question_id
stringlengths 7
12
| nl
stringlengths 4
200
| cmd
stringlengths 2
232
| oracle_man
sequence | canonical_cmd
stringlengths 2
228
| cmd_name
stringclasses 1
value |
|---|---|---|---|---|---|
19490064-50 | merge rows from dataframe `df1` with rows from dataframe `df2` and calculate the mean for rows that have the same value of axis 1 | pd.concat((df1, df2), axis=1).mean(axis=1) | [
"pandas.reference.api.pandas.concat",
"pandas.reference.api.pandas.dataframe.mean"
] | pd.concat((VAR_STR, VAR_STR), axis=1).mean(axis=1) | conala |
4880960-33 | sum of all values in a python dict `d` | sum(d.values()) | [
"python.library.functions#sum",
"python.library.stdtypes#dict.values"
] | sum(VAR_STR.values()) | conala |
4880960-87 | Sum of all values in a Python dict | sum(d.values()) | [
"python.library.functions#sum",
"python.library.stdtypes#dict.values"
] | sum(d.values()) | conala |
627435-73 | remove the last element in list `a` | del a[(-1)] | [] | del VAR_STR[-1] | conala |
627435-63 | remove the element in list `a` with index 1 | a.pop(1) | [
"python.library.stdtypes#frozenset.pop"
] | VAR_STR.pop(1) | conala |
627435-40 | remove the last element in list `a` | a.pop() | [
"python.library.stdtypes#frozenset.pop"
] | VAR_STR.pop() | conala |
627435-31 | remove the element in list `a` at index `index` | a.pop(index) | [
"python.library.stdtypes#frozenset.pop"
] | VAR_STR.pop(VAR_STR) | conala |
627435-36 | remove the element in list `a` at index `index` | del a[index] | [] | del VAR_STR[VAR_STR] | conala |
16868457-20 | sort a dictionary `d` by length of its values and print as string | print(' '.join(sorted(d, key=lambda k: len(d[k]), reverse=True))) | [
"python.library.functions#sorted",
"python.library.functions#len",
"python.library.stdtypes#str.join"
] | print(' '.join(sorted(VAR_STR, key=lambda k: len(VAR_STR[k]), reverse=True))) | conala |
8172861-52 | Replace comma with dot in a string `original_string` using regex | new_string = re.sub('"(\\d+),(\\d+)"', '\\1.\\2', original_string) | [
"python.library.re#re.sub"
] | new_string = re.sub('"(\\d+),(\\d+)"', '\\1.\\2', VAR_STR) | conala |
20084487-20 | plot data of column 'index' versus column 'A' of dataframe `monthly_mean` after resetting its index | monthly_mean.reset_index().plot(x='index', y='A') | [
"pandas.reference.api.pandas.dataframe.reset_index",
"pandas.reference.api.pandas.dataframe.plot"
] | VAR_STR.reset_index().plot(x='VAR_STR', y='VAR_STR') | conala |
5971312-4 | set environment variable 'DEBUSSY' equal to 1 | os.environ['DEBUSSY'] = '1' | [] | os.environ['VAR_STR'] = '1' | conala |
5971312-29 | Get a environment variable `DEBUSSY` | print(os.environ['DEBUSSY']) | [] | print(os.environ['VAR_STR']) | conala |
5971312-73 | set environment variable 'DEBUSSY' to '1' | os.environ['DEBUSSY'] = '1' | [] | os.environ['VAR_STR'] = 'VAR_STR' | conala |
4921038-69 | flask-sqlalchemy delete row `page` | db.session.delete(page) | [
"python.library.ast#ast.Delete"
] | db.session.delete(VAR_STR) | conala |
14301913-69 | convert pandas group by object to multi-indexed dataframe with indices 'Name' and 'Destination' | df.set_index(['Name', 'Destination']) | [
"pandas.reference.api.pandas.dataframe.set_index"
] | df.set_index(['VAR_STR', 'VAR_STR']) | conala |
6504200-56 | decode unicode string `s` into a readable unicode literal | s.decode('unicode_escape') | [
"python.library.stdtypes#bytearray.decode"
] | VAR_STR.decode('unicode_escape') | conala |
3262437-3 | get the non-masked values of array `m` | m[~m.mask] | [] | VAR_STR[~VAR_STR.mask] | conala |
4859292-70 | get a random key `country` and value `capital` form a dictionary `d` | country, capital = random.choice(list(d.items())) | [
"python.library.random#random.choice",
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | VAR_STR, VAR_STR = random.choice(list(VAR_STR.items())) | conala |
12777222-51 | zip file `pdffile` using its basename as directory name | archive.write(pdffile, os.path.basename(pdffile)) | [
"python.library.os.path#os.path.basename",
"python.library.os#os.write"
] | archive.write(VAR_STR, os.path.basename(VAR_STR)) | conala |
7323859-99 | call bash command 'tar c my_dir | md5sum' with pipe | subprocess.call('tar c my_dir | md5sum', shell=True) | [
"python.library.subprocess#subprocess.call"
] | subprocess.call('VAR_STR', shell=True) | conala |
1185524-91 | trim whitespace in string `s` | s.strip() | [
"python.library.stdtypes#str.strip"
] | VAR_STR.strip() | conala |
1185524-91 | trim whitespace (including tabs) in `s` on the left side | s = s.lstrip() | [
"python.library.stdtypes#str.strip"
] | VAR_STR = VAR_STR.lstrip() | conala |
1185524-8 | trim whitespace (including tabs) in `s` on the right side | s = s.rstrip() | [
"python.library.stdtypes#str.rstrip"
] | VAR_STR = VAR_STR.rstrip() | conala |
1185524-9 | trim characters ' \t\n\r' in `s` | s = s.strip(' \t\n\r') | [
"python.library.stdtypes#str.strip"
] | VAR_STR = VAR_STR.strip(' \t\n\r') | conala |
1185524-31 | trim whitespaces (including tabs) in string `s` | print(re.sub('[\\s+]', '', s)) | [
"python.library.re#re.sub"
] | print(re.sub('[\\s+]', '', VAR_STR)) | conala |
8409095-82 | set color marker styles `--bo` in matplotlib | plt.plot(list(range(10)), '--bo') | [
"python.library.functions#range",
"python.library.functions#list",
"pandas.reference.api.pandas.dataframe.plot"
] | plt.plot(list(range(10)), 'VAR_STR') | conala |
8409095-48 | set circle markers on plot for individual points defined in list `[1,2,3,4,5,6,7,8,9,10]` created by range(10) | plt.plot(list(range(10)), linestyle='--', marker='o', color='b') | [
"python.library.functions#range",
"python.library.functions#list",
"pandas.reference.api.pandas.dataframe.plot"
] | plt.plot(list(range(10)), linestyle='--', marker='o', color='b') | conala |
13438574-91 | sort list `results` by keys value 'year' | sorted(results, key=itemgetter('year')) | [
"python.library.functions#sorted",
"python.library.operator#operator.itemgetter"
] | sorted(VAR_STR, key=itemgetter('VAR_STR')) | conala |
10078470-99 | sort array `arr` in ascending order by values of the 3rd column | arr[arr[:, (2)].argsort()] | [
"numpy.reference.generated.numpy.argsort"
] | VAR_STR[VAR_STR[:, (2)].argsort()] | conala |
10078470-100 | sort rows of numpy matrix `arr` in ascending order according to all column values | numpy.sort(arr, axis=0) | [
"numpy.reference.generated.numpy.sort"
] | numpy.sort(VAR_STR, axis=0) | conala |
2783079-30 | Format a string `u'Andr\xc3\xa9'` that has unicode characters | """""".join(chr(ord(c)) for c in 'Andr\xc3\xa9') | [
"python.library.functions#chr",
"python.library.functions#ord",
"python.library.stdtypes#str.join"
] | """""".join(chr(ord(c)) for c in 'André') | conala |
2783079-88 | convert a unicode 'Andr\xc3\xa9' to a string | """""".join(chr(ord(c)) for c in 'Andr\xc3\xa9').decode('utf8') | [
"python.library.functions#chr",
"python.library.functions#ord",
"python.library.stdtypes#str.join",
"python.library.stdtypes#bytearray.decode"
] | """""".join(chr(ord(c)) for c in 'VAR_STR').decode('utf8') | conala |
2372573-38 | remove white spaces from the end of string " xyz " | """ xyz """.rstrip() | [
"python.library.stdtypes#str.rstrip"
] | """ xyz """.rstrip() | conala |
14295673-41 | Convert string '03:55' into datetime.time object | datetime.datetime.strptime('03:55', '%H:%M').time() | [
"python.library.datetime#datetime.datetime.strptime",
"python.library.datetime#datetime.datetime.time"
] | datetime.datetime.strptime('VAR_STR', '%H:%M').time() | conala |
4059550-66 | generate all possible string permutations of each two elements in list `['hel', 'lo', 'bye']` | print([''.join(a) for a in combinations(['hel', 'lo', 'bye'], 2)]) | [
"python.library.itertools#itertools.combinations",
"python.library.stdtypes#str.join"
] | print([''.join(a) for a in combinations([VAR_STR], 2)]) | conala |
3590165-87 | print a list of integers `list_of_ints` using string formatting | print(', '.join(str(x) for x in list_of_ints)) | [
"python.library.stdtypes#str",
"python.library.stdtypes#str.join"
] | print(', '.join(str(x) for x in VAR_STR)) | conala |
5555063-8 | un-escaping characters in a string with python | """\\u003Cp\\u003E""".decode('unicode-escape') | [
"python.library.stdtypes#bytearray.decode"
] | """\\u003Cp\\u003E""".decode('unicode-escape') | conala |
9402255-38 | save current figure to file 'graph.png' with resolution of 1000 dpi | plt.savefig('graph.png', dpi=1000) | [
"matplotlib.figure_api#matplotlib.figure.Figure.savefig"
] | plt.savefig('VAR_STR', dpi=1000) | conala |
38147259-48 | Print a emoji from a string `\\ud83d\\ude4f` having surrogate pairs | """\\ud83d\\ude4f""".encode('utf-16', 'surrogatepass').decode('utf-16') | [
"python.library.stdtypes#str.encode",
"python.library.stdtypes#bytearray.decode"
] | """VAR_STR""".encode('utf-16', 'surrogatepass').decode('utf-16') | conala |
12589481-54 | apply two different aggregating functions `mean` and `sum` to the same column `dummy` in pandas data frame `df` | df.groupby('dummy').agg({'returns': [np.mean, np.sum]}) | [
"pandas.reference.api.pandas.dataframe.groupby",
"pandas.reference.api.pandas.dataframe.agg"
] | VAR_STR.groupby('VAR_STR').agg({'returns': [np.VAR_STR, np.VAR_STR]}) | conala |
209840-22 | map two lists `keys` and `values` into a dictionary | new_dict = {k: v for k, v in zip(keys, values)} | [
"python.library.functions#zip"
] | new_dict = {k: v for k, v in zip(VAR_STR, VAR_STR)} | conala |
209840-67 | map two lists `keys` and `values` into a dictionary | dict((k, v) for k, v in zip(keys, values)) | [
"python.library.functions#zip",
"python.library.stdtypes#dict"
] | dict((k, v) for k, v in zip(VAR_STR, VAR_STR)) | conala |
209840-17 | map two lists `keys` and `values` into a dictionary | dict([(k, v) for k, v in zip(keys, values)]) | [
"python.library.functions#zip",
"python.library.stdtypes#dict"
] | dict([(k, v) for k, v in zip(VAR_STR, VAR_STR)]) | conala |
38379453-42 | get a list of substrings consisting of the first 5 characters of every string in list `buckets` | [s[:5] for s in buckets] | [] | [s[:5] for s in VAR_STR] | conala |
12329853-55 | Rearrange the columns 'a','b','x','y' of pandas DataFrame `df` in mentioned sequence 'x' ,'y','a' ,'b' | df = df[['x', 'y', 'a', 'b']] | [] | VAR_STR = VAR_STR[['VAR_STR', 'VAR_STR', 'VAR_STR', 'VAR_STR']] | conala |
8586738-95 | Get a list of all fields in class `User` that are marked `required` | [k for k, v in User._fields.items() if v.required] | [
"python.library.stdtypes#dict.items"
] | [k for k, v in VAR_STR._fields.items() if v.VAR_STR] | conala |
3817529-35 | create a dictionary `{'spam': 5, 'ham': 6}` into another dictionary `d` field 'dict3' | d['dict3'] = {'spam': 5, 'ham': 6} | [] | VAR_STR['VAR_STR'] = {VAR_STR} | conala |
26720916-8 | Get rank of rows from highest to lowest of dataframe `df`, grouped by value in column `group`, according to value in column `value` | df.groupby('group')['value'].rank(ascending=False) | [
"pandas.reference.api.pandas.dataframe.groupby",
"pandas.reference.api.pandas.dataframe.rank"
] | VAR_STR.groupby('VAR_STR')['VAR_STR'].rank(ascending=False) | conala |
19973489-29 | remove column by index `[:, 0:2]` in dataframe `df` | df = df.ix[:, 0:2] | [] | VAR_STR = VAR_STR.ix[VAR_STR] | conala |
2397687-56 | convert a list of hex byte strings `['BB', 'A7', 'F6', '9E']` to a list of hex integers | [int(x, 16) for x in ['BB', 'A7', 'F6', '9E']] | [
"python.library.functions#int"
] | [int(x, 16) for x in [VAR_STR]] | conala |
2397687-31 | convert the elements of list `L` from hex byte strings to hex integers | [int(x, 16) for x in L] | [
"python.library.functions#int"
] | [int(x, 16) for x in VAR_STR] | conala |
1747817-96 | Create a dictionary `d` from list `iterable` | d = dict(((key, value) for (key, value) in iterable)) | [
"python.library.stdtypes#dict"
] | VAR_STR = dict((key, value) for key, value in VAR_STR) | conala |
1747817-8 | Create a dictionary `d` from list `iterable` | d = {key: value for (key, value) in iterable} | [] | VAR_STR = {key: value for key, value in VAR_STR} | conala |
1747817-34 | Create a dictionary `d` from list of key value pairs `iterable` | d = {k: v for (k, v) in iterable} | [] | VAR_STR = {k: v for k, v in VAR_STR} | conala |
22397058-19 | drop a single subcolumn 'a' in column 'col1' from a dataframe `df` | df.drop(('col1', 'a'), axis=1) | [
"pandas.reference.api.pandas.dataframe.drop"
] | VAR_STR.drop(('VAR_STR', 'VAR_STR'), axis=1) | conala |
22397058-80 | dropping all columns named 'a' from a multiindex 'df', across all level. | df.drop('a', level=1, axis=1) | [
"pandas.reference.api.pandas.dataframe.drop"
] | VAR_STR.drop('VAR_STR', level=1, axis=1) | conala |
13283689-71 | return list `result` of sum of elements of each list `b` in list of lists `a` | result = [sum(b) for b in a] | [
"python.library.functions#sum"
] | VAR_STR = [sum(VAR_STR) for VAR_STR in VAR_STR] | conala |
13395888-35 | make a line plot with errorbars, `ebar`, from data `x, y, err` and set color of the errorbars to `y` (yellow) | ebar = plt.errorbar(x, y, yerr=err, ecolor='y') | [
"matplotlib._as_gen.mpl_toolkits.mplot3d.axes3d.axes3d#mpl_toolkits.mplot3d.axes3d.Axes3D.errorbar"
] | VAR_STR = plt.errorbar(x, VAR_STR, yerr=err, ecolor='VAR_STR') | conala |
5285181-18 | open a file `/home/user/test/wsservice/data.pkl` in binary write mode | output = open('/home/user/test/wsservice/data.pkl', 'wb') | [
"python.library.urllib.request#open"
] | output = open('VAR_STR', 'wb') | conala |
1388818-50 | compare two lists in python `a` and `b` and return matches | set(a).intersection(b) | [
"python.library.stdtypes#set",
"python.library.stdtypes#frozenset.intersection"
] | set(VAR_STR).intersection(VAR_STR) | conala |
1388818-27 | How can I compare two lists in python and return matches | [i for i, j in zip(a, b) if i == j] | [
"python.library.functions#zip"
] | [i for i, j in zip(a, b) if i == j] | conala |
20230211-71 | sort a dictionary `a` by values that are list type | t = sorted(list(a.items()), key=lambda x: x[1]) | [
"python.library.functions#sorted",
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | t = sorted(list(VAR_STR.items()), key=lambda x: x[1]) | conala |
12985456-66 | Replace all non-alphanumeric characters in a string | re.sub('[^0-9a-zA-Z]+', '*', 'h^&ell`.,|o w]{+orld') | [
"python.library.re#re.sub"
] | re.sub('[^0-9a-zA-Z]+', '*', 'h^&ell`.,|o w]{+orld') | conala |
9040939-18 | find all possible sequences of elements in a list `[2, 3, 4]` | map(list, permutations([2, 3, 4])) | [
"python.library.functions#map",
"python.library.itertools#itertools.permutations"
] | map(list, permutations([VAR_STR])) | conala |
35797523-43 | create a list by appending components from list `a` and reversed list `b` interchangeably | [value for pair in zip(a, b[::-1]) for value in pair] | [
"python.library.functions#zip"
] | [value for pair in zip(VAR_STR, VAR_STR[::-1]) for value in pair] | conala |
29386995-92 | get http header of the key 'your-header-name' in flask | request.headers['your-header-name'] | [] | request.headers['VAR_STR'] | conala |
7745562-86 | Create list `listy` containing 3 empty lists | listy = [[] for i in range(3)] | [
"python.library.functions#range"
] | VAR_STR = [[] for i in range(3)] | conala |
8777753-52 | convert datetime.date `dt` to utc timestamp | timestamp = (dt - datetime(1970, 1, 1)).total_seconds() | [
"python.library.datetime#datetime.timedelta.total_seconds",
"python.library.datetime#datetime.datetime"
] | timestamp = (VAR_STR - datetime(1970, 1, 1)).total_seconds() | conala |
12211944-86 | find float number proceeding sub-string `par` in string `dir` | float(re.findall('(?:^|_)' + par + '(\\d+\\.\\d*)', dir)[0]) | [
"python.library.re#re.findall",
"python.library.functions#float"
] | float(re.findall('(?:^|_)' + VAR_STR + '(\\d+\\.\\d*)', VAR_STR)[0]) | conala |
12211944-0 | Get all the matches from a string `abcd` if it begins with a character `a` | re.findall('[^a]', 'abcd') | [
"python.library.re#re.findall"
] | re.findall('[^a]', 'VAR_STR') | conala |
1270951-66 | get a relative path of file 'my_file' into variable `fn` | fn = os.path.join(os.path.dirname(__file__), 'my_file') | [
"python.library.os.path#os.path.dirname",
"python.library.os.path#os.path.join"
] | VAR_STR = os.path.join(os.path.dirname(__file__), 'VAR_STR') | conala |
1534542-44 | Can I sort text by its numeric value in Python? | sorted(list(mydict.items()), key=lambda a: map(int, a[0].split('.'))) | [
"python.library.functions#sorted",
"python.library.functions#map",
"python.library.functions#list",
"python.library.stdtypes#dict.items",
"python.library.stdtypes#str.split"
] | sorted(list(mydict.items()), key=lambda a: map(int, a[0].split('.'))) | conala |
39538010-46 | execute python code `myscript.py` in a virtualenv `/path/to/my/venv` from matlab | system('/path/to/my/venv/bin/python myscript.py') | [
"python.library.os#os.system"
] | system('/path/to/my/venv/bin/python myscript.py') | conala |
42260840-56 | remove dictionary from list `a` if the value associated with its key 'link' is in list `b` | a = [x for x in a if x['link'] not in b] | [] | VAR_STR = [x for x in VAR_STR if x['VAR_STR'] not in VAR_STR] | conala |
19334374-30 | Convert a string of numbers `example_string` separated by `,` into a list of integers | map(int, example_string.split(',')) | [
"python.library.functions#map",
"python.library.stdtypes#str.split"
] | map(int, VAR_STR.split('VAR_STR')) | conala |
19334374-87 | Convert a string of numbers 'example_string' separated by comma into a list of numbers | [int(s) for s in example_string.split(',')] | [
"python.library.functions#int",
"python.library.stdtypes#str.split"
] | [int(s) for s in VAR_STR.split(',')] | conala |
4270742-97 | remove newlines and whitespace from string `yourstring` | re.sub('[\\ \\n]{2,}', '', yourstring) | [
"python.library.re#re.sub"
] | re.sub('[\\ \\n]{2,}', '', VAR_STR) | conala |
16772071-63 | sort dict `data` by value | sorted(data, key=data.get) | [
"python.library.functions#sorted"
] | sorted(VAR_STR, key=VAR_STR.get) | conala |
16772071-53 | Sort a dictionary `data` by its values | sorted(data.values()) | [
"python.library.functions#sorted",
"python.library.stdtypes#dict.values"
] | sorted(VAR_STR.values()) | conala |
16772071-42 | Get a list of pairs of key-value sorted by values in dictionary `data` | sorted(list(data.items()), key=lambda x: x[1]) | [
"python.library.functions#sorted",
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | sorted(list(VAR_STR.items()), key=lambda x: x[1]) | conala |
16772071-83 | sort dict by value python | sorted(list(data.items()), key=lambda x: x[1]) | [
"python.library.functions#sorted",
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | sorted(list(data.items()), key=lambda x: x[1]) | conala |
4484690-74 | update all values associated with key `i` to string 'updated' if value `j` is not equal to 'None' in dictionary `d` | {i: 'updated' for i, j in list(d.items()) if j != 'None'} | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | {VAR_STR: 'VAR_STR' for VAR_STR, VAR_STR in list(VAR_STR.items()) if VAR_STR != 'VAR_STR'} | conala |
4484690-66 | Filter a dictionary `d` to remove keys with value None and replace other values with 'updated' | dict((k, 'updated') for k, v in d.items() if v is None) | [
"python.library.stdtypes#dict",
"python.library.stdtypes#dict.items"
] | dict((k, 'VAR_STR') for k, v in VAR_STR.items() if v is None) | conala |
4484690-31 | Filter a dictionary `d` to remove keys with value 'None' and replace other values with 'updated' | dict((k, 'updated') for k, v in d.items() if v != 'None') | [
"python.library.stdtypes#dict",
"python.library.stdtypes#dict.items"
] | dict((k, 'VAR_STR') for k, v in VAR_STR.items() if v != 'VAR_STR') | conala |
8528178-96 | create a list `listofzeros` of `n` zeros | listofzeros = [0] * n | [] | VAR_STR = [0] * VAR_STR | conala |
4233476-75 | sort a list `s` by first and second attributes | s = sorted(s, key=lambda x: (x[1], x[2])) | [
"python.library.functions#sorted"
] | VAR_STR = sorted(VAR_STR, key=lambda x: (x[1], x[2])) | conala |
4233476-98 | sort a list of lists `s` by second and third element in each list. | s.sort(key=operator.itemgetter(1, 2)) | [
"python.library.operator#operator.itemgetter",
"python.library.stdtypes#list.sort"
] | VAR_STR.sort(key=operator.itemgetter(1, 2)) | conala |
1217251-72 | sort dictionary of lists `myDict` by the third item in each list | sorted(list(myDict.items()), key=lambda e: e[1][2]) | [
"python.library.functions#sorted",
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | sorted(list(VAR_STR.items()), key=lambda e: e[1][2]) | conala |
22412258-62 | get the first element of each tuple in a list `rows` | [x[0] for x in rows] | [] | [x[0] for x in VAR_STR] | conala |
22412258-39 | get a list `res_list` of the first elements of each tuple in a list of tuples `rows` | res_list = [x[0] for x in rows] | [] | VAR_STR = [x[0] for x in VAR_STR] | conala |
7332841-60 | append the first element of array `a` to array `a` | numpy.append(a, a[0]) | [
"numpy.reference.generated.numpy.append"
] | numpy.append(VAR_STR, VAR_STR[0]) | conala |
18624039-75 | reset index of series `s` | s.reset_index(0).reset_index(drop=True) | [
"pandas.reference.api.pandas.dataframe.reset_index"
] | VAR_STR.reset_index(0).reset_index(drop=True) | conala |
4060221-89 | open a file 'bundled-resource.jpg' in the same directory as a python script | f = open(os.path.join(__location__, 'bundled-resource.jpg')) | [
"python.library.os.path#os.path.join",
"python.library.urllib.request#open"
] | f = open(os.path.join(__location__, 'VAR_STR')) | conala |
18663026-72 | Set value for key `a` in dict `count` to `0` if key `a` does not exist or if value is `none` | count.setdefault('a', 0) | [
"python.library.stdtypes#dict.setdefault"
] | VAR_STR.setdefault('VAR_STR', 0) | conala |
5022066-15 | serialise SqlAlchemy RowProxy object `row` to a json object | json.dumps([dict(list(row.items())) for row in rs]) | [
"python.library.json#json.dumps",
"python.library.stdtypes#dict",
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | json.dumps([dict(list(VAR_STR.items())) for VAR_STR in rs]) | conala |
18170459-31 | check if dictionary `L[0].f.items()` is in dictionary `a3.f.items()` | set(L[0].f.items()).issubset(set(a3.f.items())) | [
"python.library.stdtypes#set",
"python.library.stdtypes#dict.items"
] | set(L[0].f.items()).issubset(set(a3.f.items())) | conala |
674519-53 | convert a python dictionary `d` to a list of tuples | [(v, k) for k, v in list(d.items())] | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | [(v, k) for k, v in list(VAR_STR.items())] | conala |
674519-26 | convert dictionary of pairs `d` to a list of tuples | [(v, k) for k, v in d.items()] | [
"python.library.stdtypes#dict.items"
] | [(v, k) for k, v in VAR_STR.items()] | conala |
674519-5 | convert python 2 dictionary `a` to a list of tuples where the value is the first tuple element and the key is the second tuple element | [(v, k) for k, v in a.items()] | [
"python.library.stdtypes#dict.items"
] | [(v, k) for k, v in VAR_STR.items()] | conala |