code_tokens
stringlengths 60
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| doc
stringlengths 16
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|---|---|---|---|---|---|
def fast_distinct ( self ) : return self . model . objects . filter ( pk__in = self . values_list ( 'pk' , flat = True ) )
| 0 |
is there a select distinct in python
|
Because standard distinct used on the all fields are very slow and works only with PostgreSQL database this method provides alternative to the standard distinct method . : return : qs with unique objects
|
cosqa-train-16400
|
def fast_distinct(self):
"""
Because standard distinct used on the all fields are very slow and works only with PostgreSQL database
this method provides alternative to the standard distinct method.
:return: qs with unique objects
"""
return self.model.objects.filter(pk__in=self.values_list('pk', flat=True))
|
def __grid_widgets ( self ) : scrollbar_column = 0 if self . __compound is tk . LEFT else 2 self . _canvas . grid ( row = 0 , column = 1 , sticky = "nswe" ) self . _scrollbar . grid ( row = 0 , column = scrollbar_column , sticky = "ns" )
| 0 |
python widgets dont expand in grid
|
Places all the child widgets in the appropriate positions .
|
cosqa-train-16401
|
def __grid_widgets(self):
"""Places all the child widgets in the appropriate positions."""
scrollbar_column = 0 if self.__compound is tk.LEFT else 2
self._canvas.grid(row=0, column=1, sticky="nswe")
self._scrollbar.grid(row=0, column=scrollbar_column, sticky="ns")
|
def test ( ) : import unittest tests = unittest . TestLoader ( ) . discover ( 'tests' ) unittest . TextTestRunner ( verbosity = 2 ) . run ( tests )
| 1 |
is there a unit test runner in python
|
Run the unit tests .
|
cosqa-train-16402
|
def test():
"""Run the unit tests."""
import unittest
tests = unittest.TestLoader().discover('tests')
unittest.TextTestRunner(verbosity=2).run(tests)
|
def retry_on_signal ( function ) : while True : try : return function ( ) except EnvironmentError , e : if e . errno != errno . EINTR : raise
| 0 |
python will the for loop keep going after the try excpetion
|
Retries function until it doesn t raise an EINTR error
|
cosqa-train-16403
|
def retry_on_signal(function):
"""Retries function until it doesn't raise an EINTR error"""
while True:
try:
return function()
except EnvironmentError, e:
if e.errno != errno.EINTR:
raise
|
def all_equal ( arg1 , arg2 ) : if all ( hasattr ( el , '_infinitely_iterable' ) for el in [ arg1 , arg2 ] ) : return arg1 == arg2 try : return all ( a1 == a2 for a1 , a2 in zip ( arg1 , arg2 ) ) except TypeError : return arg1 == arg2
| 1 |
is there a way in python to check that 2 numpy arrays are identical
|
Return a single boolean for arg1 == arg2 even for numpy arrays using element - wise comparison .
|
cosqa-train-16404
|
def all_equal(arg1,arg2):
"""
Return a single boolean for arg1==arg2, even for numpy arrays
using element-wise comparison.
Uses all(arg1==arg2) for sequences, and arg1==arg2 otherwise.
If both objects have an '_infinitely_iterable' attribute, they are
not be zipped together and are compared directly instead.
"""
if all(hasattr(el, '_infinitely_iterable') for el in [arg1,arg2]):
return arg1==arg2
try:
return all(a1 == a2 for a1, a2 in zip(arg1, arg2))
except TypeError:
return arg1==arg2
|
def __init__ ( self , encoding = 'utf-8' ) : super ( StdinInputReader , self ) . __init__ ( sys . stdin , encoding = encoding )
| 0 |
python windows stdin encoding
|
Initializes an stdin input reader .
|
cosqa-train-16405
|
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 check_alert ( self , text ) : try : alert = Alert ( world . browser ) if alert . text != text : raise AssertionError ( "Alert text expected to be {!r}, got {!r}." . format ( text , alert . text ) ) except WebDriverException : # PhantomJS is kinda poor pass
| 0 |
is there an alert like in javascript in python
|
Assert an alert is showing with the given text .
|
cosqa-train-16406
|
def check_alert(self, text):
"""
Assert an alert is showing with the given text.
"""
try:
alert = Alert(world.browser)
if alert.text != text:
raise AssertionError(
"Alert text expected to be {!r}, got {!r}.".format(
text, alert.text))
except WebDriverException:
# PhantomJS is kinda poor
pass
|
def write_fits ( self , fitsfile ) : tab = self . create_table ( ) hdu_data = fits . table_to_hdu ( tab ) hdus = [ fits . PrimaryHDU ( ) , hdu_data ] fits_utils . write_hdus ( hdus , fitsfile )
| 0 |
python write header to fits file
|
Write the ROI model to a FITS file .
|
cosqa-train-16407
|
def write_fits(self, fitsfile):
"""Write the ROI model to a FITS file."""
tab = self.create_table()
hdu_data = fits.table_to_hdu(tab)
hdus = [fits.PrimaryHDU(), hdu_data]
fits_utils.write_hdus(hdus, fitsfile)
|
def each_img ( img_dir ) : for fname in utils . each_img ( img_dir ) : fname = os . path . join ( img_dir , fname ) yield cv . imread ( fname ) , fname
| 1 |
iterate all the images in a directory + python + opencv
|
Reads and iterates through each image file in the given directory
|
cosqa-train-16408
|
def each_img(img_dir):
"""
Reads and iterates through each image file in the given directory
"""
for fname in utils.each_img(img_dir):
fname = os.path.join(img_dir, fname)
yield cv.imread(fname), fname
|
def save_dict_to_file ( filename , dictionary ) : with open ( filename , 'w' ) as f : writer = csv . writer ( f ) for k , v in iteritems ( dictionary ) : writer . writerow ( [ str ( k ) , str ( v ) ] )
| 1 |
python writing a dict to a file
|
Saves dictionary as CSV file .
|
cosqa-train-16409
|
def save_dict_to_file(filename, dictionary):
"""Saves dictionary as CSV file."""
with open(filename, 'w') as f:
writer = csv.writer(f)
for k, v in iteritems(dictionary):
writer.writerow([str(k), str(v)])
|
def path_distance ( points ) : vecs = np . diff ( points , axis = 0 ) [ : , : 3 ] d2 = [ np . dot ( p , p ) for p in vecs ] return np . sum ( np . sqrt ( d2 ) )
| 1 |
iterate distance over list of points python
|
Compute the path distance from given set of points
|
cosqa-train-16410
|
def path_distance(points):
"""
Compute the path distance from given set of points
"""
vecs = np.diff(points, axis=0)[:, :3]
d2 = [np.dot(p, p) for p in vecs]
return np.sum(np.sqrt(d2))
|
def series_table_row_offset ( self , series ) : title_and_spacer_rows = series . index * 2 data_point_rows = series . data_point_offset return title_and_spacer_rows + data_point_rows
| 0 |
python xl number of entries in a column
|
Return the number of rows preceding the data table for * series * in the Excel worksheet .
|
cosqa-train-16411
|
def series_table_row_offset(self, series):
"""
Return the number of rows preceding the data table for *series* in
the Excel worksheet.
"""
title_and_spacer_rows = series.index * 2
data_point_rows = series.data_point_offset
return title_and_spacer_rows + data_point_rows
|
def extract_words ( lines ) : for line in lines : for word in re . findall ( r"\w+" , line ) : yield word
| 0 |
iterate over words in text line python
|
Extract from the given iterable of lines the list of words .
|
cosqa-train-16412
|
def extract_words(lines):
"""
Extract from the given iterable of lines the list of words.
:param lines: an iterable of lines;
:return: a generator of words of lines.
"""
for line in lines:
for word in re.findall(r"\w+", line):
yield word
|
def as_list ( self ) : return [ self . name , self . value , [ x . as_list for x in self . children ] ]
| 0 |
python xml elements as a list
|
Return all child objects in nested lists of strings .
|
cosqa-train-16413
|
def as_list(self):
"""Return all child objects in nested lists of strings."""
return [self.name, self.value, [x.as_list for x in self.children]]
|
def __next__ ( self , reward , ask_id , lbl ) : return self . next ( reward , ask_id , lbl )
| 1 |
iterator inpython has next next
|
For Python3 compatibility of generator .
|
cosqa-train-16414
|
def __next__(self, reward, ask_id, lbl):
"""For Python3 compatibility of generator."""
return self.next(reward, ask_id, lbl)
|
def element_to_string ( element , include_declaration = True , encoding = DEFAULT_ENCODING , method = 'xml' ) : if isinstance ( element , ElementTree ) : element = element . getroot ( ) elif not isinstance ( element , ElementType ) : element = get_element ( element ) if element is None : return u'' element_as_string = tostring ( element , encoding , method ) . decode ( encoding = encoding ) if include_declaration : return element_as_string else : return strip_xml_declaration ( element_as_string )
| 1 |
python xml elementtree to string
|
: return : the string value of the element or element tree
|
cosqa-train-16415
|
def element_to_string(element, include_declaration=True, encoding=DEFAULT_ENCODING, method='xml'):
""" :return: the string value of the element or element tree """
if isinstance(element, ElementTree):
element = element.getroot()
elif not isinstance(element, ElementType):
element = get_element(element)
if element is None:
return u''
element_as_string = tostring(element, encoding, method).decode(encoding=encoding)
if include_declaration:
return element_as_string
else:
return strip_xml_declaration(element_as_string)
|
def group_by ( iterable , key_func ) : groups = ( list ( sub ) for key , sub in groupby ( iterable , key_func ) ) return zip ( groups , groups )
| 0 |
itertools groupby in python list of dicts by key
|
Wrap itertools . groupby to make life easier .
|
cosqa-train-16416
|
def group_by(iterable, key_func):
"""Wrap itertools.groupby to make life easier."""
groups = (
list(sub) for key, sub in groupby(iterable, key_func)
)
return zip(groups, groups)
|
def _get_minidom_tag_value ( station , tag_name ) : tag = station . getElementsByTagName ( tag_name ) [ 0 ] . firstChild if tag : return tag . nodeValue return None
| 1 |
python xml get value in tag
|
get a value from a tag ( if it exists )
|
cosqa-train-16417
|
def _get_minidom_tag_value(station, tag_name):
"""get a value from a tag (if it exists)"""
tag = station.getElementsByTagName(tag_name)[0].firstChild
if tag:
return tag.nodeValue
return None
|
def jaccard ( c_1 , c_2 ) : nom = np . intersect1d ( c_1 , c_2 ) . size denom = np . union1d ( c_1 , c_2 ) . size return nom / denom
| 1 |
jacquard similarity using python
|
Calculates the Jaccard similarity between two sets of nodes . Called by mroc .
|
cosqa-train-16418
|
def jaccard(c_1, c_2):
"""
Calculates the Jaccard similarity between two sets of nodes. Called by mroc.
Inputs: - c_1: Community (set of nodes) 1.
- c_2: Community (set of nodes) 2.
Outputs: - jaccard_similarity: The Jaccard similarity of these two communities.
"""
nom = np.intersect1d(c_1, c_2).size
denom = np.union1d(c_1, c_2).size
return nom/denom
|
def required_attributes ( element , * attributes ) : if not reduce ( lambda still_valid , param : still_valid and param in element . attrib , attributes , True ) : raise NotValidXmlException ( msg_err_missing_attributes ( element . tag , * attributes ) )
| 0 |
python xml parser check attribute
|
Check element for required attributes . Raise NotValidXmlException on error .
|
cosqa-train-16419
|
def required_attributes(element, *attributes):
"""Check element for required attributes. Raise ``NotValidXmlException`` on error.
:param element: ElementTree element
:param attributes: list of attributes names to check
:raises NotValidXmlException: if some argument is missing
"""
if not reduce(lambda still_valid, param: still_valid and param in element.attrib, attributes, True):
raise NotValidXmlException(msg_err_missing_attributes(element.tag, *attributes))
|
def join ( mapping , bind , values ) : return [ ' ' . join ( [ six . text_type ( v ) for v in values if v is not None ] ) ]
| 1 |
join list of empty strings and strings python
|
Merge all the strings . Put space between them .
|
cosqa-train-16420
|
def join(mapping, bind, values):
""" Merge all the strings. Put space between them. """
return [' '.join([six.text_type(v) for v in values if v is not None])]
|
def xml_str_to_dict ( s ) : xml = minidom . parseString ( s ) return pythonzimbra . tools . xmlserializer . dom_to_dict ( xml . firstChild )
| 0 |
python xml to dictionary
|
Transforms an XML string it to python - zimbra dict format
|
cosqa-train-16421
|
def xml_str_to_dict(s):
""" Transforms an XML string it to python-zimbra dict format
For format, see:
https://github.com/Zimbra-Community/python-zimbra/blob/master/README.md
:param: a string, containing XML
:returns: a dict, with python-zimbra format
"""
xml = minidom.parseString(s)
return pythonzimbra.tools.xmlserializer.dom_to_dict(xml.firstChild)
|
def send ( self , topic , * args , * * kwargs ) : prefix_topic = self . heroku_kafka . prefix_topic ( topic ) return super ( HerokuKafkaProducer , self ) . send ( prefix_topic , * args , * * kwargs )
| 0 |
kafka python producer not sending message
|
Appends the prefix to the topic before sendingf
|
cosqa-train-16422
|
def send(self, topic, *args, **kwargs):
"""
Appends the prefix to the topic before sendingf
"""
prefix_topic = self.heroku_kafka.prefix_topic(topic)
return super(HerokuKafkaProducer, self).send(prefix_topic, *args, **kwargs)
|
def root_parent ( self , category = None ) : return next ( filter ( lambda c : c . is_root , self . hierarchy ( ) ) )
| 1 |
python xmlnode get parent
|
Returns the topmost parent of the current category .
|
cosqa-train-16423
|
def root_parent(self, category=None):
""" Returns the topmost parent of the current category. """
return next(filter(lambda c: c.is_root, self.hierarchy()))
|
def best ( self ) : b = ( - 1e999999 , None ) for k , c in iteritems ( self . counts ) : b = max ( b , ( c , k ) ) return b [ 1 ]
| 0 |
keep track of 5 largest values in python
|
Returns the element with the highest probability .
|
cosqa-train-16424
|
def best(self):
"""
Returns the element with the highest probability.
"""
b = (-1e999999, None)
for k, c in iteritems(self.counts):
b = max(b, (c, k))
return b[1]
|
def _Open ( self , hostname , port ) : try : self . _xmlrpc_server = SimpleXMLRPCServer . SimpleXMLRPCServer ( ( hostname , port ) , logRequests = False , allow_none = True ) except SocketServer . socket . error as exception : logger . warning ( ( 'Unable to bind a RPC server on {0:s}:{1:d} with error: ' '{2!s}' ) . format ( hostname , port , exception ) ) return False self . _xmlrpc_server . register_function ( self . _callback , self . _RPC_FUNCTION_NAME ) return True
| 0 |
python xmlrpc doesn't work over a network
|
Opens the RPC communication channel for clients .
|
cosqa-train-16425
|
def _Open(self, hostname, port):
"""Opens the RPC communication channel for clients.
Args:
hostname (str): hostname or IP address to connect to for requests.
port (int): port to connect to for requests.
Returns:
bool: True if the communication channel was successfully opened.
"""
try:
self._xmlrpc_server = SimpleXMLRPCServer.SimpleXMLRPCServer(
(hostname, port), logRequests=False, allow_none=True)
except SocketServer.socket.error as exception:
logger.warning((
'Unable to bind a RPC server on {0:s}:{1:d} with error: '
'{2!s}').format(hostname, port, exception))
return False
self._xmlrpc_server.register_function(
self._callback, self._RPC_FUNCTION_NAME)
return True
|
def predict ( self , X ) : return [ self . classes [ prediction . argmax ( ) ] for prediction in self . predict_proba ( X ) ]
| 0 |
keras python sequential predict batch size one one input
|
Predict the class for X .
|
cosqa-train-16426
|
def predict(self, X):
"""Predict the class for X.
The predicted class for each sample in X is returned.
Parameters
----------
X : List of ndarrays, one for each training example.
Each training example's shape is (string1_len,
string2_len, n_features), where string1_len and
string2_len are the length of the two training strings and
n_features the number of features.
Returns
-------
y : iterable of shape = [n_samples]
The predicted classes.
"""
return [self.classes[prediction.argmax()] for prediction in self.predict_proba(X)]
|
def stop ( pid ) : if psutil . pid_exists ( pid ) : try : p = psutil . Process ( pid ) p . kill ( ) except Exception : pass
| 1 |
kill a python process in linux
|
Shut down a specific process .
|
cosqa-train-16427
|
def stop(pid):
"""Shut down a specific process.
Args:
pid: the pid of the process to shutdown.
"""
if psutil.pid_exists(pid):
try:
p = psutil.Process(pid)
p.kill()
except Exception:
pass
|
def yaml_to_param ( obj , name ) : return from_pyvalue ( u"yaml:%s" % name , unicode ( yaml . dump ( obj ) ) )
| 0 |
python yaml as object attributes
|
Return the top - level element of a document sub - tree containing the YAML serialization of a Python object .
|
cosqa-train-16428
|
def yaml_to_param(obj, name):
"""
Return the top-level element of a document sub-tree containing the
YAML serialization of a Python object.
"""
return from_pyvalue(u"yaml:%s" % name, unicode(yaml.dump(obj)))
|
def timeout_thread_handler ( timeout , stop_event ) : stop_happened = stop_event . wait ( timeout ) if stop_happened is False : print ( "Killing program due to %f second timeout" % timeout ) os . _exit ( 2 )
| 0 |
kill a python program after a time limit
|
A background thread to kill the process if it takes too long .
|
cosqa-train-16429
|
def timeout_thread_handler(timeout, stop_event):
"""A background thread to kill the process if it takes too long.
Args:
timeout (float): The number of seconds to wait before killing
the process.
stop_event (Event): An optional event to cleanly stop the background
thread if required during testing.
"""
stop_happened = stop_event.wait(timeout)
if stop_happened is False:
print("Killing program due to %f second timeout" % timeout)
os._exit(2)
|
def ParseMany ( text ) : precondition . AssertType ( text , Text ) if compatibility . PY2 : text = text . encode ( "utf-8" ) return list ( yaml . safe_load_all ( text ) )
| 1 |
python yaml load multiple documents
|
Parses many YAML documents into a list of Python objects .
|
cosqa-train-16430
|
def ParseMany(text):
"""Parses many YAML documents into a list of Python objects.
Args:
text: A YAML source with multiple documents embedded.
Returns:
A list of Python data structures corresponding to the YAML documents.
"""
precondition.AssertType(text, Text)
if compatibility.PY2:
text = text.encode("utf-8")
return list(yaml.safe_load_all(text))
|
def timeout_thread_handler ( timeout , stop_event ) : stop_happened = stop_event . wait ( timeout ) if stop_happened is False : print ( "Killing program due to %f second timeout" % timeout ) os . _exit ( 2 )
| 1 |
kill a thread python after a specified time
|
A background thread to kill the process if it takes too long .
|
cosqa-train-16431
|
def timeout_thread_handler(timeout, stop_event):
"""A background thread to kill the process if it takes too long.
Args:
timeout (float): The number of seconds to wait before killing
the process.
stop_event (Event): An optional event to cleanly stop the background
thread if required during testing.
"""
stop_happened = stop_event.wait(timeout)
if stop_happened is False:
print("Killing program due to %f second timeout" % timeout)
os._exit(2)
|
def safe_dump ( data , stream = None , * * kwds ) : return yaml . dump ( data , stream = stream , Dumper = ODYD , * * kwds )
| 0 |
python yaml special dict representation
|
implementation of safe dumper using Ordered Dict Yaml Dumper
|
cosqa-train-16432
|
def safe_dump(data, stream=None, **kwds):
"""implementation of safe dumper using Ordered Dict Yaml Dumper"""
return yaml.dump(data, stream=stream, Dumper=ODYD, **kwds)
|
def cli_command_quit ( self , msg ) : if self . state == State . RUNNING and self . sprocess and self . sprocess . proc : self . sprocess . proc . kill ( ) else : sys . exit ( 0 )
| 0 |
kill command for python
|
\ kills the child and exits
|
cosqa-train-16433
|
def cli_command_quit(self, msg):
"""\
kills the child and exits
"""
if self.state == State.RUNNING and self.sprocess and self.sprocess.proc:
self.sprocess.proc.kill()
else:
sys.exit(0)
|
def yaml_to_param ( obj , name ) : return from_pyvalue ( u"yaml:%s" % name , unicode ( yaml . dump ( obj ) ) )
| 0 |
python yaml store as dict
|
Return the top - level element of a document sub - tree containing the YAML serialization of a Python object .
|
cosqa-train-16434
|
def yaml_to_param(obj, name):
"""
Return the top-level element of a document sub-tree containing the
YAML serialization of a Python object.
"""
return from_pyvalue(u"yaml:%s" % name, unicode(yaml.dump(obj)))
|
def kill_test_logger ( logger ) : for h in list ( logger . handlers ) : logger . removeHandler ( h ) if isinstance ( h , logging . FileHandler ) : h . close ( )
| 1 |
killing logging handlers in python
|
Cleans up a test logger object by removing all of its handlers .
|
cosqa-train-16435
|
def kill_test_logger(logger):
"""Cleans up a test logger object by removing all of its handlers.
Args:
logger: The logging object to clean up.
"""
for h in list(logger.handlers):
logger.removeHandler(h)
if isinstance(h, logging.FileHandler):
h.close()
|
def trap_exceptions ( results , handler , exceptions = Exception ) : try : for result in results : yield result except exceptions as exc : for result in always_iterable ( handler ( exc ) ) : yield result
| 1 |
python yield catch except
|
Iterate through the results but if an exception occurs stop processing the results and instead replace the results with the output from the exception handler .
|
cosqa-train-16436
|
def trap_exceptions(results, handler, exceptions=Exception):
"""
Iterate through the results, but if an exception occurs, stop
processing the results and instead replace
the results with the output from the exception handler.
"""
try:
for result in results:
yield result
except exceptions as exc:
for result in always_iterable(handler(exc)):
yield result
|
def _most_common ( iterable ) : data = Counter ( iterable ) return max ( data , key = data . __getitem__ )
| 0 |
least common element in a list python
|
Returns the most common element in iterable .
|
cosqa-train-16437
|
def _most_common(iterable):
"""Returns the most common element in `iterable`."""
data = Counter(iterable)
return max(data, key=data.__getitem__)
|
def connected_socket ( address , timeout = 3 ) : sock = socket . create_connection ( address , timeout ) yield sock sock . close ( )
| 0 |
python yield from memory leak
|
yields a connected socket
|
cosqa-train-16438
|
def connected_socket(address, timeout=3):
""" yields a connected socket """
sock = socket.create_connection(address, timeout)
yield sock
sock.close()
|
def value_left ( self , other ) : return other . value if isinstance ( other , self . __class__ ) else other
| 1 |
left right function in python
|
Returns the value of the other type instance to use in an operator method namely when the method s instance is on the left side of the expression .
|
cosqa-train-16439
|
def value_left(self, other):
"""
Returns the value of the other type instance to use in an
operator method, namely when the method's instance is on the
left side of the expression.
"""
return other.value if isinstance(other, self.__class__) else other
|
def _return_result ( self , done ) : chain_future ( done , self . _running_future ) self . current_future = done self . current_index = self . _unfinished . pop ( done )
| 0 |
python yield how to know the function is finish
|
Called set the returned future s state that of the future we yielded and set the current future for the iterator .
|
cosqa-train-16440
|
def _return_result(self, done):
"""Called set the returned future's state that of the future
we yielded, and set the current future for the iterator.
"""
chain_future(done, self._running_future)
self.current_future = done
self.current_index = self._unfinished.pop(done)
|
def pprint ( obj , verbose = False , max_width = 79 , newline = '\n' ) : printer = RepresentationPrinter ( sys . stdout , verbose , max_width , newline ) printer . pretty ( obj ) printer . flush ( ) sys . stdout . write ( newline ) sys . stdout . flush ( )
| 0 |
limit character length on print python
|
Like pretty but print to stdout .
|
cosqa-train-16441
|
def pprint(obj, verbose=False, max_width=79, newline='\n'):
"""
Like `pretty` but print to stdout.
"""
printer = RepresentationPrinter(sys.stdout, verbose, max_width, newline)
printer.pretty(obj)
printer.flush()
sys.stdout.write(newline)
sys.stdout.flush()
|
def unzip_file_to_dir ( path_to_zip , output_directory ) : z = ZipFile ( path_to_zip , 'r' ) z . extractall ( output_directory ) z . close ( )
| 0 |
python zipfile unzip to folder
|
Extract a ZIP archive to a directory
|
cosqa-train-16442
|
def unzip_file_to_dir(path_to_zip, output_directory):
"""
Extract a ZIP archive to a directory
"""
z = ZipFile(path_to_zip, 'r')
z.extractall(output_directory)
z.close()
|
def _get_xy_scaling_parameters ( self ) : return self . mx , self . bx , self . my , self . by
| 0 |
limit x and y python
|
Get the X / Y coordinate limits for the full resulting image
|
cosqa-train-16443
|
def _get_xy_scaling_parameters(self):
"""Get the X/Y coordinate limits for the full resulting image"""
return self.mx, self.bx, self.my, self.by
|
def start ( self , test_connection = True ) : if self . _context is None : self . _logger . debug ( 'Starting Client' ) self . _context = zmq . Context ( ) self . _poll = zmq . Poller ( ) self . _start_socket ( ) if test_connection : self . test_ping ( )
| 1 |
python zmq check if connected
|
Starts connection to server if not existent .
|
cosqa-train-16444
|
def start(self, test_connection=True):
"""Starts connection to server if not existent.
NO-OP if connection is already established.
Makes ping-pong test as well if desired.
"""
if self._context is None:
self._logger.debug('Starting Client')
self._context = zmq.Context()
self._poll = zmq.Poller()
self._start_socket()
if test_connection:
self.test_ping()
|
def open01 ( x , limit = 1.e-6 ) : try : return np . array ( [ min ( max ( y , limit ) , 1. - limit ) for y in x ] ) except TypeError : return min ( max ( x , limit ) , 1. - limit )
| 0 |
limiting a floating number range python
|
Constrain numbers to ( 0 1 ) interval
|
cosqa-train-16445
|
def open01(x, limit=1.e-6):
"""Constrain numbers to (0,1) interval"""
try:
return np.array([min(max(y, limit), 1. - limit) for y in x])
except TypeError:
return min(max(x, limit), 1. - limit)
|
def init_mq ( self ) : mq = self . init_connection ( ) self . init_consumer ( mq ) return mq . connection
| 0 |
python zmq fork new connection
|
Init connection and consumer with openstack mq .
|
cosqa-train-16446
|
def init_mq(self):
"""Init connection and consumer with openstack mq."""
mq = self.init_connection()
self.init_consumer(mq)
return mq.connection
|
def _on_text_changed ( self ) : if not self . _cleaning : ln = TextHelper ( self ) . cursor_position ( ) [ 0 ] self . _modified_lines . add ( ln )
| 0 |
line edit changed signal python
|
Adjust dirty flag depending on editor s content
|
cosqa-train-16447
|
def _on_text_changed(self):
""" Adjust dirty flag depending on editor's content """
if not self._cleaning:
ln = TextHelper(self).cursor_position()[0]
self._modified_lines.add(ln)
|
def qsize ( self ) : self . mutex . acquire ( ) n = self . _qsize ( ) self . mutex . release ( ) return n
| 0 |
python zmq get queue length
|
Return the approximate size of the queue ( not reliable! ) .
|
cosqa-train-16448
|
def qsize(self):
"""Return the approximate size of the queue (not reliable!)."""
self.mutex.acquire()
n = self._qsize()
self.mutex.release()
return n
|
def _linearInterpolationTransformMatrix ( matrix1 , matrix2 , value ) : return tuple ( _interpolateValue ( matrix1 [ i ] , matrix2 [ i ] , value ) for i in range ( len ( matrix1 ) ) )
| 0 |
linear interpolation of 3 arrays in python
|
Linear oldstyle interpolation of the transform matrix .
|
cosqa-train-16449
|
def _linearInterpolationTransformMatrix(matrix1, matrix2, value):
""" Linear, 'oldstyle' interpolation of the transform matrix."""
return tuple(_interpolateValue(matrix1[i], matrix2[i], value) for i in range(len(matrix1)))
|
def clean ( some_string , uppercase = False ) : if uppercase : return some_string . strip ( ) . upper ( ) else : return some_string . strip ( ) . lower ( )
| 0 |
python, accepting a string input as upper or lower case
|
helper to clean up an input string
|
cosqa-train-16450
|
def clean(some_string, uppercase=False):
"""
helper to clean up an input string
"""
if uppercase:
return some_string.strip().upper()
else:
return some_string.strip().lower()
|
def stack_as_string ( ) : if sys . version_info . major == 3 : stack = io . StringIO ( ) else : stack = io . BytesIO ( ) traceback . print_stack ( file = stack ) stack . seek ( 0 ) stack = stack . read ( ) return stack
| 0 |
linux python3 stack trace
|
stack_as_string
|
cosqa-train-16451
|
def stack_as_string():
"""
stack_as_string
"""
if sys.version_info.major == 3:
stack = io.StringIO()
else:
stack = io.BytesIO()
traceback.print_stack(file=stack)
stack.seek(0)
stack = stack.read()
return stack
|
def qsize ( self ) : self . mutex . acquire ( ) n = self . _qsize ( ) self . mutex . release ( ) return n
| 1 |
python, get the size of the queue
|
Return the approximate size of the queue ( not reliable! ) .
|
cosqa-train-16452
|
def qsize(self):
"""Return the approximate size of the queue (not reliable!)."""
self.mutex.acquire()
n = self._qsize()
self.mutex.release()
return n
|
def get_previous_month ( self ) : end = utils . get_month_start ( ) - relativedelta ( days = 1 ) end = utils . to_datetime ( end ) start = utils . get_month_start ( end ) return start , end
| 0 |
list following months entered in python
|
Returns date range for the previous full month .
|
cosqa-train-16453
|
def get_previous_month(self):
"""Returns date range for the previous full month."""
end = utils.get_month_start() - relativedelta(days=1)
end = utils.to_datetime(end)
start = utils.get_month_start(end)
return start, end
|
def shape_list ( l , shape , dtype ) : return np . array ( l , dtype = dtype ) . reshape ( shape )
| 1 |
python, reshape a list to array
|
Shape a list of lists into the appropriate shape and data type
|
cosqa-train-16454
|
def shape_list(l,shape,dtype):
""" Shape a list of lists into the appropriate shape and data type """
return np.array(l, dtype=dtype).reshape(shape)
|
def append_position_to_token_list ( token_list ) : return [ PositionToken ( value . content , value . gd , index , index + 1 ) for ( index , value ) in enumerate ( token_list ) ]
| 1 |
list of a list of tokens python
|
Converts a list of Token into a list of Token asuming size == 1
|
cosqa-train-16455
|
def append_position_to_token_list(token_list):
"""Converts a list of Token into a list of Token, asuming size == 1"""
return [PositionToken(value.content, value.gd, index, index+1) for (index, value) in enumerate(token_list)]
|
def ms_to_datetime ( ms ) : dt = datetime . datetime . utcfromtimestamp ( ms / 1000 ) return dt . replace ( microsecond = ( ms % 1000 ) * 1000 ) . replace ( tzinfo = pytz . utc )
| 0 |
python, time to milliseconds
|
Converts a millisecond accuracy timestamp to a datetime
|
cosqa-train-16456
|
def ms_to_datetime(ms):
"""
Converts a millisecond accuracy timestamp to a datetime
"""
dt = datetime.datetime.utcfromtimestamp(ms / 1000)
return dt.replace(microsecond=(ms % 1000) * 1000).replace(tzinfo=pytz.utc)
|
def display_list_by_prefix ( names_list , starting_spaces = 0 ) : cur_prefix , result_lines = None , [ ] space = " " * starting_spaces for name in sorted ( names_list ) : split = name . split ( "_" , 1 ) prefix = split [ 0 ] if cur_prefix != prefix : result_lines . append ( space + prefix + ":" ) cur_prefix = prefix result_lines . append ( space + " * " + name ) return "\n" . join ( result_lines )
| 1 |
list of prefixes and show as headers python
|
Creates a help string for names_list grouped by prefix .
|
cosqa-train-16457
|
def display_list_by_prefix(names_list, starting_spaces=0):
"""Creates a help string for names_list grouped by prefix."""
cur_prefix, result_lines = None, []
space = " " * starting_spaces
for name in sorted(names_list):
split = name.split("_", 1)
prefix = split[0]
if cur_prefix != prefix:
result_lines.append(space + prefix + ":")
cur_prefix = prefix
result_lines.append(space + " * " + name)
return "\n".join(result_lines)
|
def _get_random_id ( ) : symbols = string . ascii_uppercase + string . ascii_lowercase + string . digits return '' . join ( random . choice ( symbols ) for _ in range ( 15 ) )
| 1 |
python3 create random unique identifier
|
Get a random ( i . e . unique ) string identifier
|
cosqa-train-16458
|
def _get_random_id():
""" Get a random (i.e., unique) string identifier"""
symbols = string.ascii_uppercase + string.ascii_lowercase + string.digits
return ''.join(random.choice(symbols) for _ in range(15))
|
def is_iterable ( value ) : return isinstance ( value , np . ndarray ) or isinstance ( value , list ) or isinstance ( value , tuple ) , value
| 1 |
list or nd array type check python
|
must be an iterable ( list array tuple )
|
cosqa-train-16459
|
def is_iterable(value):
"""must be an iterable (list, array, tuple)"""
return isinstance(value, np.ndarray) or isinstance(value, list) or isinstance(value, tuple), value
|
def cint32_array_to_numpy ( cptr , length ) : if isinstance ( cptr , ctypes . POINTER ( ctypes . c_int32 ) ) : return np . fromiter ( cptr , dtype = np . int32 , count = length ) else : raise RuntimeError ( 'Expected int pointer' )
| 0 |
python3 ctypes pointer of array
|
Convert a ctypes int pointer array to a numpy array .
|
cosqa-train-16460
|
def cint32_array_to_numpy(cptr, length):
"""Convert a ctypes int pointer array to a numpy array."""
if isinstance(cptr, ctypes.POINTER(ctypes.c_int32)):
return np.fromiter(cptr, dtype=np.int32, count=length)
else:
raise RuntimeError('Expected int pointer')
|
def flatten_array ( grid ) : grid = [ grid [ i ] [ j ] for i in range ( len ( grid ) ) for j in range ( len ( grid [ i ] ) ) ] while type ( grid [ 0 ] ) is list : grid = flatten_array ( grid ) return grid
| 0 |
list python numpy flatten
|
Takes a multi - dimensional array and returns a 1 dimensional array with the same contents .
|
cosqa-train-16461
|
def flatten_array(grid):
"""
Takes a multi-dimensional array and returns a 1 dimensional array with the
same contents.
"""
grid = [grid[i][j] for i in range(len(grid)) for j in range(len(grid[i]))]
while type(grid[0]) is list:
grid = flatten_array(grid)
return grid
|
def get_md5_for_file ( file ) : md5 = hashlib . md5 ( ) while True : data = file . read ( md5 . block_size ) if not data : break md5 . update ( data ) return md5 . hexdigest ( )
| 0 |
python3 get file md5
|
Get the md5 hash for a file .
|
cosqa-train-16462
|
def get_md5_for_file(file):
"""Get the md5 hash for a file.
:param file: the file to get the md5 hash for
"""
md5 = hashlib.md5()
while True:
data = file.read(md5.block_size)
if not data:
break
md5.update(data)
return md5.hexdigest()
|
def get_iter_string_reader ( stdin ) : bufsize = 1024 iter_str = ( stdin [ i : i + bufsize ] for i in range ( 0 , len ( stdin ) , bufsize ) ) return get_iter_chunk_reader ( iter_str )
| 1 |
python3 how read a stream buffer without eof
|
return an iterator that returns a chunk of a string every time it is called . notice that even though bufsize_type might be line buffered we re not doing any line buffering here . that s because our StreamBufferer handles all buffering . we just need to return a reasonable - sized chunk .
|
cosqa-train-16463
|
def get_iter_string_reader(stdin):
""" return an iterator that returns a chunk of a string every time it is
called. notice that even though bufsize_type might be line buffered, we're
not doing any line buffering here. that's because our StreamBufferer
handles all buffering. we just need to return a reasonable-sized chunk. """
bufsize = 1024
iter_str = (stdin[i:i + bufsize] for i in range(0, len(stdin), bufsize))
return get_iter_chunk_reader(iter_str)
|
def _get_all_constants ( ) : return [ key for key in globals ( ) . keys ( ) if all ( [ not key . startswith ( "_" ) , # publicly accesible key . upper ( ) == key , # uppercase type ( globals ( ) [ key ] ) in _ALLOWED # and with type from _ALLOWED ] ) ]
| 0 |
list the constants in a python file dynamically
|
Get list of all uppercase non - private globals ( doesn t start with _ ) .
|
cosqa-train-16464
|
def _get_all_constants():
"""
Get list of all uppercase, non-private globals (doesn't start with ``_``).
Returns:
list: Uppercase names defined in `globals()` (variables from this \
module).
"""
return [
key for key in globals().keys()
if all([
not key.startswith("_"), # publicly accesible
key.upper() == key, # uppercase
type(globals()[key]) in _ALLOWED # and with type from _ALLOWED
])
]
|
def dedupe_list ( l ) : result = [ ] for el in l : if el not in result : result . append ( el ) return result
| 1 |
python3 how to remove multiple items from a list
|
Remove duplicates from a list preserving the order .
|
cosqa-train-16465
|
def dedupe_list(l):
"""Remove duplicates from a list preserving the order.
We might be tempted to use the list(set(l)) idiom, but it doesn't preserve
the order, which hinders testability and does not work for lists with
unhashable elements.
"""
result = []
for el in l:
if el not in result:
result.append(el)
return result
|
def recarray ( self ) : return numpy . rec . fromrecords ( self . records , names = self . names )
| 0 |
list to np array in python without add additional dimension
|
Returns data as : class : numpy . recarray .
|
cosqa-train-16466
|
def recarray(self):
"""Returns data as :class:`numpy.recarray`."""
return numpy.rec.fromrecords(self.records, names=self.names)
|
def ip_address_list ( ips ) : # first, try it as a single IP address try : return ip_address ( ips ) except ValueError : pass # then, consider it as an ipaddress.IPv[4|6]Network instance and expand it return list ( ipaddress . ip_network ( u ( ips ) ) . hosts ( ) )
| 0 |
python3 ip expand cidr notations
|
IP address range validation and expansion .
|
cosqa-train-16467
|
def ip_address_list(ips):
""" IP address range validation and expansion. """
# first, try it as a single IP address
try:
return ip_address(ips)
except ValueError:
pass
# then, consider it as an ipaddress.IPv[4|6]Network instance and expand it
return list(ipaddress.ip_network(u(ips)).hosts())
|
def be_array_from_bytes ( fmt , data ) : arr = array . array ( str ( fmt ) , data ) return fix_byteorder ( arr )
| 0 |
load in data as bytearray python
|
Reads an array from bytestring with big - endian data .
|
cosqa-train-16468
|
def be_array_from_bytes(fmt, data):
"""
Reads an array from bytestring with big-endian data.
"""
arr = array.array(str(fmt), data)
return fix_byteorder(arr)
|
def polite_string ( a_string ) : if is_py3 ( ) and hasattr ( a_string , 'decode' ) : try : return a_string . decode ( 'utf-8' ) except UnicodeDecodeError : return a_string return a_string
| 0 |
python3 not equal string
|
Returns a proper string that should work in both Py3 / Py2
|
cosqa-train-16469
|
def polite_string(a_string):
"""Returns a "proper" string that should work in both Py3/Py2"""
if is_py3() and hasattr(a_string, 'decode'):
try:
return a_string.decode('utf-8')
except UnicodeDecodeError:
return a_string
return a_string
|
def import_js ( path , lib_name , globals ) : with codecs . open ( path_as_local ( path ) , "r" , "utf-8" ) as f : js = f . read ( ) e = EvalJs ( ) e . execute ( js ) var = e . context [ 'var' ] globals [ lib_name ] = var . to_python ( )
| 0 |
load javascript file in python
|
Imports from javascript source file . globals is your globals ()
|
cosqa-train-16470
|
def import_js(path, lib_name, globals):
"""Imports from javascript source file.
globals is your globals()"""
with codecs.open(path_as_local(path), "r", "utf-8") as f:
js = f.read()
e = EvalJs()
e.execute(js)
var = e.context['var']
globals[lib_name] = var.to_python()
|
def paste ( cmd = paste_cmd , stdout = PIPE ) : return Popen ( cmd , stdout = stdout ) . communicate ( ) [ 0 ] . decode ( 'utf-8' )
| 1 |
python3 read linux clipboard
|
Returns system clipboard contents .
|
cosqa-train-16471
|
def paste(cmd=paste_cmd, stdout=PIPE):
"""Returns system clipboard contents.
"""
return Popen(cmd, stdout=stdout).communicate()[0].decode('utf-8')
|
def Load ( file ) : with open ( file , 'rb' ) as file : model = dill . load ( file ) return model
| 1 |
loading a file in python
|
Loads a model from specified file
|
cosqa-train-16472
|
def Load(file):
""" Loads a model from specified file """
with open(file, 'rb') as file:
model = dill.load(file)
return model
|
def py3round ( number ) : if abs ( round ( number ) - number ) == 0.5 : return int ( 2.0 * round ( number / 2.0 ) ) return int ( round ( number ) )
| 0 |
python3 round comparison float
|
Unified rounding in all python versions .
|
cosqa-train-16473
|
def py3round(number):
"""Unified rounding in all python versions."""
if abs(round(number) - number) == 0.5:
return int(2.0 * round(number / 2.0))
return int(round(number))
|
def delete_lines ( self ) : cursor = self . textCursor ( ) self . __select_text_under_cursor_blocks ( cursor ) cursor . removeSelectedText ( ) cursor . deleteChar ( ) return True
| 0 |
python3 select all text in a text document and delete text
|
Deletes the document lines under cursor .
|
cosqa-train-16474
|
def delete_lines(self):
"""
Deletes the document lines under cursor.
:return: Method success.
:rtype: bool
"""
cursor = self.textCursor()
self.__select_text_under_cursor_blocks(cursor)
cursor.removeSelectedText()
cursor.deleteChar()
return True
|
def __enter__ ( self ) : self . fd = open ( self . filename , 'a' ) fcntl . lockf ( self . fd , fcntl . LOCK_EX ) return self . fd
| 0 |
lock the file python
|
Acquire a lock on the output file prevents collisions between multiple runs .
|
cosqa-train-16475
|
def __enter__(self):
"""Acquire a lock on the output file, prevents collisions between multiple runs."""
self.fd = open(self.filename, 'a')
fcntl.lockf(self.fd, fcntl.LOCK_EX)
return self.fd
|
def to_bytes ( value ) : vtype = type ( value ) if vtype == bytes or vtype == type ( None ) : return value try : return vtype . encode ( value ) except UnicodeEncodeError : pass return value
| 0 |
python3 string byte enciode
|
str to bytes ( py3k )
|
cosqa-train-16476
|
def to_bytes(value):
""" str to bytes (py3k) """
vtype = type(value)
if vtype == bytes or vtype == type(None):
return value
try:
return vtype.encode(value)
except UnicodeEncodeError:
pass
return value
|
def ln_norm ( x , mu , sigma = 1.0 ) : return np . log ( stats . norm ( loc = mu , scale = sigma ) . pdf ( x ) )
| 0 |
log normal distribution in python
|
Natural log of scipy norm function truncated at zero
|
cosqa-train-16477
|
def ln_norm(x, mu, sigma=1.0):
""" Natural log of scipy norm function truncated at zero """
return np.log(stats.norm(loc=mu, scale=sigma).pdf(x))
|
def _run_cmd_get_output ( cmd ) : process = subprocess . Popen ( cmd . split ( ) , stdout = subprocess . PIPE ) out , err = process . communicate ( ) return out or err
| 0 |
python3 subprocess get stdout text
|
Runs a shell command returns console output .
|
cosqa-train-16478
|
def _run_cmd_get_output(cmd):
"""Runs a shell command, returns console output.
Mimics python3's subprocess.getoutput
"""
process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE)
out, err = process.communicate()
return out or err
|
def cric__lasso ( ) : model = sklearn . linear_model . LogisticRegression ( penalty = "l1" , C = 0.002 ) # we want to explain the raw probability outputs of the trees model . predict = lambda X : model . predict_proba ( X ) [ : , 1 ] return model
| 0 |
logistic regression lasso python
|
Lasso Regression
|
cosqa-train-16479
|
def cric__lasso():
""" Lasso Regression
"""
model = sklearn.linear_model.LogisticRegression(penalty="l1", C=0.002)
# we want to explain the raw probability outputs of the trees
model.predict = lambda X: model.predict_proba(X)[:,1]
return model
|
def unique ( transactions ) : seen = set ( ) # TODO: Handle comments return [ x for x in transactions if not ( x in seen or seen . add ( x ) ) ]
| 0 |
python3 syntax for deletin g duplicate entries
|
Remove any duplicate entries .
|
cosqa-train-16480
|
def unique(transactions):
""" Remove any duplicate entries. """
seen = set()
# TODO: Handle comments
return [x for x in transactions if not (x in seen or seen.add(x))]
|
def survival ( value = t , lam = lam , f = failure ) : return sum ( f * log ( lam ) - lam * value )
| 0 |
logistic regression overflow python
|
Exponential survival likelihood accounting for censoring
|
cosqa-train-16481
|
def survival(value=t, lam=lam, f=failure):
"""Exponential survival likelihood, accounting for censoring"""
return sum(f * log(lam) - lam * value)
|
def to_identifier ( s ) : if s . startswith ( 'GPS' ) : s = 'Gps' + s [ 3 : ] return '' . join ( [ i . capitalize ( ) for i in s . split ( '_' ) ] ) if '_' in s else s
| 0 |
pythone code to make first and last letter of string capital
|
Convert snake_case to camel_case .
|
cosqa-train-16482
|
def to_identifier(s):
"""
Convert snake_case to camel_case.
"""
if s.startswith('GPS'):
s = 'Gps' + s[3:]
return ''.join([i.capitalize() for i in s.split('_')]) if '_' in s else s
|
def get_longest_orf ( orfs ) : sorted_orf = sorted ( orfs , key = lambda x : len ( x [ 'sequence' ] ) , reverse = True ) [ 0 ] return sorted_orf
| 0 |
longest non decreasing subsequence python
|
Find longest ORF from the given list of ORFs .
|
cosqa-train-16483
|
def get_longest_orf(orfs):
"""Find longest ORF from the given list of ORFs."""
sorted_orf = sorted(orfs, key=lambda x: len(x['sequence']), reverse=True)[0]
return sorted_orf
|
def get_table_columns ( dbconn , tablename ) : cur = dbconn . cursor ( ) cur . execute ( "PRAGMA table_info('%s');" % tablename ) info = cur . fetchall ( ) cols = [ ( i [ 1 ] , i [ 2 ] ) for i in info ] return cols
| 1 |
pythong mysql how to get column names
|
Return a list of tuples specifying the column name and type
|
cosqa-train-16484
|
def get_table_columns(dbconn, tablename):
"""
Return a list of tuples specifying the column name and type
"""
cur = dbconn.cursor()
cur.execute("PRAGMA table_info('%s');" % tablename)
info = cur.fetchall()
cols = [(i[1], i[2]) for i in info]
return cols
|
def strip_spaces ( s ) : return u" " . join ( [ c for c in s . split ( u' ' ) if c ] )
| 0 |
loooping through a string with white spaces python
|
Strip excess spaces from a string
|
cosqa-train-16485
|
def strip_spaces(s):
""" Strip excess spaces from a string """
return u" ".join([c for c in s.split(u' ') if c])
|
def is_non_empty_string ( input_string ) : try : if not input_string . strip ( ) : raise ValueError ( ) except AttributeError as error : raise TypeError ( error ) return True
| 1 |
pythonic way to check if a string is empty
|
Validate if non empty string
|
cosqa-train-16486
|
def is_non_empty_string(input_string):
"""
Validate if non empty string
:param input_string: Input is a *str*.
:return: True if input is string and non empty.
Raise :exc:`Exception` otherwise.
"""
try:
if not input_string.strip():
raise ValueError()
except AttributeError as error:
raise TypeError(error)
return True
|
def _unordered_iterator ( self ) : for i , qs in zip ( self . _queryset_idxs , self . _querysets ) : for item in qs : setattr ( item , '#' , i ) yield item
| 0 |
loop through queryset python
|
Return the value of each QuerySet but also add the # property to each return item .
|
cosqa-train-16487
|
def _unordered_iterator(self):
"""
Return the value of each QuerySet, but also add the '#' property to each
return item.
"""
for i, qs in zip(self._queryset_idxs, self._querysets):
for item in qs:
setattr(item, '#', i)
yield item
|
def handle_qbytearray ( obj , encoding ) : if isinstance ( obj , QByteArray ) : obj = obj . data ( ) return to_text_string ( obj , encoding = encoding )
| 0 |
qbytearray to python str
|
Qt / Python2 / 3 compatibility helper .
|
cosqa-train-16488
|
def handle_qbytearray(obj, encoding):
"""Qt/Python2/3 compatibility helper."""
if isinstance(obj, QByteArray):
obj = obj.data()
return to_text_string(obj, encoding=encoding)
|
def searchlast ( self , n = 10 ) : solutions = deque ( [ ] , n ) for solution in self : solutions . append ( solution ) return solutions
| 0 |
loops through the last n elements python
|
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-16489
|
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 search ( self , filterstr , attrlist ) : return self . _paged_search_ext_s ( self . settings . BASE , ldap . SCOPE_SUBTREE , filterstr = filterstr , attrlist = attrlist , page_size = self . settings . PAGE_SIZE )
| 1 |
query server objects ldap in python
|
Query the configured LDAP server .
|
cosqa-train-16490
|
def search(self, filterstr, attrlist):
"""Query the configured LDAP server."""
return self._paged_search_ext_s(self.settings.BASE, ldap.SCOPE_SUBTREE, filterstr=filterstr,
attrlist=attrlist, page_size=self.settings.PAGE_SIZE)
|
def osx_clipboard_get ( ) : p = subprocess . Popen ( [ 'pbpaste' , '-Prefer' , 'ascii' ] , stdout = subprocess . PIPE ) text , stderr = p . communicate ( ) # Text comes in with old Mac \r line endings. Change them to \n. text = text . replace ( '\r' , '\n' ) return text
| 0 |
mac python clean clipboard
|
Get the clipboard s text on OS X .
|
cosqa-train-16491
|
def osx_clipboard_get():
""" Get the clipboard's text on OS X.
"""
p = subprocess.Popen(['pbpaste', '-Prefer', 'ascii'],
stdout=subprocess.PIPE)
text, stderr = p.communicate()
# Text comes in with old Mac \r line endings. Change them to \n.
text = text.replace('\r', '\n')
return text
|
def urlencoded ( body , charset = 'ascii' , * * kwargs ) : return parse_query_string ( text ( body , charset = charset ) , False )
| 1 |
querystring to url python
|
Converts query strings into native Python objects
|
cosqa-train-16492
|
def urlencoded(body, charset='ascii', **kwargs):
"""Converts query strings into native Python objects"""
return parse_query_string(text(body, charset=charset), False)
|
def magnitude ( X ) : r = np . real ( X ) i = np . imag ( X ) return np . sqrt ( r * r + i * i )
| 0 |
magnitude of matrix exponential python
|
Magnitude of a complex matrix .
|
cosqa-train-16493
|
def magnitude(X):
"""Magnitude of a complex matrix."""
r = np.real(X)
i = np.imag(X)
return np.sqrt(r * r + i * i);
|
def pack_triples_numpy ( triples ) : if len ( triples ) == 0 : return np . array ( [ ] , dtype = np . int64 ) return np . stack ( list ( map ( _transform_triple_numpy , triples ) ) , axis = 0 )
| 0 |
quick way to make a python array with sequence without forloop
|
Packs a list of triple indexes into a 2D numpy array .
|
cosqa-train-16494
|
def pack_triples_numpy(triples):
"""Packs a list of triple indexes into a 2D numpy array."""
if len(triples) == 0:
return np.array([], dtype=np.int64)
return np.stack(list(map(_transform_triple_numpy, triples)), axis=0)
|
def image_set_aspect ( aspect = 1.0 , axes = "gca" ) : if axes is "gca" : axes = _pylab . gca ( ) e = axes . get_images ( ) [ 0 ] . get_extent ( ) axes . set_aspect ( abs ( ( e [ 1 ] - e [ 0 ] ) / ( e [ 3 ] - e [ 2 ] ) ) / aspect )
| 0 |
maintaining an aspect ration in gridspec python
|
sets the aspect ratio of the current zoom level of the imshow image
|
cosqa-train-16495
|
def image_set_aspect(aspect=1.0, axes="gca"):
"""
sets the aspect ratio of the current zoom level of the imshow image
"""
if axes is "gca": axes = _pylab.gca()
e = axes.get_images()[0].get_extent()
axes.set_aspect(abs((e[1]-e[0])/(e[3]-e[2]))/aspect)
|
def positive_integer ( anon , obj , field , val ) : return anon . faker . positive_integer ( field = field )
| 1 |
random int except a number python
|
Returns a random positive integer ( for a Django PositiveIntegerField )
|
cosqa-train-16496
|
def positive_integer(anon, obj, field, val):
"""
Returns a random positive integer (for a Django PositiveIntegerField)
"""
return anon.faker.positive_integer(field=field)
|
def str_dict ( some_dict ) : return { str ( k ) : str ( v ) for k , v in some_dict . items ( ) }
| 0 |
make a dict a string python
|
Convert dict of ascii str / unicode to dict of str if necessary
|
cosqa-train-16497
|
def str_dict(some_dict):
"""Convert dict of ascii str/unicode to dict of str, if necessary"""
return {str(k): str(v) for k, v in some_dict.items()}
|
def runiform ( lower , upper , size = None ) : return np . random . uniform ( lower , upper , size )
| 0 |
random number of a given range python
|
Random uniform variates .
|
cosqa-train-16498
|
def runiform(lower, upper, size=None):
"""
Random uniform variates.
"""
return np.random.uniform(lower, upper, size)
|
def stringify_dict_contents ( dct ) : return { str_if_nested_or_str ( k ) : str_if_nested_or_str ( v ) for k , v in dct . items ( ) }
| 0 |
make a dictionary a string in python
|
Turn dict keys and values into native strings .
|
cosqa-train-16499
|
def stringify_dict_contents(dct):
"""Turn dict keys and values into native strings."""
return {
str_if_nested_or_str(k): str_if_nested_or_str(v)
for k, v in dct.items()
}
|
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