Datasets:
xszheng2020
/
the_stack_dedup_python_hits_6

Dataset card Data Studio Files
xet
Community
hexsha
string
size
int64
ext
string
lang
string
max_stars_repo_path
string
max_stars_repo_name
string
max_stars_repo_head_hexsha
string
max_stars_repo_licenses
list
max_stars_count
int64
max_stars_repo_stars_event_min_datetime
string
max_stars_repo_stars_event_max_datetime
string
max_issues_repo_path
string
max_issues_repo_name
string
max_issues_repo_head_hexsha
string
max_issues_repo_licenses
list
max_issues_count
int64
max_issues_repo_issues_event_min_datetime
string
max_issues_repo_issues_event_max_datetime
string
max_forks_repo_path
string
max_forks_repo_name
string
max_forks_repo_head_hexsha
string
max_forks_repo_licenses
list
max_forks_count
int64
max_forks_repo_forks_event_min_datetime
string
max_forks_repo_forks_event_max_datetime
string
content
string
avg_line_length
float64
max_line_length
int64
alphanum_fraction
float64
qsc_code_num_words_quality_signal
int64
qsc_code_num_chars_quality_signal
float64
qsc_code_mean_word_length_quality_signal
float64
qsc_code_frac_words_unique_quality_signal
float64
qsc_code_frac_chars_top_2grams_quality_signal
float64
qsc_code_frac_chars_top_3grams_quality_signal
float64
qsc_code_frac_chars_top_4grams_quality_signal
float64
qsc_code_frac_chars_dupe_5grams_quality_signal
float64
qsc_code_frac_chars_dupe_6grams_quality_signal
float64
qsc_code_frac_chars_dupe_7grams_quality_signal
float64
qsc_code_frac_chars_dupe_8grams_quality_signal
float64
qsc_code_frac_chars_dupe_9grams_quality_signal
float64
qsc_code_frac_chars_dupe_10grams_quality_signal
float64
qsc_code_frac_chars_replacement_symbols_quality_signal
float64
qsc_code_frac_chars_digital_quality_signal
float64
qsc_code_frac_chars_whitespace_quality_signal
float64
qsc_code_size_file_byte_quality_signal
float64
qsc_code_num_lines_quality_signal
float64
qsc_code_num_chars_line_max_quality_signal
float64
qsc_code_num_chars_line_mean_quality_signal
float64
qsc_code_frac_chars_alphabet_quality_signal
float64
qsc_code_frac_chars_comments_quality_signal
float64
qsc_code_cate_xml_start_quality_signal
float64
qsc_code_frac_lines_dupe_lines_quality_signal
float64
qsc_code_cate_autogen_quality_signal
float64
qsc_code_frac_lines_long_string_quality_signal
float64
qsc_code_frac_chars_string_length_quality_signal
float64
qsc_code_frac_chars_long_word_length_quality_signal
float64
qsc_code_frac_lines_string_concat_quality_signal
float64
qsc_code_cate_encoded_data_quality_signal
float64
qsc_code_frac_chars_hex_words_quality_signal
float64
qsc_code_frac_lines_prompt_comments_quality_signal
float64
qsc_code_frac_lines_assert_quality_signal
float64
qsc_codepython_cate_ast_quality_signal
float64
qsc_codepython_frac_lines_func_ratio_quality_signal
float64
qsc_codepython_cate_var_zero_quality_signal
bool
qsc_codepython_frac_lines_pass_quality_signal
float64
qsc_codepython_frac_lines_import_quality_signal
float64
qsc_codepython_frac_lines_simplefunc_quality_signal
float64
qsc_codepython_score_lines_no_logic_quality_signal
float64
qsc_codepython_frac_lines_print_quality_signal
float64
qsc_code_num_words
int64
qsc_code_num_chars
int64
qsc_code_mean_word_length
int64
qsc_code_frac_words_unique
null
qsc_code_frac_chars_top_2grams
int64
qsc_code_frac_chars_top_3grams
int64
qsc_code_frac_chars_top_4grams
int64
qsc_code_frac_chars_dupe_5grams
int64
qsc_code_frac_chars_dupe_6grams
int64
qsc_code_frac_chars_dupe_7grams
int64
qsc_code_frac_chars_dupe_8grams
int64
qsc_code_frac_chars_dupe_9grams
int64
qsc_code_frac_chars_dupe_10grams
int64
qsc_code_frac_chars_replacement_symbols
int64
qsc_code_frac_chars_digital
int64
qsc_code_frac_chars_whitespace
int64
qsc_code_size_file_byte
int64
qsc_code_num_lines
int64
qsc_code_num_chars_line_max
int64
qsc_code_num_chars_line_mean
int64
qsc_code_frac_chars_alphabet
int64
qsc_code_frac_chars_comments
int64
qsc_code_cate_xml_start
int64
qsc_code_frac_lines_dupe_lines
int64
qsc_code_cate_autogen
int64
qsc_code_frac_lines_long_string
int64
qsc_code_frac_chars_string_length
int64
qsc_code_frac_chars_long_word_length
int64
qsc_code_frac_lines_string_concat
null
qsc_code_cate_encoded_data
int64
qsc_code_frac_chars_hex_words
int64
qsc_code_frac_lines_prompt_comments
int64
qsc_code_frac_lines_assert
int64
qsc_codepython_cate_ast
int64
qsc_codepython_frac_lines_func_ratio
int64
qsc_codepython_cate_var_zero
int64
qsc_codepython_frac_lines_pass
int64
qsc_codepython_frac_lines_import
int64
qsc_codepython_frac_lines_simplefunc
int64
qsc_codepython_score_lines_no_logic
int64
qsc_codepython_frac_lines_print
int64
effective
string
hits
int64
8098676a40412eb52c1fff71d39e75e131acacd9
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py
Python
src/whylogs/src/whylabs/logs/core/statistics/datatypes/__init__.py
bernease/cli-demo-1
895d9eddc95ca3dd43b7ae8b33a8fbdedbc855f5
[ "Apache-2.0" ]
null
null
null
src/whylogs/src/whylabs/logs/core/statistics/datatypes/__init__.py
bernease/cli-demo-1
895d9eddc95ca3dd43b7ae8b33a8fbdedbc855f5
[ "Apache-2.0" ]
null
null
null
src/whylogs/src/whylabs/logs/core/statistics/datatypes/__init__.py
bernease/cli-demo-1
895d9eddc95ca3dd43b7ae8b33a8fbdedbc855f5
[ "Apache-2.0" ]
null
null
null
from .variancetracker import * from .integertracker import * from .floattracker import * from .stringtracker import *
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py
Python
models/autoencoder.py
garedaba/BERMUDA
ad989cbdae03efafe81d1d0aa36673dd6ffa2e14
[ "MIT" ]
null
null
null
models/autoencoder.py
garedaba/BERMUDA
ad989cbdae03efafe81d1d0aa36673dd6ffa2e14
[ "MIT" ]
null
null
null
models/autoencoder.py
garedaba/BERMUDA
ad989cbdae03efafe81d1d0aa36673dd6ffa2e14
[ "MIT" ]
null
null
null
#!/usr/bin/env python # coding: utf-8 import torch.nn as nn def init_weights(m): """ initialize weights of fully connected layer """ if type(m) == nn.Linear: nn.init.xavier_uniform_(m.weight) m.bias.data.fill_(0.01) # autoencoder with hidden units 20, latent, 20 # Encoder class Encoder_20(nn.Module): def __init__(self, num_inputs, code_dim): super(Encoder_20, self).__init__() self.encoder = nn.Sequential( nn.Linear(num_inputs, 20), nn.ReLU(), nn.Linear(20, code_dim)) self.encoder.apply(init_weights) def forward(self, x): x = self.encoder(x) return x # Decoder class Decoder_20(nn.Module): def __init__(self, num_inputs, code_dim): super(Decoder_20, self).__init__() self.decoder = nn.Sequential( nn.Linear(code_dim, 20), nn.ReLU(), nn.Linear(20, num_inputs), nn.Sigmoid()) self.decoder.apply(init_weights) def forward(self, x): x = self.decoder(x) return x # Autoencoder class autoencoder_20(nn.Module): def __init__(self, num_inputs, code_dim): super(autoencoder_20, self).__init__() self.encoder = Encoder_20(num_inputs, code_dim) self.decoder = Decoder_20(num_inputs, code_dim) def forward(self, x): code = self.encoder(x) x = self.decoder(code) return code, x # autoencoder with hidden units 100, latent, 100 # Encoder class Encoder_100(nn.Module): def __init__(self, num_inputs, code_dim): super(Encoder_100, self).__init__() self.encoder = nn.Sequential( nn.Linear(num_inputs, 100), nn.ReLU(), nn.Linear(100, code_dim)) self.encoder.apply(init_weights) def forward(self, x): x = self.encoder(x) return x # Decoder class Decoder_100(nn.Module): def __init__(self, num_inputs, code_dim): super(Decoder_100, self).__init__() self.decoder = nn.Sequential( nn.Linear(code_dim, 100), nn.ReLU(), nn.Linear(100, num_inputs), nn.Sigmoid()) self.decoder.apply(init_weights) def forward(self, x): x = self.decoder(x) return x # Autoencoder class autoencoder_100(nn.Module): def __init__(self, num_inputs, code_dim): super(autoencoder_100, self).__init__() self.encoder = Encoder_100(num_inputs, code_dim) self.decoder = Decoder_100(num_inputs, code_dim) def forward(self, x): code = self.encoder(x) x = self.decoder(code) return code, x # autoencoder with hidden units 8, 4, latent, 4, 8 class Encoder_3(nn.Module): def __init__(self, num_inputs, code_dim): super(Encoder_3, self).__init__() self.encoder = nn.Sequential( nn.Linear(num_inputs, 20), nn.ReLU(), nn.Linear(20, 10), nn.ReLU(), nn.Linear(10, code_dim)) self.encoder.apply(init_weights) def forward(self, x): x = self.encoder(x) return x # Decoder class Decoder_3(nn.Module): def __init__(self, num_inputs, code_dim): super(Decoder_3, self).__init__() self.decoder = nn.Sequential( nn.Linear(code_dim, 10), nn.ReLU(), nn.Linear(10, 20), nn.ReLU(), nn.Linear(20, num_inputs), nn.Sigmoid()) self.decoder.apply(init_weights) def forward(self, x): x = self.decoder(x) return x # Autoencoder class autoencoder_3(nn.Module): def __init__(self, num_inputs, code_dim): super(autoencoder_3, self).__init__() self.encoder = Encoder_3(num_inputs, code_dim) self.decoder = Decoder_3(num_inputs, code_dim) def forward(self, x): code = self.encoder(x) x = self.decoder(code) return code, x
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py
Python
zfit_physics/unstable/__init__.py
chm-ipmu/zfit-physics
9e6b1f857fe993fadb888612822c394db4d0f5c5
[ "BSD-3-Clause" ]
null
null
null
zfit_physics/unstable/__init__.py
chm-ipmu/zfit-physics
9e6b1f857fe993fadb888612822c394db4d0f5c5
[ "BSD-3-Clause" ]
null
null
null
zfit_physics/unstable/__init__.py
chm-ipmu/zfit-physics
9e6b1f857fe993fadb888612822c394db4d0f5c5
[ "BSD-3-Clause" ]
null
null
null
from . import pdf
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03d374576d2ec245ce83ddf40486d33b88e37cfb
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py
Python
src/sas/sascalc/pr/fit/__init__.py
opendatafit/sasview
c470220eecfc9f6d8a0e27e2ea8919dcb1b38e39
[ "BSD-3-Clause" ]
null
null
null
src/sas/sascalc/pr/fit/__init__.py
opendatafit/sasview
c470220eecfc9f6d8a0e27e2ea8919dcb1b38e39
[ "BSD-3-Clause" ]
1
2021-09-20T13:20:35.000Z
2021-09-20T13:20:35.000Z
src/sas/sascalc/pr/fit/__init__.py
opendatafit/sasview
c470220eecfc9f6d8a0e27e2ea8919dcb1b38e39
[ "BSD-3-Clause" ]
null
null
null
from .AbstractFitEngine import FitHandler
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03d3ede9bf333e5ac91b4bfab7687b8821f0f6c6
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py
Python
week10/CinemaReservation/hack_cinema/db_schema/__init__.py
HackBulgaria/Programming-101-Python-2020-Spring
443446028df7fe78fcdd6c37dada0b5cd8ed3c93
[ "MIT" ]
30
2020-01-22T17:22:43.000Z
2022-01-26T08:28:57.000Z
week10/CinemaReservation/hack_cinema/db_schema/__init__.py
HackBulgaria/Programming-101-Python-2020-Spring
443446028df7fe78fcdd6c37dada0b5cd8ed3c93
[ "MIT" ]
1
2020-01-21T19:50:47.000Z
2020-03-18T16:18:31.000Z
week10/CinemaReservation/hack_cinema/db_schema/__init__.py
HackBulgaria/Programming-101-Python-2020-Spring
443446028df7fe78fcdd6c37dada0b5cd8ed3c93
[ "MIT" ]
7
2019-11-28T15:59:16.000Z
2020-12-05T08:39:02.000Z
from .users import CREATE_USERS from .movies import CREATE_MOVIES
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ff04416537a6ec02a7d39411cd2da79a2c52d956
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py
Python
client_apis/python/test/test_conflict_error.py
alikins/galaxy-api-swaggerhub
5d6d4070cd6964c6d6217cad6743de89cf4eac24
[ "MIT" ]
null
null
null
client_apis/python/test/test_conflict_error.py
alikins/galaxy-api-swaggerhub
5d6d4070cd6964c6d6217cad6743de89cf4eac24
[ "MIT" ]
3
2020-07-17T10:18:45.000Z
2022-01-22T05:24:05.000Z
client_apis/python/test/test_conflict_error.py
alikins/galaxy-api-swaggerhub
5d6d4070cd6964c6d6217cad6743de89cf4eac24
[ "MIT" ]
null
null
null
# coding: utf-8 """ Galaxy 3.2 API (wip) Galaxy 3.2 API (wip) # noqa: E501 The version of the OpenAPI document: 1.2.0 Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import unittest import openapi_client from openapi_client.models.conflict_error import ConflictError # noqa: E501 from openapi_client.rest import ApiException class TestConflictError(unittest.TestCase): """ConflictError unit test stubs""" def setUp(self): pass def tearDown(self): pass def testConflictError(self): """Test ConflictError""" # FIXME: construct object with mandatory attributes with example values # model = openapi_client.models.conflict_error.ConflictError() # noqa: E501 pass if __name__ == '__main__': unittest.main()
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206b7a3d5225ff49bcbb58405bc70465ecf3e182
69
py
Python
sklearnbot/__init__.py
openml/sklearn-bot
7476dd6e27f087166fc416974fc67a78dd4fa4d2
[ "BSD-3-Clause" ]
1
2020-05-06T14:54:32.000Z
2020-05-06T14:54:32.000Z
sklearnbot/__init__.py
openml/sklearn-bot
7476dd6e27f087166fc416974fc67a78dd4fa4d2
[ "BSD-3-Clause" ]
2
2018-10-07T17:30:03.000Z
2018-10-19T00:06:35.000Z
sklearnbot/__init__.py
openml/sklearn-bot
7476dd6e27f087166fc416974fc67a78dd4fa4d2
[ "BSD-3-Clause" ]
1
2019-07-03T20:35:22.000Z
2019-07-03T20:35:22.000Z
from . import bot from . import config_spaces from . import sklearn
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209515769e0305875dba77990be0750bb976af34
9,391
py
Python
legacy/minimize.py
patrikkj/algorithms
25799fb57807eca1784202c499fda8a5a94acea3
[ "MIT" ]
null
null
null
legacy/minimize.py
patrikkj/algorithms
25799fb57807eca1784202c499fda8a5a94acea3
[ "MIT" ]
null
null
null
legacy/minimize.py
patrikkj/algorithms
25799fb57807eca1784202c499fda8a5a94acea3
[ "MIT" ]
null
null
null
import numpy as np from .helpers import (step_adam, step_gradient_descent, step_momentum, step_rmsprop) def mini_batch_gradient_descent(params, X, y, cost_func, grad_func, alpha=0.01, epochs=100, k=64, l=0, step_func=None, **hparams): """Minimizes the objective function using mini-batch gradient descent. Args: params (ndarray[1, n]): initial parameters X (ndarray[m, ...]): input features y (ndarray[m, 1]): output labels cost_func (... -> float32): mapping of the form (params, X, Y) -> cost grad_func (... -> ndarray[1, n]): gradients of cost function alpha (float, optional): learning rate (defaults to 0.01) epochs (int, optional): number of iterations (defaults to 100) k (int, optional): mini-batch size (defaults to 64) l (float, optional): regularization parameter (defaults to 0) Returns: params (ndarray[1, n]): updated parameters costs (ndarray[epochs, 1]): costs for each batch iteration grads (ndarray[n, epochs]): gradients for each batch iteration """ # Initialization if step_func is None: step_func = step_gradient_descent costs, grads = [], [] for _ in range(epochs): # Shuffle input and labels m = X.shape[0] p = np.random.permutation(m) X, y = X[p], y[p] # Partition input and labels X_batches = np.split(X, range(k, m, k)) y_batches = np.split(y, range(k, m, k)) # Perform a single iteration of gradient descent for every mini-batch for X_batch, y_batch in zip(X_batches, y_batches): grad = grad_func(params, X_batch, y_batch, l) cost = cost_func(params, X_batch, y_batch, l) params = step_func(params, grad, alpha, **hparams) costs.append(cost) grads.append(grad) return params, np.array(costs), np.array(grads) def batch_gradient_descent(params, X, y, cost_func, grad_func, alpha=0.01, epochs=100, l=0): """Minimizes the objective function using batch gradient descent. Args: params (ndarray[1, n]): initial parameters X (ndarray[m, ...]): input features y (ndarray[m, 1]): output labels cost_func (... -> float32): mapping of the form (params, X, Y) -> cost grad_func (... -> ndarray[1, n]): gradients of cost function alpha (float, optional): learning rate (defaults to 0.01) epochs (int, optional): number of iterations (defaults to 100) l (float, optional): regularization parameter (defaults to 0) Returns: params (ndarray[1, n]): updated parameters costs (ndarray[epochs, 1]): costs for each batch iteration grads (ndarray[n, epochs]): gradients for each batch iteration """ return mini_batch_gradient_descent(params, X, y, cost_func, grad_func, alpha, epochs, X.shape[0], l) def stochastic_gradient_descent(params, X, y, cost_func, grad_func, alpha=0.01, epochs=100, l=0): """Minimizes the objective function using stochastic gradient descent. Args: params (ndarray[1, n]): initial parameters X (ndarray[m, ...]): input features y (ndarray[m, 1]): output labels cost_func (... -> float32): mapping of the form (params, X, Y) -> cost grad_func (... -> ndarray[1, n]): gradients of cost function alpha (float, optional): learning rate (defaults to 0.01) epochs (int, optional): number of iterations (defaults to 100) l (float, optional): regularization parameter (defaults to 0) Returns: params (ndarray[1, n]): updated parameters costs (ndarray[epochs, 1]): costs for each batch iteration grads (ndarray[n, epochs]): gradients for each batch iteration """ return mini_batch_gradient_descent(params, X, y, cost_func, grad_func, alpha, epochs, 1, l) def momentum_gradient_descent(params, X, y, cost_func, grad_func, alpha=0.01, epochs=100, k=64, l=0, beta=0.9): """Minimizes the objective function using mini-batch gradient descent w/ momentum. Args: params (ndarray[1, n]): initial parameters X (ndarray[m, ...]): input features y (ndarray[m, 1]): output labels cost_func (... -> float32): mapping of the form (params, X, Y) -> cost grad_func (... -> ndarray[1, n]): gradients of cost function alpha (float, optional): learning rate (defaults to 0.01) epochs (int, optional): number of iterations (defaults to 100) k (int, optional): mini-batch size (defaults to 64) l (float, optional): regularization parameter (defaults to 0) beta (float, optional): moment decay rate (defaults to 0.9) Returns: params (ndarray[1, n]): updated parameters costs (ndarray[epochs, 1]): costs for each batch iteration grads (ndarray[n, epochs]): gradients for each batch iteration """ args = (params, X, y, cost_func, grad_func) kwargs = { 'alpha': alpha, 'epochs': epochs, 'k': k, 'l': l, 'step_func': step_momentum } hparams = { # Hyperparameters passed to the step function 'v': np.zeros(params.shape), 'beta': beta } return mini_batch_gradient_descent(*args, **kwargs, **hparams) def rmsprop(params, X, y, cost_func, grad_func, alpha=0.01, epochs=100, k=64, l=0, beta=0.9): """Minimizes the objective function using RMSprop. Args: params (ndarray[1, n]): initial parameters X (ndarray[m, ...]): input features y (ndarray[m, 1]): output labels cost_func (... -> float32): mapping of the form (params, X, Y) -> cost grad_func (... -> ndarray[1, n]): gradients of cost function alpha (float, optional): learning rate (defaults to 0.01) epochs (int, optional): number of iterations (defaults to 100) k (int, optional): mini-batch size (defaults to 64) l (float, optional): regularization parameter (defaults to 0) beta (float, optional): moment decay rate (defaults to 0.9) Returns: params (ndarray[1, n]): updated parameters costs (ndarray[epochs, 1]): costs for each batch iteration grads (ndarray[n, epochs]): gradients for each batch iteration """ args = (params, X, y, cost_func, grad_func) kwargs = { 'alpha': alpha, 'epochs': epochs, 'k': k, 'l': l, 'step_func': step_rmsprop } hparams = { # Hyperparameters passed to the step function 's': np.zeros(params.shape), 'beta': beta } return mini_batch_gradient_descent(*args, **kwargs, **hparams) def adam(params, X, y, cost_func, grad_func, alpha=0.01, epochs=100, k=64, l=0, beta1=0.9, beta2=0.999, epsilon=10e-8): """Minimizes the objective function using Adam. Args: params (ndarray[1, n]): initial parameters X (ndarray[m, ...]): input features y (ndarray[m, 1]): output labels cost_func (... -> float32): mapping of the form (params, X, Y) -> cost grad_func (... -> ndarray[1, n]): gradients of cost function alpha (float, optional): learning rate (defaults to 0.01) epochs (int, optional): number of iterations (defaults to 100) k (int, optional): mini-batch size (defaults to 64) l (float, optional): regularization parameter (defaults to 0) beta1 (float, optional): 1st order moment decay rate (defaults to 0.9) beta2 (float, optional): 2nd order moment decay rate (defaults to 0.999) epsilon (float, optional): numerical stability constant (defaults to 10e-8) Returns: params (ndarray[1, n]): updated parameters costs (ndarray[epochs, 1]): costs for each batch iteration grads (ndarray[n, epochs]): gradients for each batch iteration """ args = (params, X, y, cost_func, grad_func) kwargs = { 'alpha': alpha, 'epochs': epochs, 'k': k, 'l': l, 'step_func': step_adam } hparams = { # Hyperparameters passed to the step function 'v': np.zeros(params.shape), 's': np.zeros(params.shape), 't': np.array([0]), 'beta1': beta1, 'beta2': beta2, 'epsilon': epsilon } return mini_batch_gradient_descent(*args, **kwargs, **hparams)
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py
Python
tests/integration/__init__.py
wlan0/docker-py
ae11d81b183db2f6641c6e64329820ac10597a13
[ "Apache-2.0" ]
null
null
null
tests/integration/__init__.py
wlan0/docker-py
ae11d81b183db2f6641c6e64329820ac10597a13
[ "Apache-2.0" ]
null
null
null
tests/integration/__init__.py
wlan0/docker-py
ae11d81b183db2f6641c6e64329820ac10597a13
[ "Apache-2.0" ]
null
null
null
# flake8: noqa # FIXME: crutch while we transition to the new folder architecture # Remove imports when merged in master and Jenkins is updated to find the # tests in the new location. from .api_test import * from .build_test import * from .container_test import * from .exec_test import * from .image_test import * from .network_test import * from .regression_test import * from .volume_test import *
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py
Python
exercises/transpose/transpose.py
RJTK/python
f9678d629735f75354bbd543eb7f10220a498dae
[ "MIT" ]
1
2021-05-15T19:59:04.000Z
2021-05-15T19:59:04.000Z
exercises/transpose/transpose.py
RJTK/python
f9678d629735f75354bbd543eb7f10220a498dae
[ "MIT" ]
null
null
null
exercises/transpose/transpose.py
RJTK/python
f9678d629735f75354bbd543eb7f10220a498dae
[ "MIT" ]
2
2018-03-03T08:32:12.000Z
2019-08-22T11:55:53.000Z
def transpose(): pass
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py
Python
FastlyPythonCLI/scripts/WAF/emergency.py
hummelm10/FastlyPythonAPI
cf2d880649319c56f38a74bc76ea50c642ad2f11
[ "MIT" ]
1
2020-05-06T17:07:52.000Z
2020-05-06T17:07:52.000Z
FastlyPythonCLI/scripts/WAF/emergency.py
hummelm10/FastlyPythonAPI
cf2d880649319c56f38a74bc76ea50c642ad2f11
[ "MIT" ]
null
null
null
FastlyPythonCLI/scripts/WAF/emergency.py
hummelm10/FastlyPythonAPI
cf2d880649319c56f38a74bc76ea50c642ad2f11
[ "MIT" ]
null
null
null
import requests import scripts import pprint import pandas from .listWAFIDs import listWAFIDsNoPrompt def disableWAF(): print(scripts.bcolors.FAIL + scripts.bcolors.UNDERLINE + "EMERGENCY DISABLE: THIS IS TO BE USED IN AN EMERGENCY ONLY\n(Requires Superuser permissions)" + scripts.bcolors.ENDC + scripts.bcolors.ENDC) if scripts.checkAPINoPrint(): dfObj = listWAFIDsNoPrompt() try: inVar = int(input("\n\nEnter index of WAF to display [Enter to exit]: ")) print(str(dfObj['WAF ID'].iloc[inVar])) except: e = input("Not a valid number. Press enter to continue or E to exit...") if e.strip(' ').lower() == 'e': scripts.clear() scripts.WAFMenu() scripts.clear() disableWAF() print(scripts.bcolors.WARNING + scripts.bcolors.UNDERLINE + "EMERGENCY DISABLE: THIS IS TO BE USED IN AN EMERGENCY ONLY" + scripts.bcolors.ENDC + scripts.bcolors.ENDC) while "Not a valid response.": reply = str(input("Request: https://api.fastly.com/wafs/" + str(dfObj['WAF ID'].iloc[inVar]) + "/disable\nCorrect service " + str(dfObj['Name'].iloc[inVar]) + " [Y/n]: ")).lower().strip() if reply[0] == 'y': break if reply[0] == 'n': scripts.clear() disableWAF() break header={"Accept":"application/vnd.api+json"} header.update({"Content-Type":"application/vnd.api+json"}) header.update({"Fastly-Key":scripts.getKeyFromConfig()}) r=requests.patch("https://api.fastly.com/wafs/" + str(dfObj['WAF ID'].iloc[inVar]) + "/disable",headers=header) if r.status_code == 202: print(scripts.bcolors.OKGREEN + "Disabled WAF" + scripts.bcolors.ENDC) pprint.pprint(r.json()['data']) input("Press ENTER to return to menu...") else: input(scripts.bcolors.WARNING + "Error with request.\nStatus: " + str(r.status_code) + "\nPress ENTER to continue..." + scripts.bcolors.ENDC) else: input(scripts.bcolors.WARNING + "Error with API Key, generate a new one. Press ENTER to continue..." + scripts.bcolors.ENDC) def enableWAF(): print(scripts.bcolors.WARNING + scripts.bcolors.UNDERLINE + "EMERGENCY ENABLE: THIS IS TO BE USED IN AN EMERGENCY ONLY (only works on emergency disabled WAF)\n(Requires Superuser permissions)" + scripts.bcolors.ENDC + scripts.bcolors.ENDC) if scripts.checkAPINoPrint(): dfObj = listWAFIDsNoPrompt() try: inVar = int(input("\n\nEnter index of WAF to display: ")) str(dfObj['WAF ID'].iloc[inVar]) except: e = input("Not a valid number. Press enter to continue or E to exit...") if e.strip(' ').lower() == 'e': scripts.clear() scripts.WAFMenu() scripts.clear() enableWAF() header={"Accept":"application/vnd.api+json"} header.update({"Content-Type":"application/vnd.api+json"}) header.update({"Fastly-Key":scripts.getKeyFromConfig()}) r=requests.patch("https://api.fastly.com/wafs/" + str(dfObj['WAF ID'].iloc[inVar]) + "/enable",headers=header) if r.status_code == 202: print(scripts.bcolors.OKGREEN + "Enabled WAF" + scripts.bcolors.ENDC) pprint.pprint(r.json()['data']) input("Press ENTER to return to menu...") else: input(scripts.bcolors.WARNING + "Error with request.\nStatus: " + str(r.status_code) + "\nPress ENTER to continue..." + scripts.bcolors.ENDC) else: input(scripts.bcolors.WARNING + "Error with API Key, generate a new one. Press ENTER to continue..." + scripts.bcolors.ENDC)
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4561c551d821590b6ee24ff780ae4785a6cc7028
38,036
py
Python
instances/passenger_demand/pas-20210421-2109-int18e/47.py
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
[ "BSD-3-Clause" ]
null
null
null
instances/passenger_demand/pas-20210421-2109-int18e/47.py
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
[ "BSD-3-Clause" ]
null
null
null
instances/passenger_demand/pas-20210421-2109-int18e/47.py
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
[ "BSD-3-Clause" ]
null
null
null
""" PASSENGERS """ numPassengers = 4249 passenger_arriving = ( (2, 15, 5, 3, 2, 0, 9, 9, 8, 5, 1, 0), # 0 (4, 9, 10, 3, 3, 0, 12, 10, 7, 10, 3, 0), # 1 (2, 6, 7, 2, 2, 0, 3, 17, 5, 7, 3, 0), # 2 (6, 13, 7, 7, 4, 0, 7, 14, 5, 7, 2, 0), # 3 (5, 12, 9, 3, 3, 0, 12, 10, 9, 9, 3, 0), # 4 (4, 13, 14, 5, 0, 0, 4, 7, 7, 4, 0, 0), # 5 (9, 12, 8, 4, 2, 0, 10, 8, 8, 5, 6, 0), # 6 (5, 8, 6, 5, 2, 0, 5, 11, 10, 5, 2, 0), # 7 (7, 10, 7, 11, 2, 0, 7, 4, 9, 11, 6, 0), # 8 (9, 14, 2, 3, 2, 0, 7, 16, 7, 8, 3, 0), # 9 (6, 7, 16, 5, 2, 0, 3, 8, 9, 10, 2, 0), # 10 (7, 14, 7, 2, 5, 0, 16, 10, 6, 3, 5, 0), # 11 (7, 9, 9, 9, 5, 0, 6, 14, 5, 2, 1, 0), # 12 (10, 13, 7, 2, 4, 0, 8, 9, 5, 8, 3, 0), # 13 (5, 16, 11, 5, 1, 0, 10, 11, 11, 9, 1, 0), # 14 (3, 10, 7, 6, 2, 0, 7, 7, 7, 12, 3, 0), # 15 (4, 14, 9, 6, 5, 0, 15, 16, 8, 5, 3, 0), # 16 (3, 13, 8, 7, 4, 0, 9, 7, 9, 6, 5, 0), # 17 (5, 8, 11, 3, 8, 0, 6, 15, 8, 10, 1, 0), # 18 (8, 14, 8, 3, 3, 0, 6, 19, 7, 5, 2, 0), # 19 (7, 14, 12, 9, 2, 0, 7, 10, 8, 6, 3, 0), # 20 (4, 13, 13, 2, 3, 0, 5, 10, 13, 4, 3, 0), # 21 (10, 11, 10, 5, 4, 0, 8, 8, 6, 8, 2, 0), # 22 (9, 11, 8, 5, 4, 0, 11, 17, 5, 7, 3, 0), # 23 (7, 21, 8, 5, 5, 0, 3, 15, 11, 9, 3, 0), # 24 (5, 11, 12, 5, 1, 0, 11, 15, 6, 4, 3, 0), # 25 (4, 8, 12, 4, 1, 0, 11, 18, 10, 5, 2, 0), # 26 (6, 11, 9, 10, 4, 0, 6, 21, 6, 5, 2, 0), # 27 (7, 15, 10, 1, 1, 0, 7, 11, 10, 5, 4, 0), # 28 (5, 13, 9, 3, 4, 0, 6, 11, 10, 7, 3, 0), # 29 (5, 18, 10, 5, 1, 0, 8, 8, 6, 5, 3, 0), # 30 (10, 10, 4, 5, 0, 0, 5, 12, 9, 5, 4, 0), # 31 (4, 13, 16, 1, 2, 0, 19, 11, 7, 5, 5, 0), # 32 (5, 13, 11, 5, 1, 0, 11, 7, 10, 4, 3, 0), # 33 (2, 17, 6, 3, 2, 0, 9, 4, 11, 4, 3, 0), # 34 (11, 9, 12, 5, 6, 0, 3, 7, 9, 4, 0, 0), # 35 (6, 10, 10, 4, 2, 0, 8, 16, 9, 5, 6, 0), # 36 (9, 9, 11, 4, 5, 0, 13, 13, 0, 4, 1, 0), # 37 (3, 9, 9, 3, 5, 0, 10, 10, 4, 4, 2, 0), # 38 (1, 16, 17, 8, 2, 0, 5, 12, 5, 5, 1, 0), # 39 (6, 10, 8, 4, 2, 0, 3, 15, 3, 5, 2, 0), # 40 (7, 7, 12, 3, 4, 0, 10, 13, 9, 9, 4, 0), # 41 (6, 10, 7, 6, 3, 0, 8, 9, 11, 7, 3, 0), # 42 (5, 21, 9, 5, 8, 0, 4, 10, 7, 5, 1, 0), # 43 (6, 11, 10, 6, 2, 0, 10, 8, 5, 3, 5, 0), # 44 (8, 10, 4, 3, 2, 0, 7, 10, 8, 5, 4, 0), # 45 (5, 14, 11, 5, 3, 0, 9, 15, 18, 8, 3, 0), # 46 (8, 9, 15, 5, 1, 0, 2, 6, 7, 2, 1, 0), # 47 (7, 17, 10, 9, 3, 0, 9, 21, 10, 7, 5, 0), # 48 (9, 11, 11, 4, 4, 0, 10, 10, 11, 9, 3, 0), # 49 (3, 13, 7, 7, 8, 0, 4, 10, 8, 3, 4, 0), # 50 (5, 12, 10, 4, 3, 0, 12, 15, 8, 9, 4, 0), # 51 (6, 16, 14, 5, 6, 0, 8, 11, 7, 7, 4, 0), # 52 (11, 11, 8, 8, 2, 0, 6, 13, 8, 8, 5, 0), # 53 (12, 15, 6, 5, 3, 0, 8, 11, 3, 3, 6, 0), # 54 (7, 12, 14, 3, 2, 0, 3, 13, 4, 8, 5, 0), # 55 (8, 13, 8, 5, 4, 0, 4, 13, 4, 10, 1, 0), # 56 (7, 15, 6, 3, 3, 0, 8, 9, 11, 7, 2, 0), # 57 (3, 19, 11, 5, 4, 0, 5, 13, 8, 4, 5, 0), # 58 (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 59 ) station_arriving_intensity = ( (4.769372805092186, 12.233629261363635, 14.389624839331619, 11.405298913043477, 12.857451923076923, 8.562228260869567), # 0 (4.81413961808604, 12.369674877683082, 14.46734796754499, 11.46881589673913, 12.953819711538461, 8.559309850543478), # 1 (4.8583952589991215, 12.503702525252525, 14.54322622107969, 11.530934782608696, 13.048153846153847, 8.556302173913043), # 2 (4.902102161984196, 12.635567578125, 14.617204169344474, 11.591602581521737, 13.14036778846154, 8.553205638586958), # 3 (4.94522276119403, 12.765125410353535, 14.689226381748071, 11.650766304347826, 13.230375, 8.550020652173911), # 4 (4.987719490781387, 12.892231395991162, 14.759237427699228, 11.708372961956522, 13.318088942307691, 8.546747622282608), # 5 (5.029554784899035, 13.01674090909091, 14.827181876606687, 11.764369565217393, 13.403423076923078, 8.54338695652174), # 6 (5.0706910776997365, 13.138509323705808, 14.893004297879177, 11.818703125, 13.486290865384618, 8.5399390625), # 7 (5.1110908033362605, 13.257392013888888, 14.956649260925452, 11.871320652173912, 13.56660576923077, 8.536404347826087), # 8 (5.1507163959613695, 13.373244353693181, 15.018061335154243, 11.922169157608696, 13.644281249999999, 8.532783220108696), # 9 (5.1895302897278315, 13.485921717171717, 15.077185089974291, 11.971195652173915, 13.719230769230771, 8.529076086956522), # 10 (5.227494918788412, 13.595279478377526, 15.133965094794343, 12.018347146739131, 13.791367788461539, 8.525283355978262), # 11 (5.2645727172958745, 13.701173011363636, 15.188345919023137, 12.063570652173912, 13.860605769230768, 8.521405434782608), # 12 (5.3007261194029835, 13.803457690183082, 15.240272132069407, 12.106813179347826, 13.926858173076925, 8.51744273097826), # 13 (5.335917559262511, 13.90198888888889, 15.289688303341899, 12.148021739130433, 13.99003846153846, 8.513395652173912), # 14 (5.370109471027217, 13.996621981534089, 15.336539002249355, 12.187143342391304, 14.050060096153846, 8.509264605978261), # 15 (5.403264288849868, 14.087212342171718, 15.380768798200515, 12.224124999999999, 14.10683653846154, 8.50505), # 16 (5.4353444468832315, 14.173615344854797, 15.422322260604112, 12.258913722826087, 14.16028125, 8.500752241847827), # 17 (5.46631237928007, 14.255686363636363, 15.461143958868895, 12.291456521739132, 14.210307692307696, 8.496371739130435), # 18 (5.496130520193152, 14.333280772569443, 15.4971784624036, 12.321700407608695, 14.256829326923079, 8.491908899456522), # 19 (5.524761303775241, 14.40625394570707, 15.530370340616965, 12.349592391304348, 14.299759615384616, 8.487364130434782), # 20 (5.552167164179106, 14.47446125710227, 15.56066416291774, 12.375079483695652, 14.339012019230768, 8.482737839673913), # 21 (5.578310535557506, 14.537758080808082, 15.588004498714653, 12.398108695652175, 14.374499999999998, 8.47803043478261), # 22 (5.603153852063214, 14.595999790877526, 15.612335917416454, 12.418627038043478, 14.40613701923077, 8.473242323369567), # 23 (5.62665954784899, 14.649041761363636, 15.633602988431875, 12.43658152173913, 14.433836538461538, 8.468373913043479), # 24 (5.648790057067603, 14.696739366319445, 15.651750281169667, 12.451919157608696, 14.457512019230768, 8.463425611413044), # 25 (5.669507813871817, 14.738947979797977, 15.66672236503856, 12.464586956521739, 14.477076923076922, 8.458397826086957), # 26 (5.688775252414398, 14.77552297585227, 15.6784638094473, 12.474531929347828, 14.492444711538463, 8.453290964673915), # 27 (5.7065548068481124, 14.806319728535353, 15.68691918380463, 12.481701086956523, 14.503528846153845, 8.448105434782608), # 28 (5.722808911325724, 14.831193611900254, 15.69203305751928, 12.486041440217392, 14.510242788461538, 8.44284164402174), # 29 (5.7375, 14.85, 15.69375, 12.4875, 14.512500000000001, 8.4375), # 30 (5.751246651214834, 14.865621839488634, 15.692462907608693, 12.487236580882353, 14.511678590425532, 8.430077267616193), # 31 (5.7646965153452685, 14.881037215909092, 15.68863804347826, 12.486451470588234, 14.509231914893617, 8.418644565217393), # 32 (5.777855634590792, 14.896244211647728, 15.682330027173915, 12.485152389705883, 14.50518630319149, 8.403313830584706), # 33 (5.790730051150895, 14.91124090909091, 15.67359347826087, 12.483347058823531, 14.499568085106382, 8.38419700149925), # 34 (5.803325807225064, 14.926025390624996, 15.662483016304348, 12.481043198529411, 14.492403590425532, 8.361406015742128), # 35 (5.815648945012788, 14.940595738636366, 15.649053260869564, 12.478248529411767, 14.48371914893617, 8.335052811094453), # 36 (5.8277055067135555, 14.954950035511365, 15.63335883152174, 12.474970772058823, 14.47354109042553, 8.305249325337332), # 37 (5.839501534526853, 14.969086363636364, 15.615454347826088, 12.471217647058824, 14.461895744680852, 8.272107496251873), # 38 (5.851043070652174, 14.983002805397728, 15.595394429347825, 12.466996875000001, 14.44880944148936, 8.23573926161919), # 39 (5.862336157289003, 14.99669744318182, 15.573233695652176, 12.462316176470589, 14.434308510638296, 8.196256559220389), # 40 (5.873386836636828, 15.010168359374997, 15.549026766304348, 12.457183272058824, 14.418419281914893, 8.153771326836583), # 41 (5.88420115089514, 15.023413636363639, 15.522828260869566, 12.451605882352942, 14.401168085106384, 8.108395502248875), # 42 (5.894785142263428, 15.03643135653409, 15.494692798913043, 12.445591727941178, 14.38258125, 8.060241023238381), # 43 (5.905144852941176, 15.049219602272727, 15.464675, 12.439148529411764, 14.36268510638298, 8.009419827586207), # 44 (5.915286325127877, 15.061776455965909, 15.432829483695656, 12.43228400735294, 14.341505984042554, 7.956043853073464), # 45 (5.925215601023019, 15.074100000000003, 15.39921086956522, 12.425005882352941, 14.319070212765958, 7.90022503748126), # 46 (5.934938722826087, 15.086188316761364, 15.363873777173913, 12.417321874999999, 14.295404122340427, 7.842075318590705), # 47 (5.944461732736574, 15.098039488636365, 15.326872826086957, 12.409239705882353, 14.27053404255319, 7.7817066341829095), # 48 (5.953790672953963, 15.10965159801136, 15.288262635869566, 12.400767095588236, 14.24448630319149, 7.71923092203898), # 49 (5.96293158567775, 15.121022727272724, 15.248097826086958, 12.391911764705883, 14.217287234042553, 7.65476011994003), # 50 (5.971890513107417, 15.132150958806818, 15.206433016304347, 12.38268143382353, 14.188963164893616, 7.588406165667167), # 51 (5.980673497442456, 15.143034375, 15.163322826086954, 12.373083823529411, 14.159540425531915, 7.5202809970015), # 52 (5.989286580882353, 15.153671058238638, 15.118821875, 12.363126654411765, 14.129045345744682, 7.450496551724138), # 53 (5.9977358056266, 15.164059090909088, 15.072984782608694, 12.352817647058824, 14.09750425531915, 7.379164767616192), # 54 (6.00602721387468, 15.174196555397728, 15.02586616847826, 12.342164522058825, 14.064943484042553, 7.306397582458771), # 55 (6.014166847826087, 15.184081534090907, 14.977520652173913, 12.331175, 14.031389361702129, 7.232306934032984), # 56 (6.022160749680308, 15.193712109375003, 14.92800285326087, 12.319856801470587, 13.996868218085105, 7.15700476011994), # 57 (6.030014961636829, 15.203086363636363, 14.877367391304347, 12.308217647058825, 13.961406382978723, 7.0806029985007495), # 58 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59 ) passenger_arriving_acc = ( (2, 15, 5, 3, 2, 0, 9, 9, 8, 5, 1, 0), # 0 (6, 24, 15, 6, 5, 0, 21, 19, 15, 15, 4, 0), # 1 (8, 30, 22, 8, 7, 0, 24, 36, 20, 22, 7, 0), # 2 (14, 43, 29, 15, 11, 0, 31, 50, 25, 29, 9, 0), # 3 (19, 55, 38, 18, 14, 0, 43, 60, 34, 38, 12, 0), # 4 (23, 68, 52, 23, 14, 0, 47, 67, 41, 42, 12, 0), # 5 (32, 80, 60, 27, 16, 0, 57, 75, 49, 47, 18, 0), # 6 (37, 88, 66, 32, 18, 0, 62, 86, 59, 52, 20, 0), # 7 (44, 98, 73, 43, 20, 0, 69, 90, 68, 63, 26, 0), # 8 (53, 112, 75, 46, 22, 0, 76, 106, 75, 71, 29, 0), # 9 (59, 119, 91, 51, 24, 0, 79, 114, 84, 81, 31, 0), # 10 (66, 133, 98, 53, 29, 0, 95, 124, 90, 84, 36, 0), # 11 (73, 142, 107, 62, 34, 0, 101, 138, 95, 86, 37, 0), # 12 (83, 155, 114, 64, 38, 0, 109, 147, 100, 94, 40, 0), # 13 (88, 171, 125, 69, 39, 0, 119, 158, 111, 103, 41, 0), # 14 (91, 181, 132, 75, 41, 0, 126, 165, 118, 115, 44, 0), # 15 (95, 195, 141, 81, 46, 0, 141, 181, 126, 120, 47, 0), # 16 (98, 208, 149, 88, 50, 0, 150, 188, 135, 126, 52, 0), # 17 (103, 216, 160, 91, 58, 0, 156, 203, 143, 136, 53, 0), # 18 (111, 230, 168, 94, 61, 0, 162, 222, 150, 141, 55, 0), # 19 (118, 244, 180, 103, 63, 0, 169, 232, 158, 147, 58, 0), # 20 (122, 257, 193, 105, 66, 0, 174, 242, 171, 151, 61, 0), # 21 (132, 268, 203, 110, 70, 0, 182, 250, 177, 159, 63, 0), # 22 (141, 279, 211, 115, 74, 0, 193, 267, 182, 166, 66, 0), # 23 (148, 300, 219, 120, 79, 0, 196, 282, 193, 175, 69, 0), # 24 (153, 311, 231, 125, 80, 0, 207, 297, 199, 179, 72, 0), # 25 (157, 319, 243, 129, 81, 0, 218, 315, 209, 184, 74, 0), # 26 (163, 330, 252, 139, 85, 0, 224, 336, 215, 189, 76, 0), # 27 (170, 345, 262, 140, 86, 0, 231, 347, 225, 194, 80, 0), # 28 (175, 358, 271, 143, 90, 0, 237, 358, 235, 201, 83, 0), # 29 (180, 376, 281, 148, 91, 0, 245, 366, 241, 206, 86, 0), # 30 (190, 386, 285, 153, 91, 0, 250, 378, 250, 211, 90, 0), # 31 (194, 399, 301, 154, 93, 0, 269, 389, 257, 216, 95, 0), # 32 (199, 412, 312, 159, 94, 0, 280, 396, 267, 220, 98, 0), # 33 (201, 429, 318, 162, 96, 0, 289, 400, 278, 224, 101, 0), # 34 (212, 438, 330, 167, 102, 0, 292, 407, 287, 228, 101, 0), # 35 (218, 448, 340, 171, 104, 0, 300, 423, 296, 233, 107, 0), # 36 (227, 457, 351, 175, 109, 0, 313, 436, 296, 237, 108, 0), # 37 (230, 466, 360, 178, 114, 0, 323, 446, 300, 241, 110, 0), # 38 (231, 482, 377, 186, 116, 0, 328, 458, 305, 246, 111, 0), # 39 (237, 492, 385, 190, 118, 0, 331, 473, 308, 251, 113, 0), # 40 (244, 499, 397, 193, 122, 0, 341, 486, 317, 260, 117, 0), # 41 (250, 509, 404, 199, 125, 0, 349, 495, 328, 267, 120, 0), # 42 (255, 530, 413, 204, 133, 0, 353, 505, 335, 272, 121, 0), # 43 (261, 541, 423, 210, 135, 0, 363, 513, 340, 275, 126, 0), # 44 (269, 551, 427, 213, 137, 0, 370, 523, 348, 280, 130, 0), # 45 (274, 565, 438, 218, 140, 0, 379, 538, 366, 288, 133, 0), # 46 (282, 574, 453, 223, 141, 0, 381, 544, 373, 290, 134, 0), # 47 (289, 591, 463, 232, 144, 0, 390, 565, 383, 297, 139, 0), # 48 (298, 602, 474, 236, 148, 0, 400, 575, 394, 306, 142, 0), # 49 (301, 615, 481, 243, 156, 0, 404, 585, 402, 309, 146, 0), # 50 (306, 627, 491, 247, 159, 0, 416, 600, 410, 318, 150, 0), # 51 (312, 643, 505, 252, 165, 0, 424, 611, 417, 325, 154, 0), # 52 (323, 654, 513, 260, 167, 0, 430, 624, 425, 333, 159, 0), # 53 (335, 669, 519, 265, 170, 0, 438, 635, 428, 336, 165, 0), # 54 (342, 681, 533, 268, 172, 0, 441, 648, 432, 344, 170, 0), # 55 (350, 694, 541, 273, 176, 0, 445, 661, 436, 354, 171, 0), # 56 (357, 709, 547, 276, 179, 0, 453, 670, 447, 361, 173, 0), # 57 (360, 728, 558, 281, 183, 0, 458, 683, 455, 365, 178, 0), # 58 (360, 728, 558, 281, 183, 0, 458, 683, 455, 365, 178, 0), # 59 ) passenger_arriving_rate = ( (4.769372805092186, 9.786903409090908, 8.63377490359897, 4.56211956521739, 2.5714903846153843, 0.0, 8.562228260869567, 10.285961538461537, 6.843179347826086, 5.755849935732647, 2.446725852272727, 0.0), # 0 (4.81413961808604, 9.895739902146465, 8.680408780526994, 4.587526358695651, 2.5907639423076922, 0.0, 8.559309850543478, 10.363055769230769, 6.881289538043478, 5.786939187017995, 2.4739349755366162, 0.0), # 1 (4.8583952589991215, 10.00296202020202, 8.725935732647814, 4.612373913043478, 2.609630769230769, 0.0, 8.556302173913043, 10.438523076923076, 6.918560869565217, 5.817290488431875, 2.500740505050505, 0.0), # 2 (4.902102161984196, 10.1084540625, 8.770322501606683, 4.636641032608694, 2.628073557692308, 0.0, 8.553205638586958, 10.512294230769232, 6.954961548913042, 5.846881667737789, 2.527113515625, 0.0), # 3 (4.94522276119403, 10.212100328282828, 8.813535829048842, 4.66030652173913, 2.6460749999999997, 0.0, 8.550020652173911, 10.584299999999999, 6.990459782608696, 5.875690552699228, 2.553025082070707, 0.0), # 4 (4.987719490781387, 10.313785116792928, 8.855542456619537, 4.6833491847826085, 2.663617788461538, 0.0, 8.546747622282608, 10.654471153846153, 7.025023777173913, 5.90369497107969, 2.578446279198232, 0.0), # 5 (5.029554784899035, 10.413392727272727, 8.896309125964011, 4.705747826086957, 2.680684615384615, 0.0, 8.54338695652174, 10.72273846153846, 7.058621739130436, 5.930872750642674, 2.603348181818182, 0.0), # 6 (5.0706910776997365, 10.510807458964646, 8.935802578727506, 4.72748125, 2.697258173076923, 0.0, 8.5399390625, 10.789032692307693, 7.0912218750000005, 5.95720171915167, 2.6277018647411614, 0.0), # 7 (5.1110908033362605, 10.60591361111111, 8.97398955655527, 4.7485282608695645, 2.7133211538461537, 0.0, 8.536404347826087, 10.853284615384615, 7.122792391304347, 5.982659704370181, 2.6514784027777774, 0.0), # 8 (5.1507163959613695, 10.698595482954543, 9.010836801092546, 4.768867663043478, 2.7288562499999993, 0.0, 8.532783220108696, 10.915424999999997, 7.153301494565217, 6.007224534061697, 2.6746488707386358, 0.0), # 9 (5.1895302897278315, 10.788737373737373, 9.046311053984574, 4.7884782608695655, 2.743846153846154, 0.0, 8.529076086956522, 10.975384615384616, 7.182717391304348, 6.030874035989716, 2.697184343434343, 0.0), # 10 (5.227494918788412, 10.87622358270202, 9.080379056876605, 4.807338858695652, 2.7582735576923074, 0.0, 8.525283355978262, 11.03309423076923, 7.2110082880434785, 6.053586037917737, 2.719055895675505, 0.0), # 11 (5.2645727172958745, 10.960938409090907, 9.113007551413881, 4.825428260869565, 2.7721211538461534, 0.0, 8.521405434782608, 11.088484615384614, 7.238142391304347, 6.0753383676092545, 2.740234602272727, 0.0), # 12 (5.3007261194029835, 11.042766152146465, 9.144163279241644, 4.8427252717391305, 2.7853716346153847, 0.0, 8.51744273097826, 11.141486538461539, 7.264087907608696, 6.096108852827762, 2.760691538036616, 0.0), # 13 (5.335917559262511, 11.121591111111112, 9.173812982005138, 4.859208695652173, 2.7980076923076918, 0.0, 8.513395652173912, 11.192030769230767, 7.288813043478259, 6.115875321336759, 2.780397777777778, 0.0), # 14 (5.370109471027217, 11.19729758522727, 9.201923401349612, 4.874857336956521, 2.810012019230769, 0.0, 8.509264605978261, 11.240048076923076, 7.312286005434782, 6.134615600899742, 2.7993243963068175, 0.0), # 15 (5.403264288849868, 11.269769873737372, 9.228461278920308, 4.88965, 2.8213673076923076, 0.0, 8.50505, 11.28546923076923, 7.334474999999999, 6.152307519280206, 2.817442468434343, 0.0), # 16 (5.4353444468832315, 11.338892275883836, 9.253393356362468, 4.903565489130434, 2.83205625, 0.0, 8.500752241847827, 11.328225, 7.3553482336956515, 6.168928904241644, 2.834723068970959, 0.0), # 17 (5.46631237928007, 11.40454909090909, 9.276686375321336, 4.916582608695652, 2.842061538461539, 0.0, 8.496371739130435, 11.368246153846156, 7.374873913043479, 6.184457583547558, 2.8511372727272724, 0.0), # 18 (5.496130520193152, 11.466624618055553, 9.298307077442159, 4.928680163043477, 2.8513658653846155, 0.0, 8.491908899456522, 11.405463461538462, 7.393020244565217, 6.198871384961439, 2.866656154513888, 0.0), # 19 (5.524761303775241, 11.525003156565655, 9.318222204370178, 4.939836956521739, 2.859951923076923, 0.0, 8.487364130434782, 11.439807692307692, 7.409755434782609, 6.212148136246785, 2.8812507891414136, 0.0), # 20 (5.552167164179106, 11.579569005681815, 9.336398497750643, 4.95003179347826, 2.8678024038461536, 0.0, 8.482737839673913, 11.471209615384614, 7.425047690217391, 6.224265665167096, 2.894892251420454, 0.0), # 21 (5.578310535557506, 11.630206464646465, 9.352802699228791, 4.95924347826087, 2.8748999999999993, 0.0, 8.47803043478261, 11.499599999999997, 7.438865217391305, 6.235201799485861, 2.907551616161616, 0.0), # 22 (5.603153852063214, 11.67679983270202, 9.367401550449872, 4.967450815217391, 2.8812274038461534, 0.0, 8.473242323369567, 11.524909615384614, 7.451176222826087, 6.244934366966581, 2.919199958175505, 0.0), # 23 (5.62665954784899, 11.719233409090908, 9.380161793059125, 4.974632608695652, 2.8867673076923075, 0.0, 8.468373913043479, 11.54706923076923, 7.461948913043478, 6.25344119537275, 2.929808352272727, 0.0), # 24 (5.648790057067603, 11.757391493055556, 9.391050168701799, 4.980767663043478, 2.8915024038461534, 0.0, 8.463425611413044, 11.566009615384614, 7.471151494565217, 6.260700112467866, 2.939347873263889, 0.0), # 25 (5.669507813871817, 11.79115838383838, 9.400033419023135, 4.985834782608695, 2.8954153846153843, 0.0, 8.458397826086957, 11.581661538461537, 7.478752173913043, 6.266688946015424, 2.947789595959595, 0.0), # 26 (5.688775252414398, 11.820418380681815, 9.40707828566838, 4.989812771739131, 2.8984889423076923, 0.0, 8.453290964673915, 11.593955769230769, 7.484719157608696, 6.271385523778919, 2.9551045951704538, 0.0), # 27 (5.7065548068481124, 11.84505578282828, 9.412151510282778, 4.992680434782609, 2.9007057692307687, 0.0, 8.448105434782608, 11.602823076923075, 7.489020652173913, 6.274767673521851, 2.96126394570707, 0.0), # 28 (5.722808911325724, 11.864954889520202, 9.415219834511568, 4.994416576086956, 2.902048557692307, 0.0, 8.44284164402174, 11.608194230769229, 7.491624864130435, 6.276813223007712, 2.9662387223800506, 0.0), # 29 (5.7375, 11.879999999999999, 9.41625, 4.995, 2.9025, 0.0, 8.4375, 11.61, 7.4925, 6.277499999999999, 2.9699999999999998, 0.0), # 30 (5.751246651214834, 11.892497471590906, 9.415477744565216, 4.994894632352941, 2.9023357180851064, 0.0, 8.430077267616193, 11.609342872340426, 7.492341948529411, 6.276985163043476, 2.9731243678977264, 0.0), # 31 (5.7646965153452685, 11.904829772727274, 9.413182826086956, 4.994580588235293, 2.901846382978723, 0.0, 8.418644565217393, 11.607385531914892, 7.49187088235294, 6.275455217391303, 2.9762074431818184, 0.0), # 32 (5.777855634590792, 11.916995369318181, 9.40939801630435, 4.994060955882353, 2.9010372606382977, 0.0, 8.403313830584706, 11.60414904255319, 7.491091433823529, 6.272932010869566, 2.9792488423295453, 0.0), # 33 (5.790730051150895, 11.928992727272727, 9.40415608695652, 4.993338823529412, 2.899913617021276, 0.0, 8.38419700149925, 11.599654468085104, 7.490008235294118, 6.269437391304347, 2.9822481818181816, 0.0), # 34 (5.803325807225064, 11.940820312499996, 9.39748980978261, 4.9924172794117645, 2.898480718085106, 0.0, 8.361406015742128, 11.593922872340425, 7.488625919117647, 6.264993206521739, 2.985205078124999, 0.0), # 35 (5.815648945012788, 11.952476590909091, 9.389431956521738, 4.9912994117647065, 2.896743829787234, 0.0, 8.335052811094453, 11.586975319148936, 7.486949117647059, 6.259621304347825, 2.988119147727273, 0.0), # 36 (5.8277055067135555, 11.96396002840909, 9.380015298913044, 4.989988308823529, 2.8947082180851056, 0.0, 8.305249325337332, 11.578832872340422, 7.484982463235293, 6.253343532608695, 2.9909900071022726, 0.0), # 37 (5.839501534526853, 11.97526909090909, 9.369272608695653, 4.988487058823529, 2.89237914893617, 0.0, 8.272107496251873, 11.56951659574468, 7.4827305882352935, 6.246181739130434, 2.9938172727272727, 0.0), # 38 (5.851043070652174, 11.986402244318182, 9.357236657608695, 4.98679875, 2.8897618882978717, 0.0, 8.23573926161919, 11.559047553191487, 7.480198125, 6.23815777173913, 2.9966005610795454, 0.0), # 39 (5.862336157289003, 11.997357954545455, 9.343940217391305, 4.984926470588235, 2.886861702127659, 0.0, 8.196256559220389, 11.547446808510635, 7.477389705882353, 6.22929347826087, 2.999339488636364, 0.0), # 40 (5.873386836636828, 12.008134687499997, 9.329416059782607, 4.982873308823529, 2.8836838563829783, 0.0, 8.153771326836583, 11.534735425531913, 7.474309963235294, 6.219610706521738, 3.002033671874999, 0.0), # 41 (5.88420115089514, 12.01873090909091, 9.31369695652174, 4.980642352941176, 2.880233617021277, 0.0, 8.108395502248875, 11.520934468085107, 7.4709635294117644, 6.209131304347826, 3.0046827272727277, 0.0), # 42 (5.894785142263428, 12.02914508522727, 9.296815679347825, 4.978236691176471, 2.8765162499999994, 0.0, 8.060241023238381, 11.506064999999998, 7.467355036764706, 6.1978771195652165, 3.0072862713068176, 0.0), # 43 (5.905144852941176, 12.03937568181818, 9.278805, 4.975659411764705, 2.8725370212765955, 0.0, 8.009419827586207, 11.490148085106382, 7.4634891176470575, 6.1858699999999995, 3.009843920454545, 0.0), # 44 (5.915286325127877, 12.049421164772726, 9.259697690217394, 4.972913602941176, 2.8683011968085106, 0.0, 7.956043853073464, 11.473204787234042, 7.459370404411764, 6.1731317934782615, 3.0123552911931815, 0.0), # 45 (5.925215601023019, 12.059280000000001, 9.239526521739132, 4.970002352941176, 2.8638140425531913, 0.0, 7.90022503748126, 11.455256170212765, 7.455003529411765, 6.159684347826087, 3.0148200000000003, 0.0), # 46 (5.934938722826087, 12.06895065340909, 9.218324266304347, 4.966928749999999, 2.859080824468085, 0.0, 7.842075318590705, 11.43632329787234, 7.450393124999999, 6.145549510869564, 3.0172376633522724, 0.0), # 47 (5.944461732736574, 12.07843159090909, 9.196123695652174, 4.9636958823529405, 2.854106808510638, 0.0, 7.7817066341829095, 11.416427234042551, 7.445543823529412, 6.130749130434782, 3.0196078977272727, 0.0), # 48 (5.953790672953963, 12.087721278409088, 9.17295758152174, 4.960306838235294, 2.8488972606382976, 0.0, 7.71923092203898, 11.39558904255319, 7.4404602573529415, 6.115305054347826, 3.021930319602272, 0.0), # 49 (5.96293158567775, 12.096818181818177, 9.148858695652175, 4.956764705882353, 2.8434574468085105, 0.0, 7.65476011994003, 11.373829787234042, 7.43514705882353, 6.099239130434783, 3.0242045454545443, 0.0), # 50 (5.971890513107417, 12.105720767045453, 9.123859809782608, 4.953072573529411, 2.837792632978723, 0.0, 7.588406165667167, 11.351170531914892, 7.429608860294118, 6.082573206521738, 3.026430191761363, 0.0), # 51 (5.980673497442456, 12.114427499999998, 9.097993695652173, 4.949233529411764, 2.8319080851063827, 0.0, 7.5202809970015, 11.32763234042553, 7.4238502941176465, 6.065329130434781, 3.0286068749999995, 0.0), # 52 (5.989286580882353, 12.122936846590909, 9.071293125, 4.945250661764706, 2.8258090691489364, 0.0, 7.450496551724138, 11.303236276595745, 7.417875992647058, 6.04752875, 3.030734211647727, 0.0), # 53 (5.9977358056266, 12.13124727272727, 9.043790869565216, 4.941127058823529, 2.8195008510638297, 0.0, 7.379164767616192, 11.278003404255319, 7.411690588235294, 6.0291939130434775, 3.0328118181818176, 0.0), # 54 (6.00602721387468, 12.139357244318182, 9.015519701086955, 4.93686580882353, 2.8129886968085103, 0.0, 7.306397582458771, 11.251954787234041, 7.405298713235295, 6.010346467391304, 3.0348393110795455, 0.0), # 55 (6.014166847826087, 12.147265227272724, 8.986512391304348, 4.9324699999999995, 2.8062778723404254, 0.0, 7.232306934032984, 11.225111489361701, 7.398705, 5.991008260869565, 3.036816306818181, 0.0), # 56 (6.022160749680308, 12.154969687500001, 8.95680171195652, 4.927942720588234, 2.7993736436170207, 0.0, 7.15700476011994, 11.197494574468083, 7.391914080882352, 5.9712011413043475, 3.0387424218750003, 0.0), # 57 (6.030014961636829, 12.16246909090909, 8.926420434782608, 4.923287058823529, 2.792281276595744, 0.0, 7.0806029985007495, 11.169125106382976, 7.384930588235295, 5.950946956521738, 3.0406172727272724, 0.0), # 58 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59 ) passenger_allighting_rate = ( (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 0 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 1 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 2 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 3 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 4 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 5 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 6 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 7 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 8 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 9 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 10 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 11 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 12 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 13 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 14 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 15 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 16 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 17 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 18 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 19 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 20 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 21 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 22 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 23 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 24 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 25 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 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56 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 57 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 58 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 59 ) """ parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html """ #initial entropy entropy = 258194110137029475889902652135037600173 #index for seed sequence child child_seed_index = ( 1, # 0 46, # 1 )
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4599568de9d33307f2941439c89fdd2b50cdda0f
4,416
py
Python
tests/test_objects_list.py
omaralvarez/trakt.py
93a6beb73cdd37ffb354d2e9c1892dc39d9c4baf
[ "MIT" ]
null
null
null
tests/test_objects_list.py
omaralvarez/trakt.py
93a6beb73cdd37ffb354d2e9c1892dc39d9c4baf
[ "MIT" ]
null
null
null
tests/test_objects_list.py
omaralvarez/trakt.py
93a6beb73cdd37ffb354d2e9c1892dc39d9c4baf
[ "MIT" ]
null
null
null
from tests.core.helpers import authenticated_response from trakt import Trakt import responses @responses.activate def test_list_add(): responses.add_callback( responses.GET, 'http://mock/users/me/lists/movies', callback=authenticated_response('fixtures/users/me/lists/movies.json'), content_type='application/json' ) responses.add_callback( responses.POST, 'http://mock/users/me/lists/123456/items', callback=authenticated_response(data='{"mock": "mock"}'), content_type='application/json' ) Trakt.base_url = 'http://mock' with Trakt.configuration.auth('mock', 'mock'): movies_list = Trakt['users/me/lists/movies'].get() result = movies_list.add({ 'shows': [ {'ids': {'tvdb': 121361}} ] }) assert result is not None @responses.activate def test_list_delete(): responses.add_callback( responses.GET, 'http://mock/users/me/lists/movies', callback=authenticated_response('fixtures/users/me/lists/movies.json'), content_type='application/json' ) responses.add_callback( responses.DELETE, 'http://mock/users/me/lists/123456', callback=authenticated_response(data='{"mock": "mock"}'), content_type='application/json' ) Trakt.base_url = 'http://mock' with Trakt.configuration.auth('mock', 'mock'): movies_list = Trakt['users/me/lists/movies'].get() success = movies_list.delete() assert success is True @responses.activate def test_list_update(): responses.add_callback( responses.GET, 'http://mock/users/me/lists/movies', callback=authenticated_response('fixtures/users/me/lists/movies.json'), content_type='application/json' ) responses.add_callback( responses.PUT, 'http://mock/users/me/lists/123456', callback=authenticated_response('fixtures/users/me/lists/shows.json'), content_type='application/json' ) Trakt.base_url = 'http://mock' with Trakt.configuration.auth('mock', 'mock'): movies_list = Trakt['users/me/lists/movies'].get() result = movies_list.update( name="Shows (2)" ) assert result is not None @responses.activate def test_list_remove(): responses.add_callback( responses.GET, 'http://mock/users/me/lists/movies', callback=authenticated_response('fixtures/users/me/lists/movies.json'), content_type='application/json' ) responses.add_callback( responses.POST, 'http://mock/users/me/lists/123456/items/remove', callback=authenticated_response(data='{"mock": "mock"}'), content_type='application/json' ) Trakt.base_url = 'http://mock' with Trakt.configuration.auth('mock', 'mock'): movies_list = Trakt['users/me/lists/movies'].get() result = movies_list.remove({ 'shows': [ {'ids': {'tvdb': 121361}} ] }) assert result is not None @responses.activate def test_list_like(): responses.add_callback( responses.GET, 'http://mock/users/me/lists/movies', callback=authenticated_response('fixtures/users/me/lists/movies.json'), content_type='application/json' ) responses.add_callback( responses.POST, 'http://mock/users/me/lists/123456/like', callback=authenticated_response(data='{"mock": "mock"}'), content_type='application/json' ) Trakt.base_url = 'http://mock' with Trakt.configuration.auth('mock', 'mock'): movies_list = Trakt['users/me/lists/movies'].get() success = movies_list.like() assert success is True @responses.activate def test_list_unlike(): responses.add_callback( responses.GET, 'http://mock/users/me/lists/movies', callback=authenticated_response('fixtures/users/me/lists/movies.json'), content_type='application/json' ) responses.add_callback( responses.DELETE, 'http://mock/users/me/lists/123456/like', callback=authenticated_response(data='{"mock": "mock"}'), content_type='application/json' ) Trakt.base_url = 'http://mock' with Trakt.configuration.auth('mock', 'mock'): movies_list = Trakt['users/me/lists/movies'].get() success = movies_list.unlike() assert success is True
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93
py
Python
probe_ably/core/tasks/utils/__init__.py
ai-systems/Probe-Ably
45b283ee5068289f9a1844cae9f109c000507723
[ "MIT" ]
12
2021-03-26T14:56:42.000Z
2022-02-11T15:37:58.000Z
probe_ably/core/tasks/utils/__init__.py
ai-systems/Probe-Ably
45b283ee5068289f9a1844cae9f109c000507723
[ "MIT" ]
1
2021-11-28T13:45:22.000Z
2021-11-28T13:45:22.000Z
probe_ably/core/tasks/utils/__init__.py
ai-systems/Probe-Ably
45b283ee5068289f9a1844cae9f109c000507723
[ "MIT" ]
null
null
null
from .read_input_task import ReadInputTask from .visualization_task import VisualiaztionTask
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45d108d58b5811673fd7982ea764cff0e29030a6
2,983
py
Python
plugins/diffusion/tests/test_io.py
bsavelev/medipy
f0da3750a6979750d5f4c96aedc89ad5ae74545f
[ "CECILL-B" ]
null
null
null
plugins/diffusion/tests/test_io.py
bsavelev/medipy
f0da3750a6979750d5f4c96aedc89ad5ae74545f
[ "CECILL-B" ]
null
null
null
plugins/diffusion/tests/test_io.py
bsavelev/medipy
f0da3750a6979750d5f4c96aedc89ad5ae74545f
[ "CECILL-B" ]
1
2022-03-04T05:47:08.000Z
2022-03-04T05:47:08.000Z
import os import shutil import tempfile import unittest import numpy import medipy.base import medipy.io import medipy.diffusion class TestIO(unittest.TestCase): def test_itk_io(self): tensors = medipy.base.Image( data=numpy.arange(10*20*30*6, dtype=numpy.single).reshape((10,20,30,6)), dti="tensor_2", origin=(1,2,3), spacing=(4,5,6), direction=medipy.base.coordinate_system.RAS) directory = tempfile.mkdtemp() medipy.io.save(tensors, os.path.join(directory, "tensors.nii")) other_tensors = medipy.io.load( os.path.join(directory, "tensors.nii"), None) self.assertTrue(isinstance( other_tensors.metadata["loader"]["loader"], medipy.diffusion.itk_io.ITK)) self.assertEqual(other_tensors.shape, (10,20,30)) self.assertEqual(other_tensors.dtype, numpy.single) self.assertEqual(other_tensors.data_type, "vector") self.assertEqual(other_tensors.image_type, "tensor_2") numpy.testing.assert_array_almost_equal(other_tensors.origin, (1,2,3)) numpy.testing.assert_array_almost_equal(other_tensors.spacing, (4,5,6)) numpy.testing.assert_array_almost_equal( other_tensors.direction, medipy.base.coordinate_system.RAS) numpy.testing.assert_array_almost_equal( other_tensors.data, numpy.arange(10*20*30*6, dtype=numpy.single).reshape((10,20,30,6))) shutil.rmtree(directory) def test_vtk_io(self): tensors = medipy.base.Image( data=numpy.arange(10*20*30*6, dtype=numpy.single).reshape((10,20,30,6)), dti="tensor_2", origin=(1,2,3), spacing=(4,5,6), direction=medipy.base.coordinate_system.LPS) directory = tempfile.mkdtemp() medipy.io.save(tensors, os.path.join(directory, "tensors.vtk")) other_tensors = medipy.io.load( os.path.join(directory, "tensors.vtk"), None) self.assertTrue(isinstance( other_tensors.metadata["loader"]["loader"], medipy.diffusion.vtk_io.Vtk)) self.assertEqual(other_tensors.shape, (10,20,30)) self.assertEqual(other_tensors.dtype, numpy.single) self.assertEqual(other_tensors.data_type, "vector") self.assertEqual(other_tensors.image_type, "tensor_2") numpy.testing.assert_array_almost_equal(other_tensors.origin, (1,2,3)) numpy.testing.assert_array_almost_equal(other_tensors.spacing, (4,5,6)) numpy.testing.assert_array_almost_equal( other_tensors.direction, medipy.base.coordinate_system.LPS) numpy.testing.assert_array_almost_equal( other_tensors.data, numpy.arange(10*20*30*6, dtype=numpy.single).reshape((10,20,30,6))) shutil.rmtree(directory) if __name__ == "__main__" : unittest.main()
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6
2fb0d19430a1dfba3007eefc0c0eb056cf430ea1
6,522
py
Python
tests/scaffold/test_validation.py
haowen-xu/tfsnippet-pre-alpha
31eb2cf692ac25b95cc815aaca53754d6db42d9f
[ "MIT" ]
null
null
null
tests/scaffold/test_validation.py
haowen-xu/tfsnippet-pre-alpha
31eb2cf692ac25b95cc815aaca53754d6db42d9f
[ "MIT" ]
null
null
null
tests/scaffold/test_validation.py
haowen-xu/tfsnippet-pre-alpha
31eb2cf692ac25b95cc815aaca53754d6db42d9f
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import os import unittest import tensorflow as tf from tfsnippet.scaffold import early_stopping from tfsnippet.utils import (TemporaryDirectory, set_variable_values, get_variable_values) from tests.helper import TestCase def _populate_variables(): a = tf.get_variable('a', shape=(), dtype=tf.int32) b = tf.get_variable('b', shape=(), dtype=tf.int32) c = tf.get_variable('c', shape=(), dtype=tf.int32) set_variable_values([a, b, c], [1, 2, 3]) return [a, b, c] class EarlyStoppingTestCase(TestCase): def test_basic(self): with self.get_session(): a, b, c = _populate_variables() self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) # test: param-vars must not be empty with self.assertRaisesRegex( ValueError, '`param_vars` must not be empty.'): with early_stopping([]): pass # test: early-stopping context without updating loss with early_stopping([a, b]): set_variable_values([a], [10]) self.assertEqual(get_variable_values([a, b, c]), [10, 2, 3]) # test: the first loss will always cause saving with early_stopping([a, b]) as es: set_variable_values([a], [10]) self.assertTrue(es.update(1.)) set_variable_values([a, b], [100, 20]) self.assertAlmostEqual(es.best_metric, 1.) self.assertEqual(get_variable_values([a, b, c]), [10, 2, 3]) # test: memorize the best loss set_variable_values([a, b, c], [1, 2, 3]) self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) with early_stopping([a, b]) as es: set_variable_values([a], [10]) self.assertTrue(es.update(1.)) self.assertAlmostEqual(es.best_metric, 1.) set_variable_values([a, b], [100, 20]) self.assertTrue(es.update(.5)) self.assertAlmostEqual(es.best_metric, .5) set_variable_values([a, b, c], [1000, 200, 30]) self.assertFalse(es.update(.8)) self.assertAlmostEqual(es.best_metric, .5) self.assertAlmostEqual(es.best_metric, .5) self.assertEqual(get_variable_values([a, b, c]), [100, 20, 30]) # test: initial_loss set_variable_values([a, b, c], [1, 2, 3]) self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) with early_stopping([a, b], initial_metric=.6) as es: set_variable_values([a], [10]) self.assertFalse(es.update(1.)) self.assertAlmostEqual(es.best_metric, .6) set_variable_values([a, b], [100, 20]) self.assertTrue(es.update(.5)) self.assertAlmostEqual(es.best_metric, .5) self.assertEqual(get_variable_values([a, b, c]), [100, 20, 3]) def test_restore_on_error(self): with self.get_session(): a, b, c = _populate_variables() self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) # test: do not restore on error with self.assertRaisesRegex(ValueError, 'value error'): with early_stopping([a, b], restore_on_error=False) as es: self.assertTrue(es.update(1.)) set_variable_values([a, b], [10, 20]) raise ValueError('value error') self.assertAlmostEqual(es.best_metric, 1.) self.assertEqual(get_variable_values([a, b, c]), [10, 20, 3]) # test: restore on error set_variable_values([a, b, c], [1, 2, 3]) self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) with self.assertRaisesRegex(ValueError, 'value error'): with early_stopping([a, b], restore_on_error=True) as es: self.assertTrue(es.update(1.)) set_variable_values([a, b], [10, 20]) raise ValueError('value error') self.assertAlmostEqual(es.best_metric, 1.) self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) def test_bigger_is_better(self): with self.get_session(): a, b, c = _populate_variables() self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) # test: memorize the best loss set_variable_values([a, b, c], [1, 2, 3]) self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) with early_stopping([a, b], smaller_is_better=False) as es: set_variable_values([a], [10]) self.assertTrue(es.update(.5)) self.assertAlmostEqual(es.best_metric, .5) set_variable_values([a, b], [100, 20]) self.assertTrue(es.update(1.)) self.assertAlmostEqual(es.best_metric, 1.) set_variable_values([a, b, c], [1000, 200, 30]) self.assertFalse(es.update(.8)) self.assertAlmostEqual(es.best_metric, 1.) self.assertAlmostEqual(es.best_metric, 1.) self.assertEqual(get_variable_values([a, b, c]), [100, 20, 30]) def test_save_dir(self): with self.get_session(): a, b, c = _populate_variables() self.assertEqual(get_variable_values([a, b, c]), [1, 2, 3]) with TemporaryDirectory() as tempdir: # test cleanup save_dir save_dir = os.path.join(tempdir, '1') with early_stopping([a, b], save_dir=save_dir) as es: self.assertTrue(es.update(1.)) self.assertTrue( os.path.exists(os.path.join(save_dir, 'latest'))) self.assertFalse(os.path.exists(save_dir)) # test not cleanup save_dir save_dir = os.path.join(tempdir, '2') with early_stopping([a, b], save_dir=save_dir, cleanup=False) as es: self.assertTrue(es.update(1.)) self.assertTrue( os.path.exists(os.path.join(save_dir, 'latest'))) self.assertTrue( os.path.exists(os.path.join(save_dir, 'latest'))) if __name__ == '__main__': unittest.main()
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2fc73255fc7175f53a2c57f4e7942a5944ee76dd
5,754
py
Python
TAE.py
behnamh217rn21/DTC
4f70d6b24722bd9f8331502d9cae00d35686a4d2
[ "MIT" ]
153
2019-06-13T12:38:22.000Z
2022-03-23T02:35:11.000Z
TAE.py
behnamh217rn21/DTC
4f70d6b24722bd9f8331502d9cae00d35686a4d2
[ "MIT" ]
21
2019-11-19T11:38:26.000Z
2022-02-13T21:07:11.000Z
TAE.py
behnamh217rn21/DTC
4f70d6b24722bd9f8331502d9cae00d35686a4d2
[ "MIT" ]
48
2019-07-01T07:55:29.000Z
2022-03-02T21:45:20.000Z
""" Implementation of the Deep Temporal Clustering model Temporal Autoencoder (TAE) @author Florent Forest (FlorentF9) """ from keras.models import Model from keras.layers import Input, Conv1D, LeakyReLU, MaxPool1D, CuDNNLSTM, Bidirectional, TimeDistributed, Dense, Reshape from keras.layers import UpSampling2D, Conv2DTranspose def temporal_autoencoder(input_dim, timesteps, n_filters=50, kernel_size=10, strides=1, pool_size=10, n_units=[50, 1]): """ Temporal Autoencoder (TAE) model with Convolutional and BiLSTM layers. # Arguments input_dim: input dimension timesteps: number of timesteps (can be None for variable length sequences) n_filters: number of filters in convolutional layer kernel_size: size of kernel in convolutional layer strides: strides in convolutional layer pool_size: pooling size in max pooling layer, must divide time series length n_units: numbers of units in the two BiLSTM layers alpha: coefficient in Student's kernel dist_metric: distance metric between latent sequences # Return (ae_model, encoder_model, decoder_model): AE, encoder and decoder models """ assert(timesteps % pool_size == 0) # Input x = Input(shape=(timesteps, input_dim), name='input_seq') # Encoder encoded = Conv1D(n_filters, kernel_size, strides=strides, padding='same', activation='linear')(x) encoded = LeakyReLU()(encoded) encoded = MaxPool1D(pool_size)(encoded) encoded = Bidirectional(CuDNNLSTM(n_units[0], return_sequences=True), merge_mode='sum')(encoded) encoded = LeakyReLU()(encoded) encoded = Bidirectional(CuDNNLSTM(n_units[1], return_sequences=True), merge_mode='sum')(encoded) encoded = LeakyReLU(name='latent')(encoded) # Decoder decoded = Reshape((-1, 1, n_units[1]), name='reshape')(encoded) decoded = UpSampling2D((pool_size, 1), name='upsampling')(decoded) #decoded = UpSampling1D(pool_size, name='upsampling')(decoded) decoded = Conv2DTranspose(input_dim, (kernel_size, 1), padding='same', name='conv2dtranspose')(decoded) output = Reshape((-1, input_dim), name='output_seq')(decoded) #output = Conv1D(1, kernel_size, strides=strides, padding='same', activation='linear', name='output_seq')(decoded) # AE model autoencoder = Model(inputs=x, outputs=output, name='AE') # Encoder model encoder = Model(inputs=x, outputs=encoded, name='encoder') # Create input for decoder model encoded_input = Input(shape=(timesteps // pool_size, n_units[1]), name='decoder_input') # Internal layers in decoder decoded = autoencoder.get_layer('reshape')(encoded_input) decoded = autoencoder.get_layer('upsampling')(decoded) decoded = autoencoder.get_layer('conv2dtranspose')(decoded) decoder_output = autoencoder.get_layer('output_seq')(decoded) # Decoder model decoder = Model(inputs=encoded_input, outputs=decoder_output, name='decoder') return autoencoder, encoder, decoder def temporal_autoencoder_v2(input_dim, timesteps, n_filters=50, kernel_size=10, strides=1, pool_size=10, n_units=[50, 1]): """ Temporal Autoencoder (TAE) model with Convolutional and BiLSTM layers. # Arguments input_dim: input dimension timesteps: number of timesteps (can be None for variable length sequences) n_filters: number of filters in convolutional layer kernel_size: size of kernel in convolutional layer strides: strides in convolutional layer pool_size: pooling size in max pooling layer n_units: numbers of units in the two BiLSTM layers alpha: coefficient in Student's kernel dist_metric: distance metric between latent sequences # Return (ae_model, encoder_model, decoder_model): AE, encoder and decoder models """ assert (timesteps % pool_size == 0) # Input x = Input(shape=(timesteps, input_dim), name='input_seq') # Encoder encoded = Conv1D(n_filters, kernel_size, strides=strides, padding='same', activation='linear')(x) encoded = LeakyReLU()(encoded) encoded = MaxPool1D(pool_size)(encoded) encoded = Bidirectional(CuDNNLSTM(n_units[0], return_sequences=True), merge_mode='concat')(encoded) encoded = LeakyReLU()(encoded) encoded = Bidirectional(CuDNNLSTM(n_units[1], return_sequences=True), merge_mode='concat')(encoded) encoded = LeakyReLU(name='latent')(encoded) # Decoder decoded = TimeDistributed(Dense(units=n_filters), name='dense')(encoded) # sequence labeling decoded = LeakyReLU(name='act')(decoded) decoded = Reshape((-1, 1, n_filters), name='reshape')(decoded) decoded = UpSampling2D((pool_size, 1), name='upsampling')(decoded) decoded = Conv2DTranspose(input_dim, (kernel_size, 1), padding='same', name='conv2dtranspose')(decoded) output = Reshape((-1, input_dim), name='output_seq')(decoded) # AE model autoencoder = Model(inputs=x, outputs=output, name='AE') # Encoder model encoder = Model(inputs=x, outputs=encoded, name='encoder') # Create input for decoder model encoded_input = Input(shape=(timesteps // pool_size, 2 * n_units[1]), name='decoder_input') # Internal layers in decoder decoded = autoencoder.get_layer('dense')(encoded_input) decoded = autoencoder.get_layer('act')(decoded) decoded = autoencoder.get_layer('reshape')(decoded) decoded = autoencoder.get_layer('upsampling')(decoded) decoded = autoencoder.get_layer('conv2dtranspose')(decoded) decoder_output = autoencoder.get_layer('output_seq')(decoded) # Decoder model decoder = Model(inputs=encoded_input, outputs=decoder_output, name='decoder') return autoencoder, encoder, decoder
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2fcde4aa9f5097aba12efe70f82fa5e688a50a08
16,582
py
Python
apl104lib.py
maikeriva/APL104
fe29a89e8965811313df6d06de8f878b10e7987e
[ "MIT" ]
2
2020-01-10T06:52:02.000Z
2020-01-14T19:44:47.000Z
apl104lib.py
maikeriva/APL104
fe29a89e8965811313df6d06de8f878b10e7987e
[ "MIT" ]
null
null
null
apl104lib.py
maikeriva/APL104
fe29a89e8965811313df6d06de8f878b10e7987e
[ "MIT" ]
null
null
null
""" apl104lib.py Python library implementation of: Interdiffusion across solid electrolyte-electrode interface Applied Physics Letters 104 (2014) Tested on: - python 3.6.5 - numpy 1.14.2 - matplotlib 2.2.2 """ import numpy as np import matplotlib.pyplot as plt import time """ 1D model """ class Sample1D: def __init__(sample,species=1,dim=200,res=64): sample.species=species # Number of chemical species sample.dim=dim # Sample dimension (nm) sample.res=res # Harmonic resolution of the domain sample.z=np.zeros(species) # Ionic valence vector sample.c1_bulk=np.zeros(species) # Bulk concentrations vector (material 1) sample.c2_bulk=np.zeros(species) # Bulk concentrations vector (material 2) sample.D1=np.zeros(species) # Diffusion coefficients vector (material 1, nm²/s) sample.D2=np.zeros(species) # Diffusion coefficients vector (material 2, nm²/s) sample.L=0 # Phase evolution coefficient (nm³/(J*s)) sample.W0=0 # Phase gradient coefficient (J/nm) sample.fc=0 # Free energy coefficient (J/(nm^3)) sample.c=np.zeros((res,species)) # Concentrations domain sample.p=np.zeros(res) # Phase domain # Plotting parameters sample.name=' ' sample.specienames=[' ' for specie in range(sample.species)] def h(sample): return sample.p**3*(6*sample.p**2-15*sample.p+10) def D(sample): return sample.h()[...,np.newaxis,np.newaxis]*sample.D1mat+(1-sample.h())[...,np.newaxis,np.newaxis]*sample.D2mat def f(sample): return np.sum((sample.c[...,0:-1]-sample.c1_bulk[0:-1])**2,axis=-1)*sample.h()+\ np.sum((sample.c[...,0:-1]-sample.c2_bulk[0:-1])**2,axis=-1)*(1-sample.h())+\ 2*(sample.p**4-2*sample.p**3+sample.p**2) def dfdp(sample): return (30*sample.p**4-60*sample.p**3+30*sample.p**2)*\ (np.sum((sample.c[...,0:-1]-sample.c1_bulk[0:-1])**2,axis=-1)-\ np.sum((sample.c[...,0:-1]-sample.c2_bulk[0:-1])**2,axis=-1))+\ (8*sample.p**3-12*sample.p**2+4*sample.p) def update(sample): # Update diffusion matrices. Call after editing the sample. sample.D1mat=(sample.res/sample.dim)**2*(np.diag(sample.D1[0:-1])-(sample.z[0:-1]*sample.c1_bulk[0:-1]*sample.D1[0:-1])[:,np.newaxis]*\ (sample.z[0:-1]*(sample.D1[0:-1]-sample.D1[-1]))[np.newaxis,:]/np.sum(sample.z**2*sample.c1_bulk*sample.D1)) sample.D2mat=(sample.res/sample.dim)**2*(np.diag(sample.D2[0:-1])-(sample.z[0:-1]*sample.c2_bulk[0:-1]*sample.D2[0:-1])[:,np.newaxis]*\ (sample.z[0:-1]*(sample.D2[0:-1]-sample.D2[-1]))[np.newaxis,:]/np.sum(sample.z**2*sample.c2_bulk*sample.D2)) ### # Finite-difference explicit Euler FW solver ### def efwsolve(sample,dt,steps): # Prepare scaled coefficients sample.L_s=sample.L*(sample.res/sample.dim)**3 # nm³/(J*s) sample.W0_s=sample.W0*(sample.dim/sample.res) # J/(nm) sample.fc_s=sample.fc*(sample.dim/sample.res)**3 # J/(nm³) # Update sample internal data sample.update() # Performance improvement matmuldest=np.ndarray((sample.res,sample.species-1,1)) # Euler forward explicit algorithm for step in range(steps): sample.c[...,0:-1]=sample.c[...,0:-1]+dt*np.gradient(np.matmul(sample.D(),np.gradient(sample.c[...,0:-1],axis=0)[...,np.newaxis],matmuldest)[...,0],axis=0) sample.p=sample.p+dt*sample.L_s*(sample.W0_s*np.gradient(np.gradient(sample.p))-sample.fc_s*sample.dfdp()) # Compute last species once cycle has finished sample.c[...,-1]=1-np.sum(sample.c[...,0:-1],axis=-1) ### # Spectral semi-implicit Fourier solver with real numbers optimization ### def rfftsolve(sample,dt,steps,log=False): # Prepare scaled coefficients sample.L_s=sample.L*(sample.res/sample.dim)**3 # nm³/(J*s) sample.W0_s=sample.W0*(sample.dim/sample.res) # J/(nm) sample.fc_s=sample.fc*(sample.dim/sample.res)**3 # J/(nm³) # Update sample internal data sample.update() # Performance improvement matmuldest=np.ndarray((sample.res,sample.species-1,1)) # Prepare fourier coefficients for real FFT kx=np.linspace(0,sample.res/2,sample.res/2+1)*2*np.pi/sample.res k=np.sqrt(kx**2) if log: # Prepare arrays for storage clog=np.zeros((steps,sample.res,sample.species)) plog=np.zeros((steps,sample.res)) # Prepare first FFT c_fft=np.fft.rfft(sample.c[...,0:-1],axis=0) p_fft=np.fft.rfft(sample.p) # Solving cycle for step in range(steps): # Phase evolution equation in fourier space p_fft=(p_fft-dt*sample.L_s*sample.fc_s*np.fft.rfft(sample.dfdp()))/(1+dt*sample.L_s*sample.W0_s*k**2) sample.p=np.fft.irfft(p_fft) # Concentration evolution equation in fourier space c_fft=c_fft+dt*1j*k[...,np.newaxis]*np.fft.rfft(np.matmul(sample.D(),np.fft.irfft(1j*k[...,np.newaxis]*c_fft,axis=0)[...,np.newaxis],matmuldest)[...,0],axis=0) sample.c[...,0:-1]=np.fft.irfft(c_fft,axis=0) # Compute last specie sample.c[...,-1]=1-np.sum(sample.c[...,0:-1],axis=-1) # Store logs clog[step]=sample.c plog[step]=sample.p # Return logs return clog,plog else: # Prepare first FFT c_fft=np.fft.rfft(sample.c[...,0:-1],axis=0) p_fft=np.fft.rfft(sample.p) # Solving cycle for step in range(steps): # Phase evolution equation in fourier space p_fft=(p_fft-dt*sample.L_s*sample.fc_s*np.fft.rfft(sample.dfdp()))/(1+dt*sample.L_s*sample.W0_s*k**2) sample.p=np.fft.irfft(p_fft) # Concentration evolution equation in fourier space c_fft=c_fft+dt*1j*k[...,np.newaxis]*np.fft.rfft(np.matmul(sample.D(),np.fft.irfft(1j*k[...,np.newaxis]*c_fft,axis=0)[...,np.newaxis],matmuldest)[...,0],axis=0) sample.c[...,0:-1]=np.fft.irfft(c_fft,axis=0) # Compute last species once cycle has finished sample.c[...,-1]=1-np.sum(sample.c[...,0:-1],axis=-1) """ Interface evaluation """ def cifeval(sample,tol=1e-3): ifstart=np.argmin(np.abs(sample.c[0:int(sample.res/2)]-sample.c1_bulk)<tol,axis=0)*sample.dim/sample.res ifend=(sample.res/2-np.argmin(np.abs(np.flip(sample.c[0:int(sample.res/2)],axis=0)-sample.c2_bulk)<tol,axis=0))*sample.dim/sample.res return ifend-ifstart,ifstart,ifend def pifeval(sample,tol=1e-3): ifstart=np.argmin(np.abs(sample.p[0:int(sample.res/2)]-1)<tol,axis=0)*sample.dim/sample.res ifend=(sample.res/2-np.argmin(np.abs(np.flip(sample.p[0:int(sample.res/2)],axis=0)-0)<tol,axis=0))*sample.dim/sample.res return ifend-ifstart,ifstart,ifend def cifevallog(log,sample,tol=1e-3): ifstart=np.argmin(np.abs(log[:,0:int(sample.res/2),:]-sample.c1_bulk)<tol,axis=1)*sample.dim/sample.res ifend=(sample.res/2-np.argmin(np.abs(np.flip(log[:,0:int(sample.res/2),:],axis=1)-sample.c2_bulk)<tol,axis=1))*sample.dim/sample.res return ifend-ifstart,ifstart,ifend def pifevallog(log,sample,tol=1e-3): ifstart=np.argmin(np.abs(log[:,0:int(sample.res/2)]-1)<tol,axis=1)*sample.dim/sample.res ifend=(sample.res/2-np.argmin(np.abs(np.flip(log[:,0:int(sample.res/2)],axis=1)-0)<tol,axis=1))*sample.dim/sample.res return ifend-ifstart,ifstart,ifend ### # Plotting functions ### def summaryplot(sample,interface=True,ifspecie=0,iftol=1e-3,save=False,filename="summaryplot.pdf"): fig,ax1=plt.subplots() ax1.plot(np.linspace(0,sample.dim,sample.res),sample.p,linestyle='dashed') ax1.set_ylim([-0.1,1.1]) ax1.set_title("Results overview") ax1.set_xlabel("Coordinate (nm)") ax1.set_ylabel("Phase (dashed line)") ax1.grid() ax2=ax1.twinx() ax2.plot(np.linspace(0,sample.dim,sample.res),sample.c) ax2.set_ylim([-0.1,1.1]) ax2.set_ylabel("Molar concentration (solid line)") ax2.legend(sample.specienames) if interface: iflength,ifstart,ifend=cifeval(sample,iftol) ax2.vlines([ifstart[ifspecie],ifend[ifspecie],sample.dim-ifend[ifspecie],sample.dim-ifstart[ifspecie]],0,1,linestyle='dotted') if save: fig.savefig(filename) return fig def pplot(sample,interface=True,iftol=1e-3,save=False,filename="pplot.pdf"): fig=plt.figure() plt.plot(np.linspace(0,sample.dim,sample.res),sample.p) plt.ylim([-0.1,1.1]) plt.grid() plt.title("Phase profile") plt.xlabel("Coordinate (nm)") if interface: iflength,ifstart,ifend=pifeval(sample,iftol) plt.vlines([ifstart,ifend,ifstart+sample.dim/2,ifend+sample.dim/2],0,1,linestyle='dotted') if save: fig.savefig(filename) return fig def cplot(sample,interface=True,ifspecie=0,iftol=1e-3,save=False,filename="cplot.pdf"): fig=plt.figure() plt.plot(np.linspace(0,sample.dim,sample.res),sample.c) plt.ylim([-0.1,1.1]) plt.grid() plt.title("Concentration profiles") plt.xlabel("Coordinate (nm)") plt.ylabel("Molar concentration") plt.legend(sample.specienames) if interface: iflength,ifstart,ifend=cifeval(sample,ifspecie,iftol) plt.vlines([ifstart[...,ifspecie],ifend[...,ifspecie],ifstart[...,ifspecie]+sample.dim/2,ifend[...,ifspecie]+sample.dim/2],0,1,linestyle='dotted') if save: fig.savefig(filename) return fig def fplot(sample,interface=True,ifspecie=0,iftol=1e-3,save=False,filename="fplot.pdf"): fig=plt.figure() plt.plot(np.linspace(0,sample.dim,sample.res),sample.f()) plt.grid() plt.title("f plot") plt.xlabel("Coordinate (nm)") plt.ylabel("Energy (J/nm^3)") if interface: iflength,ifstart,ifend=cifeval(sample,ifspecie,iftol) plt.vlines([ifstart[...,ifspecie],ifend[...,ifspecie],ifstart[...,ifspecie]+sample.dim/2,ifend[...,ifspecie]+sample.dim/2],0,1,linestyle='dotted') if save: fig.savefig(filename) return fig def dfdpplot(sample,interface=True,ifspecie=0,iftol=1e-3,save=False,filename="dfdpplot.pdf"): fig=plt.figure() plt.plot(np.linspace(0,sample.dim,sample.res),sample.dfdp()) plt.grid() plt.title("dfdp plot") plt.xlabel("Coordinate (nm)") plt.ylabel("Energy variation (J/nm^3)") if interface: iflength,ifstart,ifend=cifeval(sample,ifspecie,iftol) plt.vlines([ifstart[...,ifspecie],ifend[...,ifspecie],ifstart[...,ifspecie]+sample.dim/2,ifend[...,ifspecie]+sample.dim/2],0,1,linestyle='dotted') if save: fig.savefig(filename) return fig def showplots(): plt.show() """ 2D model """ class Sample2D: def __init__(sample,species=1,dim=200,res=64): sample.species=species sample.dim=dim sample.res=res sample.z=np.zeros(species) sample.c1_bulk=np.zeros(species) sample.c2_bulk=np.zeros(species) sample.D1=np.zeros(species) # nm^2/s sample.D2=np.zeros(species) # nm^2/s sample.L=0 # nm^3/(J*s) sample.W0=0 # J/nm sample.fc=0 # J/(nm^3) sample.c=np.zeros([res,res,species]) sample.p=np.zeros([res,res]) # Plotting parameters sample.name=' ' sample.specienames=[' ' for specie in range(sample.species)] def h(sample): return sample.p**3*(6*sample.p**2-15*sample.p+10) def D(sample): return sample.h()[...,np.newaxis,np.newaxis]*sample.D1mat+(1-sample.h())[...,np.newaxis,np.newaxis]*sample.D2mat def f(sample): return np.sum((sample.c[...,0:-1]-sample.c1_bulk[0:-1])**2,axis=-1)*sample.h()+\ np.sum((sample.c[...,0:-1]-sample.c2_bulk[0:-1])**2,axis=-1)*(1-sample.h())+\ 2*(sample.p**4-2*sample.p**3+sample.p**2) def dfdp(sample): return (30*sample.p**4-60*sample.p**3+30*sample.p**2)*\ (np.sum((sample.c[...,0:-1]-sample.c1_bulk[0:-1])**2,axis=-1)-\ np.sum((sample.c[...,0:-1]-sample.c2_bulk[0:-1])**2,axis=-1))+\ (8*sample.p**3-12*sample.p**2+4*sample.p) def update(sample): sample.D1mat=(sample.res/sample.dim)**2*(np.diag(sample.D1[0:-1])-(sample.z[0:-1]*sample.c1_bulk[0:-1]*sample.D1[0:-1])[:,np.newaxis]*\ (sample.z[0:-1]*(sample.D1[0:-1]-sample.D1[-1]))[np.newaxis,:]/np.sum(sample.z**2*sample.c1_bulk*sample.D1)) sample.D2mat=(sample.res/sample.dim)**2*(np.diag(sample.D2[0:-1])-(sample.z[0:-1]*sample.c2_bulk[0:-1]*sample.D2[0:-1])[:,np.newaxis]*\ (sample.z[0:-1]*(sample.D2[0:-1]-sample.D2[-1]))[np.newaxis,:]/np.sum(sample.z**2*sample.c2_bulk*sample.D2)) ### # Spectral semi-implicit Fourier solver without real numbers optimization ### def fftsolve2D(sample,dt,steps,log=False): # Prepare scaled coefficients sample.L_s=sample.L*(sample.res/sample.dim)**3 # nm³/(J*s) sample.W0_s=sample.W0*(sample.dim/sample.res) # J/(nm) sample.fc_s=sample.fc*(sample.dim/sample.res)**3 # J/(nm³) # Update sample internal data sample.update() # Performance improvement matmuldest=np.ndarray((sample.res,sample.res,sample.species-1,1),dtype=complex) # Prepare fourier coefficients for real FFT kx=np.concatenate([np.linspace(0,sample.res/2,sample.res/2,False),np.linspace(-sample.res/2,0,sample.res/2,False)])*2*np.pi/sample.res ky=np.concatenate([np.linspace(0,sample.res/2,sample.res/2,False),np.linspace(-sample.res/2,0,sample.res/2,False)])*2*np.pi/sample.res k=np.sqrt(kx[np.newaxis,:]**2+ky[:,np.newaxis]**2) if log: # Prepare arrays for storage clog=np.zeros((steps,sample.res,sample.res,sample.species)) plog=np.zeros((steps,sample.res,sample.res)) # Prepare first FFT c_fft=np.fft.fftn(sample.c[...,0:-1],axes=(0,1)) p_fft=np.fft.fftn(sample.p) # Solving cycle for step in range(steps): # Phase evolution equation in fourier space p_fft=(p_fft-dt*sample.L_s*sample.fc_s*np.fft.fftn(sample.dfdp()))/(1+dt*sample.L_s*sample.W0_s*k**2) sample.p=np.real(np.fft.ifftn(p_fft)) # Concentration evolution equation in fourier space c_fft=c_fft+dt*1j*k[...,np.newaxis]*np.fft.fftn(np.matmul(sample.D(),np.fft.ifftn(1j*k[...,np.newaxis]*c_fft,axes=(0,1))[...,np.newaxis],matmuldest)[...,0],axes=(0,1)) sample.c[...,0:-1]=np.real(np.fft.ifftn(c_fft,axes=(0,-1))) # Compute last specie sample.c[...,-1]=1-np.sum(sample.c[...,0:-1],axis=-1) # Store logs clog[step]=sample.c plog[step]=sample.p # Return logs return clog,plog else: # Prepare first FFT c_fft=np.fft.fftn(sample.c[...,0:-1],axes=(0,1)) p_fft=np.fft.fftn(sample.p) # Solving cycle for step in range(steps): # Phase evolution equation in fourier space p_fft=(p_fft-dt*sample.L_s*sample.fc_s*np.fft.fftn(sample.dfdp()))/(1+dt*sample.L_s*sample.W0_s*k**2) sample.p=np.real(np.fft.ifftn(p_fft)) # Concentration evolution equation in fourier space c_fft=c_fft+dt*1j*k[...,np.newaxis]*np.fft.fftn(np.matmul(sample.D(),np.fft.ifftn(1j*k[...,np.newaxis]*c_fft,axes=(0,1))[...,np.newaxis],matmuldest)[...,0],axes=(0,1)) sample.c[...,0:-1]=np.real(np.fft.ifftn(c_fft,axes=(0,1))) # Compute last species once cycle has finished sample.c[...,-1]=1-np.sum(sample.c[...,0:-1],axis=-1) """ 2D contour plot functions """ def contourcplot2d(sample,specie=0,save=False,filename="contourcplot2d.pdf"): speciename=sample.specienames(specie) plt.figure() plt.contourf(np.linspace(0,sample.dim,sample.res),np.linspace(0,sample.dim,sample.res),sample.c[...,specie]) plt.colorbar() plt.title("Molar concentration of {}".format(speciename)) plt.xlabel("Coordinate (nm)") plt.ylabel("Coordinate (nm)") if save: fig.savefig(filename) def contourpplot2d(sample,save=False,filename="contourpplot.pdf"): pfig=plt.figure() pplot=plt.contourf(np.linspace(0,sample.dim,sample.res),np.linspace(0,sample.dim,sample.res),sample.p) plt.colorbar(pplot) plt.title("Phase") plt.xlabel("Coordinate (nm)") plt.ylabel("Coordinate (nm)") if save: fig.savefig(filename)
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6
64226494c732aeeceef7d12ba018e16839e8d97f
3,646
py
Python
old_code/street_cross_exp.py
pulkitag/egomotion
fad2ab94b0c2f5533c79a01d1b0546b8d0c64f19
[ "BSD-3-Clause" ]
9
2017-11-25T14:24:23.000Z
2022-03-25T07:08:28.000Z
old_code/street_cross_exp.py
pulkitag/egomotion
fad2ab94b0c2f5533c79a01d1b0546b8d0c64f19
[ "BSD-3-Clause" ]
null
null
null
old_code/street_cross_exp.py
pulkitag/egomotion
fad2ab94b0c2f5533c79a01d1b0546b8d0c64f19
[ "BSD-3-Clause" ]
3
2017-10-13T02:30:28.000Z
2021-06-30T05:55:42.000Z
##Records/Performs the experiment which evaluate the pose model on the patch task and ## vice-versa. import street_params as sp import street_exp as se import my_exp_ptch as mept import my_exp_pose as mepo import my_exp_v2 as mev2 def train_ptch_using_pose(isRun=False, deviceId=[0]): ptPrms, ptCPrms = mept.smallnetv2_pool4_ptch_crp192_rawImSz256(isPythonLayer=True, lrAbove='common_fc', deviceId=deviceId) poPrms, poCPrms = mepo.smallnetv2_pool4_pose_euler_mx90_crp192_rawImSz256(isPythonLayer=True, extraFc=512) exp, modelFile = se.setup_experiment_from_previous(poPrms, poCPrms, ptPrms, ptCPrms, srcModelIter=60000) #Rename common_fc so that it is initialized randomly exp.expFile_.netDef_.rename_layer('common_fc', 'common_fc_new') if isRun: exp.make(modelFile=modelFile) exp.run() return exp def train_pose_using_ptch(isRun=False, deviceId=[0]): poPrms, poCPrms = mepo.smallnetv5_fc5_pose_euler_mx90_crp192_rawImSz256(numFc5=512, lrAbove='common_fc', isPythonLayer=True, deviceId=deviceId) ptPrms, ptCPrms = mept.smallnetv5_fc5_ptch_crp192_rawImSz256(numFc5=512, isPythonLayer=True) exp, modelFile = se.setup_experiment_from_previous(ptPrms, ptCPrms, poPrms, poCPrms, srcModelIter=60000) #Rename common_fc so that it is initialized randomly exp.expFile_.netDef_.rename_layer('common_fc', 'common_fc_new') if isRun: exp.make(modelFile=modelFile) exp.run() return exp def train_ptch_using_pose_fc5(isRun=False, deviceId=[0]): poPrms, poCPrms = mepo.smallnetv5_fc5_pose_euler_crp192_rawImSz256(numFc5=512, isPythonLayer=True) ptPrms, ptCPrms = mept.smallnetv5_fc5_ptch_crp192_rawImSz256(numFc5=512, isPythonLayer=True, lrAbove='common_fc', deviceId=deviceId) exp, modelFile = se.setup_experiment_from_previous(poPrms, poCPrms, ptPrms, ptCPrms, srcModelIter=60000) #Rename common_fc so that it is initialized randomly exp.expFile_.netDef_.rename_layer('common_fc', 'common_fc_new') if isRun: exp.make(modelFile=modelFile) exp.run() return exp def train_ptch_using_ptch_lt5(isRun=False, deviceId=[0]): #The target experiment is to peform ptch matching on general angles tgtPrms, tgtCPrms = mept.smallnetv5_fc5_ptch_crp192_rawImSz256(isPythonLayer=True, lrAbove='common_fc', deviceId=deviceId) #The source experiment is ptch matching with positives only from euler angles lt 5 srcPrms, srcCPrms = mept.smallnetv5_fc5_ptch_euler_mx5_crp192_rawImSz256(numFc5=512) exp, modelFile = se.setup_experiment_from_previous(srcPrms, srcCPrms, tgtPrms, tgtCPrms, srcModelIter=36000) #Rename common_fc so that it is initialized randomly exp.expFile_.netDef_.rename_layer('common_fc', 'common_fc_new') if isRun: exp.make(modelFile=modelFile) exp.run() return exp def train_ptch_using_ptch_lt5_pose_all(isRun=False, deviceId=[0]): #The target experiment is to peform ptch matching on general angles tgtPrms, tgtCPrms = mept.smallnetv5_fc5_ptch_crp192_rawImSz256(isPythonLayer=True, lrAbove='common_fc', deviceId=deviceId) #The source experiment is ptch matching with positives only from euler angles lt 5 srcPrms, srcCPrms = mev2.ptch_euler_mx5_pose_euler_smallnet_v5_fc5_exp1(numFc5=512) exp, modelFile = se.setup_experiment_from_previous(srcPrms, srcCPrms, tgtPrms, tgtCPrms, srcModelIter=36000) #Rename common_fc so that it is initialized randomly exp.expFile_.netDef_.rename_layer('common_fc', 'common_fc_new') if isRun: exp.make(modelFile=modelFile) exp.run() return exp
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6
ff5b4e0eba6b9304a2a09908cb2a3999b01dd80a
14,470
py
Python
koku/reporting/migrations/0103_azurecomputesummary_azurecostsummary_azurecostsummarybyaccount_azurecostsummarybylocation_azurecosts.py
Vasyka/koku
b5aa9ec41c3b0821e74afe9ff3a5ffaedb910614
[ "Apache-2.0" ]
2
2022-01-12T03:42:39.000Z
2022-01-12T03:42:40.000Z
koku/reporting/migrations/0103_azurecomputesummary_azurecostsummary_azurecostsummarybyaccount_azurecostsummarybylocation_azurecosts.py
Vasyka/koku
b5aa9ec41c3b0821e74afe9ff3a5ffaedb910614
[ "Apache-2.0" ]
null
null
null
koku/reporting/migrations/0103_azurecomputesummary_azurecostsummary_azurecostsummarybyaccount_azurecostsummarybylocation_azurecosts.py
Vasyka/koku
b5aa9ec41c3b0821e74afe9ff3a5ffaedb910614
[ "Apache-2.0" ]
1
2021-07-21T09:33:59.000Z
2021-07-21T09:33:59.000Z
# Generated by Django 2.2.11 on 2020-03-25 18:52 import django.contrib.postgres.fields from django.db import migrations from django.db import models class Migration(migrations.Migration): dependencies = [("reporting", "0102_auto_20200228_1812")] operations = [ migrations.CreateModel( name="AzureComputeSummary", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("instance_type", models.CharField(max_length=50, null=True)), ( "instance_ids", django.contrib.postgres.fields.ArrayField( base_field=models.CharField(max_length=256), null=True, size=None ), ), ("instance_count", models.IntegerField(null=True)), ("usage_quantity", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("unit_of_measure", models.CharField(max_length=63, null=True)), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_compute_summary", "managed": False}, ), migrations.CreateModel( name="AzureCostSummary", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_cost_summary", "managed": False}, ), migrations.CreateModel( name="AzureCostSummaryByAccount", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("subscription_guid", models.CharField(max_length=50)), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_cost_summary_by_account", "managed": False}, ), migrations.CreateModel( name="AzureCostSummaryByLocation", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("resource_location", models.CharField(max_length=50)), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_cost_summary_by_location", "managed": False}, ), migrations.CreateModel( name="AzureCostSummaryByService", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("service_name", models.TextField()), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_cost_summary_by_service", "managed": False}, ), migrations.CreateModel( name="AzureDatabaseSummary", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("service_name", models.TextField()), ("usage_quantity", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("unit_of_measure", models.CharField(max_length=63, null=True)), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_database_summary", "managed": False}, ), migrations.CreateModel( name="AzureNetworkSummary", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("service_name", models.TextField()), ("usage_quantity", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("unit_of_measure", models.CharField(max_length=63, null=True)), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_network_summary", "managed": False}, ), migrations.CreateModel( name="AzureStorageSummary", fields=[ ("id", models.IntegerField(primary_key=True, serialize=False)), ("usage_start", models.DateField()), ("usage_end", models.DateField()), ("service_name", models.TextField()), ("usage_quantity", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("unit_of_measure", models.CharField(max_length=63, null=True)), ("pretax_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("markup_cost", models.DecimalField(decimal_places=9, max_digits=24, null=True)), ("currency", models.CharField(default="USD", max_length=10)), ], options={"db_table": "reporting_azure_storage_summary", "managed": False}, ), migrations.RunSQL( sql=""" CREATE MATERIALIZED VIEW reporting_azure_cost_summary AS( SELECT row_number() OVER(ORDER BY usage_start) as id, usage_start as usage_start, usage_start as usage_end, sum(pretax_cost) as pretax_cost, sum(markup_cost) as markup_cost, max(currency) as currency FROM reporting_azurecostentrylineitem_daily_summary -- Get data for this month or last month WHERE usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date GROUP BY usage_start ) ; CREATE UNIQUE INDEX azure_cost_summary ON reporting_azure_cost_summary (usage_start) ; CREATE MATERIALIZED VIEW reporting_azure_cost_summary_by_account AS( SELECT row_number() OVER(ORDER BY usage_start, subscription_guid) as id, usage_start as usage_start, usage_start as usage_end, subscription_guid, sum(pretax_cost) as pretax_cost, sum(markup_cost) as markup_cost, max(currency) as currency FROM reporting_azurecostentrylineitem_daily_summary -- Get data for this month or last month WHERE usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date GROUP BY usage_start, subscription_guid ) ; CREATE UNIQUE INDEX azure_cost_summary_account ON reporting_azure_cost_summary_by_account (usage_start, subscription_guid) ; CREATE MATERIALIZED VIEW reporting_azure_cost_summary_by_location AS( SELECT row_number() OVER(ORDER BY usage_start, resource_location) as id, usage_start as usage_start, usage_start as usage_end, resource_location, sum(pretax_cost) as pretax_cost, sum(markup_cost) as markup_cost, max(currency) as currency FROM reporting_azurecostentrylineitem_daily_summary -- Get data for this month or last month WHERE usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date GROUP BY usage_start, resource_location ) ; CREATE UNIQUE INDEX azure_cost_summary_location ON reporting_azure_cost_summary_by_location (usage_start, resource_location) ; CREATE MATERIALIZED VIEW reporting_azure_cost_summary_by_service AS( SELECT row_number() OVER(ORDER BY usage_start, service_name) as id, usage_start as usage_start, usage_start as usage_end, service_name, sum(pretax_cost) as pretax_cost, sum(markup_cost) as markup_cost, max(currency) as currency FROM reporting_azurecostentrylineitem_daily_summary -- Get data for this month or last month WHERE usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date GROUP BY usage_start, service_name ) ; CREATE UNIQUE INDEX azure_cost_summary_service ON reporting_azure_cost_summary_by_service (usage_start, service_name) ; CREATE MATERIALIZED VIEW reporting_azure_compute_summary AS( SELECT ROW_NUMBER() OVER(ORDER BY c.usage_start, c.instance_type) AS id, c.usage_start, c.usage_start as usage_end, c.instance_type, r.instance_ids, CARDINALITY(r.instance_ids) AS instance_count, c.usage_quantity, c.unit_of_measure, c.pretax_cost, c.markup_cost, c.currency FROM ( -- this group by gets the counts SELECT usage_start, instance_type, SUM(usage_quantity) AS usage_quantity, MAX(unit_of_measure) AS unit_of_measure, SUM(pretax_cost) AS pretax_cost, SUM(markup_cost) AS markup_cost, MAX(currency) AS currency FROM reporting_azurecostentrylineitem_daily_summary WHERE usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date AND instance_type IS NOT NULL GROUP BY usage_start, instance_type ) AS c JOIN ( -- this group by gets the distinct resources running by day SELECT usage_start, instance_type, ARRAY_AGG(DISTINCT instance_id ORDER BY instance_id) as instance_ids FROM ( SELECT usage_start, instance_type, UNNEST(instance_ids) AS instance_id FROM reporting_azurecostentrylineitem_daily_summary WHERE usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date AND instance_type IS NOT NULL ) AS x GROUP BY usage_start, instance_type ) AS r ON c.usage_start = r.usage_start AND c.instance_type = r.instance_type ) WITH DATA ; CREATE UNIQUE INDEX azure_compute_summary ON reporting_azure_compute_summary (usage_start, instance_type) ; CREATE MATERIALIZED VIEW reporting_azure_storage_summary AS( SELECT row_number() OVER(ORDER BY usage_start, service_name) as id, usage_start as usage_start, usage_start as usage_end, service_name, sum(usage_quantity) as usage_quantity, max(unit_of_measure) as unit_of_measure, sum(pretax_cost) as pretax_cost, sum(markup_cost) as markup_cost, max(currency) as currency FROM reporting_azurecostentrylineitem_daily_summary -- Get data for this month or last month WHERE service_name LIKE '%Storage%' AND usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date GROUP BY usage_start, service_name ) ; CREATE UNIQUE INDEX azure_storage_summary ON reporting_azure_storage_summary (usage_start, service_name) ; CREATE MATERIALIZED VIEW reporting_azure_network_summary AS( SELECT row_number() OVER(ORDER BY usage_start, service_name) as id, usage_start as usage_start, usage_start as usage_end, service_name, sum(usage_quantity) as usage_quantity, max(unit_of_measure) as unit_of_measure, sum(pretax_cost) as pretax_cost, sum(markup_cost) as markup_cost, max(currency) as currency FROM reporting_azurecostentrylineitem_daily_summary -- Get data for this month or last month WHERE service_name IN ('Virtual Network','VPN','DNS','Traffic Manager','ExpressRoute','Load Balancer','Application Gateway') AND usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date GROUP BY usage_start, service_name ) ; CREATE UNIQUE INDEX azure_network_summary ON reporting_azure_network_summary (usage_start, service_name) ; CREATE MATERIALIZED VIEW reporting_azure_database_summary AS( SELECT row_number() OVER(ORDER BY usage_start, service_name) as id, usage_start as usage_start, usage_start as usage_end, service_name, sum(usage_quantity) as usage_quantity, max(unit_of_measure) as unit_of_measure, sum(pretax_cost) as pretax_cost, sum(markup_cost) as markup_cost, max(currency) as currency FROM reporting_azurecostentrylineitem_daily_summary -- Get data for this month or last month WHERE service_name IN ('Cosmos DB','Cache for Redis') OR service_name ILIKE '%database%' AND usage_start >= DATE_TRUNC('month', NOW() - '1 month'::interval)::date GROUP BY usage_start, service_name ) ; CREATE UNIQUE INDEX azure_database_summary ON reporting_azure_database_summary (usage_start, service_name) ; """ ), ]
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6
ff767c05e0464633a3c3327ed0a5c1bfd230ded3
65
py
Python
graphpype/__init__.py
davidmeunier79/graphpype
800d1f8cbfdf3a18de77558c3b88eeb31735857e
[ "BSD-3-Clause" ]
17
2017-12-26T18:51:43.000Z
2022-02-25T19:42:09.000Z
graphpype/__init__.py
davidmeunier79/graphpype
800d1f8cbfdf3a18de77558c3b88eeb31735857e
[ "BSD-3-Clause" ]
44
2017-12-09T19:14:08.000Z
2021-08-17T14:42:48.000Z
graphpype/__init__.py
davidmeunier79/graphpype
800d1f8cbfdf3a18de77558c3b88eeb31735857e
[ "BSD-3-Clause" ]
12
2017-05-28T20:38:27.000Z
2022-03-16T20:57:47.000Z
from . import pipelines # noqa from . import interfaces # noqa
21.666667
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80ff3db18bef9a18287b2733b1c09bd2f373a218
13,287
py
Python
tests/containers/test_AudioContainer.py
gertdekkers/dcase_util
e5b80cc98b28facad2f3fff9acba126487b19879
[ "MIT" ]
null
null
null
tests/containers/test_AudioContainer.py
gertdekkers/dcase_util
e5b80cc98b28facad2f3fff9acba126487b19879
[ "MIT" ]
null
null
null
tests/containers/test_AudioContainer.py
gertdekkers/dcase_util
e5b80cc98b28facad2f3fff9acba126487b19879
[ "MIT" ]
null
null
null
""" Unit tests for AudioContainer """ import nose.tools import dcase_util import os import numpy import tempfile def test_load(): # Mono audio = dcase_util.containers.AudioContainer( filename=dcase_util.utils.Example.audio_filename() ).load( mono=True ) nose.tools.eq_(audio.fs, 44100) nose.tools.eq_(len(audio.data.shape), 1) nose.tools.eq_(audio.data.shape[0], 441001) # Stereo audio = dcase_util.containers.AudioContainer( filename=dcase_util.utils.Example.audio_filename() ).load( mono=False ) nose.tools.eq_(audio.fs, 44100) nose.tools.eq_(audio.data.shape[0], 2) nose.tools.eq_(audio.data.shape[1], 441001) # Re-sampling audio = dcase_util.containers.AudioContainer( filename=dcase_util.utils.Example.audio_filename() ).load( fs=16000, mono=True ) nose.tools.eq_(audio.fs, 16000) nose.tools.eq_(len(audio.data.shape), 1) nose.tools.eq_(audio.data.shape[0], 160001) # Segment audio = dcase_util.containers.AudioContainer( filename=dcase_util.utils.Example.audio_filename() ).load( mono=True, start=4.0, stop=6.0 ) nose.tools.eq_(audio.fs, 44100) nose.tools.eq_(len(audio.data.shape), 1) nose.tools.eq_(audio.data.shape[0], 88200) def test_load_youtube(): with dcase_util.utils.DisableLogger(): audio_container = dcase_util.containers.AudioContainer().load_from_youtube( query_id='2ceUOv8A3FE', start=1, stop=5 ) nose.tools.eq_(audio_container.fs, 44100) nose.tools.eq_(len(audio_container.data.shape), 2) nose.tools.eq_(audio_container.streams, 2) nose.tools.eq_(audio_container.shape, (2, 176400)) def test_container(): # Empty a = dcase_util.utils.Example.audio_container() if a: pass nose.tools.eq_(a.empty, False) nose.tools.eq_(dcase_util.containers.AudioContainer().empty, True) # Basic info a = dcase_util.utils.Example.audio_container() nose.tools.eq_(a.fs, 44100) nose.tools.eq_(len(a.data.shape), 2) nose.tools.eq_(a.data.shape, a.shape) nose.tools.eq_(a.duration_ms, 2000) nose.tools.eq_(a.duration_sec, 2) nose.tools.eq_(a.duration_samples, 2*44100) nose.tools.eq_(a.channels, 2) # Focus #1.1 a = dcase_util.utils.Example.audio_container() a.set_focus(start_seconds=0.5, stop_seconds=0.8) a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 13230)) # Focus #1.2 a = dcase_util.utils.Example.audio_container() a.set_focus(start_seconds=0.5, duration_seconds=0.3) a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 13230)) # Focus #1.3 a = dcase_util.utils.Example.audio_container() a.set_focus(start=0, duration=44100) a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 44100)) # Focus #1.4 a = dcase_util.utils.Example.audio_container() a.set_focus(start=0, stop=44100) a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 44100)) # Focus #1.5 a = dcase_util.utils.Example.audio_container() a.set_focus() a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 2*44100)) # Focus #2.1 a = dcase_util.utils.Example.audio_container() a.focus_start_samples = int(0.2 * 44100) a.focus_stop_samples = int(0.5 * 44100) a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 0.3 * 44100)) # Focus #2.2 a = dcase_util.utils.Example.audio_container() a.focus_start_samples = 0.2 * 44100 a.focus_stop_samples = 0.5 * 44100 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 0.3 * 44100)) # Focus #2.3 a = dcase_util.utils.Example.audio_container() a.focus_start_samples = 0.5 * 44100 a.focus_stop_samples = 0.2 * 44100 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 0.3 * 44100)) # Focus #2.4 a = dcase_util.utils.Example.audio_container() a.focus_stop_samples = 0.2 * 44100 a.focus_start_samples = 0.5 * 44100 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 0.3 * 44100)) # Focus #2.5 a = dcase_util.utils.Example.audio_container() a.focus_start_samples = 0.5 * 44100 a.focus_stop_samples = None a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 1.5 * 44100)) # Focus #2.6 a = dcase_util.utils.Example.audio_container() a.focus_start_samples = None a.focus_stop_samples = 0.5 * 44100 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 0.5 * 44100)) # Focus #2.7 a = dcase_util.utils.Example.audio_container() a.focus_start_samples = 0 a.focus_stop_samples = 30 * 44100 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, a.length)) # Focus #3.1 a = dcase_util.utils.Example.audio_container() a.focus_start_seconds = 1.0 a.focus_stop_seconds = 2.0 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, 1 * 44100)) # Focus #4.1 a = dcase_util.utils.Example.audio_container() a.focus_channel = 0 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 1) nose.tools.eq_(a_focused.shape, (a.length, )) numpy.testing.assert_array_almost_equal(a_focused, a.data[0, :]) # Focus #4.2 a = dcase_util.utils.Example.audio_container() a.focus_channel = 1 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 1) nose.tools.eq_(a_focused.shape, (a.length, )) numpy.testing.assert_array_almost_equal(a_focused, a.data[1, :]) # Focus #4.3 a = dcase_util.utils.Example.audio_container() a.focus_channel = 'left' a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 1) nose.tools.eq_(a_focused.shape, (a.length, )) numpy.testing.assert_array_almost_equal(a_focused, a.data[0, :]) # Focus #4.4 a = dcase_util.utils.Example.audio_container() a.focus_channel = 'right' a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 1) nose.tools.eq_(a_focused.shape, (a.length, )) numpy.testing.assert_array_almost_equal(a_focused, a.data[1, :]) # Focus #4.5 a = dcase_util.utils.Example.audio_container() a.focus_channel = 123 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 2) nose.tools.eq_(a_focused.shape, (2, a.length)) # Focus #4.6 a = dcase_util.utils.Example.audio_container() a.focus_channel = 0 a_focused = a.get_focused() nose.tools.eq_(len(a_focused.shape), 1) nose.tools.eq_(a_focused.shape, (a.length, )) # Channel average a = dcase_util.utils.Example.audio_container() a.mixdown() nose.tools.eq_(a.channels, 1) nose.tools.eq_(a.duration_ms, 2000) nose.tools.eq_(a.duration_sec, 2) nose.tools.eq_(a.duration_samples, 2*44100) # Normalization a = dcase_util.utils.Example.audio_container() a.normalize(headroom=0.5) nose.tools.eq_(a.duration_ms, 2000) nose.tools.eq_(a.duration_sec, 2) nose.tools.eq_(a.duration_samples, 2*44100) nose.tools.assert_almost_equal(numpy.max(numpy.abs(a.data)), 0.66666661027952101, places=6) # Normalization / Mono a = dcase_util.utils.Example.audio_container().mixdown() a.normalize(headroom=0.5) nose.tools.eq_(a.duration_ms, 2000) nose.tools.eq_(a.duration_sec, 2) nose.tools.eq_(a.duration_samples, 2*44100) nose.tools.assert_almost_equal(numpy.max(numpy.abs(a.data)), 0.63770331161958482, places=6) # Re-sampling a = dcase_util.utils.Example.audio_container() a.resample(target_fs=16000) nose.tools.eq_(a.fs, 16000) nose.tools.eq_(a.duration_ms, 2000) nose.tools.eq_(a.duration_sec, 2) nose.tools.eq_(a.duration_samples, 2*16000) # Select channel # make_monophonic a = dcase_util.utils.Example.audio_container() x1 = a.data[0, :] x2 = a.data[1, :] a.mixdown() nose.tools.eq_(a.fs, 44100) nose.tools.eq_(len(a.data.shape), 1) nose.tools.eq_(a.data.shape, a.shape) nose.tools.eq_(a.duration_ms, 2000) nose.tools.eq_(a.duration_sec, 2) nose.tools.eq_(a.duration_samples, 2*44100) nose.tools.eq_(a.channels, 1) def test_save(): a_out = dcase_util.utils.Example.audio_container() # 16 bit / wav tmp = tempfile.NamedTemporaryFile('r+', suffix='.wav', prefix='16_', dir='/tmp', delete=False) try: a_out.save(filename=tmp.name, bit_depth=16) a_in = dcase_util.containers.AudioContainer().load(filename=tmp.name) nose.tools.eq_(a_out.shape, a_in.shape) numpy.testing.assert_array_almost_equal(a_out.data, a_in.data, decimal=4) finally: os.unlink(tmp.name) # 24 bit / wav tmp = tempfile.NamedTemporaryFile('r+', suffix='.wav', prefix='24_', dir='/tmp', delete=False) try: a_out.save(filename=tmp.name, bit_depth=24) a_in = dcase_util.containers.AudioContainer().load(filename=tmp.name) nose.tools.eq_(a_out.shape, a_in.shape) numpy.testing.assert_array_almost_equal(a_out.data, a_in.data, decimal=5) finally: os.unlink(tmp.name) # 32 bit / wav tmp = tempfile.NamedTemporaryFile('r+', suffix='.wav', prefix='32_', dir='/tmp', delete=False) try: a_out.save(filename=tmp.name, bit_depth=32) a_in = dcase_util.containers.AudioContainer().load(filename=tmp.name) nose.tools.eq_(a_out.shape, a_in.shape) numpy.testing.assert_array_almost_equal(a_out.data, a_in.data, decimal=6) finally: os.unlink(tmp.name) def test_log(): with dcase_util.utils.DisableLogger(): a = dcase_util.utils.Example.audio_container() a.log() a.filename = 'test.wav' a.log() a.focus_start_samples = 0.1 a.focus_stop_samples = 0.5 a.log() a.focus_channel = 'left' a.log() def test_pad(): a = dcase_util.utils.Example.audio_container().mixdown() a.pad(length_seconds=10) nose.tools.eq_(a.duration_sec, 10) a = dcase_util.utils.Example.audio_container() a.pad(length_seconds=10) nose.tools.eq_(a.duration_sec, 10) a = dcase_util.utils.Example.audio_container_ch4() a.pad(length_seconds=10) nose.tools.eq_(a.duration_sec, 10) def test_segments(): a = dcase_util.utils.Example.audio_container().mixdown() segments, segment_meta = a.segments(segment_length=1000) nose.tools.eq_(len(segments), 88) nose.tools.eq_(len(segments), len(segment_meta)) segments, segment_meta = a.segments(segment_length_seconds=0.5) nose.tools.eq_(len(segments), 3) nose.tools.eq_(len(segments), len(segment_meta)) segments, segment_meta = a.segments( segments=[ {'onset': 0.5, 'offset': 0.8} ] ) nose.tools.eq_(len(segments), 1) nose.tools.eq_(len(segments), len(segment_meta)) nose.tools.eq_(segment_meta[0]['onset'], 0.5) nose.tools.eq_(segment_meta[0]['offset'], 0.8) segments, segment_meta = a.segments( segment_length_seconds=0.5, skip_segments=[ { 'onset': 0.6, 'offset': 0.8 } ] ) nose.tools.eq_(len(segments), 3) nose.tools.eq_(len(segments), len(segment_meta)) nose.tools.eq_(segment_meta, [ { 'onset': 0.0, 'offset': 0.5 }, { 'onset': 0.8, 'offset': 1.3 }, { 'onset': 1.3, 'offset': 1.8 } ]) a = dcase_util.utils.Example.audio_container() segments, segment_meta = a.segments(segment_length=1000) nose.tools.eq_(len(segments), 88) nose.tools.eq_(len(segments), len(segment_meta)) def test_frames(): a = dcase_util.utils.Example.audio_container().mixdown() frames = a.frames(frame_length=1000, hop_length=1000) nose.tools.eq_(frames.shape[0], 1000) nose.tools.eq_(frames.shape[1], 88) a = dcase_util.utils.Example.audio_container() frames = a.frames(frame_length=1000, hop_length=1000) nose.tools.eq_(frames.shape[0], 2) nose.tools.eq_(frames.shape[1], 1000) nose.tools.eq_(frames.shape[2], 88) @nose.tools.raises(ValueError) def test_focus_channel(): with dcase_util.utils.DisableLogger(): a = dcase_util.utils.Example.audio_container() a.focus_channel = 'wrong' @nose.tools.raises(IOError) def test_load_error(): with dcase_util.utils.DisableLogger(): dcase_util.containers.AudioContainer( filename='Test.test' ).load()
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py
Python
mizarlabs/transformers/__init__.py
MizarAI/mizar-labs
c6ec17bc3d9a91ec3f6ee2e7b20017499115fc37
[ "MIT" ]
18
2021-03-19T15:41:43.000Z
2022-03-20T14:23:07.000Z
mizarlabs/transformers/__init__.py
MizarAI/mizar-labs
c6ec17bc3d9a91ec3f6ee2e7b20017499115fc37
[ "MIT" ]
14
2021-03-17T14:16:02.000Z
2021-05-31T16:51:12.000Z
mizarlabs/transformers/__init__.py
MizarAI/mizar-labs
c6ec17bc3d9a91ec3f6ee2e7b20017499115fc37
[ "MIT" ]
3
2021-07-02T21:38:06.000Z
2022-01-10T09:56:18.000Z
from .utils import IdentityTransformer
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443d208ce4e7d48d2dc3609083791d96721ec308
13,452
py
Python
tests/test_setup.py
nickzuber/add-reason
c0f902bc59a6b0eca044750d4a1c99c48754971f
[ "MIT" ]
169
2017-12-18T21:48:01.000Z
2020-05-25T01:19:08.000Z
tests/test_setup.py
nickzuber/add-reason
c0f902bc59a6b0eca044750d4a1c99c48754971f
[ "MIT" ]
7
2017-12-30T05:43:42.000Z
2018-02-23T02:49:14.000Z
tests/test_setup.py
nickzuber/add-reason
c0f902bc59a6b0eca044750d4a1c99c48754971f
[ "MIT" ]
2
2018-02-08T16:25:17.000Z
2018-02-08T23:24:40.000Z
import os import subprocess from tests.framework.base_command_test_case import BaseCommandTestCase from tests.framework.context_manager import cd class TestInit(BaseCommandTestCase): # This is a portion of the postinstall script we generate that should always be there only once, since # our script should never write itself more than once. should_exist_once_in_postinstall = "fs=require('fs');if(fs.existsSync(d)===false){fs.symlinkSync(s,d,'dir')}" should_exist_once_in_build = "bsb -make-world" name = "reason-package" directory = "src/myCode" def test_steps_pass(self): with cd('./tests/root_for_testing'): result = self.call("node", "../../index.js", "setup", self.directory, self.name) self.assertTrue(result, 'Standard setup call did not pass successfully.') def test_steps_pass_no_linking_flag(self): with cd('./tests/root_for_testing'): result = self.call("node", "../../index.js", "setup", self.directory, self.name, "--no-linking") self.assertTrue(result, 'Standard --no-linking setup call did not pass successfully.') def test_steps_pass_in_source_flag(self): with cd('./tests/root_for_testing'): result = self.call("node", "../../index.js", "setup", self.directory, self.name, "--in-source") self.assertTrue(result, 'Standard --in-source setup call did not pass successfully.') def test_bsconfig_was_created(self): with cd('./tests/root_for_testing'): self.call("node", "../../index.js", "setup", self.directory, self.name) exists = os.path.isfile('bsconfig.json') self.assertTrue(exists, 'bsconfig.json was never created') def test_merlin_was_created(self): with cd('./tests/root_for_testing'): self.call("node", "../../index.js", "setup", self.directory, self.name) exists = os.path.isfile('.merlin') self.assertTrue(exists, '.merlin was never created') ### postinstall testing def test_postinstall_was_correctly_added_to_package_file_with_no_scripts(self): with cd('./tests/root_for_testing'): self.call("cp", "package.no_scripts.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('postinstall', contents['scripts'], 'Could not find postinstall key in the package.json scripts key') postinstall_script = contents['scripts']['postinstall'] self.assertEqual(postinstall_script.count(self.should_exist_once_in_postinstall), 1, 'Found more than one instance of our postinstall script') def test_postinstall_was_correctly_added_to_package_file_with_empty_scripts(self): with cd('./tests/root_for_testing'): self.call("cp", "package.empty_scripts.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('postinstall', contents['scripts'], 'Could not find postinstall key in the package.json scripts key') postinstall_script = contents['scripts']['postinstall'] self.assertEqual(postinstall_script.count(self.should_exist_once_in_postinstall), 1, 'Found more than one instance of our postinstall script') def test_postinstall_was_correctly_added_to_package_file_with_other_script(self): with cd('./tests/root_for_testing'): self.call("cp", "package.other_script.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('postinstall', contents['scripts'], 'Could not find postinstall key in the package.json scripts key') postinstall_script = contents['scripts']['postinstall'] self.assertEqual(postinstall_script.count(self.should_exist_once_in_postinstall), 1, 'Found more than one instance of our postinstall script') def test_postinstall_was_correctly_added_to_package_file_with_other_postinstall(self): with cd('./tests/root_for_testing'): self.call("cp", "package.other_postinstall.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('postinstall', contents['scripts'], 'Could not find postinstall key in the package.json scripts key') postinstall_script = contents['scripts']['postinstall'] self.assertIn(' && ', postinstall_script, 'Our postinstall script was probably not integrated correctly with an existing postinstall') self.assertEqual(postinstall_script.count(self.should_exist_once_in_postinstall), 1, 'Found more than one instance of our postinstall script') def test_postinstall_was_correctly_added_to_package_file_with_no_scripts_called_twice(self): with cd('./tests/root_for_testing'): self.call("node", "../../index.js", "setup", self.directory, self.name) self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('postinstall', contents['scripts'], 'Could not find postinstall key in the package.json scripts key') postinstall_script = contents['scripts']['postinstall'] self.assertEqual(postinstall_script.count(self.should_exist_once_in_postinstall), 1, 'Found more than one instance of our postinstall script') ### build command testing def test_build_command_was_correctly_added_to_package_file_with_no_scripts(self): with cd('./tests/root_for_testing'): self.call("cp", "package.no_scripts.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('build-reason', contents['scripts'], 'Could not find build-reason key in the package.json scripts key') build_command = contents['scripts']['build-reason'] self.assertEqual(build_command.count(self.should_exist_once_in_build), 1, 'Found more than one instance of our build script') def test_build_command_was_correctly_added_to_package_file_with_empty_scripts(self): with cd('./tests/root_for_testing'): self.call("cp", "package.empty_scripts.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('build-reason', contents['scripts'], 'Could not find build-reason key in the package.json scripts key') build_command = contents['scripts']['build-reason'] self.assertEqual(build_command.count(self.should_exist_once_in_build), 1, 'Found more than one instance of our postinstall script') def test_build_command_was_correctly_added_to_package_file_with_other_script(self): with cd('./tests/root_for_testing'): self.call("cp", "package.other_script.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('build-reason', contents['scripts'], 'Could not find build-reason key in the package.json scripts key') build_command = contents['scripts']['build-reason'] self.assertEqual(build_command.count(self.should_exist_once_in_build), 1, 'Found more than one instance of our postinstall script') def test_build_command_was_correctly_added_to_package_file_with_other_build_command(self): with cd('./tests/root_for_testing'): self.call("cp", "package.other_postinstall.json", "package.json") self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('build-reason', contents['scripts'], 'Could not find build-reason key in the package.json scripts key') build_command = contents['scripts']['build-reason'] self.assertIn(' && ', build_command, 'Our postinstall script was probably not integrated correctly with an existing postinstall') self.assertEqual(build_command.count(self.should_exist_once_in_build), 1, 'Found more than one instance of our postinstall script') def test_build_command_was_correctly_added_to_package_file_with_no_scripts_called_twice(self): with cd('./tests/root_for_testing'): self.call("node", "../../index.js", "setup", self.directory, self.name) self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_json('package.json') self.assertIn('scripts', contents, 'Could not find scripts key in the package.json file') self.assertIn('build-reason', contents['scripts'], 'Could not find build-reason key in the package.json scripts key') build_command = contents['scripts']['build-reason'] self.assertEqual(build_command.count(self.should_exist_once_in_build), 1, 'Found more than one instance of our postinstall script') def test_postinstall_was_not_added_to_package_file_with_in_source_flag(self): with cd('./tests/root_for_testing'): # This uses our default package.json copy which has a scripts key and no postinstall key self.call("node", "../../index.js", "setup", self.directory, self.name, "--in-source") contents = self.read_json('package.json') self.assertNotIn('postinstall', contents['scripts'], 'Postinstall was created when it should not have been') def test_proper_bsconfig_file_generated_with_in_source_flag(self): with cd('./tests/root_for_testing'): # This uses our default package.json copy which has a scripts key and no postinstall key self.call("node", "../../index.js", "setup", self.directory, self.name, "--in-source") contents = self.read_file('bsconfig.json') self.assertIn('in-source', contents, 'Config file doesn\'t have `in-source` set to true') def test_proper_bsconfig_file_generated_with(self): with cd('./tests/root_for_testing'): # This uses our default package.json copy which has a scripts key and no postinstall key self.call("node", "../../index.js", "setup", self.directory, self.name) contents = self.read_file('bsconfig.json') self.assertNotIn('in-source', contents, 'Config file wrongly has `in-source` set to true') def test_postinstall_was_not_added_to_package_file_with_no_linking_flag(self): with cd('./tests/root_for_testing'): # This uses our default package.json copy which has a scripts key and no postinstall key self.call("node", "../../index.js", "setup", self.directory, self.name, "--no-linking") contents = self.read_json('package.json') self.assertNotIn('postinstall', contents['scripts'], 'Postinstall was created when it should not have been') def test_config_was_not_created_when_given_bad_target(self): with cd('./tests/root_for_testing'): self.call("node", "../../index.js", "setup", 'some/bad/target', self.name) existsMerlin = self.exists('.merlin') existsBsconfig = self.exists('bsconfig.json') self.assertFalse(existsMerlin, '.merlin file was created even though we gave a bad target') self.assertFalse(existsBsconfig, 'bsconfig.json file was created even though we gave a bad target') def test_config_was_not_created_when_given_bad_target_no_linking(self): with cd('./tests/root_for_testing'): self.call("node", "../../index.js", "setup", 'some/bad/target', self.name, "--no-linking") existsMerlin = self.exists('.merlin') existsBsconfig = self.exists('bsconfig.json') self.assertFalse(existsMerlin, '.merlin file was created even though we gave a bad target') self.assertFalse(existsBsconfig, 'bsconfig.json file was created even though we gave a bad target') def test_postinstall_was_not_created_when_given_bad_target(self): with cd('./tests/root_for_testing'): self.call("cp", "package.other_postinstall.json", "package.json") contents = self.read_json('package.json') postinstall_before = contents['scripts']['postinstall'] self.call("node", "../../index.js", "setup", 'some/bad/target', self.name) contents = self.read_json('package.json') postinstall_after = contents['scripts']['postinstall'] self.assertEqual(postinstall_before, postinstall_after, 'The postinstall script was altered even though we gave bad target') def tearDown(self): with cd('./tests/root_for_testing'): self.call("rm", "-f", "bsconfig.json") self.call("rm", "-f", ".merlin") self.call("rm", "-rf", "lib") self.call("rm", "-f", "node_modules/reason-package") self.call("cp", "package.empty_scripts.json", "package.json")
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6
92726e39c726bfb77d4b6e053ffdca72cb2c6fb3
96
py
Python
venv/lib/python3.8/site-packages/rope/base/oi/type_hinting/providers/numpydocstrings.py
Retraces/UkraineBot
3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71
[ "MIT" ]
2
2022-03-13T01:58:52.000Z
2022-03-31T06:07:54.000Z
venv/lib/python3.8/site-packages/rope/base/oi/type_hinting/providers/numpydocstrings.py
DesmoSearch/Desmobot
b70b45df3485351f471080deb5c785c4bc5c4beb
[ "MIT" ]
19
2021-11-20T04:09:18.000Z
2022-03-23T15:05:55.000Z
venv/lib/python3.8/site-packages/rope/base/oi/type_hinting/providers/numpydocstrings.py
DesmoSearch/Desmobot
b70b45df3485351f471080deb5c785c4bc5c4beb
[ "MIT" ]
null
null
null
/home/runner/.cache/pip/pool/04/24/99/6e383995c777d21346cf27bed1be350c26cd82b9bd2745c6a780c01b54
96
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6
929757bef39e04b4376186e065d1cfa8ca63a044
13,187
py
Python
tests/test_population.py
comic31/MongoDBQueriesManager
34d2a0bd73777dc12ee860bbd8929254bed48791
[ "MIT" ]
2
2021-04-29T12:05:36.000Z
2021-07-15T08:42:40.000Z
tests/test_population.py
comic31/MongoDBQueriesManager
34d2a0bd73777dc12ee860bbd8929254bed48791
[ "MIT" ]
null
null
null
tests/test_population.py
comic31/MongoDBQueriesManager
34d2a0bd73777dc12ee860bbd8929254bed48791
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # coding: utf-8 # Copyright (c) Modos Team, 2020 import pytest from mongo_queries_manager import mqm, LogicalPopulationError, LogicalSubPopulationError class TestPopulation: def test_empty_population(self): query_result = mqm(string_query="populate=", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': []} def test_simple_population(self): query_result = mqm(string_query="populate=user", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [{'path': 'user', 'projection': None}]} def test_multi_population(self): query_result = mqm(string_query="populate=user,settings", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [{'path': 'user', 'projection': None}, {'path': 'settings', 'projection': None}]} def test_multi_population_2(self): query_result = mqm(string_query="populate=user,user.settings", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [{'path': 'user', 'projection': None, 'population': [{ 'path': 'settings', 'projection': None}]}]} def test_multi_population_3(self): query_result = mqm(string_query="populate=user,user.settings,user.comments,user.info", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [{'path': 'user', 'projection': None, 'population': [{ 'path': 'settings', 'projection': None}, { 'path': 'comments', 'projection': None}, { 'path': 'info', 'projection': None} ]}]} def test_multi_population_4(self): query_result = mqm(string_query="populate=user,user.settings,user.settings.info,user.settings.info.rates", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [ {'path': 'user', 'projection': None, 'population': [ { 'path': 'settings', 'projection': None, 'population': [ { 'path': 'info', 'projection': None, 'population': [ { 'path': 'rates', 'projection': None }] }] }] } ]} def test_multi_population_5(self): query_result = mqm( string_query="populate=user,user.settings,user.settings.notifications,user.settings.configuration", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [ {'path': 'user', 'projection': None, 'population': [ { 'path': 'settings', 'projection': None, 'population': [ { 'path': 'notifications', 'projection': None }, { 'path': 'configuration', 'projection': None } ] } ]}]} def test_multi_population_6(self): query_result = mqm( string_query="populate=user,user.life,user.life.info,user.settings,user.settings.notifications", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [ {'path': 'user', 'projection': None, 'population': [ { 'path': 'life', 'projection': None, 'population': [ { 'path': 'info', 'projection': None } ] }, { 'path': 'settings', 'projection': None, 'population': [ { 'path': 'notifications', 'projection': None } ] } ]}]} def test_simple_population_with_projection(self): query_result = mqm(string_query="fields=-created_at,-updated_at,hives.label&populate=hives", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': {'created_at': 0, 'updated_at': 0}, 'population': [{'path': 'hives', 'projection': {'label': 1}}]} def test_multi_population_with_multi_projection(self): query_result = mqm(string_query="fields=-created_at,-updated_at,hives.label,hives._id," "data.temperature&populate=hives,data", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': {'created_at': 0, 'updated_at': 0}, 'population': [{'path': 'hives', 'projection': {'label': 1, '_id': 1}}, {'path': 'data', 'projection': {'temperature': 1}}]} def test_multi_population_with_multi_projection_2(self): query_result = mqm(string_query="fields=-created_at,-updated_at,-service.created_at,-service.updated_at," "-service.description.created_at,-service." "description.updated_at&populate=service,service.description,service." "description.picture,animal,animal.info", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': {'created_at': 0, 'updated_at': 0}, 'population': [{ 'path': 'service', 'projection': {'created_at': 0, 'updated_at': 0}, 'population': [{ 'path': 'description', 'projection': {'created_at': 0, 'updated_at': 0}, 'population': [ {'path': 'picture', 'projection': None}] }]}, { 'path': 'animal', 'projection': None, 'population': [ {'path': 'info', 'projection': None}] }] } def test_bad_population_logic(self): with pytest.raises(LogicalPopulationError) as excinfo: query_result = mqm(string_query="populate=service.description", populate=True) assert excinfo.value.__str__() == 'Fail to find logical population item' def test_bad_population_logic_2(self): with pytest.raises(LogicalPopulationError) as excinfo: query_result = mqm(string_query="populate=service,service.description,service.description.toto.titi", populate=True) assert excinfo.value.__str__() == 'Fail to find logical population item' def test_bad_sub_population_logic(self): with pytest.raises(LogicalSubPopulationError) as excinfo: query_result = mqm(string_query="populate=service,service.description," "service.description.info,service.descriptions.info", populate=True) assert excinfo.value.__str__() == 'Fail to find logical sub population item' def test_bad_sub_population_logic_2(self): with pytest.raises(LogicalSubPopulationError) as excinfo: query_result = mqm(string_query="populate=service,service.description,service.description.info," "service.description.info,service.description.info.toto," "service.descriptions.info.titi", populate=True) assert excinfo.value.__str__() == 'Fail to find logical sub population item' def test_sub_population_alex(self): query_result = mqm(string_query="populate=animal,crossbreed,crossbreed.crossbreeds,company,service," "service.service_description,pet&fields=-company.settings.booking", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [{'path': 'animal', 'projection': None}, {'path': 'crossbreed', 'projection': None, 'population': [ {'path': 'crossbreeds', 'projection': None}]}, {'path': 'company', 'projection': {'settings.booking': 0}}, {'path': 'service', 'projection': None, 'population': [ {'path': 'service_description', 'projection': None}]}, {'path': 'pet', 'projection': None}]} def test_sub_population_alex_2(self): query_result = mqm(string_query="populate=animal,crossbreed,crossbreed.crossbreeds,company,service," "service.service_description,pet&fields=-company.settings.booking," "-company.settings.toto", populate=True) assert query_result == {'filter': {}, 'sort': None, 'skip': 0, 'limit': 0, 'projection': None, 'population': [{'path': 'animal', 'projection': None}, {'path': 'crossbreed', 'projection': None, 'population': [ {'path': 'crossbreeds', 'projection': None}]}, {'path': 'company', 'projection': {'settings.booking': 0, 'settings.toto': 0}}, {'path': 'service', 'projection': None, 'population': [ {'path': 'service_description', 'projection': None}]}, {'path': 'pet', 'projection': None}]}
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6
2bc83f7a6460e5b4c817a612aa26c80f1e0aa5f7
1,076
py
Python
rest_framework_extensions/decorators.py
maryokhin/drf-extensions
8223db2bdddaf3cd99f951b2291210c5fd5b0e6f
[ "MIT" ]
null
null
null
rest_framework_extensions/decorators.py
maryokhin/drf-extensions
8223db2bdddaf3cd99f951b2291210c5fd5b0e6f
[ "MIT" ]
null
null
null
rest_framework_extensions/decorators.py
maryokhin/drf-extensions
8223db2bdddaf3cd99f951b2291210c5fd5b0e6f
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import warnings def link(endpoint=None, is_for_list=False, **kwargs): """ Used to mark a method on a ViewSet that should be routed for GET requests. """ msg = 'link is pending deprecation. Use detail_route instead.' warnings.warn(msg, PendingDeprecationWarning, stacklevel=2) def decorator(func): func.bind_to_methods = ['get'] func.kwargs = kwargs func.endpoint = endpoint or func.__name__ func.is_for_list = is_for_list return func return decorator def action(methods=['post'], endpoint=None, is_for_list=False, **kwargs): """ Used to mark a method on a ViewSet that should be routed for POST requests. """ msg = 'action is pending deprecation. Use detail_route instead.' warnings.warn(msg, PendingDeprecationWarning, stacklevel=2) def decorator(func): func.bind_to_methods = methods func.kwargs = kwargs func.endpoint = endpoint or func.__name__ func.is_for_list = is_for_list return func return decorator
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6
2bd6bebfa58de8e850328790a29e3c49bb9c5ebf
257
py
Python
container/pyf/schemas/classroom.py
Pompino/react-components-23KB
3201a417c5160e1b77f29fc1eac74ae9dc10d6ad
[ "MIT" ]
2
2021-10-30T18:18:33.000Z
2021-12-01T10:21:28.000Z
container/pyf/schemas/classroom.py
Pompino/react-components-23KB
3201a417c5160e1b77f29fc1eac74ae9dc10d6ad
[ "MIT" ]
null
null
null
container/pyf/schemas/classroom.py
Pompino/react-components-23KB
3201a417c5160e1b77f29fc1eac74ae9dc10d6ad
[ "MIT" ]
null
null
null
from pydantic import BaseModel as BaseSchema from simpleschemas import UserGetSimpleSchema, GroupGetSimpleSchema, EventGetSimpleSchema, ClassRoomGetSimpleSchema class ClassRoomGetSchema(ClassRoomGetSimpleSchema): class Config: orm_mode = True
32.125
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2be0f2e2264d868d4ffaee8e3626c464c7c8ebbf
217
py
Python
core/extensions/xtp/__init__.py
yunnant/kungfu
03dba19c922a5950068bd2d223488b8543ad8dd1
[ "Apache-2.0" ]
2,209
2017-11-15T07:51:14.000Z
2021-01-19T03:16:48.000Z
core/extensions/xtp/__init__.py
yunnant/kungfu
03dba19c922a5950068bd2d223488b8543ad8dd1
[ "Apache-2.0" ]
45
2017-11-16T04:38:51.000Z
2021-01-18T22:20:33.000Z
core/extensions/xtp/__init__.py
yunnant/kungfu
03dba19c922a5950068bd2d223488b8543ad8dd1
[ "Apache-2.0" ]
889
2017-11-15T08:04:38.000Z
2021-01-16T12:41:25.000Z
from . import ${PROJECT_NAME} as ext from extensions import EXTENSION_REGISTRY_MD, EXTENSION_REGISTRY_TD EXTENSION_REGISTRY_MD.register_extension('xtp', ext.MD) EXTENSION_REGISTRY_TD.register_extension('xtp', ext.TD)
43.4
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6
920fd84acb260e96a57d6c63a4c7b8e5cb0ed55a
17,682
py
Python
poda/segmentation/InceptionV4ResnetV2.py
gideonmanurung/poda
0a64cfa474f82acb891454141bc537d81bc77092
[ "MIT" ]
null
null
null
poda/segmentation/InceptionV4ResnetV2.py
gideonmanurung/poda
0a64cfa474f82acb891454141bc537d81bc77092
[ "MIT" ]
4
2020-09-26T01:08:59.000Z
2022-02-10T01:40:42.000Z
poda/segmentation/InceptionV4ResnetV2.py
gideonmanurung/poda
0a64cfa474f82acb891454141bc537d81bc77092
[ "MIT" ]
null
null
null
import tensorflow as tf from poda.layers.convolutional import * class InceptionV4ResnetV2(object): def __init__(self, is_training = True): """[summary] Arguments: num_classes {[type]} -- [description] Keyword Arguments: input_tensor {[type]} -- [description] (default: {None}) input_shape {tuple} -- [description] (default: {(None, 300, 300, 3)}) learning_rate {float} -- [description] (default: {0.0001}) is_training {bool} -- [description] (default: {True}) """ self.is_training = is_training def conv_block(self, inputs, filters, kernel_size, strides=(2,2), padding='VALID', dropout_rate=0.2, activation='relu', batch_normalization=True): """[summary] Arguments: inputs {[type]} -- [description] filters {[type]} -- [description] kernel_size {[type]} -- [description] Keyword Arguments: strides {tuple} -- [description] (default: {(2,2)}) padding {str} -- [description] (default: {'valid'}) batch_normalization {bool} -- [description] (default: {True}) dropout_rate {float} -- [description] (default: {0.15}) activation {str} -- [description] (default: {'relu'}) is_training {bool} -- [description] (default: {True}) Returns: [type] -- [description] """ conv = convolution_2d(input_tensor=inputs, number_filters=filters, kernel_sizes=kernel_size, stride_sizes=strides, paddings=padding, activations=activation) conv = batch_normalization(input_tensor=conv, is_trainable=batch_normalization) conv = dropout(input_tensor=conv, dropout_rates=dropout_rate) return conv def stem_block(self, input_tensor, batch_normalization=True): """[summary] Arguments: input_tensor {[type]} -- [description] Returns: [type] -- [description] """ conv_1 = self.conv_block(inputs=input_tensor, filters=32, kernel_size=(3,3), strides=(2, 2), batch_normalization=batch_normalization) conv_2 = self.conv_block(inputs=conv_1, filters=32, kernel_size=(3,3), strides=(1,1), batch_normalization=batch_normalization) conv_3 = self.conv_block(inputs=conv_2, filters=64, kernel_size=(3,3), padding='same', strides=(1, 1), batch_normalization=batch_normalization) conv_4 = self.conv_block(inputs=conv_3, filters=96, kernel_size=(3,3), strides=(2,2), batch_normalization=batch_normalization) max_pool_1 = max_pool_2d(input_tensor=conv_3, pool_sizes=(3,3), stride_sizes=(2,2)) concat_1 = tf.concat([conv_4, max_pool_1], -1) conv_5 = self.conv_block(inputs=concat_1, filters=64, kernel_size=(3,3), strides=(1,1), batch_normalization=batch_normalization) conv_6 = self.conv_block(inputs=conv_5, filters=64, kernel_size=(7,1), padding='same', strides=(1, 1), batch_normalization=batch_normalization) conv_7 = self.conv_block(inputs=conv_6, filters=64, kernel_size=(1,7), padding='same', strides=(1, 1), batch_normalization=batch_normalization) conv_8 = self.conv_block(inputs=conv_7, filters=96, kernel_size=(3,3), padding='same', strides=(1, 1), batch_normalization=batch_normalization) conv_9 = self.conv_block(inputs=concat_1, filters=64, kernel_size=(1,1), strides=(1,1), batch_normalization=batch_normalization) conv_10 = self.conv_block(inputs=conv_9, filters=96, kernel_size=(3,3), strides=(1,1), batch_normalization=batch_normalization) concat_2 = tf.concat([conv_8, conv_10], -1) max_pool_2 = max_pool_2d(inputs=concat_2, pool_sizes=(3,3), stride_sizes=(2,2)) conv_11 = self.conv_block(inputs=concat_2, filters=192, kernel_size=(3,3), strides=(2,2), batch_normalization=batch_normalization) concat_3 = tf.concat([max_pool_2, conv_11], -1) return concat_3 def inception_resnet_a(self, input_tensor, drop_out=0.80, batch_normalization=True): """[summary] Arguments: inputs {[type]} -- [description] Keyword Arguments: drop_out {float} -- [description] (default: {0.85}) activation {str} -- [description] (default: {'NONE'}) is_training {bool} -- [description] (default: {True}) use_bias {bool} -- [description] (default: {True}) use_batchnorm {bool} -- [description] (default: {True}) """ conv_1 = self.conv_block(inputs=input_tensor, filters=64, kernel_size=(1,1) , strides=(1,1), batch_normalization=batch_normalization) conv_2 = self.conv_block(inputs=conv_1, filters=96, kernel_size=(3,3) , strides=(1,1), batch_normalization=batch_normalization) conv_3 = self.conv_block(inputs=conv_2, filters=96, kernel_size=(3,3) , strides=(1,1), batch_normalization=batch_normalization) conv_4 = self.conv_block(inputs=input_tensor, filters=64, kernel_size=(1,1) , strides=(1,1), batch_normalization=batch_normalization) conv_5 = self.conv_block(inputs=conv_4, filters=96, kernel_size=(3,3) , strides=(1,1), batch_normalization=batch_normalization) conv_6 = self.conv_block(inputs=input_tensor, filters=96, kernel_size=(1,1) , strides=(1,1), batch_normalization=batch_normalization) conv_7 = self.conv_block(inputs=conv_2, filters=96, kernel_size=(3,3) , strides=(1,1), batch_normalization=batch_normalization) input_depth = conv_right1.get_shape().as_list()[-1] conv_right2, _ = new_conv2d_layer(input=conv_right1, filter_shape=[3, 3, input_depth, 48], name='inres_a_conv_r2', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = conv_right2.get_shape().as_list()[-1] conv_right3, _ = new_conv2d_layer(input=conv_right2, filter_shape=[3, 3, input_depth, 32], name='inres_a_conv_r3', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = inputs.get_shape().as_list()[-1] conv_mid1, _ = new_conv2d_layer(input=inputs, filter_shape=[1, 1, input_depth, 32], name='inres_a_conv_m1', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = conv_mid1.get_shape().as_list()[-1] conv_mid2, _ = new_conv2d_layer(input=conv_mid1, filter_shape=[3, 3, input_depth, 32], name='inres_a_conv_m2', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = inputs.get_shape().as_list()[-1] conv_left1, _ = new_conv2d_layer(input=inputs, filter_shape=[1, 1, input_depth, 32], name='inres_a_conv_l1', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) concat_conv = tf.concat([conv_right3, conv_mid2, conv_left1], -1) input_depth = concat_conv.get_shape().as_list()[-1] output_depth = inputs.get_shape().as_list()[-1] conv_mixed, _ = new_conv2d_layer(input=concat_conv, filter_shape=[1, 1, input_depth, output_depth], name='inres_a_conv_concat', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) final_conv = inputs + conv_mixed return final_conv #return tf.nn.leaky_relu(final_conv) # Reduction A def reduction_a(self, inputs, drop_out=0.80, activation='NONE', use_bias=True, use_batchnorm=True): """[summary] Arguments: inputs {[type]} -- [description] Keyword Arguments: drop_out {float} -- [description] (default: {0.85}) activation {str} -- [description] (default: {'NONE'}) is_training {bool} -- [description] (default: {True}) use_bias {bool} -- [description] (default: {True}) use_batchnorm {bool} -- [description] (default: {True}) """ input_depth = inputs.get_shape().as_list()[-1] conv_right1, _ = new_conv2d_layer(input=inputs, filter_shape=[1, 1, input_depth, 256], name='reduc_a_conv_r1', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = conv_right1.get_shape().as_list()[-1] conv_right2, _ = new_conv2d_layer(input=conv_right1, filter_shape=[3, 3, input_depth, 256], name='reduc_a_conv_r2', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = conv_right2.get_shape().as_list()[-1] conv_right3, _ = new_conv2d_layer(input=conv_right2, filter_shape=[3, 3, input_depth, 384], name='reduc_a_conv_r3', dropout_val=drop_out, activation=activation, strides=[1, 2, 2, 1], padding='VALID', is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = inputs.get_shape().as_list()[-1] conv_mid1, _ = new_conv2d_layer(input=inputs, filter_shape=[3, 3, input_depth, 384], name='reduc_a_conv_m1', dropout_val=drop_out, activation=activation, strides=[1, 2, 2, 1], padding='VALID', is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) """ max_pool = tf.nn.max_pool(value=inputs, ksize=[1, 3, 3, 1], strides=[1, 1, 1, 15], padding='VALID', name='reduc_a_conv_mp') """ return tf.concat([conv_right3, conv_mid1], -1, name='hellloooooo') # Inception ResNet B def inception_resnet_b(self, inputs, drop_out=0.80, activation='NONE', use_bias=True, use_batchnorm=True): """[summary] Arguments: inputs {[type]} -- [description] Keyword Arguments: drop_out {float} -- [description] (default: {0.85}) activation {str} -- [description] (default: {'NONE'}) is_training {bool} -- [description] (default: {True}) use_bias {bool} -- [description] (default: {True}) use_batchnorm {bool} -- [description] (default: {True}) """ input_depth = inputs.get_shape().as_list()[-1] conv_right1, _ = new_conv2d_layer(input=inputs, filter_shape=[1, 1, input_depth, 128], name='inres_a_conv_r1', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = conv_right1.get_shape().as_list()[-1] conv_right2, _ = new_conv2d_layer(input=conv_right1, filter_shape=[1, 7, input_depth, 160], name='inres_a_conv_r2', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = conv_right2.get_shape().as_list()[-1] conv_right3, _ = new_conv2d_layer(input=conv_right2, filter_shape=[7, 1, input_depth, 192], name='inres_a_conv_r3', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) input_depth = inputs.get_shape().as_list()[-1] conv_mid1, _ = new_conv2d_layer(input=inputs, filter_shape=[1, 1, input_depth, 192], name='inres_a_conv_m1', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) concat_conv = tf.concat([conv_right3, conv_mid1], -1) input_depth = concat_conv.get_shape().as_list()[-1] output_depth = inputs.get_shape().as_list()[-1] conv_mixed, _ = new_conv2d_layer(input=concat_conv, filter_shape=[1, 1, input_depth, output_depth], name='inres_a_conv_mx', dropout_val=drop_out, activation=activation, is_training=self.is_training, use_bias=use_bias, use_batchnorm=use_batchnorm) final_conv = inputs + conv_mixed return final_conv #return tf.nn.leaky_relu(final_conv) def create_base_model(self, input=None): """[summary] Arguments: classes {[type]} -- [description] Returns: [type] -- [description] """ with tf.variable_scope("stem"): net = self.stem_block(input) print (net, "===================>>>") with tf.variable_scope("inception_resnet_a"): for i in range(5): net = self.inception_resnet_a(inputs=net) print (net, "===================>>>") with tf.variable_scope("reduction_a"): net = self.reduction_a(inputs=net) print(net, "===================>>>") with tf.variable_scope("inception_resnet_b"): for i in range(10): net = self.inception_resnet_b(inputs=net) print (net, "===================>>>") return net
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6
a626c17f1ddc96620ae5513ec6da9897863fb641
173
py
Python
rest_ml/firstApp/admin.py
Binucb/machineLearning_RestAPI
5ffb51febd9ac31e74977aa20cb1ab8c9e44560a
[ "MIT" ]
null
null
null
rest_ml/firstApp/admin.py
Binucb/machineLearning_RestAPI
5ffb51febd9ac31e74977aa20cb1ab8c9e44560a
[ "MIT" ]
4
2021-03-19T02:02:07.000Z
2021-06-04T22:54:44.000Z
rest_ml/firstApp/admin.py
Binucb/machineLearning_RestAPI
5ffb51febd9ac31e74977aa20cb1ab8c9e44560a
[ "MIT" ]
null
null
null
from django.contrib import admin from firstApp import models # Register your models here. admin.site.register(models.PersonDetail) admin.site.register(models.MovieRating)
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6
a6f78b91c5bbb2598357f86be62fa5d4530bb764
177
py
Python
contact/fields.py
uktrade/great-domestic-ui
e4c1e4783d7321e170ecb6fd5f9eb6c30cd21f4c
[ "MIT" ]
null
null
null
contact/fields.py
uktrade/great-domestic-ui
e4c1e4783d7321e170ecb6fd5f9eb6c30cd21f4c
[ "MIT" ]
369
2019-02-18T15:53:55.000Z
2021-06-09T13:17:37.000Z
contact/fields.py
uktrade/great-domestic-ui
e4c1e4783d7321e170ecb6fd5f9eb6c30cd21f4c
[ "MIT" ]
3
2019-03-11T12:04:22.000Z
2020-11-12T15:28:13.000Z
from directory_components.forms import DirectoryComponentsFieldMixin from django import forms class IntegerField(DirectoryComponentsFieldMixin, forms.IntegerField): pass
22.125
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6
470ee63186367deeb54b613f36979408b5081240
20
py
Python
__init__.py
rodrigo203203/person_track_yolo_detection
b6210467ca188af44b9c1b513fcbfa8af240a66a
[ "MIT" ]
null
null
null
__init__.py
rodrigo203203/person_track_yolo_detection
b6210467ca188af44b9c1b513fcbfa8af240a66a
[ "MIT" ]
null
null
null
__init__.py
rodrigo203203/person_track_yolo_detection
b6210467ca188af44b9c1b513fcbfa8af240a66a
[ "MIT" ]
null
null
null
from . import prueba
20
20
0.8
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6
5bbc5268cd81744970ec1919181a5071a75fc258
22
py
Python
writing/__init__.py
akyruu/blender-cartography-addon
4f34b029d9b6a72619227ab3ceaed9393506934e
[ "Apache-2.0" ]
null
null
null
writing/__init__.py
akyruu/blender-cartography-addon
4f34b029d9b6a72619227ab3ceaed9393506934e
[ "Apache-2.0" ]
null
null
null
writing/__init__.py
akyruu/blender-cartography-addon
4f34b029d9b6a72619227ab3ceaed9393506934e
[ "Apache-2.0" ]
null
null
null
from .writer import *
11
21
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6
5bc46372f756cc1ca3bfb90fe230442edd601420
3,999
py
Python
mlxtk/doit_analyses/expval.py
f-koehler/mlxtk
373aed06ab23ab9b70cd99e160228c50b87e939a
[ "MIT" ]
2
2018-12-21T19:41:10.000Z
2019-11-25T15:26:27.000Z
mlxtk/doit_analyses/expval.py
f-koehler/mlxtk
373aed06ab23ab9b70cd99e160228c50b87e939a
[ "MIT" ]
73
2017-12-22T13:30:16.000Z
2022-02-22T04:21:14.000Z
mlxtk/doit_analyses/expval.py
f-koehler/mlxtk
373aed06ab23ab9b70cd99e160228c50b87e939a
[ "MIT" ]
null
null
null
from pathlib import Path from typing import List, Union import matplotlib.pyplot as plt import numpy from mlxtk.doit_analyses.collect import collect_values from mlxtk.doit_analyses.plot import doit_plot_individual from mlxtk.inout.expval import read_expval_hdf5 from mlxtk.parameter_selection import load_scan from mlxtk.plot import PlotArgs2D from mlxtk.plot.expval import plot_expval from mlxtk.util import make_path def collect_initial_expval( scan_dir: Union[Path, str], expval: Union[Path, str], output_file: Union[Path, str] = None, node: int = 1, dof: int = 1, missing_ok: bool = True, ): expval = make_path(expval) if output_file is None: folder_name = "expval_" + expval.name.rstrip(".exp.h5") if not folder_name.startswith("initial_"): folder_name = "initial_" + folder_name output_file = Path("data") / (folder_name) / (make_path(scan_dir).name + ".txt") def fetch(index, path, parameters): _, data = numpy.array(read_expval_hdf5(path / expval)) return data[0].real, data[0].imag return collect_values(scan_dir, [expval], output_file, fetch, missing_ok=missing_ok) def collect_final_expval( scan_dir: Union[Path, str], expval: Union[Path, str], output_file: Union[Path, str] = None, node: int = 1, dof: int = 1, missing_ok: bool = True, ): expval = make_path(expval) if output_file is None: folder_name = "expval_" + expval.name.rstrip(".exp.h5") if not folder_name.startswith("final_"): folder_name = "final_" + folder_name output_file = Path("data") / (folder_name) / (make_path(scan_dir).name + ".txt") def fetch(index, path, parameters): _, data = numpy.array(read_expval_hdf5(path / expval)) return data[-1].real, data[-1].imag return collect_values(scan_dir, [expval], output_file, fetch, missing_ok=missing_ok) def scan_plot_expval( scan_dir: Union[Path, str], expval: Union[Path, str], extensions: List[str] = [ ".png", ], **kwargs, ): scan_dir = make_path(scan_dir) expval = make_path(expval) kwargs["coefficient"] = kwargs.get("coefficient", 1.0) plotting_args = PlotArgs2D.from_dict(kwargs) selection = load_scan(scan_dir) def plot_func(index, path, parameters): del path del parameters data = read_expval_hdf5( str((scan_dir / "by_index" / str(index) / expval).with_suffix(".exp.h5")) ) fig, axis = plt.subplots(1, 1) plot_expval(axis, *data, **kwargs) return fig, [axis] return doit_plot_individual( selection, f"expval_{str(expval)}".replace("/", "_"), [str(expval.with_suffix(".exp.h5"))], plot_func, plotting_args, extensions, decorator_funcs=kwargs.get("decorator_funcs", []), extra_args={"coefficient": kwargs["coefficient"]}, ) def scan_plot_variance( scan_dir: Union[Path, str], variance: Union[Path, str], extensions: List[str] = [ ".png", ], **kwargs, ): scan_dir = make_path(scan_dir) variance = make_path(variance) kwargs["coefficient"] = kwargs.get("coefficient", 1.0) plotting_args = PlotArgs2D.from_dict(kwargs) selection = load_scan(scan_dir) def plot_func(index, path, parameters): del path del parameters data = read_expval_hdf5( str((scan_dir / "by_index" / str(index) / variance).with_suffix(".var.h5")) ) fig, axis = plt.subplots(1, 1) plot_expval(axis, *data, **kwargs) return fig, [axis] return doit_plot_individual( selection, f"variance_{str(variance)}".replace("/", "_"), [str(variance.with_suffix(".var.h5"))], plot_func, plotting_args, extensions, decorator_funcs=kwargs.get("decorator_funcs", []), extra_args={"coefficient": kwargs["coefficient"]}, )
28.564286
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3,999
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0.046167
0.049464
0.026381
0.761748
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0.72094
0.72094
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3,999
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false
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6
752792d2db55ad4d968b8ab127cfa45e80d8b3e6
31
py
Python
invoice2data/__init__.py
GfxKai/invoice2data
caec851578e99d40b989cabba07cfdf61f71ac58
[ "MIT" ]
1
2018-02-14T17:24:09.000Z
2018-02-14T17:24:09.000Z
invoice2data/__init__.py
GfxKai/invoice2data
caec851578e99d40b989cabba07cfdf61f71ac58
[ "MIT" ]
null
null
null
invoice2data/__init__.py
GfxKai/invoice2data
caec851578e99d40b989cabba07cfdf61f71ac58
[ "MIT" ]
1
2020-08-15T19:38:16.000Z
2020-08-15T19:38:16.000Z
from .main import extract_data
15.5
30
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31
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6
7537ad02c36716a036312fc684cd33bf734c864a
26
py
Python
src/perceptron/Neuron/__init__.py
SweetBubaleXXX/sweet-perceptron
473f4372fb6821c073da249a35a06b82378357f6
[ "MIT" ]
1
2022-03-21T14:48:27.000Z
2022-03-21T14:48:27.000Z
src/perceptron/Neuron/__init__.py
SweetBubaleXXX/sweet-perceptron
473f4372fb6821c073da249a35a06b82378357f6
[ "MIT" ]
null
null
null
src/perceptron/Neuron/__init__.py
SweetBubaleXXX/sweet-perceptron
473f4372fb6821c073da249a35a06b82378357f6
[ "MIT" ]
null
null
null
from .Neuron import Neuron
26
26
0.846154
4
26
5.5
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1
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26
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1
0
0
6
7542753a75521d181dd4d8301078e512e589a13d
125
py
Python
RiboGraphViz/__init__.py
rkretsch/RiboGraphViz
5a844dc9857bd4e20218ec65942ffbc899f8956f
[ "MIT" ]
5
2020-09-11T23:32:59.000Z
2022-03-31T09:01:11.000Z
RiboGraphViz/__init__.py
rkretsch/RiboGraphViz
5a844dc9857bd4e20218ec65942ffbc899f8956f
[ "MIT" ]
1
2021-08-13T20:40:46.000Z
2021-08-13T23:15:15.000Z
RiboGraphViz/__init__.py
rkretsch/RiboGraphViz
5a844dc9857bd4e20218ec65942ffbc899f8956f
[ "MIT" ]
2
2021-07-28T20:03:36.000Z
2022-01-08T07:11:09.000Z
from .RiboGraphViz import RiboGraphViz as RGV from .LoopExtruder import LoopExtruder from .LoopExtruder import StackExtruder
31.25
45
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125
7.714286
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125
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6
f33dc56a546a050d746f893b7bec5e3047c2293b
162
py
Python
server/tests/__init__.py
natowi/pepi
22df696209ac2545d1e8e1cf0c8822725acadb29
[ "Apache-2.0" ]
4
2017-08-30T03:17:34.000Z
2019-09-24T08:57:41.000Z
server/tests/__init__.py
natowi/pepi
22df696209ac2545d1e8e1cf0c8822725acadb29
[ "Apache-2.0" ]
14
2017-09-02T03:53:14.000Z
2022-03-11T23:19:04.000Z
server/tests/__init__.py
natowi/pepi
22df696209ac2545d1e8e1cf0c8822725acadb29
[ "Apache-2.0" ]
3
2019-03-27T18:33:25.000Z
2021-07-17T02:18:19.000Z
from .test_server import MetaCameraServerContract from .test_server_over_thrift import MetaCameraServerOverThrift from .test_camera import AbstractCameraContract
40.5
63
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162
8.352941
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0.197183
0
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6
f364ccac5cd5496ec7276b703ef853b316a142bc
128
py
Python
mandala/core/exceptions.py
amakelov/mandala
a9ec051ef730ada4eed216c62a07b033126e78d5
[ "Apache-2.0" ]
9
2022-02-22T19:24:01.000Z
2022-03-23T04:46:41.000Z
mandala/core/exceptions.py
amakelov/mandala
a9ec051ef730ada4eed216c62a07b033126e78d5
[ "Apache-2.0" ]
null
null
null
mandala/core/exceptions.py
amakelov/mandala
a9ec051ef730ada4eed216c62a07b033126e78d5
[ "Apache-2.0" ]
null
null
null
from ..common_imports import * class SynchronizationError(Exception): pass class VRefNotInMemoryError(Exception): pass
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0
6
f38cecc11daf613785082bebda6a274a61e723f2
22,356
py
Python
test/unit/live_cluster/test_manage_controller.py
jfwm2/aerospike-admin
3ce721bbd249eca73046345620941a6aef325589
[ "Apache-2.0" ]
null
null
null
test/unit/live_cluster/test_manage_controller.py
jfwm2/aerospike-admin
3ce721bbd249eca73046345620941a6aef325589
[ "Apache-2.0" ]
null
null
null
test/unit/live_cluster/test_manage_controller.py
jfwm2/aerospike-admin
3ce721bbd249eca73046345620941a6aef325589
[ "Apache-2.0" ]
null
null
null
from lib.base_controller import ShellException import unittest from mock import MagicMock, patch from lib.live_cluster.client.info import ASProtocolError, ASResponse from lib.live_cluster.manage_controller import ( ManageACLCreateRoleController, ManageACLCreateUserController, ManageACLQuotasRoleController, ) from lib.live_cluster.live_cluster_root_controller import LiveClusterRootController from test.unit import util as test_util class ManageACLCreateUserControllerTest(unittest.TestCase): def setUp(self) -> None: patch("lib.live_cluster.live_cluster_root_controller.Cluster").start() self.root_controller = LiveClusterRootController() self.controller = ManageACLCreateUserController() self.cluster_mock = patch( "lib.live_cluster.manage_controller.ManageACLCreateUserController.cluster" ).start() self.logger_mock = patch("lib.base_controller.BaseController.logger").start() self.view_mock = patch("lib.base_controller.BaseController.view").start() self.mods = {"like": [], "with": [], "for": [], "line": []} self.addCleanup(patch.stopall) def test_no_roles_and_no_password(self): getpass_mock = patch("lib.live_cluster.manage_controller.getpass").start() getpass_mock.return_value = "pass" self.cluster_mock.get_expected_principal.return_value = "principal" self.cluster_mock.admin_create_user.return_value = { "principal_ip": ASResponse.OK } self.controller.execute(["test-user"]) self.cluster_mock.admin_create_user.assert_called_with( "test-user", "pass", [], nodes=["principal"] ) self.view_mock.print_result.assert_called_with( "Successfully created user test-user." ) def test_with_roles_and_password(self): self.cluster_mock.get_expected_principal.return_value = "principal" self.cluster_mock.admin_create_user.return_value = { "principal_ip": ASResponse.OK } self.controller.execute( ["test-user", "password", "pass", "roles", "role1", "role2", "role3"] ) self.cluster_mock.admin_create_user.assert_called_with( "test-user", "pass", ["role1", "role2", "role3"], nodes=["principal"] ) self.view_mock.print_result.assert_called_with( "Successfully created user test-user." ) def test_with_role_and_password(self): self.cluster_mock.get_expected_principal.return_value = "principal" self.cluster_mock.admin_create_user.return_value = { "principal_ip": ASResponse.OK } self.controller.execute( ["test-user", "password", "pass", "role", "role1", "role2", "role3"] ) self.cluster_mock.admin_create_user.assert_called_with( "test-user", "pass", ["role1", "role2", "role3"], nodes=["principal"] ) self.view_mock.print_result.assert_called_with( "Successfully created user test-user." ) def test_logs_error_when_asprotocol_error_returned(self): as_error = ASProtocolError(ASResponse.USER_ALREADY_EXISTS, "test-message") log_message = "test-message : User already exists." line = "test-user password pass" self.cluster_mock.get_expected_principal.return_value = "principal" self.cluster_mock.admin_create_user.return_value = {"principal_ip": as_error} self.controller.execute(line.split()) self.cluster_mock.admin_create_user.assert_called_with( "test-user", "pass", [], nodes=["principal"] ) self.logger_mock.error.assert_called_with(log_message) self.view_mock.print_result.assert_not_called() def test_raises_exception_when_exception_returned(self): as_error = IOError("test-message") line = "test-user password pass" self.cluster_mock.get_expected_principal.return_value = "principal" self.cluster_mock.admin_create_user.return_value = {"principal_ip": as_error} test_util.assert_exception( self, ShellException, "test-message", self.controller.execute, line.split() ) self.cluster_mock.admin_create_user.assert_called_with( "test-user", "pass", [], nodes=["principal"] ) self.view_mock.print_result.assert_not_called() class ManageACLCreateRoleControllerTest(unittest.TestCase): def setUp(self) -> None: patch("lib.live_cluster.live_cluster_root_controller.Cluster").start() self.root_controller = LiveClusterRootController() self.controller = ManageACLCreateRoleController() self.cluster_mock = patch( "lib.live_cluster.manage_controller.ManageACLCreateRoleController.cluster" ).start() self.logger_mock = patch("lib.base_controller.BaseController.logger").start() self.view_mock = patch("lib.base_controller.BaseController.view").start() self.mods = {"like": [], "with": [], "for": [], "line": []} self.cluster_mock.info_build_version.return_value = {"principal": "5.6.0.0"} self.cluster_mock.get_expected_principal.return_value = "principal" self.addCleanup(patch.stopall) def test_logs_error_when_server_does_not_support_quotas(self): log_message = "'read' and 'write' modifiers are not supported on aerospike versions <= 5.5" line = "test-role priv test-priv read 100 write 200" self.cluster_mock.info_build_version.side_effect = [ {"principal": "5.5.0.0"}, {"principal": "5.5.9.9"}, ] self.cluster_mock.get_expected_principal.side_effect = ["principal"] * 2 self.cluster_mock.admin_create_role.side_effect = [ {"principal_ip": ASResponse.OK} ] * 2 for _ in range(2): self.controller.execute(line.split()) self.logger_mock.warning.assert_called_with(log_message) def test_with_only_privilege(self): self.cluster_mock.get_expected_principal.return_value = "principal" self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv test-priv" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["test-priv"], whitelist=[], read_quota=None, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_privilege_with_namespace(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv test-priv ns test-ns" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["test-priv.test-ns"], whitelist=[], read_quota=None, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_privilege_and_namespace_and_set(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv test-priv ns test-ns set test-set" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["test-priv.test-ns.test-set"], whitelist=[], read_quota=None, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_privilege_and_set_logs_error(self): self.controller.execute_help = MagicMock() line = "test-role priv test-priv set test-set" self.controller.execute(line.split()) self.logger_mock.error.assert_called_with( "A set must be accompanied by a namespace." ) def test_with_privilege_and_allowlist(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv test-priv ns test-ns set test-set allow 3.3.3.3 4.4.4.4" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["test-priv.test-ns.test-set"], whitelist=["3.3.3.3", "4.4.4.4"], read_quota=None, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_privilege_and_read_and_write_quota(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv test-priv ns test-ns set test-set read 111 write 222" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["test-priv.test-ns.test-set"], whitelist=[], read_quota=111, write_quota=222, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_privilege_and_allowlist_and_read_and_write_quota(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv test-priv ns test-ns set test-set allow 3.3.3.3 4.4.4.4 read 111 write 222" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["test-priv.test-ns.test-set"], whitelist=["3.3.3.3", "4.4.4.4"], read_quota=111, write_quota=222, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_read_privilege_only(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv read" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["read"], whitelist=[], read_quota=None, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_write_privilege_only(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv write" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["write"], whitelist=[], read_quota=None, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_conflicting_write_privilege_and_write_quota(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv write write 111" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["write"], whitelist=[], read_quota=None, write_quota=111, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_conflicting_read_privilege_and_read_quota(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv read read 111" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["read"], whitelist=[], read_quota=111, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_with_conflicting_read_privilege_and_write_quota(self): self.cluster_mock.admin_create_role.return_value = { "principal_ip": ASResponse.OK } line = "test-role priv read write 111" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["read"], whitelist=[], read_quota=None, write_quota=111, nodes=["principal"], ) self.view_mock.print_result.assert_called_with( "Successfully created role test-role." ) def test_logs_error_when_quotas_are_not_int(self): log_message = "Quotas must be integers." line = "test-role priv write write 100a read 100" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_not_called() self.logger_mock.error.assert_called_with(log_message) self.view_mock.print_result.assert_not_called() line = "test-role priv write write 100 read 100a" self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_not_called() self.logger_mock.error.assert_called_with(log_message) self.view_mock.print_result.assert_not_called() def test_logs_error_when_asprotocol_error_returned(self): as_error = ASProtocolError(ASResponse.ROLE_ALREADY_EXISTS, "test-message") log_message = "test-message : Role already exists." line = "test-role priv sys-admin" self.cluster_mock.admin_create_role.return_value = {"principal_ip": as_error} self.controller.execute(line.split()) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["sys-admin"], whitelist=[], read_quota=None, write_quota=None, nodes=["principal"], ) self.logger_mock.error.assert_called_with(log_message) self.view_mock.print_result.assert_not_called() def test_raises_exception_when_exception_returned(self): as_error = IOError("test-message") line = "test-role priv sys-admin" self.cluster_mock.admin_create_role.return_value = {"principal_ip": as_error} test_util.assert_exception( self, ShellException, "test-message", self.controller.execute, line.split() ) self.cluster_mock.admin_create_role.assert_called_with( "test-role", privileges=["sys-admin"], whitelist=[], read_quota=None, write_quota=None, nodes=["principal"], ) self.view_mock.print_result.assert_not_called() class ManageACLRateLimitControllerTest(unittest.TestCase): def setUp(self) -> None: patch("lib.live_cluster.live_cluster_root_controller.Cluster").start() self.root_controller = LiveClusterRootController() self.controller = ManageACLQuotasRoleController() self.cluster_mock = patch( "lib.live_cluster.manage_controller.ManageACLQuotasRoleController.cluster" ).start() self.logger_mock = patch("lib.base_controller.BaseController.logger").start() self.view_mock = patch("lib.base_controller.BaseController.view").start() self.mods = {"like": [], "with": [], "for": [], "line": []} self.cluster_mock.info_build_version.return_value = {"principal": "5.6.0.0"} self.cluster_mock.get_expected_principal.return_value = "principal" self.addCleanup(patch.stopall) def test_logs_error_when_server_does_not_support_quotas(self): log_message = "'manage quotas' is not supported on aerospike versions <= 5.5" line = "role test-role read 100 write 200" self.cluster_mock.info_build_version.side_effect = [ {"principal": "5.5.0.0"}, {"principal": "5.5.9.9"}, ] self.cluster_mock.get_expected_principal.side_effect = ["principal"] * 2 self.cluster_mock.admin_set_quotas.side_effect = [ {"principal_ip": ASResponse.OK} ] * 2 for _ in range(2): self.controller.execute(line.split()) self.logger_mock.error.assert_called_with(log_message) def test_logs_error_with_read_and_write_not_provided(self): log_message = "'read' or 'write' is required." self.controller.execute(["role", "test-role"]) self.logger_mock.error.assert_called_with(log_message) def test_success_with_read_and_write(self): log_message = "Successfully set quotas for role test-role." line = "role test-role read 100 write 200" self.cluster_mock.admin_set_quotas.return_value = { "principal_ip": ASResponse.OK } self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_called_with( "test-role", read_quota=100, write_quota=200, nodes=["principal"] ) self.view_mock.print_result.assert_called_with(log_message) def test_success_with_just_read(self): log_message = "Successfully set quota for role test-role." line = "role test-role read 100" self.cluster_mock.admin_set_quotas.return_value = { "principal_ip": ASResponse.OK } self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_called_with( "test-role", read_quota=100, write_quota=None, nodes=["principal"] ) self.view_mock.print_result.assert_called_with(log_message) def test_success_with_just_write(self): log_message = "Successfully set quota for role test-role." line = "role test-role write 100" self.cluster_mock.admin_set_quotas.return_value = { "principal_ip": ASResponse.OK } self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_called_with( "test-role", read_quota=None, write_quota=100, nodes=["principal"] ) self.view_mock.print_result.assert_called_with(log_message) def test_correct_call_with_conflicting_read_role_and_read_quota(self): line = "role read read 100" self.cluster_mock.admin_set_quotas.return_value = { "principal_ip": ASResponse.OK } self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_called_with( "read", read_quota=100, write_quota=None, nodes=["principal"] ) def test_correct_call_with_conflicting_write_role_and_write_quota(self): line = "role write write 100" self.cluster_mock.admin_set_quotas.return_value = { "principal_ip": ASResponse.OK } self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_called_with( "write", read_quota=None, write_quota=100, nodes=["principal"] ) def test_correct_call_with_conflicting_write_role_and_read_quota(self): line = "role write read 100" self.cluster_mock.admin_set_quotas.return_value = { "principal_ip": ASResponse.OK } self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_called_with( "write", read_quota=100, write_quota=None, nodes=["principal"] ) def test_logs_error_when_quotas_are_not_int(self): log_message = "Quotas must be integers." line = "role test-role write 100a read 100" self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_not_called() self.logger_mock.error.assert_called_with(log_message) self.view_mock.print_result.assert_not_called() line = "role test-role write 100 read 100a" self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_not_called() self.logger_mock.error.assert_called_with(log_message) self.view_mock.print_result.assert_not_called() def test_logs_error_when_asprotocol_error_returned(self): as_error = ASProtocolError(ASResponse.RATE_QUOTA_EXCEEDED, "test-message") log_message = "test-message : Rate quota exceeded." line = "role test-role write 100 read 100" self.cluster_mock.admin_set_quotas.return_value = {"principal_ip": as_error} self.controller.execute(line.split()) self.cluster_mock.admin_set_quotas.assert_called_with( "test-role", read_quota=100, write_quota=100, nodes=["principal"] ) self.logger_mock.error.assert_called_with(log_message) self.view_mock.print_result.assert_not_called() def test_raises_exception_when_exception_returned(self): as_error = IOError("test-message") line = "role test-role write 100 read 100" self.cluster_mock.admin_set_quotas.return_value = {"principal_ip": as_error} test_util.assert_exception( self, ShellException, "test-message", self.controller.execute, line.split() ) self.cluster_mock.admin_set_quotas.assert_called_with( "test-role", read_quota=100, write_quota=100, nodes=["principal"] ) self.view_mock.print_result.assert_not_called()
37.447236
106
0.649803
2,641
22,356
5.189322
0.056797
0.060197
0.082087
0.084641
0.921343
0.916308
0.896826
0.884276
0.871069
0.858592
0
0.013138
0.24414
22,356
596
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0.185632
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0.147303
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0.072614
false
0.029046
0.014523
0
0.093361
0.056017
0
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0
0
0
0
0
0
0
0
0
6
34346eb8110c90b4aeba3424b6d1fd701f282806
253
py
Python
app/app/admin_views.py
AttiR/Flask-Web-Development
f8d6bf0f16b3858f21df87a3b09ed7dbe5d52636
[ "MIT" ]
null
null
null
app/app/admin_views.py
AttiR/Flask-Web-Development
f8d6bf0f16b3858f21df87a3b09ed7dbe5d52636
[ "MIT" ]
null
null
null
app/app/admin_views.py
AttiR/Flask-Web-Development
f8d6bf0f16b3858f21df87a3b09ed7dbe5d52636
[ "MIT" ]
null
null
null
from app import app from flask import render_template @app.route("/admin/dashboard") def dashboard(): return render_template("admin/dashboard.html") @app.route("/admin/profile") def profile(): return render_template("admin/profile.html")
25.3
50
0.735178
33
253
5.545455
0.393939
0.229508
0.142077
0.273224
0
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0.130435
253
10
51
25.3
0.831818
0
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0.267717
0
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0.25
true
0
0.25
0.25
0.75
0
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1
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1
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0
1
1
0
0
1
1
0
0
6
346e7c5b1137d08aa04255422af6fff0a73b54d3
132
py
Python
defaultindexfile.py
himanshurajora/VChat-Node
b5bca8491248b074607ad222931fa7965823ae09
[ "MIT" ]
2
2021-05-06T15:12:49.000Z
2021-05-06T15:16:45.000Z
defaultindexfile.py
himanshurajora/VChat-Node
b5bca8491248b074607ad222931fa7965823ae09
[ "MIT" ]
null
null
null
defaultindexfile.py
himanshurajora/VChat-Node
b5bca8491248b074607ad222931fa7965823ae09
[ "MIT" ]
null
null
null
print("hello world") print("this is another stuff i am gonna write in it") print("see ya") print("this is where the new file is")
33
54
0.704545
25
132
3.72
0.76
0.193548
0.236559
0
0
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0.174242
132
4
55
33
0.853211
0
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0.692308
0
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true
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6
346f47182c2c06cb08adcdc75ffcb05376a32e22
307
py
Python
paypalpayoutssdk/core/__init__.py
truthiswill/Payouts-Python-SDK
ba04ffafb8165a1b7cdfd5841f08a96dccdd190b
[ "BSD-Source-Code" ]
23
2020-03-02T13:31:55.000Z
2022-03-06T11:25:21.000Z
paypalpayoutssdk/core/__init__.py
truthiswill/Payouts-Python-SDK
ba04ffafb8165a1b7cdfd5841f08a96dccdd190b
[ "BSD-Source-Code" ]
4
2020-09-26T08:40:26.000Z
2022-03-01T17:29:51.000Z
paypalpayoutssdk/core/__init__.py
truthiswill/Payouts-Python-SDK
ba04ffafb8165a1b7cdfd5841f08a96dccdd190b
[ "BSD-Source-Code" ]
21
2020-02-07T10:02:57.000Z
2021-09-09T18:05:02.000Z
from paypalpayoutssdk.core.access_token import * from paypalpayoutssdk.core.access_token_request import * from paypalpayoutssdk.core.refresh_token_request import * from paypalpayoutssdk.core.environment import * from paypalpayoutssdk.core.paypal_http_client import * from paypalpayoutssdk.core.util import *
51.166667
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0.86645
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0.351351
0.46332
0.555985
0.579151
0.57529
0.324324
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0
0.074919
307
6
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51.166667
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3473e1d04173dce320ccfad6577589b952c4e190
37,934
py
Python
python/REDSHIFT_DB_ENCRYPTED/REDSHIFT_DB_ENCRYPTED_test.py
UrfTheManatee/aws-config-rules
fbbfede71bf90f14a8b448447d28b12a68a1f20a
[ "CC0-1.0" ]
null
null
null
python/REDSHIFT_DB_ENCRYPTED/REDSHIFT_DB_ENCRYPTED_test.py
UrfTheManatee/aws-config-rules
fbbfede71bf90f14a8b448447d28b12a68a1f20a
[ "CC0-1.0" ]
null
null
null
python/REDSHIFT_DB_ENCRYPTED/REDSHIFT_DB_ENCRYPTED_test.py
UrfTheManatee/aws-config-rules
fbbfede71bf90f14a8b448447d28b12a68a1f20a
[ "CC0-1.0" ]
null
null
null
# Copyright 2017-2022 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You may # not use this file except in compliance with the License. A copy of the License is located at # # http://aws.amazon.com/apache2.0/ # # or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for # the specific language governing permissions and limitations under the License. import sys import unittest from botocore.exceptions import ClientError try: from unittest.mock import MagicMock except ImportError: from mock import MagicMock ############## # Parameters # ############## # Define the default resource to report to Config Rules DEFAULT_RESOURCE_TYPE = "AWS::Redshift::Cluster" ############# # Main Code # ############# CONFIG_CLIENT_MOCK = MagicMock() STS_CLIENT_MOCK = MagicMock() REDSHIFT_CLIENT_MOCK = MagicMock() PAGINATOR_MOCK = MagicMock() class Boto3Mock: @staticmethod def client(client_name, *args, **kwargs): if client_name == "config": return CONFIG_CLIENT_MOCK if client_name == "sts": return STS_CLIENT_MOCK if client_name == "redshift": return REDSHIFT_CLIENT_MOCK raise Exception("Attempting to create an unknown client") sys.modules["boto3"] = Boto3Mock() RULE = __import__("REDSHIFT_DB_ENCRYPTED") class ComplianceTest(unittest.TestCase): # Unit test for no Cluster is present -- GHERKIN Scenario 1 def test_scenario_1(self): clusters_is_empty = [{"Clusters": []}] REDSHIFT_CLIENT_MOCK.get_paginator.return_value = PAGINATOR_MOCK PAGINATOR_MOCK.paginate.return_value = clusters_is_empty response = RULE.lambda_handler(build_lambda_scheduled_event(), {}) expected_response = [ build_expected_response( "NOT_APPLICABLE", "123456789012", "AWS::::Account", annotation="No clusters found.", ) ] assert_successful_evaluation(self, response, expected_response) # Unit test for if Encrypted to false -- GHERKIN Scenario 2 def test_scenario_2(self): clusters_is_present = [ { "Clusters": [ { "ClusterIdentifier": "redshift-cluster-1", "NodeType": "ra3.4xlarge", "ClusterStatus": "available", "ClusterAvailabilityStatus": "Available", "MasterUsername": "awsuser", "DBName": "dev", "Endpoint": { "Address": "redshift-cluster-1.crmh4vec7kyo.us-east-2.redshift.amazonaws.com", "Port": 5439, }, "ClusterCreateTime": "datetime.datetime(2022, 1, 7, 7, 35, 2, 232000, tzinfo=tzlocal())", "AutomatedSnapshotRetentionPeriod": 1, "ManualSnapshotRetentionPeriod": -1, "ClusterSecurityGroups": [], "VpcSecurityGroups": [ { "VpcSecurityGroupId": "sg-065ea7b9c71408f17", "Status": "active", } ], "ClusterParameterGroups": [ { "ParameterGroupName": "myparametergroup", "ParameterApplyStatus": "in-sync", "ClusterParameterStatusList": [ { "ParameterName": "use_fips_ssl", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "query_group", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "datestyle", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "extra_float_digits", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "search_path", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "statement_timeout", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "wlm_json_configuration", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "require_ssl", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "enable_user_activity_logging", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "max_cursor_result_set_size", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "auto_analyze", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "max_concurrency_scaling_clusters", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "enable_case_sensitive_identifier", "ParameterApplyStatus": "in-sync", }, ], } ], "ClusterSubnetGroupName": "default", "VpcId": "vpc-0c1fbf2379152d7f4", "AvailabilityZone": "us-east-2c", "PreferredMaintenanceWindow": "wed:08:30-wed:09:00", "PendingModifiedValues": {}, "ClusterVersion": "1.0", "AllowVersionUpgrade": True, "NumberOfNodes": 2, "PubliclyAccessible": False, "Encrypted": False, "ClusterPublicKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCanvmYtbNIGA5PiAY4rF" "6ppg1wR3QY0f860EPUpRSaoc07UHOV4S2QLk21m5KEQm15rTE6dxVWrkXBzNabgdAsuiAo+Abur3D3y8xSZ" "STMpD4e0Kn3UQ9nKw/2WWKWslNjKyzsBRSHv0jdVgg7KjtxoKAYNu/PbH4WCv2bcX+2nz8jxxDg2IOS/A6I3D" "3pha9Q/FX0MMPYDKwKWw4TZ83PsZQvGWkW37TKaiGHFUpRfpuL/W8gHVD0ZJo8cK+WBxQsG5CujHlyifMQPBG" "mKiFW8IeHS2evKzPAqIUlUTUA/t8t7EeCw5rnby8raUj7qWbeGqJ55d9CjcndHgaY5TZV " "Amazon-Redshift\n", "ClusterNodes": [ { "NodeRole": "LEADER", "PrivateIPAddress": "172.31.34.184", "PublicIPAddress": "3.133.24.130", }, { "NodeRole": "COMPUTE-0", "PrivateIPAddress": "172.31.35.209", "PublicIPAddress": "18.220.99.27", }, { "NodeRole": "COMPUTE-1", "PrivateIPAddress": "172.31.33.222", "PublicIPAddress": "18.224.176.198", }, ], "ClusterRevisionNumber": "35480", "Tags": [], "EnhancedVpcRouting": False, "IamRoles": [ { "IamRoleArn": "arn:aws:iam::529010877102:role/service-role/" "AmazonRedshift-CommandsAccessRole-20211209T063611", "ApplyStatus": "in-sync", } ], "MaintenanceTrackName": "current", "ElasticResizeNumberOfNodeOptions": "[3,4,5,6,7,8]", "DeferredMaintenanceWindows": [], "NextMaintenanceWindowStartTime": "datetime.datetime(2022, 2, 16, 8, 30, tzinfo=tzlocal())", "AvailabilityZoneRelocationStatus": "disabled", "ClusterNamespaceArn": "arn:aws:redshift:us-east-2:529010877102:namespace:95b46b68-0afa-4ca9-" "baf2-b6bf714431bc", "TotalStorageCapacityInMegaBytes": 256000000, "AquaConfiguration": { "AquaStatus": "disabled", "AquaConfigurationStatus": "auto", }, } ] } ] REDSHIFT_CLIENT_MOCK.get_paginator.return_value = PAGINATOR_MOCK PAGINATOR_MOCK.paginate.return_value = clusters_is_present parameters = { "Parameters": [ { "ParameterName": "auto_analyze", "ParameterValue": "true", "Description": "Use auto analyze", "Source": "engine-default", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "datestyle", "ParameterValue": "ISO, MDY", "Description": "Sets the display format for date and time values.", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "enable_case_sensitive_identifier", "ParameterValue": "true", "Description": "Preserve case sensitivity for database identifiers such as table or column names in parser", "Source": "user", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "enable_user_activity_logging", "ParameterValue": "false", "Description": "parameter for audit logging purpose", "Source": "user", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "extra_float_digits", "ParameterValue": "0", "Description": "Sets the number of digits displayed for floating-point values", "Source": "engine-default", "DataType": "integer", "AllowedValues": "-15-2", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "max_concurrency_scaling_clusters", "ParameterValue": "1", "Description": "The maximum concurrency scaling clusters can be used.", "Source": "engine-default", "DataType": "integer", "AllowedValues": "0-10", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "max_cursor_result_set_size", "ParameterValue": "default", "Description": "Sets the max cursor result set size", "Source": "engine-default", "DataType": "integer", "AllowedValues": "0-14400000", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "query_group", "ParameterValue": "default", "Description": "This parameter applies a user-defined label to a group of queries that are run during the " "same session..", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "require_ssl", "ParameterValue": "false", "Description": "require ssl for all databaseconnections", "Source": "user", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "search_path", "ParameterValue": "$user, public", "Description": "Sets the schema search order for names that are not schema-qualified.", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "statement_timeout", "ParameterValue": "0", "Description": "Aborts any statement that takes over the specified number of milliseconds.", "Source": "engine-default", "DataType": "integer", "AllowedValues": "0,100-2147483647", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "use_fips_ssl", "ParameterValue": "false", "Description": "Use fips ssl library", "Source": "engine-default", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "wlm_json_configuration", "ParameterValue": '[{"auto_wlm":true}]', "Description": "wlm json configuration", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, ], "ResponseMetadata": { "RequestId": "839a0ffc-1ea6-4700-94a2-76ead2a7cb5e", "HTTPStatusCode": 200, "HTTPHeaders": { "x-amzn-requestid": "839a0ffc-1ea6-4700-94a2-76ead2a7cb5e", "content-type": "text/xml", "content-length": "5806", "vary": "accept-encoding", "date": "Tue, 15 Feb 2022 12:08:59 GMT", }, "RetryAttempts": 0, }, } REDSHIFT_CLIENT_MOCK.describe_cluster_parameters = MagicMock( return_value=parameters ) response = RULE.lambda_handler(build_lambda_scheduled_event(), {}) expected_response = [ build_expected_response( "NON_COMPLIANT", "redshift-cluster-1", annotation="The database cluster is not encrypted.", ) ] assert_successful_evaluation(self, response, expected_response) # Unit test for if Encrypted to true -- GHERKIN Scenario 3 def test_scenario_3(self): clusters_is_present = [ { "Clusters": [ { "ClusterIdentifier": "redshift-cluster-1", "NodeType": "ra3.4xlarge", "ClusterStatus": "available", "ClusterAvailabilityStatus": "Available", "MasterUsername": "awsuser", "DBName": "dev", "Endpoint": { "Address": "redshift-cluster-1.crmh4vec7kyo.us-east-2.redshift.amazonaws.com", "Port": 5439, }, "ClusterCreateTime": "datetime.datetime(2022, 1, 7, 7, 35, 2, 232000, tzinfo=tzlocal())", "AutomatedSnapshotRetentionPeriod": 1, "ManualSnapshotRetentionPeriod": -1, "ClusterSecurityGroups": [], "VpcSecurityGroups": [ { "VpcSecurityGroupId": "sg-065ea7b9c71408f17", "Status": "active", } ], "ClusterParameterGroups": [ { "ParameterGroupName": "myparametergroup", "ParameterApplyStatus": "in-sync", "ClusterParameterStatusList": [ { "ParameterName": "use_fips_ssl", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "query_group", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "datestyle", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "extra_float_digits", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "search_path", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "statement_timeout", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "wlm_json_configuration", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "require_ssl", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "enable_user_activity_logging", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "max_cursor_result_set_size", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "auto_analyze", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "max_concurrency_scaling_clusters", "ParameterApplyStatus": "in-sync", }, { "ParameterName": "enable_case_sensitive_identifier", "ParameterApplyStatus": "in-sync", }, ], } ], "ClusterSubnetGroupName": "default", "VpcId": "vpc-0c1fbf2379152d7f4", "AvailabilityZone": "us-east-2c", "PreferredMaintenanceWindow": "wed:08:30-wed:09:00", "PendingModifiedValues": {}, "ClusterVersion": "1.0", "AllowVersionUpgrade": True, "NumberOfNodes": 2, "PubliclyAccessible": False, "Encrypted": True, "ClusterPublicKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCanvmYtbNIGA5PiAY4rF" "6ppg1wR3QY0f860EPUpRSaoc07UHOV4S2QLk21m5KEQm15rTE6dxVWrkXBzNabgdAsuiAo+Abur3D3y8xSZ" "STMpD4e0Kn3UQ9nKw/2WWKWslNjKyzsBRSHv0jdVgg7KjtxoKAYNu/PbH4WCv2bcX+2nz8jxxDg2IOS/A6I3D" "3pha9Q/FX0MMPYDKwKWw4TZ83PsZQvGWkW37TKaiGHFUpRfpuL/W8gHVD0ZJo8cK+WBxQsG5CujHlyifMQPBG" "mKiFW8IeHS2evKzPAqIUlUTUA/t8t7EeCw5rnby8raUj7qWbeGqJ55d9CjcndHgaY5TZV " "Amazon-Redshift\n", "ClusterNodes": [ { "NodeRole": "LEADER", "PrivateIPAddress": "172.31.34.184", "PublicIPAddress": "3.133.24.130", }, { "NodeRole": "COMPUTE-0", "PrivateIPAddress": "172.31.35.209", "PublicIPAddress": "18.220.99.27", }, { "NodeRole": "COMPUTE-1", "PrivateIPAddress": "172.31.33.222", "PublicIPAddress": "18.224.176.198", }, ], "ClusterRevisionNumber": "35480", "Tags": [], "EnhancedVpcRouting": False, "IamRoles": [ { "IamRoleArn": "arn:aws:iam::529010877102:role/service-role/" "AmazonRedshift-CommandsAccessRole-20211209T063611", "ApplyStatus": "in-sync", } ], "MaintenanceTrackName": "current", "ElasticResizeNumberOfNodeOptions": "[3,4,5,6,7,8]", "DeferredMaintenanceWindows": [], "NextMaintenanceWindowStartTime": "datetime.datetime(2022, 2, 16, 8, 30, tzinfo=tzlocal())", "AvailabilityZoneRelocationStatus": "disabled", "ClusterNamespaceArn": "arn:aws:redshift:us-east-2:529010877102:namespace:95b46b68-0afa-4ca9-" "baf2-b6bf714431bc", "TotalStorageCapacityInMegaBytes": 256000000, "AquaConfiguration": { "AquaStatus": "disabled", "AquaConfigurationStatus": "auto", }, } ] } ] REDSHIFT_CLIENT_MOCK.get_paginator.return_value = PAGINATOR_MOCK PAGINATOR_MOCK.paginate.return_value = clusters_is_present parameters = { "Parameters": [ { "ParameterName": "auto_analyze", "ParameterValue": "true", "Description": "Use auto analyze", "Source": "engine-default", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "datestyle", "ParameterValue": "ISO, MDY", "Description": "Sets the display format for date and time values.", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "enable_case_sensitive_identifier", "ParameterValue": "true", "Description": "Preserve case sensitivity for database identifiers such as table or column names in parser", "Source": "user", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "enable_user_activity_logging", "ParameterValue": "false", "Description": "parameter for audit logging purpose", "Source": "user", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "extra_float_digits", "ParameterValue": "0", "Description": "Sets the number of digits displayed for floating-point values", "Source": "engine-default", "DataType": "integer", "AllowedValues": "-15-2", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "max_concurrency_scaling_clusters", "ParameterValue": "1", "Description": "The maximum concurrency scaling clusters can be used.", "Source": "engine-default", "DataType": "integer", "AllowedValues": "0-10", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "max_cursor_result_set_size", "ParameterValue": "default", "Description": "Sets the max cursor result set size", "Source": "engine-default", "DataType": "integer", "AllowedValues": "0-14400000", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "query_group", "ParameterValue": "default", "Description": "This parameter applies a user-defined label to a group of queries that are run during the " "same session..", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "require_ssl", "ParameterValue": "false", "Description": "require ssl for all databaseconnections", "Source": "user", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "search_path", "ParameterValue": "$user, public", "Description": "Sets the schema search order for names that are not schema-qualified.", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "statement_timeout", "ParameterValue": "0", "Description": "Aborts any statement that takes over the specified number of milliseconds.", "Source": "engine-default", "DataType": "integer", "AllowedValues": "0,100-2147483647", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "use_fips_ssl", "ParameterValue": "false", "Description": "Use fips ssl library", "Source": "engine-default", "DataType": "boolean", "AllowedValues": "true,false", "ApplyType": "static", "IsModifiable": True, }, { "ParameterName": "wlm_json_configuration", "ParameterValue": '[{"auto_wlm":true}]', "Description": "wlm json configuration", "Source": "engine-default", "DataType": "string", "ApplyType": "static", "IsModifiable": True, }, ], "ResponseMetadata": { "RequestId": "839a0ffc-1ea6-4700-94a2-76ead2a7cb5e", "HTTPStatusCode": 200, "HTTPHeaders": { "x-amzn-requestid": "839a0ffc-1ea6-4700-94a2-76ead2a7cb5e", "content-type": "text/xml", "content-length": "5806", "vary": "accept-encoding", "date": "Tue, 15 Feb 2022 12:08:59 GMT", }, "RetryAttempts": 0, }, } REDSHIFT_CLIENT_MOCK.describe_cluster_parameters = MagicMock( return_value=parameters ) response = RULE.lambda_handler(build_lambda_scheduled_event(), {}) expected_response = [ build_expected_response( "COMPLIANT", "redshift-cluster-1", ) ] assert_successful_evaluation(self, response, expected_response) #################### # Helper Functions # #################### def build_lambda_configurationchange_event(invoking_event, rule_parameters=None): event_to_return = { "configRuleName": "myrule", "executionRoleArn": "roleArn", "eventLeftScope": False, "invokingEvent": invoking_event, "accountId": "123456789012", "configRuleArn": "arn:aws:config:us-east-1:123456789012:config-rule/config-rule-8fngan", "resultToken": "token", } if rule_parameters: event_to_return["ruleParameters"] = rule_parameters return event_to_return def build_lambda_scheduled_event(rule_parameters=None): invoking_event = '{"messageType":"ScheduledNotification","notificationCreationTime":"2017-12-23T22:11:18.158Z"}' event_to_return = { "configRuleName": "myrule", "executionRoleArn": "roleArn", "eventLeftScope": False, "invokingEvent": invoking_event, "accountId": "123456789012", "configRuleArn": "arn:aws:config:us-east-1:123456789012:config-rule/config-rule-8fngan", "resultToken": "token", } if rule_parameters: event_to_return["ruleParameters"] = rule_parameters return event_to_return def build_expected_response( compliance_type, compliance_resource_id, compliance_resource_type=DEFAULT_RESOURCE_TYPE, annotation=None, ): if not annotation: return { "ComplianceType": compliance_type, "ComplianceResourceId": compliance_resource_id, "ComplianceResourceType": compliance_resource_type, } return { "ComplianceType": compliance_type, "ComplianceResourceId": compliance_resource_id, "ComplianceResourceType": compliance_resource_type, "Annotation": annotation, } def assert_successful_evaluation( test_class, response, resp_expected, evaluations_count=1 ): if isinstance(response, dict): test_class.assertEquals( resp_expected["ComplianceResourceType"], response["ComplianceResourceType"] ) test_class.assertEquals( resp_expected["ComplianceResourceId"], response["ComplianceResourceId"] ) test_class.assertEquals( resp_expected["ComplianceType"], response["ComplianceType"] ) test_class.assertTrue(response["OrderingTimestamp"]) if "Annotation" in resp_expected or "Annotation" in response: test_class.assertEquals(resp_expected["Annotation"], response["Annotation"]) elif isinstance(response, list): test_class.assertEquals(evaluations_count, len(response)) for i, response_expected in enumerate(resp_expected): test_class.assertEquals( response_expected["ComplianceResourceType"], response[i]["ComplianceResourceType"], ) test_class.assertEquals( response_expected["ComplianceResourceId"], response[i]["ComplianceResourceId"], ) test_class.assertEquals( response_expected["ComplianceType"], response[i]["ComplianceType"] ) test_class.assertTrue(response[i]["OrderingTimestamp"]) if "Annotation" in response_expected or "Annotation" in response[i]: test_class.assertEquals( response_expected["Annotation"], response[i]["Annotation"] ) def assert_customer_error_response( test_class, response, customer_error_code=None, customer_error_message=None ): if customer_error_code: test_class.assertEqual(customer_error_code, response["customerErrorCode"]) if customer_error_message: test_class.assertEqual(customer_error_message, response["customerErrorMessage"]) test_class.assertTrue(response["customerErrorCode"]) test_class.assertTrue(response["customerErrorMessage"]) if "internalErrorMessage" in response: test_class.assertTrue(response["internalErrorMessage"]) if "internalErrorDetails" in response: test_class.assertTrue(response["internalErrorDetails"]) def sts_mock(): assume_role_response = { "Credentials": { "AccessKeyId": "string", "SecretAccessKey": "string", "SessionToken": "string", } } STS_CLIENT_MOCK.reset_mock(return_value=True) STS_CLIENT_MOCK.assume_role = MagicMock(return_value=assume_role_response) ################## # Common Testing # ################## class TestStsErrors(unittest.TestCase): def test_sts_unknown_error(self): RULE.ASSUME_ROLE_MODE = True STS_CLIENT_MOCK.assume_role = MagicMock( side_effect=ClientError( {"Error": {"Code": "unknown-code", "Message": "unknown-message"}}, "operation", ) ) response = RULE.lambda_handler(build_lambda_configurationchange_event("{}"), {}) assert_customer_error_response(self, response, "InternalError", "InternalError") def test_sts_access_denied(self): RULE.ASSUME_ROLE_MODE = True STS_CLIENT_MOCK.assume_role = MagicMock( side_effect=ClientError( {"Error": {"Code": "AccessDenied", "Message": "access-denied"}}, "operation", ) ) response = RULE.lambda_handler(build_lambda_configurationchange_event("{}"), {}) assert_customer_error_response( self, response, "AccessDenied", "AWS Config does not have permission to assume the IAM role.", ) if __name__ == "__main__": unittest.main()
45.267303
128
0.442242
2,281
37,934
7.199036
0.207804
0.010962
0.044333
0.049083
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0.779307
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6
cad462b46d744a7bb97f4a59e074561b900bafaa
169
py
Python
app/app/calc.py
josekang/recipe-app-api
059e5b048d09943ccb11442d584d83a5f4e036df
[ "MIT" ]
null
null
null
app/app/calc.py
josekang/recipe-app-api
059e5b048d09943ccb11442d584d83a5f4e036df
[ "MIT" ]
null
null
null
app/app/calc.py
josekang/recipe-app-api
059e5b048d09943ccb11442d584d83a5f4e036df
[ "MIT" ]
null
null
null
def add(x, y): """ Add two numbers and return their sum""" return x+y def subtract(x, y): """ Subtract to numbers and return their results""" return x-y
24.142857
55
0.621302
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3.75
0.464286
0.07619
0.304762
0.4
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0.248521
169
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24.142857
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6
1b6f15802051aabf0f363bfe4453b067eb32ef94
2,294
py
Python
epytope/Data/pssms/smmpmbec/mat/A_26_03_9.py
christopher-mohr/epytope
8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd
[ "BSD-3-Clause" ]
7
2021-02-01T18:11:28.000Z
2022-01-31T19:14:07.000Z
epytope/Data/pssms/smmpmbec/mat/A_26_03_9.py
christopher-mohr/epytope
8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd
[ "BSD-3-Clause" ]
22
2021-01-02T15:25:23.000Z
2022-03-14T11:32:53.000Z
epytope/Data/pssms/smmpmbec/mat/A_26_03_9.py
christopher-mohr/epytope
8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd
[ "BSD-3-Clause" ]
4
2021-05-28T08:50:38.000Z
2022-03-14T11:45:32.000Z
A_26_03_9 = {0: {'A': 0.049, 'C': -0.208, 'E': -0.569, 'D': -0.387, 'G': 0.127, 'F': -0.129, 'I': 0.311, 'H': -0.25, 'K': 0.62, 'M': 0.204, 'L': 0.206, 'N': -0.038, 'Q': 0.063, 'P': 0.176, 'S': -0.032, 'R': 0.67, 'T': -0.177, 'W': -0.351, 'V': 0.02, 'Y': -0.305}, 1: {'A': -0.372, 'C': 0.11, 'E': 0.235, 'D': 0.145, 'G': 0.022, 'F': 0.207, 'I': -0.5, 'H': 0.442, 'K': 0.22, 'M': 0.223, 'L': -0.13, 'N': 0.135, 'Q': 0.136, 'P': -0.076, 'S': -0.174, 'R': 0.556, 'T': -0.688, 'W': 0.115, 'V': -0.854, 'Y': 0.247}, 2: {'A': -0.071, 'C': -0.005, 'E': 0.183, 'D': 0.2, 'G': 0.18, 'F': 0.111, 'I': -0.484, 'H': 0.036, 'K': 0.088, 'M': 0.015, 'L': 0.088, 'N': -0.021, 'Q': 0.153, 'P': 0.019, 'S': 0.027, 'R': 0.069, 'T': -0.037, 'W': -0.137, 'V': -0.281, 'Y': -0.132}, 3: {'A': -0.189, 'C': -0.129, 'E': -0.233, 'D': -0.091, 'G': -0.141, 'F': 0.189, 'I': 0.405, 'H': 0.025, 'K': 0.202, 'M': 0.083, 'L': 0.19, 'N': -0.053, 'Q': -0.179, 'P': 0.01, 'S': -0.142, 'R': -0.008, 'T': -0.082, 'W': 0.021, 'V': 0.149, 'Y': -0.028}, 4: {'A': -0.037, 'C': -0.047, 'E': 0.011, 'D': -0.168, 'G': -0.015, 'F': -0.108, 'I': 0.229, 'H': -0.119, 'K': 0.005, 'M': 0.16, 'L': 0.152, 'N': 0.083, 'Q': 0.118, 'P': -0.077, 'S': 0.124, 'R': -0.115, 'T': 0.004, 'W': -0.074, 'V': 0.169, 'Y': -0.296}, 5: {'A': 0.052, 'C': 0.035, 'E': 0.125, 'D': -0.028, 'G': -0.097, 'F': -0.337, 'I': -0.016, 'H': 0.104, 'K': 0.234, 'M': -0.06, 'L': -0.077, 'N': -0.015, 'Q': 0.178, 'P': 0.184, 'S': 0.116, 'R': 0.163, 'T': -0.06, 'W': -0.266, 'V': -0.026, 'Y': -0.209}, 6: {'A': -0.232, 'C': 0.01, 'E': 0.078, 'D': 0.113, 'G': -0.313, 'F': -0.064, 'I': -0.08, 'H': 0.141, 'K': 0.096, 'M': 0.021, 'L': -0.005, 'N': 0.01, 'Q': 0.045, 'P': -0.015, 'S': -0.155, 'R': -0.018, 'T': 0.017, 'W': 0.19, 'V': 0.097, 'Y': 0.064}, 7: {'A': -0.238, 'C': -0.005, 'E': 0.152, 'D': 0.201, 'G': -0.377, 'F': -0.115, 'I': 0.171, 'H': 0.008, 'K': 0.084, 'M': 0.064, 'L': 0.015, 'N': -0.251, 'Q': 0.039, 'P': -0.321, 'S': -0.091, 'R': 0.3, 'T': 0.027, 'W': 0.097, 'V': 0.082, 'Y': 0.157}, 8: {'A': 0.25, 'C': 0.076, 'E': 0.233, 'D': 0.172, 'G': 0.166, 'F': -0.194, 'I': 0.014, 'H': -0.178, 'K': 0.203, 'M': -0.759, 'L': -0.11, 'N': -0.044, 'Q': 0.075, 'P': 0.459, 'S': 0.107, 'R': -0.419, 'T': 0.289, 'W': -0.154, 'V': 0.201, 'Y': -0.389}, -1: {'con': 4.43222}}
2,294
2,294
0.393636
557
2,294
1.615799
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0.02
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0.013333
0.031111
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0.162598
2,294
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2,294
2,294
0.095783
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0.079739
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0
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6
1b9f6f5d303b9ad2ece7d73d6e474d7eef30db56
23,567
py
Python
tests/test_atokaconn.py
openpolis/atokaconn
071aebfc408e4f661a9cd98ea91daf9e01b87bad
[ "MIT" ]
1
2021-08-13T10:36:34.000Z
2021-08-13T10:36:34.000Z
tests/test_atokaconn.py
openpolis/atokaconn
071aebfc408e4f661a9cd98ea91daf9e01b87bad
[ "MIT" ]
null
null
null
tests/test_atokaconn.py
openpolis/atokaconn
071aebfc408e4f661a9cd98ea91daf9e01b87bad
[ "MIT" ]
null
null
null
import logging from requests.exceptions import Timeout from atokaconn import __version__, AtokaObjectDoesNotExist, AtokaResponseError, AtokaMultipleObjectsReturned, \ AtokaException, AtokaTimeoutException from atokaconn import AtokaConn from faker import Factory from unittest import TestCase from unittest.mock import patch from tests.factories import AreaFactory, PersonFactory from tests.mocked_responses import get_void_response, get_person_ok, get_person_multiple, \ get_companies_economics, get_companies def test_version(): assert __version__ == '0.1.6' faker = Factory.create("it_IT") # a factory to create fake data for tests logger = logging.getLogger(__name__) class MockResponse: """class that mocks requests' response (json method) """ def __init__(self, json_data, status_code, ok, reason=None): self.json_data = json_data self.status_code = status_code self.ok = ok self.reason = reason def json(self): return self.json_data class MockBrokenJsonResponse: """class that mocks requests' response with a broken json """ def __init__(self, json_data, status_code, ok, reason=None): self.json_data = json_data self.status_code = status_code self.ok = ok self.reason = reason def json(self): raise Exception("Json is broken") class ConnectionsTestCase(TestCase): @classmethod def setUpClass(cls): super(ConnectionsTestCase, cls).setUpClass() setattr(cls, 'mock_get_patcher', patch('requests.Session.get')) setattr(cls, 'mock_post_patcher', patch('requests.Session.post')) cls.mock_get = getattr(cls, 'mock_get_patcher').start() cls.mock_post = getattr(cls, 'mock_post_patcher').start() @classmethod def tearDownClass(cls): getattr(cls, 'mock_get_patcher').stop() getattr(cls, 'mock_post_patcher').stop() super(ConnectionsTestCase, cls).tearDownClass() class ATOKAConnTest(ConnectionsTestCase): def test_no_key_failure(self): with self.assertRaises(AtokaException): _ = AtokaConn() def test_get_person_from_tax_id_ok(self): """Test get_person_from_tax_id returns the correct result """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_person_ok(tax_id=tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_p = atoka_conn.get_person_from_tax_id(tax_id) self.assertEqual(atoka_p['base']['taxId'], tax_id) def test_get_person_from_tax_id_broken_json_failure(self): """Test get_person_from_tax_id fails when json is broken """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockBrokenJsonResponse( get_person_ok(tax_id=tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(Exception): _ = atoka_conn.get_person_from_tax_id(tax_id) def test_get_person_from_tax_id_timeout_failure(self): """Test get_person_from_tax_id fails when connection fails """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_person_ok(tax_id=tax_id), status_code=200, ok=True ) self.mock_get.side_effect = Timeout() # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaTimeoutException): _ = atoka_conn.get_person_from_tax_id(tax_id) self.mock_get.side_effect = None def test_search_person_ok(self): """Test get_person_from_tax_id returns the correct result """ parent_area = AreaFactory(name='Lazio') area = AreaFactory(name='Roma', parent=parent_area) person = PersonFactory.create( family_name=faker.last_name_male(), given_name=faker.first_name_male(), birth_date=faker.date(pattern="%Y-%m-%d", end_datetime="-47y"), birth_location_area=area ) tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_person_ok(tax_id=tax_id, search_params={ "family_name": person.family_name, "given_name": person.given_name, "birth_date": person.birth_date, }), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_p = atoka_conn.search_person(person) self.assertEqual(atoka_p['name'], person.name) self.assertEqual(atoka_p['base']['taxId'], tax_id) def test_search_person_timeout_failure(self): """Test timeout during search_person invocations """ parent_area = AreaFactory(name='Lazio') area = AreaFactory(name='Roma', parent=parent_area) person = PersonFactory.create( family_name=faker.last_name_male(), given_name=faker.first_name_male(), birth_date=faker.date(pattern="%Y-%m-%d", end_datetime="-47y"), birth_location_area=area ) tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_person_ok(tax_id=tax_id, search_params={ "family_name": person.family_name, "given_name": person.given_name, "birth_date": person.birth_date, }), status_code=200, ok=True ) self.mock_get.side_effect = Timeout() # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaTimeoutException): _ = atoka_conn.search_person(person) self.mock_get.side_effect = None def test_get_person_from_tax_id_fails_doesnotexist(self): """Test get_person_from_tax_id returns void result """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_void_response(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaObjectDoesNotExist): atoka_conn.get_person_from_tax_id(tax_id) def test_get_person_from_tax_id_fails_notok(self): """Test get_person_from_tax_id returns not ok """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_void_response(), status_code=404, ok=False, reason="Requested URI was not found here", ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaResponseError): atoka_conn.get_person_from_tax_id(tax_id) def test_get_person_from_tax_id_fails_multiple(self): """Test get_person_from_tax_id returns void result """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_person_multiple(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaMultipleObjectsReturned): atoka_conn.get_person_from_tax_id(tax_id) def test_search_person_fails_doesnotexist(self): """Test search_person returns a not found result """ parent_area = AreaFactory(name='Lazio') area = AreaFactory(name='Roma', parent=parent_area) person = PersonFactory.create( family_name=faker.last_name_male(), given_name=faker.first_name_male(), birth_date=faker.date(pattern="%Y-%m-%d", end_datetime="-47y"), birth_location_area=area ) person.tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_void_response(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaObjectDoesNotExist): atoka_conn.search_person(person) def test_search_person_fails_notok(self): """Test search_person returns not ok """ parent_area = AreaFactory(name='Lazio') area = AreaFactory(name='Roma', parent=parent_area) person = PersonFactory.create( family_name=faker.last_name_male(), given_name=faker.first_name_male(), birth_date=faker.date(pattern="%Y-%m-%d", end_datetime="-47y"), birth_location_area=area ) person.tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_void_response(), status_code=404, ok=False, reason="Requested URI was not found here", ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaResponseError): atoka_conn.search_person(person) def test_search_person_fails_multiple(self): """Test search_person returns multiple results """ parent_area = AreaFactory(name='Lazio') area = AreaFactory(name='Roma', parent=parent_area) person = PersonFactory.create( family_name=faker.last_name_male(), given_name=faker.first_name_male(), birth_date=faker.date(pattern="%Y-%m-%d", end_datetime="-47y"), birth_location_area=area ) person.tax_id = faker.ssn() # mock atoka request using tax_id self.mock_get.return_value = MockResponse( get_person_multiple(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaMultipleObjectsReturned): atoka_conn.search_person(person) def test_get_companies_from_tax_id_ok(self): """Test getcompany_from_tax_id returns one result """ tax_id = "80002270660" # mock atoka request using tax_id # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing', logger=logger) atoka_p = atoka_conn.get_companies_from_tax_ids(tax_id.split(","), packages='base,shares', active="true") self.assertEqual(len(atoka_p), 1) self.assertEqual(atoka_p[0]['base']['taxId'], tax_id) self.assertEqual('shares' in atoka_p[0], True) def test_get_companies_from_tax_id_ok_extend_response(self): """Test get_companies_from_tax_id returns more than 50 results """ tax_id = "01234567890" # mock atoka request using tax_id # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing', logger=logger) atoka_p = atoka_conn.get_companies_from_tax_ids(tax_id.split(","), packages='base,shares', active="true") self.assertGreaterEqual(len(atoka_p), 50) def test_get_companies_from_tax_id_multiple_results(self): """Test getcompany_from_tax_id returns more than one result """ tax_id = "02438750586" # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_p = atoka_conn.get_companies_from_tax_ids(tax_id.split(","), packages='base,shares', active="true") self.assertEqual(len(atoka_p), 2) self.assertEqual(atoka_p[0]['base']['taxId'], tax_id) self.assertEqual(atoka_p[1]['base']['taxId'], tax_id) self.assertEqual('shares' in atoka_p[0], True) self.assertEqual('shares' in atoka_p[1], False) def test_get_companies_from_tax_id_returns_empty_if_missing(self): """Test get_person_from_tax_id returns void result """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_void_response(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') items = atoka_conn.get_companies_from_tax_ids(tax_id, packages='base,shares', active="true") self.assertEqual(items, []) def test_get_companies_from_tax_id_empty_if_post_response_notok(self): """Test get_companies_from_tax_id returns empty list when response is not ok """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_void_response(), status_code=404, ok=False, reason="Requested URI was not found here", ) # do the test atoka_conn = AtokaConn(key='testing') items = atoka_conn.get_companies_from_tax_ids(tax_id, packages='base,shares', active="true") self.assertEqual(items, []) def test_get_companies_from_tax_id_empty_if_post_request_timeouts(self): """Test get_companies_from_tax_id returns empty list when post reuest timeouts """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_void_response(), status_code=404, ok=False, reason="Requested URI was not found here", ) # do the test self.mock_post.side_effect = Timeout() atoka_conn = AtokaConn(key='testing') items = atoka_conn.get_companies_from_tax_ids(tax_id, packages='base,shares', active="true") self.assertEqual(items, []) self.mock_post.side_effect = None def test_get_companies_from_tax_id_empty_if_post_request_response_void(self): """Test get_companies_from_tax_id returns empty list when post reuest returns a void response """ tax_id = faker.ssn() # mock atoka request using tax_id self.mock_post.return_value = None # do the test atoka_conn = AtokaConn(key='testing') items = atoka_conn.get_companies_from_tax_ids(tax_id, packages='base,shares', active="true") self.assertEqual(items, []) def test_get_items_from_ids_fails_wrong_ids_field_name(self): """Test get_items_from_ids fails when an unknown ids_field_name is passed """ tax_id = "02438750586" # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaException): _ = atoka_conn.get_items_from_ids( tax_id.split(","), item_type='companies', ids_field_name='cfs', batch_size=50, packages='base,shares', active="true" ) def test_get_items_from_ids_fails_wrong_item_type(self): """Test get_items_from_ids fails when an unknown iem_type is passed """ tax_id = "02438750586" # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaException): _ = atoka_conn.get_items_from_ids( tax_id.split(","), item_type='smurfs', ids_field_name='taxIds', batch_size=50, packages='base,shares', active="true" ) def test_get_items_from_ids_fails_wrong_batch_size(self): """Test get_items_from_ids fails when an batch_size out of range is passed """ tax_id = "02438750586" # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') with self.assertRaises(AtokaException): _ = atoka_conn.get_items_from_ids( tax_id.split(","), item_type='companies', ids_field_name='taxIds', batch_size=100, packages='base,shares', active="true" ) def test_get_items_from_ids_returns_empty_list_if_empty_ids(self): """Test get_items_from_ids returns and empy items list when an empty ids list is passed """ # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_void_response(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') ids = atoka_conn.get_items_from_ids( [], item_type='companies', ids_field_name='taxIds', batch_size=50, packages='base,shares', active="true" ) self.assertEqual(len(ids), 0) def test_get_items_from_ids_ok_with_chunks_and_logger(self): """Test get_items_from_ids is ok when requests are grouped in chunks (batch_size=1) """ tax_id = "02438750586" # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing', max_batch_file_lines=1, logger=logger) items = atoka_conn.get_items_from_ids( ["02438750586", "01234567890"], item_type='companies', ids_field_name='taxIds', batch_size=1, packages='base,shares', active="true" ) self.assertEqual(len(items), 2) self.assertEqual(items[0]['base']['taxId'], tax_id) def test_get_companies_economics_ok(self): """Test get_companies_from_tax_ids with economics details has the correct information """ tax_ids = ['02241890223', '09988761004'] # mock atoka request using tax_id # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies_economics(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_resp = atoka_conn.get_companies_from_tax_ids(tax_ids, packages='base,economics', active="true") self.assertEqual(len(atoka_resp), 2) c = atoka_resp[0] self.assertEqual(c['base']['taxId'], tax_ids[0]) self.assertEqual('economics' in c, True) ce = c['economics'] self.assertEqual('balanceSheets' in ce, True) self.assertEqual(len(ce['balanceSheets']) > 1, True) self.assertEqual('employees' in ce, True) self.assertEqual(len(ce['employees']) > 1, True) def test_get_companies_from_atoka_ids_ok(self): """Test test get_companies_from_atoka_ids returns one result The test only needs to test the correct wrapping of get_items_from_ids, so it mocks the usual response, not a correct one """ tax_id = "80002270660" # mock atoka request using tax_id # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_p = atoka_conn.get_companies_from_atoka_ids(tax_id.split(","), packages='base,shares', active="true") self.assertEqual(len(atoka_p), 1) def test_get_people_from_tax_ids_ok(self): """Test test get_people_from_tax_ids returns one result The test only needs to test the correct wrapping of get_items_from_ids, so it mocks the usual response, not a correct one """ tax_id = "80002270660" # mock atoka request using tax_id # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_p = atoka_conn.get_people_from_tax_ids(tax_id.split(","), packages='base,shares', active="true") self.assertEqual(len(atoka_p), 1) def test_get_people_from_atoka_ids_ok(self): """Test test get_people_from_atoka_ids returns one result The test only needs to test the correct wrapping of get_items_from_ids, so it mocks the usual response, not a correct one """ tax_id = "80002270660" # mock atoka request using tax_id # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_p = atoka_conn.get_people_from_atoka_ids(tax_id.split(","), packages='base,shares', active="true") self.assertEqual(len(atoka_p), 1) def test_get_roles_from_atoka_ids_ok(self): """Test test get_roles_from_atoka_ids returns one result The test only needs to test the correct wrapping of get_items_from_ids, so it mocks the usual response, not a correct one """ tax_id = "80002270660" # mock atoka request using tax_id # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_companies(tax_id), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') atoka_p = atoka_conn.get_roles_from_atoka_ids(tax_id.split(","), packages='base,shares', active="true") self.assertEqual(len(atoka_p), 1) def test_get_roles_from_atoka_ids_handles_doesnotexist(self): """Test get_roles_from_atoka_ids handles the AtokaObjectDoesNotExist exception and returns empty list """ # mock atoka request using tax_id self.mock_post.return_value = MockResponse( get_void_response(), status_code=200, ok=True ) # do the test atoka_conn = AtokaConn(key='testing') items = atoka_conn.get_roles_from_atoka_ids([faker.ssn(), faker.ssn()]) self.assertEqual(len(items), 0)
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6
1baf2fcaf7159ab076b1c4d2870222d7a2a80ece
245
py
Python
test/runtime/frontend_test/tensorflow_test/util.py
gunpowder78/webdnn
c659ea49007f91d178ce422a1eebe289516a71ee
[ "MIT" ]
1
2018-07-26T13:52:21.000Z
2018-07-26T13:52:21.000Z
test/runtime/frontend_test/tensorflow_test/util.py
gunpowder78/webdnn
c659ea49007f91d178ce422a1eebe289516a71ee
[ "MIT" ]
null
null
null
test/runtime/frontend_test/tensorflow_test/util.py
gunpowder78/webdnn
c659ea49007f91d178ce422a1eebe289516a71ee
[ "MIT" ]
null
null
null
import logging logging.getLogger("tensorflow").setLevel(logging.WARNING) # noinspection PyUnresolvedReferences import tensorflow as tf # noinspection PyUnresolvedReferences from webdnn.frontend.tensorflow.converter import TensorFlowConverter
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6
1bc0d0c400f5e2c75cba06c90e875d42e90539d7
163
py
Python
apps/responsible_disc/admin.py
blockomat2100/vulnman
835ff3aae1168d8e2fa5556279bc86efd2e46472
[ "MIT" ]
null
null
null
apps/responsible_disc/admin.py
blockomat2100/vulnman
835ff3aae1168d8e2fa5556279bc86efd2e46472
[ "MIT" ]
23
2021-12-01T10:00:38.000Z
2021-12-11T11:43:13.000Z
apps/responsible_disc/admin.py
blockomat2100/vulnman
835ff3aae1168d8e2fa5556279bc86efd2e46472
[ "MIT" ]
null
null
null
from django.contrib import admin from apps.responsible_disc import models admin.site.register(models.Vulnerability) admin.site.register(models.VulnerabilityLog)
23.285714
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6
1bc4003a82673af42ffaa542b30d9f8cf9ed719d
196
py
Python
braintree/exceptions/too_many_requests_error.py
futureironman/braintree_python
26bb8a857bc29322a8bca2e8e0fe6d99cfe6a1ac
[ "MIT" ]
182
2015-01-09T05:26:46.000Z
2022-03-16T14:10:06.000Z
braintree/exceptions/too_many_requests_error.py
futureironman/braintree_python
26bb8a857bc29322a8bca2e8e0fe6d99cfe6a1ac
[ "MIT" ]
95
2015-02-24T23:29:56.000Z
2022-03-13T03:27:58.000Z
braintree/exceptions/too_many_requests_error.py
futureironman/braintree_python
26bb8a857bc29322a8bca2e8e0fe6d99cfe6a1ac
[ "MIT" ]
93
2015-02-19T17:59:06.000Z
2022-03-19T17:01:25.000Z
from braintree.exceptions.braintree_error import BraintreeError class TooManyRequestsError(BraintreeError): """ Raised when the rate limit request threshold is exceeded. """ pass
24.5
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6
1bce3cb96247b723262e79c696c42ce97633e06f
37
py
Python
specter/modules/SpecterTools/packagermodule.py
iplo/Specter
e1cfe48c9656efdddb3abbd2ea7d0bfa38d1380e
[ "MIT" ]
2
2017-04-09T19:40:03.000Z
2017-04-21T16:49:57.000Z
specter/modules/SpecterTools/packagermodule.py
iplo/Specter
e1cfe48c9656efdddb3abbd2ea7d0bfa38d1380e
[ "MIT" ]
1
2017-04-09T19:45:14.000Z
2017-04-22T12:37:37.000Z
specter/modules/SpecterTools/packagermodule.py
iplo/Specter
e1cfe48c9656efdddb3abbd2ea7d0bfa38d1380e
[ "MIT" ]
null
null
null
def printname(): print("Packager")
12.333333
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37
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6
59ef67df6b2617a20373d356ccca8f0058036eac
189
py
Python
python/test_rel_import/dir3/module3b.py
galdebert/sandbox
1489ed6dfe0b7e44fbc4dc71942bf1d5377a9de9
[ "Apache-2.0" ]
1
2015-09-15T21:41:57.000Z
2015-09-15T21:41:57.000Z
python/test_rel_import/dir3/module3b.py
autodefrost/sandbox
1489ed6dfe0b7e44fbc4dc71942bf1d5377a9de9
[ "Apache-2.0" ]
null
null
null
python/test_rel_import/dir3/module3b.py
autodefrost/sandbox
1489ed6dfe0b7e44fbc4dc71942bf1d5377a9de9
[ "Apache-2.0" ]
null
null
null
#from . import module3a # ok but pylint makes an error: Attempted relative import beyond top-level package (relative-beyond-top-level) def func3b(): print('3b') #module3a.func3a()
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6
94036ce97154cb2a51f593a1ed2d221389e7c264
282
py
Python
cupy/cuda/memory_hooks/__init__.py
svlandeg/cupy
484e007d5bf58a0445af2f6e7aa3fdfe0fcc2363
[ "MIT" ]
6,180
2016-11-01T14:22:30.000Z
2022-03-31T08:39:20.000Z
cupy/cuda/memory_hooks/__init__.py
svlandeg/cupy
484e007d5bf58a0445af2f6e7aa3fdfe0fcc2363
[ "MIT" ]
6,281
2016-12-22T07:42:31.000Z
2022-03-31T19:57:02.000Z
cupy/cuda/memory_hooks/__init__.py
svlandeg/cupy
484e007d5bf58a0445af2f6e7aa3fdfe0fcc2363
[ "MIT" ]
829
2017-02-23T05:46:12.000Z
2022-03-27T17:40:03.000Z
from cupy.cuda.memory_hooks import debug_print # NOQA from cupy.cuda.memory_hooks import line_profile # NOQA # import class and function from cupy.cuda.memory_hooks.debug_print import DebugPrintHook # NOQA from cupy.cuda.memory_hooks.line_profile import LineProfileHook # NOQA
40.285714
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6
9405276746939238041e75e50590bbaf5faba208
20
py
Python
python/testData/editing/tripleQuotesInsideTripleQuotedStringLiteral.after.py
jnthn/intellij-community
8fa7c8a3ace62400c838e0d5926a7be106aa8557
[ "Apache-2.0" ]
2
2019-04-28T07:48:50.000Z
2020-12-11T14:18:08.000Z
python/testData/editing/tripleQuotesInsideTripleQuotedStringLiteral.after.py
jnthn/intellij-community
8fa7c8a3ace62400c838e0d5926a7be106aa8557
[ "Apache-2.0" ]
173
2018-07-05T13:59:39.000Z
2018-08-09T01:12:03.000Z
python/testData/editing/tripleQuotesInsideTripleQuotedStringLiteral.after.py
jnthn/intellij-community
8fa7c8a3ace62400c838e0d5926a7be106aa8557
[ "Apache-2.0" ]
2
2020-03-15T08:57:37.000Z
2020-04-07T04:48:14.000Z
s = ''' '\\'''' '''
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6
941518d2b2d421b4b85957705d0030fc8262d4b3
20,870
py
Python
src/geocurrency/rates/tests.py
comradekingu/geocurrency
00131739555438b6926caea7c5b237bb23b9848d
[ "MIT" ]
null
null
null
src/geocurrency/rates/tests.py
comradekingu/geocurrency
00131739555438b6926caea7c5b237bb23b9848d
[ "MIT" ]
null
null
null
src/geocurrency/rates/tests.py
comradekingu/geocurrency
00131739555438b6926caea7c5b237bb23b9848d
[ "MIT" ]
null
null
null
import datetime import uuid from datetime import date from django.contrib.auth.models import User from django.core.cache import cache from django.conf import settings from django.test import TestCase from rest_framework import status from rest_framework.authtoken.models import Token from rest_framework.test import APIClient from .models import Rate, RateConverter from .serializers import RateAmountSerializer class RateTest(TestCase): base_currency = 'EUR' currency = 'USD' def setUp(self) -> None: settings.RATE_SERVICE = 'forex' self.user, created = User.objects.get_or_create( username='test', email='test@ipd.com' ) self.user.set_password('test') self.user.save() Token.objects.create(user=self.user) self.key = uuid.uuid4() self.amounts = [ { 'currency': 'USD', 'amount': 100, 'date_obj': '2020-07-22' }, { 'currency': 'AUD', 'amount': 50, 'date_obj': '2020-07-23' }, ] self.trash_amounts = [ { 'currency': 'USD', 'amount': 'toto', 'date_obj': '01/01/2020' }, { 'currency': 'LOL', 'date_obj': '2020-07-23' }, { 'date_obj': '2020-07-23' }, { 'currency': 'JPY', }, ] def test_fetch_rates(self): rates = Rate.objects.fetch_rates(base_currency=self.base_currency) self.assertIsNotNone(rates) def test_fetch_rates_with_date(self): rates = Rate.objects.fetch_rates(base_currency=self.base_currency, date_obj=date(year=2020, month=6, day=1)) self.assertIsNotNone(rates) def test_fetch_rate(self): rate = Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) self.assertIsNotNone(rate) def test_fetch_rate_with_date(self): rate = Rate.objects.fetch_rates( base_currency=self.base_currency, currency=self.currency, date_obj=date(year=2020, month=6, day=1) ) self.assertIsNotNone(rate) def test_find_direct_rate(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) rate = Rate.objects.find_direct_rate(base_currency=self.base_currency, currency=self.currency) self.assertIsNotNone(rate, msg="no direct rate found") def test_find_pivot_rate(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) Rate.objects.fetch_rates(base_currency=self.currency, currency='AUD') rate = Rate.objects.find_pivot_rate(base_currency=self.base_currency, currency='AUD') self.assertIsNotNone(rate, msg="no pivot rate found") def test_rate_at_date(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) Rate.objects.fetch_rates(base_currency=self.currency, currency='AUD') rate = Rate.objects.find_direct_rate(base_currency=self.base_currency, currency=self.currency) self.assertIsNotNone(rate.pk, msg="no direct rate found") rate = Rate.objects.find_pivot_rate(base_currency=self.base_currency, currency='AUD') self.assertIsNotNone(rate.pk, msg="no pivot rate found") def test_post_rate(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(response.status_code, 201) response = client.get( '/rates/', format='json') self.assertEqual(len(response.json()), 2) def test_post_rate_without_key(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) response = client.post( '/rates/', data={ 'key': '', 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) def test_list_request(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) client = APIClient() response = client.get( '/rates/', format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) def test_stats_request(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) client = APIClient() response = client.get( '/rates/stats/', data={}, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) def test_connected_list_request(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) self.assertIn('id', post_response.json()) response = client.get( '/rates/', format='json') anon_client = APIClient() anon_response = anon_client.get( '/rates/', format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(anon_response.status_code, status.HTTP_200_OK) self.assertEqual(len(response.json()), len(anon_response.json()) + 2) def test_list_user_request(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) self.assertIn('id', post_response.json()) response = client.get( '/rates/', format='json') anon_client = APIClient() anon_response = anon_client.get( '/rates/', format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(anon_response.status_code, status.HTTP_200_OK) self.assertEqual(len(response.json()), len(anon_response.json()) + 2) def test_list_with_key_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) response = client.get( '/rates/', data={'key': self.key}, format='json') self.assertEqual(response.json()[0]['key'], self.key) def test_list_with_key_or_null_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) response = client.get( '/rates/', data={'key_or_null': self.key}, format='json') self.assertEqual(len(response.json()), 3) def test_list_with_key_isnull_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) response = client.get( '/rates/', data={'key_isnull': self.key}, format='json') self.assertEqual(response.json()[0]['key'], None) def test_list_with_key_and_currency_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) response = client.get( '/rates/', data={'key': self.key, 'currency': 'USD'}, format='json') self.assertEqual(len(response.json()), 1) def test_stats_with_key_and_currency_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-02', 'value': 1.20, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) response = client.get( '/rates/stats/', data={'key': self.key, 'currency': 'EUR'}, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) def test_list_with_key_and_base_currency_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'value_date': '2020-01-01', 'value': 1.10, } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) response = client.get( '/rates/', data={'key': self.key, 'base_currency': 'USD'}, format='json') self.assertEqual(len(response.json()), 1) def test_retrieve_request(self): client = APIClient() response = client.get( '/rates/', format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) def test_bulk_create_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/bulk/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'from_date': '2020-01-01', 'to_date': '2020-09-01', 'value': 1.10 } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) self.assertEqual(len(post_response.json()), (datetime.date(year=2020, month=9, day=1) - datetime.date(year=2020, month=1, day=1)).days + 1) def test_latest_currency_request(self): client = APIClient() token = Token.objects.get(user__username=self.user.username) client.credentials(HTTP_AUTHORIZATION='Token ' + token.key) post_response = client.post( '/rates/bulk/', data={ 'key': self.key, 'currency': 'USD', 'base_currency': 'EUR', 'from_date': '2020-01-01', 'to_date': '2020-09-01', 'value': 1.10 } ) self.assertEqual(post_response.status_code, status.HTTP_201_CREATED) response = client.get( '/rates/?currency_latest_values=USD' ) self.assertEqual(len(response.json()), 1) response = client.get( '/rates/?base_currency_latest_values=EUR' ) self.assertEqual(len(response.json()), 1) class RateConverterTest(TestCase): base_currency = 'EUR' currency = 'USD' def setUp(self) -> None: self.user, created = User.objects.get_or_create( username='test', email='test@ipd.com' ) self.converter = RateConverter(user=self.user, base_currency='EUR') self.amounts = [ { 'currency': 'USD', 'amount': 100, 'date_obj': '2020-07-22' }, { 'currency': 'AUD', 'amount': 50, 'date_obj': '2020-07-23' }, ] self.trash_amounts = [ { 'currency': 'USD', 'amount': 'toto', 'date_obj': '01/01/2020' }, { 'currency': 'LOL', 'date_obj': '2020-07-23' }, { 'date_obj': '2020-07-23' }, { 'currency': 'JPY', }, ] def test_created(self): self.assertEqual(self.converter.status, self.converter.INITIATED_STATUS) def test_add_data(self): errors = self.converter.add_data(self.amounts) self.assertEqual(errors, []) self.assertEqual(self.converter.status, self.converter.INSERTING_STATUS) self.assertIsNotNone(self.converter.cached_currencies) self.assertIsNotNone(cache.get(self.converter.id)) def test_trash_amounts(self): converter = RateConverter(user=self.user, base_currency='EUR') errors = converter.add_data(self.trash_amounts) self.assertEqual(len(errors), 4) self.assertIn("amount", errors[0]) self.assertIn("currency", errors[1]) self.assertNotIn("date_obj", errors[2]) self.assertNotIn("currency", errors[3]) def test_convert(self): result = self.converter.convert() self.assertEqual(result.id, self.converter.id) self.assertEqual(result.target, 'EUR') self.assertEqual(self.converter.status, self.converter.FINISHED) self.assertEqual(len(result.errors), 0) self.assertEqual(len(result.detail), len(self.converter.data)) converted_sum = sum([d.converted_value for d in result.detail]) self.assertEqual(result.sum, converted_sum) def test_convert_pivot(self): converter = RateConverter(self.user, base_currency='JPY') amounts = [ { 'currency': 'AUD', 'amount': 50, 'date_obj': '2020-07-23' }, ] converter.add_data(amounts) result = converter.convert() self.assertEqual(result.id, converter.id) self.assertEqual(result.target, 'JPY') self.assertEqual(converter.status, converter.FINISHED) self.assertEqual(result.errors, []) self.assertEqual(len(result.detail), len(converter.data)) converted_sum = sum([d.converted_value for d in result.detail]) self.assertEqual(result.sum, converted_sum) def test_convert_request(self): Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) Rate.objects.fetch_rates(base_currency=self.currency, currency='AUD') amounts = RateAmountSerializer(self.amounts, many=True) client = APIClient() response = client.post( '/rates/convert/', data={ 'data': amounts.data, 'target': 'EUR', }, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertIn('sum', response.json()) self.assertEqual(len(response.json().get('detail')), len(self.amounts)) def test_convert_batch_request(self): batch_id = uuid.uuid4() Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) Rate.objects.fetch_rates(base_currency=self.currency, currency='AUD') client = APIClient() amounts = RateAmountSerializer(self.amounts, many=True) response = client.post( '/rates/convert/', data={ 'data': amounts.data, 'target': 'EUR', 'batch_id': batch_id, }, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertIn('id', response.json()) self.assertEqual(response.json().get('status'), RateConverter.INSERTING_STATUS) self.assertEqual(response.json().get('id'), str(batch_id)) response = client.post( '/rates/convert/', data={ 'data': amounts.data, 'batch_id': batch_id, 'target': 'EUR', 'eob': True }, format='json') self.assertEqual(response.json().get('status'), RateConverter.FINISHED) self.assertEqual(len(response.json().get('detail')), 2 * len(self.amounts)) def test_watch_request(self): batch_id = uuid.uuid4() Rate.objects.fetch_rates(base_currency=self.base_currency, currency=self.currency) Rate.objects.fetch_rates(base_currency=self.currency, currency='AUD') client = APIClient() amounts = RateAmountSerializer(self.amounts, many=True) response = client.post( '/rates/convert/', data={ 'data': amounts.data, 'target': 'EUR', 'batch_id': batch_id, }, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertIn('id', response.json()) self.assertEqual(response.json().get('status'), RateConverter.INSERTING_STATUS) self.assertEqual(response.json().get('id'), str(batch_id)) response = client.get( f'/watch/{str(batch_id)}/', format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.json().get('status'), RateConverter.INSERTING_STATUS) self.assertEqual(response.json().get('id'), str(batch_id))
37.468582
120
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5.197632
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6
941a3fde75eb9abd61d2da57ff5caf55b245627c
1,740
py
Python
moog/env_wrappers/abstract_wrapper.py
juanpablordz/moog.github.io
d7995d3563492378d0877ce8d16f5ca9a8031794
[ "Apache-2.0", "MIT" ]
22
2021-02-26T18:19:35.000Z
2022-03-05T19:01:00.000Z
moog/env_wrappers/abstract_wrapper.py
juanpablordz/moog.github.io
d7995d3563492378d0877ce8d16f5ca9a8031794
[ "Apache-2.0", "MIT" ]
1
2021-04-01T06:15:02.000Z
2021-04-23T13:14:12.000Z
moog/env_wrappers/abstract_wrapper.py
juanpablordz/moog.github.io
d7995d3563492378d0877ce8d16f5ca9a8031794
[ "Apache-2.0", "MIT" ]
2
2021-05-02T02:20:39.000Z
2021-05-06T16:24:35.000Z
"""Abstract wrapper. This file contains AbstractEnvironmentWrapper, an abstract base class for environment wrappers that mimics the interface of the underlying environment. """ import abc class AbstractEnvironmentWrapper(abc.ABC): """Abstract environment wrapper class. All environment wrappers must inherit from this class. """ def __init__(self, environment): self._environment = environment def reset(self): return self._environment.reset() def step(self, action): return self._environment.step(action) def observation(self): return self._environment.observation() def observation_spec(self): return self._environment.observation_spec() def action_spec(self): return self._environment.action_spec() @property def state(self): return self._environment.state @property def meta_state(self): return self._environment.meta_state @property def state_initializer(self): return self._environment.state_initializer @property def physics(self): return self._environment.physics @property def task(self): return self._environment.task @property def action_space(self): return self._environment.action_space @property def observers(self): return self._environment.observers @property def game_rules(self): return self._environment.game_rules @property def environment(self): return self._environment @property def step_count(self): return self._environment.step_count @property def reset_next_step(self): return self._environment.reset_next_step
22.597403
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6
9453a06e79f1363f657d9429737a9a558bc3a9e5
1,482
py
Python
pa1-skeleton/pa1-data/8/www.stanford.edu_class_cs221_progAssignments_PA3_analysis.py
yzhong94/cs276-spring-2019
a4780a9f88b8c535146040fe11bb513c91c5693b
[ "MIT" ]
null
null
null
pa1-skeleton/pa1-data/8/www.stanford.edu_class_cs221_progAssignments_PA3_analysis.py
yzhong94/cs276-spring-2019
a4780a9f88b8c535146040fe11bb513c91c5693b
[ "MIT" ]
null
null
null
pa1-skeleton/pa1-data/8/www.stanford.edu_class_cs221_progAssignments_PA3_analysis.py
yzhong94/cs276-spring-2019
a4780a9f88b8c535146040fe11bb513c91c5693b
[ "MIT" ]
null
null
null
analysis py licensing information please do not distribute or publish solutions to this project you are free to use and extend these projects for educational purposes the pacman ai projects were developed at uc berkeley primarily by john denero denero cs berkeley edu and dan klein klein cs berkeley edu for more info see http inst eecs berkeley edu cs188 sp09 pacman html analysis questions change these default values to obtain the specified policies through value iteration def question2a answerdiscount 0.9 answernoise 0.2 answerlivingreward 0.0 return answerdiscount answernoise answerlivingreward if not possible return not possible def question2b answerdiscount 0.9 answernoise 0.2 answerlivingreward 0.0 return answerdiscount answernoise answerlivingreward if not possible return not possible def question2c answerdiscount 0.9 answernoise 0.2 answerlivingreward 0.0 return answerdiscount answernoise answerlivingreward if not possible return not possible def question2d answerdiscount 0.9 answernoise 0.2 answerlivingreward 0.0 return answerdiscount answernoise answerlivingreward if not possible return not possible def question2e answerdiscount 0.9 answernoise 0.2 answerlivingreward 0.0 return answerdiscount answernoise answerlivingreward if not possible return not possible if __name__ __main__ print answers to analysis questions import analysis for q in q for q in dir analysis if q startswith question response getattr analysis q print question s t s q str response
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6
84cc32ee525f608a0c3d16f25e8391b031a0c411
44
py
Python
python/tinypostman/__init__.py
francc/tinypacks
96c63e872068ac70222887d6a36b56f01048febb
[ "MIT-0" ]
23
2015-06-16T21:33:44.000Z
2021-06-20T01:19:10.000Z
python/tinypostman/__init__.py
francc/tinypacks
96c63e872068ac70222887d6a36b56f01048febb
[ "MIT-0" ]
null
null
null
python/tinypostman/__init__.py
francc/tinypacks
96c63e872068ac70222887d6a36b56f01048febb
[ "MIT-0" ]
8
2015-09-04T20:07:29.000Z
2020-06-22T04:48:30.000Z
#!/usr/bin/python from tinypostman import *
14.666667
25
0.75
6
44
5.5
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1
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0
6
ca0a7666701e48d9a8acdf35dda9b4f2d842f32c
46
py
Python
zgres/tests/test_show.py
jinty/zgres
88730e94bb543ec4d48c27523d02e3136b332173
[ "MIT" ]
12
2015-11-08T21:29:52.000Z
2018-10-25T04:45:58.000Z
zgres/tests/test_show.py
jinty/zgres
88730e94bb543ec4d48c27523d02e3136b332173
[ "MIT" ]
null
null
null
zgres/tests/test_show.py
jinty/zgres
88730e94bb543ec4d48c27523d02e3136b332173
[ "MIT" ]
6
2015-10-25T05:59:12.000Z
2021-01-06T08:02:46.000Z
def test_import(): from zgres import show
15.333333
26
0.717391
7
46
4.571429
0.857143
0
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46
2
27
23
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1
0
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0
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6
ca171731bedf825af0644d55db11dce2ad1c068e
102
py
Python
tests/dd.py
laiyuanliang/myBlog
0eb3a5e8ba857589a623c087fe2ca696b8339346
[ "BSD-3-Clause" ]
null
null
null
tests/dd.py
laiyuanliang/myBlog
0eb3a5e8ba857589a623c087fe2ca696b8339346
[ "BSD-3-Clause" ]
null
null
null
tests/dd.py
laiyuanliang/myBlog
0eb3a5e8ba857589a623c087fe2ca696b8339346
[ "BSD-3-Clause" ]
null
null
null
import os #direc = os.path.join(os.path.dirname(__file__), 'd.sql') print(os.path.abspath(__file__))
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py
Python
output/models/nist_data/list_pkg/id/schema_instance/nistschema_sv_iv_list_id_enumeration_3_xsd/nistschema_sv_iv_list_id_enumeration_3.py
tefra/xsdata-w3c-tests
b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f
[ "MIT" ]
1
2021-08-14T17:59:21.000Z
2021-08-14T17:59:21.000Z
output/models/nist_data/list_pkg/id/schema_instance/nistschema_sv_iv_list_id_enumeration_3_xsd/nistschema_sv_iv_list_id_enumeration_3.py
tefra/xsdata-w3c-tests
b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f
[ "MIT" ]
4
2020-02-12T21:30:44.000Z
2020-04-15T20:06:46.000Z
output/models/nist_data/list_pkg/id/schema_instance/nistschema_sv_iv_list_id_enumeration_3_xsd/nistschema_sv_iv_list_id_enumeration_3.py
tefra/xsdata-w3c-tests
b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f
[ "MIT" ]
null
null
null
from dataclasses import dataclass, field from enum import Enum from typing import Optional __NAMESPACE__ = "NISTSchema-SV-IV-list-ID-enumeration-3-NS" class NistschemaSvIvListIdEnumeration3Type(Enum): MLEADERS_FFACT_PRODUC_FAND_MEMORY_THAT_AND_MEA_ACHIEVED_SIGNATURE_P_TCOMPATIBILITY_TO_ABOUT_NETWORKING_ROBUST_FROM_FOR_TH_XWHICH_OF_BUSINESS_INCLUDE_THESE_DEVICES_THE = ( "mleaders", "ffact_produc", "fand-memory_that-and.mea", "_achieved_signature-p", "tcompatibility_to_about-networking-robust-from_for_th", "xwhich-of-business_include.these_devices_the", ) VA_OF_USERS_THE_AND_AN_TO_FOR_VOICED_PROFILE_OF_XTHE_POSSIBLE_SUCCESS_WEB_OF_INCLUDING_I_YWIDE_DEFINES_BUS_AND_SMALL_BOTTLENECKS_THE_FIL_DOF_THE_TO_WID_LED_LOCALIZED_THE_TRANSFORMING_REGISTRIES_BY_OTO_INFORMATION_G_SENSORS_A_OLDER_OVER_INDUSTRY_PROVIDE_ENOUGH_INFLUENCE_NEWCOM = ( "va-of-users-the.and.an_to-for-voiced.profile-of_", "xthe.possible.success.web.of_including_i", "ywide_defines.bus", "_and.small-_bottlenecks.the_fil", "dof.the-to_wid", "_led-localized_the.transforming_registries_by-", "oto-information-g_sensors.a.older.over.industry.provide-enough-", "_influence_newcom", ) TREPOSITORY_AN_C_ICOMPUTING_FOR_AS_TESTING_MAKE_SOFTWARE_OF_INTERNATIONAL_NRETRIEVE_SENSE_TO_THEIR_SOL_XAPPLICATIONS_OF_AND_THE_FRAMEWORKS_THE_SPECIFIC_S_THESE_WE_RET_TSECOND_GENERATION_HAS_TO_LARGE_THE_THEM_RELAT_BCAN_MUST_CCOMPATIBILITY_SHIFT_G_AS_PARTNER_TKNOWN_FOR_WITH_SYSTEM_AREAS_CHO = ( "trepository_an.c", "icomputing_for-as.testing_make.software_of-international", "nretrieve-sense-to_their_sol", "xapplications-of.and_the-frameworks_the-specific-s.these_we-ret", "tsecond-generation.has-to.large.the_them.relat", "bcan-must", "ccompatibility_shift.g.as.partner", "tknown_for.with.system-areas.cho", ) LSPECIFICATIONS_TOOL_NEW_WIRELESS_THE_ARE_H_CCONSISTENCY_TO_PERSONAL_RBACK_IN_OF_THE_ON_AS_PROTOTYPE_PROVIDES_IN_LED_THE_PROVIDE_HUSER_ALL_TECHNOLOGY_THE_MUST_AS_BE_PROFILE_FOR_COMPETEN_XSTRUCTURE_USES_CUSED_AND_OF_IS_COMPUTING_ASPECTS_THOSE_E_NAND_BE_REPOSITORY_TESTS_ITS_CTHE_STAKEHOLDERS_DIRECTIONS_DEFINE_OF_BECOME_SOFTWA = ( "lspecifications-tool_new.wireless.the.are.h", "cconsistency.to-personal", "rback_in-of_the-on.as-prototype-provides-in_led-the-provide", "huser-all.technology-the_must_as-be.profile_for-competen", "xstructure-uses", "cused_and_of.is.computing.aspects.those.e", "nand-be_repository_tests.its", "cthe-stakeholders.directions.define-of_become_softwa", ) BRIGOROUS_THAT_CAN_TO_CRE_CCOST_OF_MANIPULATE_SEN_KINVOLVED_ORGANIZATIONS_AND_ISSUES_UWELL_DEVICES_HAS_WITH_BENEFITS_AUTOMATIC_MOST_STA_AND_SPECIFICATIONS_INDIVIDUAL_PORTABLE_SERIES_USE_QAND_THE_COME_THE_FILE_AU = ( "brigorous.that-can.to_cre", "ccost.of_manipulate_sen", "kinvolved.organizations-and.issues", "uwell-devices.has-with-benefits_automatic.most_sta", "_and_specifications.individual.portable_series.use", "qand-the_come-the.file_au", ) PLED_AND_THESE_AMONG_REPUTATION_FULL_AN_RECOGNITION_AND_INDICATION_UNDERSTAND_INDUSTRY_APPL_YAN_VCREATION_MEANS_TOOLS_ON_WITH_IS_THE_FIVE_WILL_H_NUNBIASED_RESULT_FROM_OUR_GENERATION_FILES_ALLOW_R_QBOTH_COMPLETION_PROCESSORS_RI_CF_QTO_EMBEDDED_ANY_EFFECTIVELY_AREAS_OF = ( "pled_and_these.among-reputation.full_an", "_recognition_and-indication.understand-industry-appl", "yan", "vcreation_means_tools_on.with_is.the_five_will_h", "nunbiased-result_from.our.generation-files_allow-r", "qboth-completion_processors-ri", "cf", "qto-embedded.any_effectively_areas_of.", ) MGUIDELINES_FOR_CHOICES_MARKET_MANIP_URETRIEVES_THE_WILL_OF_COST_FR_PL_PBETWEEN_TO_ENFORCEM_VFOR_HELP_WITH_AND_PRECISE_DEVELOPED_THAT_IN_USED_REVIE = ( "mguidelines-for.choices.market.manip", "uretrieves.the.will_of_cost-fr", "pl", "pbetween-to.enforcem", "vfor.help.with.and-precise-developed-that_in_used.revie", ) @dataclass class Out: class Meta: name = "out" namespace = "NISTSchema-SV-IV-list-ID-enumeration-3-NS" any_element: Optional[object] = field( default=None, metadata={ "type": "Wildcard", "namespace": "##any", } ) @dataclass class NistschemaSvIvListIdEnumeration3: class Meta: name = "NISTSchema-SV-IV-list-ID-enumeration-3" namespace = "NISTSchema-SV-IV-list-ID-enumeration-3-NS" value: Optional[NistschemaSvIvListIdEnumeration3Type] = field( default=None, metadata={ "required": True, } )
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6
ca776bb9333fc39e5aa2a696195e371b76534d94
138
py
Python
pyyeti/nastran/__init__.py
twmacro/pyye
c4febd44be836bd87368da13c1fb0cf82838b687
[ "BSD-3-Clause" ]
17
2016-03-02T18:29:13.000Z
2022-03-18T08:41:56.000Z
pyyeti/nastran/__init__.py
twmacro/pyye
c4febd44be836bd87368da13c1fb0cf82838b687
[ "BSD-3-Clause" ]
2
2021-04-15T02:11:10.000Z
2021-12-06T12:49:57.000Z
pyyeti/nastran/__init__.py
twmacro/pyye
c4febd44be836bd87368da13c1fb0cf82838b687
[ "BSD-3-Clause" ]
6
2020-06-11T17:09:50.000Z
2022-02-07T19:15:07.000Z
""" A collection of tools for working with Nastran files """ from .bulk import * from .n2p import * from .op2 import * from . import op4
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6
ca9a6019f7e38198676cf58bba1a1504560edd2d
2,811
py
Python
yolov2_caffe/udacity_darknet_label_converter.py
dedoogong/asrada
55fbc6acae562d534ee0dcbc6b2931d77abe5203
[ "Apache-2.0" ]
2
2018-02-05T08:16:51.000Z
2020-01-11T08:48:28.000Z
yolov2_caffe/udacity_darknet_label_converter.py
dedoogong/asrada
55fbc6acae562d534ee0dcbc6b2931d77abe5203
[ "Apache-2.0" ]
null
null
null
yolov2_caffe/udacity_darknet_label_converter.py
dedoogong/asrada
55fbc6acae562d534ee0dcbc6b2931d77abe5203
[ "Apache-2.0" ]
1
2019-06-23T07:03:07.000Z
2019-06-23T07:03:07.000Z
import os import cv2 as cv import csv import numpy as np csv_dir_1 = '/media/lee/ETC_300_150GB/FaceDB/object-dataset/labels.csv' csv_root_dir_1 = '/media/lee/ETC_300_150GB/FaceDB/object-dataset/' csv_dir_2 = '/media/lee/ETC_300_150GB/FaceDB/object-detection-crowdai/labels.csv' csv_root_dir_2 = '/media/lee/ETC_300_150GB/FaceDB/object-detection-crowdai/' with open(csv_dir_1 , 'r') as f: # f == pts file reader = csv.reader(f, dialect='excel', delimiter=' ') for row in reader: imageFullPath=csv_root_dir_1+row[0] img = cv.imread(imageFullPath) img_height = float(img.shape[0]) img_width = float(img.shape[1]) ori_x_min = float(row[1]) ori_y_min = float(row[2]) ori_x_max = float(row[3]) ori_y_max = float(row[4]) front_back = int(row[5]) label = row[6] class_id = -1 if label == 'pedestrian': class_id = 0 elif label == 'car': class_id = 1 elif label == 'biker': class_id = 2 elif label == 'truck': class_id = 5 elif label == 'trafficLight': class_id = 6 normed_cx = (ori_x_max+ori_x_min)/(2*img_width) normed_cy = (ori_y_max+ori_y_min)/(2*img_height) normed_w = (ori_x_max-ori_x_min)/img_width normed_h = (ori_y_max-ori_y_min)/img_height data=str( class_id ) + ' ' + str(normed_cx ) + ' ' +str(normed_cy ) + ' ' + str(normed_w ) + ' ' + str(normed_h ) + '\n' f1=open(imageFullPath.replace('jpg','txt'),'a') f1.write(data) f1.close() with open(csv_dir_2, 'r') as f: # f == pts file reader = csv.reader(f, dialect='excel', delimiter=' ') for row in reader: imageFullPath = csv_root_dir_2 + row[0].split(',')[4] img = cv.imread(imageFullPath) img_height = float(img.shape[0]) img_width = float(img.shape[1]) ori_x_min = float(row[0].split(',')[0]) ori_y_min = float(row[0].split(',')[1]) ori_x_max = float(row[0].split(',')[2]) ori_y_max = float(row[0].split(',')[3]) label = row[0].split(',')[5] class_id = -1 if label == 'Pedestrian': class_id = 0 elif label == 'Car': class_id = 1 elif label == 'Truck': class_id = 5 normed_cx = (ori_x_max + ori_x_min) / (2 * img_width) normed_cy = (ori_y_max + ori_y_min) / (2 * img_height) normed_w = (ori_x_max - ori_x_min) / img_width normed_h = (ori_y_max - ori_y_min) / img_height data = str(class_id) + ' ' + str(normed_cx) + ' ' + str(normed_cy) + ' ' + str(normed_w) + ' ' + str(normed_h) + '\n' f1 = open(imageFullPath.replace('jpg', 'txt'), 'a') f1.write(data) f1.close()
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6
0460fadd2b2a71f8b43a411436e4f494440bcb0c
139
py
Python
settings/__init__.py
symeonp/choronzon
a9eed1ea2cab6bf2c3e020adf4951f6d01eecf72
[ "BSD-3-Clause" ]
null
null
null
settings/__init__.py
symeonp/choronzon
a9eed1ea2cab6bf2c3e020adf4951f6d01eecf72
[ "BSD-3-Clause" ]
null
null
null
settings/__init__.py
symeonp/choronzon
a9eed1ea2cab6bf2c3e020adf4951f6d01eecf72
[ "BSD-3-Clause" ]
1
2020-02-29T13:55:25.000Z
2020-02-29T13:55:25.000Z
import platform if platform.system() == 'Linux': from system import * elif platform.system() == 'Windows': from winsystem import *
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0466266d2220c9c760b9dacf4d32bb0347fb9a33
164
py
Python
opyoid/bindings/self_binding/__init__.py
illuin-tech/opyoid
a2ca485e1820ba0d12a86ba91100aa097a1e5736
[ "MIT" ]
37
2020-08-25T07:22:41.000Z
2022-03-18T03:05:53.000Z
opyoid/bindings/self_binding/__init__.py
illuin-tech/opyoid
a2ca485e1820ba0d12a86ba91100aa097a1e5736
[ "MIT" ]
18
2020-10-04T17:33:24.000Z
2021-12-16T16:28:35.000Z
opyoid/bindings/self_binding/__init__.py
illuin-tech/opyoid
a2ca485e1820ba0d12a86ba91100aa097a1e5736
[ "MIT" ]
2
2021-01-26T19:58:15.000Z
2021-11-30T01:10:25.000Z
from .from_class_provider import FromClassProvider from .self_binding import SelfBinding from .self_binding_to_provider_adapter import SelfBindingToProviderAdapter
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04b62cbb1b4ac4c14a7ab80ed6743b18700bb823
24,977
py
Python
Main Program.py
akri16/adi-mone-buzzer
b49df404eef589b5487b198b7aadf3777b9092d2
[ "MIT" ]
null
null
null
Main Program.py
akri16/adi-mone-buzzer
b49df404eef589b5487b198b7aadf3777b9092d2
[ "MIT" ]
null
null
null
Main Program.py
akri16/adi-mone-buzzer
b49df404eef589b5487b198b7aadf3777b9092d2
[ "MIT" ]
null
null
null
import os os.startfile('p.mp3') from random import * from qa import * from intro import * from functions import blank from RULES import* def asdf1 (t,h): t1=eval(''.join((t,'n1'))) t2=eval(''.join((t,'n2'))) s=0 if h==1: print '(1)',k1 print '(2)',k2 print '(3)',k3 print '(4)',k4 pas=[k1,k2,k3,k4] global pas else: pas.remove(zz2) lok=0 for lkj in pas: lok=lok+1 print lok,lkj if h==1: user_in=raw_input('Select the desired subject') while user_in not in ('1','2','3','4'): print 'INVALID input' user_in=raw_input('Select the desired subject') zz=pas zz1=int(user_in)-1 zz2=zz[zz1] print 'Guruji question please' print 'Which of the following are',zz2,'?' zz3=sub1.index(zz2) zz4=zz3+1 zz5=eval(''.join(('n',str(zz4)))) print zz5 global zz2 else : user_in=raw_input('Select the desired subject') while user_in not in ('1','2','3'): print 'INVALID input' user_in=raw_input('Select the desired subject') zz1=int(user_in)-1 print pas zz2=pas[zz1] print zz2 print 'Guruji question please' print 'Which of the following are',zz2,'?' zz3=sub1.index(zz2) zz4=zz3+1 zz5=eval(''.join(('n',str(zz4)))) print zz5 global zz2 hyt=['1','2','3','4','5','6','7','8','9','10'] print t1,'it is your turn now' print 'Type the correct answer:' sln1=raw_input('sol1:') while sln1 not in hyt: print 'INVALID input' sln1=raw_input('sol1:') hyt.remove(sln1) sln2=raw_input('sol2:') while sln2 not in hyt: print 'INVALID input' sln2=raw_input('sol2:') hyt.remove(sln2) sln3=raw_input('sol3:') while sln3 not in hyt: print 'INVALID input' sln3=raw_input('sol3:') hyt.remove(sln3) sln4=raw_input('sol4:') while sln4 not in hyt: print 'INVALID input' sln4=raw_input('sol4:') hyt.remove(sln4) sln5=raw_input('sol5:') while sln5 not in hyt: print 'INVALID input' sln5=raw_input('sol5:') print t1,'type "change" to change the solutions else proceed' cnf=raw_input() while (cnf !='change') and (cnf !=''): print 'INVALID input' print t1,'type "change" to change the solutions else proceed' cnf=raw_input() hyt=['1','2','3','4','5','6','7','8','9','10'] if cnf=='change': print 'retype the correct answers' sln1=raw_input('sol1:') while sln1 not in hyt: print 'INVALID input' sln1=raw_input('sol1:') hyt.remove(sln1) sln2=raw_input('sol2:') while sln2 not in hyt: print 'INVALID input' sln2=raw_input('sol1:') hyt.remove(sln2) sln3=raw_input('sol3:') while sln3 not in hyt: print 'INVALID input' sln3=raw_input('sol1:') hyt.remove(sln3) sln4=raw_input('sol4:') while sln4 not in hyt: print 'INVALID input' sln4=raw_input('sol1:') hyt.remove(sln4) sln5=raw_input('sol5:') while sln5 not in hyt: print 'INVALID input' sln5=raw_input('sol1:') if cnf=='' or cnf=='change': blank() print t2,'its your turn.....' print t2,'type "change" to change the solutions else proceed' cnf1=raw_input() while (cnf1 !='change')and (cnf1 !=''): print 'INVALID input' print t2,'type "change" to change the solutions else proceed' cnf1=raw_input() if cnf1=='change': s=0 hyt=['1','2','3','4','5','6','7','8','9','10'] print 'retype the correct answers' sLn1=raw_input('sol1:') while sLn1 not in hyt: print 'INVALID input' sLn1=raw_input('sol1:') hyt.remove(sLn1) sLn2=raw_input('sol2:') while sLn2 not in hyt : print 'INVALID input' sLn1=raw_input('sol1:') hyt.remove(sLn2) sLn3=raw_input('sol3:') while sLn3 not in hyt: print 'INVALID input' sLn1=raw_input('sol1:') hyt.remove(sLn3) sLn4=raw_input('sol4:') while sLn4 not in hyt: print 'INVALID input' sLn1=raw_input('sol1:') hyt.remove(sLn4) sLn5=raw_input('sol5:') while sLn5 not in hyt: print 'INVALID input' sLn1=raw_input('sol1:') if cnf1=='' or cnf1=='change': blank() print 'Now lets see to the answers','Dont be afraid!!!' xcv=[sln1,sln2,sln3,sln4,sln5] if cnf1=='': for afgh in xcv: if int(afgh)in (eval(''.join(('Ans',str(zz4))))): ast=zz5[(int(afgh))-1] print ast,'--> double correct-->2000 points' s=s+2000 else: ast=zz5[(int(afgh))-1] print ast,'-->Sorry,wrong answer' elif cnf1=='change': mnb=[sLn1,sLn2,sLn3,sLn4,sLn5] for y in xcv : if (y in mnb) and (int(y) in(eval(''.join(('Ans',str(zz4)))))): s=s+2000 mnb.remove(y) mnj=zz5[(int(y))-1] print mnj,'--> double correct-->2000 points' for pl in mnb: if int(pl) in (eval(''.join(('Ans',str(zz4))))): s=s+1000 act=zz5[(int(pl))-1] print act,'--> correct-->1000 points' else: act=zz5[(int(pl))-1] print act,'-->Sorry,wrong answer' print 'Now lets see which all are right answers' print 'So the correct answers are--->' for asw in (eval(''.join(('Ans',str(zz4))))): print zz5[asw-1] blank() if s==10000: print 'ya!hoo!,you`ve got a bonus!!!' s=s+5000 if t=='g1': score1=s global score1 elif t=='g2': score2=s global score2 t=eval(t) print 'team', t,'your team score is',s def osub1 (R): x1=randint(0,13) if R=='r1': k1=sub1[x1] else :k1=sub3[x1] print '(1)',k1 x2=randint(0,13) while x2==x1: x2=randint(0,13) if R=='r1': k2=sub1[x2] else :k2=sub3[x2] print '(2)',k2 x3=randint(0,13) while (x3==x1) or (x3==x2): x3=randint(0,13) if R=='r1': k3=sub1[x3] else :k3=sub3[x3] print '(3)',k3 x4=randint(0,13) while (x4==x1)or (x4==x2)or(x4==x3): x4=randint(0,13) if R=='r1': k4=sub1[x4] else :k4=sub3[x4] print '(4)',k4 global k1 global k2 global k3 global k4 #------------------------------ def main (): print'ADI MONA BUZZER FOR ROUND-1-->TYPE IT RIGHT' rul1() print ('guruji subjects please') osub1 ('r1') blank() print 'So your buzzer question is........' x=randint(0,5) print bq[x] b=(raw_input('type 1,2,3,or 4 for player 1 player 2 player3 and player 4 respectively:')) while (b not in ('1','2','3','4'))or b=='' : print'INVALID input' b=raw_input('type the right input:') b=int(b) an_no=('a',str(x+1)) an_no=eval(''.join(an_no)) if b==1: print g1n2,'type the appropriate answer:' s1=raw_input() while len(s1)==0 or len(s1)>25: print 'INVALID Input' print g1n2,'type the appropriate answer:' s1=raw_input() if an_no in s1 : print 'Right Answer' print 'Team',g1,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g1',1) blank() asew='g2' pm=g1 else: print 'Sorry wrong answer' print 'Team',g2,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g2',1) blank() asew='g1' pm=g1 elif b==2: print g1n1,'type the appropriate answer:' s2=raw_input() while len(s2)==0 or len(s2)>25: print 'INVALID Input' print g1n1,'type the appropriate answer:' s2=raw_input() if an_no in s2 : print 'Right Answer' print 'Team',g1,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g1',1) blank() asew='g2' else: print 'Sorry wrong answer' print 'Team',g2,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g2',1) blank() asew='g1' pm=g1 elif b==3: print g2n2,'type the appropriate answer:' u1=raw_input() while len(u1)==0 or len(u1)>25: print 'INVALID Input' print g2n2,'type the appropriate answer:' u1=raw_input() if an_no in u1 : print 'Right Answer' print 'Team',g2,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g2',1) blank() asew='g1' pm=g1 else: print 'Sorry wrong answer' print 'Team',g1,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g1',1) blank() asew='g2' pm=g2 elif b==4: print g2n1,'type the appropriate answer:' u2=raw_input() while len(u2)==0 or len(u2)>25: print 'INVALID Input' print g2n2,'type the appropriate answer:' u2=raw_input() if an_no in u2 : print 'Right Answer' print 'Team',g2,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g2',1) blank() asew='g1' pm=g1 else: print 'Sorry wrong answer' print 'Team',g1,'get on to the play station' print 'Lets review the subjects' blank() asdf1('g1',1) blank() asew='g2' pm=g2 print 'So the right answer is-->' print an_no if asew ==g1: print 'Team',g2,',you can get back to your team station' print 'Team',g1,'get on to the play station' else: print 'Team',g1,',you can get back to your team station' print 'Team',g2,'get on to the play station' print 'Lets review the subjects' asdf1(asew,2) print 'So by the end of round 1 lets see the scores' print 'Team',g1,'-->',score1 print 'Team',g2,'-->',score2 if score1!=score2: qw=max( score1,score2) wq=min(score1,score2) if qw==score1: mnk=g1 mpk=g2 else : mnk=g2 mpk=g1 print mnk,'you are leading with',qw, 'Keep playing!!! ' print mpk,'don`t worry,you have earned',wq,'.One more round left.Keep playing!!!' else:print 'Team',g1,'and Team',g2,'you have earned a tie of', score1 blank() print 'Now lets play ROUND-2 --> KNOCK OUT ROUND' blank() print 'ADI MONA BUZZER for ROUND-2 --> KNOCK OUT ROUND' blank() rul2() print 'Best of luck!!!!' blank() print 'Guruji Question Please' print 'So your first question is.....' just=range(0,21) global just asdf2() blank() print 'Now your second question .....' asdf2() blank() print 'Here goes your third question.....' asdf2() blank() print 'Now your fourth question...' asdf2() blank() print 'And the final question of this round....' print 'Here goes it' asdf2() blank() print 'So by the end of Round 2, lets see your team scores' print 'Team',g1,'-->',score1,'Points' print 'Team',g2,'-->',score2,'Points' if score1!=score2: qw=max( score1,score2) wq=min(score1,score2) if qw==score1: mnk=g1 mpk=g2 else : mnk=g2 mpk=g1 print mnk,'you are leading with',qw, 'Keep playing!!! ' print 'So Team',mnk,'You are qualified for JACKPOT ROUND' print mpk,'don`t worry,you have earned',wq,'you have done your best!!!' else: print 'Team',g1,'and Team',g2,'you have earned a tie of', score1 print 'So lets have a TIE BREAK question for JACKPOT qualification' print 'So now lets play ROUND-3 JACKPOT ROUND' print 'ADI MONA BUZZER for ROUND-3 -->JACKPOT ROUND' blank() rul3() print 'Team',mnk,'get on to the play station' blank() asdf3() print 'So by the end of JACKPOT ROUND ,lets view the scores' print 'Team',g1,'--->',score1,'Points' print 'Team',g2,'--->',score2,'Points' if score1!=score2: qw=max( score1,score2) wq=min(score1,score2) if qw==score1: mnk=g1 mpk=g2 else : mnk=g2 mpk=g1 print 'Team',mnk,'you are leading with',qw print mpk,'don`t worry,you have earned',wq,'you have done your best!!!' blank() print'So today we had tough contestents' blank() print'They have cooperated with us well to provide the global a fruitful and enjoyable game' print 'Thank you all my contestents' blank() print 'Now I thank the holy GURUJI who have spreaded knowledge to us' blank() print'Last but not the least, I thank all the global malayalees' blank() print'My buddies sweet hearts ,love sky high and keep falling in love again and again and again' blank() print 'SO THERE COME TO END THIS ADI MONA BUZZER PROGRAM!!!' blank() print 'Thank you for your kind cooperation' blank() dfrew=raw_input('Would you like to drop a feedback to us?(y/n)') while dfrew!='y'and dfrew!='n': print 'INVALID input' dfrew=raw_input('Would you like to drop a feedback to us?(y/n)') if dfrew=='y': feedback=raw_input('Enter your feedback and name') target=open('feedback.txt',"w") target.write(feedback+"\n") print 'Thank you for your kind feedback' else:print 'Ok Thank You' blank() print 'I Amit signing off',',good bye' os.system("TASKKILL /F /IM wmplayer.exe") global mnk print '----------------------THE END--------------------------' asde=raw_input('Do you want to run the programme again?(y/n):') while asde!='y' and asde!='n': print'INVALID INPUT' asde=raw_input('Do you want to run the programme again?(y/n):') if asde=='y': from intro import* main() else: print 'Ok,Thank you' quit() def asdf2(): global score1 global score2 ran=choice(just) _just= sub2[ran] print _just just.remove(ran) bp=(raw_input('type 1,2,3,or 4 for player 1 player 2 player3 and player 4 respectively:')) while (bp not in ('1','2','3','4')) : print'INVALID input' bp=raw_input('type the right input:') bp=int(bp) an_n=('p',str(ran+1)) an_n=eval(''.join(an_n)) if bp==1: print g1n2,'type the appropriate answer:' s1=raw_input() while len(s1)==0 or len(s1)>25: print 'INVALID Input' print g1n2,'type the appropriate answer:' s1=raw_input() if an_n in s1 : print 'Right Answer' blank() score1=score1+4000 print 'Team',g1 ,'You get 4000 points' else: print 'Sorry wrong answer' blank() score1=score1-3000 blank() print 'Team',g1,'I am sorry,you get -3000 points' print 'Team',g1,'your current score is',score1 elif bp==2: print g1n1,'type the appropriate answer:' s2=raw_input() while len(s2)==0 or len(s2)>25: print 'INVALID Input' print g1n1,'type the appropriate answer:' s2=raw_input() if an_n in s2 : print 'Right Answer' blank() print 'Team',g1 ,'You get 4000 points' s1=score1+4000 else: print 'Sorry wrong answer' blank() score1=score1-3000 print 'Team',g1,'I am sorry,you get -3000 points' print 'Team',g1,'your current score is',score1 elif bp==3: print g2n2,'type the appropriate answer:' u1=raw_input() while len(u1)==0 or len(u1)>25: print 'INVALID Input' print g2n2,'type the appropriate answer:' u1=raw_input() if an_n in u1 : print 'Right Answer' blank() score2=score2+4000 print 'Team',g2 ,'You get 4000 points' else: print 'Sorry wrong answer' blank() score2=score2-3000 print 'Team',g2,'I am sorry,you get -3000 points' print 'Team',g2,'your current score is',score2 elif bp==4: print g2n1,'type the appropriate answer:' u2=raw_input() while len(u2)==0 or len(u2)>25: print 'INVALID Input' print g2n2,'type the appropriate answer:' u2=raw_input() if an_n in u2 : print 'Right Answer' blank() score2=score2+4000 print 'Team',g2 ,'You get 4000 points' else: print 'Sorry wrong answer' blank() score2=score2-3000 print 'Team',g2,'I am sorry,you get -3000 points' print 'Team',g2,'your current score is',score2 print 'So the right answer is-->' print an_n global sub2 def tb(): ran=choice(just) _just= sub2[ran] print _just sub2.remove(_just) bp=(raw_input('type 1,2,3,or 4 for player 1 player 2 player3 and player 4 respectively:')) while (bp not in ('1','2','3','4')) : print'INVALID input' bp=raw_input('type the right input:') bp=int(bp) an_n=('p',str(just+1)) an_n=eval(''.join(an_n)) if b==1: print g1n2,'type the appropriate answer:' s1=raw_input() while len(s1)==0 or len(s1)>25: print 'INVALID Input' print g1n2,'type the appropriate answer:' s1=raw_input() if an_no in s1 : print 'Right Answer' print 'Team',g1,'you are qualified for JACKPOT ROUND' print 'Team',g1,'get on to the play station' mnk=g1 else: print 'Sorry wrong answer' print 'Now,Team',g2,'you are qualified for JACKPOT ROUND' print 'Team',g2,'get on to the play station' mnk=g2 elif b==2: print g1n1,'type the appropriate answer:' s2=raw_input() while len(s2)==0 or len(s2)>25: print 'INVALID Input' print g1n1,'type the appropriate answer:' s2=raw_input() if an_no in s2 : print 'Right Answer' print 'Team',g1,'you are qualified for JACKPOT ROUND' print 'Team',g1,'get on to the play station' mnk=g1 else: print 'Sorry wrong answer' print 'Team',g2,'get on to the play station' mnk=g2 elif b==3: print g2n2,'type the appropriate answer:' u1=raw_input() while len(u1)==0 or len(u1)>25: print 'INVALID Input' print g2n2,'type the appropriate answer:' u1=raw_input() if an_no in u1 : print 'Right Answer' print 'Team',g2,'you are qualified for JACKPOT ROUND' print 'Team',g2,'get on to the play station' mnk=g2 else: print 'Sorry wrong answer' print 'Team',g1,'get on to the play station' mnk=g1 elif b==4: print g2n1,'type the appropriate answer:' u2=raw_input() while len(u2)==0 or len(u2)>25: print 'INVALID Input' print g2n2,'type the appropriate answer:' u2=raw_input() if an_no in u2 : print 'Right Answer' print 'Team',g2,'you are qualified for JACKPOT ROUND' print 'Team',g2,'get on to the play station' mnk=g2 else: print 'Sorry wrong answer' print 'Team',g1,'get on to the play station' mnk=g1 global mnk print 'So the right answer is-->' print an_n def asdf3(): print 'So lets see today`s subjects' blank() osub1('r3') blank() if mnk==g1: pl1=g1n1 pl2=g2n2 elif mnk==g2: pl1=g2n1 pl2=g2n2 cmos=[pl1,pl2] pq=choice(cmos) cmos.remove(pq) print pq,'Its your turn now' user_in=raw_input('Select the desired subject') while user_in not in ('1','2','3','4'): print 'INVALID input' user_in=raw_input('Select the desired subject') pas=(k1,k2,k3,k4) zz=pas zz1=int(user_in)-1 zz2=zz[zz1] print 'Guruji question please' print 'Which of the following are',zz2,'?' zz3=sub3.index(zz2) zz4=zz3+1 zz5=eval(''.join(('m',str(zz4)))) print zz5 global zz2 print 'Type the correct answer:' sln1=raw_input('sol1:') while sln1 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln1=raw_input('sol1:') sln2=raw_input('sol2:') while sln2 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln2=raw_input('sol2:') sln3=raw_input('sol3:') while sln3 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln3=raw_input('sol3:') sln4=raw_input('sol4:') while sln4 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln4=raw_input('sol4:') sln5=raw_input('sol5:') while sln5 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln5=raw_input('sol5:') print pq,'type "change" to change the solutions else proceed' cnf=raw_input() while (cnf !='change') and (cnf !=''): print 'INVALID input' print t1,'type "change" to change the solutions else proceed' cnf=raw_input() if cnf=='change': print 'retype the correct answers' sln1=raw_input('sol1:') while sln1 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln1=raw_input('sol1:') sln2=raw_input('sol2:') while sln2 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln2=raw_input('sol1:') sln3=raw_input('sol3:') while sln3 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln3=raw_input('sol1:') sln4=raw_input('sol4:') while sln4 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln4=raw_input('sol1:') sln5=raw_input('sol5:') while sln5 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sln5=raw_input('sol1:') lk=cmos[0] if cnf=='' or cnf=='change': blank() print lk,'its your turn.....' print lk,'type "change" to change the solutions else proceed' cnf1=raw_input() while (cnf1 !='change')and (cnf1 !=''): print 'INVALID input' print t2,'type "change" to change the solutions else proceed' cnf1=raw_input() if cnf1=='change': s=0 print 'retype the correct answers' sln1=raw_input('sol1:') while sLn1 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sLn1=raw_input('sol1:') sln2=raw_input('sol2:') while sLn2 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sLn1=raw_input('sol1:') sln3=raw_input('sol3:') while sLn3 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sLn1=raw_input('sol1:') sln4=raw_input('sol4:') while sLn4 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sLn1=raw_input('sol1:') sln5=raw_input('sol5:') while sln5 not in ('1','2','3','4','5','6','7','8','9','10'): print 'INVALID input' sLn1=raw_input('sol1:') if cnf1=='' or cnf1=='change': blank() print 'Now lets see to the answers','Dont be afraid!!!' xcv=[sln1,sln2,sln3,sln4,sln5] if cnf1=='' or cnf1=='change': for afgh in xcv: ast=zz5[(int(afgh))-1] if int(afgh)in (eval(''.join(('sol',str(zz4))))): print ast,'You have got it right' else:print 'I am Sorry',ast,'is wrong answer' kljh=(eval(''.join(('sol',str(zz4))))) print 'So the correct answers are--->' for asw in kljh: print zz5[asw-1] if sln1 in kljh and sln2 in kljh and sln3 in kljh and sln4 in kljh : print 'Team',mnk,'You have won a JACKPOT!!!!!!!!!!!!!!!!!' if mnk==g1: score1='JACKPOT +',score1 elif mnk==g2: score2='JACKPOT +',score2 print'-----------YA!HOOO!!!,YOU HAVE WON JACKPOT!,JACKPOT!!,JACKPOT!!!-----------' else:print 'I am sorry you have lost the JACKPOT ROUND' main()
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04b98009e7a3d9bca27a451c6b65771903ef34d0
6,239
py
Python
tests/test_require_org_member.py
PropelAuth/propelauth-fastapi
631bcfd923f25967214409ec8f87201096be9230
[ "MIT" ]
null
null
null
tests/test_require_org_member.py
PropelAuth/propelauth-fastapi
631bcfd923f25967214409ec8f87201096be9230
[ "MIT" ]
null
null
null
tests/test_require_org_member.py
PropelAuth/propelauth-fastapi
631bcfd923f25967214409ec8f87201096be9230
[ "MIT" ]
null
null
null
from datetime import timedelta from uuid import uuid4 from fastapi import Depends from starlette.responses import PlainTextResponse from tests.auth_helpers import create_access_token, orgs_to_org_id_map, random_org, random_user_id from tests.conftest import HTTP_BASE_AUTH_URL from propelauth_fastapi import UserRole ROUTE_NAME = "/require_org_member_route" def test_require_org_member_without_auth(app, auth, client, rsa_keys): create_route_expecting_user_and_org(app, auth, None, None, None) org_id = str(uuid4()) response = client.get(route_for(org_id)) assert response.status_code == 401 def test_require_org_member_with_auth_but_no_org_membership(app, auth, client, rsa_keys): create_route_expecting_user_and_org(app, auth, None, None, None) org_id = str(uuid4()) user_id = random_user_id() access_token = create_access_token({"user_id": user_id}, rsa_keys.private_pem) response = client.get(route_for(org_id), headers={"Authorization": "Bearer " + access_token}) assert response.status_code == 403 def test_require_org_member_with_auth_and_org_member(app, auth, client, rsa_keys): user_id = random_user_id() org = random_org("Owner") org_id_to_org_member_info = orgs_to_org_id_map([org]) create_route_expecting_user_and_org(app, auth, user_id, org, UserRole.Owner) access_token = create_access_token({ "user_id": user_id, "org_id_to_org_member_info": org_id_to_org_member_info }, rsa_keys.private_pem) response = client.get(route_for(org["org_id"]), headers={"Authorization": "Bearer " + access_token}) assert response.status_code == 200 assert response.text == "ok" def test_require_org_member_with_auth_but_wrong_org_id(app, auth, client, rsa_keys): user_id = random_user_id() org = random_org("Owner") org_id_to_org_member_info = orgs_to_org_id_map([org]) wrong_org_id = str(uuid4()) create_route_expecting_user_and_org(app, auth, user_id, org, UserRole.Owner) access_token = create_access_token({ "user_id": user_id, "org_id_to_org_member_info": org_id_to_org_member_info }, rsa_keys.private_pem) # Pass wrong org_id as a path parameter response = client.get(route_for(wrong_org_id), headers={"Authorization": "Bearer " + access_token}) assert response.status_code == 403 def test_require_org_member_with_auth_but_no_permission(app, auth, client, rsa_keys): user_id = random_user_id() org = random_org("Member") org_id_to_org_member_info = orgs_to_org_id_map([org]) create_route_expecting_user_and_org(app, auth, user_id, org, UserRole.Admin) access_token = create_access_token({ "user_id": user_id, "org_id_to_org_member_info": org_id_to_org_member_info }, rsa_keys.private_pem) response = client.get(route_for(org["org_id"]), headers={"Authorization": "Bearer " + access_token}) assert response.status_code == 403 def test_require_org_member_with_auth_with_permission(app, auth, client, rsa_keys): user_id = random_user_id() org = random_org("Admin") org_id_to_org_member_info = orgs_to_org_id_map([org]) create_route_expecting_user_and_org(app, auth, user_id, org, UserRole.Admin) access_token = create_access_token({ "user_id": user_id, "org_id_to_org_member_info": org_id_to_org_member_info }, rsa_keys.private_pem) response = client.get(route_for(org["org_id"]), headers={"Authorization": "Bearer " + access_token}) assert response.status_code == 200 assert response.text == "ok" def test_require_org_member_with_bad_header(app, auth, client, rsa_keys): create_route_expecting_user_and_org(app, auth, None, None, None) user_id = random_user_id() org = random_org("Admin") org_id_to_org_member_info = orgs_to_org_id_map([org]) access_token = create_access_token({ "user_id": user_id, "org_id_to_org_member_info": org_id_to_org_member_info }, rsa_keys.private_pem) response = client.get(route_for(org["org_id"]), headers={"Authorization": "token " + access_token}) assert response.status_code == 401 def test_require_org_member_with_wrong_token(app, auth, client, rsa_keys): create_route_expecting_user_and_org(app, auth, None, None, None) org_id = str(uuid4()) response = client.get(route_for(org_id), headers={"Authorization": "Bearer whatisthis"}) assert response.status_code == 401 def test_require_org_member_with_expired_token(app, auth, client, rsa_keys): user_id = random_user_id() org = random_org("Owner") org_id_to_org_member_info = orgs_to_org_id_map([org]) create_route_expecting_user_and_org(app, auth, user_id, org, UserRole.Owner) access_token = create_access_token({ "user_id": user_id, "org_id_to_org_member_info": org_id_to_org_member_info }, rsa_keys.private_pem, expires_in=timedelta(minutes=-1)) response = client.get(route_for(org["org_id"]), headers={"Authorization": "Bearer " + access_token}) assert response.status_code == 401 def test_require_user_with_bad_issuer(app, auth, client, rsa_keys): user_id = random_user_id() org = random_org("Owner") org_id_to_org_member_info = orgs_to_org_id_map([org]) create_route_expecting_user_and_org(app, auth, user_id, org, UserRole.Owner) access_token = create_access_token({ "user_id": user_id, "org_id_to_org_member_info": org_id_to_org_member_info }, rsa_keys.private_pem, issuer=HTTP_BASE_AUTH_URL) response = client.get(route_for(org["org_id"]), headers={"Authorization": "Bearer " + access_token}) assert response.status_code == 401 def create_route_expecting_user_and_org(app, auth, user_id, org, user_role): @app.get(ROUTE_NAME) async def route(org_id, current_user=Depends(auth.require_user)): current_org = auth.require_org_member(current_user, org_id, user_role) assert current_user.user_id == user_id assert current_org.org_id == org["org_id"] assert current_org.org_name == org["org_name"] assert current_org.user_role == user_role return PlainTextResponse("ok") def route_for(org_id): return ROUTE_NAME + "?org_id=" + org_id
36.91716
104
0.741946
955
6,239
4.369634
0.092147
0.062305
0.045291
0.050324
0.816439
0.787203
0.784807
0.784807
0.78313
0.770189
0
0.006835
0.155794
6,239
168
105
37.136905
0.785457
0.00593
0
0.663793
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0
0.087903
0.032258
0
0
0
0
0.137931
1
0.103448
false
0
0.060345
0.008621
0.181034
0
0
0
0
null
0
0
0
1
1
1
1
1
1
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0
0
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0
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0
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null
0
0
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0
0
0
0
0
0
0
0
0
0
6
04dbbb817466a90a9dede798d66c632f8c1fae56
147
py
Python
quizmous_api/version.py
szykol/quizmous-api
b33704701f258752bab0cddff44e7f357d6d5a99
[ "MIT" ]
4
2020-05-17T19:26:55.000Z
2021-12-04T17:58:17.000Z
quizmous_api/version.py
szykol/quizmous-api
b33704701f258752bab0cddff44e7f357d6d5a99
[ "MIT" ]
null
null
null
quizmous_api/version.py
szykol/quizmous-api
b33704701f258752bab0cddff44e7f357d6d5a99
[ "MIT" ]
null
null
null
from json import load def get_api_version(): with open('/usr/local/api/version.json', 'r') as version_file: return load(version_file)
24.5
66
0.70068
23
147
4.304348
0.695652
0.20202
0
0
0
0
0
0
0
0
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0
0.176871
147
5
67
29.4
0.818182
0
0
0
0
0
0.190476
0.183673
0
0
0
0
0
1
0.25
true
0
0.25
0
0.75
0
1
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0
null
1
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0
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0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
null
0
0
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0
0
1
1
0
0
0
1
0
0
6
b6f98dc527c7501d7e3880fb20d885cc038421f3
53
py
Python
PythonCrashCourse/3List/clip_test.py
dzylikecode/Python_Tutorial
bff425b11d6eeaa5733c1c710a570f83c52e4d97
[ "MIT" ]
null
null
null
PythonCrashCourse/3List/clip_test.py
dzylikecode/Python_Tutorial
bff425b11d6eeaa5733c1c710a570f83c52e4d97
[ "MIT" ]
null
null
null
PythonCrashCourse/3List/clip_test.py
dzylikecode/Python_Tutorial
bff425b11d6eeaa5733c1c710a570f83c52e4d97
[ "MIT" ]
null
null
null
list = [0, 1, 2, 3, 4, 5, 6, 7, 8] print(list[1:-1])
17.666667
34
0.45283
14
53
1.714286
0.785714
0
0
0
0
0
0
0
0
0
0
0.268293
0.226415
53
2
35
26.5
0.317073
0
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0
0
0
0.5
1
0
1
null
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
1
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
1
0
6
6d072f189ad7ba990ab26410eca98ffec6db6f31
29
py
Python
crawlino/modules/sources_module/__init__.py
BBVA/crawlino
685f57e6b3e9356484ead2681bb178f651d2f371
[ "Apache-2.0" ]
1
2018-11-11T21:07:54.000Z
2018-11-11T21:07:54.000Z
crawlino/modules/sources_module/__init__.py
BBVA/crawlino
685f57e6b3e9356484ead2681bb178f651d2f371
[ "Apache-2.0" ]
null
null
null
crawlino/modules/sources_module/__init__.py
BBVA/crawlino
685f57e6b3e9356484ead2681bb178f651d2f371
[ "Apache-2.0" ]
null
null
null
from .plugins_model import *
14.5
28
0.793103
4
29
5.5
1
0
0
0
0
0
0
0
0
0
0
0
0.137931
29
1
29
29
0.88
0
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
1
0
1
0
1
1
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
1
0
1
0
1
0
0
6
6d4588df711bf8609b1c23abeddd81d4f0629456
292
py
Python
Python/Strings/designer-door-mat.py
mateusnr/hackerrank-solutions
2fa60bae480d8afb46e3d99929707a7d9d92858f
[ "CC0-1.0" ]
1
2015-08-01T04:03:47.000Z
2015-08-01T04:03:47.000Z
Python/Strings/designer-door-mat.py
mateusnr/hackerrank-solutions
2fa60bae480d8afb46e3d99929707a7d9d92858f
[ "CC0-1.0" ]
null
null
null
Python/Strings/designer-door-mat.py
mateusnr/hackerrank-solutions
2fa60bae480d8afb46e3d99929707a7d9d92858f
[ "CC0-1.0" ]
4
2020-05-04T15:12:21.000Z
2021-02-18T11:58:30.000Z
N, M = map(int,input().split()) for i in range(1,N,2): print('-' * int((M-(3*i))/2) + i*'.|.' + '-' * int((M-(3*i))/2)) print('-' * int((M-7)/2) + "WELCOME" + '-' * int((M-7)/2)) for i in range(N-2,-1,-2): print('-' * int((M - (3 * i)) / 2) + i * '.|.' + '-' * int((M - (3 * i)) / 2))
48.666667
82
0.380137
55
292
2.018182
0.290909
0.216216
0.18018
0.216216
0.378378
0.378378
0.378378
0.378378
0.378378
0.378378
0
0.073276
0.205479
292
6
82
48.666667
0.405172
0
0
0.333333
0
0
0.064846
0
0
0
0
0
0
1
0
false
0
0
0
0
0.5
0
0
0
null
1
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
1
0
6
b65a8e8dd9515dcfca09370480910afbd6d840cc
19
py
Python
bayesian_networks_intro.py
https-seyhan/Bayesian-Networks
bf69e2cf52eba37ffea5596b767454899422bd9f
[ "MIT" ]
null
null
null
bayesian_networks_intro.py
https-seyhan/Bayesian-Networks
bf69e2cf52eba37ffea5596b767454899422bd9f
[ "MIT" ]
null
null
null
bayesian_networks_intro.py
https-seyhan/Bayesian-Networks
bf69e2cf52eba37ffea5596b767454899422bd9f
[ "MIT" ]
null
null
null
import pymc3 as pm
9.5
18
0.789474
4
19
3.75
1
0
0
0
0
0
0
0
0
0
0
0.066667
0.210526
19
1
19
19
0.933333
0
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
1
0
1
0
1
1
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
1
0
1
0
1
0
0
6
b667077f312cf39b99ae8493d597f29204857a42
126
py
Python
mcetl/cli_utils/__init__.py
materials-commons/pymcetl
b4311ba50bb35bc36527b9d313a91778f9550a92
[ "MIT" ]
null
null
null
mcetl/cli_utils/__init__.py
materials-commons/pymcetl
b4311ba50bb35bc36527b9d313a91778f9550a92
[ "MIT" ]
null
null
null
mcetl/cli_utils/__init__.py
materials-commons/pymcetl
b4311ba50bb35bc36527b9d313a91778f9550a92
[ "MIT" ]
null
null
null
try: from pathlib import Path Path().expanduser() except (ImportError, AttributeError): from pathlib2 import Path
21
37
0.722222
14
126
6.5
0.714286
0.21978
0
0
0
0
0
0
0
0
0
0.009901
0.198413
126
5
38
25.2
0.891089
0
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
0.6
0
0.6
0
1
0
0
null
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
1
0
1
0
1
0
0
6
b686af997b0efadf779a323fd3ef06eed8d7c64f
143
py
Python
azure/cognitive/Emotion.py
crwilcox/MicrosoftCognitive
62913e9c6d04d0b698d4b548c517cea07396eaf3
[ "Apache-2.0" ]
null
null
null
azure/cognitive/Emotion.py
crwilcox/MicrosoftCognitive
62913e9c6d04d0b698d4b548c517cea07396eaf3
[ "Apache-2.0" ]
null
null
null
azure/cognitive/Emotion.py
crwilcox/MicrosoftCognitive
62913e9c6d04d0b698d4b548c517cea07396eaf3
[ "Apache-2.0" ]
null
null
null
raise NotImplementedError("Not Implemented. Jupyter Notebooks on these APIs are here: https://github.com/Microsoft/Cognitive-Emotion-Python ")
71.5
142
0.818182
18
143
6.5
1
0
0
0
0
0
0
0
0
0
0
0
0.083916
143
1
143
143
0.89313
0
0
0
0
1
0.79021
0
0
0
0
0
0
1
0
true
0
0
0
0
0
1
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
1
1
0
null
0
0
0
0
0
0
1
0
0
0
0
0
0
6
b6a3482ded0b1416ab665e9ddc374c24d4db10ed
197
py
Python
subject/contrib/plugins/artifacts_sample/__init__.py
laoyigrace/subject
e6ed989fdc250917a19788112b22322b73b3550f
[ "Apache-2.0" ]
null
null
null
subject/contrib/plugins/artifacts_sample/__init__.py
laoyigrace/subject
e6ed989fdc250917a19788112b22322b73b3550f
[ "Apache-2.0" ]
null
null
null
subject/contrib/plugins/artifacts_sample/__init__.py
laoyigrace/subject
e6ed989fdc250917a19788112b22322b73b3550f
[ "Apache-2.0" ]
null
null
null
from subject.contrib.plugins.artifacts_sample.v1 import artifact as art1 from subject.contrib.plugins.artifacts_sample.v2 import artifact as art2 MY_ARTIFACT = [art1.MyArtifact, art2.MyArtifact]
32.833333
72
0.837563
28
197
5.785714
0.535714
0.135802
0.222222
0.308642
0.493827
0.493827
0
0
0
0
0
0.03352
0.091371
197
5
73
39.4
0.871508
0
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0.666667
0
0.666667
0
1
0
0
null
0
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
1
0
1
0
0
6
fcc7975a3e747f5bd52d538e404d99777f6c893c
180
py
Python
tests/extract_method/test_9.py
Amin-MAG/CodART
a964a506d031f6eea505df081b9ba946f490d021
[ "MIT" ]
1
2021-10-10T23:56:49.000Z
2021-10-10T23:56:49.000Z
tests/extract_method/test_9.py
Amin-MAG/CodART
a964a506d031f6eea505df081b9ba946f490d021
[ "MIT" ]
null
null
null
tests/extract_method/test_9.py
Amin-MAG/CodART
a964a506d031f6eea505df081b9ba946f490d021
[ "MIT" ]
1
2021-08-21T11:25:49.000Z
2021-08-21T11:25:49.000Z
""" extracting lines containing method calls test status: failed """ from refactorings.extract_method import extract_method import os import errno def main(): pass
12.857143
54
0.733333
22
180
5.909091
0.772727
0.2
0.292308
0
0
0
0
0
0
0
0
0
0.205556
180
13
55
13.846154
0.909091
0.338889
0
0
0
0
0
0
0
0
0
0
0
1
0.2
true
0.2
0.6
0
0.8
0
1
0
0
null
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
1
1
1
0
1
0
0
6
1e125e069951aa5943282e8630e9541ec6266a68
9,024
py
Python
openstackinabox/tests/services/keystone/v2/user/test_update.py
BenjamenMeyer/openstackinabox
b5097695719b818dd06e3773899f80a15e7e71c1
[ "Apache-2.0" ]
1
2017-11-19T20:31:48.000Z
2017-11-19T20:31:48.000Z
openstackinabox/tests/services/keystone/v2/user/test_update.py
TestInABox/openstackinabox
00dcac601d14e1cfc240840dd92895ee322caf96
[ "Apache-2.0" ]
38
2016-05-05T18:03:21.000Z
2020-04-11T03:33:01.000Z
openstackinabox/tests/services/keystone/v2/user/test_update.py
BenjamenMeyer/openstackinabox
b5097695719b818dd06e3773899f80a15e7e71c1
[ "Apache-2.0" ]
1
2015-05-28T14:53:46.000Z
2015-05-28T14:53:46.000Z
""" Stack-In-A-Box: Basic Test """ import json import unittest import requests import stackinabox.util.requests_mock.core from stackinabox.stack import StackInABox from openstackinabox.services.keystone import KeystoneV2Service class TestKeystoneV2UserUpdate(unittest.TestCase): def setUp(self): super(TestKeystoneV2UserUpdate, self).setUp() self.keystone = KeystoneV2Service() self.headers = { 'x-auth-token': self.keystone.model.tokens.admin_token } self.tenant_id = self.keystone.model.tenants.add( tenant_name='neo', description='The One' ) self.user_info = { 'user': { 'username': 'trinity', 'enabled': True, 'email': 'trinity@theone.matrix', 'OS-KSADM:password': 'Inl0veWithNeo' } } self.user_info['user']['userid'] = self.keystone.model.users.add( tenant_id=self.tenant_id, username=self.user_info['user']['username'], email=self.user_info['user']['email'], password=self.user_info['user']['OS-KSADM:password'], enabled=self.user_info['user']['enabled'] ) self.keystone.model.tokens.add( tenant_id=self.tenant_id, user_id=self.user_info['user']['userid'] ) StackInABox.register_service(self.keystone) def tearDown(self): super(TestKeystoneV2UserUpdate, self).tearDown() StackInABox.reset_services() def test_user_update_no_token(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') json_data = json.dumps(self.user_info) res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), data=json_data) self.assertEqual(res.status_code, 403) def test_user_update_invalid_token(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') json_data = json.dumps(self.user_info) self.headers['x-auth-token'] = 'new_token' res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), headers=self.headers, data=json_data) self.assertEqual(res.status_code, 401) def test_user_update_no_user(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') user_data = self.keystone.model.tokens.get_by_user_id( self.user_info['user']['userid']) self.headers['x-auth-token'] = user_data['token'] res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), headers=self.headers, data=json.dumps({'family': {}})) self.assertEqual(res.status_code, 400) def test_user_update_no_user_id(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost' ) user_data = self.keystone.model.tokens.get_by_user_id( self.user_info['user']['userid'] ) self.headers['x-auth-token'] = user_data['token'] res = requests.post( 'http://localhost/keystone/v2.0/users/{0}'.format( self.user_info['user']['userid'] ), headers=self.headers, data=json.dumps({'user': {}}) ) self.assertEqual(res.status_code, 400) def test_user_update_invalid_user_id(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') user_data = self.keystone.model.tokens.get_by_user_id( self.user_info['user']['userid']) self.headers['x-auth-token'] = user_data['token'] self.user_info['user']['userid'] = '1234567890' self.user_info['user']['email'] = 'trinity@lost.matrix' self.user_info['user']['id'] = self.user_info['user']['userid'] self.user_info['user']['enabled'] = False self.user_info['user']['OS-KSADM:password'] = 'neocortex' res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), headers=self.headers, data=json.dumps(self.user_info)) self.assertEqual(res.status_code, 404) def test_user_update(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') user_data = self.keystone.model.tokens.get_by_user_id( self.user_info['user']['userid']) self.headers['x-auth-token'] = user_data['token'] self.user_info['user']['email'] = 'trinity@lost.matrix' self.user_info['user']['id'] = self.user_info['user']['userid'] self.user_info['user']['enabled'] = False self.user_info['user']['OS-KSADM:password'] = 'neocortex' res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), headers=self.headers, data=json.dumps(self.user_info)) self.assertEqual(res.status_code, 200) def test_user_update_no_enabled(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') user_data = self.keystone.model.tokens.get_by_user_id( self.user_info['user']['userid']) self.headers['x-auth-token'] = user_data['token'] self.user_info['user']['email'] = 'trinity@lost.matrix' self.user_info['user']['id'] = self.user_info['user']['userid'] del self.user_info['user']['enabled'] self.user_info['user']['OS-KSADM:password'] = 'neocortex' res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), headers=self.headers, data=json.dumps(self.user_info)) self.assertEqual(res.status_code, 200) def test_user_update_no_email(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') user_data = self.keystone.model.tokens.get_by_user_id( self.user_info['user']['userid']) self.headers['x-auth-token'] = user_data['token'] del self.user_info['user']['email'] self.user_info['user']['id'] = self.user_info['user']['userid'] self.user_info['user']['enabled'] = False self.user_info['user']['OS-KSADM:password'] = 'neocortex' res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), headers=self.headers, data=json.dumps(self.user_info)) self.assertEqual(res.status_code, 200) def test_user_update_no_password(self): with stackinabox.util.requests_mock.core.activate(): stackinabox.util.requests_mock.core.requests_mock_registration( 'localhost') user_data = self.keystone.model.tokens.get_by_user_id( self.user_info['user']['userid']) self.headers['x-auth-token'] = user_data['token'] self.user_info['user']['email'] = 'trinity@lost.matrix' self.user_info['user']['id'] = self.user_info['user']['userid'] self.user_info['user']['enabled'] = False del self.user_info['user']['OS-KSADM:password'] res = requests.post('http://localhost/keystone/v2.0/users/{0}' .format(self.user_info['user']['userid']), headers=self.headers, data=json.dumps(self.user_info)) self.assertEqual(res.status_code, 200)
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6
1e7952c2f8bcfb01e23c83ef5580af74e47174fb
19
py
Python
clib/__init__.py
bracca95/Probabilistic-Face-Embeddings
3a4ae6f5e7b0287dbba55f14618cbfaf7ccb7b41
[ "MIT" ]
312
2019-04-22T03:29:27.000Z
2022-03-30T07:29:04.000Z
clib/__init__.py
guanfangdong/Probabilistic-Face-Embeddings
23191e9b068dbf495a37daa071a1383f12f2799b
[ "MIT" ]
15
2019-04-28T20:57:46.000Z
2021-10-13T07:26:55.000Z
clib/__init__.py
guanfangdong/Probabilistic-Face-Embeddings
23191e9b068dbf495a37daa071a1383f12f2799b
[ "MIT" ]
57
2019-04-23T02:38:07.000Z
2022-03-21T13:05:06.000Z
from .mls import *
9.5
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6
1ebbc67bb522a03771db9858ec68b68ddccdf463
257
py
Python
trees/tssb/__init__.py
islamazhar/trees
502565c5bf02503c7bece09cddd93f9368da02c3
[ "MIT" ]
null
null
null
trees/tssb/__init__.py
islamazhar/trees
502565c5bf02503c7bece09cddd93f9368da02c3
[ "MIT" ]
null
null
null
trees/tssb/__init__.py
islamazhar/trees
502565c5bf02503c7bece09cddd93f9368da02c3
[ "MIT" ]
null
null
null
from trees.tssb.tssb import TSSB from trees.tssb.itssb import InteractiveTSSB from trees.tssb.gibbs import GibbsSampler from trees.tssb.parameter import GaussianParameterProcess from trees.tssb.df import DepthFunction, QuadraticDepth import trees.tssb.util
36.714286
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6
9493617586973d6676a50a84d7aa4061b3d71aec
114
py
Python
atlas/providers/env.py
citruspi/Atlas
ae9d47e7410e7bb50b8891e6cbe1803620f46588
[ "Unlicense" ]
null
null
null
atlas/providers/env.py
citruspi/Atlas
ae9d47e7410e7bb50b8891e6cbe1803620f46588
[ "Unlicense" ]
null
null
null
atlas/providers/env.py
citruspi/Atlas
ae9d47e7410e7bb50b8891e6cbe1803620f46588
[ "Unlicense" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf8 -*- import os def env(variable): return os.environ.get(variable)
11.4
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0
0
1
1
1
0
0
6
44f4a198ac8866b45cb790c1bbd52360070ab988
165
py
Python
test1.py
ytyaru/Python.pylangstudy.Subjects.Data.Partial.201705221751
fd63dd3b7c0e1151365a1c66d32cc15d8c699916
[ "CC0-1.0" ]
null
null
null
test1.py
ytyaru/Python.pylangstudy.Subjects.Data.Partial.201705221751
fd63dd3b7c0e1151365a1c66d32cc15d8c699916
[ "CC0-1.0" ]
null
null
null
test1.py
ytyaru/Python.pylangstudy.Subjects.Data.Partial.201705221751
fd63dd3b7c0e1151365a1c66d32cc15d8c699916
[ "CC0-1.0" ]
null
null
null
def Dict1(): return {'key1': 'value1'} def Dict2(): return {'key2': 'value1'} # print(Dict1().update(Dict2())) # None d = Dict1() d.update(Dict2()) print(d)
18.333333
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4.409091
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0.163636
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8
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6
781153a4c14bf8e15626011bb1b33fe4dddcd3d6
141
py
Python
SimPEG/utils/meshutils.py
prisae/simpeg
5cdd1b496bddcf3d9acd714b901a57bad6fb1ef9
[ "MIT" ]
3
2021-08-04T02:27:41.000Z
2022-01-12T00:20:07.000Z
SimPEG/utils/meshutils.py
thast/simpeg
8021082b8b53f3c08fa87fc085547bdd56437c6b
[ "MIT" ]
2
2020-06-16T00:11:37.000Z
2020-07-10T19:45:09.000Z
SimPEG/utils/meshutils.py
thast/simpeg
8021082b8b53f3c08fa87fc085547bdd56437c6b
[ "MIT" ]
1
2021-12-29T00:06:07.000Z
2021-12-29T00:06:07.000Z
from .code_utils import deprecate_module deprecate_module("meshutils", "mesh_utils", "0.16.0", future_warn=True) from .mesh_utils import *
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6
7821f2a895ed1e8f9878313a8ef1a8553a2f9dd9
163
py
Python
app/auth/__init__.py
luxutao/staffms
6fe2a263fca4a817fbd18965327bd8ad5326dc6b
[ "Apache-2.0" ]
1
2019-12-25T11:11:33.000Z
2019-12-25T11:11:33.000Z
app/auth/__init__.py
luxutao/staffms
6fe2a263fca4a817fbd18965327bd8ad5326dc6b
[ "Apache-2.0" ]
null
null
null
app/auth/__init__.py
luxutao/staffms
6fe2a263fca4a817fbd18965327bd8ad5326dc6b
[ "Apache-2.0" ]
null
null
null
#!/usr/local/bin/python3 # -*- conding: utf-8 -*- from flask import Blueprint auth_api = Blueprint('auth', __name__, url_prefix='/api/auth') from . import views
20.375
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0
1
0
1
1
0
6
788b6c2d64fc46b3979208b77756c41de2149fb3
261
py
Python
Python/04/Py04_03.py
Pantoofle/Language-Practice
f5d4b3f5eb745f0e9abf50f2ddb08fd902225f07
[ "MIT" ]
null
null
null
Python/04/Py04_03.py
Pantoofle/Language-Practice
f5d4b3f5eb745f0e9abf50f2ddb08fd902225f07
[ "MIT" ]
null
null
null
Python/04/Py04_03.py
Pantoofle/Language-Practice
f5d4b3f5eb745f0e9abf50f2ddb08fd902225f07
[ "MIT" ]
null
null
null
#! /usr/bin/env python3 x = 2.21 print(str(x), "Gigowatts !!!", str(x), "Gigowatts !! Nom de Zeus ! Marty !") print("%s Gigowatts !!! %s Gigowatts !! Nom de Zeus ! Marty !" %(x, x)) print("{} Gigowatts !!! {} Gigowatts !! Nom de Zeus ! Marty !".format(x, x))
32.625
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0.578544
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261
3.871795
0.410256
0.238411
0.278146
0.357616
0.456954
0
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0
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0.018692
0.180077
261
7
77
37.285714
0.686916
0.084291
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1
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false
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null
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0
0
0
0
1
0
6
78c3a2c3801c686e3f64453a63ceafc93bc89b29
812
py
Python
src/gelanis/sql/_expressions/aggregate/aggregations.py
svaningelgem/gelanis
12360ead579816e5a2764dc9f995449bacf67ecc
[ "Apache-2.0" ]
1
2021-07-30T11:23:43.000Z
2021-07-30T11:23:43.000Z
src/gelanis/sql/_expressions/aggregate/aggregations.py
svaningelgem/gelanis
12360ead579816e5a2764dc9f995449bacf67ecc
[ "Apache-2.0" ]
3
2021-03-05T14:45:38.000Z
2021-03-10T16:19:38.000Z
src/gelanis/sql/_expressions/aggregate/aggregations.py
svaningelgem/gelanis
12360ead579816e5a2764dc9f995449bacf67ecc
[ "Apache-2.0" ]
1
2021-03-17T19:43:05.000Z
2021-03-17T19:43:05.000Z
from .. import Expression from ...types import ArrayType class Aggregation(Expression): @property def is_an_aggregation(self): return True def merge(self, row, schema): raise NotImplementedError def mergeStats(self, other, schema): raise NotImplementedError def eval(self, row, schema): raise NotImplementedError def args(self): raise NotImplementedError def data_type(self, schema): # TODO: Check if we can generalize this. By default, this should be fine, but needs to be overridden in each # subclass where it deviates from this standard. # pylint: disable=E1101 return ArrayType( elementType=schema[str(self.column)].dataType, containsNull=self.column.is_nullable )
27.066667
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92
812
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0.619565
0.180451
0.203008
0.18609
0.150376
0.150376
0
0
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0
0
0.006745
0.269704
812
29
117
28
0.890388
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0.210526
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1
0.315789
false
0
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0.105263
0.578947
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null
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null
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1
0
0
1
0
0
0
1
1
0
0
6
1531fd8a220b7ae58756e479981c53b088532678
110
py
Python
visualization/utils.py
hemiku/Visualization
b21bfc738278c1ce8f2df52e41230dcd58c8913e
[ "MIT" ]
null
null
null
visualization/utils.py
hemiku/Visualization
b21bfc738278c1ce8f2df52e41230dcd58c8913e
[ "MIT" ]
1
2022-02-20T12:37:19.000Z
2022-02-20T12:37:19.000Z
visualization/utils.py
hemiku/Visualization
b21bfc738278c1ce8f2df52e41230dcd58c8913e
[ "MIT" ]
null
null
null
def letters( input): return ''.join(filter(str.isalpha, input)) def strip_input_name( input ): return
22
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0.690909
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110
4.933333
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110
5
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null
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0
1
1
0
0
6
1543094846a6d68b30a0f9477428ed13a96860d0
117
py
Python
rpd/factories/__init__.py
ooliver1/RPD
e4900eed75ee636385749b883fe63e1cb48d81bd
[ "MIT" ]
null
null
null
rpd/factories/__init__.py
ooliver1/RPD
e4900eed75ee636385749b883fe63e1cb48d81bd
[ "MIT" ]
null
null
null
rpd/factories/__init__.py
ooliver1/RPD
e4900eed75ee636385749b883fe63e1cb48d81bd
[ "MIT" ]
null
null
null
""" rpd.factories ~~~~~~~~~~~~~ Factory Module for RPD. """ from .event_factory import * from .rest_factory import *
14.625
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117
5.285714
0.642857
0.351351
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0.136752
117
7
29
16.714286
0.732673
0.435897
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1
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0
6
154c05f9fb11353a8fc87e83851f5359f0313358
112
py
Python
lang/py/cookbook/v2/source/cb2_11_15_exm_1.py
ch1huizong/learning
632267634a9fd84a5f5116de09ff1e2681a6cc85
[ "MIT" ]
null
null
null
lang/py/cookbook/v2/source/cb2_11_15_exm_1.py
ch1huizong/learning
632267634a9fd84a5f5116de09ff1e2681a6cc85
[ "MIT" ]
null
null
null
lang/py/cookbook/v2/source/cb2_11_15_exm_1.py
ch1huizong/learning
632267634a9fd84a5f5116de09ff1e2681a6cc85
[ "MIT" ]
null
null
null
# jythonc -w C:\ImageJ\plugins\Jython -C C:\ImageJ\jikes -J "-bootclasspath C:\ImageJ\jre\lib\rt.jar -nowarn"
37.333333
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112
4.157895
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112
2
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56
0.79
0.482143
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0.428571
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0
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0
0
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0
0
0
6
156f5e23167ce4f7b01f9c8ef4c3bd0d428f1aa3
164
py
Python
scripts/mlp/centroidal/muscod.py
stonneau/multicontact-locomotion-planning
a2c5dd35955a44c5a454d114c9dcaf0fec19424f
[ "BSD-2-Clause" ]
null
null
null
scripts/mlp/centroidal/muscod.py
stonneau/multicontact-locomotion-planning
a2c5dd35955a44c5a454d114c9dcaf0fec19424f
[ "BSD-2-Clause" ]
null
null
null
scripts/mlp/centroidal/muscod.py
stonneau/multicontact-locomotion-planning
a2c5dd35955a44c5a454d114c9dcaf0fec19424f
[ "BSD-2-Clause" ]
null
null
null
import mlp.config as cfg def generateCentroidalTrajectory(cs, cs_initGuess=None, fullBody=None, viewer=None, first_iter = True): raise NotImplemented("TODO")
27.333333
103
0.780488
21
164
6
0.857143
0
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0
0
0
0.121951
164
5
104
32.8
0.875
0
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0
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0.333333
false
0
0.333333
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null
0
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0
0
1
0
1
0
0
6
159bab273e13b63b6ad11de09064927878b70d09
7,240
py
Python
plugin_kube/__init__.py
DNXLabs/plugin-kube
1c674dd6b5dd8f809bd1b0932c8e22773522556a
[ "Apache-2.0" ]
null
null
null
plugin_kube/__init__.py
DNXLabs/plugin-kube
1c674dd6b5dd8f809bd1b0932c8e22773522556a
[ "Apache-2.0" ]
null
null
null
plugin_kube/__init__.py
DNXLabs/plugin-kube
1c674dd6b5dd8f809bd1b0932c8e22773522556a
[ "Apache-2.0" ]
null
null
null
import click from one.one import cli from one.docker.container import Container from one.docker.image import Image from one.utils.environment.aws import EnvironmentAws from one.utils.config import get_config_value container = Container() image = Image() environment = EnvironmentAws() AWS_IMAGE = image.get_image('aws') KUBE_TOOLS_IMAGE = 'dnxsolutions/docker-kube-tools:0.3.2' def __init__(): cli.add_command(kubectl) cli.add_command(helm) cli.add_command(kube_shell) cli.add_command(kube_proxy) def get_kube_config(aws_default_region, cluster_name, envs): kubeconfig = get_config_value('plugins.kube.parameters.kubeconfig', '') or '/work/.kube-config' command = 'eks --region %s update-kubeconfig --name %s --kubeconfig %s' % (aws_default_region, cluster_name, kubeconfig) container.create( image=AWS_IMAGE, command=command, volumes=['.:/work'], environment=envs ) @click.command(name='kubectl', help='Kubectl wrap command entry.') @click.argument('args', nargs=-1) @click.option('-n', '--cluster-name', 'cluster_name', default=None, type=str, help='AWS EKS cluster name.') @click.option('-w', '--workspace', default=None, type=str, help='Workspace to use.') @click.option('-r', '--aws-role', 'aws_role', default=None, type=str, help='AWS role to use.') @click.option('-a', '--aws-assume-role', 'aws_assume_role', default=None, type=str, help='AWS assume role.') @click.option('-R', '--aws-default-region', 'aws_default_region', default=None, type=str, help='AWS default region to use.') def kubectl(args, cluster_name, workspace, aws_role, aws_assume_role, aws_default_region): cluster_name = cluster_name or get_config_value('plugins.kube.parameters.cluster_name') aws_default_region = aws_default_region or get_config_value('plugins.kube.parameters.aws_default_region') aws_assume_role = aws_assume_role or get_config_value('plugins.kube.parameters.aws_assume_role', 'false') envs = environment.build(workspace=workspace, aws_role=aws_role, aws_assume_role=aws_assume_role).get_env() envs['KUBECONFIG'] = get_config_value('plugins.kube.parameters.kubeconfig', '') or '/work/.kube-config' get_kube_config(aws_default_region, cluster_name, envs) entrypoint = 'kubectl' command = '' for arg in args: command += '%s ' % (arg) container.create( image=KUBE_TOOLS_IMAGE, command=command, entrypoint=entrypoint, volumes=['.:/work'], environment=envs ) @click.command(name='helm', help='Helm wrap command entry.') @click.argument('args', nargs=-1) @click.option('-n', '--cluster-name', 'cluster_name', default=None, type=str, help='AWS EKS cluster name.') @click.option('-w', '--workspace', default=None, type=str, help='Workspace to use.') @click.option('-r', '--aws-role', 'aws_role', default=None, type=str, help='AWS role to use.') @click.option('-a', '--aws-assume-role', 'aws_assume_role', default=None, type=str, help='AWS assume role.') @click.option('-R', '--aws-default-region', 'aws_default_region', default=None, type=str, help='AWS default region to use.') def helm(args, cluster_name, workspace, aws_role, aws_assume_role, aws_default_region): cluster_name = cluster_name or get_config_value('plugins.kube.parameters.cluster_name') aws_default_region = aws_default_region or get_config_value('plugins.kube.parameters.aws_default_region') aws_assume_role = aws_assume_role or get_config_value('plugins.kube.parameters.aws_assume_role', 'false') envs = environment.build(workspace=workspace, aws_role=aws_role, aws_assume_role=aws_assume_role).get_env() envs['KUBECONFIG'] = get_config_value('plugins.kube.parameters.kubeconfig', '') or '/work/.kube-config' get_kube_config(aws_default_region, cluster_name, envs) entrypoint = 'helm' command = '' for arg in args: command += '%s ' % (arg) container.create( image=KUBE_TOOLS_IMAGE, command=command, entrypoint=entrypoint, volumes=['.:/work'], environment=envs ) @click.command(name='kube-shell', help='Shell entry to EKS environment.') @click.option('-n', '--cluster-name', 'cluster_name', default=None, type=str, help='AWS EKS cluster name.') @click.option('-w', '--workspace', default=None, type=str, help='Workspace to use.') @click.option('-r', '--aws-role', 'aws_role', default=None, type=str, help='AWS role to use.') @click.option('-a', '--aws-assume-role', 'aws_assume_role', default=None, type=str, help='AWS assume role.') @click.option('-R', '--aws-default-region', 'aws_default_region', default=None, type=str, help='AWS default region to use.') def kube_shell(cluster_name, workspace, aws_role, aws_assume_role, aws_default_region): cluster_name = cluster_name or get_config_value('plugins.kube.parameters.cluster_name') aws_default_region = aws_default_region or get_config_value('plugins.kube.parameters.aws_default_region') aws_assume_role = aws_assume_role or get_config_value('plugins.kube.parameters.aws_assume_role', 'false') envs = environment.build(workspace=workspace, aws_role=aws_role, aws_assume_role=aws_assume_role).get_env() envs['KUBECONFIG'] = get_config_value('plugins.kube.parameters.kubeconfig', '') or '/work/.kube-config' get_kube_config(aws_default_region, cluster_name, envs) entrypoint = '/bin/bash' container.create( image=KUBE_TOOLS_IMAGE, entrypoint=entrypoint, ports=['8001:8001'], volumes=['.:/work'], environment=envs ) @click.command(name='kube-proxy', help='Proxy entry to EKS environment.') @click.option('-n', '--cluster-name', 'cluster_name', default=None, type=str, help='AWS EKS cluster name.') @click.option('-w', '--workspace', default=None, type=str, help='Workspace to use.') @click.option('-r', '--aws-role', 'aws_role', default=None, type=str, help='AWS role to use.') @click.option('-a', '--aws-assume-role', 'aws_assume_role', default=None, type=str, help='AWS assume role.') @click.option('-R', '--aws-default-region', 'aws_default_region', default=None, type=str, help='AWS default region to use.') @click.option('-p', '--port', 'port', default='8001:8001', type=str, help='Proxy port to expose.') def kube_proxy(cluster_name, workspace, aws_role, aws_assume_role, aws_default_region, port): cluster_name = cluster_name or get_config_value('plugins.kube.parameters.cluster_name') aws_default_region = aws_default_region or get_config_value('plugins.kube.parameters.aws_default_region') aws_assume_role = aws_assume_role or get_config_value('plugins.kube.parameters.aws_assume_role', 'false') envs = environment.build(workspace=workspace, aws_role=aws_role, aws_assume_role=aws_assume_role).get_env() envs['KUBECONFIG'] = get_config_value('plugins.kube.parameters.kubeconfig', '') or '/work/.kube-config' get_kube_config(aws_default_region, cluster_name, envs) entrypoint = 'kubectl' command = 'proxy --address 0.0.0.0 --port %s' % port.split(":")[1] container.create( image=KUBE_TOOLS_IMAGE, entrypoint=entrypoint, command=command, ports=[port], volumes=['.:/work'], environment=envs )
50.277778
124
0.715331
1,003
7,240
4.939182
0.079761
0.065402
0.094469
0.072669
0.8478
0.84235
0.84235
0.833872
0.801978
0.793904
0
0.004126
0.129558
7,240
143
125
50.629371
0.781974
0
0
0.675
0
0
0.292127
0.093094
0
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0
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0.05
false
0
0.05
0
0.1
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null
0
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1
1
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0
0
0
0
0
0
0
6
159c652139885ce492019dbb08e43f59fbd4718f
19
py
Python
bad/listOutOfBounds.py
Alberto42/Interpreter
a56c4d905672572734a8470ef607b66727489f15
[ "BSD-3-Clause" ]
null
null
null
bad/listOutOfBounds.py
Alberto42/Interpreter
a56c4d905672572734a8470ef607b66727489f15
[ "BSD-3-Clause" ]
null
null
null
bad/listOutOfBounds.py
Alberto42/Interpreter
a56c4d905672572734a8470ef607b66727489f15
[ "BSD-3-Clause" ]
null
null
null
l = [0] print(l[1])
9.5
11
0.473684
5
19
1.8
0.8
0
0
0
0
0
0
0
0
0
0
0.125
0.157895
19
2
11
9.5
0.4375
0
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0
0
0
0.5
1
1
1
null
0
0
0
0
0
0
0
0
0
0
0
0
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1
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0
1
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
1
0
6
ec7bf5524ae0b7edeed7e6a2ecd35d8c77cb0f33
218
py
Python
src/myexceptions.py
delete/spymanager
c5886141000ad8b6b8e7c8ae6bc2ad631da33c72
[ "MIT" ]
7
2017-02-01T00:34:30.000Z
2022-01-28T22:05:14.000Z
src/myexceptions.py
delete/spymanager
c5886141000ad8b6b8e7c8ae6bc2ad631da33c72
[ "MIT" ]
8
2017-01-08T21:06:43.000Z
2020-10-18T13:20:13.000Z
src/myexceptions.py
delete/spylist
c5886141000ad8b6b8e7c8ae6bc2ad631da33c72
[ "MIT" ]
1
2018-10-24T00:37:08.000Z
2018-10-24T00:37:08.000Z
class GroupNotFoundException(Exception): pass class UserNotFoundException(Exception): pass class AlreadyExistsOnDatabaseException(Exception): pass class ChatIdOrTextCannotBeEmpty(Exception): pass
14.533333
50
0.788991
16
218
10.75
0.4375
0.302326
0.313953
0
0
0
0
0
0
0
0
0
0.155963
218
14
51
15.571429
0.934783
0
0
0.5
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true
0.5
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0
0.5
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1
null
1
1
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null
0
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0
0
1
1
0
0
0
0
0
6
ec9ea6c4e8a18d90e2b074f39f761faafa07e859
176
py
Python
markdown_external_link_finder/__main__.py
MatMoore/markdown-external-link-finder
bb04d2573e150d8efe61063deafa3119c5f2ef3f
[ "MIT" ]
null
null
null
markdown_external_link_finder/__main__.py
MatMoore/markdown-external-link-finder
bb04d2573e150d8efe61063deafa3119c5f2ef3f
[ "MIT" ]
4
2019-06-04T22:36:17.000Z
2021-06-25T15:34:31.000Z
markdown_external_link_finder/__main__.py
MatMoore/markdown-external-link-finder
bb04d2573e150d8efe61063deafa3119c5f2ef3f
[ "MIT" ]
null
null
null
import glob from .extract import extract_markdown_links markdown_files = glob.glob('**/*.md', recursive=True) for url in extract_markdown_links(markdown_files): print(url)
29.333333
53
0.784091
25
176
5.28
0.56
0.227273
0.30303
0.424242
0.5
0
0
0
0
0
0
0
0.107955
176
6
54
29.333333
0.840764
0
0
0
0
0
0.039548
0
0
0
0
0
0
1
0
false
0
0.4
0
0.4
0.2
1
0
0
null
1
1
1
0
0
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0
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0
0
0
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null
0
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0
0
0
0
0
1
0
0
0
0
6
01a7f4e684575fc5f27ecaaf024bb9c8377dbebd
69
py
Python
ui/__init__.py
neuromancer/lisa
817efdf2ffd69de983f2b4f12d4db2885bd1b308
[ "Apache-2.0" ]
2
2017-11-05T22:14:19.000Z
2019-05-07T15:33:06.000Z
ui/__init__.py
kevinmel2000/lisa
817efdf2ffd69de983f2b4f12d4db2885bd1b308
[ "Apache-2.0" ]
1
2018-02-26T19:24:54.000Z
2018-02-26T19:47:08.000Z
ui/__init__.py
kevinmel2000/lisa
817efdf2ffd69de983f2b4f12d4db2885bd1b308
[ "Apache-2.0" ]
4
2017-11-05T22:14:23.000Z
2021-05-21T16:59:24.000Z
from ui.notification import notify def say(x): return notify(x)
13.8
34
0.724638
11
69
4.545455
0.818182
0
0
0
0
0
0
0
0
0
0
0
0.188406
69
4
35
17.25
0.892857
0
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0.333333
false
0
0.333333
0.333333
1
0
1
0
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null
0
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null
0
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0
0
1
0
0
1
1
1
0
0
6
01b4680ca55594868c63cb44eaf96b1ae3894315
3,085
py
Python
kitchen/tests/test_init.py
honzas83/kitchen
749953fe28895ed51cd7283800a9bb591c269da2
[ "BSD-3-Clause" ]
null
null
null
kitchen/tests/test_init.py
honzas83/kitchen
749953fe28895ed51cd7283800a9bb591c269da2
[ "BSD-3-Clause" ]
null
null
null
kitchen/tests/test_init.py
honzas83/kitchen
749953fe28895ed51cd7283800a9bb591c269da2
[ "BSD-3-Clause" ]
null
null
null
import kitchen import lasagne import numpy as np from sklearn.base import BaseEstimator, clone, is_classifier from sklearn.utils.testing import assert_equal from nose.tools import raises class NetInitNormal(kitchen.Network, kitchen.ADADelta, kitchen.BinaryCrossentropy): def create_layers(self, X_dim, y_dim, random_state): initW = kitchen.init.Normal(random_state=random_state) initb = kitchen.init.Normal(random_state=random_state) l0 = lasagne.layers.InputLayer(shape=(None, X_dim)) l02 = kitchen.layers.DropoutLayer(l0, p=0.5, random_state=random_state) l1 = lasagne.layers.DenseLayer(l02, num_units=128, nonlinearity=lasagne.nonlinearities.LeakyRectify(), W=initW, b=initb) l12 = kitchen.layers.DropoutLayer(l1, p=0.5, random_state=random_state) l3 = lasagne.layers.DenseLayer(l12, num_units=y_dim, nonlinearity=lasagne.nonlinearities.sigmoid, W=initW, b=initb) return l0, l3 def test_fit_normal(): X = np.array([[1, 2, 3], [4, 5, 6]]) y = np.array([[0], [1]]) net = NetInitNormal(random_state=42) net.fit(X, y) net.loss(X, y) y_pred = net.predict(X) class NetGlorotFail(kitchen.Network, kitchen.ADADelta, kitchen.BinaryCrossentropy): def create_layers(self, X_dim, y_dim, random_state): initW = kitchen.init.GlorotNormal(random_state=random_state) initb = kitchen.init.GlorotNormal(random_state=random_state) l0 = lasagne.layers.InputLayer(shape=(None, X_dim)) l02 = kitchen.layers.DropoutLayer(l0, p=0.5, random_state=random_state) l1 = lasagne.layers.DenseLayer(l02, num_units=128, nonlinearity=lasagne.nonlinearities.LeakyRectify(), W=initW, b=initb) l12 = kitchen.layers.DropoutLayer(l1, p=0.5, random_state=random_state) l3 = lasagne.layers.DenseLayer(l12, num_units=y_dim, nonlinearity=lasagne.nonlinearities.sigmoid, W=initW, b=initb) return l0, l3 @raises(RuntimeError) def test_fit_glorot_fail(): X = np.array([[1, 2, 3], [4, 5, 6]]) y = np.array([[0], [1]]) net = NetGlorotFail(random_state=42) net.fit(X, y) class NetGlorotFail2(kitchen.Network, kitchen.ADADelta, kitchen.BinaryCrossentropy): def create_layers(self, X_dim, y_dim, random_state): initW = kitchen.init.GlorotNormal(random_state=random_state, c01b=True) initb = kitchen.init.Uniform(random_state=random_state) l0 = lasagne.layers.InputLayer(shape=(None, X_dim)) l02 = kitchen.layers.DropoutLayer(l0, p=0.5, random_state=random_state) l1 = lasagne.layers.DenseLayer(l02, num_units=128, nonlinearity=lasagne.nonlinearities.LeakyRectify(), W=initW, b=initb) l12 = kitchen.layers.DropoutLayer(l1, p=0.5, random_state=random_state) l3 = lasagne.layers.DenseLayer(l12, num_units=y_dim, nonlinearity=lasagne.nonlinearities.sigmoid, W=initW, b=initb) return l0, l3 @raises(RuntimeError) def test_fit_glorot_fail2(): X = np.array([[1, 2, 3], [4, 5, 6]]) y = np.array([[0], [1]]) net = NetGlorotFail2(random_state=42) net.fit(X, y)
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6
01db0918d6d3710e18091923be0871474e8b909d
51
py
Python
_init_.py
devsahu99/hybrid_recommender
0e1b32de8bda5ababa83a366fa740528c4c63c5d
[ "MIT" ]
1
2021-02-02T09:15:19.000Z
2021-02-02T09:15:19.000Z
_init_.py
devsahu99/hybrid_recommender
0e1b32de8bda5ababa83a366fa740528c4c63c5d
[ "MIT" ]
null
null
null
_init_.py
devsahu99/hybrid_recommender
0e1b32de8bda5ababa83a366fa740528c4c63c5d
[ "MIT" ]
1
2019-05-16T12:46:08.000Z
2019-05-16T12:46:08.000Z
from .hybrid_recommender import hybrid_recommender
25.5
50
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51
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1
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6
bf147825412b56b22c16ab18fb1054a03a991aa6
19
py
Python
part_c/c_constants.py
cconnerolson/aerospace_assignment_6
adeb4aaee29198cac06321f2a7a23efd20cf56e6
[ "MIT" ]
1
2020-11-28T05:16:22.000Z
2020-11-28T05:16:22.000Z
part_c/c_constants.py
cconnerolson/aerospace_assignment_6
adeb4aaee29198cac06321f2a7a23efd20cf56e6
[ "MIT" ]
null
null
null
part_c/c_constants.py
cconnerolson/aerospace_assignment_6
adeb4aaee29198cac06321f2a7a23efd20cf56e6
[ "MIT" ]
1
2020-11-28T05:16:29.000Z
2020-11-28T05:16:29.000Z
A_e = 4.478 # m**2
19
19
0.473684
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19
1.333333
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1
19
19
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6
1723ef876c0d25797b84c463a68b426d30239207
326
py
Python
model_field_meta/mixins.py
melvinkcx/django-model-field-meta
27ba8928bd90eeb3340cccafcc4c99f32a2e1c5e
[ "MIT" ]
8
2019-11-07T08:23:22.000Z
2022-02-20T12:59:03.000Z
model_field_meta/mixins.py
melvinkcx/django-model-field-meta
27ba8928bd90eeb3340cccafcc4c99f32a2e1c5e
[ "MIT" ]
7
2019-11-19T01:14:03.000Z
2021-06-09T18:41:49.000Z
model_field_meta/mixins.py
melvinkcx/django-model-field-meta
27ba8928bd90eeb3340cccafcc4c99f32a2e1c5e
[ "MIT" ]
1
2020-12-07T02:59:43.000Z
2020-12-07T02:59:43.000Z
class FieldMetaMixin: @classmethod def get_field_meta(cls, field_name): return cls._meta.get_field(field_name).get_meta() @classmethod def has_field_meta(cls, field_name): return hasattr(cls._meta.get_field(field_name), "_meta") \ and cls.get_field_meta(field_name) is not None
32.6
66
0.693252
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326
4.543478
0.347826
0.215311
0.114833
0.162679
0.488038
0.488038
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0.211656
326
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67
36.222222
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0.25
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1
1
0
0
6
1736c11c89c70a1c7e787faaddd0bcfff5d92330
158
py
Python
sbroccoli/tasks/__init__.py
modamod/special-broccoli
7b82e15cf9ebef73e7bbb4e251780acddae75428
[ "MIT" ]
null
null
null
sbroccoli/tasks/__init__.py
modamod/special-broccoli
7b82e15cf9ebef73e7bbb4e251780acddae75428
[ "MIT" ]
null
null
null
sbroccoli/tasks/__init__.py
modamod/special-broccoli
7b82e15cf9ebef73e7bbb4e251780acddae75428
[ "MIT" ]
null
null
null
from invoke import Collection from . import utils, aws ns = Collection() ns.add_collection(ns.from_module(utils)) ns.add_collection(ns.from_module(aws))
26.333333
41
0.772152
24
158
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0.305085
0.254237
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0.457627
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