = SSAFile.from_string(text) """ fp = io.StringIO(string) return cls.from_file(fp, format_, fps=fps, **kwargs)
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Load subtitle file from string. See :meth:`SSAFile.load()` for full description. Arguments: string (str): Subtitle file in a string. Note that the string must be Unicode (in Python 2). Returns: SSAFile Example: >>> text = ''' ... 1 ... 00:00:00,000 --> 00:00:05,000 ... An example SubRip file. ... ''' >>> subs = SSAFile.from_string(text)
[ "Load", "subtitle", "file", "from", "string", "." ]
train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L95-L118
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.from_file
def from_file(cls, fp, format_=None, fps=None, **kwargs): """ Read subtitle file from file object. See :meth:`SSAFile.load()` for full description. Note: This is a low-level method. Usually, one of :meth:`SSAFile.load()` or :meth:`SSAFile.from_string()` is preferable. Arguments: fp (file object): A file object, ie. :class:`io.TextIOBase` instance. Note that the file must be opened in text mode (as opposed to binary). Returns: SSAFile """ if format_ is None: # Autodetect subtitle format, then read again using correct parser. # The file might be a pipe and we need to read it twice, # so just buffer everything. text = fp.read() fragment = text[:10000] format_ = autodetect_format(fragment) fp = io.StringIO(text) impl = get_format_class(format_) subs = cls() # an empty subtitle file subs.format = format_ subs.fps = fps impl.from_file(subs, fp, format_, fps=fps, **kwargs) return subs
python
def from_file(cls, fp, format_=None, fps=None, **kwargs): """ Read subtitle file from file object. See :meth:`SSAFile.load()` for full description. Note: This is a low-level method. Usually, one of :meth:`SSAFile.load()` or :meth:`SSAFile.from_string()` is preferable. Arguments: fp (file object): A file object, ie. :class:`io.TextIOBase` instance. Note that the file must be opened in text mode (as opposed to binary). Returns: SSAFile """ if format_ is None: # Autodetect subtitle format, then read again using correct parser. # The file might be a pipe and we need to read it twice, # so just buffer everything. text = fp.read() fragment = text[:10000] format_ = autodetect_format(fragment) fp = io.StringIO(text) impl = get_format_class(format_) subs = cls() # an empty subtitle file subs.format = format_ subs.fps = fps impl.from_file(subs, fp, format_, fps=fps, **kwargs) return subs
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L121-L153
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.save
def save(self, path, encoding="utf-8", format_=None, fps=None, **kwargs): """ Save subtitle file to given path. Arguments: path (str): Path to subtitle file. encoding (str): Character encoding of output file. Defaults to UTF-8, which should be fine for most purposes. format_ (str): Optional, specifies desired subtitle format (eg. `"srt"`, `"ass"`). Otherwise, format is detected automatically from file extension. Thus, this argument is rarely needed. fps (float): Framerate for frame-based formats (MicroDVD), for other formats this argument is ignored. When omitted, :attr:`SSAFile.fps` value is used (ie. the framerate used for loading the file, if any). When the :class:`SSAFile` wasn't loaded from MicroDVD, or if you wish save it with different framerate, use this argument. See also :meth:`SSAFile.transform_framerate()` for fixing bad frame-based to time-based conversions. kwargs: Extra options for the writer. Raises: IOError UnicodeEncodeError pysubs2.exceptions.UnknownFPSError pysubs2.exceptions.UnknownFormatIdentifierError pysubs2.exceptions.UnknownFileExtensionError """ if format_ is None: ext = os.path.splitext(path)[1].lower() format_ = get_format_identifier(ext) with open(path, "w", encoding=encoding) as fp: self.to_file(fp, format_, fps=fps, **kwargs)
python
def save(self, path, encoding="utf-8", format_=None, fps=None, **kwargs): """ Save subtitle file to given path. Arguments: path (str): Path to subtitle file. encoding (str): Character encoding of output file. Defaults to UTF-8, which should be fine for most purposes. format_ (str): Optional, specifies desired subtitle format (eg. `"srt"`, `"ass"`). Otherwise, format is detected automatically from file extension. Thus, this argument is rarely needed. fps (float): Framerate for frame-based formats (MicroDVD), for other formats this argument is ignored. When omitted, :attr:`SSAFile.fps` value is used (ie. the framerate used for loading the file, if any). When the :class:`SSAFile` wasn't loaded from MicroDVD, or if you wish save it with different framerate, use this argument. See also :meth:`SSAFile.transform_framerate()` for fixing bad frame-based to time-based conversions. kwargs: Extra options for the writer. Raises: IOError UnicodeEncodeError pysubs2.exceptions.UnknownFPSError pysubs2.exceptions.UnknownFormatIdentifierError pysubs2.exceptions.UnknownFileExtensionError """ if format_ is None: ext = os.path.splitext(path)[1].lower() format_ = get_format_identifier(ext) with open(path, "w", encoding=encoding) as fp: self.to_file(fp, format_, fps=fps, **kwargs)
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Save subtitle file to given path. Arguments: path (str): Path to subtitle file. encoding (str): Character encoding of output file. Defaults to UTF-8, which should be fine for most purposes. format_ (str): Optional, specifies desired subtitle format (eg. `"srt"`, `"ass"`). Otherwise, format is detected automatically from file extension. Thus, this argument is rarely needed. fps (float): Framerate for frame-based formats (MicroDVD), for other formats this argument is ignored. When omitted, :attr:`SSAFile.fps` value is used (ie. the framerate used for loading the file, if any). When the :class:`SSAFile` wasn't loaded from MicroDVD, or if you wish save it with different framerate, use this argument. See also :meth:`SSAFile.transform_framerate()` for fixing bad frame-based to time-based conversions. kwargs: Extra options for the writer. Raises: IOError UnicodeEncodeError pysubs2.exceptions.UnknownFPSError pysubs2.exceptions.UnknownFormatIdentifierError pysubs2.exceptions.UnknownFileExtensionError
[ "Save", "subtitle", "file", "to", "given", "path", "." ]
train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L155-L190
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.to_string
def to_string(self, format_, fps=None, **kwargs): """ Get subtitle file as a string. See :meth:`SSAFile.save()` for full description. Returns: str """ fp = io.StringIO() self.to_file(fp, format_, fps=fps, **kwargs) return fp.getvalue()
python
def to_string(self, format_, fps=None, **kwargs): """ Get subtitle file as a string. See :meth:`SSAFile.save()` for full description. Returns: str """ fp = io.StringIO() self.to_file(fp, format_, fps=fps, **kwargs) return fp.getvalue()
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Get subtitle file as a string. See :meth:`SSAFile.save()` for full description. Returns: str
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L192-L204
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.to_file
def to_file(self, fp, format_, fps=None, **kwargs): """ Write subtitle file to file object. See :meth:`SSAFile.save()` for full description. Note: This is a low-level method. Usually, one of :meth:`SSAFile.save()` or :meth:`SSAFile.to_string()` is preferable. Arguments: fp (file object): A file object, ie. :class:`io.TextIOBase` instance. Note that the file must be opened in text mode (as opposed to binary). """ impl = get_format_class(format_) impl.to_file(self, fp, format_, fps=fps, **kwargs)
python
def to_file(self, fp, format_, fps=None, **kwargs): """ Write subtitle file to file object. See :meth:`SSAFile.save()` for full description. Note: This is a low-level method. Usually, one of :meth:`SSAFile.save()` or :meth:`SSAFile.to_string()` is preferable. Arguments: fp (file object): A file object, ie. :class:`io.TextIOBase` instance. Note that the file must be opened in text mode (as opposed to binary). """ impl = get_format_class(format_) impl.to_file(self, fp, format_, fps=fps, **kwargs)
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Write subtitle file to file object. See :meth:`SSAFile.save()` for full description. Note: This is a low-level method. Usually, one of :meth:`SSAFile.save()` or :meth:`SSAFile.to_string()` is preferable. Arguments: fp (file object): A file object, ie. :class:`io.TextIOBase` instance. Note that the file must be opened in text mode (as opposed to binary).
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L206-L222
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.transform_framerate
def transform_framerate(self, in_fps, out_fps): """ Rescale all timestamps by ratio of in_fps/out_fps. Can be used to fix files converted from frame-based to time-based with wrongly assumed framerate. Arguments: in_fps (float) out_fps (float) Raises: ValueError: Non-positive framerate given. """ if in_fps <= 0 or out_fps <= 0: raise ValueError("Framerates must be positive, cannot transform %f -> %f" % (in_fps, out_fps)) ratio = in_fps / out_fps for line in self: line.start = int(round(line.start * ratio)) line.end = int(round(line.end * ratio))
python
def transform_framerate(self, in_fps, out_fps): """ Rescale all timestamps by ratio of in_fps/out_fps. Can be used to fix files converted from frame-based to time-based with wrongly assumed framerate. Arguments: in_fps (float) out_fps (float) Raises: ValueError: Non-positive framerate given. """ if in_fps <= 0 or out_fps <= 0: raise ValueError("Framerates must be positive, cannot transform %f -> %f" % (in_fps, out_fps)) ratio = in_fps / out_fps for line in self: line.start = int(round(line.start * ratio)) line.end = int(round(line.end * ratio))
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Rescale all timestamps by ratio of in_fps/out_fps. Can be used to fix files converted from frame-based to time-based with wrongly assumed framerate. Arguments: in_fps (float) out_fps (float) Raises: ValueError: Non-positive framerate given.
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L250-L271
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.rename_style
def rename_style(self, old_name, new_name): """ Rename a style, including references to it. Arguments: old_name (str): Style to be renamed. new_name (str): New name for the style (must be unused). Raises: KeyError: No style named old_name. ValueError: new_name is not a legal name (cannot use commas) or new_name is taken. """ if old_name not in self.styles: raise KeyError("Style %r not found" % old_name) if new_name in self.styles: raise ValueError("There is already a style called %r" % new_name) if not is_valid_field_content(new_name): raise ValueError("%r is not a valid name" % new_name) self.styles[new_name] = self.styles[old_name] del self.styles[old_name] for line in self: # XXX also handle \r override tag if line.style == old_name: line.style = new_name
python
def rename_style(self, old_name, new_name): """ Rename a style, including references to it. Arguments: old_name (str): Style to be renamed. new_name (str): New name for the style (must be unused). Raises: KeyError: No style named old_name. ValueError: new_name is not a legal name (cannot use commas) or new_name is taken. """ if old_name not in self.styles: raise KeyError("Style %r not found" % old_name) if new_name in self.styles: raise ValueError("There is already a style called %r" % new_name) if not is_valid_field_content(new_name): raise ValueError("%r is not a valid name" % new_name) self.styles[new_name] = self.styles[old_name] del self.styles[old_name] for line in self: # XXX also handle \r override tag if line.style == old_name: line.style = new_name
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Rename a style, including references to it. Arguments: old_name (str): Style to be renamed. new_name (str): New name for the style (must be unused). Raises: KeyError: No style named old_name. ValueError: new_name is not a legal name (cannot use commas) or new_name is taken.
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L277-L304
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.import_styles
def import_styles(self, subs, overwrite=True): """ Merge in styles from other SSAFile. Arguments: subs (SSAFile): Subtitle file imported from. overwrite (bool): On name conflict, use style from the other file (default: True). """ if not isinstance(subs, SSAFile): raise TypeError("Must supply an SSAFile.") for name, style in subs.styles.items(): if name not in self.styles or overwrite: self.styles[name] = style
python
def import_styles(self, subs, overwrite=True): """ Merge in styles from other SSAFile. Arguments: subs (SSAFile): Subtitle file imported from. overwrite (bool): On name conflict, use style from the other file (default: True). """ if not isinstance(subs, SSAFile): raise TypeError("Must supply an SSAFile.") for name, style in subs.styles.items(): if name not in self.styles or overwrite: self.styles[name] = style
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Merge in styles from other SSAFile. Arguments: subs (SSAFile): Subtitle file imported from. overwrite (bool): On name conflict, use style from the other file (default: True).
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L306-L321
tkarabela/pysubs2
pysubs2/ssafile.py
SSAFile.equals
def equals(self, other): """ Equality of two SSAFiles. Compares :attr:`SSAFile.info`, :attr:`SSAFile.styles` and :attr:`SSAFile.events`. Order of entries in OrderedDicts does not matter. "ScriptType" key in info is considered an implementation detail and thus ignored. Useful mostly in unit tests. Differences are logged at DEBUG level. """ if isinstance(other, SSAFile): for key in set(chain(self.info.keys(), other.info.keys())) - {"ScriptType"}: sv, ov = self.info.get(key), other.info.get(key) if sv is None: logging.debug("%r missing in self.info", key) return False elif ov is None: logging.debug("%r missing in other.info", key) return False elif sv != ov: logging.debug("info %r differs (self=%r, other=%r)", key, sv, ov) return False for key in set(chain(self.styles.keys(), other.styles.keys())): sv, ov = self.styles.get(key), other.styles.get(key) if sv is None: logging.debug("%r missing in self.styles", key) return False elif ov is None: logging.debug("%r missing in other.styles", key) return False elif sv != ov: for k in sv.FIELDS: if getattr(sv, k) != getattr(ov, k): logging.debug("difference in field %r", k) logging.debug("style %r differs (self=%r, other=%r)", key, sv.as_dict(), ov.as_dict()) return False if len(self) != len(other): logging.debug("different # of subtitles (self=%d, other=%d)", len(self), len(other)) return False for i, (se, oe) in enumerate(zip(self.events, other.events)): if not se.equals(oe): for k in se.FIELDS: if getattr(se, k) != getattr(oe, k): logging.debug("difference in field %r", k) logging.debug("event %d differs (self=%r, other=%r)", i, se.as_dict(), oe.as_dict()) return False return True else: raise TypeError("Cannot compare to non-SSAFile object")
python
def equals(self, other): """ Equality of two SSAFiles. Compares :attr:`SSAFile.info`, :attr:`SSAFile.styles` and :attr:`SSAFile.events`. Order of entries in OrderedDicts does not matter. "ScriptType" key in info is considered an implementation detail and thus ignored. Useful mostly in unit tests. Differences are logged at DEBUG level. """ if isinstance(other, SSAFile): for key in set(chain(self.info.keys(), other.info.keys())) - {"ScriptType"}: sv, ov = self.info.get(key), other.info.get(key) if sv is None: logging.debug("%r missing in self.info", key) return False elif ov is None: logging.debug("%r missing in other.info", key) return False elif sv != ov: logging.debug("info %r differs (self=%r, other=%r)", key, sv, ov) return False for key in set(chain(self.styles.keys(), other.styles.keys())): sv, ov = self.styles.get(key), other.styles.get(key) if sv is None: logging.debug("%r missing in self.styles", key) return False elif ov is None: logging.debug("%r missing in other.styles", key) return False elif sv != ov: for k in sv.FIELDS: if getattr(sv, k) != getattr(ov, k): logging.debug("difference in field %r", k) logging.debug("style %r differs (self=%r, other=%r)", key, sv.as_dict(), ov.as_dict()) return False if len(self) != len(other): logging.debug("different # of subtitles (self=%d, other=%d)", len(self), len(other)) return False for i, (se, oe) in enumerate(zip(self.events, other.events)): if not se.equals(oe): for k in se.FIELDS: if getattr(se, k) != getattr(oe, k): logging.debug("difference in field %r", k) logging.debug("event %d differs (self=%r, other=%r)", i, se.as_dict(), oe.as_dict()) return False return True else: raise TypeError("Cannot compare to non-SSAFile object")
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Equality of two SSAFiles. Compares :attr:`SSAFile.info`, :attr:`SSAFile.styles` and :attr:`SSAFile.events`. Order of entries in OrderedDicts does not matter. "ScriptType" key in info is considered an implementation detail and thus ignored. Useful mostly in unit tests. Differences are logged at DEBUG level.
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/ssafile.py#L327-L379
tkarabela/pysubs2
pysubs2/formats.py
get_file_extension
def get_file_extension(format_): """Format identifier -> file extension""" if format_ not in FORMAT_IDENTIFIER_TO_FORMAT_CLASS: raise UnknownFormatIdentifierError(format_) for ext, f in FILE_EXTENSION_TO_FORMAT_IDENTIFIER.items(): if f == format_: return ext raise RuntimeError("No file extension for format %r" % format_)
python
def get_file_extension(format_): """Format identifier -> file extension""" if format_ not in FORMAT_IDENTIFIER_TO_FORMAT_CLASS: raise UnknownFormatIdentifierError(format_) for ext, f in FILE_EXTENSION_TO_FORMAT_IDENTIFIER.items(): if f == format_: return ext raise RuntimeError("No file extension for format %r" % format_)
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Format identifier -> file extension
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/formats.py#L42-L51
tkarabela/pysubs2
pysubs2/formats.py
autodetect_format
def autodetect_format(content): """Return format identifier for given fragment or raise FormatAutodetectionError.""" formats = set() for impl in FORMAT_IDENTIFIER_TO_FORMAT_CLASS.values(): guess = impl.guess_format(content) if guess is not None: formats.add(guess) if len(formats) == 1: return formats.pop() elif not formats: raise FormatAutodetectionError("No suitable formats") else: raise FormatAutodetectionError("Multiple suitable formats (%r)" % formats)
python
def autodetect_format(content): """Return format identifier for given fragment or raise FormatAutodetectionError.""" formats = set() for impl in FORMAT_IDENTIFIER_TO_FORMAT_CLASS.values(): guess = impl.guess_format(content) if guess is not None: formats.add(guess) if len(formats) == 1: return formats.pop() elif not formats: raise FormatAutodetectionError("No suitable formats") else: raise FormatAutodetectionError("Multiple suitable formats (%r)" % formats)
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Return format identifier for given fragment or raise FormatAutodetectionError.
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train
https://github.com/tkarabela/pysubs2/blob/6439eb5159e6aa6b47e0f8e1d950e8bdd7c5341f/pysubs2/formats.py#L53-L66
aio-libs/aiohttp-devtools
aiohttp_devtools/runserver/serve.py
modify_main_app
def modify_main_app(app, config: Config): """ Modify the app we're serving to make development easier, eg. * modify responses to add the livereload snippet * set ``static_root_url`` on the app * setup the debug toolbar """ app._debug = True dft_logger.debug('livereload enabled: %s', '✓' if config.livereload else '✖') def get_host(request): if config.infer_host: return request.headers.get('host', 'localhost').split(':', 1)[0] else: return config.host if config.livereload: async def on_prepare(request, response): if (not request.path.startswith('/_debugtoolbar') and 'text/html' in response.content_type and getattr(response, 'body', False)): lr_snippet = LIVE_RELOAD_HOST_SNIPPET.format(get_host(request), config.aux_port) dft_logger.debug('appending live reload snippet "%s" to body', lr_snippet) response.body += lr_snippet.encode() app.on_response_prepare.append(on_prepare) static_path = config.static_url.strip('/') if config.infer_host and config.static_path is not None: # we set the app key even in middleware to make the switch to production easier and for backwards compat. @web.middleware async def static_middleware(request, handler): static_url = 'http://{}:{}/{}'.format(get_host(request), config.aux_port, static_path) dft_logger.debug('settings app static_root_url to "%s"', static_url) request.app['static_root_url'].change(static_url) return await handler(request) app.middlewares.insert(0, static_middleware) if config.static_path is not None: static_url = 'http://{}:{}/{}'.format(config.host, config.aux_port, static_path) dft_logger.debug('settings app static_root_url to "%s"', static_url) app['static_root_url'] = MutableValue(static_url) if config.debug_toolbar and aiohttp_debugtoolbar: aiohttp_debugtoolbar.setup(app, intercept_redirects=False)
python
def modify_main_app(app, config: Config): """ Modify the app we're serving to make development easier, eg. * modify responses to add the livereload snippet * set ``static_root_url`` on the app * setup the debug toolbar """ app._debug = True dft_logger.debug('livereload enabled: %s', '✓' if config.livereload else '✖') def get_host(request): if config.infer_host: return request.headers.get('host', 'localhost').split(':', 1)[0] else: return config.host if config.livereload: async def on_prepare(request, response): if (not request.path.startswith('/_debugtoolbar') and 'text/html' in response.content_type and getattr(response, 'body', False)): lr_snippet = LIVE_RELOAD_HOST_SNIPPET.format(get_host(request), config.aux_port) dft_logger.debug('appending live reload snippet "%s" to body', lr_snippet) response.body += lr_snippet.encode() app.on_response_prepare.append(on_prepare) static_path = config.static_url.strip('/') if config.infer_host and config.static_path is not None: # we set the app key even in middleware to make the switch to production easier and for backwards compat. @web.middleware async def static_middleware(request, handler): static_url = 'http://{}:{}/{}'.format(get_host(request), config.aux_port, static_path) dft_logger.debug('settings app static_root_url to "%s"', static_url) request.app['static_root_url'].change(static_url) return await handler(request) app.middlewares.insert(0, static_middleware) if config.static_path is not None: static_url = 'http://{}:{}/{}'.format(config.host, config.aux_port, static_path) dft_logger.debug('settings app static_root_url to "%s"', static_url) app['static_root_url'] = MutableValue(static_url) if config.debug_toolbar and aiohttp_debugtoolbar: aiohttp_debugtoolbar.setup(app, intercept_redirects=False)
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/runserver/serve.py#L36-L80
aio-libs/aiohttp-devtools
aiohttp_devtools/runserver/serve.py
src_reload
async def src_reload(app, path: str = None): """ prompt each connected browser to reload by sending websocket message. :param path: if supplied this must be a path relative to app['static_path'], eg. reload of a single file is only supported for static resources. :return: number of sources reloaded """ cli_count = len(app[WS]) if cli_count == 0: return 0 is_html = None if path: path = str(Path(app['static_url']) / Path(path).relative_to(app['static_path'])) is_html = mimetypes.guess_type(path)[0] == 'text/html' reloads = 0 aux_logger.debug('prompting source reload for %d clients', cli_count) for ws, url in app[WS]: if path and is_html and path not in {url, url + '.html', url.rstrip('/') + '/index.html'}: aux_logger.debug('skipping reload for client at %s', url) continue aux_logger.debug('reload client at %s', url) data = { 'command': 'reload', 'path': path or url, 'liveCSS': True, 'liveImg': True, } try: await ws.send_str(json.dumps(data)) except RuntimeError as e: # eg. "RuntimeError: websocket connection is closing" aux_logger.error('Error broadcasting change to %s, RuntimeError: %s', path or url, e) else: reloads += 1 if reloads: s = '' if reloads == 1 else 's' aux_logger.info('prompted reload of %s on %d client%s', path or 'page', reloads, s) return reloads
python
async def src_reload(app, path: str = None): """ prompt each connected browser to reload by sending websocket message. :param path: if supplied this must be a path relative to app['static_path'], eg. reload of a single file is only supported for static resources. :return: number of sources reloaded """ cli_count = len(app[WS]) if cli_count == 0: return 0 is_html = None if path: path = str(Path(app['static_url']) / Path(path).relative_to(app['static_path'])) is_html = mimetypes.guess_type(path)[0] == 'text/html' reloads = 0 aux_logger.debug('prompting source reload for %d clients', cli_count) for ws, url in app[WS]: if path and is_html and path not in {url, url + '.html', url.rstrip('/') + '/index.html'}: aux_logger.debug('skipping reload for client at %s', url) continue aux_logger.debug('reload client at %s', url) data = { 'command': 'reload', 'path': path or url, 'liveCSS': True, 'liveImg': True, } try: await ws.send_str(json.dumps(data)) except RuntimeError as e: # eg. "RuntimeError: websocket connection is closing" aux_logger.error('Error broadcasting change to %s, RuntimeError: %s', path or url, e) else: reloads += 1 if reloads: s = '' if reloads == 1 else 's' aux_logger.info('prompted reload of %s on %d client%s', path or 'page', reloads, s) return reloads
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prompt each connected browser to reload by sending websocket message. :param path: if supplied this must be a path relative to app['static_path'], eg. reload of a single file is only supported for static resources. :return: number of sources reloaded
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/runserver/serve.py#L145-L186
aio-libs/aiohttp-devtools
aiohttp_devtools/runserver/serve.py
CustomStaticResource.modify_request
def modify_request(self, request): """ Apply common path conventions eg. / > /index.html, /foobar > /foobar.html """ filename = URL.build(path=request.match_info['filename'], encoded=True).path raw_path = self._directory.joinpath(filename) try: filepath = raw_path.resolve() if not filepath.exists(): # simulate strict=True for python 3.6 which is not permitted with 3.5 raise FileNotFoundError() except FileNotFoundError: try: html_file = raw_path.with_name(raw_path.name + '.html').resolve().relative_to(self._directory) except (FileNotFoundError, ValueError): pass else: request.match_info['filename'] = str(html_file) else: if filepath.is_dir(): index_file = filepath / 'index.html' if index_file.exists(): try: request.match_info['filename'] = str(index_file.relative_to(self._directory)) except ValueError: # path is not not relative to self._directory pass
python
def modify_request(self, request): """ Apply common path conventions eg. / > /index.html, /foobar > /foobar.html """ filename = URL.build(path=request.match_info['filename'], encoded=True).path raw_path = self._directory.joinpath(filename) try: filepath = raw_path.resolve() if not filepath.exists(): # simulate strict=True for python 3.6 which is not permitted with 3.5 raise FileNotFoundError() except FileNotFoundError: try: html_file = raw_path.with_name(raw_path.name + '.html').resolve().relative_to(self._directory) except (FileNotFoundError, ValueError): pass else: request.match_info['filename'] = str(html_file) else: if filepath.is_dir(): index_file = filepath / 'index.html' if index_file.exists(): try: request.match_info['filename'] = str(index_file.relative_to(self._directory)) except ValueError: # path is not not relative to self._directory pass
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/runserver/serve.py#L288-L314
aio-libs/aiohttp-devtools
aiohttp_devtools/start/template/app/settings.py
Settings.substitute_environ
def substitute_environ(self): """ Substitute environment variables into settings. """ for attr_name in dir(self): if attr_name.startswith('_') or attr_name.upper() != attr_name: continue orig_value = getattr(self, attr_name) is_required = isinstance(orig_value, Required) orig_type = orig_value.v_type if is_required else type(orig_value) env_var_name = self._ENV_PREFIX + attr_name env_var = os.getenv(env_var_name, None) if env_var is not None: if issubclass(orig_type, bool): env_var = env_var.upper() in ('1', 'TRUE') elif issubclass(orig_type, int): env_var = int(env_var) elif issubclass(orig_type, Path): env_var = Path(env_var) elif issubclass(orig_type, bytes): env_var = env_var.encode() # could do floats here and lists etc via json setattr(self, attr_name, env_var) elif is_required and attr_name not in self._custom_settings: raise RuntimeError('The required environment variable "{0}" is currently not set, ' 'you\'ll need to run `source activate.settings.sh` ' 'or you can set that single environment variable with ' '`export {0}="<value>"`'.format(env_var_name))
python
def substitute_environ(self): """ Substitute environment variables into settings. """ for attr_name in dir(self): if attr_name.startswith('_') or attr_name.upper() != attr_name: continue orig_value = getattr(self, attr_name) is_required = isinstance(orig_value, Required) orig_type = orig_value.v_type if is_required else type(orig_value) env_var_name = self._ENV_PREFIX + attr_name env_var = os.getenv(env_var_name, None) if env_var is not None: if issubclass(orig_type, bool): env_var = env_var.upper() in ('1', 'TRUE') elif issubclass(orig_type, int): env_var = int(env_var) elif issubclass(orig_type, Path): env_var = Path(env_var) elif issubclass(orig_type, bytes): env_var = env_var.encode() # could do floats here and lists etc via json setattr(self, attr_name, env_var) elif is_required and attr_name not in self._custom_settings: raise RuntimeError('The required environment variable "{0}" is currently not set, ' 'you\'ll need to run `source activate.settings.sh` ' 'or you can set that single environment variable with ' '`export {0}="<value>"`'.format(env_var_name))
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/start/template/app/settings.py#L48-L76
aio-libs/aiohttp-devtools
aiohttp_devtools/start/template/app/management.py
prepare_database
def prepare_database(delete_existing: bool) -> bool: """ (Re)create a fresh database and run migrations. :param delete_existing: whether or not to drop an existing database if it exists :return: whether or not a database has been (re)created """ settings = Settings() conn = psycopg2.connect( password=settings.DB_PASSWORD, host=settings.DB_HOST, port=settings.DB_PORT, user=settings.DB_USER, ) conn.autocommit = True cur = conn.cursor() db_name = settings.DB_NAME cur.execute('SELECT EXISTS (SELECT datname FROM pg_catalog.pg_database WHERE datname=%s)', (db_name,)) already_exists = bool(cur.fetchone()[0]) if already_exists: if not delete_existing: print('database "{}" already exists, skipping'.format(db_name)) return False else: print('dropping database "{}" as it already exists...'.format(db_name)) cur.execute('DROP DATABASE {}'.format(db_name)) else: print('database "{}" does not yet exist'.format(db_name)) print('creating database "{}"...'.format(db_name)) cur.execute('CREATE DATABASE {}'.format(db_name)) cur.close() conn.close() # {% if database.is_pg_sqlalchemy %} engine = create_engine(pg_dsn(settings)) print('creating tables from model definition...') Base.metadata.create_all(engine) engine.dispose() # {% else %} # TODO # {% endif %} return True
python
def prepare_database(delete_existing: bool) -> bool: """ (Re)create a fresh database and run migrations. :param delete_existing: whether or not to drop an existing database if it exists :return: whether or not a database has been (re)created """ settings = Settings() conn = psycopg2.connect( password=settings.DB_PASSWORD, host=settings.DB_HOST, port=settings.DB_PORT, user=settings.DB_USER, ) conn.autocommit = True cur = conn.cursor() db_name = settings.DB_NAME cur.execute('SELECT EXISTS (SELECT datname FROM pg_catalog.pg_database WHERE datname=%s)', (db_name,)) already_exists = bool(cur.fetchone()[0]) if already_exists: if not delete_existing: print('database "{}" already exists, skipping'.format(db_name)) return False else: print('dropping database "{}" as it already exists...'.format(db_name)) cur.execute('DROP DATABASE {}'.format(db_name)) else: print('database "{}" does not yet exist'.format(db_name)) print('creating database "{}"...'.format(db_name)) cur.execute('CREATE DATABASE {}'.format(db_name)) cur.close() conn.close() # {% if database.is_pg_sqlalchemy %} engine = create_engine(pg_dsn(settings)) print('creating tables from model definition...') Base.metadata.create_all(engine) engine.dispose() # {% else %} # TODO # {% endif %} return True
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(Re)create a fresh database and run migrations. :param delete_existing: whether or not to drop an existing database if it exists :return: whether or not a database has been (re)created
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/start/template/app/management.py#L11-L54
aio-libs/aiohttp-devtools
aiohttp_devtools/start/template/app/views.py
index
async def index(request): """ This is the view handler for the "/" url. **Note: returning html without a template engine like jinja2 is ugly, no way around that.** :param request: the request object see http://aiohttp.readthedocs.io/en/stable/web_reference.html#request :return: aiohttp.web.Response object """ # {% if database.is_none and example.is_message_board %} # app.router allows us to generate urls based on their names, # see http://aiohttp.readthedocs.io/en/stable/web.html#reverse-url-constructing-using-named-resources message_url = request.app.router['messages'].url_for() ctx = dict( title=request.app['name'], styles_css_url=request.app['static_root_url'] + '/styles.css', content="""\ <p>Success! you've setup a basic aiohttp app.</p> <p>To demonstrate a little of the functionality of aiohttp this app implements a very simple message board.</p> <b> <a href="{message_url}">View and add messages</a> </b>""".format(message_url=message_url) ) # {% else %} ctx = dict( title=request.app['name'], styles_css_url=request.app['static_root_url'] + '/styles.css', content="<p>Success! you've setup a basic aiohttp app.</p>", ) # {% endif %} # with the base web.Response type we have to manually set the content type, otherwise text/plain will be used. return web.Response(text=BASE_PAGE.format(**ctx), content_type='text/html')
python
async def index(request): """ This is the view handler for the "/" url. **Note: returning html without a template engine like jinja2 is ugly, no way around that.** :param request: the request object see http://aiohttp.readthedocs.io/en/stable/web_reference.html#request :return: aiohttp.web.Response object """ # {% if database.is_none and example.is_message_board %} # app.router allows us to generate urls based on their names, # see http://aiohttp.readthedocs.io/en/stable/web.html#reverse-url-constructing-using-named-resources message_url = request.app.router['messages'].url_for() ctx = dict( title=request.app['name'], styles_css_url=request.app['static_root_url'] + '/styles.css', content="""\ <p>Success! you've setup a basic aiohttp app.</p> <p>To demonstrate a little of the functionality of aiohttp this app implements a very simple message board.</p> <b> <a href="{message_url}">View and add messages</a> </b>""".format(message_url=message_url) ) # {% else %} ctx = dict( title=request.app['name'], styles_css_url=request.app['static_root_url'] + '/styles.css', content="<p>Success! you've setup a basic aiohttp app.</p>", ) # {% endif %} # with the base web.Response type we have to manually set the content type, otherwise text/plain will be used. return web.Response(text=BASE_PAGE.format(**ctx), content_type='text/html')
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https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/start/template/app/views.py#L60-L91
aio-libs/aiohttp-devtools
aiohttp_devtools/start/template/app/views.py
message_data
async def message_data(request): """ As an example of aiohttp providing a non-html response, we load the actual messages for the "messages" view above via ajax using this endpoint to get data. see static/message_display.js for details of rendering. """ messages = [] # {% if database.is_none %} if request.app['settings'].MESSAGE_FILE.exists(): # read the message file, process it and populate the "messages" list with request.app['settings'].MESSAGE_FILE.open() as msg_file: for line in msg_file: if not line: # ignore blank lines eg. end of file continue # split the line into it constituent parts, see process_form above username, ts, message = line.split('|', 2) # parse the datetime string and render it in a more readable format. ts = '{:%Y-%m-%d %H:%M:%S}'.format(datetime.strptime(ts, '%Y-%m-%dT%H:%M:%S.%f')) messages.append({'username': username, 'timestamp': ts, 'message': message}) messages.reverse() # {% elif database.is_pg_sqlalchemy %} async with request.app['pg_engine'].acquire() as conn: async for row in conn.execute(sa_messages.select().order_by(sa_messages.c.timestamp.desc())): ts = '{:%Y-%m-%d %H:%M:%S}'.format(row.timestamp) messages.append({'username': row.username, 'timestamp': ts, 'message': row.message}) # {% endif %} return json_response(messages)
python
async def message_data(request): """ As an example of aiohttp providing a non-html response, we load the actual messages for the "messages" view above via ajax using this endpoint to get data. see static/message_display.js for details of rendering. """ messages = [] # {% if database.is_none %} if request.app['settings'].MESSAGE_FILE.exists(): # read the message file, process it and populate the "messages" list with request.app['settings'].MESSAGE_FILE.open() as msg_file: for line in msg_file: if not line: # ignore blank lines eg. end of file continue # split the line into it constituent parts, see process_form above username, ts, message = line.split('|', 2) # parse the datetime string and render it in a more readable format. ts = '{:%Y-%m-%d %H:%M:%S}'.format(datetime.strptime(ts, '%Y-%m-%dT%H:%M:%S.%f')) messages.append({'username': username, 'timestamp': ts, 'message': message}) messages.reverse() # {% elif database.is_pg_sqlalchemy %} async with request.app['pg_engine'].acquire() as conn: async for row in conn.execute(sa_messages.select().order_by(sa_messages.c.timestamp.desc())): ts = '{:%Y-%m-%d %H:%M:%S}'.format(row.timestamp) messages.append({'username': row.username, 'timestamp': ts, 'message': row.message}) # {% endif %} return json_response(messages)
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https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/start/template/app/views.py#L193-L220
aio-libs/aiohttp-devtools
aiohttp_devtools/start/template/app/main.py
pg_dsn
def pg_dsn(settings: Settings) -> str: """ :param settings: settings including connection settings :return: DSN url suitable for sqlalchemy and aiopg. """ return str(URL( database=settings.DB_NAME, password=settings.DB_PASSWORD, host=settings.DB_HOST, port=settings.DB_PORT, username=settings.DB_USER, drivername='postgres', ))
python
def pg_dsn(settings: Settings) -> str: """ :param settings: settings including connection settings :return: DSN url suitable for sqlalchemy and aiopg. """ return str(URL( database=settings.DB_NAME, password=settings.DB_PASSWORD, host=settings.DB_HOST, port=settings.DB_PORT, username=settings.DB_USER, drivername='postgres', ))
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:param settings: settings including connection settings :return: DSN url suitable for sqlalchemy and aiopg.
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https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/start/template/app/main.py#L32-L44
aio-libs/aiohttp-devtools
aiohttp_devtools/cli.py
serve
def serve(path, livereload, port, verbose): """ Serve static files from a directory. """ setup_logging(verbose) run_app(*serve_static(static_path=path, livereload=livereload, port=port))
python
def serve(path, livereload, port, verbose): """ Serve static files from a directory. """ setup_logging(verbose) run_app(*serve_static(static_path=path, livereload=livereload, port=port))
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Serve static files from a directory.
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/cli.py#L38-L43
aio-libs/aiohttp-devtools
aiohttp_devtools/cli.py
runserver
def runserver(**config): """ Run a development server for an aiohttp apps. Takes one argument "app-path" which should be a path to either a directory containing a recognized default file ("app.py" or "main.py") or to a specific file. Defaults to the environment variable "AIO_APP_PATH" or ".". The app path is run directly, see the "--app-factory" option for details on how an app is loaded from a python module. """ active_config = {k: v for k, v in config.items() if v is not None} setup_logging(config['verbose']) try: run_app(*_runserver(**active_config)) except AiohttpDevException as e: if config['verbose']: tb = click.style(traceback.format_exc().strip('\n'), fg='white', dim=True) main_logger.warning('AiohttpDevException traceback:\n%s', tb) main_logger.error('Error: %s', e) sys.exit(2)
python
def runserver(**config): """ Run a development server for an aiohttp apps. Takes one argument "app-path" which should be a path to either a directory containing a recognized default file ("app.py" or "main.py") or to a specific file. Defaults to the environment variable "AIO_APP_PATH" or ".". The app path is run directly, see the "--app-factory" option for details on how an app is loaded from a python module. """ active_config = {k: v for k, v in config.items() if v is not None} setup_logging(config['verbose']) try: run_app(*_runserver(**active_config)) except AiohttpDevException as e: if config['verbose']: tb = click.style(traceback.format_exc().strip('\n'), fg='white', dim=True) main_logger.warning('AiohttpDevException traceback:\n%s', tb) main_logger.error('Error: %s', e) sys.exit(2)
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Run a development server for an aiohttp apps. Takes one argument "app-path" which should be a path to either a directory containing a recognized default file ("app.py" or "main.py") or to a specific file. Defaults to the environment variable "AIO_APP_PATH" or ".". The app path is run directly, see the "--app-factory" option for details on how an app is loaded from a python module.
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/cli.py#L73-L92
aio-libs/aiohttp-devtools
aiohttp_devtools/cli.py
start
def start(*, path, name, verbose, **kwargs): """ Create a new aiohttp app. """ setup_logging(verbose) try: check_dir_clean(Path(path)) if name is None: name = Path(path).name for kwarg_name, choice_enum in DECISIONS: docs = dedent(choice_enum.__doc__).split('\n') title, *help_text = filter(bool, docs) click.secho('\n' + title, fg='green') if kwargs[kwarg_name] is None: click.secho('\n'.join(help_text), dim=True) choices = _display_enum_choices(choice_enum) kwargs[kwarg_name] = click.prompt( 'choose which {} to use {}'.format(kwarg_name, choices), type=EnumChoice(choice_enum), show_default=False, default=enum_default(choice_enum), ) click.echo('using: {}'.format(click.style(kwargs[kwarg_name], bold=True))) continue StartProject(path=path, name=name, **kwargs) except AiohttpDevException as e: main_logger.error('Error: %s', e) sys.exit(2)
python
def start(*, path, name, verbose, **kwargs): """ Create a new aiohttp app. """ setup_logging(verbose) try: check_dir_clean(Path(path)) if name is None: name = Path(path).name for kwarg_name, choice_enum in DECISIONS: docs = dedent(choice_enum.__doc__).split('\n') title, *help_text = filter(bool, docs) click.secho('\n' + title, fg='green') if kwargs[kwarg_name] is None: click.secho('\n'.join(help_text), dim=True) choices = _display_enum_choices(choice_enum) kwargs[kwarg_name] = click.prompt( 'choose which {} to use {}'.format(kwarg_name, choices), type=EnumChoice(choice_enum), show_default=False, default=enum_default(choice_enum), ) click.echo('using: {}'.format(click.style(kwargs[kwarg_name], bold=True))) continue StartProject(path=path, name=name, **kwargs) except AiohttpDevException as e: main_logger.error('Error: %s', e) sys.exit(2)
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/cli.py#L125-L154
aio-libs/aiohttp-devtools
aiohttp_devtools/runserver/config.py
Config.import_app_factory
def import_app_factory(self): """ Import attribute/class from from a python module. Raise AdevConfigError if the import failed. :return: (attribute, Path object for directory of file) """ rel_py_file = self.py_file.relative_to(self.python_path) module_path = '.'.join(rel_py_file.with_suffix('').parts) sys.path.append(str(self.python_path)) try: module = import_module(module_path) except ImportError as e: raise AdevConfigError('error importing "{}" ' 'from "{}": {}'.format(module_path, self.python_path, e)) from e logger.debug('successfully loaded "%s" from "%s"', module_path, self.python_path) if self.app_factory_name is None: try: self.app_factory_name = next(an for an in APP_FACTORY_NAMES if hasattr(module, an)) except StopIteration as e: raise AdevConfigError('No name supplied and no default app factory ' 'found in {s.py_file.name}'.format(s=self)) from e else: logger.debug('found default attribute "%s" in module "%s"', self.app_factory_name, module) try: attr = getattr(module, self.app_factory_name) except AttributeError as e: raise AdevConfigError('Module "{s.py_file.name}" ' 'does not define a "{s.app_factory_name}" attribute/class'.format(s=self)) from e self.watch_path = self.watch_path or Path(module.__file__).parent return attr
python
def import_app_factory(self): """ Import attribute/class from from a python module. Raise AdevConfigError if the import failed. :return: (attribute, Path object for directory of file) """ rel_py_file = self.py_file.relative_to(self.python_path) module_path = '.'.join(rel_py_file.with_suffix('').parts) sys.path.append(str(self.python_path)) try: module = import_module(module_path) except ImportError as e: raise AdevConfigError('error importing "{}" ' 'from "{}": {}'.format(module_path, self.python_path, e)) from e logger.debug('successfully loaded "%s" from "%s"', module_path, self.python_path) if self.app_factory_name is None: try: self.app_factory_name = next(an for an in APP_FACTORY_NAMES if hasattr(module, an)) except StopIteration as e: raise AdevConfigError('No name supplied and no default app factory ' 'found in {s.py_file.name}'.format(s=self)) from e else: logger.debug('found default attribute "%s" in module "%s"', self.app_factory_name, module) try: attr = getattr(module, self.app_factory_name) except AttributeError as e: raise AdevConfigError('Module "{s.py_file.name}" ' 'does not define a "{s.app_factory_name}" attribute/class'.format(s=self)) from e self.watch_path = self.watch_path or Path(module.__file__).parent return attr
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/runserver/config.py#L123-L158
aio-libs/aiohttp-devtools
aiohttp_devtools/runserver/main.py
runserver
def runserver(**config_kwargs): """ Prepare app ready to run development server. :param config_kwargs: see config.Config for more details :return: tuple (auxiliary app, auxiliary app port, event loop) """ # force a full reload in sub processes so they load an updated version of code, this must be called only once set_start_method('spawn') config = Config(**config_kwargs) config.import_app_factory() loop = asyncio.get_event_loop() loop.run_until_complete(check_port_open(config.main_port, loop)) aux_app = create_auxiliary_app( static_path=config.static_path_str, static_url=config.static_url, livereload=config.livereload, ) main_manager = AppTask(config, loop) aux_app.on_startup.append(main_manager.start) aux_app.on_shutdown.append(main_manager.close) if config.static_path: static_manager = LiveReloadTask(config.static_path, loop) logger.debug('starting livereload to watch %s', config.static_path_str) aux_app.on_startup.append(static_manager.start) aux_app.on_shutdown.append(static_manager.close) url = 'http://{0.host}:{0.aux_port}'.format(config) logger.info('Starting aux server at %s ◆', url) if config.static_path: rel_path = config.static_path.relative_to(os.getcwd()) logger.info('serving static files from ./%s/ at %s%s', rel_path, url, config.static_url) return aux_app, config.aux_port, loop, AuxAccessLogger
python
def runserver(**config_kwargs): """ Prepare app ready to run development server. :param config_kwargs: see config.Config for more details :return: tuple (auxiliary app, auxiliary app port, event loop) """ # force a full reload in sub processes so they load an updated version of code, this must be called only once set_start_method('spawn') config = Config(**config_kwargs) config.import_app_factory() loop = asyncio.get_event_loop() loop.run_until_complete(check_port_open(config.main_port, loop)) aux_app = create_auxiliary_app( static_path=config.static_path_str, static_url=config.static_url, livereload=config.livereload, ) main_manager = AppTask(config, loop) aux_app.on_startup.append(main_manager.start) aux_app.on_shutdown.append(main_manager.close) if config.static_path: static_manager = LiveReloadTask(config.static_path, loop) logger.debug('starting livereload to watch %s', config.static_path_str) aux_app.on_startup.append(static_manager.start) aux_app.on_shutdown.append(static_manager.close) url = 'http://{0.host}:{0.aux_port}'.format(config) logger.info('Starting aux server at %s ◆', url) if config.static_path: rel_path = config.static_path.relative_to(os.getcwd()) logger.info('serving static files from ./%s/ at %s%s', rel_path, url, config.static_url) return aux_app, config.aux_port, loop, AuxAccessLogger
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/runserver/main.py#L34-L73
aio-libs/aiohttp-devtools
aiohttp_devtools/logs.py
log_config
def log_config(verbose: bool) -> dict: """ Setup default config. for dictConfig. :param verbose: level: DEBUG if True, INFO if False :return: dict suitable for ``logging.config.dictConfig`` """ log_level = 'DEBUG' if verbose else 'INFO' return { 'version': 1, 'disable_existing_loggers': False, 'formatters': { 'default': { 'format': '[%(asctime)s] %(message)s', 'datefmt': '%H:%M:%S', 'class': 'aiohttp_devtools.logs.DefaultFormatter', }, 'no_ts': { 'format': '%(message)s', 'class': 'aiohttp_devtools.logs.DefaultFormatter', }, 'aiohttp': { 'format': '%(message)s', 'class': 'aiohttp_devtools.logs.AccessFormatter', }, }, 'handlers': { 'default': { 'level': log_level, 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'default' }, 'no_ts': { 'level': log_level, 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'no_ts' }, 'aiohttp_access': { 'level': log_level, 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'aiohttp' }, 'aiohttp_server': { 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'aiohttp' }, }, 'loggers': { rs_dft_logger.name: { 'handlers': ['default'], 'level': log_level, }, rs_aux_logger.name: { 'handlers': ['default'], 'level': log_level, }, tools_logger.name: { 'handlers': ['default'], 'level': log_level, }, main_logger.name: { 'handlers': ['no_ts'], 'level': log_level, }, 'aiohttp.access': { 'handlers': ['aiohttp_access'], 'level': log_level, 'propagate': False, }, 'aiohttp.server': { 'handlers': ['aiohttp_server'], 'level': log_level, }, }, }
python
def log_config(verbose: bool) -> dict: """ Setup default config. for dictConfig. :param verbose: level: DEBUG if True, INFO if False :return: dict suitable for ``logging.config.dictConfig`` """ log_level = 'DEBUG' if verbose else 'INFO' return { 'version': 1, 'disable_existing_loggers': False, 'formatters': { 'default': { 'format': '[%(asctime)s] %(message)s', 'datefmt': '%H:%M:%S', 'class': 'aiohttp_devtools.logs.DefaultFormatter', }, 'no_ts': { 'format': '%(message)s', 'class': 'aiohttp_devtools.logs.DefaultFormatter', }, 'aiohttp': { 'format': '%(message)s', 'class': 'aiohttp_devtools.logs.AccessFormatter', }, }, 'handlers': { 'default': { 'level': log_level, 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'default' }, 'no_ts': { 'level': log_level, 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'no_ts' }, 'aiohttp_access': { 'level': log_level, 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'aiohttp' }, 'aiohttp_server': { 'class': 'aiohttp_devtools.logs.HighlightStreamHandler', 'formatter': 'aiohttp' }, }, 'loggers': { rs_dft_logger.name: { 'handlers': ['default'], 'level': log_level, }, rs_aux_logger.name: { 'handlers': ['default'], 'level': log_level, }, tools_logger.name: { 'handlers': ['default'], 'level': log_level, }, main_logger.name: { 'handlers': ['no_ts'], 'level': log_level, }, 'aiohttp.access': { 'handlers': ['aiohttp_access'], 'level': log_level, 'propagate': False, }, 'aiohttp.server': { 'handlers': ['aiohttp_server'], 'level': log_level, }, }, }
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train
https://github.com/aio-libs/aiohttp-devtools/blob/e9ea6feb43558e6e64595ea0ea5613f226cba81f/aiohttp_devtools/logs.py#L93-L166
loads/molotov
molotov/api.py
scenario
def scenario(weight=1, delay=0.0, name=None): """Decorator to register a function as a Molotov test. Options: - **weight** used by Molotov when the scenarii are randomly picked. The functions with the highest values are more likely to be picked. Integer, defaults to 1. This value is ignored when the *scenario_picker* decorator is used. - **delay** once the scenario is done, the worker will sleep *delay* seconds. Float, defaults to 0. The general --delay argument you can pass to Molotov will be summed with this delay. - **name** name of the scenario. If not provided, will use the function __name___ attribute. The decorated function receives an :class:`aiohttp.ClientSession` instance. """ def _scenario(func, *args, **kw): _check_coroutine(func) if weight > 0: sname = name or func.__name__ data = {'name': sname, 'weight': weight, 'delay': delay, 'func': func, 'args': args, 'kw': kw} _SCENARIO[sname] = data @functools.wraps(func) def __scenario(*args, **kw): return func(*args, **kw) return __scenario return _scenario
python
def scenario(weight=1, delay=0.0, name=None): """Decorator to register a function as a Molotov test. Options: - **weight** used by Molotov when the scenarii are randomly picked. The functions with the highest values are more likely to be picked. Integer, defaults to 1. This value is ignored when the *scenario_picker* decorator is used. - **delay** once the scenario is done, the worker will sleep *delay* seconds. Float, defaults to 0. The general --delay argument you can pass to Molotov will be summed with this delay. - **name** name of the scenario. If not provided, will use the function __name___ attribute. The decorated function receives an :class:`aiohttp.ClientSession` instance. """ def _scenario(func, *args, **kw): _check_coroutine(func) if weight > 0: sname = name or func.__name__ data = {'name': sname, 'weight': weight, 'delay': delay, 'func': func, 'args': args, 'kw': kw} _SCENARIO[sname] = data @functools.wraps(func) def __scenario(*args, **kw): return func(*args, **kw) return __scenario return _scenario
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