body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def process_file(filename: str) -> DateDict:
'\n Method that take path to crawled file and outputs date dictionary:\n Date dictionary is a dictionary where keys are dates in format YYYY-mm-dd-hh (2018-04-08-15)\n and value is dictionary where keys are devices (specified in configuration file)\n and valu... | -5,522,921,133,619,537,000 | Method that take path to crawled file and outputs date dictionary:
Date dictionary is a dictionary where keys are dates in format YYYY-mm-dd-hh (2018-04-08-15)
and value is dictionary where keys are devices (specified in configuration file)
and value is CSVDataLine.csv_data_line with device,date and occurrence
Args:
f... | modules/crawler/DatasetProcessing/OBSAZENIMISTNOSTI_processor.py | process_file | kivzcu/heatmap.zcu | python | def process_file(filename: str) -> DateDict:
'\n Method that take path to crawled file and outputs date dictionary:\n Date dictionary is a dictionary where keys are dates in format YYYY-mm-dd-hh (2018-04-08-15)\n and value is dictionary where keys are devices (specified in configuration file)\n and valu... |
def user_input_handling_function_ninth():
' a parser '
print()
user_input = input('Enter: ')
print()
term = ''
lict = []
for element in user_input:
if (element != ' '):
term = (term + element)
else:
lict.append(term)
term = ''
lict.appe... | 8,264,336,917,387,615,000 | a parser | lists_of_terms/shodule_for_lists_of_terms.py | user_input_handling_function_ninth | ShawnJSavoie2/ToBeRedone | python | def user_input_handling_function_ninth():
' '
print()
user_input = input('Enter: ')
print()
term =
lict = []
for element in user_input:
if (element != ' '):
term = (term + element)
else:
lict.append(term)
term =
lict.append(term)
... |
def user_input_handling_function_tenth(dictionary):
' a dictionary checker '
user_input = user_input_handling_function_ninth()
good_to_go = 'no'
errors = []
while (good_to_go == 'no'):
string = ''
lict = []
for element in user_input:
string = (string + element)
... | -2,635,322,934,253,187,600 | a dictionary checker | lists_of_terms/shodule_for_lists_of_terms.py | user_input_handling_function_tenth | ShawnJSavoie2/ToBeRedone | python | def user_input_handling_function_tenth(dictionary):
' '
user_input = user_input_handling_function_ninth()
good_to_go = 'no'
errors = []
while (good_to_go == 'no'):
string =
lict = []
for element in user_input:
string = (string + element)
for key in dicti... |
@login_required
def contact_list(request, pk):
'\n Displays a list of :model:`rr.Contact` linked to\n :model:`rr.ServiceProvider`.\n\n Includes a ModelForm for adding :model:`rr.Contact` to\n :model:`rr.ServiceProvider`.\n\n **Context**\n\n ``object_list``\n List of :model:`rr.Contact`.\n\n... | 7,067,613,641,276,462,000 | Displays a list of :model:`rr.Contact` linked to
:model:`rr.ServiceProvider`.
Includes a ModelForm for adding :model:`rr.Contact` to
:model:`rr.ServiceProvider`.
**Context**
``object_list``
List of :model:`rr.Contact`.
``form``
ModelForm for creating a :model:`rr.Contact`
``object``
An instance of :mod... | rr/views/contact.py | contact_list | UniversityofHelsinki/sp-registry | python | @login_required
def contact_list(request, pk):
'\n Displays a list of :model:`rr.Contact` linked to\n :model:`rr.ServiceProvider`.\n\n Includes a ModelForm for adding :model:`rr.Contact` to\n :model:`rr.ServiceProvider`.\n\n **Context**\n\n ``object_list``\n List of :model:`rr.Contact`.\n\n... |
def preprocess_input(x):
'Preprocesses a numpy array encoding a batch of images.\n\n Arguments:\n x: a 4D numpy array consists of RGB values within [0, 255].\n\n Returns:\n Preprocessed array.\n '
return imagenet_utils.preprocess_input(x, mode='tf') | -231,657,472,479,496,000 | Preprocesses a numpy array encoding a batch of images.
Arguments:
x: a 4D numpy array consists of RGB values within [0, 255].
Returns:
Preprocessed array. | tensorflow/python/keras/_impl/keras/applications/mobilenet.py | preprocess_input | DylanDmitri/tensorflow | python | def preprocess_input(x):
'Preprocesses a numpy array encoding a batch of images.\n\n Arguments:\n x: a 4D numpy array consists of RGB values within [0, 255].\n\n Returns:\n Preprocessed array.\n '
return imagenet_utils.preprocess_input(x, mode='tf') |
def MobileNet(input_shape=None, alpha=1.0, depth_multiplier=1, dropout=0.001, include_top=True, weights='imagenet', input_tensor=None, pooling=None, classes=1000):
"Instantiates the MobileNet architecture.\n\n Note that only TensorFlow is supported for now,\n therefore it only works with the data format\n `image... | -3,885,951,292,928,177,000 | Instantiates the MobileNet architecture.
Note that only TensorFlow is supported for now,
therefore it only works with the data format
`image_data_format='channels_last'` in your Keras config
at `~/.keras/keras.json`.
To load a MobileNet model via `load_model`, import the custom
objects `relu6` and `DepthwiseConv2D` a... | tensorflow/python/keras/_impl/keras/applications/mobilenet.py | MobileNet | DylanDmitri/tensorflow | python | def MobileNet(input_shape=None, alpha=1.0, depth_multiplier=1, dropout=0.001, include_top=True, weights='imagenet', input_tensor=None, pooling=None, classes=1000):
"Instantiates the MobileNet architecture.\n\n Note that only TensorFlow is supported for now,\n therefore it only works with the data format\n `image... |
def _conv_block(inputs, filters, alpha, kernel=(3, 3), strides=(1, 1)):
"Adds an initial convolution layer (with batch normalization and relu6).\n\n Arguments:\n inputs: Input tensor of shape `(rows, cols, 3)`\n (with `channels_last` data format) or\n (3, rows, cols) (with `channels_first` d... | 321,854,916,225,204,350 | Adds an initial convolution layer (with batch normalization and relu6).
Arguments:
inputs: Input tensor of shape `(rows, cols, 3)`
(with `channels_last` data format) or
(3, rows, cols) (with `channels_first` data format).
It should have exactly 3 inputs channels,
and width and heigh... | tensorflow/python/keras/_impl/keras/applications/mobilenet.py | _conv_block | DylanDmitri/tensorflow | python | def _conv_block(inputs, filters, alpha, kernel=(3, 3), strides=(1, 1)):
"Adds an initial convolution layer (with batch normalization and relu6).\n\n Arguments:\n inputs: Input tensor of shape `(rows, cols, 3)`\n (with `channels_last` data format) or\n (3, rows, cols) (with `channels_first` d... |
def _depthwise_conv_block(inputs, pointwise_conv_filters, alpha, depth_multiplier=1, strides=(1, 1), block_id=1):
"Adds a depthwise convolution block.\n\n A depthwise convolution block consists of a depthwise conv,\n batch normalization, relu6, pointwise convolution,\n batch normalization and relu6 activation.\n... | 4,224,460,810,474,824,700 | Adds a depthwise convolution block.
A depthwise convolution block consists of a depthwise conv,
batch normalization, relu6, pointwise convolution,
batch normalization and relu6 activation.
Arguments:
inputs: Input tensor of shape `(rows, cols, channels)`
(with `channels_last` data format) or
(chan... | tensorflow/python/keras/_impl/keras/applications/mobilenet.py | _depthwise_conv_block | DylanDmitri/tensorflow | python | def _depthwise_conv_block(inputs, pointwise_conv_filters, alpha, depth_multiplier=1, strides=(1, 1), block_id=1):
"Adds a depthwise convolution block.\n\n A depthwise convolution block consists of a depthwise conv,\n batch normalization, relu6, pointwise convolution,\n batch normalization and relu6 activation.\n... |
def __call__(self, image, crop_region=False, return_result=False, output_path=None):
'\n Input: path to image\n Output: boxes (coordinates of 4 points)\n '
if (output_path is None):
assert crop_region, 'Please specify output_path'
else:
output_path = os.path.join(output_... | -4,561,561,648,685,451,000 | Input: path to image
Output: boxes (coordinates of 4 points) | modules/__init__.py | __call__ | kaylode/vietnamese-ocr-toolbox | python | def __call__(self, image, crop_region=False, return_result=False, output_path=None):
'\n Input: path to image\n Output: boxes (coordinates of 4 points)\n '
if (output_path is None):
assert crop_region, 'Please specify output_path'
else:
output_path = os.path.join(output_... |
def successful_signing_test(self):
'Create and sign a valid raw transaction with one input.\n\n Expected results:\n\n 1) The transaction has a complete set of signatures\n 2) No script verification error occurred'
privKeys = ['EXAMPLE_KEY']
inputs = [{'txid': 'EXAMPLE_KEY', 'vout': 0, '... | 1,666,485,727,681,946,600 | Create and sign a valid raw transaction with one input.
Expected results:
1) The transaction has a complete set of signatures
2) No script verification error occurred | test/functional/rpc_signrawtransaction.py | successful_signing_test | anandsinha095/JDCION | python | def successful_signing_test(self):
'Create and sign a valid raw transaction with one input.\n\n Expected results:\n\n 1) The transaction has a complete set of signatures\n 2) No script verification error occurred'
privKeys = ['EXAMPLE_KEY']
inputs = [{'txid': 'EXAMPLE_KEY', 'vout': 0, '... |
def script_verification_error_test(self):
'Create and sign a raw transaction with valid (vin 0), invalid (vin 1) and one missing (vin 2) input script.\n\n Expected results:\n\n 3) The transaction has no complete set of signatures\n 4) Two script verification errors occurred\n 5) Script v... | -7,263,459,259,928,583,000 | Create and sign a raw transaction with valid (vin 0), invalid (vin 1) and one missing (vin 2) input script.
Expected results:
3) The transaction has no complete set of signatures
4) Two script verification errors occurred
5) Script verification errors have certain properties ("txid", "vout", "scriptSig", "sequence", ... | test/functional/rpc_signrawtransaction.py | script_verification_error_test | anandsinha095/JDCION | python | def script_verification_error_test(self):
'Create and sign a raw transaction with valid (vin 0), invalid (vin 1) and one missing (vin 2) input script.\n\n Expected results:\n\n 3) The transaction has no complete set of signatures\n 4) Two script verification errors occurred\n 5) Script v... |
def assertTypedEquals(self, expected, actual):
'Asserts that both the types and values are the same.'
self.assertEqual(type(expected), type(actual))
self.assertEqual(expected, actual) | -3,258,969,304,466,242,600 | Asserts that both the types and values are the same. | Mark_attandance_py_selenium/py/App/Python/Lib/test/test_fractions.py | assertTypedEquals | 4nkitd/pyAutomation | python | def assertTypedEquals(self, expected, actual):
self.assertEqual(type(expected), type(actual))
self.assertEqual(expected, actual) |
def assertRaisesMessage(self, exc_type, message, callable, *args, **kwargs):
'Asserts that callable(*args, **kwargs) raises exc_type(message).'
try:
callable(*args, **kwargs)
except exc_type as e:
self.assertEqual(message, str(e))
else:
self.fail(('%s not raised' % exc_type.__nam... | -4,005,090,857,821,129,000 | Asserts that callable(*args, **kwargs) raises exc_type(message). | Mark_attandance_py_selenium/py/App/Python/Lib/test/test_fractions.py | assertRaisesMessage | 4nkitd/pyAutomation | python | def assertRaisesMessage(self, exc_type, message, callable, *args, **kwargs):
try:
callable(*args, **kwargs)
except exc_type as e:
self.assertEqual(message, str(e))
else:
self.fail(('%s not raised' % exc_type.__name__)) |
def __init__(self, parametrization):
'Initializes the CirqOperation\n\n Args:\n parametrization (Tuple[float] -> Union[Cirq:Qid, List[Cirq:Qid]]): Converts the\n PennyLane gate parameters to an ordered list of gates that are to be applied.\n '
self.parametrization = param... | -9,183,222,663,540,377,000 | Initializes the CirqOperation
Args:
parametrization (Tuple[float] -> Union[Cirq:Qid, List[Cirq:Qid]]): Converts the
PennyLane gate parameters to an ordered list of gates that are to be applied. | pennylane_cirq/cirq_operation.py | __init__ | PennyLaneAI/pennylane-cirq | python | def __init__(self, parametrization):
'Initializes the CirqOperation\n\n Args:\n parametrization (Tuple[float] -> Union[Cirq:Qid, List[Cirq:Qid]]): Converts the\n PennyLane gate parameters to an ordered list of gates that are to be applied.\n '
self.parametrization = param... |
def parametrize(self, *args):
'Parametrizes the CirqOperation.\n\n Args:\n *args (float): the parameters for the operations\n '
self.parametrized_cirq_gates = self.parametrization(*args)
if (not isinstance(self.parametrized_cirq_gates, Sequence)):
self.parametrized_cirq_gate... | -2,579,435,966,490,960,400 | Parametrizes the CirqOperation.
Args:
*args (float): the parameters for the operations | pennylane_cirq/cirq_operation.py | parametrize | PennyLaneAI/pennylane-cirq | python | def parametrize(self, *args):
'Parametrizes the CirqOperation.\n\n Args:\n *args (float): the parameters for the operations\n '
self.parametrized_cirq_gates = self.parametrization(*args)
if (not isinstance(self.parametrized_cirq_gates, Sequence)):
self.parametrized_cirq_gate... |
def apply(self, *qubits):
'Applies the CirqOperation.\n\n Args:\n *qubits (Cirq:Qid): the qubits on which the Cirq gates should be performed.\n '
if (not self.parametrized_cirq_gates):
raise qml.DeviceError('CirqOperation must be parametrized before it can be applied.')
retu... | 7,338,081,575,973,967,000 | Applies the CirqOperation.
Args:
*qubits (Cirq:Qid): the qubits on which the Cirq gates should be performed. | pennylane_cirq/cirq_operation.py | apply | PennyLaneAI/pennylane-cirq | python | def apply(self, *qubits):
'Applies the CirqOperation.\n\n Args:\n *qubits (Cirq:Qid): the qubits on which the Cirq gates should be performed.\n '
if (not self.parametrized_cirq_gates):
raise qml.DeviceError('CirqOperation must be parametrized before it can be applied.')
retu... |
def inv(self):
'Inverses the CirqOperation.'
if self.parametrized_cirq_gates:
raise qml.DeviceError("CirqOperation can't be inverted after it was parametrized.")
self.is_inverse = (not self.is_inverse) | 4,247,073,013,365,585,000 | Inverses the CirqOperation. | pennylane_cirq/cirq_operation.py | inv | PennyLaneAI/pennylane-cirq | python | def inv(self):
if self.parametrized_cirq_gates:
raise qml.DeviceError("CirqOperation can't be inverted after it was parametrized.")
self.is_inverse = (not self.is_inverse) |
@commands.Cog.listener()
async def on_command_error(self, ctx, error):
'The event triggered when an error is raised while invoking a command.'
if hasattr(ctx.command, 'on_error'):
return
error = getattr(error, 'original', error)
if isinstance(error, commands.CommandNotFound):
return
... | 6,489,049,612,741,809,000 | The event triggered when an error is raised while invoking a command. | cogs/errorhandler.py | on_command_error | ZackHart2400/miso-bot | python | @commands.Cog.listener()
async def on_command_error(self, ctx, error):
if hasattr(ctx.command, 'on_error'):
return
error = getattr(error, 'original', error)
if isinstance(error, commands.CommandNotFound):
return
if isinstance(error, commands.MissingRequiredArgument):
return ... |
def sigmoid_rampup(current, rampup_length):
'Exponential rampup from https://arxiv.org/abs/1610.02242'
if (rampup_length == 0):
return 1.0
else:
current = np.clip(current, 0.0, rampup_length)
phase = (1.0 - (current / rampup_length))
w = float(np.exp((((- 2.0) * phase) * phas... | -5,048,476,405,849,566,000 | Exponential rampup from https://arxiv.org/abs/1610.02242 | PNet/train_pnet.py | sigmoid_rampup | mangye16/ReID-Label-Noise | python | def sigmoid_rampup(current, rampup_length):
if (rampup_length == 0):
return 1.0
else:
current = np.clip(current, 0.0, rampup_length)
phase = (1.0 - (current / rampup_length))
w = float(np.exp((((- 2.0) * phase) * phase)))
return min(w, 0.5) |
@abstractmethod
def apply(self, board):
'\n Apply a move to a board and retrieve the board produced by the move.\n\n Parameters\n ----------\n board\n The board to apply the move to.\n\n Returns\n -------\n Board\n A new board that will be produ... | -6,482,721,186,070,927,000 | Apply a move to a board and retrieve the board produced by the move.
Parameters
----------
board
The board to apply the move to.
Returns
-------
Board
A new board that will be produced after applying this move. | libcheckers/movement.py | apply | YuriyGuts/libcheckers | python | @abstractmethod
def apply(self, board):
'\n Apply a move to a board and retrieve the board produced by the move.\n\n Parameters\n ----------\n board\n The board to apply the move to.\n\n Returns\n -------\n Board\n A new board that will be produ... |
def find_opponent_square(self, board):
'\n Retrieve the index of the square that contains the enemy piece to be captured.\n '
path_indexes = get_indexes_between(self.start_index, self.end_index)
own_color = board.owner[self.start_index]
own_path_squares = [index for index in path_indexes i... | 2,956,729,355,891,111,000 | Retrieve the index of the square that contains the enemy piece to be captured. | libcheckers/movement.py | find_opponent_square | YuriyGuts/libcheckers | python | def find_opponent_square(self, board):
'\n \n '
path_indexes = get_indexes_between(self.start_index, self.end_index)
own_color = board.owner[self.start_index]
own_path_squares = [index for index in path_indexes if (board.owner[index] == own_color)]
opponent_path_squares = [index for in... |
def move_piece(self, start_index, end_index):
'\n Move an existing game piece from point A to point B.\n '
self.owner[end_index] = self.owner[start_index]
self.owner[start_index] = None
self.piece_class[end_index] = self.piece_class[start_index]
self.piece_class[start_index] = None
... | -6,216,466,120,835,834,000 | Move an existing game piece from point A to point B. | libcheckers/movement.py | move_piece | YuriyGuts/libcheckers | python | def move_piece(self, start_index, end_index):
'\n \n '
self.owner[end_index] = self.owner[start_index]
self.owner[start_index] = None
self.piece_class[end_index] = self.piece_class[start_index]
self.piece_class[start_index] = None
if ((self.owner[end_index] == Player.WHITE) and is_... |
def add_piece(self, index, player, piece_class):
'\n Place a new piece on the board with the specified owner and class.\n '
self.owner[index] = player
self.piece_class[index] = piece_class | 467,345,209,544,386,750 | Place a new piece on the board with the specified owner and class. | libcheckers/movement.py | add_piece | YuriyGuts/libcheckers | python | def add_piece(self, index, player, piece_class):
'\n \n '
self.owner[index] = player
self.piece_class[index] = piece_class |
def remove_piece(self, index):
'\n Clear the specified square from the board.\n '
self.owner[index] = None
self.piece_class[index] = None | -6,348,893,047,659,651,000 | Clear the specified square from the board. | libcheckers/movement.py | remove_piece | YuriyGuts/libcheckers | python | def remove_piece(self, index):
'\n \n '
self.owner[index] = None
self.piece_class[index] = None |
def get_player_squares(self, player):
'\n Get all squares on the board owned by the specified player.\n '
return [index for index in range(1, (BoardConfig.total_squares + 1)) if (self.owner[index] == player)] | 1,008,148,386,689,905,000 | Get all squares on the board owned by the specified player. | libcheckers/movement.py | get_player_squares | YuriyGuts/libcheckers | python | def get_player_squares(self, player):
'\n \n '
return [index for index in range(1, (BoardConfig.total_squares + 1)) if (self.owner[index] == player)] |
def get_free_movement_destinations(self, index):
'\n Get all allowed destinations for free movement for the piece at the specified square.\n '
own_color = self.owner[index]
own_class = self.piece_class[index]
visibility_range = (BoardConfig.board_dim if (own_class == PieceClass.KING) else ... | -241,082,711,958,797,380 | Get all allowed destinations for free movement for the piece at the specified square. | libcheckers/movement.py | get_free_movement_destinations | YuriyGuts/libcheckers | python | def get_free_movement_destinations(self, index):
'\n \n '
own_color = self.owner[index]
own_class = self.piece_class[index]
visibility_range = (BoardConfig.board_dim if (own_class == PieceClass.KING) else 1)
lines_of_sight = get_lines_of_sight(index, visibility_range)
if ((own_clas... |
def get_capturable_pieces(self, index):
"\n Get all squares that contain opponent's pieces capturable from the specified position.\n "
own_color = self.owner[index]
own_class = self.piece_class[index]
visibility_range = (BoardConfig.board_dim if (own_class == PieceClass.KING) else 2)
l... | 3,072,183,555,115,830,300 | Get all squares that contain opponent's pieces capturable from the specified position. | libcheckers/movement.py | get_capturable_pieces | YuriyGuts/libcheckers | python | def get_capturable_pieces(self, index):
"\n \n "
own_color = self.owner[index]
own_class = self.piece_class[index]
visibility_range = (BoardConfig.board_dim if (own_class == PieceClass.KING) else 2)
lines_of_sight = get_lines_of_sight(index, visibility_range)
result = []
for li... |
def get_available_capture_landing_positions(self, attacker_index, capture_index):
'\n If the specified square is captured by the specified attacker,\n get all possible squares the attacker can land on.\n '
own_class = self.piece_class[attacker_index]
(attacker_row, attacker_col) = index... | 9,079,244,142,070,687,000 | If the specified square is captured by the specified attacker,
get all possible squares the attacker can land on. | libcheckers/movement.py | get_available_capture_landing_positions | YuriyGuts/libcheckers | python | def get_available_capture_landing_positions(self, attacker_index, capture_index):
'\n If the specified square is captured by the specified attacker,\n get all possible squares the attacker can land on.\n '
own_class = self.piece_class[attacker_index]
(attacker_row, attacker_col) = index... |
def get_capture_sequence_candidates(self, player):
'\n Get all possible capture move sequences (not necessarily maximum ones)\n starting from every piece owned by the specified player.\n '
player_squares = self.get_player_squares(player)
attack_options = []
for attacker in player_sq... | -7,375,068,571,418,206,000 | Get all possible capture move sequences (not necessarily maximum ones)
starting from every piece owned by the specified player. | libcheckers/movement.py | get_capture_sequence_candidates | YuriyGuts/libcheckers | python | def get_capture_sequence_candidates(self, player):
'\n Get all possible capture move sequences (not necessarily maximum ones)\n starting from every piece owned by the specified player.\n '
player_squares = self.get_player_squares(player)
attack_options = []
for attacker in player_sq... |
def get_available_moves(self, player):
'\n For the specified player, get the list of all allowed moves that are applicable\n to this board according to the game rules.\n '
result = []
capture_sequences = self.get_capture_sequence_candidates(player)
if (not capture_sequences):
... | -5,256,897,743,708,423,000 | For the specified player, get the list of all allowed moves that are applicable
to this board according to the game rules. | libcheckers/movement.py | get_available_moves | YuriyGuts/libcheckers | python | def get_available_moves(self, player):
'\n For the specified player, get the list of all allowed moves that are applicable\n to this board according to the game rules.\n '
result = []
capture_sequences = self.get_capture_sequence_candidates(player)
if (not capture_sequences):
... |
def check_game_over(self, player_turn):
"\n Check if the game board is in a terminal state from the specified player's point of view.\n (e.g. a certain player has won or lost, or there is a draw).\n "
white_moves = self.get_available_moves(Player.WHITE)
black_moves = self.get_available_... | -3,846,133,922,372,637,700 | Check if the game board is in a terminal state from the specified player's point of view.
(e.g. a certain player has won or lost, or there is a draw). | libcheckers/movement.py | check_game_over | YuriyGuts/libcheckers | python | def check_game_over(self, player_turn):
"\n Check if the game board is in a terminal state from the specified player's point of view.\n (e.g. a certain player has won or lost, or there is a draw).\n "
white_moves = self.get_available_moves(Player.WHITE)
black_moves = self.get_available_... |
def clone(self):
'\n Create an independent copy of this board.\n '
return deepcopy(self) | 7,946,742,403,737,371,000 | Create an independent copy of this board. | libcheckers/movement.py | clone | YuriyGuts/libcheckers | python | def clone(self):
'\n \n '
return deepcopy(self) |
def __init__(self):
'\n Inits a new transaction.\n '
import revitron
bundle = script.get_bundle_name().replace('.pushbutton', '')
self.transaction = revitron.DB.Transaction(revitron.DOC, bundle)
self.transaction.Start() | -3,308,001,345,332,747,300 | Inits a new transaction. | revitron/transaction.py | __init__ | YKato521/revitron-for-RevitPythonShell | python | def __init__(self):
'\n \n '
import revitron
bundle = script.get_bundle_name().replace('.pushbutton', )
self.transaction = revitron.DB.Transaction(revitron.DOC, bundle)
self.transaction.Start() |
def commit(self):
'\n Commits the open transaction.\n '
self.transaction.Commit() | 6,035,886,319,970,189,000 | Commits the open transaction. | revitron/transaction.py | commit | YKato521/revitron-for-RevitPythonShell | python | def commit(self):
'\n \n '
self.transaction.Commit() |
def rollback(self):
'\n Rolls back the open transaction.\n '
self.transaction.RollBack() | -1,146,533,772,664,958,100 | Rolls back the open transaction. | revitron/transaction.py | rollback | YKato521/revitron-for-RevitPythonShell | python | def rollback(self):
'\n \n '
self.transaction.RollBack() |
@classmethod
def defaults(cls, *args):
'Get default arguments added to a parser by all ``*args``.'
dummy_parser = cls()
for callback in args:
callback(dummy_parser)
defaults = dummy_parser.parse_known_args([])[0]
return defaults | 3,302,161,372,159,137,000 | Get default arguments added to a parser by all ``*args``. | onmt/utils/parse.py | defaults | ACL2020-Submission/ACL2020 | python | @classmethod
def defaults(cls, *args):
dummy_parser = cls()
for callback in args:
callback(dummy_parser)
defaults = dummy_parser.parse_known_args([])[0]
return defaults |
def __init__(self, hass: HomeAssistant, entry: ConfigEntry, client: GitHubAPI, repository: str) -> None:
'Initialize GitHub data update coordinator base class.'
self.config_entry = entry
self.repository = repository
self._client = client
super().__init__(hass, LOGGER, name=DOMAIN, update_interval=DE... | 5,124,193,583,015,939,000 | Initialize GitHub data update coordinator base class. | homeassistant/components/github/coordinator.py | __init__ | Arquiteto/core | python | def __init__(self, hass: HomeAssistant, entry: ConfigEntry, client: GitHubAPI, repository: str) -> None:
self.config_entry = entry
self.repository = repository
self._client = client
super().__init__(hass, LOGGER, name=DOMAIN, update_interval=DEFAULT_UPDATE_INTERVAL) |
async def fetch_data(self) -> T:
'Fetch data from GitHub API.' | -5,836,349,995,842,303,000 | Fetch data from GitHub API. | homeassistant/components/github/coordinator.py | fetch_data | Arquiteto/core | python | async def fetch_data(self) -> T:
|
async def fetch_data(self) -> GitHubRepositoryModel:
'Get the latest data from GitHub.'
result = (await self._client.repos.get(self.repository))
return result.data | 4,338,848,196,831,356,400 | Get the latest data from GitHub. | homeassistant/components/github/coordinator.py | fetch_data | Arquiteto/core | python | async def fetch_data(self) -> GitHubRepositoryModel:
result = (await self._client.repos.get(self.repository))
return result.data |
async def fetch_data(self) -> (GitHubReleaseModel | None):
'Get the latest data from GitHub.'
result = (await self._client.repos.releases.list(self.repository, **{'params': {'per_page': 1}}))
if (not result.data):
return None
for release in result.data:
if (not release.prerelease):
... | 5,219,791,198,494,509,000 | Get the latest data from GitHub. | homeassistant/components/github/coordinator.py | fetch_data | Arquiteto/core | python | async def fetch_data(self) -> (GitHubReleaseModel | None):
result = (await self._client.repos.releases.list(self.repository, **{'params': {'per_page': 1}}))
if (not result.data):
return None
for release in result.data:
if (not release.prerelease):
return release
return r... |
async def fetch_data(self) -> IssuesPulls:
'Get the latest data from GitHub.'
base_issue_response = (await self._client.repos.issues.list(self.repository, **{'params': {'per_page': 1}}))
pull_response = (await self._client.repos.pulls.list(self.repository, **{'params': {'per_page': 1}}))
pulls_count = (... | -2,304,525,900,436,716,000 | Get the latest data from GitHub. | homeassistant/components/github/coordinator.py | fetch_data | Arquiteto/core | python | async def fetch_data(self) -> IssuesPulls:
base_issue_response = (await self._client.repos.issues.list(self.repository, **{'params': {'per_page': 1}}))
pull_response = (await self._client.repos.pulls.list(self.repository, **{'params': {'per_page': 1}}))
pulls_count = (pull_response.last_page_number or ... |
async def fetch_data(self) -> (GitHubCommitModel | None):
'Get the latest data from GitHub.'
result = (await self._client.repos.list_commits(self.repository, **{'params': {'per_page': 1}}))
return (result.data[0] if result.data else None) | -1,005,978,423,350,740,500 | Get the latest data from GitHub. | homeassistant/components/github/coordinator.py | fetch_data | Arquiteto/core | python | async def fetch_data(self) -> (GitHubCommitModel | None):
result = (await self._client.repos.list_commits(self.repository, **{'params': {'per_page': 1}}))
return (result.data[0] if result.data else None) |
def htCache(factory):
'Output the cache of a servlet factory.'
html = []
wr = html.append
cache = factory._classCache
keys = sorted(cache)
wr(('<p>Uniqueness: %s</p>' % factory.uniqueness()))
wr(('<p>Extensions: %s</p>' % ', '.join(map(repr, factory.extensions()))))
wr(('<p>Unique paths ... | 2,626,865,298,280,618,000 | Output the cache of a servlet factory. | WebKit/Admin/ServletCache.py | htCache | Cito/w4py | python | def htCache(factory):
html = []
wr = html.append
cache = factory._classCache
keys = sorted(cache)
wr(('<p>Uniqueness: %s</p>' % factory.uniqueness()))
wr(('<p>Extensions: %s</p>' % ', '.join(map(repr, factory.extensions()))))
wr(('<p>Unique paths in the servlet cache: <strong>%d</strong... |
def register_modules(self, **kwargs):
' Registers modules in current module dictionary.\n '
self.module_dict.update(kwargs) | -1,205,675,546,938,575,400 | Registers modules in current module dictionary. | graf-main/submodules/GAN_stability/gan_training/checkpoints.py | register_modules | 1ucky40nc3/mednerf | python | def register_modules(self, **kwargs):
' \n '
self.module_dict.update(kwargs) |
def save(self, filename, **kwargs):
' Saves the current module dictionary.\n\n Args:\n filename (str): name of output file\n '
if (not os.path.isabs(filename)):
filename = os.path.join(self.checkpoint_dir, filename)
outdict = kwargs
for (k, v) in self.module_dict.items()... | -7,547,054,072,814,241,000 | Saves the current module dictionary.
Args:
filename (str): name of output file | graf-main/submodules/GAN_stability/gan_training/checkpoints.py | save | 1ucky40nc3/mednerf | python | def save(self, filename, **kwargs):
' Saves the current module dictionary.\n\n Args:\n filename (str): name of output file\n '
if (not os.path.isabs(filename)):
filename = os.path.join(self.checkpoint_dir, filename)
outdict = kwargs
for (k, v) in self.module_dict.items()... |
def load(self, filename):
'Loads a module dictionary from local file or url.\n \n Args:\n filename (str): name of saved module dictionary\n '
if is_url(filename):
return self.load_url(filename)
else:
return self.load_file(filename) | -2,890,154,249,354,038,300 | Loads a module dictionary from local file or url.
Args:
filename (str): name of saved module dictionary | graf-main/submodules/GAN_stability/gan_training/checkpoints.py | load | 1ucky40nc3/mednerf | python | def load(self, filename):
'Loads a module dictionary from local file or url.\n \n Args:\n filename (str): name of saved module dictionary\n '
if is_url(filename):
return self.load_url(filename)
else:
return self.load_file(filename) |
def load_file(self, filename):
'Loads a module dictionary from file.\n \n Args:\n filename (str): name of saved module dictionary\n '
if (not os.path.isabs(filename)):
filename = os.path.join(self.checkpoint_dir, filename)
if os.path.exists(filename):
print(fi... | -6,940,442,115,957,106,000 | Loads a module dictionary from file.
Args:
filename (str): name of saved module dictionary | graf-main/submodules/GAN_stability/gan_training/checkpoints.py | load_file | 1ucky40nc3/mednerf | python | def load_file(self, filename):
'Loads a module dictionary from file.\n \n Args:\n filename (str): name of saved module dictionary\n '
if (not os.path.isabs(filename)):
filename = os.path.join(self.checkpoint_dir, filename)
if os.path.exists(filename):
print(fi... |
def load_url(self, url):
'Load a module dictionary from url.\n \n Args:\n url (str): url to saved model\n '
print(url)
print('=> Loading checkpoint from url...')
state_dict = model_zoo.load_url(url, progress=True)
scalars = self.parse_state_dict(state_dict)
return... | 610,299,147,669,909,500 | Load a module dictionary from url.
Args:
url (str): url to saved model | graf-main/submodules/GAN_stability/gan_training/checkpoints.py | load_url | 1ucky40nc3/mednerf | python | def load_url(self, url):
'Load a module dictionary from url.\n \n Args:\n url (str): url to saved model\n '
print(url)
print('=> Loading checkpoint from url...')
state_dict = model_zoo.load_url(url, progress=True)
scalars = self.parse_state_dict(state_dict)
return... |
def parse_state_dict(self, state_dict):
'Parse state_dict of model and return scalars.\n \n Args:\n state_dict (dict): State dict of model\n '
for (k, v) in self.module_dict.items():
if (k in state_dict):
v.load_state_dict(state_dict[k])
else:
... | -3,472,864,303,789,836,300 | Parse state_dict of model and return scalars.
Args:
state_dict (dict): State dict of model | graf-main/submodules/GAN_stability/gan_training/checkpoints.py | parse_state_dict | 1ucky40nc3/mednerf | python | def parse_state_dict(self, state_dict):
'Parse state_dict of model and return scalars.\n \n Args:\n state_dict (dict): State dict of model\n '
for (k, v) in self.module_dict.items():
if (k in state_dict):
v.load_state_dict(state_dict[k])
else:
... |
def __init__(self, k: int) -> PolynomialFitting:
'\n Instantiate a polynomial fitting estimator\n\n Parameters\n ----------\n k : int\n Degree of polynomial to fit\n '
super().__init__()
self.deg_ = k
(self.vander_, self.vander_linear_) = (None, LinearRegres... | 2,860,509,653,220,064,000 | Instantiate a polynomial fitting estimator
Parameters
----------
k : int
Degree of polynomial to fit | IMLearn/learners/regressors/polynomial_fitting.py | __init__ | shirlevy007/IML.HUJI | python | def __init__(self, k: int) -> PolynomialFitting:
'\n Instantiate a polynomial fitting estimator\n\n Parameters\n ----------\n k : int\n Degree of polynomial to fit\n '
super().__init__()
self.deg_ = k
(self.vander_, self.vander_linear_) = (None, LinearRegres... |
def _fit(self, X: np.ndarray, y: np.ndarray) -> NoReturn:
'\n Fit Least Squares model to polynomial transformed samples\n\n Parameters\n ----------\n X : ndarray of shape (n_samples, n_features)\n Input data to fit an estimator for\n\n y : ndarray of shape (n_samples, )... | 1,178,176,510,061,192,200 | Fit Least Squares model to polynomial transformed samples
Parameters
----------
X : ndarray of shape (n_samples, n_features)
Input data to fit an estimator for
y : ndarray of shape (n_samples, )
Responses of input data to fit to | IMLearn/learners/regressors/polynomial_fitting.py | _fit | shirlevy007/IML.HUJI | python | def _fit(self, X: np.ndarray, y: np.ndarray) -> NoReturn:
'\n Fit Least Squares model to polynomial transformed samples\n\n Parameters\n ----------\n X : ndarray of shape (n_samples, n_features)\n Input data to fit an estimator for\n\n y : ndarray of shape (n_samples, )... |
def _predict(self, X: np.ndarray) -> np.ndarray:
'\n Predict responses for given samples using fitted estimator\n\n Parameters\n ----------\n X : ndarray of shape (n_samples, n_features)\n Input data to predict responses for\n\n Returns\n -------\n respons... | 3,464,361,381,715,352,000 | Predict responses for given samples using fitted estimator
Parameters
----------
X : ndarray of shape (n_samples, n_features)
Input data to predict responses for
Returns
-------
responses : ndarray of shape (n_samples, )
Predicted responses of given samples | IMLearn/learners/regressors/polynomial_fitting.py | _predict | shirlevy007/IML.HUJI | python | def _predict(self, X: np.ndarray) -> np.ndarray:
'\n Predict responses for given samples using fitted estimator\n\n Parameters\n ----------\n X : ndarray of shape (n_samples, n_features)\n Input data to predict responses for\n\n Returns\n -------\n respons... |
def _loss(self, X: np.ndarray, y: np.ndarray) -> float:
'\n Evaluate performance under MSE loss function\n\n Parameters\n ----------\n X : ndarray of shape (n_samples, n_features)\n Test samples\n\n y : ndarray of shape (n_samples, )\n True labels of test sam... | -4,140,011,508,131,796,500 | Evaluate performance under MSE loss function
Parameters
----------
X : ndarray of shape (n_samples, n_features)
Test samples
y : ndarray of shape (n_samples, )
True labels of test samples
Returns
-------
loss : float
Performance under MSE loss function | IMLearn/learners/regressors/polynomial_fitting.py | _loss | shirlevy007/IML.HUJI | python | def _loss(self, X: np.ndarray, y: np.ndarray) -> float:
'\n Evaluate performance under MSE loss function\n\n Parameters\n ----------\n X : ndarray of shape (n_samples, n_features)\n Test samples\n\n y : ndarray of shape (n_samples, )\n True labels of test sam... |
def __transform(self, X: np.ndarray) -> np.ndarray:
'\n Transform given input according to the univariate polynomial transformation\n\n Parameters\n ----------\n X: ndarray of shape (n_samples,)\n\n Returns\n -------\n transformed: ndarray of shape (n_samples, k+1)\n... | -2,425,109,902,432,135,700 | Transform given input according to the univariate polynomial transformation
Parameters
----------
X: ndarray of shape (n_samples,)
Returns
-------
transformed: ndarray of shape (n_samples, k+1)
Vandermonde matrix of given samples up to degree k | IMLearn/learners/regressors/polynomial_fitting.py | __transform | shirlevy007/IML.HUJI | python | def __transform(self, X: np.ndarray) -> np.ndarray:
'\n Transform given input according to the univariate polynomial transformation\n\n Parameters\n ----------\n X: ndarray of shape (n_samples,)\n\n Returns\n -------\n transformed: ndarray of shape (n_samples, k+1)\n... |
def __init__(self, config):
'\n Initialize SGD Env\n\n Parameters\n -------\n config : objdict\n Environment configuration\n '
super(SGDEnv, self).__init__(config)
self.batch_size = config.training_batch_size
self.validation_batch_size = config.validation_ba... | -5,901,484,696,904,247,000 | Initialize SGD Env
Parameters
-------
config : objdict
Environment configuration | dacbench/envs/sgd.py | __init__ | goktug97/DACBench | python | def __init__(self, config):
'\n Initialize SGD Env\n\n Parameters\n -------\n config : objdict\n Environment configuration\n '
super(SGDEnv, self).__init__(config)
self.batch_size = config.training_batch_size
self.validation_batch_size = config.validation_ba... |
def seed(self, seed=None):
'\n Set rng seed\n\n Parameters\n ----------\n seed:\n seed for rng\n '
(_, seed) = seeding.np_random(seed)
if (seed is not None):
torch.manual_seed(seed)
np.random.seed(seed)
return [seed] | -1,746,096,113,128,371,000 | Set rng seed
Parameters
----------
seed:
seed for rng | dacbench/envs/sgd.py | seed | goktug97/DACBench | python | def seed(self, seed=None):
'\n Set rng seed\n\n Parameters\n ----------\n seed:\n seed for rng\n '
(_, seed) = seeding.np_random(seed)
if (seed is not None):
torch.manual_seed(seed)
np.random.seed(seed)
return [seed] |
def step(self, action):
'\n Execute environment step\n\n Parameters\n ----------\n action : list\n action to execute\n\n Returns\n -------\n np.array, float, bool, dict\n state, reward, done, info\n '
done = super(SGDEnv, self).step_(... | 483,047,106,780,406,660 | Execute environment step
Parameters
----------
action : list
action to execute
Returns
-------
np.array, float, bool, dict
state, reward, done, info | dacbench/envs/sgd.py | step | goktug97/DACBench | python | def step(self, action):
'\n Execute environment step\n\n Parameters\n ----------\n action : list\n action to execute\n\n Returns\n -------\n np.array, float, bool, dict\n state, reward, done, info\n '
done = super(SGDEnv, self).step_(... |
def reset(self):
'\n Reset environment\n\n Returns\n -------\n np.array\n Environment state\n '
super(SGDEnv, self).reset_()
dataset = self.instance[0]
instance_seed = self.instance[1]
construct_model = self.instance[2]
self.seed(instance_seed)
s... | -2,251,031,008,396,713,500 | Reset environment
Returns
-------
np.array
Environment state | dacbench/envs/sgd.py | reset | goktug97/DACBench | python | def reset(self):
'\n Reset environment\n\n Returns\n -------\n np.array\n Environment state\n '
super(SGDEnv, self).reset_()
dataset = self.instance[0]
instance_seed = self.instance[1]
construct_model = self.instance[2]
self.seed(instance_seed)
s... |
def close(self):
'\n No additional cleanup necessary\n\n Returns\n -------\n bool\n Cleanup flag\n '
return True | -9,155,946,635,410,039,000 | No additional cleanup necessary
Returns
-------
bool
Cleanup flag | dacbench/envs/sgd.py | close | goktug97/DACBench | python | def close(self):
'\n No additional cleanup necessary\n\n Returns\n -------\n bool\n Cleanup flag\n '
return True |
def render(self, mode: str='human'):
'\n Render env in human mode\n\n Parameters\n ----------\n mode : str\n Execution mode\n '
if (mode != 'human'):
raise NotImplementedError
pass | -4,692,031,195,429,529,000 | Render env in human mode
Parameters
----------
mode : str
Execution mode | dacbench/envs/sgd.py | render | goktug97/DACBench | python | def render(self, mode: str='human'):
'\n Render env in human mode\n\n Parameters\n ----------\n mode : str\n Execution mode\n '
if (mode != 'human'):
raise NotImplementedError
pass |
def get_default_state(self, _):
'\n Gather state description\n\n Returns\n -------\n dict\n Environment state\n\n '
gradients = self._get_gradients()
(self.firstOrderMomentum, self.secondOrderMomentum) = self._get_momentum(gradients)
(predictiveChangeVarDisc... | 150,674,990,009,349,800 | Gather state description
Returns
-------
dict
Environment state | dacbench/envs/sgd.py | get_default_state | goktug97/DACBench | python | def get_default_state(self, _):
'\n Gather state description\n\n Returns\n -------\n dict\n Environment state\n\n '
gradients = self._get_gradients()
(self.firstOrderMomentum, self.secondOrderMomentum) = self._get_momentum(gradients)
(predictiveChangeVarDisc... |
def __init__(self, black_patterns=(CONFIG_URLPATTERN_ALL,), white_patterns=('^http',), capacity=None):
'\n constructor, use variable of BloomFilter if capacity else variable of set\n '
self._re_black_list = ([re.compile(pattern, flags=re.IGNORECASE) for pattern in black_patterns] if black_patterns... | 390,878,835,707,812,300 | constructor, use variable of BloomFilter if capacity else variable of set | spider/utilities/util_urlfilter.py | __init__ | charlesXu86/PSpider | python | def __init__(self, black_patterns=(CONFIG_URLPATTERN_ALL,), white_patterns=('^http',), capacity=None):
'\n \n '
self._re_black_list = ([re.compile(pattern, flags=re.IGNORECASE) for pattern in black_patterns] if black_patterns else [])
self._re_white_list = ([re.compile(pattern, flags=re.IGNORE... |
def update(self, url_list):
'\n update this urlfilter using url_list\n '
if (self._url_set is not None):
self._url_set.update(url_list)
else:
for url in url_list:
self._bloom_filter.add(url)
return | 6,770,847,336,451,332,000 | update this urlfilter using url_list | spider/utilities/util_urlfilter.py | update | charlesXu86/PSpider | python | def update(self, url_list):
'\n \n '
if (self._url_set is not None):
self._url_set.update(url_list)
else:
for url in url_list:
self._bloom_filter.add(url)
return |
def check(self, url):
'\n check the url based on self._re_black_list and self._re_white_list\n '
for re_black in self._re_black_list:
if re_black.search(url):
return False
for re_white in self._re_white_list:
if re_white.search(url):
return True
retu... | -5,244,254,235,561,446,000 | check the url based on self._re_black_list and self._re_white_list | spider/utilities/util_urlfilter.py | check | charlesXu86/PSpider | python | def check(self, url):
'\n \n '
for re_black in self._re_black_list:
if re_black.search(url):
return False
for re_white in self._re_white_list:
if re_white.search(url):
return True
return (False if self._re_white_list else True) |
def check_and_add(self, url):
"\n check the url to make sure that the url hasn't been fetched, and add url to urlfilter\n "
result = False
if self.check(url):
if (self._url_set is not None):
result = (url not in self._url_set)
self._url_set.add(url)
else... | 4,728,054,450,603,104,000 | check the url to make sure that the url hasn't been fetched, and add url to urlfilter | spider/utilities/util_urlfilter.py | check_and_add | charlesXu86/PSpider | python | def check_and_add(self, url):
"\n \n "
result = False
if self.check(url):
if (self._url_set is not None):
result = (url not in self._url_set)
self._url_set.add(url)
else:
result = (not self._bloom_filter.add(url))
return result |
def get_extra_rules(use_extra: bool, extra_json_path: Path_Str) -> Optional[ActionsDict]:
'Helper to provide custom (project level/user level) anonymization\n rules as a mapping of tags -> action function.\n\n Args:\n use_extra (bool): If use extra rules.\n extra_json_path (Path_Str): Path to ex... | -9,007,312,869,837,651,000 | Helper to provide custom (project level/user level) anonymization
rules as a mapping of tags -> action function.
Args:
use_extra (bool): If use extra rules.
extra_json_path (Path_Str): Path to extra rules json file.
It should be flat json with action as a key and list of tags as value.
Returns:
Option... | dicomanonymizer/batch_anonymizer.py | get_extra_rules | ademyanchuk/dicom-anonymizer | python | def get_extra_rules(use_extra: bool, extra_json_path: Path_Str) -> Optional[ActionsDict]:
'Helper to provide custom (project level/user level) anonymization\n rules as a mapping of tags -> action function.\n\n Args:\n use_extra (bool): If use extra rules.\n extra_json_path (Path_Str): Path to ex... |
def anonymize_dicom_folder(in_path: Path_Str, out_path: Path_Str, debug: bool=False, **kwargs):
'Anonymize dicom files in `in_path`, if `in_path` doesn\'t\n contain dicom files, will do nothing. Debug == True will do\n sort of dry run to check if all good for the large data storages\n\n Args:\n in_p... | 8,963,746,500,322,977,000 | Anonymize dicom files in `in_path`, if `in_path` doesn't
contain dicom files, will do nothing. Debug == True will do
sort of dry run to check if all good for the large data storages
Args:
in_path (Path_Str): path to the folder containing dicom files
out_path (Path_Str): path to the folder there anonymized copi... | dicomanonymizer/batch_anonymizer.py | anonymize_dicom_folder | ademyanchuk/dicom-anonymizer | python | def anonymize_dicom_folder(in_path: Path_Str, out_path: Path_Str, debug: bool=False, **kwargs):
'Anonymize dicom files in `in_path`, if `in_path` doesn\'t\n contain dicom files, will do nothing. Debug == True will do\n sort of dry run to check if all good for the large data storages\n\n Args:\n in_p... |
def anonymize_root_folder(in_root: Path_Str, out_root: Path_Str, **kwargs):
'The fuction will get all nested folders from `in_root`\n and perform anonymization of all folders containg dicom-files\n Will recreate the `in_root` folders structure in the `out_root`\n\n Args:\n in_root (Path_Str): source... | -6,255,924,792,182,228,000 | The fuction will get all nested folders from `in_root`
and perform anonymization of all folders containg dicom-files
Will recreate the `in_root` folders structure in the `out_root`
Args:
in_root (Path_Str): source root folder (presumably has
some dicom-files inide, maybe nested)
out_root (Path_Str): destin... | dicomanonymizer/batch_anonymizer.py | anonymize_root_folder | ademyanchuk/dicom-anonymizer | python | def anonymize_root_folder(in_root: Path_Str, out_root: Path_Str, **kwargs):
'The fuction will get all nested folders from `in_root`\n and perform anonymization of all folders containg dicom-files\n Will recreate the `in_root` folders structure in the `out_root`\n\n Args:\n in_root (Path_Str): source... |
@cmd.add(_cmdd, 'rules')
async def _cmdf_enable(self, substr, msg, privilege_level):
'`{cmd}` - View game rules.'
(await self._client.send_msg(msg, self._RULES_STRING))
return | -7,856,957,651,585,113,000 | `{cmd}` - View game rules. | mentionbot/servermodules/truthgame.py | _cmdf_enable | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'rules')
async def _cmdf_enable(self, substr, msg, privilege_level):
(await self._client.send_msg(msg, self._RULES_STRING))
return |
@cmd.add(_cmdd, 'newgame', top=True)
@cmd.minimum_privilege(PrivilegeLevel.TRUSTED)
async def _cmdf_newgame(self, substr, msg, privilege_level):
'`{cmd}` - New game.'
channel = msg.channel
(await self._abort_if_not_truth_channel(channel))
(await self._new_game(channel))
(await self._client.send_msg(... | 5,801,103,587,893,892,000 | `{cmd}` - New game. | mentionbot/servermodules/truthgame.py | _cmdf_newgame | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'newgame', top=True)
@cmd.minimum_privilege(PrivilegeLevel.TRUSTED)
async def _cmdf_newgame(self, substr, msg, privilege_level):
channel = msg.channel
(await self._abort_if_not_truth_channel(channel))
(await self._new_game(channel))
(await self._client.send_msg(channel, 'Truth game ... |
@cmd.add(_cmdd, 'in', top=True)
async def _cmdf_in(self, substr, msg, privilege_level):
'\n `{cmd}` - Adds you to the game.\n\n This command also allows moderators to add other users and arbitrary strings as participants.\n **Example:** `{cmd} an elephant` - Adds "an elephant" as a participant.\n ... | -4,829,615,238,631,485,000 | `{cmd}` - Adds you to the game.
This command also allows moderators to add other users and arbitrary strings as participants.
**Example:** `{cmd} an elephant` - Adds "an elephant" as a participant. | mentionbot/servermodules/truthgame.py | _cmdf_in | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'in', top=True)
async def _cmdf_in(self, substr, msg, privilege_level):
'\n `{cmd}` - Adds you to the game.\n\n This command also allows moderators to add other users and arbitrary strings as participants.\n **Example:** `{cmd} an elephant` - Adds "an elephant" as a participant.\n ... |
@cmd.add(_cmdd, 'out', top=True)
async def _cmdf_out(self, substr, msg, privilege_level):
'\n `{cmd}` - Removes you from the game.\n\n This command also allows moderators to remove other users and arbitrary strings.\n **Example:** `{cmd} an elephant` - Removes "an elephant" as a participant.\n '... | 8,620,157,351,105,654,000 | `{cmd}` - Removes you from the game.
This command also allows moderators to remove other users and arbitrary strings.
**Example:** `{cmd} an elephant` - Removes "an elephant" as a participant. | mentionbot/servermodules/truthgame.py | _cmdf_out | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'out', top=True)
async def _cmdf_out(self, substr, msg, privilege_level):
'\n `{cmd}` - Removes you from the game.\n\n This command also allows moderators to remove other users and arbitrary strings.\n **Example:** `{cmd} an elephant` - Removes "an elephant" as a participant.\n '... |
@cmd.add(_cmdd, 'enablechannel')
@cmd.minimum_privilege(PrivilegeLevel.ADMIN)
async def _cmdf_enable(self, substr, msg, privilege_level):
'`{cmd}` - Enable Truth in this channel.'
channel = msg.channel
if (channel.id in self._enabled_channels):
(await self._client.send_msg(channel, 'This channel is ... | 8,307,452,712,083,425,000 | `{cmd}` - Enable Truth in this channel. | mentionbot/servermodules/truthgame.py | _cmdf_enable | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'enablechannel')
@cmd.minimum_privilege(PrivilegeLevel.ADMIN)
async def _cmdf_enable(self, substr, msg, privilege_level):
channel = msg.channel
if (channel.id in self._enabled_channels):
(await self._client.send_msg(channel, 'This channel is already a Truth game channel.'))
else... |
@cmd.add(_cmdd, 'disablechannel')
@cmd.minimum_privilege(PrivilegeLevel.ADMIN)
async def _cmdf_disable(self, substr, msg, privilege_level):
'`{cmd}` - Disable Truth in this channel.'
channel = msg.channel
if (channel.id in self._enabled_channels):
self._enabled_channels.remove(channel.id)
se... | 1,501,719,110,497,770,200 | `{cmd}` - Disable Truth in this channel. | mentionbot/servermodules/truthgame.py | _cmdf_disable | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'disablechannel')
@cmd.minimum_privilege(PrivilegeLevel.ADMIN)
async def _cmdf_disable(self, substr, msg, privilege_level):
channel = msg.channel
if (channel.id in self._enabled_channels):
self._enabled_channels.remove(channel.id)
self._save_settings()
(await self._c... |
@cmd.add(_cmdd, 'viewenabled')
async def _cmdf_viewenabled(self, substr, msg, privilege_level):
'`{cmd}` - View all channels that are enabled as Truth channels.'
buf = None
if (len(self._enabled_channels) == 0):
buf = 'No channels have Truth game enabled.'
else:
buf = '**Truth game enabl... | 6,277,485,582,689,504,000 | `{cmd}` - View all channels that are enabled as Truth channels. | mentionbot/servermodules/truthgame.py | _cmdf_viewenabled | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'viewenabled')
async def _cmdf_viewenabled(self, substr, msg, privilege_level):
buf = None
if (len(self._enabled_channels) == 0):
buf = 'No channels have Truth game enabled.'
else:
buf = '**Truth game enabled channels:**'
for channel_id in self._enabled_channels:... |
@cmd.add(_cmdd, 'choose', 'random', 'rand')
async def _cmdf_choosetruth(self, substr, msg, privilege_level):
'`{cmd}` - Pick a random participant other than yourself.'
topic = msg.channel.topic
if (topic is None):
(await self._client.send_msg(msg, "There doesn't appear to be a truth game in here."))... | 5,147,312,669,561,219,000 | `{cmd}` - Pick a random participant other than yourself. | mentionbot/servermodules/truthgame.py | _cmdf_choosetruth | simshadows/Discord-mentionbot | python | @cmd.add(_cmdd, 'choose', 'random', 'rand')
async def _cmdf_choosetruth(self, substr, msg, privilege_level):
topic = msg.channel.topic
if (topic is None):
(await self._client.send_msg(msg, "There doesn't appear to be a truth game in here."))
raise errors.OperationAborted
mentions = util... |
def test_username_validation_error_msg(self, user: User):
"\n Tests UserCreation Form's unique validator functions correctly by testing:\n 1) A new user with an existing username cannot be added.\n 2) Only 1 error is raised by the UserCreation Form\n 3) The desired error mess... | 1,755,965,056,911,758,800 | Tests UserCreation Form's unique validator functions correctly by testing:
1) A new user with an existing username cannot be added.
2) Only 1 error is raised by the UserCreation Form
3) The desired error message is raised | my_blog/users/tests/test_forms.py | test_username_validation_error_msg | Tanishk-Sharma/my_blog | python | def test_username_validation_error_msg(self, user: User):
"\n Tests UserCreation Form's unique validator functions correctly by testing:\n 1) A new user with an existing username cannot be added.\n 2) Only 1 error is raised by the UserCreation Form\n 3) The desired error mess... |
def convert_types(self, schema, col_type_dict, row):
'Convert values from DBAPI to output-friendly formats.'
return [self.convert_type(value, col_type_dict.get(name)) for (name, value) in zip(schema, row)] | 7,978,365,602,373,941,000 | Convert values from DBAPI to output-friendly formats. | airflow/providers/google/cloud/operators/sql_to_gcs.py | convert_types | FRI-DAY/airflow | python | def convert_types(self, schema, col_type_dict, row):
return [self.convert_type(value, col_type_dict.get(name)) for (name, value) in zip(schema, row)] |
def _write_local_data_files(self, cursor):
'\n Takes a cursor, and writes results to a local file.\n\n :return: A dictionary where keys are filenames to be used as object\n names in GCS, and values are file handles to local files that\n contain the data for the GCS objects.\n ... | 6,549,307,246,991,140,000 | Takes a cursor, and writes results to a local file.
:return: A dictionary where keys are filenames to be used as object
names in GCS, and values are file handles to local files that
contain the data for the GCS objects. | airflow/providers/google/cloud/operators/sql_to_gcs.py | _write_local_data_files | FRI-DAY/airflow | python | def _write_local_data_files(self, cursor):
'\n Takes a cursor, and writes results to a local file.\n\n :return: A dictionary where keys are filenames to be used as object\n names in GCS, and values are file handles to local files that\n contain the data for the GCS objects.\n ... |
def _configure_csv_file(self, file_handle, schema):
'Configure a csv writer with the file_handle and write schema\n as headers for the new file.\n '
csv_writer = csv.writer(file_handle, encoding='utf-8', delimiter=self.field_delimiter)
csv_writer.writerow(schema)
return csv_writer | 112,089,612,591,239,120 | Configure a csv writer with the file_handle and write schema
as headers for the new file. | airflow/providers/google/cloud/operators/sql_to_gcs.py | _configure_csv_file | FRI-DAY/airflow | python | def _configure_csv_file(self, file_handle, schema):
'Configure a csv writer with the file_handle and write schema\n as headers for the new file.\n '
csv_writer = csv.writer(file_handle, encoding='utf-8', delimiter=self.field_delimiter)
csv_writer.writerow(schema)
return csv_writer |
@abc.abstractmethod
def query(self):
'Execute DBAPI query.' | 2,809,730,422,140,370,000 | Execute DBAPI query. | airflow/providers/google/cloud/operators/sql_to_gcs.py | query | FRI-DAY/airflow | python | @abc.abstractmethod
def query(self):
|
@abc.abstractmethod
def field_to_bigquery(self, field):
'Convert a DBAPI field to BigQuery schema format.' | 2,258,237,604,328,877,600 | Convert a DBAPI field to BigQuery schema format. | airflow/providers/google/cloud/operators/sql_to_gcs.py | field_to_bigquery | FRI-DAY/airflow | python | @abc.abstractmethod
def field_to_bigquery(self, field):
|
@abc.abstractmethod
def convert_type(self, value, schema_type):
'Convert a value from DBAPI to output-friendly formats.' | -2,785,577,839,560,248,300 | Convert a value from DBAPI to output-friendly formats. | airflow/providers/google/cloud/operators/sql_to_gcs.py | convert_type | FRI-DAY/airflow | python | @abc.abstractmethod
def convert_type(self, value, schema_type):
|
def _get_col_type_dict(self):
'\n Return a dict of column name and column type based on self.schema if not None.\n '
schema = []
if isinstance(self.schema, str):
schema = json.loads(self.schema)
elif isinstance(self.schema, list):
schema = self.schema
elif (self.schema ... | -6,582,290,293,196,102,000 | Return a dict of column name and column type based on self.schema if not None. | airflow/providers/google/cloud/operators/sql_to_gcs.py | _get_col_type_dict | FRI-DAY/airflow | python | def _get_col_type_dict(self):
'\n \n '
schema = []
if isinstance(self.schema, str):
schema = json.loads(self.schema)
elif isinstance(self.schema, list):
schema = self.schema
elif (self.schema is not None):
self.log.warning('Using default schema due to unexpected... |
def _write_local_schema_file(self, cursor):
'\n Takes a cursor, and writes the BigQuery schema for the results to a\n local file system.\n\n :return: A dictionary where key is a filename to be used as an object\n name in GCS, and values are file handles to local files that\n ... | 5,382,904,820,138,505,000 | Takes a cursor, and writes the BigQuery schema for the results to a
local file system.
:return: A dictionary where key is a filename to be used as an object
name in GCS, and values are file handles to local files that
contains the BigQuery schema fields in .json format. | airflow/providers/google/cloud/operators/sql_to_gcs.py | _write_local_schema_file | FRI-DAY/airflow | python | def _write_local_schema_file(self, cursor):
'\n Takes a cursor, and writes the BigQuery schema for the results to a\n local file system.\n\n :return: A dictionary where key is a filename to be used as an object\n name in GCS, and values are file handles to local files that\n ... |
def _upload_to_gcs(self, files_to_upload):
'\n Upload all of the file splits (and optionally the schema .json file) to\n Google Cloud Storage.\n '
hook = GCSHook(google_cloud_storage_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to)
for tmp_file in files_to_upload:
hook.up... | 4,584,763,336,989,765,600 | Upload all of the file splits (and optionally the schema .json file) to
Google Cloud Storage. | airflow/providers/google/cloud/operators/sql_to_gcs.py | _upload_to_gcs | FRI-DAY/airflow | python | def _upload_to_gcs(self, files_to_upload):
'\n Upload all of the file splits (and optionally the schema .json file) to\n Google Cloud Storage.\n '
hook = GCSHook(google_cloud_storage_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to)
for tmp_file in files_to_upload:
hook.up... |
def description(self):
'\n Returns a description for the actor.\n\n :return: the actor description\n :rtype: str\n '
return 'Outputs an integer from the specified range.' | 6,808,793,563,313,494,000 | Returns a description for the actor.
:return: the actor description
:rtype: str | base/src/shallowflow/base/sources/_ForLoop.py | description | waikato-datamining/shallow-flow | python | def description(self):
'\n Returns a description for the actor.\n\n :return: the actor description\n :rtype: str\n '
return 'Outputs an integer from the specified range.' |
def _define_options(self):
'\n For configuring the options.\n '
super()._define_options()
self._option_manager.add(Option(name='start', value_type=int, def_value=1, help='The starting value'))
self._option_manager.add(Option(name='end', value_type=int, def_value=10, help='The last value (i... | 1,926,360,857,306,023,200 | For configuring the options. | base/src/shallowflow/base/sources/_ForLoop.py | _define_options | waikato-datamining/shallow-flow | python | def _define_options(self):
'\n \n '
super()._define_options()
self._option_manager.add(Option(name='start', value_type=int, def_value=1, help='The starting value'))
self._option_manager.add(Option(name='end', value_type=int, def_value=10, help='The last value (incl)'))
self._option_man... |
def _get_item_type(self):
'\n Returns the type of the individual items that get generated, when not outputting a list.\n\n :return: the type that gets generated\n '
return int | 2,031,864,802,038,898,000 | Returns the type of the individual items that get generated, when not outputting a list.
:return: the type that gets generated | base/src/shallowflow/base/sources/_ForLoop.py | _get_item_type | waikato-datamining/shallow-flow | python | def _get_item_type(self):
'\n Returns the type of the individual items that get generated, when not outputting a list.\n\n :return: the type that gets generated\n '
return int |
def setup(self):
'\n Prepares the actor for use.\n\n :return: None if successful, otherwise error message\n :rtype: str\n '
result = super().setup()
if (result is None):
if (self.get('end') < self.get('start')):
result = ('End value (%s) must be smaller than s... | 2,356,912,509,369,107,000 | Prepares the actor for use.
:return: None if successful, otherwise error message
:rtype: str | base/src/shallowflow/base/sources/_ForLoop.py | setup | waikato-datamining/shallow-flow | python | def setup(self):
'\n Prepares the actor for use.\n\n :return: None if successful, otherwise error message\n :rtype: str\n '
result = super().setup()
if (result is None):
if (self.get('end') < self.get('start')):
result = ('End value (%s) must be smaller than s... |
def _do_execute(self):
'\n Performs the actual execution.\n\n :return: None if successful, otherwise error message\n :rtype: str\n '
i = self.get('start')
step = self.get('step')
end = self.get('end')
while (i <= end):
self._output.append(i)
i += step
... | 2,658,049,908,359,687,000 | Performs the actual execution.
:return: None if successful, otherwise error message
:rtype: str | base/src/shallowflow/base/sources/_ForLoop.py | _do_execute | waikato-datamining/shallow-flow | python | def _do_execute(self):
'\n Performs the actual execution.\n\n :return: None if successful, otherwise error message\n :rtype: str\n '
i = self.get('start')
step = self.get('step')
end = self.get('end')
while (i <= end):
self._output.append(i)
i += step
... |
def __init__(self, *, host: str='vision.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Sequence[str]=None, channel: grpc.Channel=None, api_mtls_endpoint: str=None, client_cert_source: Callable[([], Tuple[(bytes, bytes)])]=None, ssl_channel_credentials: grpc.ChannelCre... | -5,878,449,379,749,531,000 | Instantiate the transport.
Args:
host (Optional[str]):
The hostname to connect to.
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified,... | google/cloud/vision/v1p3beta1/vision-v1p3beta1-py/google/cloud/vision_v1p3beta1/services/image_annotator/transports/grpc.py | __init__ | googleapis/googleapis-gen | python | def __init__(self, *, host: str='vision.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Sequence[str]=None, channel: grpc.Channel=None, api_mtls_endpoint: str=None, client_cert_source: Callable[([], Tuple[(bytes, bytes)])]=None, ssl_channel_credentials: grpc.ChannelCre... |
@classmethod
def create_channel(cls, host: str='vision.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Optional[Sequence[str]]=None, quota_project_id: Optional[str]=None, **kwargs) -> grpc.Channel:
'Create and return a gRPC channel object.\n Args:\n ... | -3,496,580,290,601,304,000 | Create and return a gRPC channel object.
Args:
host (Optional[str]): The host for the channel to use.
credentials (Optional[~.Credentials]): The
authorization credentials to attach to requests. These
credentials identify this application to the service. If
none are specified, the client ... | google/cloud/vision/v1p3beta1/vision-v1p3beta1-py/google/cloud/vision_v1p3beta1/services/image_annotator/transports/grpc.py | create_channel | googleapis/googleapis-gen | python | @classmethod
def create_channel(cls, host: str='vision.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Optional[Sequence[str]]=None, quota_project_id: Optional[str]=None, **kwargs) -> grpc.Channel:
'Create and return a gRPC channel object.\n Args:\n ... |
@property
def grpc_channel(self) -> grpc.Channel:
'Return the channel designed to connect to this service.\n '
return self._grpc_channel | -1,956,682,971,687,930,400 | Return the channel designed to connect to this service. | google/cloud/vision/v1p3beta1/vision-v1p3beta1-py/google/cloud/vision_v1p3beta1/services/image_annotator/transports/grpc.py | grpc_channel | googleapis/googleapis-gen | python | @property
def grpc_channel(self) -> grpc.Channel:
'\n '
return self._grpc_channel |
@property
def operations_client(self) -> operations_v1.OperationsClient:
'Create the client designed to process long-running operations.\n\n This property caches on the instance; repeated calls return the same\n client.\n '
if (self._operations_client is None):
self._operations_clie... | -7,084,677,965,328,057,000 | Create the client designed to process long-running operations.
This property caches on the instance; repeated calls return the same
client. | google/cloud/vision/v1p3beta1/vision-v1p3beta1-py/google/cloud/vision_v1p3beta1/services/image_annotator/transports/grpc.py | operations_client | googleapis/googleapis-gen | python | @property
def operations_client(self) -> operations_v1.OperationsClient:
'Create the client designed to process long-running operations.\n\n This property caches on the instance; repeated calls return the same\n client.\n '
if (self._operations_client is None):
self._operations_clie... |
@property
def batch_annotate_images(self) -> Callable[([image_annotator.BatchAnnotateImagesRequest], image_annotator.BatchAnnotateImagesResponse)]:
'Return a callable for the batch annotate images method over gRPC.\n\n Run image detection and annotation for a batch of\n images.\n\n Returns:\n ... | -4,998,487,497,053,026,000 | Return a callable for the batch annotate images method over gRPC.
Run image detection and annotation for a batch of
images.
Returns:
Callable[[~.BatchAnnotateImagesRequest],
~.BatchAnnotateImagesResponse]:
A function that, when called, will call the underlying RPC
on the server. | google/cloud/vision/v1p3beta1/vision-v1p3beta1-py/google/cloud/vision_v1p3beta1/services/image_annotator/transports/grpc.py | batch_annotate_images | googleapis/googleapis-gen | python | @property
def batch_annotate_images(self) -> Callable[([image_annotator.BatchAnnotateImagesRequest], image_annotator.BatchAnnotateImagesResponse)]:
'Return a callable for the batch annotate images method over gRPC.\n\n Run image detection and annotation for a batch of\n images.\n\n Returns:\n ... |
@property
def async_batch_annotate_files(self) -> Callable[([image_annotator.AsyncBatchAnnotateFilesRequest], operations_pb2.Operation)]:
'Return a callable for the async batch annotate files method over gRPC.\n\n Run asynchronous image detection and annotation for a list of\n generic files, such as P... | -3,732,901,292,045,829,600 | Return a callable for the async batch annotate files method over gRPC.
Run asynchronous image detection and annotation for a list of
generic files, such as PDF files, which may contain multiple
pages and multiple images per page. Progress and results can be
retrieved through the ``google.longrunning.Operations``
inter... | google/cloud/vision/v1p3beta1/vision-v1p3beta1-py/google/cloud/vision_v1p3beta1/services/image_annotator/transports/grpc.py | async_batch_annotate_files | googleapis/googleapis-gen | python | @property
def async_batch_annotate_files(self) -> Callable[([image_annotator.AsyncBatchAnnotateFilesRequest], operations_pb2.Operation)]:
'Return a callable for the async batch annotate files method over gRPC.\n\n Run asynchronous image detection and annotation for a list of\n generic files, such as P... |
def resize_axis(tensor, axis, new_size, fill_value=0, random_sampling=False):
'Truncates or pads a tensor to new_size on on a given axis.\n Truncate or extend tensor such that tensor.shape[axis] == new_size. If the\n size increases, the padding will be performed at the end, using fill_value.\n Args:\n ... | 3,647,447,032,106,927,600 | Truncates or pads a tensor to new_size on on a given axis.
Truncate or extend tensor such that tensor.shape[axis] == new_size. If the
size increases, the padding will be performed at the end, using fill_value.
Args:
tensor: The tensor to be resized.
axis: An integer representing the dimension to be sliced.
new_si... | utils.py | resize_axis | glee1228/segment_temporal_context_aggregation | python | def resize_axis(tensor, axis, new_size, fill_value=0, random_sampling=False):
'Truncates or pads a tensor to new_size on on a given axis.\n Truncate or extend tensor such that tensor.shape[axis] == new_size. If the\n size increases, the padding will be performed at the end, using fill_value.\n Args:\n ... |
def __init__(self, value: T, parent: Optional[Any]=None, callback: Optional[Callable[([], None)]]=None):
' Initialize the PageProperty to always have value v.'
self._values: List[Tuple[(int, T)]] = [(0, value)]
self.set_parent(parent)
self._callback = callback | -7,846,967,357,376,559,000 | Initialize the PageProperty to always have value v. | chart/chart/python/spectralsequence_chart/page_property.py | __init__ | JoeyBF/sseq | python | def __init__(self, value: T, parent: Optional[Any]=None, callback: Optional[Callable[([], None)]]=None):
' '
self._values: List[Tuple[(int, T)]] = [(0, value)]
self.set_parent(parent)
self._callback = callback |
@click.command(name='about')
@click.pass_obj
@click.pass_context
def about(ctx, cli_obj):
'Print information about osxphotos including license.'
click.echo_via_pager(f'''osxphotos, version {__version__}
Source code available at: {OSXPHOTOS_URL}
{LICENSE}''') | 63,966,833,063,543,110 | Print information about osxphotos including license. | osxphotos/cli/about.py | about | oPromessa/osxphotos | python | @click.command(name='about')
@click.pass_obj
@click.pass_context
def about(ctx, cli_obj):
click.echo_via_pager(f'osxphotos, version {__version__}
Source code available at: {OSXPHOTOS_URL}
{LICENSE}') |
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