code_tokens
stringlengths 60
3.94k
| label
int64 0
1
| doc
stringlengths 16
98
| docstring_tokens
stringlengths 0
1.41k
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stringlengths 13
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| code
stringlengths 87
6.4k
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|---|---|---|---|---|---|
def url ( self ) : with switch_window ( self . _browser , self . name ) : return self . _browser . url
| 0 |
python get url in browser
|
The url of this window
|
cosqa-train-500
|
def url(self):
""" The url of this window """
with switch_window(self._browser, self.name):
return self._browser.url
|
def euclidean ( c1 , c2 ) : diffs = ( ( i - j ) for i , j in zip ( c1 , c2 ) ) return sum ( x * x for x in diffs )
| 0 |
euclidean distance of two lists python
|
Square of the euclidean distance
|
cosqa-train-501
|
def euclidean(c1, c2):
"""Square of the euclidean distance"""
diffs = ((i - j) for i, j in zip(c1, c2))
return sum(x * x for x in diffs)
|
def get_free_memory_win ( ) : stat = MEMORYSTATUSEX ( ) ctypes . windll . kernel32 . GlobalMemoryStatusEx ( ctypes . byref ( stat ) ) return int ( stat . ullAvailPhys / 1024 / 1024 )
| 0 |
python get used memory info
|
Return current free memory on the machine for windows .
|
cosqa-train-502
|
def get_free_memory_win():
"""Return current free memory on the machine for windows.
Warning : this script is really not robust
Return in MB unit
"""
stat = MEMORYSTATUSEX()
ctypes.windll.kernel32.GlobalMemoryStatusEx(ctypes.byref(stat))
return int(stat.ullAvailPhys / 1024 / 1024)
|
def xpathEvalExpression ( self , str ) : ret = libxml2mod . xmlXPathEvalExpression ( str , self . _o ) if ret is None : raise xpathError ( 'xmlXPathEvalExpression() failed' ) return xpathObjectRet ( ret )
| 0 |
evaluate expression python xpath
|
Evaluate the XPath expression in the given context .
|
cosqa-train-503
|
def xpathEvalExpression(self, str):
"""Evaluate the XPath expression in the given context. """
ret = libxml2mod.xmlXPathEvalExpression(str, self._o)
if ret is None:raise xpathError('xmlXPathEvalExpression() failed')
return xpathObjectRet(ret)
|
def EnumValueName ( self , enum , value ) : return self . enum_types_by_name [ enum ] . values_by_number [ value ] . name
| 0 |
python get value from enum
|
Returns the string name of an enum value .
|
cosqa-train-504
|
def EnumValueName(self, enum, value):
"""Returns the string name of an enum value.
This is just a small helper method to simplify a common operation.
Args:
enum: string name of the Enum.
value: int, value of the enum.
Returns:
string name of the enum value.
Raises:
KeyError if either the Enum doesn't exist or the value is not a valid
value for the enum.
"""
return self.enum_types_by_name[enum].values_by_number[value].name
|
def is_in ( self , point_x , point_y ) : point_array = array ( ( ( point_x , point_y ) , ) ) vertices = array ( self . points ) winding = self . inside_rule == "winding" result = points_in_polygon ( point_array , vertices , winding ) return result [ 0 ]
| 1 |
evaluate if a set of points are inside of a polygon python
|
Test if a point is within this polygonal region
|
cosqa-train-505
|
def is_in(self, point_x, point_y):
""" Test if a point is within this polygonal region """
point_array = array(((point_x, point_y),))
vertices = array(self.points)
winding = self.inside_rule == "winding"
result = points_in_polygon(point_array, vertices, winding)
return result[0]
|
def extent_count ( self ) : self . open ( ) count = lvm_vg_get_extent_count ( self . handle ) self . close ( ) return count
| 0 |
python get volume size
|
Returns the volume group extent count .
|
cosqa-train-506
|
def extent_count(self):
"""
Returns the volume group extent count.
"""
self.open()
count = lvm_vg_get_extent_count(self.handle)
self.close()
return count
|
def numpy_aware_eq ( a , b ) : if isinstance ( a , np . ndarray ) or isinstance ( b , np . ndarray ) : return np . array_equal ( a , b ) if ( ( isinstance ( a , Iterable ) and isinstance ( b , Iterable ) ) and not isinstance ( a , str ) and not isinstance ( b , str ) ) : if len ( a ) != len ( b ) : return False return all ( numpy_aware_eq ( x , y ) for x , y in zip ( a , b ) ) return a == b
| 0 |
evaluate if two ndarrays are equal python
|
Return whether two objects are equal via recursion using : func : numpy . array_equal for comparing numpy arays .
|
cosqa-train-507
|
def numpy_aware_eq(a, b):
"""Return whether two objects are equal via recursion, using
:func:`numpy.array_equal` for comparing numpy arays.
"""
if isinstance(a, np.ndarray) or isinstance(b, np.ndarray):
return np.array_equal(a, b)
if ((isinstance(a, Iterable) and isinstance(b, Iterable)) and
not isinstance(a, str) and not isinstance(b, str)):
if len(a) != len(b):
return False
return all(numpy_aware_eq(x, y) for x, y in zip(a, b))
return a == b
|
def title ( self ) : with switch_window ( self . _browser , self . name ) : return self . _browser . title
| 0 |
python get window title of selected window
|
The title of this window
|
cosqa-train-508
|
def title(self):
""" The title of this window """
with switch_window(self._browser, self.name):
return self._browser.title
|
def visit_BoolOp ( self , node ) : return sum ( ( self . visit ( value ) for value in node . values ) , [ ] )
| 0 |
evaluting boolean values in python function
|
Return type may come from any boolop operand .
|
cosqa-train-509
|
def visit_BoolOp(self, node):
""" Return type may come from any boolop operand. """
return sum((self.visit(value) for value in node.values), [])
|
def __get_xml_text ( root ) : txt = "" for e in root . childNodes : if ( e . nodeType == e . TEXT_NODE ) : txt += e . data return txt
| 0 |
python get xml text
|
Return the text for the given root node ( xml . dom . minidom ) .
|
cosqa-train-510
|
def __get_xml_text(root):
""" Return the text for the given root node (xml.dom.minidom). """
txt = ""
for e in root.childNodes:
if (e.nodeType == e.TEXT_NODE):
txt += e.data
return txt
|
def runcode ( code ) : for line in code : print ( '# ' + line ) exec ( line , globals ( ) ) print ( '# return ans' ) return ans
| 0 |
execute code line by line in python
|
Run the given code line by line with printing as list of lines and return variable ans .
|
cosqa-train-511
|
def runcode(code):
"""Run the given code line by line with printing, as list of lines, and return variable 'ans'."""
for line in code:
print('# '+line)
exec(line,globals())
print('# return ans')
return ans
|
def fetch_event ( urls ) : rs = ( grequests . get ( u ) for u in urls ) return [ content . json ( ) for content in grequests . map ( rs ) ]
| 0 |
python gevent pool paralle
|
This parallel fetcher uses gevent one uses gevent
|
cosqa-train-512
|
def fetch_event(urls):
"""
This parallel fetcher uses gevent one uses gevent
"""
rs = (grequests.get(u) for u in urls)
return [content.json() for content in grequests.map(rs)]
|
def get_order ( self , codes ) : return sorted ( codes , key = lambda e : [ self . ev2idx . get ( e ) ] )
| 0 |
execute order based on value python
|
Return evidence codes in order shown in code2name .
|
cosqa-train-513
|
def get_order(self, codes):
"""Return evidence codes in order shown in code2name."""
return sorted(codes, key=lambda e: [self.ev2idx.get(e)])
|
def equal ( list1 , list2 ) : return [ item1 == item2 for item1 , item2 in broadcast_zip ( list1 , list2 ) ]
| 0 |
python given an array of boolean to decide values of another array
|
takes flags returns indexes of True values
|
cosqa-train-514
|
def equal(list1, list2):
""" takes flags returns indexes of True values """
return [item1 == item2 for item1, item2 in broadcast_zip(list1, list2)]
|
def select ( self , cmd , * args , * * kwargs ) : self . cursor . execute ( cmd , * args , * * kwargs ) return self . cursor . fetchall ( )
| 0 |
execute(query, arg) cursor python
|
Execute the SQL command and return the data rows as tuples
|
cosqa-train-515
|
def select(self, cmd, *args, **kwargs):
""" Execute the SQL command and return the data rows as tuples
"""
self.cursor.execute(cmd, *args, **kwargs)
return self.cursor.fetchall()
|
def go_to_parent_directory ( self ) : self . chdir ( osp . abspath ( osp . join ( getcwd_or_home ( ) , os . pardir ) ) )
| 0 |
python go to parent folder
|
Go to parent directory
|
cosqa-train-516
|
def go_to_parent_directory(self):
"""Go to parent directory"""
self.chdir(osp.abspath(osp.join(getcwd_or_home(), os.pardir)))
|
def _convert_to_float_if_possible ( s ) : try : ret = float ( s ) except ( ValueError , TypeError ) : ret = s return ret
| 0 |
expected string got float instead python
|
A small helper function to convert a string to a numeric value if appropriate
|
cosqa-train-517
|
def _convert_to_float_if_possible(s):
"""
A small helper function to convert a string to a numeric value
if appropriate
:param s: the string to be converted
:type s: str
"""
try:
ret = float(s)
except (ValueError, TypeError):
ret = s
return ret
|
def _top ( self ) : # Goto top of the list self . top . body . focus_position = 2 if self . compact is False else 0 self . top . keypress ( self . size , "" )
| 0 |
python go to the bottom of a listbox
|
g
|
cosqa-train-518
|
def _top(self):
""" g """
# Goto top of the list
self.top.body.focus_position = 2 if self.compact is False else 0
self.top.keypress(self.size, "")
|
def exp_fit_fun ( x , a , tau , c ) : # pylint: disable=invalid-name return a * np . exp ( - x / tau ) + c
| 0 |
exponential decay python fit
|
Function used to fit the exponential decay .
|
cosqa-train-519
|
def exp_fit_fun(x, a, tau, c):
"""Function used to fit the exponential decay."""
# pylint: disable=invalid-name
return a * np.exp(-x / tau) + c
|
def to_gtp ( coord ) : if coord is None : return 'pass' y , x = coord return '{}{}' . format ( _GTP_COLUMNS [ x ] , go . N - y )
| 0 |
python gps coordinates to x, y, z
|
Converts from a Minigo coordinate to a GTP coordinate .
|
cosqa-train-520
|
def to_gtp(coord):
"""Converts from a Minigo coordinate to a GTP coordinate."""
if coord is None:
return 'pass'
y, x = coord
return '{}{}'.format(_GTP_COLUMNS[x], go.N - y)
|
def nb_to_python ( nb_path ) : exporter = python . PythonExporter ( ) output , resources = exporter . from_filename ( nb_path ) return output
| 1 |
export ipynb as python file
|
convert notebook to python script
|
cosqa-train-521
|
def nb_to_python(nb_path):
"""convert notebook to python script"""
exporter = python.PythonExporter()
output, resources = exporter.from_filename(nb_path)
return output
|
def searchlast ( self , n = 10 ) : solutions = deque ( [ ] , n ) for solution in self : solutions . append ( solution ) return solutions
| 0 |
python grab last n elments
|
Return the last n results ( or possibly less if not found ) . Note that the last results are not necessarily the best ones! Depending on the search type .
|
cosqa-train-522
|
def searchlast(self,n=10):
"""Return the last n results (or possibly less if not found). Note that the last results are not necessarily the best ones! Depending on the search type."""
solutions = deque([], n)
for solution in self:
solutions.append(solution)
return solutions
|
def to_json ( df , state_index , color_index , fills ) : records = { } for i , row in df . iterrows ( ) : records [ row [ state_index ] ] = { "fillKey" : row [ color_index ] } return { "data" : records , "fills" : fills }
| 0 |
expose data in json format in python using data frame
|
Transforms dataframe to json response
|
cosqa-train-523
|
def to_json(df, state_index, color_index, fills):
"""Transforms dataframe to json response"""
records = {}
for i, row in df.iterrows():
records[row[state_index]] = {
"fillKey": row[color_index]
}
return {
"data": records,
"fills": fills
}
|
def _text_to_graphiz ( self , text ) : dot = Source ( text , format = 'svg' ) return dot . pipe ( ) . decode ( 'utf-8' )
| 0 |
python graphviz format png
|
create a graphviz graph from text
|
cosqa-train-524
|
def _text_to_graphiz(self, text):
"""create a graphviz graph from text"""
dot = Source(text, format='svg')
return dot.pipe().decode('utf-8')
|
def get_colors ( img ) : w , h = img . size return [ color [ : 3 ] for count , color in img . convert ( 'RGB' ) . getcolors ( w * h ) ]
| 0 |
extract color components of an image in python
|
Returns a list of all the image s colors .
|
cosqa-train-525
|
def get_colors(img):
"""
Returns a list of all the image's colors.
"""
w, h = img.size
return [color[:3] for count, color in img.convert('RGB').getcolors(w * h)]
|
def _round_half_hour ( record ) : k = record . datetime + timedelta ( minutes = - ( record . datetime . minute % 30 ) ) return datetime ( k . year , k . month , k . day , k . hour , k . minute , 0 )
| 0 |
python group minute data into half hour
|
Round a time DOWN to half nearest half - hour .
|
cosqa-train-526
|
def _round_half_hour(record):
"""
Round a time DOWN to half nearest half-hour.
"""
k = record.datetime + timedelta(minutes=-(record.datetime.minute % 30))
return datetime(k.year, k.month, k.day, k.hour, k.minute, 0)
|
def get_X0 ( X ) : if pandas_available and isinstance ( X , pd . DataFrame ) : assert len ( X ) == 1 x = np . array ( X . iloc [ 0 ] ) else : x , = X return x
| 0 |
extract first array in python
|
Return zero - th element of a one - element data container .
|
cosqa-train-527
|
def get_X0(X):
""" Return zero-th element of a one-element data container.
"""
if pandas_available and isinstance(X, pd.DataFrame):
assert len(X) == 1
x = np.array(X.iloc[0])
else:
x, = X
return x
|
def threads_init ( gtk = True ) : # enable X11 multithreading x11 . XInitThreads ( ) if gtk : from gtk . gdk import threads_init threads_init ( )
| 0 |
python gtk starting separate thread but doesn't run
|
Enables multithreading support in Xlib and PyGTK . See the module docstring for more info . : Parameters : gtk : bool May be set to False to skip the PyGTK module .
|
cosqa-train-528
|
def threads_init(gtk=True):
"""Enables multithreading support in Xlib and PyGTK.
See the module docstring for more info.
:Parameters:
gtk : bool
May be set to False to skip the PyGTK module.
"""
# enable X11 multithreading
x11.XInitThreads()
if gtk:
from gtk.gdk import threads_init
threads_init()
|
def security ( self ) : return { k : v for i in self . pdf . resolvedObjects . items ( ) for k , v in i [ 1 ] . items ( ) }
| 0 |
extract pdf fields in python
|
Print security object information for a pdf document
|
cosqa-train-529
|
def security(self):
"""Print security object information for a pdf document"""
return {k: v for i in self.pdf.resolvedObjects.items() for k, v in i[1].items()}
|
def enable_gtk3 ( self , app = None ) : from pydev_ipython . inputhookgtk3 import create_inputhook_gtk3 self . set_inputhook ( create_inputhook_gtk3 ( self . _stdin_file ) ) self . _current_gui = GUI_GTK
| 0 |
python gtk3 not work on window
|
Enable event loop integration with Gtk3 ( gir bindings ) .
|
cosqa-train-530
|
def enable_gtk3(self, app=None):
"""Enable event loop integration with Gtk3 (gir bindings).
Parameters
----------
app : ignored
Ignored, it's only a placeholder to keep the call signature of all
gui activation methods consistent, which simplifies the logic of
supporting magics.
Notes
-----
This methods sets the PyOS_InputHook for Gtk3, which allows
the Gtk3 to integrate with terminal based applications like
IPython.
"""
from pydev_ipython.inputhookgtk3 import create_inputhook_gtk3
self.set_inputhook(create_inputhook_gtk3(self._stdin_file))
self._current_gui = GUI_GTK
|
def dot ( a , b ) : b = numpy . asarray ( b ) return numpy . dot ( a , b . reshape ( b . shape [ 0 ] , - 1 ) ) . reshape ( a . shape [ : - 1 ] + b . shape [ 1 : ] )
| 0 |
fast matrix dot products in python
|
Take arrays a and b and form the dot product between the last axis of a and the first of b .
|
cosqa-train-531
|
def dot(a, b):
"""Take arrays `a` and `b` and form the dot product between the last axis
of `a` and the first of `b`.
"""
b = numpy.asarray(b)
return numpy.dot(a, b.reshape(b.shape[0], -1)).reshape(a.shape[:-1] + b.shape[1:])
|
def guess_encoding ( text , default = DEFAULT_ENCODING ) : result = chardet . detect ( text ) return normalize_result ( result , default = default )
| 0 |
python guess text encoding
|
Guess string encoding .
|
cosqa-train-532
|
def guess_encoding(text, default=DEFAULT_ENCODING):
"""Guess string encoding.
Given a piece of text, apply character encoding detection to
guess the appropriate encoding of the text.
"""
result = chardet.detect(text)
return normalize_result(result, default=default)
|
def check_precomputed_distance_matrix ( X ) : tmp = X . copy ( ) tmp [ np . isinf ( tmp ) ] = 1 check_array ( tmp )
| 0 |
fast way of setting certain elements in array to zero python
|
Perform check_array ( X ) after removing infinite values ( numpy . inf ) from the given distance matrix .
|
cosqa-train-533
|
def check_precomputed_distance_matrix(X):
"""Perform check_array(X) after removing infinite values (numpy.inf) from the given distance matrix.
"""
tmp = X.copy()
tmp[np.isinf(tmp)] = 1
check_array(tmp)
|
def __gzip ( filename ) : zipname = filename + '.gz' file_pointer = open ( filename , 'rb' ) zip_pointer = gzip . open ( zipname , 'wb' ) zip_pointer . writelines ( file_pointer ) file_pointer . close ( ) zip_pointer . close ( ) return zipname
| 0 |
python gzip compress a file
|
Compress a file returning the new filename ( . gz )
|
cosqa-train-534
|
def __gzip(filename):
""" Compress a file returning the new filename (.gz)
"""
zipname = filename + '.gz'
file_pointer = open(filename,'rb')
zip_pointer = gzip.open(zipname,'wb')
zip_pointer.writelines(file_pointer)
file_pointer.close()
zip_pointer.close()
return zipname
|
def forceupdate ( self , * args , * * kw ) : self . _update ( False , self . _ON_DUP_OVERWRITE , * args , * * kw )
| 1 |
faster update bulk in python mysql
|
Like a bulk : meth : forceput .
|
cosqa-train-535
|
def forceupdate(self, *args, **kw):
"""Like a bulk :meth:`forceput`."""
self._update(False, self._ON_DUP_OVERWRITE, *args, **kw)
|
def create_h5py_with_large_cache ( filename , cache_size_mb ) : # h5py does not allow to control the cache size from the high level # we employ the workaround # sources: #http://stackoverflow.com/questions/14653259/how-to-set-cache-settings-while-using-h5py-high-level-interface #https://groups.google.com/forum/#!msg/h5py/RVx1ZB6LpE4/KH57vq5yw2AJ propfaid = h5py . h5p . create ( h5py . h5p . FILE_ACCESS ) settings = list ( propfaid . get_cache ( ) ) settings [ 2 ] = 1024 * 1024 * cache_size_mb propfaid . set_cache ( * settings ) fid = h5py . h5f . create ( filename , flags = h5py . h5f . ACC_EXCL , fapl = propfaid ) fin = h5py . File ( fid ) return fin
| 0 |
python h5 file how to decrease size
|
Allows to open the hdf5 file with specified cache size
|
cosqa-train-536
|
def create_h5py_with_large_cache(filename, cache_size_mb):
"""
Allows to open the hdf5 file with specified cache size
"""
# h5py does not allow to control the cache size from the high level
# we employ the workaround
# sources:
#http://stackoverflow.com/questions/14653259/how-to-set-cache-settings-while-using-h5py-high-level-interface
#https://groups.google.com/forum/#!msg/h5py/RVx1ZB6LpE4/KH57vq5yw2AJ
propfaid = h5py.h5p.create(h5py.h5p.FILE_ACCESS)
settings = list(propfaid.get_cache())
settings[2] = 1024 * 1024 * cache_size_mb
propfaid.set_cache(*settings)
fid = h5py.h5f.create(filename, flags=h5py.h5f.ACC_EXCL, fapl=propfaid)
fin = h5py.File(fid)
return fin
|
def rfft2d_freqs ( h , w ) : fy = np . fft . fftfreq ( h ) [ : , None ] # when we have an odd input dimension we need to keep one additional # frequency and later cut off 1 pixel if w % 2 == 1 : fx = np . fft . fftfreq ( w ) [ : w // 2 + 2 ] else : fx = np . fft . fftfreq ( w ) [ : w // 2 + 1 ] return np . sqrt ( fx * fx + fy * fy )
| 0 |
fft 2d spectrum python
|
Computes 2D spectrum frequencies .
|
cosqa-train-537
|
def rfft2d_freqs(h, w):
"""Computes 2D spectrum frequencies."""
fy = np.fft.fftfreq(h)[:, None]
# when we have an odd input dimension we need to keep one additional
# frequency and later cut off 1 pixel
if w % 2 == 1:
fx = np.fft.fftfreq(w)[: w // 2 + 2]
else:
fx = np.fft.fftfreq(w)[: w // 2 + 1]
return np.sqrt(fx * fx + fy * fy)
|
def md5_hash_file ( fh ) : md5 = hashlib . md5 ( ) while True : data = fh . read ( 8192 ) if not data : break md5 . update ( data ) return md5 . hexdigest ( )
| 0 |
python h5file force read into memory
|
Return the md5 hash of the given file - object
|
cosqa-train-538
|
def md5_hash_file(fh):
"""Return the md5 hash of the given file-object"""
md5 = hashlib.md5()
while True:
data = fh.read(8192)
if not data:
break
md5.update(data)
return md5.hexdigest()
|
def software_fibonacci ( n ) : a , b = 0 , 1 for i in range ( n ) : a , b = b , a + b return a
| 0 |
fibonacci with function for in python
|
a normal old python function to return the Nth fibonacci number .
|
cosqa-train-539
|
def software_fibonacci(n):
""" a normal old python function to return the Nth fibonacci number. """
a, b = 0, 1
for i in range(n):
a, b = b, a + b
return a
|
def h5ToDict ( h5 , readH5pyDataset = True ) : h = h5py . File ( h5 , "r" ) ret = unwrapArray ( h , recursive = True , readH5pyDataset = readH5pyDataset ) if readH5pyDataset : h . close ( ) return ret
| 0 |
python h5py read data
|
Read a hdf5 file into a dictionary
|
cosqa-train-540
|
def h5ToDict(h5, readH5pyDataset=True):
""" Read a hdf5 file into a dictionary """
h = h5py.File(h5, "r")
ret = unwrapArray(h, recursive=True, readH5pyDataset=readH5pyDataset)
if readH5pyDataset: h.close()
return ret
|
def current_zipfile ( ) : if zipfile . is_zipfile ( sys . argv [ 0 ] ) : fd = open ( sys . argv [ 0 ] , "rb" ) return zipfile . ZipFile ( fd )
| 0 |
file is not a zip file python
|
A function to vend the current zipfile if any
|
cosqa-train-541
|
def current_zipfile():
"""A function to vend the current zipfile, if any"""
if zipfile.is_zipfile(sys.argv[0]):
fd = open(sys.argv[0], "rb")
return zipfile.ZipFile(fd)
|
def __unixify ( self , s ) : return os . path . normpath ( s ) . replace ( os . sep , "/" )
| 0 |
python handling windows paths in strings
|
stupid windows . converts the backslash to forwardslash for consistency
|
cosqa-train-542
|
def __unixify(self, s):
""" stupid windows. converts the backslash to forwardslash for consistency """
return os.path.normpath(s).replace(os.sep, "/")
|
def __init__ ( self , encoding = 'utf-8' ) : super ( StdinInputReader , self ) . __init__ ( sys . stdin , encoding = encoding )
| 0 |
fileinput python specify encoding
|
Initializes an stdin input reader .
|
cosqa-train-543
|
def __init__(self, encoding='utf-8'):
"""Initializes an stdin input reader.
Args:
encoding (Optional[str]): input encoding.
"""
super(StdinInputReader, self).__init__(sys.stdin, encoding=encoding)
|
def _add_hash ( source ) : source = '\n' . join ( '# ' + line . rstrip ( ) for line in source . splitlines ( ) ) return source
| 0 |
python hash bang line
|
Add a leading hash # at the beginning of every line in the source .
|
cosqa-train-544
|
def _add_hash(source):
"""Add a leading hash '#' at the beginning of every line in the source."""
source = '\n'.join('# ' + line.rstrip()
for line in source.splitlines())
return source
|
def apply ( f , obj , * args , * * kwargs ) : return vectorize ( f ) ( obj , * args , * * kwargs )
| 0 |
fille a vector in a parallelize way python
|
Apply a function in parallel to each element of the input
|
cosqa-train-545
|
def apply(f, obj, *args, **kwargs):
"""Apply a function in parallel to each element of the input"""
return vectorize(f)(obj, *args, **kwargs)
|
def double_sha256 ( data ) : return bytes_as_revhex ( hashlib . sha256 ( hashlib . sha256 ( data ) . digest ( ) ) . digest ( ) )
| 0 |
python hashlib return string
|
A standard compound hash .
|
cosqa-train-546
|
def double_sha256(data):
"""A standard compound hash."""
return bytes_as_revhex(hashlib.sha256(hashlib.sha256(data).digest()).digest())
|
def drop_empty ( rows ) : return zip ( * [ col for col in zip ( * rows ) if bool ( filter ( bool , col [ 1 : ] ) ) ] )
| 0 |
filter empty rows python
|
Transpose the columns into rows remove all of the rows that are empty after the first cell then transpose back . The result is that columns that have a header but no data in the body are removed assuming the header is the first row .
|
cosqa-train-547
|
def drop_empty(rows):
"""Transpose the columns into rows, remove all of the rows that are empty after the first cell, then
transpose back. The result is that columns that have a header but no data in the body are removed, assuming
the header is the first row. """
return zip(*[col for col in zip(*rows) if bool(filter(bool, col[1:]))])
|
def heappush_max ( heap , item ) : heap . append ( item ) _siftdown_max ( heap , 0 , len ( heap ) - 1 )
| 0 |
python heap limit length
|
Push item onto heap maintaining the heap invariant .
|
cosqa-train-548
|
def heappush_max(heap, item):
"""Push item onto heap, maintaining the heap invariant."""
heap.append(item)
_siftdown_max(heap, 0, len(heap) - 1)
|
def split_addresses ( email_string_list ) : return [ f for f in [ s . strip ( ) for s in email_string_list . split ( "," ) ] if f ]
| 0 |
filter list using regex email example python
|
Converts a string containing comma separated email addresses into a list of email addresses .
|
cosqa-train-549
|
def split_addresses(email_string_list):
"""
Converts a string containing comma separated email addresses
into a list of email addresses.
"""
return [f for f in [s.strip() for s in email_string_list.split(",")] if f]
|
def _heappush_max ( heap , item ) : heap . append ( item ) heapq . _siftdown_max ( heap , 0 , len ( heap ) - 1 )
| 0 |
python heap sort stackoverflow
|
why is this not in heapq
|
cosqa-train-550
|
def _heappush_max(heap, item):
""" why is this not in heapq """
heap.append(item)
heapq._siftdown_max(heap, 0, len(heap) - 1)
|
def _remove_keywords ( d ) : return { k : v for k , v in iteritems ( d ) if k not in RESERVED }
| 0 |
filter stopwords from a dictionary python
|
copy the dict filter_keywords
|
cosqa-train-551
|
def _remove_keywords(d):
"""
copy the dict, filter_keywords
Parameters
----------
d : dict
"""
return { k:v for k, v in iteritems(d) if k not in RESERVED }
|
def _heapify_max ( x ) : n = len ( x ) for i in reversed ( range ( n // 2 ) ) : _siftup_max ( x , i )
| 0 |
python heapify time complexity
|
Transform list into a maxheap in - place in O ( len ( x )) time .
|
cosqa-train-552
|
def _heapify_max(x):
"""Transform list into a maxheap, in-place, in O(len(x)) time."""
n = len(x)
for i in reversed(range(n//2)):
_siftup_max(x, i)
|
def uniq ( seq ) : seen = set ( ) return [ x for x in seq if str ( x ) not in seen and not seen . add ( str ( x ) ) ]
| 0 |
filter uniques from python list
|
Return a copy of seq without duplicates .
|
cosqa-train-553
|
def uniq(seq):
""" Return a copy of seq without duplicates. """
seen = set()
return [x for x in seq if str(x) not in seen and not seen.add(str(x))]
|
def pop ( h ) : n = h . size ( ) - 1 h . swap ( 0 , n ) down ( h , 0 , n ) return h . pop ( )
| 0 |
python heapq get last element
|
Pop the heap value from the heap .
|
cosqa-train-554
|
def pop(h):
"""Pop the heap value from the heap."""
n = h.size() - 1
h.swap(0, n)
down(h, 0, n)
return h.pop()
|
def replace_all ( filepath , searchExp , replaceExp ) : for line in fileinput . input ( filepath , inplace = 1 ) : if searchExp in line : line = line . replace ( searchExp , replaceExp ) sys . stdout . write ( line )
| 0 |
find/replace in a file python
|
Replace all the ocurrences ( in a file ) of a string with another value .
|
cosqa-train-555
|
def replace_all(filepath, searchExp, replaceExp):
"""
Replace all the ocurrences (in a file) of a string with another value.
"""
for line in fileinput.input(filepath, inplace=1):
if searchExp in line:
line = line.replace(searchExp, replaceExp)
sys.stdout.write(line)
|
def __call__ ( self , kind : Optional [ str ] = None , * * kwargs ) : return plot ( self . histogram , kind = kind , * * kwargs )
| 0 |
python histogram matplotlib kwargs
|
Use the plotter as callable .
|
cosqa-train-556
|
def __call__(self, kind: Optional[str] = None, **kwargs):
"""Use the plotter as callable."""
return plot(self.histogram, kind=kind, **kwargs)
|
def ci ( a , which = 95 , axis = None ) : p = 50 - which / 2 , 50 + which / 2 return percentiles ( a , p , axis )
| 0 |
finding 25 percent points in distribution python
|
Return a percentile range from an array of values .
|
cosqa-train-557
|
def ci(a, which=95, axis=None):
"""Return a percentile range from an array of values."""
p = 50 - which / 2, 50 + which / 2
return percentiles(a, p, axis)
|
def dtype ( self ) : try : return self . data . dtype except AttributeError : return numpy . dtype ( '%s%d' % ( self . _sample_type , self . _sample_bytes ) )
| 0 |
python how do i know what data type
|
Pixel data type .
|
cosqa-train-558
|
def dtype(self):
"""Pixel data type."""
try:
return self.data.dtype
except AttributeError:
return numpy.dtype('%s%d' % (self._sample_type, self._sample_bytes))
|
def tuple_search ( t , i , v ) : for e in t : if e [ i ] == v : return e return None
| 0 |
finding a string in a python tuple
|
Search tuple array by index and value : param t : tuple array : param i : index of the value in each tuple : param v : value : return : the first tuple in the array with the specific index / value
|
cosqa-train-559
|
def tuple_search(t, i, v):
"""
Search tuple array by index and value
:param t: tuple array
:param i: index of the value in each tuple
:param v: value
:return: the first tuple in the array with the specific index / value
"""
for e in t:
if e[i] == v:
return e
return None
|
def from_pairs_to_array_values ( pairs ) : result = { } for pair in pairs : result [ pair [ 0 ] ] = concat ( prop_or ( [ ] , pair [ 0 ] , result ) , [ pair [ 1 ] ] ) return result
| 0 |
python how join to lists as pairs
|
Like from pairs but combines duplicate key values into arrays : param pairs : : return :
|
cosqa-train-560
|
def from_pairs_to_array_values(pairs):
"""
Like from pairs but combines duplicate key values into arrays
:param pairs:
:return:
"""
result = {}
for pair in pairs:
result[pair[0]] = concat(prop_or([], pair[0], result), [pair[1]])
return result
|
def area ( x , y ) : # http://stackoverflow.com/questions/24467972/calculate-area-of-polygon-given-x-y-coordinates return 0.5 * np . abs ( np . dot ( x , np . roll ( y , 1 ) ) - np . dot ( y , np . roll ( x , 1 ) ) )
| 0 |
finding area of an irregular polygon python
|
Calculate the area of a polygon given as x ( ... ) y ( ... ) Implementation of Shoelace formula
|
cosqa-train-561
|
def area(x,y):
"""
Calculate the area of a polygon given as x(...),y(...)
Implementation of Shoelace formula
"""
# http://stackoverflow.com/questions/24467972/calculate-area-of-polygon-given-x-y-coordinates
return 0.5 * np.abs(np.dot(x, np.roll(y, 1)) - np.dot(y, np.roll(x, 1)))
|
def _getSuperFunc ( self , s , func ) : return getattr ( super ( self . cls ( ) , s ) , func . __name__ )
| 0 |
python how to autocomplate to show super method
|
Return the the super function .
|
cosqa-train-562
|
def _getSuperFunc(self, s, func):
"""Return the the super function."""
return getattr(super(self.cls(), s), func.__name__)
|
def val_to_bin ( edges , x ) : ibin = np . digitize ( np . array ( x , ndmin = 1 ) , edges ) - 1 return ibin
| 0 |
finding center of histogram bins python
|
Convert axis coordinate to bin index .
|
cosqa-train-563
|
def val_to_bin(edges, x):
"""Convert axis coordinate to bin index."""
ibin = np.digitize(np.array(x, ndmin=1), edges) - 1
return ibin
|
def val_to_bin ( edges , x ) : ibin = np . digitize ( np . array ( x , ndmin = 1 ) , edges ) - 1 return ibin
| 0 |
python how to calculate bins from bin edges
|
Convert axis coordinate to bin index .
|
cosqa-train-564
|
def val_to_bin(edges, x):
"""Convert axis coordinate to bin index."""
ibin = np.digitize(np.array(x, ndmin=1), edges) - 1
return ibin
|
def compare ( dicts ) : common_members = { } common_keys = reduce ( lambda x , y : x & y , map ( dict . keys , dicts ) ) for k in common_keys : common_members [ k ] = list ( reduce ( lambda x , y : x & y , [ set ( d [ k ] ) for d in dicts ] ) ) return common_members
| 0 |
finding common values in dictionaries python
|
Compare by iteration
|
cosqa-train-565
|
def compare(dicts):
"""Compare by iteration"""
common_members = {}
common_keys = reduce(lambda x, y: x & y, map(dict.keys, dicts))
for k in common_keys:
common_members[k] = list(
reduce(lambda x, y: x & y, [set(d[k]) for d in dicts]))
return common_members
|
def convert_timestamp ( timestamp ) : datetime = dt . datetime . utcfromtimestamp ( timestamp / 1000. ) return np . datetime64 ( datetime . replace ( tzinfo = None ) )
| 0 |
python how to cast string to timestamp
|
Converts bokehJS timestamp to datetime64 .
|
cosqa-train-566
|
def convert_timestamp(timestamp):
"""
Converts bokehJS timestamp to datetime64.
"""
datetime = dt.datetime.utcfromtimestamp(timestamp/1000.)
return np.datetime64(datetime.replace(tzinfo=None))
|
def _get_compiled_ext ( ) : for ext , mode , typ in imp . get_suffixes ( ) : if typ == imp . PY_COMPILED : return ext
| 0 |
finding extensions of files through python
|
Official way to get the extension of compiled files ( . pyc or . pyo )
|
cosqa-train-567
|
def _get_compiled_ext():
"""Official way to get the extension of compiled files (.pyc or .pyo)"""
for ext, mode, typ in imp.get_suffixes():
if typ == imp.PY_COMPILED:
return ext
|
def list_add_capitalize ( l ) : nl = [ ] for i in l : nl . append ( i ) if hasattr ( i , "capitalize" ) : nl . append ( i . capitalize ( ) ) return list ( set ( nl ) )
| 0 |
python how to change list items to capital
|
cosqa-train-568
|
def list_add_capitalize(l):
"""
@type l: list
@return: list
"""
nl = []
for i in l:
nl.append(i)
if hasattr(i, "capitalize"):
nl.append(i.capitalize())
return list(set(nl))
|
|
def inh ( table ) : t = [ ] for i in table : t . append ( np . ndarray . tolist ( np . arcsinh ( i ) ) ) return t
| 0 |
finding inverse of matrix in python
|
inverse hyperbolic sine transformation
|
cosqa-train-569
|
def inh(table):
"""
inverse hyperbolic sine transformation
"""
t = []
for i in table:
t.append(np.ndarray.tolist(np.arcsinh(i)))
return t
|
def to_camel_case ( text ) : split = text . split ( '_' ) return split [ 0 ] + "" . join ( x . title ( ) for x in split [ 1 : ] )
| 0 |
python how to change text to uppercase
|
Convert to camel case .
|
cosqa-train-570
|
def to_camel_case(text):
"""Convert to camel case.
:param str text:
:rtype: str
:return:
"""
split = text.split('_')
return split[0] + "".join(x.title() for x in split[1:])
|
def median ( lst ) : #: http://stackoverflow.com/a/24101534 sortedLst = sorted ( lst ) lstLen = len ( lst ) index = ( lstLen - 1 ) // 2 if ( lstLen % 2 ) : return sortedLst [ index ] else : return ( sortedLst [ index ] + sortedLst [ index + 1 ] ) / 2.0
| 0 |
finding median of list python
|
Calcuates the median value in a
|
cosqa-train-571
|
def median(lst):
""" Calcuates the median value in a @lst """
#: http://stackoverflow.com/a/24101534
sortedLst = sorted(lst)
lstLen = len(lst)
index = (lstLen - 1) // 2
if (lstLen % 2):
return sortedLst[index]
else:
return (sortedLst[index] + sortedLst[index + 1])/2.0
|
def _IsRetryable ( error ) : if not isinstance ( error , MySQLdb . OperationalError ) : return False if not error . args : return False code = error . args [ 0 ] return code in _RETRYABLE_ERRORS
| 0 |
python how to check if a database query failed
|
Returns whether error is likely to be retryable .
|
cosqa-train-572
|
def _IsRetryable(error):
"""Returns whether error is likely to be retryable."""
if not isinstance(error, MySQLdb.OperationalError):
return False
if not error.args:
return False
code = error.args[0]
return code in _RETRYABLE_ERRORS
|
def iter_finds ( regex_obj , s ) : if isinstance ( regex_obj , str ) : for m in re . finditer ( regex_obj , s ) : yield m . group ( ) else : for m in regex_obj . finditer ( s ) : yield m . group ( )
| 0 |
finding multiple strings using regex in python
|
Generate all matches found within a string for a regex and yield each match as a string
|
cosqa-train-573
|
def iter_finds(regex_obj, s):
"""Generate all matches found within a string for a regex and yield each match as a string"""
if isinstance(regex_obj, str):
for m in re.finditer(regex_obj, s):
yield m.group()
else:
for m in regex_obj.finditer(s):
yield m.group()
|
def pid_exists ( pid ) : try : os . kill ( pid , 0 ) except OSError as exc : return exc . errno == errno . EPERM else : return True
| 0 |
python how to check if a process exists by pid
|
Determines if a system process identifer exists in process table .
|
cosqa-train-574
|
def pid_exists(pid):
""" Determines if a system process identifer exists in process table.
"""
try:
os.kill(pid, 0)
except OSError as exc:
return exc.errno == errno.EPERM
else:
return True
|
def getPrimeFactors ( n ) : lo = [ 1 ] n2 = n // 2 k = 2 for k in range ( 2 , n2 + 1 ) : if ( n // k ) * k == n : lo . append ( k ) return lo + [ n , ]
| 0 |
finding prime and divisors python
|
Get all the prime factor of given integer
|
cosqa-train-575
|
def getPrimeFactors(n):
"""
Get all the prime factor of given integer
@param n integer
@return list [1, ..., n]
"""
lo = [1]
n2 = n // 2
k = 2
for k in range(2, n2 + 1):
if (n // k)*k == n:
lo.append(k)
return lo + [n, ]
|
def _isstring ( dtype ) : return dtype . type == numpy . unicode_ or dtype . type == numpy . string_
| 0 |
python how to check if datattype is string
|
Given a numpy dtype determines whether it is a string . Returns True if the dtype is string or unicode .
|
cosqa-train-576
|
def _isstring(dtype):
"""Given a numpy dtype, determines whether it is a string. Returns True
if the dtype is string or unicode.
"""
return dtype.type == numpy.unicode_ or dtype.type == numpy.string_
|
def find_lt ( a , x ) : i = bs . bisect_left ( a , x ) if i : return i - 1 raise ValueError
| 0 |
finding the two smallest values in a list python
|
Find rightmost value less than x .
|
cosqa-train-577
|
def find_lt(a, x):
"""Find rightmost value less than x."""
i = bs.bisect_left(a, x)
if i: return i - 1
raise ValueError
|
def _is_override ( meta , method ) : from taipan . objective . modifiers import _OverriddenMethod return isinstance ( method , _OverriddenMethod )
| 1 |
python how to check if method is overload
|
Checks whether given class or instance method has been marked with the
|
cosqa-train-578
|
def _is_override(meta, method):
"""Checks whether given class or instance method has been marked
with the ``@override`` decorator.
"""
from taipan.objective.modifiers import _OverriddenMethod
return isinstance(method, _OverriddenMethod)
|
def is_in ( self , point_x , point_y ) : point_array = array ( ( ( point_x , point_y ) , ) ) vertices = array ( self . points ) winding = self . inside_rule == "winding" result = points_in_polygon ( point_array , vertices , winding ) return result [ 0 ]
| 0 |
finding what points are contained in polygon python
|
Test if a point is within this polygonal region
|
cosqa-train-579
|
def is_in(self, point_x, point_y):
""" Test if a point is within this polygonal region """
point_array = array(((point_x, point_y),))
vertices = array(self.points)
winding = self.inside_rule == "winding"
result = points_in_polygon(point_array, vertices, winding)
return result[0]
|
def should_skip_logging ( func ) : disabled = strtobool ( request . headers . get ( "x-request-nolog" , "false" ) ) return disabled or getattr ( func , SKIP_LOGGING , False )
| 1 |
python how to check logging is disabled
|
Should we skip logging for this handler?
|
cosqa-train-580
|
def should_skip_logging(func):
"""
Should we skip logging for this handler?
"""
disabled = strtobool(request.headers.get("x-request-nolog", "false"))
return disabled or getattr(func, SKIP_LOGGING, False)
|
def calc_cR ( Q2 , sigma ) : return Q2 * np . exp ( np . sum ( np . log ( sigma ** 2 ) ) / sigma . shape [ 0 ] )
| 0 |
fit r like formula model in python without intercept
|
Returns the cR statistic for the variogram fit ( see [ 1 ] ) .
|
cosqa-train-581
|
def calc_cR(Q2, sigma):
"""Returns the cR statistic for the variogram fit (see [1])."""
return Q2 * np.exp(np.sum(np.log(sigma**2))/sigma.shape[0])
|
def is_builtin_type ( tp ) : return hasattr ( __builtins__ , tp . __name__ ) and tp is getattr ( __builtins__ , tp . __name__ )
| 0 |
python how to check methods implemented in a type
|
Checks if the given type is a builtin one .
|
cosqa-train-582
|
def is_builtin_type(tp):
"""Checks if the given type is a builtin one.
"""
return hasattr(__builtins__, tp.__name__) and tp is getattr(__builtins__, tp.__name__)
|
def apply_fit ( xy , coeffs ) : x_new = coeffs [ 0 ] [ 2 ] + coeffs [ 0 ] [ 0 ] * xy [ : , 0 ] + coeffs [ 0 ] [ 1 ] * xy [ : , 1 ] y_new = coeffs [ 1 ] [ 2 ] + coeffs [ 1 ] [ 0 ] * xy [ : , 0 ] + coeffs [ 1 ] [ 1 ] * xy [ : , 1 ] return x_new , y_new
| 0 |
fit the variables into a equation python
|
Apply the coefficients from a linear fit to an array of x y positions .
|
cosqa-train-583
|
def apply_fit(xy,coeffs):
""" Apply the coefficients from a linear fit to
an array of x,y positions.
The coeffs come from the 'coeffs' member of the
'fit_arrays()' output.
"""
x_new = coeffs[0][2] + coeffs[0][0]*xy[:,0] + coeffs[0][1]*xy[:,1]
y_new = coeffs[1][2] + coeffs[1][0]*xy[:,0] + coeffs[1][1]*xy[:,1]
return x_new,y_new
|
def forget_coords ( self ) : self . w . ntotal . set_text ( '0' ) self . coords_dict . clear ( ) self . redo ( )
| 0 |
python how to clear a variables value
|
Forget all loaded coordinates .
|
cosqa-train-584
|
def forget_coords(self):
"""Forget all loaded coordinates."""
self.w.ntotal.set_text('0')
self.coords_dict.clear()
self.redo()
|
def flat_list ( lst ) : if isinstance ( lst , list ) : for item in lst : for i in flat_list ( item ) : yield i else : yield lst
| 0 |
flatten list of list python using yield
|
This function flatten given nested list . Argument : nested list Returns : flat list
|
cosqa-train-585
|
def flat_list(lst):
"""This function flatten given nested list.
Argument:
nested list
Returns:
flat list
"""
if isinstance(lst, list):
for item in lst:
for i in flat_list(item):
yield i
else:
yield lst
|
def safe_exit ( output ) : try : sys . stdout . write ( output ) sys . stdout . flush ( ) except IOError : pass
| 0 |
python how to close and if
|
exit without breaking pipes .
|
cosqa-train-586
|
def safe_exit(output):
"""exit without breaking pipes."""
try:
sys.stdout.write(output)
sys.stdout.flush()
except IOError:
pass
|
def imflip ( img , direction = 'horizontal' ) : assert direction in [ 'horizontal' , 'vertical' ] if direction == 'horizontal' : return np . flip ( img , axis = 1 ) else : return np . flip ( img , axis = 0 )
| 0 |
flip a 1d vector python
|
Flip an image horizontally or vertically .
|
cosqa-train-587
|
def imflip(img, direction='horizontal'):
"""Flip an image horizontally or vertically.
Args:
img (ndarray): Image to be flipped.
direction (str): The flip direction, either "horizontal" or "vertical".
Returns:
ndarray: The flipped image.
"""
assert direction in ['horizontal', 'vertical']
if direction == 'horizontal':
return np.flip(img, axis=1)
else:
return np.flip(img, axis=0)
|
def get_order ( self ) : return [ dict ( reverse = r [ 0 ] , key = r [ 1 ] ) for r in self . get_model ( ) ]
| 0 |
python how to create a ordered dict
|
Return a list of dicionaries . See set_order .
|
cosqa-train-588
|
def get_order(self):
"""
Return a list of dicionaries. See `set_order`.
"""
return [dict(reverse=r[0], key=r[1]) for r in self.get_model()]
|
def hflip ( img ) : if not _is_pil_image ( img ) : raise TypeError ( 'img should be PIL Image. Got {}' . format ( type ( img ) ) ) return img . transpose ( Image . FLIP_LEFT_RIGHT )
| 0 |
flip image vertical python
|
Horizontally flip the given PIL Image .
|
cosqa-train-589
|
def hflip(img):
"""Horizontally flip the given PIL Image.
Args:
img (PIL Image): Image to be flipped.
Returns:
PIL Image: Horizontall flipped image.
"""
if not _is_pil_image(img):
raise TypeError('img should be PIL Image. Got {}'.format(type(img)))
return img.transpose(Image.FLIP_LEFT_RIGHT)
|
def mkdir ( dir , enter ) : if not os . path . exists ( dir ) : os . makedirs ( dir )
| 0 |
python how to create dir
|
Create directory with template for topic of the current environment
|
cosqa-train-590
|
def mkdir(dir, enter):
"""Create directory with template for topic of the current environment
"""
if not os.path.exists(dir):
os.makedirs(dir)
|
def get_document_frequency ( self , term ) : if term not in self . _terms : raise IndexError ( TERM_DOES_NOT_EXIST ) else : return len ( self . _terms [ term ] )
| 0 |
frequency of a word in a document python
|
Returns the number of documents the specified term appears in .
|
cosqa-train-591
|
def get_document_frequency(self, term):
"""
Returns the number of documents the specified term appears in.
"""
if term not in self._terms:
raise IndexError(TERM_DOES_NOT_EXIST)
else:
return len(self._terms[term])
|
def destroy ( self ) : if self . widget : self . set_active ( False ) super ( AndroidBarcodeView , self ) . destroy ( )
| 0 |
python how to disconnect signal from a widget
|
Cleanup the activty lifecycle listener
|
cosqa-train-592
|
def destroy(self):
""" Cleanup the activty lifecycle listener """
if self.widget:
self.set_active(False)
super(AndroidBarcodeView, self).destroy()
|
def connect ( ) : ftp_class = ftplib . FTP if not SSL else ftplib . FTP_TLS ftp = ftp_class ( timeout = TIMEOUT ) ftp . connect ( HOST , PORT ) ftp . login ( USER , PASSWORD ) if SSL : ftp . prot_p ( ) # secure data connection return ftp
| 1 |
ftplib python secure connection
|
Connect to FTP server login and return an ftplib . FTP instance .
|
cosqa-train-593
|
def connect():
"""Connect to FTP server, login and return an ftplib.FTP instance."""
ftp_class = ftplib.FTP if not SSL else ftplib.FTP_TLS
ftp = ftp_class(timeout=TIMEOUT)
ftp.connect(HOST, PORT)
ftp.login(USER, PASSWORD)
if SSL:
ftp.prot_p() # secure data connection
return ftp
|
def one_for_all ( self , deps ) : requires , dependencies = [ ] , [ ] deps . reverse ( ) # Inverting the list brings the # dependencies in order to be installed. requires = Utils ( ) . dimensional_list ( deps ) dependencies = Utils ( ) . remove_dbs ( requires ) return dependencies
| 0 |
python how to dowload all dependencies
|
Because there are dependencies that depend on other dependencies are created lists into other lists . Thus creating this loop create one - dimensional list and remove double packages from dependencies .
|
cosqa-train-594
|
def one_for_all(self, deps):
"""Because there are dependencies that depend on other
dependencies are created lists into other lists.
Thus creating this loop create one-dimensional list and
remove double packages from dependencies.
"""
requires, dependencies = [], []
deps.reverse()
# Inverting the list brings the
# dependencies in order to be installed.
requires = Utils().dimensional_list(deps)
dependencies = Utils().remove_dbs(requires)
return dependencies
|
def trigger_fullscreen_action ( self , fullscreen ) : action = self . action_group . get_action ( 'fullscreen' ) action . set_active ( fullscreen )
| 1 |
full screen in python tkinter
|
Toggle fullscreen from outside the GUI causes the GUI to updated and run all its actions .
|
cosqa-train-595
|
def trigger_fullscreen_action(self, fullscreen):
"""
Toggle fullscreen from outside the GUI,
causes the GUI to updated and run all its actions.
"""
action = self.action_group.get_action('fullscreen')
action.set_active(fullscreen)
|
def download_json ( local_filename , url , clobber = False ) : with open ( local_filename , 'w' ) as json_file : json_file . write ( json . dumps ( requests . get ( url ) . json ( ) , sort_keys = True , indent = 2 , separators = ( ',' , ': ' ) ) )
| 0 |
python how to download a json url
|
Download the given JSON file and pretty - print before we output it .
|
cosqa-train-596
|
def download_json(local_filename, url, clobber=False):
"""Download the given JSON file, and pretty-print before we output it."""
with open(local_filename, 'w') as json_file:
json_file.write(json.dumps(requests.get(url).json(), sort_keys=True, indent=2, separators=(',', ': ')))
|
def is_password_valid ( password ) : pattern = re . compile ( r"^.{4,75}$" ) return bool ( pattern . match ( password ) )
| 0 |
function to check strngth of password with regex in python
|
Check if a password is valid
|
cosqa-train-597
|
def is_password_valid(password):
"""
Check if a password is valid
"""
pattern = re.compile(r"^.{4,75}$")
return bool(pattern.match(password))
|
def drag_and_drop ( self , droppable ) : self . scroll_to ( ) ActionChains ( self . parent . driver ) . drag_and_drop ( self . _element , droppable . _element ) . perform ( )
| 1 |
python how to drag a element to another element and stay at second element
|
Performs drag a element to another elmenet .
|
cosqa-train-598
|
def drag_and_drop(self, droppable):
"""
Performs drag a element to another elmenet.
Currently works only on Chrome driver.
"""
self.scroll_to()
ActionChains(self.parent.driver).drag_and_drop(self._element, droppable._element).perform()
|
def gauss_pdf ( x , mu , sigma ) : return 1 / np . sqrt ( 2 * np . pi ) / sigma * np . exp ( - ( x - mu ) ** 2 / 2. / sigma ** 2 )
| 0 |
gaussian distribution python formula
|
Normalized Gaussian
|
cosqa-train-599
|
def gauss_pdf(x, mu, sigma):
"""Normalized Gaussian"""
return 1 / np.sqrt(2 * np.pi) / sigma * np.exp(-(x - mu) ** 2 / 2. / sigma ** 2)
|
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