task_id
int64 19.3k
41.9M
| prompt
stringlengths 17
68
| suffix
stringlengths 0
22
| canonical_solution
stringlengths 6
153
| test_start
stringlengths 22
198
| test
sequence | entry_point
stringlengths 7
10
| intent
stringlengths 19
200
| library
sequence |
|---|---|---|---|---|---|---|---|---|
1,762,484 | def f_1762484(stocks_list):
return | [x for x in range(len(stocks_list)) if stocks_list[x] == 'MSFT'] |
def check(candidate): | [
"\n stocks_list = ['AAPL', 'MSFT', 'GOOG', 'MSFT', 'MSFT']\n assert(candidate(stocks_list) == [1,3,4])\n",
"\n stocks_list = ['AAPL', 'MSXT', 'GOOG', 'MSAT', 'SFT']\n assert(candidate(stocks_list) == [])\n"
] | f_1762484 | find the index of an element 'MSFT' in a list `stocks_list` | [] |
|
3,464,359 | def f_3464359(ax, labels):
return | ax.set_xticklabels(labels, rotation=45) |
import matplotlib.pyplot as plt
def check(candidate): | [
"\n fig, ax = plt.subplots()\n ax.plot([1, 2, 3, 4], [1, 4, 2, 3])\n ret = candidate(ax, [f\"#{i}\" for i in range(7)])\n assert [tt.get_rotation() == 45.0 for tt in ret]\n"
] | f_3464359 | rotate the xtick `labels` of matplotlib plot `ax` by `45` degrees to make long labels readable | [
"matplotlib"
] |
|
875,968 | def f_875968(s):
return | re.sub('[^\\w]', ' ', s) |
import re
def check(candidate): | [
"\n s = \"how much for the maple syrup? $20.99? That's ridiculous!!!\"\n assert candidate(s) == 'how much for the maple syrup 20 99 That s ridiculous '\n"
] | f_875968 | remove symbols from a string `s` | [
"re"
] |
|
34,750,084 | def f_34750084(s):
return | re.findall("'\\\\[0-7]{1,3}'", s) |
import re
def check(candidate): | [
"\n assert candidate(r\"char x = '\\077';\") == [\"'\\\\077'\"]\n"
] | f_34750084 | Find octal characters matches from a string `s` using regex | [
"re"
] |
|
13,209,288 | def f_13209288(input):
return | re.split(r'[ ](?=[A-Z]+\b)', input) |
import re
def check(candidate): | [
"\n assert candidate('HELLO there HOW are YOU') == ['HELLO there', 'HOW are', 'YOU']\n",
"\n assert candidate('hELLO there HoW are YOU') == ['hELLO there HoW are', 'YOU']\n",
"\n assert candidate('7 is a NUMBER') == ['7 is a', 'NUMBER']\n",
"\n assert candidate('NUMBER 7') == ['NUMBER 7']\n"
] | f_13209288 | split string `input` based on occurrences of regex pattern '[ ](?=[A-Z]+\\b)' | [
"re"
] |
|
13,209,288 | def f_13209288(input):
return | re.split('[ ](?=[A-Z])', input) |
import re
def check(candidate): | [
"\n assert candidate('HELLO there HOW are YOU') == ['HELLO there', 'HOW are', 'YOU']\n",
"\n assert candidate('hELLO there HoW are YOU') == ['hELLO there', 'HoW are', 'YOU']\n",
"\n assert candidate('7 is a NUMBER') == ['7 is a', 'NUMBER']\n",
"\n assert candidate('NUMBER 7') == ['NUMBER 7']\n"
] | f_13209288 | Split string `input` at every space followed by an upper-case letter | [
"re"
] |
|
24,642,040 | def f_24642040(url, files, headers, data):
return | requests.post(url, files=files, headers=headers, data=data) |
import requests
from unittest.mock import Mock
def check(candidate): | [
"\n requests.post = Mock()\n try:\n candidate('https://www.google.com', ['a.txt'], {'accept': 'text/json'}, {'name': 'abc'})\n except:\n assert False\n"
] | f_24642040 | send multipart encoded file `files` to url `url` with headers `headers` and metadata `data` | [
"requests"
] |
|
4,290,716 | def f_4290716(filename, bytes_):
return | open(filename, 'wb').write(bytes_) |
def check(candidate): | [
"\n bytes_ = b'68 65 6c 6c 6f'\n candidate(\"tmpfile\", bytes_)\n\n with open(\"tmpfile\", 'rb') as fr:\n assert fr.read() == bytes_\n"
] | f_4290716 | write bytes `bytes_` to a file `filename` in python 3 | [] |
|
33,078,554 | def f_33078554(lst, dct):
return | [dct[k] for k in lst] |
def check(candidate): | [
"\n assert candidate(['c', 'd', 'a', 'b', 'd'], {'a': '3', 'b': '3', 'c': '5', 'd': '3'}) == ['5', '3', '3', '3', '3'] \n",
"\n assert candidate(['c', 'd', 'a', 'b', 'd'], {'a': 3, 'b': 3, 'c': 5, 'd': 3}) == [5, 3, 3, 3, 3] \n",
"\n assert candidate(['c', 'd', 'a', 'b'], {'a': 3, 'b': 3, 'c': 5, 'd': 3}) == [5, 3, 3, 3]\n"
] | f_33078554 | get a list from a list `lst` with values mapped into a dictionary `dct` | [] |
|
15,247,628 | def f_15247628(x):
return | x['name'][x.duplicated('name')] |
import pandas as pd
def check(candidate): | [
"\n assert candidate(pd.DataFrame([{'name': 'willy', 'age': 10}, {'name': 'wilson', 'age': 11}, {'name': 'zoe', 'age': 10}])).tolist() == [] \n",
"\n assert candidate(pd.DataFrame([{'name': 'willy', 'age': 10}, {'name': 'willy', 'age': 11}, {'name': 'zoe', 'age': 10}])).tolist() == ['willy'] \n",
"\n assert candidate(pd.DataFrame([{'name': 'willy', 'age': 11}, {'name': 'willy', 'age': 11}, {'name': 'zoe', 'age': 10}])).tolist() == ['willy'] \n",
"\n assert candidate(pd.DataFrame([{'name': 'Willy', 'age': 11}, {'name': 'willy', 'age': 11}, {'name': 'zoe', 'age': 10}])).tolist() == []\n"
] | f_15247628 | find duplicate names in column 'name' of the dataframe `x` | [
"pandas"
] |
|
783,897 | def f_783897():
return | round(1.923328437452, 3) |
def check(candidate): | [
"\n assert candidate() == 1.923\n"
] | f_783897 | truncate float 1.923328437452 to 3 decimal places | [] |
|
22,859,493 | def f_22859493(li):
return | sorted(li, key=lambda x: datetime.strptime(x[1], '%d/%m/%Y'), reverse=True) |
from datetime import datetime
def check(candidate): | [
"\n assert candidate([['name', '01/03/2012', 'job'], ['name', '02/05/2013', 'job'], ['name', '03/08/2014', 'job']]) == [['name', '03/08/2014', 'job'], ['name', '02/05/2013', 'job'], ['name', '01/03/2012', 'job']] \n",
"\n assert candidate([['name', '01/03/2012', 'job'], ['name', '02/05/2012', 'job'], ['name', '03/08/2012', 'job']]) == [['name', '03/08/2012', 'job'], ['name', '02/05/2012', 'job'], ['name', '01/03/2012', 'job']] \n",
"\n assert candidate([['name', '01/03/2012', 'job'], ['name', '02/03/2012', 'job'], ['name', '03/03/2012', 'job']]) == [['name', '03/03/2012', 'job'], ['name', '02/03/2012', 'job'], ['name', '01/03/2012', 'job']] \n",
"\n assert candidate([['name', '03/03/2012', 'job'], ['name', '03/03/2012', 'job'], ['name', '03/03/2012', 'job']]) == [['name', '03/03/2012', 'job'], ['name', '03/03/2012', 'job'], ['name', '03/03/2012', 'job']] \n"
] | f_22859493 | sort list `li` in descending order based on the date value in second element of each list in list `li` | [
"datetime"
] |
|
29,394,552 | def f_29394552(ax):
|
return | ax.set_rlabel_position(135) |
import matplotlib.pyplot as plt
def check(candidate): | [
"\n ax = plt.subplot(111, polar=True)\n candidate(ax)\n assert ax.properties()['rlabel_position'] == 135.0\n"
] | f_29394552 | place the radial ticks in plot `ax` at 135 degrees | [
"matplotlib"
] |
3,320,406 | def f_3320406(my_path):
return | os.path.isabs(my_path) |
import os
def check(candidate): | [
"\n assert candidate('.') == False \n",
"\n assert candidate('/') == True \n",
"\n assert candidate('/usr') == True\n"
] | f_3320406 | check if path `my_path` is an absolute path | [
"os"
] |
|
2,212,433 | def f_2212433(yourdict):
return | len(list(yourdict.keys())) |
def check(candidate): | [
"\n assert candidate({'a': 1, 'b': 2, 'c': 3}) == 3 \n",
"\n assert candidate({'a': 2, 'c': 3}) == 2\n"
] | f_2212433 | get number of keys in dictionary `yourdict` | [] |
|
2,212,433 | def f_2212433(yourdictfile):
return | len(set(open(yourdictfile).read().split())) |
def check(candidate): | [
"\n with open('dict.txt', 'w') as fw:\n for w in [\"apple\", \"banana\", \"tv\", \"apple\", \"phone\"]:\n fw.write(f\"{w}\\n\")\n assert candidate('dict.txt') == 4\n"
] | f_2212433 | count the number of keys in dictionary `yourdictfile` | [] |
|
20,067,636 | def f_20067636(df):
return | df.groupby('id').first() |
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame({\n 'id': [1, 1, 1, 2, 2, 3, 3, 3, 3, 4, 4, 5, 6, 6, 6, 7, 7], \n 'value': ['first', 'second', 'second', 'first', 'second', 'first', 'third', 'fourth', 'fifth', 'second', 'fifth', 'first', 'first', 'second', 'third', 'fourth', 'fifth']\n })\n assert candidate(df).to_dict() == {'value': {1: 'first', 2: 'first', 3: 'first', 4: 'second', 5: 'first', 6: 'first', 7: 'fourth'}}\n"
] | f_20067636 | pandas dataframe `df` get first row of each group by 'id' | [
"pandas"
] |
|
40,924,332 | def f_40924332(df):
return | pd.concat([df[0].apply(pd.Series), df[1]], axis=1) |
import numpy as np
import pandas as pd
def check(callerFunction): | [
"\n assert callerFunction(pd.DataFrame([[[8, 10, 12], 'A'], [[7, 9, 11], 'B']])).equals(pd.DataFrame([[8,10,12,'A'], [7,9,11,'B']], columns=[0,1,2,1]))\n",
"\n assert callerFunction(pd.DataFrame([[[8, 10, 12], 'A'], [[7, 11], 'B']])).equals(pd.DataFrame([[8.0,10.0,12.0,'A'], [7.0,11.0,np.nan,'B']], columns=[0,1,2,1]))\n",
"\n assert callerFunction(pd.DataFrame([[[8, 10, 12]], [[7, 9, 11], 'B']])).equals(pd.DataFrame([[8,10,12,None], [7,9,11,'B']], columns=[0,1,2,1]))\n"
] | f_40924332 | split a list in first column into multiple columns keeping other columns as well in pandas data frame `df` | [
"numpy",
"pandas"
] |
|
30,759,776 | def f_30759776(data):
return | re.findall('src="js/([^"]*\\bjquery\\b[^"]*)"', data) |
import re
def check(candidate): | [
"\n data = '<script type=\"text/javascript\" src=\"js/jquery-1.9.1.min.js\"/><script type=\"text/javascript\" src=\"js/jquery-migrate-1.2.1.min.js\"/><script type=\"text/javascript\" src=\"js/jquery-ui.min.js\"/><script type=\"text/javascript\" src=\"js/abc_bsub.js\"/><script type=\"text/javascript\" src=\"js/abc_core.js\"/> <script type=\"text/javascript\" src=\"js/abc_explore.js\"/><script type=\"text/javascript\" src=\"js/abc_qaa.js\"/>'\n assert candidate(data) == ['jquery-1.9.1.min.js', 'jquery-migrate-1.2.1.min.js', 'jquery-ui.min.js']\n"
] | f_30759776 | extract attributes 'src="js/([^"]*\\bjquery\\b[^"]*)"' from string `data` | [
"re"
] |
|
25,388,796 | def f_25388796():
return | sum(int(float(item)) for item in [_f for _f in ['', '3.4', '', '', '1.0'] if _f]) |
def check(candidate): | [
"\n assert candidate() == 4\n"
] | f_25388796 | Sum integers contained in strings in list `['', '3.4', '', '', '1.0']` | [] |
|
804,995 | def f_804995():
return | subprocess.Popen(['c:\\Program Files\\VMware\\VMware Server\\vmware-cmd.bat']) |
import subprocess
from unittest.mock import Mock
def check(candidate): | [
"\n subprocess.Popen = Mock(return_value = 0)\n assert candidate() == 0\n"
] | f_804995 | Call a subprocess with arguments `c:\\Program Files\\VMware\\VMware Server\\vmware-cmd.bat` that may contain spaces | [
"subprocess"
] |
|
26,441,253 | def f_26441253(q):
|
return q | for n in [1,3,4,2]: q.put((-n, n)) |
from queue import PriorityQueue
def check(candidate): | [
"\n q = PriorityQueue()\n q = candidate(q)\n expected = [4, 3, 2, 1]\n for i in range(0, len(expected)):\n assert q.get()[1] == expected[i]\n"
] | f_26441253 | reverse a priority queue `q` in python without using classes | [
"queue"
] |
18,897,261 | def f_18897261(df):
return | df['group'].plot(kind='bar', color=['r', 'g', 'b', 'r', 'g', 'b', 'r']) |
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame([1, 3, 4, 5, 7, 9], columns = ['group'])\n a = candidate(df)\n assert 'AxesSubplot' in str(type(a))\n"
] | f_18897261 | make a barplot of data in column `group` of dataframe `df` colour-coded according to list `color` | [
"pandas"
] |
|
373,194 | def f_373194(data):
return | re.findall('([a-fA-F\\d]{32})', data) |
import re
def check(candidate): | [
"\n assert candidate('6f96cfdfe5ccc627cadf24b41725caa4 gorilla') == ['6f96cfdfe5ccc627cadf24b41725caa4']\n"
] | f_373194 | find all matches of regex pattern '([a-fA-F\\d]{32})' in string `data` | [
"re"
] |
|
518,021 | def f_518021(my_list):
return | len(my_list) |
def check(candidate): | [
"\n assert candidate([]) == 0\n",
"\n assert candidate([1]) == 1\n",
"\n assert candidate([1, 2]) == 2\n"
] | f_518021 | Get the length of list `my_list` | [] |
|
518,021 | def f_518021(l):
return | len(l) |
import numpy as np
def check(candidate): | [
"\n assert candidate([]) == 0\n",
"\n assert candidate(np.array([1])) == 1\n",
"\n assert candidate(np.array([1, 2])) == 2\n"
] | f_518021 | Getting the length of array `l` | [
"numpy"
] |
|
518,021 | def f_518021(s):
return | len(s) |
import numpy as np
def check(candidate): | [
"\n assert candidate([]) == 0\n",
"\n assert candidate(np.array([1])) == 1\n",
"\n assert candidate(np.array([1, 2])) == 2\n"
] | f_518021 | Getting the length of array `s` | [
"numpy"
] |
|
518,021 | def f_518021(my_tuple):
return | len(my_tuple) |
def check(candidate): | [
"\n assert candidate(()) == 0\n",
"\n assert candidate(('aa', 'wfseg', '')) == 3\n",
"\n assert candidate(('apple',)) == 1\n"
] | f_518021 | Getting the length of `my_tuple` | [] |
|
518,021 | def f_518021(my_string):
return | len(my_string) |
def check(candidate): | [
"\n assert candidate(\"sedfgbdjofgljnh\") == 15\n",
"\n assert candidate(\" \") == 13\n",
"\n assert candidate(\"vsdh4'cdf'\") == 10\n"
] | f_518021 | Getting the length of `my_string` | [] |
|
40,452,956 | def f_40452956():
return | b'\\a'.decode('unicode-escape') |
def check(candidate): | [
"\n assert candidate() == '\\x07'\n"
] | f_40452956 | remove escape character from string "\\a" | [] |
|
8,687,018 | def f_8687018():
return | """obama""".replace('a', '%temp%').replace('b', 'a').replace('%temp%', 'b') |
def check(candidate): | [
"\n assert candidate() == 'oabmb'\n"
] | f_8687018 | replace each 'a' with 'b' and each 'b' with 'a' in the string 'obama' in a single pass. | [] |
|
303,200 | def f_303200():
|
return | shutil.rmtree('/folder_name') |
import os
import shutil
from unittest.mock import Mock
def check(candidate): | [
"\n shutil.rmtree = Mock()\n os.walk = Mock(return_value = [])\n candidate()\n assert os.walk('/') == []\n"
] | f_303200 | remove directory tree '/folder_name' | [
"os",
"shutil"
] |
13,740,672 | def f_13740672(data):
|
return data |
def weekday(i):
if i >=1 and i <= 5: return True
else: return False
data['weekday'] = data['my_dt'].apply(lambda x: weekday(x))
|
import pandas as pd
def check(candidate): | [
"\n data = pd.DataFrame([1, 2, 3, 4, 5, 6, 7], columns = ['my_dt'])\n data = candidate(data)\n assert data['weekday'][5] == False\n assert data['weekday'][6] == False\n for i in range (0, 5):\n assert data['weekday'][i]\n"
] | f_13740672 | create a new column `weekday` in pandas data frame `data` based on the values in column `my_dt` | [
"pandas"
] |
20,950,650 | def f_20950650(x):
return | sorted(x, key=x.get, reverse=True) |
from collections import Counter
def check(candidate): | [
"\n x = Counter({'blue': 1, 'red': 2, 'green': 3})\n assert candidate(x) == ['green', 'red', 'blue']\n",
"\n x = Counter({'blue': 1.234, 'red': 1.35, 'green': 1.789})\n assert candidate(x) == ['green', 'red', 'blue']\n",
"\n x = Counter({'blue': \"b\", 'red': \"r\", 'green': \"g\"})\n assert candidate(x) == ['red', 'green', 'blue']\n"
] | f_20950650 | reverse sort Counter `x` by values | [
"collections"
] |
|
20,950,650 | def f_20950650(x):
return | sorted(list(x.items()), key=lambda pair: pair[1], reverse=True) |
from collections import Counter
def check(candidate): | [
"\n x = Counter({'blue': 1, 'red': 2, 'green': 3})\n assert candidate(x) == [('green', 3), ('red', 2), ('blue', 1)]\n",
"\n x = Counter({'blue': 1.234, 'red': 1.35, 'green': 1.789})\n assert candidate(x) == [('green', 1.789), ('red', 1.35), ('blue', 1.234)]\n",
"\n x = Counter({'blue': \"b\", 'red': \"r\", 'green': \"g\"})\n assert candidate(x) == [('red', \"r\"), ('green', \"g\"), ('blue', \"b\")]\n"
] | f_20950650 | reverse sort counter `x` by value | [
"collections"
] |
|
9,775,297 | def f_9775297(a, b):
return | np.vstack((a, b)) |
import numpy as np
def check(candidate): | [
"\n a = np.array([[1, 2, 3], [4, 5, 6]])\n b = np.array([[9, 8, 7], [6, 5, 4]])\n assert np.array_equal(candidate(a, b), np.array([[1, 2, 3], [4, 5, 6], [9, 8, 7], [6, 5, 4]]))\n",
"\n a = np.array([[1, 2.45, 3], [4, 0.55, 612]])\n b = np.array([[988, 8, 7], [6, 512, 4]])\n assert np.array_equal(candidate(a, b), np.array([[1, 2.45, 3], [4, 0.55, 612], [988, 8, 7], [6, 512, 4]]))\n"
] | f_9775297 | append a numpy array 'b' to a numpy array 'a' | [
"numpy"
] |
|
21,887,754 | def f_21887754(a, b):
return | np.concatenate((a, b), axis=0) |
import numpy as np
def check(candidate): | [
"\n a = np.array([[1, 5, 9], [2, 6, 10]])\n b = np.array([[3, 7, 11], [4, 8, 12]])\n assert np.array_equal(candidate(a, b), np.array([[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]))\n",
"\n a = np.array([[1, 2.45, 3], [4, 0.55, 612]])\n b = np.array([[988, 8, 7], [6, 512, 4]])\n assert np.array_equal(candidate(a, b), np.array([[1, 2.45, 3], [4, 0.55, 612], [988, 8, 7], [6, 512, 4]]))\n"
] | f_21887754 | numpy concatenate two arrays `a` and `b` along the first axis | [
"numpy"
] |
|
21,887,754 | def f_21887754(a, b):
return | np.concatenate((a, b), axis=1) |
import numpy as np
def check(candidate): | [
"\n a = np.array([[1, 5, 9], [2, 6, 10]])\n b = np.array([[3, 7, 11], [4, 8, 12]])\n assert np.array_equal(candidate(a, b), np.array([[1, 5, 9, 3, 7, 11], [2, 6, 10, 4, 8, 12]]))\n",
"\n a = np.array([[1, 2.45, 3], [4, 0.55, 612]])\n b = np.array([[988, 8, 7], [6, 512, 4]])\n assert np.array_equal(candidate(a, b), np.array([[1, 2.45, 3, 988, 8, 7], [4, 0.55, 612, 6, 512, 4]]))\n"
] | f_21887754 | numpy concatenate two arrays `a` and `b` along the second axis | [
"numpy"
] |
|
21,887,754 | def f_21887754(a, b):
return | np.r_[(a[None, :], b[None, :])] |
import numpy as np
def check(candidate): | [
"\n a = np.array([[1, 5, 9], [2, 6, 10]])\n b = np.array([[3, 7, 11], [4, 8, 12]])\n assert np.array_equal(candidate(a, b), np.array([[[1, 5, 9], [2, 6, 10]], [[3, 7, 11], [4, 8, 12]]]))\n",
"\n a = np.array([[1, 2.45, 3], [4, 0.55, 612]])\n b = np.array([[988, 8, 7], [6, 512, 4]])\n assert np.array_equal(candidate(a, b), np.array([[[1, 2.45, 3], [4, 0.55, 612]], [[988, 8 , 7], [6, 512, 4]]]))\n"
] | f_21887754 | numpy concatenate two arrays `a` and `b` along the first axis | [
"numpy"
] |
|
21,887,754 | def f_21887754(a, b):
return | np.array((a, b)) |
import numpy as np
def check(candidate): | [
"\n a = np.array([[1, 5, 9], [2, 6, 10]])\n b = np.array([[3, 7, 11], [4, 8, 12]])\n assert np.array_equal(candidate(a, b), np.array([[[1, 5, 9], [2, 6, 10]], [[3, 7, 11], [4, 8, 12]]]))\n",
"\n a = np.array([[1, 2.45, 3], [4, 0.55, 612]])\n b = np.array([[988, 8, 7], [6, 512, 4]])\n assert np.array_equal(candidate(a, b), np.array([[[1, 2.45, 3], [4, 0.55, 612]], [[988, 8 , 7], [6, 512, 4]]]))\n"
] | f_21887754 | numpy concatenate two arrays `a` and `b` along the first axis | [
"numpy"
] |
|
2,805,231 | def f_2805231():
return | socket.getaddrinfo('google.com', 80) |
import socket
def check(candidate): | [
"\n res = candidate()\n assert all([(add[4][1] == 80) for add in res])\n"
] | f_2805231 | fetch address information for host 'google.com' ion port 80 | [
"socket"
] |
|
17,552,997 | def f_17552997(df):
return | df.xs('sat', level='day', drop_level=False) |
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame({'year':[2008,2008,2008,2008,2009,2009,2009,2009], \n 'flavour':['strawberry','strawberry','banana','banana',\n 'strawberry','strawberry','banana','banana'],\n 'day':['sat','sun','sat','sun','sat','sun','sat','sun'],\n 'sales':[10,12,22,23,11,13,23,24]})\n df = df.set_index(['year','flavour','day'])\n assert candidate(df).to_dict() == {'sales': {(2008, 'strawberry', 'sat'): 10, (2008, 'banana', 'sat'): 22, (2009, 'strawberry', 'sat'): 11, (2009, 'banana', 'sat'): 23}}\n"
] | f_17552997 | add a column 'day' with value 'sat' to dataframe `df` | [
"pandas"
] |
|
4,356,842 | def f_4356842():
return | HttpResponse('Unauthorized', status=401) |
from django.http import HttpResponse
from django.conf import settings
if not settings.configured:
settings.configure(DEBUG=True)
def check(candidate): | [
"\n assert candidate().status_code == 401\n"
] | f_4356842 | return a 401 unauthorized in django | [
"django"
] |
|
13,598,363 | def f_13598363():
return | Flask('test', template_folder='wherever') |
from flask import Flask
def check(candidate): | [
"\n __name__ == \"test\"\n assert candidate().template_folder == \"wherever\"\n"
] | f_13598363 | Flask set folder 'wherever' as the default template folder | [
"flask"
] |
|
3,398,589 | def f_3398589(c2):
|
return c2 | c2.sort(key=lambda row: row[2]) |
def check(candidate): | [
"\n c2 = [[14, 25, 46], [1, 22, 53], [7, 8, 9]]\n candidate(c2)\n assert c2[0] == [7,8,9]\n",
"\n c2 = [[14.343, 25.24, 46], [1, 22, 53.45], [7, 8.65, 9]]\n candidate(c2)\n assert c2[0] == [7,8.65,9]\n"
] | f_3398589 | sort a list of lists 'c2' such that third row comes first | [] |
3,398,589 | def f_3398589(c2):
|
return c2 | c2.sort(key=lambda row: (row[2], row[1], row[0])) |
def check(candidate): | [
"\n c2 = [[14, 25, 46], [1, 22, 53], [7, 8, 9]]\n candidate(c2)\n assert c2[0] == [7,8,9]\n",
"\n c2 = [[14.343, 25.24, 46], [1, 22, 53.45], [7, 8.65, 9]]\n candidate(c2)\n assert c2[0] == [7,8.65,9]\n"
] | f_3398589 | sort a list of lists 'c2' in reversed row order | [] |
3,398,589 | def f_3398589(c2):
|
return c2 | c2.sort(key=lambda row: (row[2], row[1])) |
def check(candidate): | [
"\n c2 = [[14, 25, 46], [1, 22, 53], [7, 8, 9]]\n candidate(c2)\n assert c2[0] == [7,8,9]\n",
"\n c2 = [[14.343, 25.24, 46], [1, 22, 53.45], [7, 8.65, 9]]\n candidate(c2)\n assert c2[0] == [7,8.65,9]\n"
] | f_3398589 | Sorting a list of lists `c2`, each by the third and second row | [] |
10,960,463 | def f_10960463():
return | matplotlib.rc('font', **{'sans-serif': 'Arial', 'family': 'sans-serif'}) |
import matplotlib
def check(candidate): | [
"\n try:\n candidate()\n except:\n assert False\n"
] | f_10960463 | set font `Arial` to display non-ascii characters in matplotlib | [
"matplotlib"
] |
|
20,576,618 | def f_20576618(df):
return | df['date'].apply(lambda x: x.toordinal()) |
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame(\n {\n \"group\": [\"A\", \"A\", \"A\", \"A\", \"A\"],\n \"date\": pd.to_datetime([\"2020-01-02\", \"2020-01-13\", \"2020-02-01\", \"2020-02-23\", \"2020-03-05\"]),\n \"value\": [10, 20, 16, 31, 56],\n }) \n data_series = candidate(df).tolist()\n assert data_series[1] == 737437\n",
"\n df = pd.DataFrame(\n {\n \"group\": [\"A\", \"A\", \"A\", \"A\", \"A\"],\n \"date\": pd.to_datetime([\"2020-01-02\", \"2020-01-13\", \"2020-02-01\", \"2020-02-23\", \"2020-03-05\"]),\n \"value\": [10, 20, 16, 31, 56],\n }) \n data_series = candidate(df).tolist()\n assert data_series[1] == 737437\n"
] | f_20576618 | Convert DateTime column 'date' of pandas dataframe 'df' to ordinal | [
"pandas"
] |
|
31,793,195 | def f_31793195(df):
return | df.index.get_loc('bob') |
import pandas as pd
import numpy as np
def check(candidate): | [
"\n df = pd.DataFrame(data=np.asarray([[1,2,3],[4,5,6],[7,8,9]]), index=['alice', 'bob', 'charlie'])\n index = candidate(df)\n assert index == 1\n"
] | f_31793195 | Get the integer location of a key `bob` in a pandas data frame `df` | [
"numpy",
"pandas"
] |
|
10,487,278 | def f_10487278(my_dict):
|
return my_dict | my_dict.update({'third_key': 1}) |
def check(candidate): | [
"\n my_dict = {'a':1, 'b':2}\n assert candidate(my_dict) == {'a':1, 'b':2, 'third_key': 1}\n",
"\n my_dict = {'c':1, 'd':2}\n assert candidate(my_dict) == {'c':1, 'd':2, 'third_key': 1}\n"
] | f_10487278 | add an item with key 'third_key' and value 1 to an dictionary `my_dict` | [] |
10,487,278 | def f_10487278():
|
return my_list | my_list = [] |
def check(candidate): | [
"\n assert candidate() == []\n"
] | f_10487278 | declare an array `my_list` | [] |
10,487,278 | def f_10487278(my_list):
|
return my_list | my_list.append(12) |
def check(candidate): | [
"\n assert candidate([1,2]) == [1, 2, 12] \n",
"\n assert candidate([5,6]) == [5, 6, 12]\n"
] | f_10487278 | Insert item `12` to a list `my_list` | [] |
10,155,684 | def f_10155684(myList):
|
return myList | myList.insert(0, 'wuggah') |
def check(candidate): | [
"\n assert candidate([1,2]) == ['wuggah', 1, 2]\n",
"\n assert candidate([]) == ['wuggah'] \n"
] | f_10155684 | add an entry 'wuggah' at the beginning of list `myList` | [] |
3,519,125 | def f_3519125(hex_str):
return | bytes.fromhex(hex_str.replace('\\x', '')) |
def check(candidate): | [
"\n assert candidate(\"\\\\xF3\\\\xBE\\\\x80\\\\x80\") == b'\\xf3\\xbe\\x80\\x80'\n"
] | f_3519125 | convert a hex-string representation `hex_str` to actual bytes | [] |
|
40,144,769 | def f_40144769(df):
return | df[df.columns[-1]] |
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame([[1, 2, 3],[4,5,6]], columns=[\"a\", \"b\", \"c\"])\n assert candidate(df).tolist() == [3,6]\n",
"\n df = pd.DataFrame([[\"Hello\", \"world!\"],[\"Hi\", \"world!\"]], columns=[\"a\", \"b\"])\n assert candidate(df).tolist() == [\"world!\", \"world!\"]\n"
] | f_40144769 | select the last column of dataframe `df` | [
"pandas"
] |
|
30,787,901 | def f_30787901(df):
return | df.loc[df['Letters'] == 'C', 'Letters'].values[0] |
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame([[\"a\", 1],[\"C\", 6]], columns=[\"Letters\", \"Numbers\"])\n assert candidate(df) == 'C'\n",
"\n df = pd.DataFrame([[None, 1],[\"C\", 789]], columns=[\"Letters\", \"Names\"])\n assert candidate(df) == 'C'\n"
] | f_30787901 | get the first value from dataframe `df` where column 'Letters' is equal to 'C' | [
"pandas"
] |
|
18,730,044 | def f_18730044():
return | np.column_stack(([1, 2, 3], [4, 5, 6])) |
import numpy as np
def check(candidate): | [
"\n assert np.all(candidate() == np.array([[1, 4], [2, 5], [3, 6]]))\n"
] | f_18730044 | converting two lists `[1, 2, 3]` and `[4, 5, 6]` into a matrix | [
"numpy"
] |
|
402,504 | def f_402504(i):
return | type(i) |
def check(candidate): | [
"\n assert candidate(\"hello\") is str\n",
"\n assert candidate(123) is int\n",
"\n assert candidate(\"123\") is str\n",
"\n assert candidate(123.4) is float\n"
] | f_402504 | get the type of `i` | [] |
|
402,504 | def f_402504(v):
return | type(v) |
def check(candidate): | [
"\n assert candidate(\"hello\") is str\n",
"\n assert candidate(123) is int\n",
"\n assert candidate(\"123\") is str\n",
"\n assert candidate(123.4) is float\n"
] | f_402504 | determine the type of variable `v` | [] |
|
402,504 | def f_402504(v):
return | type(v) |
def check(candidate): | [
"\n assert candidate(\"hello\") is str\n",
"\n assert candidate(123) is int\n",
"\n assert candidate(\"123\") is str\n",
"\n assert candidate(123.4) is float\n"
] | f_402504 | determine the type of variable `v` | [] |
|
402,504 | def f_402504(variable_name):
return | type(variable_name) |
def check(candidate): | [
"\n assert candidate(\"hello\") is str\n",
"\n assert candidate(123) is int\n",
"\n assert candidate(\"123\") is str\n",
"\n assert candidate(123.4) is float\n"
] | f_402504 | get the type of variable `variable_name` | [] |
|
2,300,756 | def f_2300756(g):
return | next(itertools.islice(g, 5, 5 + 1)) |
import itertools
def check(candidate): | [
"\n test = [1, 2, 3, 4, 5, 6, 7]\n assert(candidate(test) == 6)\n"
] | f_2300756 | get the 5th item of a generator `g` | [
"itertools"
] |
|
20,056,548 | def f_20056548(word):
return | '"{}"'.format(word) |
def check(candidate): | [
"\n assert candidate('Some Random Word') == '\"Some Random Word\"'\n"
] | f_20056548 | return a string `word` with string format | [] |
|
8,546,245 | def f_8546245(list):
return | """ """.join(list) |
def check(candidate): | [
"\n test = ['hello', 'good', 'morning']\n assert candidate(test) == \"hello good morning\"\n"
] | f_8546245 | join a list of strings `list` using a space ' ' | [] |
|
2,276,416 | def f_2276416():
|
return y | y = [[] for n in range(2)] |
def check(candidate): | [
"\n assert(candidate() == [[], []])\n"
] | f_2276416 | create list `y` containing two empty lists | [] |
3,925,614 | def f_3925614(filename):
|
return data | data = [line.strip() for line in open(filename, 'r')] |
def check(candidate): | [
"\n file1 = open(\"myfile.txt\", \"w\")\n L = [\"This is Delhi \\n\", \"This is Paris \\n\", \"This is London \\n\"]\n file1.writelines(L)\n file1.close()\n assert candidate('myfile.txt') == ['This is Delhi', 'This is Paris', 'This is London']\n"
] | f_3925614 | read a file `filename` into a list `data` | [] |
22,187,233 | def f_22187233():
return | """""".join([char for char in 'it is icy' if char != 'i']) |
def check(candidate): | [
"\n assert candidate() == 't s cy'\n"
] | f_22187233 | delete all occurrences of character 'i' in string 'it is icy' | [] |
|
22,187,233 | def f_22187233():
return | re.sub('i', '', 'it is icy') |
import re
def check(candidate): | [
"\n assert candidate() == 't s cy'\n"
] | f_22187233 | delete all instances of a character 'i' in a string 'it is icy' | [
"re"
] |
|
22,187,233 | def f_22187233():
return | """it is icy""".replace('i', '') |
def check(candidate): | [
"\n assert candidate() == 't s cy'\n"
] | f_22187233 | delete all characters "i" in string "it is icy" | [] |
|
13,413,590 | def f_13413590(df):
return | df.dropna(subset=[1]) |
import numpy as np
import pandas as pd
def check(candidate): | [
"\n data = {0:[3.0, 4.0, 2.0], 1:[2.0, 3.0, np.nan], 2:[np.nan, 3.0, np.nan]}\n df = pd.DataFrame(data)\n d = {0:[3.0, 4.0], 1:[2.0, 3.0], 2:[np.nan, 3.0]}\n res = pd.DataFrame(d)\n assert candidate(df).equals(res)\n"
] | f_13413590 | Drop rows of pandas dataframe `df` having NaN in column at index "1" | [
"numpy",
"pandas"
] |
|
598,398 | def f_598398(myList):
return | [x for x in myList if x.n == 30] |
import numpy as np
import pandas as pd
def check(candidate): | [
"\n class Data: \n def __init__(self, a, n): \n self.a = a\n self.n = n\n \n myList = [Data(i, 10*(i%4)) for i in range(20)]\n assert candidate(myList) == [myList[i] for i in [3, 7, 11, 15, 19]]\n"
] | f_598398 | get elements from list `myList`, that have a field `n` value 30 | [
"numpy",
"pandas"
] |
|
10,351,772 | def f_10351772(intstringlist):
|
return nums | nums = [int(x) for x in intstringlist] |
def check(candidate): | [
"\n assert candidate(['1', '2', '3', '4', '5']) == [1, 2, 3, 4, 5]\n",
"\n assert candidate(['001', '200', '3', '4', '5']) == [1, 200, 3, 4, 5]\n"
] | f_10351772 | converting list of strings `intstringlist` to list of integer `nums` | [] |
493,386 | def f_493386():
return | sys.stdout.write('.') |
import sys
def check(candidate): | [
"\n assert candidate() == 1\n"
] | f_493386 | print "." without newline | [
"sys"
] |
|
6,569,528 | def f_6569528():
return | int(round(2.52 * 100)) |
def check(candidate): | [
"\n assert candidate() == 252\n"
] | f_6569528 | round off the float that is the product of `2.52 * 100` and convert it to an int | [] |
|
3,964,681 | def f_3964681():
|
return files |
os.chdir('/mydir')
files = []
for file in glob.glob('*.txt'):
files.append(file)
|
import os
import glob
from unittest.mock import Mock
def check(candidate): | [
"\n samples = ['abc.txt']\n os.chdir = Mock()\n glob.glob = Mock(return_value = samples)\n assert candidate() == samples\n"
] | f_3964681 | Find all files `files` in directory '/mydir' with extension '.txt' | [
"glob",
"os"
] |
3,964,681 | def f_3964681():
return | [file for file in os.listdir('/mydir') if file.endswith('.txt')] |
import os
from unittest.mock import Mock
def check(candidate): | [
"\n samples = ['abc.txt', 'f.csv']\n os.listdir = Mock(return_value = samples)\n assert candidate() == ['abc.txt']\n"
] | f_3964681 | Find all files in directory "/mydir" with extension ".txt" | [
"os"
] |
|
3,964,681 | def f_3964681():
return | [file for (root, dirs, files) in os.walk('/mydir') for file in files if file.endswith('.txt')] |
import os
from unittest.mock import Mock
def check(candidate): | [
"\n name = '/mydir'\n samples = [(name, [], ['abc.txt', 'f.csv'])]\n os.walk = Mock(return_value = samples)\n assert candidate() == ['abc.txt']\n"
] | f_3964681 | Find all files in directory "/mydir" with extension ".txt" | [
"os"
] |
|
20,865,487 | def f_20865487(df):
return | df.plot(legend=False) |
import os
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame([1, 2, 3, 4, 5], columns = ['Vals'])\n res = candidate(df)\n assert 'AxesSubplot' in str(type(res))\n assert res.legend_ is None\n"
] | f_20865487 | plot dataframe `df` without a legend | [
"os",
"pandas"
] |
|
13,368,659 | def f_13368659():
return | ['192.168.%d.%d'%(i, j) for i in range(256) for j in range(256)] |
def check(candidate): | [
"\n addrs = candidate()\n assert len(addrs) == 256*256\n assert addrs == [f'192.168.{i}.{j}' for i in range(256) for j in range(256)]\n"
] | f_13368659 | loop through the IP address range "192.168.x.x" | [] |
|
4,065,737 | def f_4065737(x):
return | sum(1 << i for i, b in enumerate(x) if b) |
def check(candidate): | [
"\n assert candidate([1,2,3]) == 7\n",
"\n assert candidate([1,2,None,3,None]) == 11\n"
] | f_4065737 | Sum the corresponding decimal values for binary values of each boolean element in list `x` | [] |
|
8,691,311 | def f_8691311(line1, line2, line3, target):
|
return | target.write('%r\n%r\n%r\n' % (line1, line2, line3)) |
def check(candidate): | [
"\n file_name = 'abc.txt'\n lines = ['fgh', 'ijk', 'mnop']\n f = open(file_name, 'a')\n candidate(lines[0], lines[1], lines[2], f)\n f.close()\n with open(file_name, 'r') as f:\n f_lines = f.readlines()\n for i in range (0, len(lines)):\n assert lines[i] in f_lines[i]\n"
] | f_8691311 | write multiple strings `line1`, `line2` and `line3` in one line in a file `target` | [] |
10,632,111 | def f_10632111(data):
return | [y for x in data for y in (x if isinstance(x, list) else [x])] |
def check(candidate): | [
"\n data = [[1, 2], [3]]\n assert candidate(data) == [1, 2, 3]\n",
"\n data = [[1, 2], [3], []]\n assert candidate(data) == [1, 2, 3]\n",
"\n data = [1,2,3]\n assert candidate(data) == [1, 2, 3]\n"
] | f_10632111 | Convert list of lists `data` into a flat list | [] |
|
15,392,730 | def f_15392730():
return | 'foo\nbar'.encode('unicode_escape') |
def check(candidate): | [
"\n assert candidate() == b'foo\\\\nbar'\n"
] | f_15392730 | Print new line character as `\n` in a string `foo\nbar` | [] |
|
1,010,961 | def f_1010961(s):
return | """""".join(s.rsplit(',', 1)) |
def check(candidate): | [
"\n assert candidate('abc, def, klm') == 'abc, def klm'\n"
] | f_1010961 | remove last comma character ',' in string `s` | [] |
|
23,855,976 | def f_23855976(x):
return | (x[1:] + x[:-1]) / 2 |
import numpy as np
def check(candidate): | [
"\n x = np.array([ 1230., 1230., 1227., 1235., 1217., 1153., 1170.])\n xm = np.array([1230. , 1228.5, 1231. , 1226. , 1185. , 1161.5])\n assert np.array_equal(candidate(x), xm)\n"
] | f_23855976 | calculate the mean of each element in array `x` with the element previous to it | [
"numpy"
] |
|
23,855,976 | def f_23855976(x):
return | x[:-1] + (x[1:] - x[:-1]) / 2 |
import numpy as np
def check(candidate): | [
"\n x = np.array([ 1230., 1230., 1227., 1235., 1217., 1153., 1170.])\n xm = np.array([1230. , 1228.5, 1231. , 1226. , 1185. , 1161.5])\n assert np.array_equal(candidate(x), xm)\n"
] | f_23855976 | get an array of the mean of each two consecutive values in numpy array `x` | [
"numpy"
] |
|
6,375,343 | def f_6375343():
|
return arr | arr = numpy.fromiter(codecs.open('new.txt', encoding='utf-8'), dtype='<U2') |
import numpy
import codecs
import numpy as np
def check(candidate): | [
"\n with open ('new.txt', 'a', encoding='utf-8') as f:\n f.write('ट')\n f.write('ज')\n arr = candidate()\n assert arr[0] == 'टज'\n"
] | f_6375343 | load data containing `utf-8` from file `new.txt` into numpy array `arr` | [
"codecs",
"numpy"
] |
1,547,733 | def f_1547733(l):
|
return l | l = sorted(l, key=itemgetter('time'), reverse=True) |
from operator import itemgetter
def check(candidate): | [
"\n l = [ {'time':33}, {'time':11}, {'time':66} ]\n assert candidate(l) == [{'time':66}, {'time':33}, {'time':11}]\n"
] | f_1547733 | reverse sort list of dicts `l` by value for key `time` | [
"operator"
] |
1,547,733 | def f_1547733(l):
|
return l | l = sorted(l, key=lambda a: a['time'], reverse=True) |
def check(candidate): | [
"\n l = [ {'time':33}, {'time':11}, {'time':66} ]\n assert candidate(l) == [{'time':66}, {'time':33}, {'time':11}]\n"
] | f_1547733 | Sort a list of dictionary `l` based on key `time` in descending order | [] |
37,080,612 | def f_37080612(df):
return | df.loc[df[0].str.contains('(Hel|Just)')] |
import pandas as pd
def check(candidate): | [
"\n df = pd.DataFrame([['Hello', 'World'], ['Just', 'Wanted'], ['To', 'Say'], ['I\\'m', 'Tired']])\n df1 = candidate(df)\n assert df1[0][0] == 'Hello'\n assert df1[0][1] == 'Just'\n"
] | f_37080612 | get rows of dataframe `df` that match regex '(Hel|Just)' | [
"pandas"
] |
|
14,716,342 | def f_14716342(your_string):
return | re.search('\\[(.*)\\]', your_string).group(1) |
import re
def check(candidate): | [
"\n assert candidate('[uranus]') == 'uranus'\n",
"\n assert candidate('hello[world] !') == 'world'\n"
] | f_14716342 | find the string in `your_string` between two special characters "[" and "]" | [
"re"
] |
|
18,684,076 | def f_18684076():
return | [d.strftime('%Y%m%d') for d in pandas.date_range('20130226', '20130302')] |
import pandas
def check(candidate): | [
"\n assert candidate() == ['20130226', '20130227', '20130228', '20130301', '20130302']\n"
] | f_18684076 | create a list of date string in 'yyyymmdd' format with Python Pandas from '20130226' to '20130302' | [
"pandas"
] |
|
1,666,700 | def f_1666700():
return | """The big brown fox is brown""".count('brown') |
def check(candidate): | [
"\n assert candidate() == 2\n"
] | f_1666700 | count number of times string 'brown' occurred in string 'The big brown fox is brown' | [] |
|
18,979,111 | def f_18979111(request_body):
return | json.loads(request_body) |
import json
def check(candidate): | [
"\n x = \"\"\"{\n \"Name\": \"Jennifer Smith\",\n \"Contact Number\": 7867567898,\n \"Email\": \"[email protected]\",\n \"Hobbies\":[\"Reading\", \"Sketching\", \"Horse Riding\"]\n }\"\"\"\n assert candidate(x) == {'Hobbies': ['Reading', 'Sketching', 'Horse Riding'], 'Name': 'Jennifer Smith', 'Email': '[email protected]', 'Contact Number': 7867567898}\n"
] | f_18979111 | decode json string `request_body` to python dict | [
"json"
] |
|
7,243,750 | def f_7243750(url, file_name):
return | urllib.request.urlretrieve(url, file_name) |
import urllib
def check(candidate): | [
"\n file_name = 'g.html'\n candidate('https://asia.nikkei.com/Business/Tech/Semiconductors/U.S.-chip-tool-maker-Synopsys-expands-in-Vietnam-amid-China-tech-war', file_name)\n with open (file_name, 'r') as f:\n lines = f.readlines()\n if len(lines) == 0: assert False\n else: assert True\n"
] | f_7243750 | download the file from url `url` and save it under file `file_name` | [
"urllib"
] |
|
743,806 | def f_743806(text):
return | text.split() |
def check(candidate): | [
"\n assert candidate('The quick brown fox') == ['The', 'quick', 'brown', 'fox']\n",
"\n assert candidate('hello!') == ['hello!']\n",
"\n assert candidate('hello world !') == ['hello', 'world', '!']\n"
] | f_743806 | split string `text` by space | [] |
|
743,806 | def f_743806(text):
return | text.split(',') |
def check(candidate): | [
"\n assert candidate('The quick brown fox') == ['The quick brown fox']\n",
"\n assert candidate('The,quick,brown,fox') == ['The', 'quick', 'brown', 'fox']\n"
] | f_743806 | split string `text` by "," | [] |
|
743,806 | def f_743806(line):
return | line.split() |
def check(candidate): | [
"\n assert candidate('The quick brown fox') == ['The', 'quick', 'brown', 'fox']\n"
] | f_743806 | Split string `line` into a list by whitespace | [] |
|
35,044,115 | def f_35044115(s):
return | [re.sub('(?<!\\d)\\.(?!\\d)', ' ', i) for i in s] |
import re
def check(candidate): | [
"\n assert candidate('h.j.k') == ['h', ' ', 'j', ' ', 'k']\n"
] | f_35044115 | replace dot characters '.' associated with ascii letters in list `s` with space ' ' | [
"re"
] |