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def register_on_guest_keyboard ( self , callback ) : """Set the callback function to consume on guest keyboard events Callback receives a IGuestKeyboardEvent object . Example : def callback ( event ) : print ( event . scancodes )"""
return self . event_source . register_callback ( callback , library . VBoxEventType . on_guest_keyboard )
def get_and_clear_context ( self ) : """Get and clean all of our broks , actions , external commands and homerun : return : list of all broks of the satellite link : rtype : list"""
res = ( self . broks , self . actions , self . wait_homerun , self . pushed_commands ) self . broks = [ ] self . actions = { } self . wait_homerun = { } self . pushed_commands = [ ] return res
def _check_module_is_image_embedding ( module_spec ) : """Raises ValueError if ` module _ spec ` is not usable as image embedding . Args : module _ spec : A ` _ ModuleSpec ` to test . Raises : ValueError : if ` module _ spec ` default signature is not compatible with mappingan " images " input to a Tensor ( float32 , shape = ( _ , K ) ) ."""
issues = [ ] # Find issues with " default " signature inputs . The common signatures for # image models prescribe a specific name ; we trust it if we find it # and if we can do the necessary inference of input shapes from it . input_info_dict = module_spec . get_input_info_dict ( ) if ( list ( input_info_dict . keys ( ) ) != [ "images" ] or input_info_dict [ "images" ] . dtype != tf . float32 ) : issues . append ( "Module 'default' signature must require a single input, " "which must have type float32 and name 'images'." ) else : try : image_util . get_expected_image_size ( module_spec ) except ValueError as e : issues . append ( "Module does not support hub.get_expected_image_size(); " "original error was:\n" + str ( e ) ) # Raised again below . # Find issues with " default " signature outputs . We test that the dtype and # shape is appropriate for use in input _ layer ( ) . output_info_dict = module_spec . get_output_info_dict ( ) if "default" not in output_info_dict : issues . append ( "Module 'default' signature must have a 'default' output." ) else : output_type = output_info_dict [ "default" ] . dtype output_shape = output_info_dict [ "default" ] . get_shape ( ) if not ( output_type == tf . float32 and output_shape . ndims == 2 and output_shape . dims [ 1 ] . value ) : issues . append ( "Module 'default' signature must have a 'default' output " "of tf.Tensor(shape=(_,K), dtype=float32)." ) if issues : raise ValueError ( "Module is not usable as image embedding: %r" % issues )
def get_processing_block_ids ( self ) : """Get list of processing block ids using the processing block id"""
# Initialise empty list _processing_block_ids = [ ] # Pattern used to search processing block ids pattern = '*:processing_block:*' block_ids = self . _db . get_ids ( pattern ) for block_id in block_ids : id_split = block_id . split ( ':' ) [ - 1 ] _processing_block_ids . append ( id_split ) return sorted ( _processing_block_ids )
def has_credentials ( self ) : """Does this session have valid credentials : rtype : bool"""
return all ( [ getattr ( self , '_%s' % field , None ) is not None for field in self . CredentialMap . get ( self . provider_name ) ] )
def save ( self , * args , ** kwargs ) : """when creating a new record fill CPU and RAM info if available"""
adding_new = False if not self . pk or ( not self . cpu and not self . ram ) : # if self . model . cpu is not empty if self . model . cpu : self . cpu = self . model . cpu # if self . model . ram is not empty if self . model . ram : self . ram = self . model . ram # mark to add a new antenna adding_new = True # perform save super ( DeviceToModelRel , self ) . save ( * args , ** kwargs ) # after Device2Model object has been saved try : # does the device model have an integrated antenna ? antenna_model = self . model . antennamodel except AntennaModel . DoesNotExist : # if not antenna _ model is False antenna_model = False # if we are adding a new device2model and the device model has an integrated antenna if adding_new and antenna_model : # create new Antenna object antenna = Antenna ( device = self . device , model = self . model . antennamodel ) # retrieve wireless interfaces and assign it to the antenna object if possible wireless_interfaces = self . device . interface_set . filter ( type = 2 ) if len ( wireless_interfaces ) > 0 : antenna . radio = wireless_interfaces [ 0 ] # save antenna antenna . save ( )
def pca_ellipse ( data , loc = None , ax = None , ** ellipse_kwargs ) : '''Finds the 2d PCA ellipse of given data and plots it . loc : center of the ellipse [ default : mean of the data ]'''
from sklearn . decomposition import PCA # Late import ; sklearn is optional pca = PCA ( n_components = 2 ) . fit ( data ) if loc is None : loc = pca . mean_ if ax is None : ax = plt . gca ( ) cov = pca . explained_variance_ * pca . components_ . T u , s , v = np . linalg . svd ( cov ) width , height = 2 * np . sqrt ( s [ : 2 ] ) angle = np . rad2deg ( np . arctan2 ( u [ 1 , 0 ] , u [ 0 , 0 ] ) ) ell = Ellipse ( xy = loc , width = width , height = height , angle = angle , ** ellipse_kwargs ) ax . add_patch ( ell ) return ell
def partitioned_iterator ( self , partition_size , shuffle = True , seed = None ) : """Return a partitioning : class : ` audiomate . feeding . FrameIterator ` for the dataset . Args : partition _ size ( str ) : Size of the partitions in bytes . The units ` ` k ` ` ( kibibytes ) , ` ` m ` ` ( mebibytes ) and ` ` g ` ` ( gibibytes ) are supported , i . e . a ` ` partition _ size ` ` of ` ` 1g ` ` equates : math : ` 2 ^ { 30 } ` bytes . shuffle ( bool ) : Indicates whether the data should be returned in random order ( ` ` True ` ` ) or not ( ` ` False ` ` ) . seed ( int ) : Seed to be used for the random number generator . Returns : FrameIterator : A partition iterator over the dataset ."""
return iterator . FrameIterator ( self . utt_ids , self . containers , partition_size , shuffle = shuffle , seed = seed )
def check ( self ) : """Determine how long until the next scheduled time for a Task . Returns the number of seconds until the next scheduled time or zero if the task needs to be run immediately . If it ' s an hourly task and it ' s never been run , run it now . If it ' s a daily task and it ' s never been run and the hour is right , run it now ."""
boto . log . info ( 'checking Task[%s]-now=%s, last=%s' % ( self . name , self . now , self . last_executed ) ) if self . hourly and not self . last_executed : return 0 if self . daily and not self . last_executed : if int ( self . hour ) == self . now . hour : return 0 else : return max ( ( int ( self . hour ) - self . now . hour ) , ( self . now . hour - int ( self . hour ) ) ) * 60 * 60 delta = self . now - self . last_executed if self . hourly : if delta . seconds >= 60 * 60 : return 0 else : return 60 * 60 - delta . seconds else : if int ( self . hour ) == self . now . hour : if delta . days >= 1 : return 0 else : return 82800 # 23 hours , just to be safe else : return max ( ( int ( self . hour ) - self . now . hour ) , ( self . now . hour - int ( self . hour ) ) ) * 60 * 60
def percentile_between ( self , min_percentile , max_percentile , mask = NotSpecified ) : """Construct a new Filter representing entries from the output of this Factor that fall within the percentile range defined by min _ percentile and max _ percentile . Parameters min _ percentile : float [ 0.0 , 100.0] Return True for assets falling above this percentile in the data . max _ percentile : float [ 0.0 , 100.0] Return True for assets falling below this percentile in the data . mask : zipline . pipeline . Filter , optional A Filter representing assets to consider when percentile calculating thresholds . If mask is supplied , percentile cutoffs are computed each day using only assets for which ` ` mask ` ` returns True . Assets for which ` ` mask ` ` produces False will produce False in the output of this Factor as well . Returns out : zipline . pipeline . filters . PercentileFilter A new filter that will compute the specified percentile - range mask . See Also zipline . pipeline . filters . filter . PercentileFilter"""
return PercentileFilter ( self , min_percentile = min_percentile , max_percentile = max_percentile , mask = mask , )
def logEndTime ( ) : """Write end info to log"""
logger . info ( '\n' + '#' * 70 ) logger . info ( 'Complete' ) logger . info ( datetime . today ( ) . strftime ( "%A, %d %B %Y %I:%M%p" ) ) logger . info ( '#' * 70 + '\n' )
def _valid_packet ( raw_packet ) : """Validate incoming packet ."""
if raw_packet [ 0 : 1 ] != b'\xcc' : return False if len ( raw_packet ) != 19 : return False checksum = 0 for i in range ( 1 , 17 ) : checksum += raw_packet [ i ] if checksum != raw_packet [ 18 ] : return False return True
def _get_label_encoder_and_max ( self , x ) : """Return a mapping from values and its maximum of a column to integer labels . Args : x ( pandas . Series ) : a categorical column to encode . Returns : label _ encoder ( dict ) : mapping from values of features to integers max _ label ( int ) : maximum label"""
# NaN cannot be used as a key for dict . So replace it with a random integer . label_count = x . fillna ( NAN_INT ) . value_counts ( ) n_uniq = label_count . shape [ 0 ] label_count = label_count [ label_count >= self . min_obs ] n_uniq_new = label_count . shape [ 0 ] # If every label appears more than min _ obs , new label starts from 0. # Otherwise , new label starts from 1 and 0 is used for all old labels # that appear less than min _ obs . offset = 0 if n_uniq == n_uniq_new else 1 label_encoder = pd . Series ( np . arange ( n_uniq_new ) + offset , index = label_count . index ) max_label = label_encoder . max ( ) label_encoder = label_encoder . to_dict ( ) return label_encoder , max_label
def from_pandas ( cls , index ) : """Create baloo Index from pandas Index . Parameters index : pandas . base . Index Returns Index"""
from pandas import Index as PandasIndex check_type ( index , PandasIndex ) return Index ( index . values , index . dtype , index . name )
def _get_key_info ( self ) : """Get key info appropriate for signing ."""
if self . _key_info_cache is None : self . _key_info_cache = agent_key_info_from_key_id ( self . key_id ) return self . _key_info_cache
def _observe_keep_screen_on ( self , change ) : """Sets or clears the flag to keep the screen on ."""
def set_screen_on ( window ) : from . android_window import Window window = Window ( __id__ = window ) if self . keep_screen_on : window . addFlags ( Window . FLAG_KEEP_SCREEN_ON ) else : window . clearFlags ( Window . FLAG_KEEP_SCREEN_ON ) self . widget . getWindow ( ) . then ( set_screen_on )
def open_if_exists ( filename , mode = 'rb' ) : """Returns a file descriptor for the filename if that file exists , otherwise ` None ` ."""
try : return open ( filename , mode ) except IOError , e : if e . errno not in ( errno . ENOENT , errno . EISDIR ) : raise
def get_rva_from_offset ( self , offset ) : """Get the RVA corresponding to this file offset ."""
s = self . get_section_by_offset ( offset ) if not s : if self . sections : lowest_rva = min ( [ adjust_SectionAlignment ( s . VirtualAddress , self . OPTIONAL_HEADER . SectionAlignment , self . OPTIONAL_HEADER . FileAlignment ) for s in self . sections ] ) if offset < lowest_rva : # We will assume that the offset lies within the headers , or # at least points before where the earliest section starts # and we will simply return the offset as the RVA # The case illustrating this behavior can be found at : # http : / / corkami . blogspot . com / 2010/01 / hey - hey - hey - whats - in - your - head . html # where the import table is not contained by any section # hence the RVA needs to be resolved to a raw offset return offset else : return offset # raise PEFormatError ( " specified offset ( 0x % x ) doesn ' t belong to any section . " % offset ) return s . get_rva_from_offset ( offset )
def mode_yubikey_otp ( self , private_uid , aes_key ) : """Set the YubiKey up for standard OTP validation ."""
if not self . capabilities . have_yubico_OTP ( ) : raise yubikey_base . YubiKeyVersionError ( 'Yubico OTP not available in %s version %d.%d' % ( self . capabilities . model , self . ykver [ 0 ] , self . ykver [ 1 ] ) ) if private_uid . startswith ( b'h:' ) : private_uid = binascii . unhexlify ( private_uid [ 2 : ] ) if len ( private_uid ) != yubikey_defs . UID_SIZE : raise yubico_exception . InputError ( 'Private UID must be %i bytes' % ( yubikey_defs . UID_SIZE ) ) self . _change_mode ( 'YUBIKEY_OTP' , major = 0 , minor = 9 ) self . uid = private_uid self . aes_key ( aes_key )
def calculate_normals ( vertices ) : """Return Nx3 normal array from Nx3 vertex array ."""
verts = np . array ( vertices , dtype = float ) normals = np . zeros_like ( verts ) for start , end in pairwise ( np . arange ( 0 , verts . shape [ 0 ] + 1 , 3 ) ) : vecs = np . vstack ( ( verts [ start + 1 ] - verts [ start ] , verts [ start + 2 ] - verts [ start ] ) ) # Get triangle of vertices and calculate 2-1 and 3-1 vecs /= np . linalg . norm ( vecs , axis = 1 , keepdims = True ) # normalize vectors normal = np . cross ( * vecs ) # normal is the cross products of vectors . normals [ start : end , : ] = normal / np . linalg . norm ( normal ) return normals
def generate_make_string ( out_f , max_step ) : """Generate the make _ string template"""
steps = [ 2 ** n for n in xrange ( int ( math . log ( max_step , 2 ) ) , - 1 , - 1 ) ] with Namespace ( out_f , [ 'boost' , 'metaparse' , 'v{0}' . format ( VERSION ) , 'impl' ] ) as nsp : generate_take ( out_f , steps , nsp . prefix ( ) ) out_f . write ( '{0}template <int LenNow, int LenRemaining, char... Cs>\n' '{0}struct make_string;\n' '\n' '{0}template <char... Cs>' ' struct make_string<0, 0, Cs...> : string<> {{}};\n' . format ( nsp . prefix ( ) ) ) disable_sun = False for i in reversed ( steps ) : if i > 64 and not disable_sun : out_f . write ( '#ifndef __SUNPRO_CC\n' ) disable_sun = True out_f . write ( '{0}template <int LenRemaining,{1}char... Cs>' ' struct make_string<{2},LenRemaining,{3}Cs...> :' ' concat<string<{4}>,' ' typename make_string<take(LenRemaining),' 'LenRemaining-take(LenRemaining),Cs...>::type> {{}};\n' . format ( nsp . prefix ( ) , '' . join ( 'char {0},' . format ( n ) for n in unique_names ( i ) ) , i , '' . join ( '{0},' . format ( n ) for n in unique_names ( i ) ) , ',' . join ( unique_names ( i ) ) ) ) if disable_sun : out_f . write ( '#endif\n' )
def make_ndarray ( tensor ) : """Create a numpy ndarray from a tensor . Create a numpy ndarray with the same shape and data as the tensor . Args : tensor : A TensorProto . Returns : A numpy array with the tensor contents . Raises : TypeError : if tensor has unsupported type ."""
shape = [ d . size for d in tensor . tensor_shape . dim ] num_elements = np . prod ( shape , dtype = np . int64 ) tensor_dtype = dtypes . as_dtype ( tensor . dtype ) dtype = tensor_dtype . as_numpy_dtype if tensor . tensor_content : return np . frombuffer ( tensor . tensor_content , dtype = dtype ) . copy ( ) . reshape ( shape ) elif tensor_dtype == dtypes . float16 or tensor_dtype == dtypes . bfloat16 : # the half _ val field of the TensorProto stores the binary representation # of the fp16 : we need to reinterpret this as a proper float16 if len ( tensor . half_val ) == 1 : tmp = np . array ( tensor . half_val [ 0 ] , dtype = np . uint16 ) tmp . dtype = tensor_dtype . as_numpy_dtype return np . repeat ( tmp , num_elements ) . reshape ( shape ) else : tmp = np . fromiter ( tensor . half_val , dtype = np . uint16 ) tmp . dtype = tensor_dtype . as_numpy_dtype return tmp . reshape ( shape ) elif tensor_dtype == dtypes . float32 : if len ( tensor . float_val ) == 1 : return np . repeat ( np . array ( tensor . float_val [ 0 ] , dtype = dtype ) , num_elements ) . reshape ( shape ) else : return np . fromiter ( tensor . float_val , dtype = dtype ) . reshape ( shape ) elif tensor_dtype == dtypes . float64 : if len ( tensor . double_val ) == 1 : return np . repeat ( np . array ( tensor . double_val [ 0 ] , dtype = dtype ) , num_elements ) . reshape ( shape ) else : return np . fromiter ( tensor . double_val , dtype = dtype ) . reshape ( shape ) elif tensor_dtype in [ dtypes . int32 , dtypes . uint8 , dtypes . uint16 , dtypes . int16 , dtypes . int8 , dtypes . qint32 , dtypes . quint8 , dtypes . qint8 , dtypes . qint16 , dtypes . quint16 , ] : if len ( tensor . int_val ) == 1 : return np . repeat ( np . array ( tensor . int_val [ 0 ] , dtype = dtype ) , num_elements ) . reshape ( shape ) else : return np . fromiter ( tensor . int_val , dtype = dtype ) . reshape ( shape ) elif tensor_dtype == dtypes . int64 : if len ( tensor . int64_val ) == 1 : return np . repeat ( np . array ( tensor . int64_val [ 0 ] , dtype = dtype ) , num_elements ) . reshape ( shape ) else : return np . fromiter ( tensor . int64_val , dtype = dtype ) . reshape ( shape ) elif tensor_dtype == dtypes . string : if len ( tensor . string_val ) == 1 : return np . repeat ( np . array ( tensor . string_val [ 0 ] , dtype = dtype ) , num_elements ) . reshape ( shape ) else : return np . array ( [ x for x in tensor . string_val ] , dtype = dtype ) . reshape ( shape ) elif tensor_dtype == dtypes . complex64 : it = iter ( tensor . scomplex_val ) if len ( tensor . scomplex_val ) == 2 : return np . repeat ( np . array ( complex ( tensor . scomplex_val [ 0 ] , tensor . scomplex_val [ 1 ] ) , dtype = dtype ) , num_elements , ) . reshape ( shape ) else : return np . array ( [ complex ( x [ 0 ] , x [ 1 ] ) for x in zip ( it , it ) ] , dtype = dtype ) . reshape ( shape ) elif tensor_dtype == dtypes . complex128 : it = iter ( tensor . dcomplex_val ) if len ( tensor . dcomplex_val ) == 2 : return np . repeat ( np . array ( complex ( tensor . dcomplex_val [ 0 ] , tensor . dcomplex_val [ 1 ] ) , dtype = dtype ) , num_elements , ) . reshape ( shape ) else : return np . array ( [ complex ( x [ 0 ] , x [ 1 ] ) for x in zip ( it , it ) ] , dtype = dtype ) . reshape ( shape ) elif tensor_dtype == dtypes . bool : if len ( tensor . bool_val ) == 1 : return np . repeat ( np . array ( tensor . bool_val [ 0 ] , dtype = dtype ) , num_elements ) . reshape ( shape ) else : return np . fromiter ( tensor . bool_val , dtype = dtype ) . reshape ( shape ) else : raise TypeError ( "Unsupported tensor type: %s" % tensor . dtype )
def poll ( target , step , args = ( ) , kwargs = None , timeout = None , max_tries = None , check_success = is_truthy , step_function = step_constant , ignore_exceptions = ( ) , poll_forever = False , collect_values = None , * a , ** k ) : """Poll by calling a target function until a certain condition is met . You must specify at least a target function to be called and the step - - base wait time between each function call . : param step : Step defines the amount of time to wait ( in seconds ) : param args : Arguments to be passed to the target function : type kwargs : dict : param kwargs : Keyword arguments to be passed to the target function : param timeout : The target function will be called until the time elapsed is greater than the maximum timeout ( in seconds ) . NOTE that the actual execution time of the function * can * exceed the time specified in the timeout . For instance , if the target function takes 10 seconds to execute and the timeout is 21 seconds , the polling function will take a total of 30 seconds ( two iterations of the target - - 20s which is less than the timeout - - 21s , and a final iteration ) : param max _ tries : Maximum number of times the target function will be called before failing : param check _ success : A callback function that accepts the return value of the target function . It should return true if you want the polling function to stop and return this value . It should return false if you want it to continue executing . The default is a callback that tests for truthiness ( anything not False , 0 , or empty collection ) . : param step _ function : A callback function that accepts each iteration ' s " step . " By default , this is constant , but you can also pass a function that will increase or decrease the step . As an example , you can increase the wait time between calling the target function by 10 seconds every iteration until the step is 100 seconds - - at which point it should remain constant at 100 seconds > > > def my _ step _ function ( step ) : > > > step + = 10 > > > return max ( step , 100) : type ignore _ exceptions : tuple : param ignore _ exceptions : You can specify a tuple of exceptions that should be caught and ignored on every iteration . If the target function raises one of these exceptions , it will be caught and the exception instance will be pushed to the queue of values collected during polling . Any other exceptions raised will be raised as normal . : param poll _ forever : If set to true , this function will retry until an exception is raised or the target ' s return value satisfies the check _ success function . If this is not set , then a timeout or a max _ tries must be set . : type collect _ values : Queue : param collect _ values : By default , polling will create a new Queue to store all of the target ' s return values . Optionally , you can specify your own queue to collect these values for access to it outside of function scope . : return : Polling will return first value from the target function that meets the condions of the check _ success callback . By default , this will be the first value that is not None , 0 , False , ' ' , or an empty collection ."""
assert ( timeout is not None or max_tries is not None ) or poll_forever , ( 'You did not specify a maximum number of tries or a timeout. Without either of these set, the polling ' 'function will poll forever. If this is the behavior you want, pass "poll_forever=True"' ) assert not ( ( timeout is not None or max_tries is not None ) and poll_forever ) , 'You cannot specify both the option to poll_forever and max_tries/timeout.' kwargs = kwargs or dict ( ) values = collect_values or Queue ( ) max_time = time . time ( ) + timeout if timeout else None tries = 0 last_item = None while True : if max_tries is not None and tries >= max_tries : raise MaxCallException ( values , last_item ) try : val = target ( * args , ** kwargs ) last_item = val except ignore_exceptions as e : last_item = e else : # Condition passes , this is the only " successful " exit from the polling function if check_success ( val ) : return val values . put ( last_item ) tries += 1 # Check the time after to make sure the poll function is called at least once if max_time is not None and time . time ( ) >= max_time : raise TimeoutException ( values , last_item ) time . sleep ( step ) step = step_function ( step )
def visit_and_update ( self , visitor_fn ) : """Create an updated version ( if needed ) of BetweenClause via the visitor pattern ."""
new_lower_bound = self . lower_bound . visit_and_update ( visitor_fn ) new_upper_bound = self . upper_bound . visit_and_update ( visitor_fn ) if new_lower_bound is not self . lower_bound or new_upper_bound is not self . upper_bound : return visitor_fn ( BetweenClause ( self . field , new_lower_bound , new_upper_bound ) ) else : return visitor_fn ( self )
def get_channel ( self , name ) : """Get a channel by name . To get the names , use get _ channels . : param string name : Name of channel to get : returns dict conn : A channel attribute dictionary ."""
name = quote ( name , '' ) path = Client . urls [ 'channels_by_name' ] % name chan = self . _call ( path , 'GET' ) return chan
def relative_to ( self , * other ) : """Return the relative path to another path identified by the passed arguments . If the operation is not possible ( because this is not a subpath of the other path ) , raise ValueError ."""
# For the purpose of this method , drive and root are considered # separate parts , i . e . : # Path ( ' c : / ' ) . relative _ to ( ' c : ' ) gives Path ( ' / ' ) # Path ( ' c : / ' ) . relative _ to ( ' / ' ) raise ValueError if not other : raise TypeError ( "need at least one argument" ) parts = self . _parts drv = self . _drv root = self . _root if root : abs_parts = [ drv , root ] + parts [ 1 : ] else : abs_parts = parts to_drv , to_root , to_parts = self . _parse_args ( other ) if to_root : to_abs_parts = [ to_drv , to_root ] + to_parts [ 1 : ] else : to_abs_parts = to_parts n = len ( to_abs_parts ) cf = self . _flavour . casefold_parts if ( root or drv ) if n == 0 else cf ( abs_parts [ : n ] ) != cf ( to_abs_parts ) : formatted = self . _format_parsed_parts ( to_drv , to_root , to_parts ) raise ValueError ( "{!r} does not start with {!r}" . format ( str ( self ) , str ( formatted ) ) ) return self . _from_parsed_parts ( '' , root if n == 1 else '' , abs_parts [ n : ] )
def create_cloud_user ( cfg , args ) : """Attempt to create the user on the cloud node ."""
url = cfg [ 'api_server' ] + "admin/add-user" params = { 'user_email' : args . user_email , 'user_name' : args . user_name , 'user_role' : args . user_role , 'email' : cfg [ 'email' ] , 'api_key' : cfg [ 'api_key' ] } headers = { 'Content-Type' : 'application/json' } response = requests . post ( url , data = json . dumps ( params ) , headers = headers ) if response . status_code not in range ( 200 , 299 ) : raise Exception ( "Errors contacting the cloud node: %s" % ( response . content ) ) loaded = json . loads ( response . content ) return loaded
def fetch ( self , transfer_id , data = { } , ** kwargs ) : """Fetch Transfer for given Id Args : transfer _ id : Id for which transfer object has to be retrieved Returns : Transfer dict for given transfer Id"""
return super ( Transfer , self ) . fetch ( transfer_id , data , ** kwargs )
def set_keywords ( self , keywords ) : """Pass an array to filter the result by keywords . : param keywords"""
self . _query_params += str ( QueryParam . KEYWORDS ) + '+' . join ( keywords )
def get_osds ( service , device_class = None ) : """Return a list of all Ceph Object Storage Daemons currently in the cluster ( optionally filtered by storage device class ) . : param device _ class : Class of storage device for OSD ' s : type device _ class : str"""
luminous_or_later = cmp_pkgrevno ( 'ceph-common' , '12.0.0' ) >= 0 if luminous_or_later and device_class : out = check_output ( [ 'ceph' , '--id' , service , 'osd' , 'crush' , 'class' , 'ls-osd' , device_class , '--format=json' ] ) else : out = check_output ( [ 'ceph' , '--id' , service , 'osd' , 'ls' , '--format=json' ] ) if six . PY3 : out = out . decode ( 'UTF-8' ) return json . loads ( out )
def vertices ( self ) : '''A dictionary of four points where the axes intersect the ellipse , dict .'''
return { 'a' : self . a , 'a_neg' : self . a_neg , 'b' : self . b , 'b_neg' : self . b_neg }
def rot_rads ( self , rads ) : """Rotate vector by angle in radians ."""
new_x = self . x * math . cos ( rads ) - self . y * math . sin ( rads ) self . y = self . x * math . sin ( rads ) + self . y * math . cos ( rads ) self . x = new_x
def set_position_target_local_ned_send ( self , time_boot_ms , target_system , target_component , coordinate_frame , type_mask , x , y , z , vx , vy , vz , afx , afy , afz , yaw , yaw_rate , force_mavlink1 = False ) : '''Sets a desired vehicle position in a local north - east - down coordinate frame . Used by an external controller to command the vehicle ( manual controller or other system ) . time _ boot _ ms : Timestamp in milliseconds since system boot ( uint32 _ t ) target _ system : System ID ( uint8 _ t ) target _ component : Component ID ( uint8 _ t ) coordinate _ frame : Valid options are : MAV _ FRAME _ LOCAL _ NED = 1 , MAV _ FRAME _ LOCAL _ OFFSET _ NED = 7 , MAV _ FRAME _ BODY _ NED = 8 , MAV _ FRAME _ BODY _ OFFSET _ NED = 9 ( uint8 _ t ) type _ mask : Bitmask to indicate which dimensions should be ignored by the vehicle : a value of 0b00000 or 0b00000100000 indicates that none of the setpoint dimensions should be ignored . If bit 10 is set the floats afx afy afz should be interpreted as force instead of acceleration . Mapping : bit 1 : x , bit 2 : y , bit 3 : z , bit 4 : vx , bit 5 : vy , bit 6 : vz , bit 7 : ax , bit 8 : ay , bit 9 : az , bit 10 : is force setpoint , bit 11 : yaw , bit 12 : yaw rate ( uint16 _ t ) x : X Position in NED frame in meters ( float ) y : Y Position in NED frame in meters ( float ) z : Z Position in NED frame in meters ( note , altitude is negative in NED ) ( float ) vx : X velocity in NED frame in meter / s ( float ) vy : Y velocity in NED frame in meter / s ( float ) vz : Z velocity in NED frame in meter / s ( float ) afx : X acceleration or force ( if bit 10 of type _ mask is set ) in NED frame in meter / s ^ 2 or N ( float ) afy : Y acceleration or force ( if bit 10 of type _ mask is set ) in NED frame in meter / s ^ 2 or N ( float ) afz : Z acceleration or force ( if bit 10 of type _ mask is set ) in NED frame in meter / s ^ 2 or N ( float ) yaw : yaw setpoint in rad ( float ) yaw _ rate : yaw rate setpoint in rad / s ( float )'''
return self . send ( self . set_position_target_local_ned_encode ( time_boot_ms , target_system , target_component , coordinate_frame , type_mask , x , y , z , vx , vy , vz , afx , afy , afz , yaw , yaw_rate ) , force_mavlink1 = force_mavlink1 )
def projection ( self , exprs ) : """Like mutate , but do not include existing table columns"""
w = self . _get_window ( ) windowed_exprs = [ ] exprs = self . table . _resolve ( exprs ) for expr in exprs : expr = L . windowize_function ( expr , w = w ) windowed_exprs . append ( expr ) return self . table . projection ( windowed_exprs )
def replace_negative_size_with_batch_size ( shape , batch_size ) : """Replace all dimensions with negative values to batch size"""
sl = [ ] for d in shape . dim : if d < 0 : # Negative size means batch size sl . append ( batch_size ) else : sl . append ( d ) out_shape = nnabla_pb2 . Shape ( ) out_shape . dim . extend ( sl ) return out_shape
def deprecated_opts_signature ( args , kwargs ) : """Utility to help with the deprecation of the old . opts method signature Returns whether opts . apply _ groups should be used ( as a bool ) and the corresponding options ."""
from . options import Options groups = set ( Options . _option_groups ) opts = { kw for kw in kwargs if kw != 'clone' } apply_groups = False options = None new_kwargs = { } if len ( args ) > 0 and isinstance ( args [ 0 ] , dict ) : apply_groups = True if ( not set ( args [ 0 ] ) . issubset ( groups ) and all ( isinstance ( v , dict ) and not set ( v ) . issubset ( groups ) for v in args [ 0 ] . values ( ) ) ) : apply_groups = False elif set ( args [ 0 ] . keys ( ) ) <= groups : new_kwargs = args [ 0 ] else : options = args [ 0 ] elif opts and opts . issubset ( set ( groups ) ) : apply_groups = True elif kwargs . get ( 'options' , None ) is not None : apply_groups = True elif not args and not kwargs : apply_groups = True return apply_groups , options , new_kwargs
def reduce_hierarchy ( x , depth ) : """Reduce the hierarchy ( depth by ` | ` ) string to the specified level"""
_x = x . split ( '|' ) depth = len ( _x ) + depth - 1 if depth < 0 else depth return '|' . join ( _x [ 0 : ( depth + 1 ) ] )
def unique ( seq ) : """Return the unique values in a sequence . Parameters seq : sequence Sequence with ( possibly duplicate ) elements . Returns unique : list Unique elements of ` ` seq ` ` . Order is guaranteed to be the same as in seq . Examples Determine unique elements in list > > > unique ( [ 1 , 2 , 3 , 3 ] ) [1 , 2 , 3] > > > unique ( ( 1 , ' str ' , ' str ' ) ) [1 , ' str ' ] The utility also works with unhashable types : > > > unique ( ( 1 , [ 1 ] , [ 1 ] ) ) [1 , [ 1 ] ]"""
# First check if all elements are hashable , if so O ( n ) can be done try : return list ( OrderedDict . fromkeys ( seq ) ) except TypeError : # Unhashable , resort to O ( n ^ 2) unique_values = [ ] for i in seq : if i not in unique_values : unique_values . append ( i ) return unique_values
def get_authorizations_ids_by_vault ( self , vault_ids ) : """Gets the list of ` ` Authorization Ids ` ` corresponding to a list of ` ` Vault ` ` objects . arg : vault _ ids ( osid . id . IdList ) : list of vault ` ` Ids ` ` return : ( osid . id . IdList ) - list of authorization ` ` Ids ` ` raise : NullArgument - ` ` vault _ ids ` ` is ` ` null ` ` raise : OperationFailed - unable to complete request raise : PermissionDenied - authorization failure * compliance : mandatory - - This method must be implemented . *"""
# Implemented from template for # osid . resource . ResourceBinSession . get _ resource _ ids _ by _ bin id_list = [ ] for authorization in self . get_authorizations_by_vault ( vault_ids ) : id_list . append ( authorization . get_id ( ) ) return IdList ( id_list )
def generate_all_kmers ( k ) : """Generate all possible k - mers Example : > > > generate _ all _ kmers ( 2) [ ' AA ' , ' AC ' , ' AG ' , ' AT ' , ' CA ' , ' CC ' , ' CG ' , ' CT ' , ' GA ' , ' GC ' , ' GG ' , ' GT ' , ' TA ' , ' TC ' , ' TG ' , ' TT ' ]"""
bases = [ 'A' , 'C' , 'G' , 'T' ] return [ '' . join ( p ) for p in itertools . product ( bases , repeat = k ) ]
def do_prune ( self ) : """Return True if prune _ table , prune _ column , and prune _ date are implemented . If only a subset of prune variables are override , an exception is raised to remind the user to implement all or none . Prune ( data newer than prune _ date deleted ) before copying new data in ."""
if self . prune_table and self . prune_column and self . prune_date : return True elif self . prune_table or self . prune_column or self . prune_date : raise Exception ( 'override zero or all prune variables' ) else : return False
def row ( values , width = WIDTH , format_spec = FMT , align = ALIGN , style = STYLE ) : """Returns a formatted row of data Parameters values : array _ like An iterable array of data ( numbers or strings ) , each value is printed in a separate column width : int The width of each column ( Default : 11) format _ spec : string The precision format string used to format numbers in the values array ( Default : ' 5g ' ) align : string The alignment to use ( ' left ' , ' center ' , or ' right ' ) . ( Default : ' right ' ) style : namedtuple , optional A line formatting style Returns rowstr : string A string consisting of the full row of data to print"""
tablestyle = STYLES [ style ] widths = parse_width ( width , len ( values ) ) assert isinstance ( format_spec , string_types ) | isinstance ( format_spec , list ) , "format_spec must be a string or list of strings" if isinstance ( format_spec , string_types ) : format_spec = [ format_spec ] * len ( list ( values ) ) # mapping function for string formatting def mapdata ( val ) : # unpack width , datum , prec = val if isinstance ( datum , string_types ) : return ( '{:%s%i}' % ( ALIGNMENTS [ align ] , width + ansi_len ( datum ) ) ) . format ( datum ) elif isinstance ( datum , Number ) : return ( '{:%s%i.%s}' % ( ALIGNMENTS [ align ] , width , prec ) ) . format ( datum ) else : raise ValueError ( 'Elements in the values array must be strings, ints, or floats' ) # string formatter data = map ( mapdata , zip ( widths , values , format_spec ) ) # build the row string return format_line ( data , tablestyle . row )
def do_cp ( self , line ) : """cp SOURCE DEST Copy a single SOURCE file to DEST file . cp SOURCE . . . DIRECTORY Copy multiple SOURCE files to a directory . cp [ - r | - - recursive ] [ SOURCE | SOURCE _ DIR ] . . . DIRECTORY cp [ - r ] PATTERN DIRECTORY Copy matching files to DIRECTORY . The destination must be a directory except in the case of copying a single file . To copy directories - r must be specified . This will cause directories and their contents to be recursively copied ."""
args = self . line_to_args ( line ) if len ( args . filenames ) < 2 : print_err ( 'Missing destination file' ) return dst_dirname = resolve_path ( args . filenames [ - 1 ] ) dst_mode = auto ( get_mode , dst_dirname ) d_dst = { } # Destination directory : lookup stat by basename if args . recursive : dst_files = auto ( listdir_stat , dst_dirname ) if dst_files is None : err = "cp: target {} is not a directory" print_err ( err . format ( dst_dirname ) ) return for name , stat in dst_files : d_dst [ name ] = stat src_filenames = args . filenames [ : - 1 ] # Process PATTERN sfn = src_filenames [ 0 ] if is_pattern ( sfn ) : if len ( src_filenames ) > 1 : print_err ( "Usage: cp [-r] PATTERN DIRECTORY" ) return src_filenames = process_pattern ( sfn ) if src_filenames is None : return for src_filename in src_filenames : if is_pattern ( src_filename ) : print_err ( "Only one pattern permitted." ) return src_filename = resolve_path ( src_filename ) src_mode = auto ( get_mode , src_filename ) if not mode_exists ( src_mode ) : print_err ( "File '{}' doesn't exist" . format ( src_filename ) ) return if mode_isdir ( src_mode ) : if args . recursive : # Copying a directory src_basename = os . path . basename ( src_filename ) dst_filename = dst_dirname + '/' + src_basename if src_basename in d_dst : dst_stat = d_dst [ src_basename ] dst_mode = stat_mode ( dst_stat ) if not mode_isdir ( dst_mode ) : err = "Destination {} is not a directory" print_err ( err . format ( dst_filename ) ) return else : if not mkdir ( dst_filename ) : err = "Unable to create directory {}" print_err ( err . format ( dst_filename ) ) return rsync ( src_filename , dst_filename , mirror = False , dry_run = False , print_func = lambda * args : None , recursed = False , sync_hidden = args . all ) else : print_err ( "Omitting directory {}" . format ( src_filename ) ) continue if mode_isdir ( dst_mode ) : dst_filename = dst_dirname + '/' + os . path . basename ( src_filename ) else : dst_filename = dst_dirname if not cp ( src_filename , dst_filename ) : err = "Unable to copy '{}' to '{}'" print_err ( err . format ( src_filename , dst_filename ) ) break
def get ( self , deviceId , measurementId ) : """details the specific measurement ."""
record = self . measurements . get ( deviceId ) if record is not None : return record . get ( measurementId ) return None
def face_normals ( self ) : """Return the unit normal vector for each face . If a face is degenerate and a normal can ' t be generated a zero magnitude unit vector will be returned for that face . Returns normals : ( len ( self . faces ) , 3 ) np . float64 Normal vectors of each face"""
# check shape of cached normals cached = self . _cache [ 'face_normals' ] if np . shape ( cached ) == np . shape ( self . _data [ 'faces' ] ) : return cached log . debug ( 'generating face normals' ) # use cached triangle cross products to generate normals # this will always return the correct shape but some values # will be zero or an arbitrary vector if the inputs had # a cross product below machine epsilon normals , valid = triangles . normals ( triangles = self . triangles , crosses = self . triangles_cross ) # if all triangles are valid shape is correct if valid . all ( ) : # put calculated face normals into cache manually self . _cache [ 'face_normals' ] = normals return normals # make a padded list of normals for correct shape padded = np . zeros ( ( len ( self . triangles ) , 3 ) , dtype = np . float64 ) padded [ valid ] = normals # put calculated face normals into cache manually self . _cache [ 'face_normals' ] = padded return padded
def heartbeat ( request ) : """Runs all the Django checks and returns a JsonResponse with either a status code of 200 or 500 depending on the results of the checks . Any check that returns a warning or worse ( error , critical ) will return a 500 response ."""
all_checks = checks . registry . registry . get_checks ( include_deployment_checks = not settings . DEBUG , ) details = { } statuses = { } level = 0 for check in all_checks : detail = heartbeat_check_detail ( check ) statuses [ check . __name__ ] = detail [ 'status' ] level = max ( level , detail [ 'level' ] ) if detail [ 'level' ] > 0 : details [ check . __name__ ] = detail if level < checks . messages . WARNING : status_code = 200 heartbeat_passed . send ( sender = heartbeat , level = level ) else : status_code = 500 heartbeat_failed . send ( sender = heartbeat , level = level ) payload = { 'status' : level_to_text ( level ) , 'checks' : statuses , 'details' : details , } return JsonResponse ( payload , status = status_code )
def get_overlays ( self , ** kw ) : """See Overlay . match ( ) for arguments ."""
return [ o for o in self . overlays if o . match ( ** kw ) ]
def check_move ( new , old , t ) : """Determines if a model will be accepted ."""
if ( t <= 0 ) or numpy . isclose ( t , 0.0 ) : return False K_BOLTZ = 1.9872041E-003 # kcal / mol . K if new < old : return True else : move_prob = math . exp ( - ( new - old ) / ( K_BOLTZ * t ) ) if move_prob > random . uniform ( 0 , 1 ) : return True return False
def write_element ( elem_to_parse , file_or_path , encoding = DEFAULT_ENCODING ) : """Writes the contents of the parsed element to file _ or _ path : see : get _ element ( parent _ to _ parse , element _ path )"""
xml_header = '<?xml version="1.0" encoding="{0}"?>' . format ( encoding ) get_element_tree ( elem_to_parse ) . write ( file_or_path , encoding , xml_header )
def open ( self ) : """Open the URL with urllib . request ."""
url = self . url try : request = urllib . request . Request ( url ) handle = urllib . request . build_opener ( ) except IOError : return None return ( request , handle )
def to_text ( self ) : """Render a Table MessageElement as plain text . : returns : The text representation of the Table MessageElement : rtype : basestring"""
table = '' if self . caption is not None : table += '%s</caption>\n' % self . caption table += '\n' for row in self . rows : table += row . to_text ( ) return table
def set_computable_distance ( self , value ) : '''setter'''
if isinstance ( value , ComputableDistance ) is False : raise TypeError ( ) self . __computable_distance = value
def CheckRegistryKey ( javaKey ) : """Method checks for the java in the registry entries ."""
from _winreg import ConnectRegistry , HKEY_LOCAL_MACHINE , OpenKey , QueryValueEx path = None try : aReg = ConnectRegistry ( None , HKEY_LOCAL_MACHINE ) rk = OpenKey ( aReg , javaKey ) for i in range ( 1024 ) : currentVersion = QueryValueEx ( rk , "CurrentVersion" ) if currentVersion != None : key = OpenKey ( rk , currentVersion [ 0 ] ) if key != None : path = QueryValueEx ( key , "JavaHome" ) return path [ 0 ] except Exception , err : # TODO : Add Warning / Error messages in Logger . WriteUcsWarning ( "Not able to access registry." ) return None
def packet_meta_data ( self ) : """Pull out the metadata about each packet from the input _ stream Args : None Returns : generator ( dictionary ) : a generator that contains packet meta data in the form of a dictionary"""
# For each packet in the pcap process the contents for item in self . input_stream : # Output object output = { } # Grab the fields I need timestamp = item [ 'timestamp' ] buf = item [ 'raw_buf' ] # Print out the timestamp in UTC output [ 'timestamp' ] = datetime . datetime . utcfromtimestamp ( timestamp ) # Unpack the Ethernet frame ( mac src / dst , ethertype ) eth = dpkt . ethernet . Ethernet ( buf ) output [ 'eth' ] = { 'src' : eth . src , 'dst' : eth . dst , 'type' : eth . type , 'len' : len ( eth ) } # Grab packet data packet = eth . data # Packet Type ( ' EtherType ' ) ( IP , ARP , PPPoE , IP6 . . . see http : / / en . wikipedia . org / wiki / EtherType ) if hasattr ( packet , 'data' ) : output [ 'packet' ] = { 'type' : packet . __class__ . __name__ , 'data' : packet . data } else : output [ 'packet' ] = { 'type' : None , 'data' : None } # It this an IP packet ? if output [ 'packet' ] [ 'type' ] == 'IP' : # Pull out fragment information ( flags and offset all packed into off field , so use bitmasks ) df = bool ( packet . off & dpkt . ip . IP_DF ) mf = bool ( packet . off & dpkt . ip . IP_MF ) offset = packet . off & dpkt . ip . IP_OFFMASK # Pulling out src , dst , length , fragment info , TTL , checksum and Protocol output [ 'packet' ] . update ( { 'src' : packet . src , 'dst' : packet . dst , 'p' : packet . p , 'len' : packet . len , 'ttl' : packet . ttl , 'df' : df , 'mf' : mf , 'offset' : offset , 'checksum' : packet . sum } ) # Is this an IPv6 packet ? elif output [ 'packet' ] [ 'type' ] == 'IP6' : # Pulling out the IP6 fields output [ 'packet' ] . update ( { 'src' : packet . src , 'dst' : packet . dst , 'p' : packet . p , 'len' : packet . plen , 'ttl' : packet . hlim } ) # If the packet isn ' t IP or IPV6 just pack it as a dictionary else : output [ 'packet' ] . update ( data_utils . make_dict ( packet ) ) # For the transport layer we ' re going to set the transport to None . and # hopefully a ' link ' upstream will manage the transport functionality output [ 'transport' ] = None # For the application layer we ' re going to set the application to None . and # hopefully a ' link ' upstream will manage the application functionality output [ 'application' ] = None # All done yield output
def match_entries ( entries , pattern ) : """A drop - in replacement for fnmatch . filter that supports pattern variants ( ie . { foo , bar } baz = foobaz or barbaz ) ."""
matching = [ ] for variant in expand_braces ( pattern ) : matching . extend ( fnmatch . filter ( entries , variant ) ) return list ( _deduplicate ( matching ) )
def check_valence ( self ) : """check valences of all atoms : return : list of invalid atoms"""
return [ x for x , atom in self . atoms ( ) if not atom . check_valence ( self . environment ( x ) ) ]
def last_bookmark ( bookmarks ) : """The bookmark returned by the last : class : ` . Transaction ` ."""
last = None for bookmark in bookmarks : if last is None : last = bookmark else : last = _last_bookmark ( last , bookmark ) return last
def findConnectedDevices ( self ) : """Find all the devices on the serial buss and store the results in a class member object ."""
tmpTimeout = self . _serial . timeout self . _serial . timeout = 0.01 for dev in range ( 128 ) : device = self . _getDeviceID ( dev ) if device is not None and int ( device ) not in self . _deviceConfig : config = self . _deviceConfig . setdefault ( int ( device ) , { } ) self . _deviceCallback ( device , config ) self . _log and self . _log . info ( "Found device '%s' with configuration: %s" , device , config ) self . _serial . timeout = tmpTimeout
def U ( self ) : """Property to support lazy evaluation of residuals"""
if self . _U is None : sinv = N . diag ( 1 / self . singular_values ) self . _U = dot ( self . arr , self . V . T , sinv ) return self . _U
def add_arg ( self , arg ) : """Add an argument"""
if not isinstance ( arg , File ) : arg = str ( arg ) self . _args += [ arg ]
def _gen_explain_command ( coll , spec , projection , skip , limit , batch_size , options , read_concern ) : """Generate an explain command document ."""
cmd = _gen_find_command ( coll , spec , projection , skip , limit , batch_size , options ) if read_concern . level : return SON ( [ ( 'explain' , cmd ) , ( 'readConcern' , read_concern . document ) ] ) return SON ( [ ( 'explain' , cmd ) ] )
def client ( host = 'localhost' , port = 2379 , ca_cert = None , cert_key = None , cert_cert = None , timeout = None , user = None , password = None , grpc_options = None ) : """Return an instance of an Etcd3Client ."""
return Etcd3Client ( host = host , port = port , ca_cert = ca_cert , cert_key = cert_key , cert_cert = cert_cert , timeout = timeout , user = user , password = password , grpc_options = grpc_options )
def nodes_simple_info ( self , params = { } , ** kwargs ) : """Return a dictionary of the nodes simple info that key is a column name , such as [ { " http _ address " : " 192.111.111.111 " , " name " : " test " , . . . } , . . . ]"""
h = [ 'name' , 'pid' , 'http_address' , 'version' , 'jdk' , 'disk.total' , 'disk.used_percent' , 'heap.current' , 'heap.percent' , 'ram.current' , 'ram.percent' , 'uptime' , 'node.role' ] result = self . client . cat . nodes ( v = True , h = h , ** kwargs , params = params ) result = [ x . strip ( ) . split ( ' ' ) for x in result . split ( '\n' ) ] # Clean up the space result . remove ( result [ - 1 ] ) for i in range ( len ( result ) ) : result [ i ] = list ( filter ( lambda x : x != '' , result [ i ] ) ) # Packing into the dictionary dicts = [ ] for i in range ( len ( result ) - 1 ) : dict = { } for k , v in zip ( result [ 0 ] , result [ i + 1 ] ) : dict [ k ] = v dicts . append ( dict ) logger . info ( 'Acquire simple information of the nodes is done succeeded: %s' % len ( dicts ) ) return dicts
def clear_grade_system ( self ) : """Clears the grading system . raise : NoAccess - ` ` Metadata . isRequired ( ) ` ` or ` ` Metadata . isReadOnly ( ) ` ` is ` ` true ` ` * compliance : mandatory - - This method must be implemented . *"""
# Implemented from template for osid . resource . ResourceForm . clear _ avatar _ template if ( self . get_grade_system_metadata ( ) . is_read_only ( ) or self . get_grade_system_metadata ( ) . is_required ( ) ) : raise errors . NoAccess ( ) self . _my_map [ 'gradeSystemId' ] = self . _grade_system_default
def close ( self ) : """Collects the result from the workers and closes the thread pool ."""
self . pool . close ( ) self . pool . terminate ( ) self . pool . join ( )
def find_library_linux ( cls ) : """Loads the SEGGER DLL from the root directory . On Linux , the SEGGER tools are installed under the ` ` / opt / SEGGER ` ` directory with versioned directories having the suffix ` ` _ VERSION ` ` . Args : cls ( Library ) : the ` ` Library ` ` class Returns : The paths to the J - Link library files in the order that they are found ."""
dll = Library . JLINK_SDK_NAME root = os . path . join ( '/' , 'opt' , 'SEGGER' ) for ( directory_name , subdirs , files ) in os . walk ( root ) : fnames = [ ] x86_found = False for f in files : path = os . path . join ( directory_name , f ) if os . path . isfile ( path ) and f . startswith ( dll ) : fnames . append ( f ) if '_x86' in path : x86_found = True for fname in fnames : fpath = os . path . join ( directory_name , fname ) if util . is_os_64bit ( ) : if '_x86' not in fname : yield fpath elif x86_found : if '_x86' in fname : yield fpath else : yield fpath
def report_ports ( target , ports ) : """portscan a target and output a LaTeX table report _ ports ( target , ports ) - > string"""
ans , unans = sr ( IP ( dst = target ) / TCP ( dport = ports ) , timeout = 5 ) rep = "\\begin{tabular}{|r|l|l|}\n\\hline\n" for s , r in ans : if not r . haslayer ( ICMP ) : if r . payload . flags == 0x12 : rep += r . sprintf ( "%TCP.sport% & open & SA \\\\\n" ) rep += "\\hline\n" for s , r in ans : if r . haslayer ( ICMP ) : rep += r . sprintf ( "%TCPerror.dport% & closed & ICMP type %ICMP.type%/%ICMP.code% from %IP.src% \\\\\n" ) # noqa : E501 elif r . payload . flags != 0x12 : rep += r . sprintf ( "%TCP.sport% & closed & TCP %TCP.flags% \\\\\n" ) rep += "\\hline\n" for i in unans : rep += i . sprintf ( "%TCP.dport% & ? & unanswered \\\\\n" ) rep += "\\hline\n\\end{tabular}\n" return rep
def set_params ( self , subs = None , numticks = None ) : """Set parameters within this locator . Parameters subs : array , optional Subtick values , as multiples of the main ticks . numticks : array , optional Number of ticks ."""
if numticks is not None : self . numticks = numticks if subs is not None : self . _subs = subs
def json_conversion ( obj ) : """Encode additional objects to JSON ."""
try : # numpy isn ' t an explicit dependency of bowtie # so we can ' t assume it ' s available import numpy as np if isinstance ( obj , ( np . ndarray , np . generic ) ) : return obj . tolist ( ) except ImportError : pass try : # pandas isn ' t an explicit dependency of bowtie # so we can ' t assume it ' s available import pandas as pd if isinstance ( obj , pd . Index ) : return obj . tolist ( ) except ImportError : pass if isinstance ( obj , ( datetime , time , date ) ) : return obj . isoformat ( ) raise TypeError ( 'Not sure how to serialize {} of type {}' . format ( obj , type ( obj ) ) )
def safe_filepath ( file_path_name , dir_sep = None ) : '''Input the full path and filename , splits on directory separator and calls safe _ filename _ leaf for each part of the path . dir _ sep allows coder to force a directory separate to a particular character . . versionadded : : 2017.7.2 : codeauthor : Damon Atkins < https : / / github . com / damon - atkins >'''
if not dir_sep : dir_sep = os . sep # Normally if file _ path _ name or dir _ sep is Unicode then the output will be Unicode # This code ensure the output type is the same as file _ path _ name if not isinstance ( file_path_name , six . text_type ) and isinstance ( dir_sep , six . text_type ) : dir_sep = dir_sep . encode ( 'ascii' ) # This should not be executed under PY3 # splitdrive only set drive on windows platform ( drive , path ) = os . path . splitdrive ( file_path_name ) path = dir_sep . join ( [ safe_filename_leaf ( file_section ) for file_section in path . rsplit ( dir_sep ) ] ) if drive : path = dir_sep . join ( [ drive , path ] ) return path
async def dump_variant ( obj , elem , elem_type = None , params = None , field_archiver = None ) : """Transform variant to the popo object representation . : param obj : : param elem : : param elem _ type : : param params : : param field _ archiver : : return :"""
field_archiver = field_archiver if field_archiver else dump_field if isinstance ( elem , x . VariantType ) or elem_type . WRAPS_VALUE : return { elem . variant_elem : await field_archiver ( None , getattr ( elem , elem . variant_elem ) , elem . variant_elem_type ) } else : fdef = elem_type . find_fdef ( elem_type . f_specs ( ) , elem ) return { fdef [ 0 ] : await field_archiver ( None , elem , fdef [ 1 ] ) }
def process_pgturl ( self , params ) : """Handle PGT request : param dict params : A template context dict : raises ValidateError : if pgtUrl is invalid or if TLS validation of the pgtUrl fails : return : The rendering of ` ` cas _ server / serviceValidate . xml ` ` , using ` ` params ` ` : rtype : django . http . HttpResponse"""
try : pattern = ServicePattern . validate ( self . pgt_url ) if pattern . proxy_callback : proxyid = utils . gen_pgtiou ( ) pticket = ProxyGrantingTicket . objects . create ( user = self . ticket . user , service = self . pgt_url , service_pattern = pattern , single_log_out = pattern . single_log_out ) url = utils . update_url ( self . pgt_url , { 'pgtIou' : proxyid , 'pgtId' : pticket . value } ) try : ret = requests . get ( url , verify = settings . CAS_PROXY_CA_CERTIFICATE_PATH ) if ret . status_code == 200 : params [ 'proxyGrantingTicket' ] = proxyid else : pticket . delete ( ) logger . info ( ( "ValidateService: ticket %s validated for user %s on service %s. " "Proxy Granting Ticket transmited to %s." ) % ( self . ticket . value , self . ticket . user . username , self . ticket . service , self . pgt_url ) ) logger . debug ( "ValidateService: User attributs are:\n%s" % ( pprint . pformat ( self . ticket . attributs ) , ) ) return render ( self . request , "cas_server/serviceValidate.xml" , params , content_type = "text/xml; charset=utf-8" ) except requests . exceptions . RequestException as error : error = utils . unpack_nested_exception ( error ) raise ValidateError ( u'INVALID_PROXY_CALLBACK' , u"%s: %s" % ( type ( error ) , str ( error ) ) ) else : raise ValidateError ( u'INVALID_PROXY_CALLBACK' , u"callback url not allowed by configuration" ) except ServicePattern . DoesNotExist : raise ValidateError ( u'INVALID_PROXY_CALLBACK' , u'callback url not allowed by configuration' )
def toProtocolElement ( self ) : """Converts this rnaQuant into its GA4GH protocol equivalent ."""
protocolElement = protocol . RnaQuantificationSet ( ) protocolElement . id = self . getId ( ) protocolElement . dataset_id = self . _parentContainer . getId ( ) protocolElement . name = self . _name self . serializeAttributes ( protocolElement ) return protocolElement
def delete_group ( self , name ) : """Delete contact group : param name : of group : type name : ` ` str ` ` , ` ` unicode ` ` : rtype : ` ` bool ` `"""
group = self . get_group ( name ) method , url = get_URL ( 'group_delete' ) payload = { 'apikey' : self . config . get ( 'apikey' ) , 'logintoken' : self . session . cookies . get ( 'logintoken' ) , 'contactgroupid' : group [ 'contactgroupid' ] } res = getattr ( self . session , method ) ( url , params = payload ) if res . status_code == 200 : return True hellraiser ( res )
def addSquigglyAnnot ( self , rect ) : """Wavy underline content in a rectangle or quadrilateral ."""
CheckParent ( self ) val = _fitz . Page_addSquigglyAnnot ( self , rect ) if not val : return val . thisown = True val . parent = weakref . proxy ( self ) self . _annot_refs [ id ( val ) ] = val return val
def get_F1_EM ( dataset , predict_data ) : """Calculate the F1 and EM scores of the predicted results . Use only with the SQuAD1.1 dataset . Parameters dataset _ file : string Path to the data file . predict _ data : dict All final predictions . Returns scores : dict F1 and EM scores ."""
f1 = exact_match = total = 0 for record in dataset : total += 1 if record [ 1 ] not in predict_data : message = 'Unanswered question ' + record [ 1 ] + ' will receive score 0.' print ( message ) continue ground_truths = record [ 4 ] prediction = predict_data [ record [ 1 ] ] exact_match += metric_max_over_ground_truths ( exact_match_score , prediction , ground_truths ) f1 += metric_max_over_ground_truths ( f1_score , prediction , ground_truths ) exact_match = 100.0 * exact_match / total f1 = 100.0 * f1 / total scores = { 'exact_match' : exact_match , 'f1' : f1 } return scores
def get_archs ( libname ) : """Return architecture types from library ` libname ` Parameters libname : str filename of binary for which to return arch codes Returns arch _ names : frozenset Empty ( frozen ) set if no arch codes . If not empty , contains one or more of ' ppc ' , ' ppc64 ' , ' i386 ' , ' x86_64'"""
if not exists ( libname ) : raise RuntimeError ( libname + " is not a file" ) try : stdout = back_tick ( [ 'lipo' , '-info' , libname ] ) except RuntimeError : return frozenset ( ) lines = [ line . strip ( ) for line in stdout . split ( '\n' ) if line . strip ( ) ] # For some reason , output from lipo - info on . a file generates this line if lines [ 0 ] == "input file {0} is not a fat file" . format ( libname ) : line = lines [ 1 ] else : assert len ( lines ) == 1 line = lines [ 0 ] for reggie in ( 'Non-fat file: {0} is architecture: (.*)' . format ( libname ) , 'Architectures in the fat file: {0} are: (.*)' . format ( libname ) ) : reggie = re . compile ( reggie ) match = reggie . match ( line ) if not match is None : return frozenset ( match . groups ( ) [ 0 ] . split ( ' ' ) ) raise ValueError ( "Unexpected output: '{0}' for {1}" . format ( stdout , libname ) )
def install ( self ) : """Install the generated config file ."""
outs = super ( MyInstallLib , self ) . install ( ) infile = self . create_conf_file ( ) outfile = os . path . join ( self . install_dir , os . path . basename ( infile ) ) self . copy_file ( infile , outfile ) outs . append ( outfile ) return outs
def get_repo_parent ( path ) : """Returns parent repo or input path if none found . : return : grit . Local or path"""
# path is a repository if is_repo ( path ) : return Local ( path ) # path is inside a repository elif not os . path . isdir ( path ) : _rel = '' while path and path != '/' : if is_repo ( path ) : return Local ( path ) else : _rel = os . path . join ( os . path . basename ( path ) , _rel ) path = os . path . dirname ( path ) return path
def reset ( self ) : '''Reset list of terms and y - variable .'''
self . terms = OrderedDict ( ) self . y = None self . backend = None self . added_terms = [ ] self . _added_priors = { } self . completes = [ ] self . clean_data = None
def calculate_digit_distance ( number1 , number2 ) : """A python function which calculates the digit distance between two numbers by adding the digits of the absolute difference between the numbers . Example usage : calculate _ digit _ distance ( 1 , 2 ) - > 1 calculate _ digit _ distance ( 23 , 56 ) - > 6 calculate _ digit _ distance ( 123 , 256 ) - > 7 Args : number1 : First integer . number2 : Second integer . Returns : The digit distance between the two numbers ."""
return sum ( int ( digit ) for digit in str ( abs ( number1 - number2 ) ) )
def set_all_pattern_variables ( self , patternnumber , sp0 , ti0 , sp1 , ti1 , sp2 , ti2 , sp3 , ti3 , sp4 , ti4 , sp5 , ti5 , sp6 , ti6 , sp7 , ti7 , actual_step , additional_cycles , link_pattern ) : """Set all variables for a given pattern at one time . Args : * patternnumber ( integer ) : 0-7 * sp [ * n * ] ( float ) : setpoint value for step * n * * ti [ * n * ] ( integer ? ? ) : step time for step * n * , 0-900 * actual _ step ( int ) : ? * additional _ cycles ( int ) : ? * link _ pattern ( int ) : ?"""
_checkPatternNumber ( patternnumber ) self . set_pattern_step_setpoint ( patternnumber , 0 , sp0 ) self . set_pattern_step_setpoint ( patternnumber , 1 , sp1 ) self . set_pattern_step_setpoint ( patternnumber , 2 , sp2 ) self . set_pattern_step_setpoint ( patternnumber , 3 , sp3 ) self . set_pattern_step_setpoint ( patternnumber , 4 , sp4 ) self . set_pattern_step_setpoint ( patternnumber , 5 , sp5 ) self . set_pattern_step_setpoint ( patternnumber , 6 , sp6 ) self . set_pattern_step_setpoint ( patternnumber , 7 , sp7 ) self . set_pattern_step_time ( patternnumber , 0 , ti0 ) self . set_pattern_step_time ( patternnumber , 1 , ti1 ) self . set_pattern_step_time ( patternnumber , 2 , ti2 ) self . set_pattern_step_time ( patternnumber , 3 , ti3 ) self . set_pattern_step_time ( patternnumber , 4 , ti4 ) self . set_pattern_step_time ( patternnumber , 5 , ti5 ) self . set_pattern_step_time ( patternnumber , 6 , ti6 ) self . set_pattern_step_time ( patternnumber , 7 , ti7 ) self . set_pattern_additional_cycles ( patternnumber , additional_cycles ) self . set_pattern_link_topattern ( patternnumber , link_pattern ) self . set_pattern_actual_step ( patternnumber , actual_step )
def find_behind_subscriptions ( ) : """Finds any subscriptions that are behind according to where they should be , and creates a BehindSubscription entry for them ."""
subscriptions = Subscription . objects . filter ( active = True , completed = False , process_status = 0 ) . values_list ( "id" , flat = True ) for subscription_id in subscriptions . iterator ( ) : calculate_subscription_lifecycle . delay ( str ( subscription_id ) )
def _gatherDataFromLookups ( gpos , scriptOrder ) : """Gather kerning and classes from the applicable lookups and return them in script order ."""
lookupIndexes = _gatherLookupIndexes ( gpos ) seenLookups = set ( ) kerningDictionaries = [ ] leftClassDictionaries = [ ] rightClassDictionaries = [ ] for script in scriptOrder : kerning = [ ] leftClasses = [ ] rightClasses = [ ] for lookupIndex in lookupIndexes [ script ] : if lookupIndex in seenLookups : continue seenLookups . add ( lookupIndex ) result = _gatherKerningForLookup ( gpos , lookupIndex ) if result is None : continue k , lG , rG = result kerning . append ( k ) leftClasses . append ( lG ) rightClasses . append ( rG ) if kerning : kerningDictionaries . append ( kerning ) leftClassDictionaries . append ( leftClasses ) rightClassDictionaries . append ( rightClasses ) return kerningDictionaries , leftClassDictionaries , rightClassDictionaries
def constant_fold ( code , silent = True , ignore_errors = True ) : """Constant - folds simple expressions like 2 3 + to 5. Args : code : Code in non - native types . silent : Flag that controls whether to print optimizations made . ignore _ errors : Whether to raise exceptions on found errors ."""
# Loop until we haven ' t done any optimizations . E . g . , " 2 3 + 5 * " will be # optimized to " 5 5 * " and in the next iteration to 25 . Yes , this is # extremely slow , big - O wise . We ' ll fix that some other time . ( TODO ) arithmetic = list ( map ( instructions . lookup , [ instructions . add , instructions . bitwise_and , instructions . bitwise_or , instructions . bitwise_xor , instructions . div , instructions . equal , instructions . greater , instructions . less , instructions . mod , instructions . mul , instructions . sub , ] ) ) divzero = map ( instructions . lookup , [ instructions . div , instructions . mod , ] ) lookup = instructions . lookup def isfunction ( op ) : try : instructions . lookup ( op ) return True except KeyError : return False def isconstant ( op ) : return op is None or interpreter . isconstant ( op , quoted = True ) or not isfunction ( op ) keep_running = True while keep_running : keep_running = False # Find two consecutive numbes and an arithmetic operator for i , a in enumerate ( code ) : b = code [ i + 1 ] if i + 1 < len ( code ) else None c = code [ i + 2 ] if i + 2 < len ( code ) else None # Constant fold arithmetic operations ( TODO : Move to check - func ) if interpreter . isnumber ( a , b ) and c in arithmetic : # Although we can detect division by zero at compile time , we # don ' t report it here , because the surrounding system doesn ' t # handle that very well . So just leave it for now . ( NOTE : If # we had an " error " instruction , we could actually transform # the expression to an error , or exit instruction perhaps ) if b == 0 and c in divzero : if ignore_errors : continue else : raise errors . CompileError ( ZeroDivisionError ( "Division by zero" ) ) # Calculate result by running on a machine ( lambda vm : . . . is # embedded pushes , see compiler ) result = interpreter . Machine ( [ lambda vm : vm . push ( a ) , lambda vm : vm . push ( b ) , instructions . lookup ( c ) ] ) . run ( ) . top del code [ i : i + 3 ] code . insert ( i , result ) if not silent : print ( "Optimizer: Constant-folded %s %s %s to %s" % ( a , b , c , result ) ) keep_running = True break # Translate < constant > dup to < constant > < constant > if isconstant ( a ) and b == lookup ( instructions . dup ) : code [ i + 1 ] = a if not silent : print ( "Optimizer: Translated %s %s to %s %s" % ( a , b , a , a ) ) keep_running = True break # Dead code removal : < constant > drop if isconstant ( a ) and b == lookup ( instructions . drop ) : del code [ i : i + 2 ] if not silent : print ( "Optimizer: Removed dead code %s %s" % ( a , b ) ) keep_running = True break if a == lookup ( instructions . nop ) : del code [ i ] if not silent : print ( "Optimizer: Removed dead code %s" % a ) keep_running = True break # Dead code removal : < integer > cast _ int if isinstance ( a , int ) and b == lookup ( instructions . cast_int ) : del code [ i + 1 ] if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , a ) ) keep_running = True break # Dead code removal : < float > cast _ float if isinstance ( a , float ) and b == lookup ( instructions . cast_float ) : del code [ i + 1 ] if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , a ) ) keep_running = True break # Dead code removal : < string > cast _ str if isinstance ( a , str ) and b == lookup ( instructions . cast_str ) : del code [ i + 1 ] if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , a ) ) keep_running = True break # Dead code removal : < boolean > cast _ bool if isinstance ( a , bool ) and b == lookup ( instructions . cast_bool ) : del code [ i + 1 ] if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , a ) ) keep_running = True break # < c1 > < c2 > swap - > < c2 > < c1 > if isconstant ( a ) and isconstant ( b ) and c == lookup ( instructions . swap ) : del code [ i : i + 3 ] code = code [ : i ] + [ b , a ] + code [ i : ] if not silent : print ( "Optimizer: Translated %s %s %s to %s %s" % ( a , b , c , b , a ) ) keep_running = True break # a b over - > a b a if isconstant ( a ) and isconstant ( b ) and c == lookup ( instructions . over ) : code [ i + 2 ] = a if not silent : print ( "Optimizer: Translated %s %s %s to %s %s %s" % ( a , b , c , a , b , a ) ) keep_running = True break # "123 " cast _ int - > 123 if interpreter . isstring ( a ) and b == lookup ( instructions . cast_int ) : try : number = int ( a ) del code [ i : i + 2 ] code . insert ( i , number ) if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , number ) ) keep_running = True break except ValueError : pass if isconstant ( a ) and b == lookup ( instructions . cast_str ) : del code [ i : i + 2 ] code . insert ( i , str ( a ) ) # TODO : Try - except here if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , str ( a ) ) ) keep_running = True break if isconstant ( a ) and b == lookup ( instructions . cast_bool ) : del code [ i : i + 2 ] code . insert ( i , bool ( a ) ) # TODO : Try - except here if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , bool ( a ) ) ) keep_running = True break if isconstant ( a ) and b == lookup ( instructions . cast_float ) : try : v = float ( a ) del code [ i : i + 2 ] code . insert ( i , v ) if not silent : print ( "Optimizer: Translated %s %s to %s" % ( a , b , v ) ) keep_running = True break except ValueError : pass return code
def setup ( self ) : """Collect watchdog information . Collect configuration files , custom executables for test - binary and repair - binary , and stdout / stderr logs ."""
conf_file = self . get_option ( 'conf_file' ) log_dir = '/var/log/watchdog' # Get service configuration and sysconfig files self . add_copy_spec ( [ conf_file , '/etc/sysconfig/watchdog' , ] ) # Get custom executables self . add_copy_spec ( [ '/etc/watchdog.d' , '/usr/libexec/watchdog/scripts' , ] ) # Get logs try : res = self . get_log_dir ( conf_file ) if res : log_dir = res except IOError as ex : self . _log_warn ( "Could not read %s: %s" % ( conf_file , ex ) ) if self . get_option ( 'all_logs' ) : log_files = glob ( os . path . join ( log_dir , '*' ) ) else : log_files = ( glob ( os . path . join ( log_dir , '*.stdout' ) ) + glob ( os . path . join ( log_dir , '*.stderr' ) ) ) self . add_copy_spec ( log_files ) # Get output of " wdctl < device > " for each / dev / watchdog * for dev in glob ( '/dev/watchdog*' ) : self . add_cmd_output ( "wdctl %s" % dev )
def make ( self ) : """Make the lock file ."""
try : # Create the lock file self . mkfile ( self . lock_file ) except Exception as e : self . die ( 'Failed to generate lock file: {}' . format ( str ( e ) ) )
def set_instrumentation_callback ( self , callback ) : """Assign a method to invoke when a request has completed gathering measurements . : param method callback : The method to invoke"""
self . logger . debug ( 'Setting instrumentation callback: %r' , callback ) self . _instrumentation_callback = callback
def schema ( self ) : """The DQL syntax for creating this item"""
if self . key_type is None : return "%s %s" % ( self . name , self . data_type ) else : return "%s %s %s KEY" % ( self . name , self . data_type , self . key_type )
def execute ( self , input_data ) : '''Okay this worker is going build graphs from PCAP Bro output logs'''
# Grab the Bro log handles from the input bro_logs = input_data [ 'pcap_bro' ] # Weird log if 'weird_log' in bro_logs : stream = self . workbench . stream_sample ( bro_logs [ 'weird_log' ] ) self . weird_log_graph ( stream ) # HTTP log gsleep ( ) stream = self . workbench . stream_sample ( bro_logs [ 'http_log' ] ) self . http_log_graph ( stream ) # Files log gsleep ( ) stream = self . workbench . stream_sample ( bro_logs [ 'files_log' ] ) self . files_log_graph ( stream ) return { 'output' : 'go to http://localhost:7474/browser and execute this query "match (s:origin), (t:file), p=allShortestPaths((s)--(t)) return p"' }
def generate_sub_codons_left ( codons_dict ) : """Generate the sub _ codons _ left dictionary of codon prefixes . Parameters codons _ dict : dict Dictionary , keyed by the allowed ' amino acid ' symbols with the values being lists of codons corresponding to the symbol . Returns sub _ codons _ left : dict Dictionary of the 1 and 2 nucleotide prefixes ( read from 5 ' ) for each codon in an ' amino acid ' grouping"""
sub_codons_left = { } for aa in codons_dict . keys ( ) : sub_codons_left [ aa ] = list ( set ( [ x [ 0 ] for x in codons_dict [ aa ] ] + [ x [ : 2 ] for x in codons_dict [ aa ] ] ) ) return sub_codons_left
def initialize_from_string ( content : str ) -> 'HomusSymbol' : """Create and initializes a new symbol from a string : param content : The content of a symbol as read from the text - file : return : The initialized symbol : rtype : HomusSymbol"""
if content is None or content is "" : return None lines = content . splitlines ( ) min_x = sys . maxsize max_x = 0 min_y = sys . maxsize max_y = 0 symbol_name = lines [ 0 ] strokes = [ ] for stroke_string in lines [ 1 : ] : stroke = [ ] for point_string in stroke_string . split ( ";" ) : if point_string is "" : continue # Skip the last element , that is due to a trailing ; in each line point_x , point_y = point_string . split ( "," ) x = int ( point_x ) y = int ( point_y ) stroke . append ( Point2D ( x , y ) ) max_x = max ( max_x , x ) min_x = min ( min_x , x ) max_y = max ( max_y , y ) min_y = min ( min_y , y ) strokes . append ( stroke ) dimensions = Rectangle ( Point2D ( min_x , min_y ) , max_x - min_x + 1 , max_y - min_y + 1 ) return HomusSymbol ( content , strokes , symbol_name , dimensions )
def update ( self ) : """Calculate the smoothing parameter value . The following example is explained in some detail in module | smoothtools | : > > > from hydpy . models . dam import * > > > parameterstep ( ) > > > highestremotedischarge ( 1.0) > > > highestremotetolerance ( 0.0) > > > derived . highestremotesmoothpar . update ( ) > > > from hydpy . cythons . smoothutils import smooth _ min1 > > > from hydpy import round _ > > > round _ ( smooth _ min1 ( - 4.0 , 1.5 , derived . highestremotesmoothpar ) ) -4.0 > > > highestremotetolerance ( 2.5) > > > derived . highestremotesmoothpar . update ( ) > > > round _ ( smooth _ min1 ( - 4.0 , - 1.5 , derived . highestremotesmoothpar ) ) -4.01 Note that the example above corresponds to the example on function | calc _ smoothpar _ min1 | , due to the value of parameter | HighestRemoteDischarge | being 1 m3 / s . Doubling the value of | HighestRemoteDischarge | also doubles the value of | HighestRemoteSmoothPar | proportional . This leads to the following result : > > > highestremotedischarge ( 2.0) > > > derived . highestremotesmoothpar . update ( ) > > > round _ ( smooth _ min1 ( - 4.0 , 1.0 , derived . highestremotesmoothpar ) ) -4.02 This relationship between | HighestRemoteDischarge | and | HighestRemoteSmoothPar | prevents from any smoothing when the value of | HighestRemoteDischarge | is zero : > > > highestremotedischarge ( 0.0) > > > derived . highestremotesmoothpar . update ( ) > > > round _ ( smooth _ min1(1.0 , 1.0 , derived . highestremotesmoothpar ) ) 1.0 In addition , | HighestRemoteSmoothPar | is set to zero if | HighestRemoteDischarge | is infinity ( because no actual value will ever come in the vicinit of infinity ) , which is why no value would be changed through smoothing anyway ) : > > > highestremotedischarge ( inf ) > > > derived . highestremotesmoothpar . update ( ) > > > round _ ( smooth _ min1(1.0 , 1.0 , derived . highestremotesmoothpar ) ) 1.0"""
control = self . subpars . pars . control if numpy . isinf ( control . highestremotedischarge ) : self ( 0.0 ) else : self ( control . highestremotedischarge * smoothtools . calc_smoothpar_min1 ( control . highestremotetolerance ) )
def broadcast_transaction ( hex_tx , blockchain_client ) : """Dispatches a raw hex transaction to the network ."""
if isinstance ( blockchain_client , BlockcypherClient ) : return blockcypher . broadcast_transaction ( hex_tx , blockchain_client ) elif isinstance ( blockchain_client , BlockchainInfoClient ) : return blockchain_info . broadcast_transaction ( hex_tx , blockchain_client ) elif isinstance ( blockchain_client , ChainComClient ) : return chain_com . broadcast_transaction ( hex_tx , blockchain_client ) elif isinstance ( blockchain_client , ( BitcoindClient , AuthServiceProxy ) ) : return bitcoind . broadcast_transaction ( hex_tx , blockchain_client ) elif hasattr ( blockchain_client , "broadcast_transaction" ) : return blockchain_client . broadcast_transaction ( hex_tx ) elif isinstance ( blockchain_client , BlockchainClient ) : raise Exception ( 'That blockchain interface is not supported.' ) else : raise Exception ( 'A BlockchainClient object is required' )
def call_use_cached_files ( tup ) : """Importable helper for multi - proc calling of ArtifactCache . use _ cached _ files on a cache instance . Multiprocessing map / apply / etc require functions which can be imported , not bound methods . To call a bound method , instead call a helper like this and pass tuple of the instance and args . The helper can then call the original method on the deserialized instance . : param tup : A tuple of an ArtifactCache and args ( eg CacheKey ) for ArtifactCache . use _ cached _ files ."""
try : cache , key , results_dir = tup res = cache . use_cached_files ( key , results_dir ) if res : sys . stderr . write ( '.' ) else : sys . stderr . write ( ' ' ) sys . stderr . flush ( ) return res except NonfatalArtifactCacheError as e : logger . warn ( 'Error calling use_cached_files in artifact cache: {0}' . format ( e ) ) return False
def print_version ( ) : """Print get _ version ( ) return value in a readable format . Params : None Returns : None"""
v = get_version ( ) try : s = _STR_WIN [ v ] except KeyError : s = "Unknow OS" print ( "-----------------------------------------------------------" ) print ( "###################### WinVer Report ######################" ) print ( "Python Version : {}.{}.{}" . format ( * sys . version_info [ : 3 ] ) ) print ( "Windows Version String : {}" . format ( s ) ) print ( "Windows Major Version : {}" . format ( v [ 0 ] ) ) print ( "Windows Minor Version : {}" . format ( v [ 1 ] ) ) print ( "Windows Service Pack (or Build) Version : {}" . format ( v [ 2 ] ) ) print ( "Is Windows Server : {}" . format ( 'Yes' if v [ 3 ] == 1 else 'No' ) ) print ( "Is Windows 10 (or Windows Server 2016) : {}" . format ( 'Yes' if v >= WIN_10 else 'No' ) ) print ( "-----------------------------------------------------------" )
def prime_factors ( n ) : """Lists prime factors of a given natural integer , from greatest to smallest : param n : Natural integer : rtype : list of all prime factors of the given natural n"""
i = 2 while i <= sqrt ( n ) : if n % i == 0 : l = prime_factors ( n / i ) l . append ( i ) return l i += 1 return [ n ]
def create_proxy_zip ( proxy_string , proxy_user , proxy_pass ) : """Implementation of https : / / stackoverflow . com / a / 35293284 for https : / / stackoverflow . com / questions / 12848327/ ( Run Selenium on a proxy server that requires authentication . ) Solution involves creating & adding a Chrome extension on the fly . * CHROME - ONLY for now ! *"""
proxy_host = proxy_string . split ( ':' ) [ 0 ] proxy_port = proxy_string . split ( ':' ) [ 1 ] background_js = ( """var config = {\n""" """ mode: "fixed_servers",\n""" """ rules: {\n""" """ singleProxy: {\n""" """ scheme: "http",\n""" """ host: "%s",\n""" """ port: parseInt("%s")\n""" """ },\n""" """ }\n""" """ };\n""" """chrome.proxy.settings.set(""" """{value: config, scope: "regular"}, function() {""" """});\n""" """function callbackFn(details) {\n""" """ return {\n""" """ authCredentials: {\n""" """ username: "%s",\n""" """ password: "%s"\n""" """ }\n""" """ };\n""" """}\n""" """chrome.webRequest.onAuthRequired.addListener(\n""" """ callbackFn,\n""" """ {urls: ["<all_urls>"]},\n""" """ ['blocking']\n""" """);""" % ( proxy_host , proxy_port , proxy_user , proxy_pass ) ) manifest_json = ( '''{\n''' '''"version": "1.0.0",\n''' '''"manifest_version": 2,\n''' '''"name": "Chrome Proxy",\n''' '''"permissions": [\n''' ''' "proxy",\n''' ''' "tabs",\n''' ''' "unlimitedStorage",\n''' ''' "storage",\n''' ''' "<all_urls>",\n''' ''' "webRequest",\n''' ''' "webRequestBlocking"\n''' '''],\n''' '''"background": {\n''' ''' "scripts": ["background.js"]\n''' '''},\n''' '''"minimum_chrome_version":"22.0.0"\n''' '''}''' ) lock = threading . RLock ( ) # Support multi - threaded test runs with Pytest with lock : try : zf = zipfile . ZipFile ( PROXY_ZIP_PATH , mode = 'w' ) except IOError : # Handle " Permission denied " on the default proxy . zip path abs_path = os . path . abspath ( '.' ) downloads_path = os . path . join ( abs_path , DOWNLOADS_DIR ) if not os . path . exists ( downloads_path ) : os . mkdir ( downloads_path ) zf = zipfile . ZipFile ( PROXY_ZIP_PATH_2 , mode = 'w' ) zf . writestr ( "background.js" , background_js ) zf . writestr ( "manifest.json" , manifest_json ) zf . close ( )
def configs ( self , filters = None ) : """List configs Args : filters ( dict ) : A map of filters to process on the configs list . Available filters : ` ` names ` ` Returns ( list ) : A list of configs"""
url = self . _url ( '/configs' ) params = { } if filters : params [ 'filters' ] = utils . convert_filters ( filters ) return self . _result ( self . _get ( url , params = params ) , True )
def system_monitor_LineCard_threshold_marginal_threshold ( self , ** kwargs ) : """Auto Generated Code"""
config = ET . Element ( "config" ) system_monitor = ET . SubElement ( config , "system-monitor" , xmlns = "urn:brocade.com:mgmt:brocade-system-monitor" ) LineCard = ET . SubElement ( system_monitor , "LineCard" ) threshold = ET . SubElement ( LineCard , "threshold" ) marginal_threshold = ET . SubElement ( threshold , "marginal-threshold" ) marginal_threshold . text = kwargs . pop ( 'marginal_threshold' ) callback = kwargs . pop ( 'callback' , self . _callback ) return callback ( config )