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@@ -52,3 +52,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+conala-docs.jsonl filter=lfs diff=lfs merge=lfs -text

conala-dev.jsonl

@@ -0,0 +1,201 @@
+{"nl": "Get pandas GroupBy object with sum over the rows with same column names within  dataframe `df`", "cmd": "df.groupby(df.columns, axis=1).sum()", "question_id": "13078751-34", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.groupby", "python.library.functions#sum"], "canonical_cmd": "VAR_STR.groupby(VAR_STR.columns, axis=1).sum()"}
+{"nl": "divide the value for each key `k` in dict `d2` by the value for the same key `k` in dict `d1`", "cmd": "{k: (d2[k] / d1[k]) for k in list(d1.keys()) & d2}", "question_id": "11840111-76", "cmd_name": "conala", "oracle_man": ["python.library.functions#list", "python.library.stdtypes#dict.keys"], "canonical_cmd": "{VAR_STR: (VAR_STR[VAR_STR] / VAR_STR[VAR_STR]) for VAR_STR in list(VAR_STR.keys()) & VAR_STR}"}
+{"nl": "combining rows in pandas by adding their values", "cmd": "df.groupby(df.index).sum()", "question_id": "17438906-51", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.groupby", "python.library.functions#sum"], "canonical_cmd": "df.groupby(df.index).sum()"}
+{"nl": "make all keys lowercase in dictionary `d`", "cmd": "d = {(a.lower(), b): v for (a, b), v in list(d.items())}", "question_id": "21833383-37", "cmd_name": "conala", "oracle_man": ["python.library.functions#list", "python.library.stdtypes#str.lower", "python.library.stdtypes#dict.items"], "canonical_cmd": "VAR_STR = {(a.lower(), b): v for (a, b), v in list(VAR_STR.items())}"}
+{"nl": "create a dataframe `d` filled with zeros with indices from 0 to length of `data` and column names from `feature_list`", "cmd": "d = pd.DataFrame(0, index=np.arange(len(data)), columns=feature_list)", "question_id": "22963263-45", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.arange", "python.library.functions#len", "pandas.reference.api.pandas.dataframe"], "canonical_cmd": "VAR_STR = pd.DataFrame(0, index=np.arange(len(VAR_STR)), columns=VAR_STR)"}
+{"nl": "get a dict of variable names `['some', 'list', 'of', 'vars']` as a string and their values", "cmd": "dict((name, eval(name)) for name in ['some', 'list', 'of', 'vars'])", "question_id": "2553354-9", "cmd_name": "conala", "oracle_man": ["python.library.functions#eval", "python.library.stdtypes#dict"], "canonical_cmd": "dict((name, eval(name)) for name in [VAR_STR])"}
+{"nl": "Format a date object `str_data` into iso fomrat", "cmd": "datetime.datetime.strptime(str_date, '%m/%d/%Y').date().isoformat()", "question_id": "12772057-25", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.strptime", "python.library.datetime#datetime.date.isoformat", "python.library.datetime#datetime.datetime.date"], "canonical_cmd": "datetime.datetime.strptime(str_date, '%m/%d/%Y').date().isoformat()"}
+{"nl": "sort dictionary `mydict` in descending order based on the sum of each value in it", "cmd": "sorted(iter(mydict.items()), key=lambda tup: sum(tup[1]), reverse=True)[:3]", "question_id": "3411025-33", "cmd_name": "conala", "oracle_man": ["python.library.functions#sorted", "python.library.functions#iter", "python.library.functions#sum", "python.library.stdtypes#dict.items"], "canonical_cmd": "sorted(iter(VAR_STR.items()), key=lambda tup: sum(tup[1]), reverse=True)[:3]"}
+{"nl": "get top `3` items from a dictionary `mydict` with largest sum of values", "cmd": "heapq.nlargest(3, iter(mydict.items()), key=lambda tup: sum(tup[1]))", "question_id": "3411025-3", "cmd_name": "conala", "oracle_man": ["python.library.heapq#heapq.nlargest", "python.library.functions#iter", "python.library.functions#sum", "python.library.stdtypes#dict.items"], "canonical_cmd": "heapq.nlargest(3, iter(VAR_STR.items()), key=lambda tup: sum(tup[1]))"}
+{"nl": "calculate the md5 checksum of a file named  'filename.exe'", "cmd": "hashlib.md5(open('filename.exe', 'rb').read()).hexdigest()", "question_id": "16874598-40", "cmd_name": "conala", "oracle_man": ["python.library.urllib.request#open", "python.library.hashlib#hashlib.hash.hexdigest", "python.library.os#os.read"], "canonical_cmd": "hashlib.md5(open('VAR_STR', 'rb').read()).hexdigest()"}
+{"nl": "get max key in dictionary `MyCount`", "cmd": "max(list(MyCount.keys()), key=int)", "question_id": "3108042-55", "cmd_name": "conala", "oracle_man": ["python.library.functions#max", "python.library.functions#list", "python.library.stdtypes#dict.keys"], "canonical_cmd": "max(list(VAR_STR.keys()), key=int)"}
+{"nl": "return a string from a regex match with pattern '<img.*?>' in string 'line'", "cmd": "imtag = re.match('<img.*?>', line).group(0)", "question_id": "18493677-21", "cmd_name": "conala", "oracle_man": ["python.library.re#re.match", "python.library.re#re.Match.group"], "canonical_cmd": "imtag = re.match('VAR_STR', VAR_STR).group(0)"}
+{"nl": "In Django, filter `Task.objects` based on all entities in ['A', 'P', 'F']", "cmd": "Task.objects.exclude(prerequisites__status__in=['A', 'P', 'F'])", "question_id": "1516795-1", "cmd_name": "conala", "oracle_man": ["django.ref.contrib.admin.index#django.contrib.admin.ModelAdmin.exclude"], "canonical_cmd": "Task.objects.exclude(prerequisites__status__in=['VAR_STR', 'VAR_STR', 'VAR_STR'])"}
+{"nl": "remove duplicated items from list of lists `testdata`", "cmd": "list(map(list, set(map(lambda i: tuple(i), testdata))))", "question_id": "3724551-76", "cmd_name": "conala", "oracle_man": ["python.library.functions#map", "python.library.functions#list", "python.library.functions#tuple", "python.library.stdtypes#set"], "canonical_cmd": "list(map(list, set(map(lambda i: tuple(i), VAR_STR))))"}
+{"nl": "uniqueness for list of lists `testdata`", "cmd": "[list(i) for i in set(tuple(i) for i in testdata)]", "question_id": "3724551-76", "cmd_name": "conala", "oracle_man": ["python.library.functions#map", "python.library.functions#list", "python.library.functions#tuple", "python.library.stdtypes#set"], "canonical_cmd": "[list(i) for i in set(tuple(i) for i in VAR_STR)]"}
+{"nl": "download file from http url `file_url`", "cmd": "file_name = wget.download(file_url)", "question_id": "19602931-66", "cmd_name": "conala", "oracle_man": ["matplotlib.backend_webagg_api#matplotlib.backends.backend_webagg.WebAggApplication.Download"], "canonical_cmd": "file_name = wget.download(VAR_STR)"}
+{"nl": "produce a pivot table as dataframe using column 'Y' in datafram `df` to form the axes of the resulting dataframe", "cmd": "df.pivot_table('Y', rows='X', cols='X2')", "question_id": "9550867-20", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.pivot_table"], "canonical_cmd": "VAR_STR.pivot_table('VAR_STR', rows='X', cols='X2')"}
+{"nl": "remove duplicate dict in list `l`", "cmd": "[dict(t) for t in set([tuple(d.items()) for d in l])]", "question_id": "9427163-45", "cmd_name": "conala", "oracle_man": ["python.library.functions#tuple", "python.library.stdtypes#dict", "python.library.stdtypes#set", "python.library.stdtypes#dict.items"], "canonical_cmd": "[dict(t) for t in set([tuple(d.items()) for d in VAR_STR])]"}
+{"nl": "request url 'https://www.reporo.com/' without verifying SSL certificates", "cmd": "requests.get('https://www.reporo.com/', verify=False)", "question_id": "28667684-80", "cmd_name": "conala", "oracle_man": ["python.library.webbrowser#webbrowser.get"], "canonical_cmd": "requests.get('VAR_STR', verify=False)"}
+{"nl": "Filter queryset for all objects in Django model `MyModel` where texts length are greater than `254`", "cmd": "MyModel.objects.filter(text__regex='^.{254}.*')", "question_id": "23351183-55", "cmd_name": "conala", "oracle_man": ["python.library.logging#logging.Filter.filter"], "canonical_cmd": "VAR_STR.objects.filter(text__regex='^.{254}.*')"}
+{"nl": "Get value for  \"username\" parameter in GET request  in Django", "cmd": "request.GET.get('username', '')", "question_id": "23531030-8", "cmd_name": "conala", "oracle_man": [], "canonical_cmd": "request.GET.get('VAR_STR', '')"}
+{"nl": "convert binary string '\\x00\\x00\\x80?\\x00\\x00\\x00@\\x00\\x00@@\\x00\\x00\\x80@' to numpy array", "cmd": "np.fromstring('\\x00\\x00\\x80?\\x00\\x00\\x00@\\x00\\x00@@\\x00\\x00\\x80@', dtype='<f4')", "question_id": "11760095-62", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.fromstring"], "canonical_cmd": "np.fromstring('VAR_STR', dtype='<f4')"}
+{"nl": "convert binary string to numpy array", "cmd": "np.fromstring('\\x00\\x00\\x80?\\x00\\x00\\x00@\\x00\\x00@@\\x00\\x00\\x80@', dtype='>f4')", "question_id": "11760095-48", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.fromstring"], "canonical_cmd": "np.fromstring('\\x00\\x00\\x80?\\x00\\x00\\x00@\\x00\\x00@@\\x00\\x00\\x80@', dtype='>f4')"}
+{"nl": "convert a pandas `df1` groupby object to dataframe", "cmd": "DataFrame({'count': df1.groupby(['Name', 'City']).size()}).reset_index()", "question_id": "10373660-65", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.reset_index", "pandas.reference.api.pandas.core.groupby.groupby.size", "pandas.reference.api.pandas.dataframe.groupby"], "canonical_cmd": "DataFrame({'count': VAR_STR.groupby(['Name', 'City']).size()}).reset_index()"}
+{"nl": "lowercase keys and values in dictionary `{'My Key': 'My Value'}`", "cmd": "{k.lower(): v.lower() for k, v in list({'My Key': 'My Value'}.items())}", "question_id": "764235-66", "cmd_name": "conala", "oracle_man": ["python.library.functions#list", "python.library.stdtypes#str.lower", "python.library.stdtypes#dict.items"], "canonical_cmd": "{k.lower(): v.lower() for k, v in list({VAR_STR}.items())}"}
+{"nl": "lowercase all keys and values in dictionary `{'My Key': 'My Value'}`", "cmd": "dict((k.lower(), v) for k, v in {'My Key': 'My Value'}.items())", "question_id": "764235-57", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict", "python.library.stdtypes#dict.items", "python.library.stdtypes#str.lower"], "canonical_cmd": "dict((k.lower(), v) for k, v in {VAR_STR}.items())"}
+{"nl": "Convert each key,value pair in a dictionary `{'My Key': 'My Value'}` to lowercase", "cmd": "dict((k.lower(), v.lower()) for k, v in {'My Key': 'My Value'}.items())", "question_id": "764235-84", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict", "python.library.stdtypes#str.lower", "python.library.stdtypes#dict.items"], "canonical_cmd": "dict((k.lower(), v.lower()) for k, v in {VAR_STR}.items())"}
+{"nl": "get logical xor of `a` and `b`", "cmd": "(bool(a) != bool(b))", "question_id": "432842-98", "cmd_name": "conala", "oracle_man": ["python.library.functions#bool"], "canonical_cmd": "bool(VAR_STR) != bool(VAR_STR)"}
+{"nl": "get logical xor of `a` and `b`", "cmd": "(bool(a) ^ bool(b))", "question_id": "432842-64", "cmd_name": "conala", "oracle_man": ["python.library.functions#bool"], "canonical_cmd": "bool(VAR_STR) ^ bool(VAR_STR)"}
+{"nl": "get logical xor of `a` and `b`", "cmd": "xor(bool(a), bool(b))", "question_id": "432842-23", "cmd_name": "conala", "oracle_man": ["python.library.functions#bool", "python.library.operator#operator.xor"], "canonical_cmd": "xor(bool(VAR_STR), bool(VAR_STR))"}
+{"nl": "get the logical xor of two variables `str1` and `str2`", "cmd": "return (bool(str1) ^ bool(str2))", "question_id": "432842-18", "cmd_name": "conala", "oracle_man": ["python.library.functions#bool"], "canonical_cmd": "return bool(VAR_STR) ^ bool(VAR_STR)"}
+{"nl": "Django check if an object with criteria `name` equal to 'name' and criteria `title` equal to 'title' exists in model `Entry`", "cmd": "Entry.objects.filter(name='name', title='title').exists()", "question_id": "9561243-18", "cmd_name": "conala", "oracle_man": ["python.library.logging#logging.Filter.filter", "python.library.zipfile#zipfile.Path.exists"], "canonical_cmd": "VAR_STR.objects.filter(VAR_STR='VAR_STR', VAR_STR='VAR_STR').exists()"}
+{"nl": "get the date 6 months from today", "cmd": "six_months = (date.today() + relativedelta(months=(+ 6)))", "question_id": "546321-38", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.date.today", "matplotlib.dates_api#matplotlib.dates.relativedelta"], "canonical_cmd": "six_months = date.today() + relativedelta(months=+6)"}
+{"nl": "calculate the date six months from the current date", "cmd": "print((datetime.date.today() + datetime.timedelta(((6 * 365) / 12))).isoformat())", "question_id": "546321-69", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.date.today", "python.library.datetime#datetime.timedelta", "python.library.datetime#datetime.date.isoformat"], "canonical_cmd": "print((datetime.date.today() + datetime.timedelta(6 * 365 / 12)).isoformat())"}
+{"nl": "apply itertools.product to elements of a list of lists `arrays`", "cmd": "list(itertools.product(*arrays))", "question_id": "3034014-76", "cmd_name": "conala", "oracle_man": ["python.library.itertools#itertools.product", "python.library.functions#list"], "canonical_cmd": "list(itertools.product(*VAR_STR))"}
+{"nl": "call a Python script \"test2.py\"", "cmd": "exec(compile(open('test2.py').read(), 'test2.py', 'exec'))", "question_id": "1186789-17", "cmd_name": "conala", "oracle_man": ["python.library.functions#exec", "python.library.functions#compile", "python.library.urllib.request#open", "python.library.os#os.read"], "canonical_cmd": "exec(compile(open('VAR_STR').read(), 'VAR_STR', 'exec'))"}
+{"nl": "filter dataframe `df` by sub-level index '0630' in pandas", "cmd": "df[df.index.map(lambda x: x[1].endswith('0630'))]", "question_id": "12224778-99", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.index.map", "pandas.reference.api.pandas.series.str.endswith"], "canonical_cmd": "VAR_STR[VAR_STR.index.map(lambda x: x[1].endswith('VAR_STR'))]"}
+{"nl": "evaluate the expression '20<30'", "cmd": "eval('20<30')", "question_id": "10586778-60", "cmd_name": "conala", "oracle_man": ["python.library.functions#eval"], "canonical_cmd": "eval('VAR_STR')"}
+{"nl": "Load the url `http://www.google.com` in selenium webdriver `driver`", "cmd": "driver.get('http://www.google.com')", "question_id": "4618373-40", "cmd_name": "conala", "oracle_man": ["python.library.webbrowser#webbrowser.get"], "canonical_cmd": "VAR_STR.get('VAR_STR')"}
+{"nl": "convert a 3d array `img` of dimensions 4x2x3 to a 2d array   of dimensions 3x8", "cmd": "img.transpose(2, 0, 1).reshape(3, -1)", "question_id": "32838802-21", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.reshape", "numpy.reference.generated.numpy.transpose"], "canonical_cmd": "VAR_STR.transpose(2, 0, 1).reshape(3, -1)"}
+{"nl": "close the window in tkinter", "cmd": "self.root.destroy()", "question_id": "8009176-56", "cmd_name": "conala", "oracle_man": ["matplotlib.backend_tools_api#matplotlib.backend_tools.ToolBase.destroy"], "canonical_cmd": "self.root.destroy()"}
+{"nl": "format datetime in `dt` as string in format `'%m/%d/%Y`", "cmd": "dt.strftime('%m/%d/%Y')", "question_id": "10624937-25", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.series.dt.strftime"], "canonical_cmd": "VAR_STR.strftime('%m/%d/%Y')"}
+{"nl": "concatenate a list of numpy arrays `input_list` together into a flattened list of values", "cmd": "np.concatenate(input_list).ravel().tolist()", "question_id": "33711985-27", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.concatenate", "numpy.reference.generated.numpy.ravel", "numpy.reference.generated.numpy.recarray.tolist"], "canonical_cmd": "np.concatenate(VAR_STR).ravel().tolist()"}
+{"nl": "set an array of unicode characters `[u'\\xe9', u'\\xe3', u'\\xe2']` as labels in Matplotlib `ax`", "cmd": "ax.set_yticklabels(['\\xe9', '\\xe3', '\\xe2'])", "question_id": "2406700-79", "cmd_name": "conala", "oracle_man": ["matplotlib._as_gen.matplotlib.axes.axes.set_yticklabels"], "canonical_cmd": "VAR_STR.set_yticklabels(['\u00e9', '\u00e3', '\u00e2'])"}
+{"nl": "find all files with extension '.c' in directory `folder`", "cmd": "results += [each for each in os.listdir(folder) if each.endswith('.c')]", "question_id": "3608411-24", "cmd_name": "conala", "oracle_man": ["python.library.os#os.listdir", "python.library.stdtypes#str.endswith"], "canonical_cmd": "results += [each for each in os.listdir(VAR_STR) if each.endswith('VAR_STR')]"}
+{"nl": "check if a local variable `myVar` exists", "cmd": "('myVar' in locals())", "question_id": "843277-82", "cmd_name": "conala", "oracle_man": ["python.library.functions#locals"], "canonical_cmd": "'VAR_STR' in locals()"}
+{"nl": "check if a global variable `myVar` exists", "cmd": "('myVar' in globals())", "question_id": "843277-28", "cmd_name": "conala", "oracle_man": ["python.library.functions#globals"], "canonical_cmd": "'VAR_STR' in globals()"}
+{"nl": "check if a local variable 'myVar' exists", "cmd": "if ('myVar' in locals()):\n    pass", "question_id": "843277-2", "cmd_name": "conala", "oracle_man": ["python.library.functions#locals"], "canonical_cmd": "if 'VAR_STR' in locals():\n    pass"}
+{"nl": "check if a global variable 'myVar' exists", "cmd": "if ('myVar' in globals()):\n    pass", "question_id": "843277-2", "cmd_name": "conala", "oracle_man": ["python.library.functions#locals"], "canonical_cmd": "if 'VAR_STR' in globals():\n    pass"}
+{"nl": "get a list of tuples of every three consecutive items in list `[1, 2, 3, 4, 5, 6, 7, 8, 9]`", "cmd": "list(zip(*((iter([1, 2, 3, 4, 5, 6, 7, 8, 9]),) * 3)))", "question_id": "2231663-1", "cmd_name": "conala", "oracle_man": ["python.library.functions#zip", "python.library.functions#iter", "python.library.functions#list"], "canonical_cmd": "list(zip(*((iter([VAR_STR]),) * 3)))"}
+{"nl": "read an excel file 'ComponentReport-DJI.xls'", "cmd": "open('ComponentReport-DJI.xls', 'rb').read(200)", "question_id": "118516-73", "cmd_name": "conala", "oracle_man": ["python.library.urllib.request#open", "python.library.os#os.read"], "canonical_cmd": "open('VAR_STR', 'rb').read(200)"}
+{"nl": "create a new 2D array with 2 random rows from array `A`", "cmd": "A[(np.random.choice(A.shape[0], 2, replace=False)), :]", "question_id": "14262654-99", "cmd_name": "conala", "oracle_man": ["numpy.reference.random.generated.numpy.random.choice"], "canonical_cmd": "VAR_STR[(np.random.choice(VAR_STR.shape[0], 2, replace=False)), :]"}
+{"nl": "create a new 2 dimensional array containing two random rows from array `A`", "cmd": "A[(np.random.randint(A.shape[0], size=2)), :]", "question_id": "14262654-92", "cmd_name": "conala", "oracle_man": ["numpy.reference.random.generated.numpy.random.randint"], "canonical_cmd": "VAR_STR[(np.random.randint(VAR_STR.shape[0], size=2)), :]"}
+{"nl": "Create an array containing the conversion of string '100110' into separate elements", "cmd": "np.array(map(int, '100110'))", "question_id": "28207743-2", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.array", "python.library.functions#map"], "canonical_cmd": "np.array(map(int, 'VAR_STR'))"}
+{"nl": "convert a string 'mystr' to numpy array of integer values", "cmd": "print(np.array(list(mystr), dtype=int))", "question_id": "28207743-2", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.array", "python.library.functions#map"], "canonical_cmd": "print(np.array(list(VAR_STR), dtype=int))"}
+{"nl": "print letter that appears most frequently in string `s`", "cmd": "print(collections.Counter(s).most_common(1)[0])", "question_id": "4131123-37", "cmd_name": "conala", "oracle_man": ["python.library.collections#collections.Counter", "python.library.collections#collections.Counter.most_common"], "canonical_cmd": "print(collections.Counter(VAR_STR).most_common(1)[0])"}
+{"nl": "Exit script", "cmd": "sys.exit()", "question_id": "3376534-57", "cmd_name": "conala", "oracle_man": ["python.library.sys#sys.exit"], "canonical_cmd": "sys.exit()"}
+{"nl": "match the pattern '[:;][)(](?![)(])' to the string `str`", "cmd": "re.match('[:;][)(](?![)(])', str)", "question_id": "14571103-97", "cmd_name": "conala", "oracle_man": ["python.library.re#re.match"], "canonical_cmd": "re.match('VAR_STR', VAR_STR)"}
+{"nl": "execute file 'filename.py'", "cmd": "exec(compile(open('filename.py').read(), 'filename.py', 'exec'))", "question_id": "1027714-50", "cmd_name": "conala", "oracle_man": ["python.library.functions#exec", "python.library.functions#compile", "python.library.urllib.request#open", "python.library.os#os.read"], "canonical_cmd": "exec(compile(open('VAR_STR').read(), 'VAR_STR', 'exec'))"}
+{"nl": "select records of dataframe `df` where the sum of column 'X' for each value in column 'User' is 0", "cmd": "df.groupby('User')['X'].filter(lambda x: x.sum() == 0)", "question_id": "27868020-50", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.groupby", "python.library.functions#filter", "pandas.reference.api.pandas.dataframe.sum"], "canonical_cmd": "VAR_STR.groupby('VAR_STR')['VAR_STR'].filter(lambda x: x.sum() == 0)"}
+{"nl": "Find all records from collection `collection` without extracting mongo id `_id`", "cmd": "db.collection.find({}, {'_id': False})", "question_id": "12345387-21", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#str.find"], "canonical_cmd": "db.VAR_STR.find({}, {'VAR_STR': False})"}
+{"nl": "find the magnitude (length) squared of a vector `vf` field", "cmd": "np.einsum('...j,...j->...', vf, vf)", "question_id": "19863964-8", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.einsum"], "canonical_cmd": "np.einsum('...j,...j->...', VAR_STR, VAR_STR)"}
+{"nl": "Get `3` unique items from a list", "cmd": "random.sample(list(range(1, 16)), 3)", "question_id": "6494508-48", "cmd_name": "conala", "oracle_man": ["python.library.random#random.sample", "python.library.functions#range", "python.library.functions#list"], "canonical_cmd": "random.sample(list(range(1, 16)), 3)"}
+{"nl": "convert string of bytes `y\\xcc\\xa6\\xbb` into an int", "cmd": "struct.unpack('<L', 'y\\xcc\\xa6\\xbb')[0]", "question_id": "444591-34", "cmd_name": "conala", "oracle_man": ["python.library.struct#struct.unpack"], "canonical_cmd": "struct.unpack('<L', 'VAR_STR')[0]"}
+{"nl": "get a list of all integer points in a `dim` dimensional hypercube with coordinates from `-x` to `y` for all dimensions", "cmd": "list(itertools.product(list(range(-x, y)), repeat=dim))", "question_id": "41727442-65", "cmd_name": "conala", "oracle_man": ["python.library.functions#list", "python.library.itertools#itertools.product", "python.library.functions#range"], "canonical_cmd": "list(itertools.product(list(range(-x, VAR_STR)), repeat=VAR_STR))"}
+{"nl": "extract data field 'bar' from json object", "cmd": "json.loads('{\"foo\": 42, \"bar\": \"baz\"}')['bar']", "question_id": "6407780-2", "cmd_name": "conala", "oracle_man": ["python.library.json#json.loads"], "canonical_cmd": "json.loads('{\"foo\": 42, \"bar\": \"baz\"}')['VAR_STR']"}
+{"nl": "webbrowser open url `url`", "cmd": "webbrowser.open_new(url)", "question_id": "4302027-94", "cmd_name": "conala", "oracle_man": ["python.library.webbrowser#webbrowser.open_new"], "canonical_cmd": "webbrowser.open_new(VAR_STR)"}
+{"nl": "pandas subtract a row from dataframe `df2` from dataframe `df`", "cmd": "pd.DataFrame(df.values - df2.values, columns=df.columns)", "question_id": "22093471-66", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe"], "canonical_cmd": "pd.DataFrame(VAR_STR.values - VAR_STR.values, columns=VAR_STR.columns)"}
+{"nl": "delete file `filename`", "cmd": "os.remove(filename)", "question_id": "39998424-26", "cmd_name": "conala", "oracle_man": ["python.library.os#os.remove"], "canonical_cmd": "os.remove(VAR_STR)"}
+{"nl": "update the `globals()` dictionary with the contents of the `vars(args)` dictionary", "cmd": "globals().update(vars(args))", "question_id": "8306171-4", "cmd_name": "conala", "oracle_man": ["python.library.functions#vars", "python.library.functions#globals", "python.library.stdtypes#dict.update"], "canonical_cmd": "globals().update(vars(args))"}
+{"nl": "convert a string of date strings `date_stngs ` to datetime objects and put them in a dataframe", "cmd": "pd.to_datetime(pd.Series(date_stngs))", "question_id": "17690738-39", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.to_datetime", "pandas.reference.series"], "canonical_cmd": "pd.to_datetime(pd.Series(VAR_STR))"}
+{"nl": "Formate current date and time to a string using pattern '%Y-%m-%d %H:%M:%S'", "cmd": "datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')", "question_id": "7999935-36", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.now", "python.library.datetime#datetime.datetime.strftime"], "canonical_cmd": "datetime.datetime.now().strftime('VAR_STR')"}
+{"nl": "combine two dictionaries `d ` and `d1`, concatenate string values with identical `keys`", "cmd": "dict((k, d.get(k, '') + d1.get(k, '')) for k in keys)", "question_id": "17604837-13", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict", "python.library.stdtypes#dict.get"], "canonical_cmd": "dict((k, VAR_STR.get(k, '') + VAR_STR.get(k, '')) for k in VAR_STR)"}
+{"nl": "Get day name from a datetime object", "cmd": "date.today().strftime('%A')", "question_id": "8380389-66", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.date.today", "python.library.datetime#datetime.date.strftime"], "canonical_cmd": "date.today().strftime('%A')"}
+{"nl": "generate pdf file `output_filename` from markdown file `input_filename`", "cmd": "with open(input_filename, 'r') as f:\n    html_text = markdown(f.read(), output_format='html4')\npdfkit.from_string(html_text, output_filename)", "question_id": "4135344-11", "cmd_name": "conala", "oracle_man": ["python.library.urllib.request#open", "django.ref.templates.api#django.template.Engine.from_string", "python.library.os#os.read"], "canonical_cmd": "with open(VAR_STR, 'r') as f:\n    html_text = markdown(f.read(), output_format='html4')\npdfkit.from_string(html_text, VAR_STR)"}
+{"nl": "return http status code 204 from a django view", "cmd": "return HttpResponse(status=204)", "question_id": "12476452-40", "cmd_name": "conala", "oracle_man": ["python.library.http.client#http.client.HTTPResponse"], "canonical_cmd": "return HttpResponse(status=204)"}
+{"nl": "assign an array of floats in range from 0 to 100 to a variable `values`", "cmd": "values = np.array([i for i in range(100)], dtype=np.float64)", "question_id": "23638638-89", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.array", "python.library.functions#range"], "canonical_cmd": "VAR_STR = np.array([i for i in range(100)], dtype=np.float64)"}
+{"nl": "create a NumPy array containing elements of array `A` as pointed to by index in array `B`", "cmd": "A[np.arange(A.shape[0])[:, (None)], B]", "question_id": "37878946-16", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.arange"], "canonical_cmd": "VAR_STR[np.arange(VAR_STR.shape[0])[:, (None)], VAR_STR]"}
+{"nl": "remove adjacent duplicate elements from a list `[1, 2, 2, 3, 2, 2, 4]`", "cmd": "[k for k, g in itertools.groupby([1, 2, 2, 3, 2, 2, 4])]", "question_id": "3460161-42", "cmd_name": "conala", "oracle_man": ["python.library.itertools#itertools.groupby"], "canonical_cmd": "[k for k, g in itertools.groupby([VAR_STR])]"}
+{"nl": "set labels `[1, 2, 3, 4, 5]` on axis X in plot `plt`", "cmd": "plt.xticks([1, 2, 3, 4, 5])", "question_id": "10839719-92", "cmd_name": "conala", "oracle_man": ["matplotlib._as_gen.matplotlib.pyplot.xticks"], "canonical_cmd": "VAR_STR.xticks([VAR_STR])"}
+{"nl": "get value of the environment variable 'KEY_THAT_MIGHT_EXIST'", "cmd": "print(os.environ.get('KEY_THAT_MIGHT_EXIST'))", "question_id": "4906977-8", "cmd_name": "conala", "oracle_man": ["python.library.webbrowser#webbrowser.get"], "canonical_cmd": "print(os.environ.get('VAR_STR'))"}
+{"nl": "get value of the environment variable 'HOME' with default value '/home/username/'", "cmd": "print(os.environ.get('HOME', '/home/username/'))", "question_id": "4906977-57", "cmd_name": "conala", "oracle_man": ["python.library.webbrowser#webbrowser.get"], "canonical_cmd": "print(os.environ.get('VAR_STR', 'VAR_STR'))"}
+{"nl": "find all the indexes in a Numpy 2D array where the value is 1", "cmd": "zip(*np.where(a == 1))", "question_id": "27175400-13", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.where", "python.library.functions#zip"], "canonical_cmd": "zip(*np.where(a == 1))"}
+{"nl": "How to find the index of a value in 2d array in Python?", "cmd": "np.where(a == 1)", "question_id": "27175400-85", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.where"], "canonical_cmd": "np.where(a == 1)"}
+{"nl": "split dictionary/list inside a pandas column 'b' into separate columns in dataframe `df`", "cmd": "pd.concat([df.drop('b', axis=1), pd.DataFrame(df['b'].tolist())], axis=1)", "question_id": "38231591-22", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.drop", "pandas.reference.api.pandas.dataframe", "pandas.reference.api.pandas.concat"], "canonical_cmd": "pd.concat([VAR_STR.drop('VAR_STR', axis=1), pd.DataFrame(VAR_STR['VAR_STR'].tolist(\n    ))], axis=1)"}
+{"nl": "reorder indexed rows `['Z', 'C', 'A']` based on a list in pandas data frame `df`", "cmd": "df.reindex(['Z', 'C', 'A'])", "question_id": "30009948-74", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.reindex"], "canonical_cmd": "VAR_STR.reindex([VAR_STR])"}
+{"nl": "store the output of command 'ls' in variable `direct_output`", "cmd": "direct_output = subprocess.check_output('ls', shell=True)", "question_id": "19267591-38", "cmd_name": "conala", "oracle_man": ["python.library.subprocess#subprocess.check_output"], "canonical_cmd": "VAR_STR = subprocess.check_output('VAR_STR', shell=True)"}
+{"nl": "reverse all x-axis points in pyplot", "cmd": "plt.gca().invert_xaxis()", "question_id": "2051744-10", "cmd_name": "conala", "oracle_man": ["matplotlib.figure_api#matplotlib.figure.FigureBase.gca", "matplotlib._as_gen.matplotlib.axes.axes.invert_xaxis"], "canonical_cmd": "plt.gca().invert_xaxis()"}
+{"nl": "reverse y-axis in pyplot", "cmd": "plt.gca().invert_yaxis()", "question_id": "2051744-44", "cmd_name": "conala", "oracle_man": ["matplotlib.figure_api#matplotlib.figure.FigureBase.gca", "matplotlib._as_gen.matplotlib.axes.axes.invert_yaxis"], "canonical_cmd": "plt.gca().invert_yaxis()"}
+{"nl": "Iterate over dictionary `d` in ascending order of values", "cmd": "sorted(iter(d.items()), key=lambda x: x[1])", "question_id": "674509-57", "cmd_name": "conala", "oracle_man": ["python.library.functions#sorted", "python.library.functions#iter", "python.library.stdtypes#dict.items"], "canonical_cmd": "sorted(iter(VAR_STR.items()), key=lambda x: x[1])"}
+{"nl": "read file 'myfile.txt' using universal newline mode 'U'", "cmd": "print(open('myfile.txt', 'U').read())", "question_id": "2798627-16", "cmd_name": "conala", "oracle_man": ["python.library.urllib.request#open", "python.library.os#os.read"], "canonical_cmd": "print(open('VAR_STR', 'VAR_STR').read())"}
+{"nl": "Change the mode of file 'my_script.sh' to permission number 484", "cmd": "os.chmod('my_script.sh', 484)", "question_id": "14104778-7", "cmd_name": "conala", "oracle_man": ["python.library.os#os.chmod"], "canonical_cmd": "os.chmod('VAR_STR', 484)"}
+{"nl": "multiply array `a` and array `b`respective elements then sum each row of the new array", "cmd": "np.einsum('ji,i->j', a, b)", "question_id": "21562986-78", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.einsum"], "canonical_cmd": "np.einsum('ji,i->j', VAR_STR, VAR_STR)"}
+{"nl": "add field names as headers in csv constructor `writer`", "cmd": "writer.writeheader()", "question_id": "20347766-10", "cmd_name": "conala", "oracle_man": ["python.library.csv#csv.DictWriter.writeheader"], "canonical_cmd": "VAR_STR.writeheader()"}
+{"nl": "execute sql query 'INSERT INTO table VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s)' with all parameters in list `tup`", "cmd": "cur.executemany('INSERT INTO table VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s)', tup)", "question_id": "8134602-90", "cmd_name": "conala", "oracle_man": ["python.library.sqlite3#sqlite3.Connection.executemany"], "canonical_cmd": "cur.executemany('VAR_STR', VAR_STR)"}
+{"nl": "lowercase string values with key 'content' in a list of dictionaries `messages`", "cmd": "[{'content': x['content'].lower()} for x in messages]", "question_id": "42353686-21", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#str.lower"], "canonical_cmd": "[{'VAR_STR': x['VAR_STR'].lower()} for x in VAR_STR]"}
+{"nl": "Unpack column 'stats' in dataframe `df` into a series of columns", "cmd": "df['stats'].apply(pd.Series)", "question_id": "29370211-89", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.series.apply"], "canonical_cmd": "VAR_STR['VAR_STR'].apply(pd.Series)"}
+{"nl": "lookup an attribute in any scope by name 'range'", "cmd": "getattr(__builtins__, 'range')", "question_id": "2850966-83", "cmd_name": "conala", "oracle_man": ["python.library.functions#getattr"], "canonical_cmd": "getattr(__builtins__, 'VAR_STR')"}
+{"nl": "Remove character `char` from a string `a`", "cmd": "a = a.replace(char, '')", "question_id": "3939361-45", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.char.replace"], "canonical_cmd": "VAR_STR = VAR_STR.replace(VAR_STR, '')"}
+{"nl": "Remove characters in `b` from a string `a`", "cmd": "a = a.replace(char, '')", "question_id": "3939361-16", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.char.replace"], "canonical_cmd": "VAR_STR = VAR_STR.replace(char, '')"}
+{"nl": "SQLAlchemy count the number of rows in table `Congress`", "cmd": "rows = session.query(Congress).count()", "question_id": "10822635-77", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#str.count"], "canonical_cmd": "rows = session.query(VAR_STR).count()"}
+{"nl": "find the index of the second occurrence of the substring `bar` in string `foo bar bar bar`", "cmd": "\"\"\"foo bar bar bar\"\"\".replace('bar', 'XXX', 1).find('bar')", "question_id": "1883980-4", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#str.find", "python.library.stdtypes#str.replace"], "canonical_cmd": "\"\"\"VAR_STR\"\"\".replace('VAR_STR', 'XXX', 1).find('VAR_STR')"}
+{"nl": "concatenate a series `students` onto a dataframe `marks` with pandas", "cmd": "pd.concat([students, pd.DataFrame(marks)], axis=1)", "question_id": "20512297-60", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.concat", "pandas.reference.api.pandas.dataframe"], "canonical_cmd": "pd.concat([VAR_STR, pd.DataFrame(VAR_STR)], axis=1)"}
+{"nl": "create list `randomList` with 10 random floating point numbers between 0.0 and 1.0", "cmd": "randomList = [random.random() for _ in range(10)]", "question_id": "20733827-49", "cmd_name": "conala", "oracle_man": ["python.library.functions#range"], "canonical_cmd": "VAR_STR = [random.random() for _ in range(10)]"}
+{"nl": "create dictionary from list of variables 'foo' and 'bar' already defined", "cmd": "dict((k, globals()[k]) for k in ('foo', 'bar'))", "question_id": "9495262-53", "cmd_name": "conala", "oracle_man": ["python.library.functions#globals", "python.library.stdtypes#dict"], "canonical_cmd": "dict((k, globals()[k]) for k in ('VAR_STR', 'VAR_STR'))"}
+{"nl": "get a dataframe `df2` that contains all the columns of dataframe `df` that do not end in `prefix`", "cmd": "df2 = df.ix[:, (~df.columns.str.endswith('prefix'))]", "question_id": "38426168-57", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.series.str.endswith"], "canonical_cmd": "VAR_STR = VAR_STR.ix[:, (~VAR_STR.columns.str.endswith('VAR_STR'))]"}
+{"nl": "substract 1 hour and 10 minutes from current time", "cmd": "t = datetime.datetime.now()\n(t - datetime.timedelta(hours=1, minutes=10))", "question_id": "14043934-77", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.now", "python.library.datetime#datetime.timedelta"], "canonical_cmd": "t = datetime.datetime.now()\nt - datetime.timedelta(hours=1, minutes=10)"}
+{"nl": "add 1 hour and 2 minutes to time object `t`", "cmd": "dt = datetime.datetime.combine(datetime.date.today(), t)", "question_id": "14043934-78", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.date.today", "python.library.datetime#datetime.datetime.combine"], "canonical_cmd": "dt = datetime.datetime.combine(datetime.date.today(), VAR_STR)"}
+{"nl": "Create new string with unique characters from `s` seperated by ' '", "cmd": "print(' '.join(OrderedDict.fromkeys(s)))", "question_id": "29360607-46", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict.fromkeys", "python.library.stdtypes#str.join"], "canonical_cmd": "print(' '.join(OrderedDict.fromkeys(VAR_STR)))"}
+{"nl": "create a set from string `s` to remove duplicate characters", "cmd": "print(' '.join(set(s)))", "question_id": "29360607-46", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict.fromkeys", "python.library.stdtypes#str.join"], "canonical_cmd": "print(' '.join(set(VAR_STR)))"}
+{"nl": "find the index of the maximum value in the array `arr` where the boolean condition in array `cond` is true", "cmd": "np.ma.array(np.tile(arr, 2).reshape(2, 3), mask=~cond).argmax(axis=1)", "question_id": "31767173-52", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.ma.array", "numpy.reference.generated.numpy.tile", "numpy.reference.generated.numpy.ma.argmax", "numpy.reference.generated.numpy.ma.reshape"], "canonical_cmd": "np.ma.array(np.tile(VAR_STR, 2).reshape(2, 3), mask=~VAR_STR).argmax(axis=1)"}
+{"nl": "Get data from matplotlib plot", "cmd": "gca().get_lines()[n].get_xydata()", "question_id": "8938449-32", "cmd_name": "conala", "oracle_man": ["matplotlib._as_gen.matplotlib.lines.line2d#matplotlib.lines.Line2D.get_xydata", "matplotlib.legend_api#matplotlib.legend.Legend.get_lines", "matplotlib.figure_api#matplotlib.figure.SubFigure.gca"], "canonical_cmd": "gca().get_lines()[n].get_xydata()"}
+{"nl": "BeautifulSoup search string 'Elsie' inside tag 'a'", "cmd": "soup.find_all('a', string='Elsie')", "question_id": "31958637-91", "cmd_name": "conala", "oracle_man": [], "canonical_cmd": "soup.find_all('VAR_STR', string='VAR_STR')"}
+{"nl": "create a dataframe containing the multiplication of element-wise in dataframe `df` and dataframe `df2` using index name and column labels of dataframe `df`", "cmd": "pd.DataFrame(df.values * df2.values, columns=df.columns, index=df.index)", "question_id": "21022865-77", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe"], "canonical_cmd": "pd.DataFrame(VAR_STR.values * VAR_STR.values, columns=VAR_STR.columns, index=\n    VAR_STR.index)"}
+{"nl": "sort a list of dictionaries `list_of_dct` by values in an order `order`", "cmd": "sorted(list_of_dct, key=lambda x: order.index(list(x.values())[0]))", "question_id": "35078261-21", "cmd_name": "conala", "oracle_man": ["python.library.functions#sorted", "python.library.functions#list", "pandas.reference.api.pandas.index.values"], "canonical_cmd": "sorted(VAR_STR, key=lambda x: VAR_STR.index(list(x.values())[0]))"}
+{"nl": "concatenate dataframe `df1` with `df2` whilst removing duplicates", "cmd": "pandas.concat([df1, df2]).drop_duplicates().reset_index(drop=True)", "question_id": "21317384-58", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.concat", "pandas.reference.api.pandas.dataframe.reset_index", "pandas.reference.api.pandas.dataframe.drop_duplicates"], "canonical_cmd": "pandas.concat([VAR_STR, VAR_STR]).drop_duplicates().reset_index(drop=True)"}
+{"nl": "pretty-print ordered dictionary `o`", "cmd": "pprint(dict(list(o.items())))", "question_id": "4301069-72", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict", "python.library.functions#list", "python.library.stdtypes#dict.items", "python.library.pprint#pprint.pprint"], "canonical_cmd": "pprint(dict(list(VAR_STR.items())))"}
+{"nl": "import a nested module `c.py` within `b` within `a` with importlib", "cmd": "importlib.import_module('.c', 'a.b')", "question_id": "10675054-45", "cmd_name": "conala", "oracle_man": ["python.library.importlib#importlib.import_module"], "canonical_cmd": "importlib.import_module('.c', 'a.b')"}
+{"nl": "import a module 'a.b.c' with importlib.import_module in python 2", "cmd": "importlib.import_module('a.b.c')", "question_id": "10675054-25", "cmd_name": "conala", "oracle_man": ["python.library.importlib#importlib.import_module"], "canonical_cmd": "importlib.import_module('VAR_STR')"}
+{"nl": "update fields in Django model `Book` with arguments in dictionary `d` where primary key is equal to `pk`", "cmd": "Book.objects.filter(pk=pk).update(**d)", "question_id": "5503925-38", "cmd_name": "conala", "oracle_man": ["python.library.logging#logging.Filter.filter", "python.library.stdtypes#dict.update"], "canonical_cmd": "VAR_STR.objects.filter(VAR_STR=VAR_STR).update(**VAR_STR)"}
+{"nl": "update the fields in django model `Book` using dictionary `d`", "cmd": "Book.objects.create(**d)", "question_id": "5503925-47", "cmd_name": "conala", "oracle_man": ["python.library.venv#venv.create"], "canonical_cmd": "VAR_STR.objects.create(**VAR_STR)"}
+{"nl": "Generate MD5 checksum of file in the path `full_path` in hashlib", "cmd": "print(hashlib.md5(open(full_path, 'rb').read()).hexdigest())", "question_id": "3431825-77", "cmd_name": "conala", "oracle_man": ["python.library.urllib.request#open", "python.library.hashlib#hashlib.hash.hexdigest", "python.library.os#os.read"], "canonical_cmd": "print(hashlib.md5(open(VAR_STR, 'rb').read()).hexdigest())"}
+{"nl": "Get the number of NaN values in each column of dataframe `df`", "cmd": "df.isnull().sum()", "question_id": "26266362-41", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.isnull", "python.library.functions#sum"], "canonical_cmd": "VAR_STR.isnull().sum()"}
+{"nl": "find all anchor tags in html `soup` whose url begins with `http://www.iwashere.com`", "cmd": "soup.find_all('a', href=re.compile('http://www\\\\.iwashere\\\\.com/'))", "question_id": "15313250-71", "cmd_name": "conala", "oracle_man": ["python.library.re#re.compile"], "canonical_cmd": "VAR_STR.find_all('a', href=re.compile('http://www\\\\.iwashere\\\\.com/'))"}
+{"nl": "find all anchors with a hyperlink that matches the pattern '^(?!(?:[a-zA-Z][a-zA-Z0-9+.-]*:|//))'", "cmd": "soup.find_all('a', href=re.compile('^(?!(?:[a-zA-Z][a-zA-Z0-9+.-]*:|//))'))", "question_id": "15313250-56", "cmd_name": "conala", "oracle_man": ["python.library.re#re.compile"], "canonical_cmd": "soup.find_all('a', href=re.compile('VAR_STR'))"}
+{"nl": "generate a random 12-digit number", "cmd": "int(''.join(str(random.randint(0, 9)) for _ in range(12)))", "question_id": "13496087-15", "cmd_name": "conala", "oracle_man": ["python.library.random#random.randint", "python.library.functions#range", "python.library.functions#int", "python.library.stdtypes#str", "python.library.stdtypes#str.join"], "canonical_cmd": "int(''.join(str(random.randint(0, 9)) for _ in range(12)))"}
+{"nl": "generate a random 12-digit number", "cmd": "\"\"\"\"\"\".join(str(random.randint(0, 9)) for _ in range(12))", "question_id": "13496087-80", "cmd_name": "conala", "oracle_man": ["python.library.random#random.randint", "python.library.functions#range", "python.library.stdtypes#str", "python.library.stdtypes#str.join"], "canonical_cmd": "\"\"\"\"\"\".join(str(random.randint(0, 9)) for _ in range(12))"}
+{"nl": "How to delete a record in Django models?", "cmd": "SomeModel.objects.filter(id=id).delete()", "question_id": "3805958-22", "cmd_name": "conala", "oracle_man": ["python.library.logging#logging.Filter.filter", "python.library.ast#ast.Delete"], "canonical_cmd": "SomeModel.objects.filter(id=id).delete()"}
+{"nl": "retrieve all items in an numpy array 'x' except the item of the index 1", "cmd": "x[(np.arange(x.shape[0]) != 1), :, :]", "question_id": "8712332-35", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.arange"], "canonical_cmd": "VAR_STR[(np.arange(VAR_STR.shape[0]) != 1), :, :]"}
+{"nl": "split dataframe `df` where the value of column `a` is equal to 'B'", "cmd": "df.groupby((df.a == 'B').shift(1).fillna(0).cumsum())", "question_id": "13353233-57", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.groupby", "pandas.reference.api.pandas.dataframe.fillna", "pandas.reference.api.pandas.dataframe.shift", "pandas.reference.api.pandas.dataframe.cumsum"], "canonical_cmd": "VAR_STR.groupby((VAR_STR.VAR_STR == 'VAR_STR').shift(1).fillna(0).cumsum())"}
+{"nl": "removing control characters from a string `s`", "cmd": "return ''.join(ch for ch in s if unicodedata.category(ch)[0] != 'C')", "question_id": "4324790-58", "cmd_name": "conala", "oracle_man": ["python.library.unicodedata#unicodedata.category", "python.library.stdtypes#str.join"], "canonical_cmd": "return ''.join(ch for ch in VAR_STR if unicodedata.category(ch)[0] != 'C')"}
+{"nl": "return a DateTime object with the current UTC date", "cmd": "today = datetime.datetime.utcnow().date()", "question_id": "27587127-62", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.utcnow", "python.library.datetime#datetime.datetime.date"], "canonical_cmd": "today = datetime.datetime.utcnow().date()"}
+{"nl": "remove decimal points in pandas data frame using round", "cmd": "df.round()", "question_id": "37084812-85", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.round"], "canonical_cmd": "df.round()"}
+{"nl": "print the truth value of `a`", "cmd": "print(bool(a))", "question_id": "39604780-88", "cmd_name": "conala", "oracle_man": ["python.library.functions#bool"], "canonical_cmd": "print(bool(VAR_STR))"}
+{"nl": "Parsing HTML string `html` using BeautifulSoup", "cmd": "parsed_html = BeautifulSoup(html)\nprint(parsed_html.body.find('div', attrs={'class': 'container', }).text)", "question_id": "11709079-7", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#str.find"], "canonical_cmd": "parsed_html = BeautifulSoup(VAR_STR)\nprint(parsed_html.body.find('div', attrs={'class': 'container'}).text)"}
+{"nl": "convert a column of list in series `s` to dummies", "cmd": "pd.get_dummies(s.apply(pd.Series).stack()).sum(level=0)", "question_id": "29034928-61", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.get_dummies", "python.library.functions#sum", "pandas.reference.api.pandas.series.apply", "pandas.reference.api.pandas.dataframe.stack"], "canonical_cmd": "pd.get_dummies(VAR_STR.apply(pd.Series).stack()).sum(level=0)"}
+{"nl": "create a matrix from a list `[1, 2, 3]`", "cmd": "x = scipy.matrix([1, 2, 3]).transpose()", "question_id": "4690366-20", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.matrix.transpose"], "canonical_cmd": "x = scipy.matrix([VAR_STR]).transpose()"}
+{"nl": "convert radians 1 to degrees", "cmd": "math.cos(math.radians(1))", "question_id": "9875964-60", "cmd_name": "conala", "oracle_man": ["python.library.math#math.radians", "python.library.math#math.cos"], "canonical_cmd": "math.cos(math.radians(1))"}
+{"nl": "create an empty data frame `df2` with index from another data frame `df1`", "cmd": "df2 = pd.DataFrame(index=df1.index)", "question_id": "18176933-47", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe"], "canonical_cmd": "VAR_STR = pd.DataFrame(index=VAR_STR.index)"}
+{"nl": "make a window `root` jump to the front", "cmd": "root.attributes('-topmost', True)", "question_id": "1892339-81", "cmd_name": "conala", "oracle_man": ["python.library.xml.dom#xml.dom.Node.attributes"], "canonical_cmd": "VAR_STR.attributes('-topmost', True)"}
+{"nl": "apply function `log2` to the grouped values by 'type' in dataframe `df`", "cmd": "df.groupby('type').apply(lambda x: np.mean(np.log2(x['v'])))", "question_id": "18137341-8", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.log2", "numpy.reference.generated.numpy.mean", "pandas.reference.api.pandas.dataframe.groupby", "pandas.reference.api.pandas.dataframe.apply"], "canonical_cmd": "VAR_STR.groupby('VAR_STR').apply(lambda x: np.mean(np.VAR_STR(x['v'])))"}
+{"nl": "Convert JSON array `array` to Python object", "cmd": "data = json.loads(array)", "question_id": "10973614-40", "cmd_name": "conala", "oracle_man": ["python.library.json#json.loads"], "canonical_cmd": "data = json.loads(VAR_STR)"}
+{"nl": "Convert JSON array `array` to Python object", "cmd": "data = json.loads(array)", "question_id": "10973614-6", "cmd_name": "conala", "oracle_man": ["python.library.json#json.loads"], "canonical_cmd": "data = json.loads(VAR_STR)"}
+{"nl": "print number 1255000 as thousands separators", "cmd": "locale.setlocale(locale.LC_ALL, 'en_US')\nlocale.format('%d', 1255000, grouping=True)", "question_id": "1823058-88", "cmd_name": "conala", "oracle_man": ["python.library.locale#locale.setlocale", "python.library.locale#locale.format"], "canonical_cmd": "locale.setlocale(locale.LC_ALL, 'en_US')\nlocale.format('%d', 1255000, grouping=True)"}
+{"nl": "Filter a json from a key-value pair as `{'fixed_key_1': 'foo2'}` in Django", "cmd": "Test.objects.filter(actions__contains=[{'fixed_key_1': 'foo2'}])", "question_id": "34358278-63", "cmd_name": "conala", "oracle_man": ["python.library.logging#logging.Filter.filter"], "canonical_cmd": "Test.objects.filter(actions__contains=[{VAR_STR}])"}
+{"nl": "Move x-axis of the pyplot object `ax` to the top of a plot in matplotlib", "cmd": "ax.xaxis.set_ticks_position('top')", "question_id": "14406214-99", "cmd_name": "conala", "oracle_man": ["matplotlib._as_gen.matplotlib.axis.xaxis.set_ticks_position"], "canonical_cmd": "VAR_STR.xaxis.set_ticks_position('top')"}
+{"nl": "check if date `yourdatetime` is equal to today's date", "cmd": "yourdatetime.date() == datetime.today().date()", "question_id": "6407362-46", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.date.today", "python.library.datetime#datetime.date"], "canonical_cmd": "VAR_STR.date() == datetime.today().date()"}
+{"nl": "disable the certificate check in https requests for url `https://kennethreitz.com`", "cmd": "requests.get('https://kennethreitz.com', verify=False)", "question_id": "15445981-81", "cmd_name": "conala", "oracle_man": ["python.library.webbrowser#webbrowser.get"], "canonical_cmd": "requests.get('VAR_STR', verify=False)"}
+{"nl": "create a list containing all cartesian products of elements in list `a`", "cmd": "list(itertools.product(*a))", "question_id": "798854-41", "cmd_name": "conala", "oracle_man": ["python.library.itertools#itertools.product", "python.library.functions#list"], "canonical_cmd": "list(itertools.product(*VAR_STR))"}
+{"nl": "generate a random string of length `x`  containing lower cased ASCII letters", "cmd": "\"\"\"\"\"\".join(random.choice(string.lowercase) for x in range(X))", "question_id": "1957273-17", "cmd_name": "conala", "oracle_man": ["python.library.random#random.choice", "python.library.functions#range", "python.library.stdtypes#str.join"], "canonical_cmd": "\"\"\"\"\"\".join(random.choice(string.lowercase) for VAR_STR in range(X))"}
+{"nl": "get current datetime in ISO format", "cmd": "datetime.datetime.now().isoformat()", "question_id": "2150739-61", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.now", "python.library.datetime#datetime.datetime.isoformat"], "canonical_cmd": "datetime.datetime.now().isoformat()"}
+{"nl": "get UTC datetime in ISO format", "cmd": "datetime.datetime.utcnow().isoformat()", "question_id": "2150739-5", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.utcnow", "python.library.datetime#datetime.datetime.isoformat"], "canonical_cmd": "datetime.datetime.utcnow().isoformat()"}
+{"nl": "Keep only unique words in list of words `words` and join into string", "cmd": "print(' '.join(sorted(set(words), key=words.index)))", "question_id": "7794208-3", "cmd_name": "conala", "oracle_man": ["python.library.functions#sorted", "python.library.stdtypes#set", "pandas.reference.api.pandas.index.join"], "canonical_cmd": "print(' '.join(sorted(set(VAR_STR), key=VAR_STR.index)))"}
+{"nl": "plot logarithmic axes with matplotlib", "cmd": "ax.set_yscale('log')", "question_id": "773814-28", "cmd_name": "conala", "oracle_man": ["matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_yscale"], "canonical_cmd": "ax.set_yscale('log')"}
+{"nl": "convert a number 2130706433 to ip string", "cmd": "socket.inet_ntoa(struct.pack('!L', 2130706433))", "question_id": "9590965-88", "cmd_name": "conala", "oracle_man": ["python.library.struct#struct.pack", "python.library.socket#socket.inet_ntoa"], "canonical_cmd": "socket.inet_ntoa(struct.pack('!L', 2130706433))"}
+{"nl": "numpy:  check if array 'a' contains all the numbers in array 'b'.", "cmd": "numpy.array([(x in a) for x in b])", "question_id": "10565598-47", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.array"], "canonical_cmd": "numpy.array([(x in VAR_STR) for x in VAR_STR])"}
+{"nl": "Write column 'sum' of DataFrame `a` to csv file 'test.csv'", "cmd": "a.to_csv('test.csv', cols=['sum'])", "question_id": "21206395-91", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.to_csv"], "canonical_cmd": "VAR_STR.to_csv('VAR_STR', cols=['VAR_STR'])"}
+{"nl": "filter dataframe `grouped` where the length of each group `x` is bigger than 1", "cmd": "grouped.filter(lambda x: len(x) > 1)", "question_id": "13167391-7", "cmd_name": "conala", "oracle_man": ["python.library.functions#len", "python.library.logging#logging.Filter.filter"], "canonical_cmd": "VAR_STR.filter(lambda VAR_STR: len(VAR_STR) > 1)"}
+{"nl": "set the y axis range to `0, 1000` in subplot using pylab", "cmd": "pylab.ylim([0, 1000])", "question_id": "2849286-49", "cmd_name": "conala", "oracle_man": ["matplotlib._as_gen.matplotlib.pyplot.ylim"], "canonical_cmd": "pylab.ylim([0, 1000])"}
+{"nl": "get yesterday's date as a string in `YYYY-MM-DD` format using timedelta", "cmd": "(datetime.now() - timedelta(1)).strftime('%Y-%m-%d')", "question_id": "30483977-35", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.now", "python.library.datetime#datetime.datetime.strftime", "python.library.datetime#datetime.timedelta"], "canonical_cmd": "(datetime.now() - timedelta(1)).strftime('%Y-%m-%d')"}
+{"nl": "Display a image file `pathToFile`", "cmd": "Image.open('pathToFile').show()", "question_id": "5333244-64", "cmd_name": "conala", "oracle_man": ["python.library.urllib.request#open"], "canonical_cmd": "Image.open('VAR_STR').show()"}
+{"nl": "convert decimal `8` to binary list", "cmd": "[int(x) for x in bin(8)[2:]]", "question_id": "13557937-95", "cmd_name": "conala", "oracle_man": ["python.library.functions#bin", "python.library.functions#int"], "canonical_cmd": "[int(x) for x in bin(8)[2:]]"}
+{"nl": "Rename a folder `Joe Blow` to `Blow, Joe`", "cmd": "os.rename('Joe Blow', 'Blow, Joe')", "question_id": "8735312-37", "cmd_name": "conala", "oracle_man": ["python.library.os#os.rename"], "canonical_cmd": "os.rename('VAR_STR', 'VAR_STR')"}
+{"nl": "create a 2D array of `Node` objects with dimensions `cols` columns and `rows` rows", "cmd": "nodes = [[Node() for j in range(cols)] for i in range(rows)]", "question_id": "6480441-53", "cmd_name": "conala", "oracle_man": ["python.library.functions#range", "python.library.platform#platform.node"], "canonical_cmd": "nodes = [[VAR_STR() for j in range(VAR_STR)] for i in range(VAR_STR)]"}
+{"nl": "get the indexes of the x and y axes in Numpy array `np` where variable `a` is equal to variable `value`", "cmd": "i, j = np.where(a == value)", "question_id": "18079029-69", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.where"], "canonical_cmd": "i, j = VAR_STR.where(VAR_STR == VAR_STR)"}
+{"nl": "Convert a binary value '1633837924' to string", "cmd": "struct.pack('<I', 1633837924)", "question_id": "33769531-95", "cmd_name": "conala", "oracle_man": ["python.library.struct#struct.pack"], "canonical_cmd": "struct.pack('<I', 1633837924)"}
+{"nl": "get rows of dataframe `df` where column `Col1` has values `['men', 'rocks', 'mountains']`", "cmd": "df[df.Col1.isin(['men', 'rocks', 'mountains'])]", "question_id": "39988589-27", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.isin"], "canonical_cmd": "VAR_STR[VAR_STR.VAR_STR.isin([VAR_STR])]"}
+{"nl": "print current date and time in a regular format", "cmd": "datetime.datetime.now().strftime('%Y-%m-%d %H:%M')", "question_id": "311627-6", "cmd_name": "conala", "oracle_man": ["python.library.datetime#datetime.datetime.now", "python.library.datetime#datetime.datetime.strftime"], "canonical_cmd": "datetime.datetime.now().strftime('%Y-%m-%d %H:%M')"}
+{"nl": "reverse a list `array`", "cmd": "reversed(array)", "question_id": "3940128-54", "cmd_name": "conala", "oracle_man": ["python.library.functions#reversed"], "canonical_cmd": "reversed(VAR_STR)"}
+{"nl": "reverse a list `array`", "cmd": "list(reversed(array))", "question_id": "3940128-11", "cmd_name": "conala", "oracle_man": ["python.library.functions#reversed", "python.library.functions#list"], "canonical_cmd": "list(reversed(VAR_STR))"}
+{"nl": "How do I create a LIST of unique random numbers?", "cmd": "random.sample(list(range(100)), 10)", "question_id": "9755538-3", "cmd_name": "conala", "oracle_man": ["python.library.random#random.sample", "python.library.functions#range", "python.library.functions#list"], "canonical_cmd": "random.sample(list(range(100)), 10)"}
+{"nl": "find the index of element closest to number 11.5 in list `a`", "cmd": "min(enumerate(a), key=lambda x: abs(x[1] - 11.5))", "question_id": "9706041-13", "cmd_name": "conala", "oracle_man": ["python.library.functions#enumerate", "python.library.functions#abs", "python.library.functions#min"], "canonical_cmd": "min(enumerate(VAR_STR), key=lambda x: abs(x[1] - 11.5))"}
+{"nl": "create 4 numbers in range between 1 and 3", "cmd": "print(np.linspace(1, 3, num=4, endpoint=False))", "question_id": "31143732-11", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.linspace"], "canonical_cmd": "print(np.linspace(1, 3, num=4, endpoint=False))"}
+{"nl": "Create numpy array of `5` numbers starting from `1` with interval of `3`", "cmd": "print(np.linspace(1, 3, num=5))", "question_id": "31143732-14", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.linspace"], "canonical_cmd": "print(np.linspace(1, 3, num=5))"}
+{"nl": "split list `mylist` into a list of lists whose elements have the same first five characters", "cmd": "[list(v) for k, v in itertools.groupby(mylist, key=lambda x: x[:5])]", "question_id": "13368723-57", "cmd_name": "conala", "oracle_man": ["python.library.itertools#itertools.groupby", "python.library.functions#list"], "canonical_cmd": "[list(v) for k, v in itertools.groupby(VAR_STR, key=lambda x: x[:5])]"}
+{"nl": "find the minimum value in a numpy array `arr` excluding 0", "cmd": "arr[arr != 0].min()", "question_id": "11764260-82", "cmd_name": "conala", "oracle_man": ["python.library.functions#min"], "canonical_cmd": "VAR_STR[VAR_STR != 0].min()"}
+{"nl": "Retrieve an arbitrary value from dictionary `dict`", "cmd": "next(iter(dict.values()))", "question_id": "3097866-25", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict.values", "python.library.functions#iter", "python.library.functions#next"], "canonical_cmd": "next(iter(VAR_STR.values()))"}
+{"nl": "access an arbitrary value from dictionary `dict`", "cmd": "next(iter(list(dict.values())))", "question_id": "3097866-93", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#dict.values", "python.library.functions#iter", "python.library.functions#next", "python.library.functions#list"], "canonical_cmd": "next(iter(list(VAR_STR.values())))"}
+{"nl": "rearrange tuple of tuples `t`", "cmd": "tuple(zip(*t))", "question_id": "16040156-42", "cmd_name": "conala", "oracle_man": ["python.library.functions#zip", "python.library.functions#tuple"], "canonical_cmd": "tuple(zip(*VAR_STR))"}
+{"nl": "read a single character from stdin", "cmd": "sys.stdin.read(1)", "question_id": "510357-53", "cmd_name": "conala", "oracle_man": ["python.library.os#os.read"], "canonical_cmd": "sys.stdin.read(1)"}
+{"nl": "Get a list values of a dictionary item `pass_id` from post requests in django", "cmd": "request.POST.getlist('pass_id')", "question_id": "5430470-56", "cmd_name": "conala", "oracle_man": ["python.library.cgi#cgi.FieldStorage.getlist"], "canonical_cmd": "request.POST.getlist('VAR_STR')"}
+{"nl": "get number in list `myList` closest in value to number `myNumber`", "cmd": "min(myList, key=lambda x: abs(x - myNumber))", "question_id": "12141150-81", "cmd_name": "conala", "oracle_man": ["python.library.functions#abs", "python.library.functions#min"], "canonical_cmd": "min(VAR_STR, key=lambda x: abs(x - VAR_STR))"}
+{"nl": "Concat each values in a tuple `(34.2424, -64.2344, 76.3534, 45.2344)` to get a string", "cmd": "\"\"\"\"\"\".join(str(i) for i in (34.2424, -64.2344, 76.3534, 45.2344))", "question_id": "17426386-88", "cmd_name": "conala", "oracle_man": ["python.library.stdtypes#str", "python.library.stdtypes#str.join"], "canonical_cmd": "\"\"\"\"\"\".join(str(i) for i in (VAR_STR))"}
+{"nl": "run the code contained in string \"print('Hello')\"", "cmd": "eval(\"print('Hello')\")", "question_id": "1015142-46", "cmd_name": "conala", "oracle_man": ["python.library.functions#eval"], "canonical_cmd": "eval('VAR_STR')"}
+{"nl": "convert bytes string `s`  to an unsigned integer", "cmd": "struct.unpack('>q', s)[0]", "question_id": "4433017-13", "cmd_name": "conala", "oracle_man": ["python.library.struct#struct.unpack"], "canonical_cmd": "struct.unpack('>q', VAR_STR)[0]"}
+{"nl": "Get a random string of length `length`", "cmd": "return ''.join(random.choice(string.lowercase) for i in range(length))", "question_id": "2030053-18", "cmd_name": "conala", "oracle_man": ["python.library.random#random.choice", "python.library.functions#range", "python.library.stdtypes#str.join"], "canonical_cmd": "return ''.join(random.choice(string.lowercase) for i in range(VAR_STR))"}
+{"nl": "access the class variable `a_string` from a class object `test`", "cmd": "getattr(test, a_string)", "question_id": "13303100-52", "cmd_name": "conala", "oracle_man": ["python.library.functions#getattr"], "canonical_cmd": "getattr(VAR_STR, VAR_STR)"}
+{"nl": "disable abbreviation in argparse", "cmd": "parser = argparse.ArgumentParser(allow_abbrev=False)", "question_id": "10750802-58", "cmd_name": "conala", "oracle_man": ["python.library.argparse#argparse.ArgumentParser"], "canonical_cmd": "parser = argparse.ArgumentParser(allow_abbrev=False)"}
+{"nl": "get a dictionary in list `dicts` which key 'ratio' is closer to a global value 1.77672955975", "cmd": "min(dicts, key=lambda x: (abs(1.77672955975 - x['ratio']), -x['pixels']))", "question_id": "42442428-5", "cmd_name": "conala", "oracle_man": ["python.library.functions#abs", "python.library.functions#min"], "canonical_cmd": "min(VAR_STR, key=lambda x: (abs(1.77672955975 - x['VAR_STR']), -x['pixels']))"}
+{"nl": "copy the content of file 'file.txt' to file 'file2.txt'", "cmd": "shutil.copy('file.txt', 'file2.txt')", "question_id": "36875258-12", "cmd_name": "conala", "oracle_man": ["python.library.shutil#shutil.copy"], "canonical_cmd": "shutil.copy('VAR_STR', 'VAR_STR')"}
+{"nl": "Calling an external command \"echo Hello World\"", "cmd": "print(subprocess.Popen('echo Hello World', shell=True, stdout=subprocess.PIPE).stdout.read())", "question_id": "89228-69", "cmd_name": "conala", "oracle_man": ["python.library.subprocess#subprocess.Popen", "python.library.os#os.read"], "canonical_cmd": "print(subprocess.Popen('VAR_STR', shell=True, stdout=subprocess.PIPE).stdout.\n    read())"}
+{"nl": "Calling an external command \"echo Hello World\"", "cmd": "print(os.popen('echo Hello World').read())", "question_id": "89228-17", "cmd_name": "conala", "oracle_man": ["python.library.os#os.popen", "python.library.os#os.read"], "canonical_cmd": "print(os.popen('VAR_STR').read())"}
+{"nl": "Calling an external command \"ls\"", "cmd": "p = subprocess.Popen('ls', shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)\nfor line in p.stdout.readlines():\n    print(line, end=' ')\nretval = p.wait()", "question_id": "89228-83", "cmd_name": "conala", "oracle_man": ["python.library.subprocess#subprocess.Popen", "python.library.subprocess#subprocess.Popen.wait", "python.library.io#io.IOBase.readlines"], "canonical_cmd": "p = subprocess.Popen('VAR_STR', shell=True, stdout=subprocess.PIPE, stderr=\n    subprocess.STDOUT)\nfor line in p.stdout.readlines():\n    print(line, end=' ')\nretval = p.wait()"}
+{"nl": "convert numpy array into python list structure", "cmd": "np.array([[1, 2, 3], [4, 5, 6]]).tolist()", "question_id": "1966207-46", "cmd_name": "conala", "oracle_man": ["numpy.reference.generated.numpy.array", "python.library.array#array.array.tolist"], "canonical_cmd": "np.array([[1, 2, 3], [4, 5, 6]]).tolist()"}
+{"nl": "rename file `dir` to `dir` + '!'", "cmd": "os.rename(dir, dir + '!')", "question_id": "11816315-65", "cmd_name": "conala", "oracle_man": ["python.library.os#os.rename"], "canonical_cmd": "os.rename(VAR_STR, VAR_STR + 'VAR_STR')"}
+{"nl": "find the current directory", "cmd": "os.getcwd()", "question_id": "5137497-38", "cmd_name": "conala", "oracle_man": ["python.library.os#os.getcwd"], "canonical_cmd": "os.getcwd()"}
+{"nl": "Find current directory", "cmd": "cwd = os.getcwd()", "question_id": "5137497-54", "cmd_name": "conala", "oracle_man": ["python.library.os#os.getcwd"], "canonical_cmd": "cwd = os.getcwd()"}
+{"nl": "use operations like max/min within a row to a dataframe 'd' in pandas", "cmd": "d.apply(lambda row: min([row['A'], row['B']]) - row['C'], axis=1)", "question_id": "12376863-62", "cmd_name": "conala", "oracle_man": ["python.library.functions#min"], "canonical_cmd": "VAR_STR.apply(lambda row: min([row['A'], row['B']]) - row['C'], axis=1)"}
+{"nl": "How to plot with x-axis at the top of the figure?", "cmd": "ax.xaxis.set_ticks_position('top')", "question_id": "8639973-88", "cmd_name": "conala", "oracle_man": ["matplotlib._as_gen.matplotlib.axis.xaxis.set_ticks_position"], "canonical_cmd": "ax.xaxis.set_ticks_position('top')"}
+{"nl": "sum the column `positions` along the  other columns `stock`, `same1`, `same2` in a pandas data frame `df`", "cmd": "df.groupby(['stock', 'same1', 'same2'], as_index=False)['positions'].sum()", "question_id": "17166601-53", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.groupby", "python.library.functions#sum"], "canonical_cmd": "VAR_STR.groupby(['VAR_STR', 'VAR_STR', 'VAR_STR'], as_index=False)['VAR_STR'].sum()"}
+{"nl": "Summing across rows of Pandas Dataframe", "cmd": "df.groupby(['stock', 'same1', 'same2'])['positions'].sum().reset_index()", "question_id": "17166601-28", "cmd_name": "conala", "oracle_man": ["pandas.reference.api.pandas.dataframe.groupby", "python.library.functions#sum", "pandas.reference.api.pandas.dataframe.reset_index"], "canonical_cmd": "df.groupby(['stock', 'same1', 'same2'])['positions'].sum().reset_index()"}

conala-docs.jsonl

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