prompt
stringlengths 4
181
| completion
stringlengths 2
232
|
|---|---|
heck if list `a` is empty
|
if (not a):
pass
|
heck if list `seq` is empty
|
if (not seq):
pass
|
heck if list `li` is empty
|
if (len(li) == 0):
pass
|
eate a list containing the indices of elements greater than 4 in list `a`
|
[i for i, v in enumerate(a) if v > 4]
|
everse list `yourdata`
|
sorted(yourdata, reverse=True)
|
list of nested dictionaries `yourdata` in reverse based on values associated with each dictionary's key 'subkey'
|
sorted(yourdata, key=lambda d: d.get('key', {}).get('subkey'), reverse=True)
|
list of nested dictionaries `yourdata` in reverse order of 'key' and 'subkey'
|
yourdata.sort(key=lambda e: e['key']['subkey'], reverse=True)
|
emove decimal points in pandas data frame using round
|
df.round()
|
Get data from matplotlib plo
|
gca().get_lines()[n].get_xydata()
|
get the maximum 2 values per row in array `A`
|
A[:, -2:]
|
Get value for username parameter in GET request in Django
|
request.GET.get('username', '')
|
prettyprint ordered dictionary `o`
|
pprint(dict(list(o.items())))
|
Confirm urls in Django properly
|
url('^$', include('sms.urls')),
|
Configure url in django properly
|
url('^', include('sms.urls')),
|
get the tuple in list `a_list` that has the largest item in the second index
|
max_item = max(a_list, key=operator.itemgetter(1))
|
find tuple in list of tuples `a_list` with the largest second eleme
|
max(a_list, key=operator.itemgetter(1))
|
esample series `s` into 3 months bins and sum each b
|
s.resample('3M', how='sum')
|
extract elements at indices (1, 2, 5) from a list `a`
|
[a[i] for i in (1, 2, 5)]
|
filter lines from a text file 'textfile' which contain a word 'apple'
|
[line for line in open('textfile') if 'apple' in line]
|
vert a date string `s` to a datetime objec
|
datetime.datetime.strptime(s, '%Y-%m-%dT%H:%M:%SZ')
|
eading tabdelimited csv file `filename` with pandas on mac
|
pandas.read_csv(filename, sep='\t', lineterminator='\r')
|
eplace only first occurence of string `TEST` from a string `longlongTESTstringTEST`
|
'longlongTESTstringTEST'.replace('TEST', '?', 1)
|
zip file `pdffile` using its basename as directory name
|
archive.write(pdffile, os.path.basename(pdffile))
|
eate a dictionary of pairs from a list of tuples `myListOfTuples`
|
dict(x[1:] for x in reversed(myListOfTuples))
|
btract elements of list `List1` from elements of list `List2`
|
[(x1 - x2) for x1, x2 in zip(List1, List2)]
|
heck if string `string` starts with a number
|
string[0].isdigit()
|
Check if string `strg` starts with any of the elements in list ('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')
|
strg.startswith(('0', '1', '2', '3', '4', '5', '6', '7', '8', '9'))
|
print script's directory
|
print(os.path.dirname(os.path.realpath(__file__)))
|
plit string `text` by the occurrences of regex pattern '(?<=\\?|!|\\.)\\s{0,2}(?=[AZ]|$)'
|
re.split('(?<=\\?|!|\\.)\\s{0,2}(?=[A-Z]|$)', text)
|
Make a scatter plot using unpacked values of list `li`
|
plt.scatter(*zip(*li))
|
earrange tuple of tuples `t`
|
tuple(zip(*t))
|
Get average for every three columns in `df` dataframe
|
df.groupby(np.arange(len(df.columns)) // 3, axis=1).mean()
|
vert a list `L` of ascii values to a string
|
"""""".join(chr(i) for i in L)
|
he number of pairs in dictionary `d` whose value equal to `chosen_value`
|
sum(x == chosen_value for x in list(d.values()))
|
he number of values in `d` dictionary that are predicate to function `some_condition`
|
sum(1 for x in list(d.values()) if some_condition(x))
|
vert double 0.00582811585976 to flo
|
struct.unpack('f', struct.pack('f', 0.00582811585976))
|
vert datetime.date `dt` to utc timestamp
|
timestamp = (dt - datetime(1970, 1, 1)).total_seconds()
|
lumn `m` in panda dataframe `df`
|
df.sort('m')
|
Sort a data `a` in descending order based on the `modified` attribute of elements using lambda functio
|
a = sorted(a, key=lambda x: x.modified, reverse=True)
|
print the truth value of `a`
|
print(bool(a))
|
ename `last` row index label in dataframe `df` to `a`
|
df = df.rename(index={last: 'a'})
|
Fit Kmeans function to a onedimensional array `x` by reshaping it to be a multidimensional array of single value
|
km.fit(x.reshape(-1, 1))
|
Sort a list of strings 'words' such that items starting with 's' come first.
|
sorted(words, key=lambda x: 'a' + x if x.startswith('s') else 'b' + x)
|
pen the login site 'http://somesite.com/adminpanel/index.php' in the browser
|
webbrowser.open('http://somesite.com/adminpanel/index.php')
|
fetch all elements in a dictionary `parent_dict`, falling between two keys 2 and 4
|
dict((k, v) for k, v in parent_dict.items() if 2 < k < 4)
|
fetch all elements in a dictionary 'parent_dict' where the key is between the range of 2 to 4
|
dict((k, v) for k, v in parent_dict.items() if k > 2 and k < 4)
|
wo lists `list1` and `list2` together using lambda functio
|
[list(x) for x in zip(*sorted(zip(list1, list2), key=lambda pair: pair[0]))]
|
get the number of values in list `j` that is greater than 5
|
sum(((i > 5) for i in j))
|
get the number of values in list `j` that is greater than 5
|
len([1 for i in j if (i > 5)])
|
get the number of values in list `j` that is greater than `i`
|
j = np.array(j)
sum((j > i))
|
zip list `a`, `b`, `c` into a list of tuple
|
[(x + tuple(y)) for x, y in zip(zip(a, b), c)]
|
hanging permission of file `path` to `stat.S_IRUSR | stat.S_IRGRP | stat.S_IROTH`
|
os.chmod(path, stat.S_IRUSR | stat.S_IRGRP | stat.S_IROTH)
|
gparse associate zero or more arguments with flag 'file'
|
parser.add_argument('file', nargs='*')
|
get a list of booleans `z` that shows wether the corresponding items in list `x` and `y` are equal
|
z = [(i == j) for i, j in zip(x, y)]
|
eate a list which indicates whether each element in `x` and `y` is identical
|
[(x[i] == y[i]) for i in range(len(x))]
|
Python: Extract numbers from a string
|
[int(s) for s in re.findall('\\b\\d+\\b', "he33llo 42 I'm a 32 string 30")]
|
eate an empty data frame `df2` with index from another data frame `df1`
|
df2 = pd.DataFrame(index=df1.index)
|
pack first and second bytes of byte string `pS` into integer
|
struct.unpack('h', pS[0:2])
|
print list `t` into a tablelike shape
|
print('\n'.join(' '.join(map(str, row)) for row in t))
|
Sort Pandas Dataframe by Date
|
df.sort_values(by='Date')
|
heck if a checkbox is checked in selenium python webdriver
|
driver.find_element_by_name('<check_box_name>').is_selected()
|
determine if checkbox with id '<check_box_id>' is checked in selenium python webdriver
|
driver.find_element_by_id('<check_box_id>').is_selected()
|
eplace `0` with `2` in the list `[0, 1, 0, 3]`
|
[(a if a else 2) for a in [0, 1, 0, 3]]
|
Produce a string that is suitable as Unicode literal from string 'M\\N{AMPERSAND}M\\N{APOSTROPHE}s'
|
'M\\N{AMPERSAND}M\\N{APOSTROPHE}s'.encode().decode('unicode-escape')
|
Parse a unicode string `M\\N{AMPERSAND}M\\N{APOSTROPHE}s`
|
'M\\N{AMPERSAND}M\\N{APOSTROPHE}s'.decode('unicode-escape')
|
vert Unicode codepoint to utf8 hex
|
chr(int('fd9b', 16)).encode('utf-8')
|
e upper case letters to print hex value `value`
|
print('0x%X' % value)
|
get a list `cleaned` that contains all nonempty elements in list `your_list`
|
cleaned = [x for x in your_list if x]
|
eate a slice object using string `string_slice`
|
slice(*[(int(i.strip()) if i else None) for i in string_slice.split(':')])
|
Find all the tags `a` and `div` from Beautiful Soup object `soup`
|
soup.find_all(['a', 'div'])
|
get the name of function `func` as a string
|
print(func.__name__)
|
vert dictionary `adict` into string
|
"""""".join('{}{}'.format(key, val) for key, val in sorted(adict.items()))
|
vert dictionary `adict` into string
|
"""""".join('{}{}'.format(key, val) for key, val in list(adict.items()))
|
py list `old_list` as `new_list`
|
new_list = old_list[:]
|
py list `old_list` as `new_list`
|
new_list = list(old_list)
|
py list `old_list` as `new_list`
|
new_list = copy.copy(old_list)
|
deep copy list `old_list` as `new_list`
|
new_list = copy.deepcopy(old_list)
|
ke a copy of list `old_list`
|
[i for i in old_list]
|
emove frame of legend in plot `plt`
|
plt.legend(frameon=False)
|
Print a emoji from a string `\\ud83d\\ude4f` having surrogate pair
|
"""\\ud83d\\ude4f""".encode('utf-16', 'surrogatepass').decode('utf-16')
|
alling a function named 'myfunction' in the module
|
globals()['myfunction']()
|
Check the status code of url http://www.stackoverflow.com
|
urllib.request.urlopen('http://www.stackoverflow.com').getcode()
|
Check the status code of url www.python.org
|
conn = httplib.HTTPConnection('www.python.org')
conn.request('HEAD', '/')
r1 = conn.getresponse()
print(r1.status, r1.reason)
|
Check the status code of url `url`
|
r = requests.head(url)
return (r.status_code == 200)
|
Checking if website http://www.stackoverflow.com is up
|
print(urllib.request.urlopen('http://www.stackoverflow.com').getcode())
|
Selenium `driver` click a hyperlink with the pattern a[href^='javascript']
|
driver.find_element_by_css_selector("a[href^='javascript']").click()
|
e data frame `df` to file `file_name` using pandas, pytho
|
df.to_pickle(file_name)
|
alculate the mean of columns with same name in dataframe `df`
|
df.groupby(by=df.columns, axis=1).mean()
|
list `bar` by each element's attribute `attrb1` and attribute `attrb2` in reverse order
|
bar.sort(key=lambda x: (x.attrb1, x.attrb2), reverse=True)
|
get alpha value `alpha` of a png image `img`
|
alpha = img.split()[-1]
|
w to get the length of words in a sentence?
|
[len(x) for x in s.split()]
|
BeautifulSoup find tag 'div' with styling 'width=300px;' in HTML string `soup`
|
soup.findAll('div', style='width=300px;')
|
Execute SQL statement `sql` with values of dictionary `myDict` as parameter
|
cursor.execute(sql, list(myDict.values()))
|
Convert CSV file `Result.csv` to Pandas dataframe using separator ' '
|
df.to_csv('Result.csv', index=False, sep=' ')
|
pdate the `globals()` dictionary with the contents of the `vars(args)` dictionary
|
globals().update(vars(args))
|
find all substrings in `mystring` beginning and ending with square bracke
|
re.findall('\\[(.*?)\\]', mystring)
|
Format all floating variables `var1`, `var2`, `var3`, `var1` to print to two decimal places.
|
print('%.2f kg = %.2f lb = %.2f gal = %.2f l' % (var1, var2, var3, var4))
|
Remove all items from a dictionary `d` where the values are less than `1`
|
d = dict((k, v) for k, v in d.items() if v > 0)
|
Filter dictionary `d` to have items with value greater than 0
|
d = {k: v for k, v in list(d.items()) if v > 0}
|
vert a string of date strings `date_stngs ` to datetime objects and put them in a dataframe
|
pd.to_datetime(pd.Series(date_stngs))
|
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