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find the magnitude (length) squared of a vector `vf` field | np.einsum('...j,...j->...', vf, vf) |
equest http url `url` | r = requests.get(url) |
equest http url `url` with parameters `payload` | r = requests.get(url, params=payload) |
post request url `url` with parameters `payload` | r = requests.post(url, data=payload) |
ke an HTTP post request with data `post_data` | post_response = requests.post(url='http://httpbin.org/post', json=post_data) |
django jinja slice list `mylist` by '3:8' | {{(mylist | slice): '3:8'}} |
eate dataframe `df` with content of hdf store file '/home/.../data.h5' with key of 'firstSet' | df1 = pd.read_hdf('/home/.../data.h5', 'firstSet') |
get the largest index of the last occurrence of characters '([{' in string `test_string` | max(test_string.rfind(i) for i in '([{') |
print 'here is your checkmark: ' plus unicode character u'\u2713' | print('here is your checkmark: ' + '\u2713') |
print unicode characters in a string `\u0420\u043e\u0441\u0441\u0438\u044f` | print('\u0420\u043e\u0441\u0441\u0438\u044f') |
pads string '5' on the left with 1 zero | print('{0}'.format('5'.zfill(2))) |
Remove duplicates elements from list `sequences` and sort it in ascending order | sorted(set(itertools.chain.from_iterable(sequences))) |
pandas dataframe `df` column 'a' to l | df['a'].values.tolist() |
Get a list of all values in column `a` in pandas data frame `df` | df['a'].tolist() |
escaping quotes in string | replace('"', '\\"') |
heck if all string elements in list `words` are uppercased | print(all(word[0].isupper() for word in words)) |
emove items from dictionary `myDict` if the item's value `val` is equal to 42 | myDict = {key: val for key, val in list(myDict.items()) if val != 42} |
Remove all items from a dictionary `myDict` whose values are `42` | {key: val for key, val in list(myDict.items()) if val != 42} |
Determine the byte length of a utf8 encoded string `s` | return len(s.encode('utf-8')) |
kill a process with id `process.pid` | os.kill(process.pid, signal.SIGKILL) |
get data of columns with Null values in dataframe `df` | df[pd.isnull(df).any(axis=1)] |
p everything up to and including the character `&` from url `url`, strip the character `=` from the remaining string and concatenate `.html` to the end | url.split('&')[-1].replace('=', '') + '.html' |
Parse a file `sample.xml` using expat parsing in python 3 | parser.ParseFile(open('sample.xml', 'rb')) |
Exit scrip | sys.exit() |
gn value in `group` dynamically to class property `attr` | setattr(self, attr, group) |
decode urlencoded string `some_string` to its character equivale | urllib.parse.unquote(urllib.parse.unquote(some_string)) |
decode a double URL encoded string
'FireShot3%2B%25282%2529.png' to
'FireShot3+(2).png' | urllib.parse.unquote(urllib.parse.unquote('FireShot3%2B%25282%2529.png')) |
hange flask security register url to `/create_account` | app.config['SECURITY_REGISTER_URL'] = '/create_account' |
pen a file `/home/user/test/wsservice/data.pkl` in binary write mode | output = open('/home/user/test/wsservice/data.pkl', 'wb') |
emove the last element in list `a` | del a[(-1)] |
emove the element in list `a` with index 1 | a.pop(1) |
emove the last element in list `a` | a.pop() |
emove the element in list `a` at index `index` | a.pop(index) |
emove the element in list `a` at index `index` | del a[index] |
print a celsius symbol on x axis of a plot `ax` | ax.set_xlabel('Temperature (\u2103)') |
Print a celsius symbol with matplotlib | ax.set_xlabel('Temperature ($^\\circ$C)') |
vert a list of lists `list_of_lists` into a list of strings keeping empty sublists as empty string '' | [''.join(l) for l in list_of_lists] |
get a list of all the duplicate items in dataframe `df` using pand | pd.concat(g for _, g in df.groupby('ID') if len(g) > 1) |
Delete third row in a numpy array `x` | x = numpy.delete(x, 2, axis=1) |
delete first row of array `x` | x = numpy.delete(x, 0, axis=0) |
erge rows from dataframe `df1` with rows from dataframe `df2` and calculate the mean for rows that have the same value of axis 1 | pd.concat((df1, df2), axis=1).mean(axis=1) |
Get the average values from two numpy arrays `old_set` and `new_set` | np.mean(np.array([old_set, new_set]), axis=0) |
Matplotlib change marker size to 500 | scatter(x, y, s=500, color='green', marker='h') |
Create new list `result` by splitting each item in list `words` | result = [item for word in words for item in word.split(',')] |
vert JSON string '20120529T19:30:03.283Z' into a DateTime object using format '%Y%m%dT%H:%M:%S.%fZ' | datetime.datetime.strptime('2012-05-29T19:30:03.283Z', '%Y-%m-%dT%H:%M:%S.%fZ') |
`True` values associated with key 'one' in dictionary `tadas` | sum(item['one'] for item in list(tadas.values())) |
encode a pdf file `pdf_reference.pdf` with `base64` encoding | a = open('pdf_reference.pdf', 'rb').read().encode('base64') |
plit string `a` using newline character '\n' as separator | a.rstrip().split('\n') |
plit a string `a` with new line character | a.split('\n')[:-1] |
eturn http status code 204 from a django view | return HttpResponse(status=204) |
heck if 7 is in `a` | (7 in a) |
heck if 'a' is in list `a` | ('a' in a) |
list `results` by keys value 'year' | sorted(results, key=itemgetter('year')) |
get current url in selenium webdriver `browser` | print(browser.current_url) |
plit string `str` with delimiter '; ' or delimiter ', ' | re.split('; |, ', str) |
escaping characters in a string with pytho | """\\u003Cp\\u003E""".decode('unicode-escape') |
vert date string `s` in format pattern '%d/%m/%Y' into a timestamp | time.mktime(datetime.datetime.strptime(s, '%d/%m/%Y').timetuple()) |
vert string '01/12/2011' to an integer timestamp | int(datetime.datetime.strptime('01/12/2011', '%d/%m/%Y').strftime('%s')) |
get http header of the key 'yourheadername' in flask | request.headers['your-header-name'] |
elect records of dataframe `df` where the sum of column 'X' for each value in column 'User' is 0 | df.groupby('User')['X'].filter(lambda x: x.sum() == 0) |
Get data of dataframe `df` where the sum of column 'X' grouped by column 'User' is equal to 0 | df.loc[df.groupby('User')['X'].transform(sum) == 0] |
Get data from dataframe `df` where column 'X' is equal to 0 | df.groupby('User')['X'].transform(sum) == 0 |
w do I find an element that contains specific text in Selenium Webdriver (Python)? | driver.find_elements_by_xpath("//*[contains(text(), 'My Button')]") |
vert pandas group by object to multiindexed dataframe with indices 'Name' and 'Destination' | df.set_index(['Name', 'Destination']) |
alesce nonwordcharacters in string `a` | print(re.sub('(\\W)\\1+', '\\1', a)) |
pen a file $file under Unix | os.system('start "$file"') |
Convert a Unicode string `title` to a 'ascii' string | unicodedata.normalize('NFKD', title).encode('ascii', 'ignore') |
Convert a Unicode string `a` to a 'ascii' string | a.encode('ascii', 'ignore') |
eate a list `files` containing all files in directory '.' that starts with numbers between 0 and 9 and ends with the extension '.jpg' | files = [f for f in os.listdir('.') if re.match('[0-9]+.*\\.jpg', f)] |
dding a 1d array `[1, 2, 3, 4, 5, 6, 7, 8, 9]` to a 3d array `np.zeros((6, 9, 20))` | np.zeros((6, 9, 20)) + np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])[(None), :, (None)] |
dd array of shape `(6, 9, 20)` to array `[1, 2, 3, 4, 5, 6, 7, 8, 9]` | np.zeros((6, 9, 20)) + np.array([1, 2, 3, 4, 5, 6, 7, 8, 9]).reshape((1, 9, 1)) |
w can I launch an instance of an application using Python? | os.system('start excel.exe <path/to/file>') |
get the list with the highest sum value in list `x` | print(max(x, key=sum)) |
m the length of lists in list `x` that are more than 1 item in length | sum(len(y) for y in x if len(y) > 1) |
Enclose numbers in quotes in a string `This is number 1 and this is number 22` | re.sub('(\\d+)', '"\\1"', 'This is number 1 and this is number 22') |
ltiply the columns of sparse matrix `m` by array `a` then multiply the rows of the resulting matrix by array `a` | numpy.dot(numpy.dot(a, m), a) |
Django check if an object with criteria `name` equal to 'name' and criteria `title` equal to 'title' exists in model `Entry` | Entry.objects.filter(name='name', title='title').exists() |
a nested list by the inverse of element 2, then by element 1 | sorted(l, key=lambda x: (-int(x[1]), x[0])) |
get domain/host name from request object in Django | request.META['HTTP_HOST'] |
get a string `randomkey123xyz987` between two substrings in a string `api('randomkey123xyz987', 'key', 'text')` using regex | re.findall("api\\('(.*?)'", "api('randomkey123xyz987', 'key', 'text')") |
voke perl script './uireplace.pl' using perl interpeter '/usr/bin/perl' and send argument `var` to | subprocess.call(['/usr/bin/perl', './uireplace.pl', var]) |
print list of items `myList` | print('\n'.join(str(p) for p in myList)) |
pdate the dictionary `mydic` with dynamic keys `i` and values with key 'name' from dictionary `o` | mydic.update({i: o['name']}) |
plit a `utf8` encoded string `stru` into a list of character | list(stru.decode('utf-8')) |
vert utf8 with bom string `s` to utf8 with no bom `u` | u = s.decode('utf-8-sig') |
Filter model 'Entry' where 'id' is not equal to 3 in Django | Entry.objects.filter(~Q(id=3)) |
lookup an attribute in any scope by name 'range' | getattr(__builtins__, 'range') |
estart a computer after `900` seconds using subproce | subprocess.call(['shutdown', '/r', '/t', '900']) |
hutdown a computer using subproce | subprocess.call(['shutdown', '/s']) |
bort a computer shutdown using subproce | subprocess.call(['shutdown', '/a ']) |
logoff computer having windows operating system using pytho | subprocess.call(['shutdown', '/l ']) |
hutdown and restart a computer running windows from scrip | subprocess.call(['shutdown', '/r']) |
erase the contents of a file `filename` | open('filename', 'w').close() |
w to erase the file contents of text file in Python? | open('file.txt', 'w').close() |
vert dataframe `df` to list of dictionaries including the index value | df.to_dict('index') |
Create list of dictionaries from pandas dataframe `df` | df.to_dict('records') |
Group a pandas data frame by monthly frequenct `M` using groupby | df.groupby(pd.TimeGrouper(freq='M')) |
divide the members of a list `conversions` by the corresponding members of another list `trials` | [(c / t) for c, t in zip(conversions, trials)] |
dict `data` by value | sorted(data, key=data.get) |
Sort a dictionary `data` by its value | sorted(data.values()) |