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\": \"jen123@gmail.com\",\n \"Hobbies\":[\"Reading\", \"Sketching\", \"Horse Riding\"]\n }\"\"\"\n assert candidate(x) == {'Hobbies': ['Reading', 'Sketching', 'Horse Riding'], 'Name': 'Jennifer Smith', 'Email': 'jen123@gmail.com', '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" ]