xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

b7fe729773f334991658bb6aa780e882a1299015

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py

Python

div.py

darkdebo/python_codes

5644482b7a7cb4d775de0194bae84024e24bfcaf

[ "MIT" ]

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div.py

darkdebo/python_codes

5644482b7a7cb4d775de0194bae84024e24bfcaf

[ "MIT" ]

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2019-09-03T10:15:36.000Z

div.py

darkdebo/python_codes

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print([i for i in range(21) if i%2==0 or i%4==0])

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Python

examples/00_Example_Active.py

davilamds/py_dss_interface

a447c97787aeac962381db88dd622ccb235eef4b

[ "MIT" ]

8

2020-08-15T12:56:03.000Z

2022-01-04T15:51:14.000Z

examples/00_Example_Active.py

rodolfoplondero/py_dss_interface

cb6771b34ed322a5df7ef1cc194611e794f26441

[ "MIT" ]

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2021-04-24T18:33:19.000Z

2021-11-13T14:59:54.000Z

examples/00_Example_Active.py

rodolfoplondero/py_dss_interface

cb6771b34ed322a5df7ef1cc194611e794f26441

[ "MIT" ]

7

2020-08-15T12:56:04.000Z

2021-10-04T16:14:30.000Z

# -*- encoding: utf-8 -*- """ Created by Ênio Viana at 12/05/2021 """ from py_dss_interface.models.Example.ExampleBase import ExampleBase dss = ExampleBase("13").dss # Integer methods print(45 * '=' + ' Integer Methods' + 45 * '=') print(f'dss.active_class_get_class_name(): {dss.active_class_get_class_name()}') print(f'dss.active_class_get_name(): {dss.active_class_get_name()}') print(f'dss.active_class_first(): {dss.active_class_first()}') print(f'dss.active_class_num_elements(): {dss.active_class_num_elements()}') print(f'dss.active_class_count(): {dss.active_class_count()}') print() print(f'dss.active_class_get_class_name(): {dss.active_class_get_class_name()}') print(f'dss.active_class_get_name(): {dss.active_class_get_name()}') print(f'dss.active_class_next(): {dss.active_class_next()}') print(f'dss.active_class_num_elements(): {dss.active_class_num_elements()}') print(f'dss.active_class_count(): {dss.active_class_count()}') # To iterate from begin we must call first() dss.active_class_first() for i in range(dss.active_class_num_elements()): print(f'Name: {dss.active_class_get_name()} || Index: {i}') dss.active_class_next() # String methods print(45 * '=' + ' String Methods' + 45 * '=') dss.active_class_first() print(f'dss.active_class_get_name(): {dss.active_class_get_name()}') print(f'dss.active_class_write_name(): {dss.active_class_write_name("645646")}') print(f'dss.active_class_get_name(): {dss.active_class_get_name()}') print(f'dss.active_class_get_class_name(): {dss.active_class_get_class_name()} \n') print(f'dss.active_class_parent_class_name(): {dss.active_class_parent_class_name()} \n') dss.active_class_first() for _ in range(dss.active_class_num_elements()): print(f'dss.active_class_get_name(): {dss.active_class_get_name()}') dss.active_class_next() # Variant methods print(45 * '=' + ' Variant Methods' + 45 * '=') print(dss.active_class_all_names())

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Python

stochastic_spectroscopy/layers.py

fullerf/stochastic-spectroscopy

371ac24fd65dea446ed9448cc208d83d94f7044c

[ "MIT" ]

1

2021-04-12T16:24:07.000Z

stochastic_spectroscopy/layers.py

fullerf/stochastic_spectroscopy

371ac24fd65dea446ed9448cc208d83d94f7044c

[ "MIT" ]

null

stochastic_spectroscopy/layers.py

fullerf/stochastic_spectroscopy

371ac24fd65dea446ed9448cc208d83d94f7044c

[ "MIT" ]

null

# --- # jupyter: # jupytext: # formats: ipynb,py:light # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.4.2 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- import sys sys.path.append('/home/dgp_iwvi_gpflow2/') import tensorflow as tf import tensorflow_probability as tfp import numpy as np import gpflow import enum import collections from typing import Callable, Optional, Tuple, TypeVar, Union, List from gpflow.kernels import Kernel, MultioutputKernel from gpflow.mean_functions import MeanFunction, Zero from gpflow.inducing_variables import SeparateIndependentInducingVariables, SharedIndependentInducingVariables from gpflow.kullback_leiblers import gauss_kl as gauss_kl_gpflow import attr # avoiding use of defaults kwarg, to keep compatibility with Python3.6 class RegularizerType(enum.Enum): LOCAL = 0 GLOBAL = 1 def gauss_kl(q_mu, q_sqrt, K=None): """ Wrapper for gauss_kl from gpflow that returns the negative log prob if q_sqrt is None. This can be for use in HMC: all that is required is to set q_sqrt to None and this function substitues the negative log prob instead of the KL (so no need to set q_mu.prior = gpflow.priors.Gaussian(0, 1)). Also, this allows the use of HMC in the unwhitened case. """ if q_sqrt is None: # return negative log prob with q_mu as 'x', with mean 0 and cov K (or I, if None) M, D = tf.shape(q_mu)[0], tf.shape(q_mu)[1] I = tf.eye(M, dtype=q_mu.dtype) if K is None: L = I else: L = tf.cholesky(K + I * gpflow.default_jitter()) return -tf.reduce_sum(gpflow.logdensities.multivariate_normal(q_mu, tf.zeros_like(q_mu), L)) else: # return kl return gauss_kl_gpflow(q_mu, q_sqrt, K=K) class GPLayer(gpflow.Module): regularizer_type = RegularizerType.GLOBAL def __init__(self, kernel: gpflow.kernels.Kernel, inducing: gpflow.inducing_variables.InducingVariables, mean_func: gpflow.mean_functions.MeanFunction, **kwargs ): super().__init__() """ The range of supported options for sample conditional is not complete. The following do not work: LinearCoregionalization: in order to get the proper behavior, you must have a separate kernel for each independent GP. While some things evaluate with a single shared kernel, Kuu and Kuf do not work properly and treat the number of latent gps as the number of separate kernels. LinearCoregionalization / SharedIndependentInducingVariable: In this case, you can only eval- uate the propagation when full_cov = False. However, full_cov is possible if one uses SeparateIndependentInducingVariable. """ assert issubclass(type(kernel), gpflow.kernels.Kernel) assert issubclass(type(inducing), gpflow.inducing_variables.InducingVariables) if not issubclass(type(kernel), gpflow.kernels.MultioutputKernel): self.num_latent_gps = 1 self.output_dim = 1 else: self.num_latent_gps = kernel.num_latent_gps if not len(kernel.kernels) == self.num_latent_gps: # we want to catch the error with LinearCoregionalization mentioned above raise ValueError( f"number of kernels should match number of latent gps " \ f"({self.num_latent_gps}) got {len(kernel.kernels)} kernels" ) if issubclass(type(kernel), gpflow.kernels.LinearCoregionalization): self.output_dim = kernel.W.shape[-2] else: self.output_dim = self.num_latent_gps self.kernel = kernel self.inducing = inducing if hasattr(self.inducing, 'inducing_variable_list'): # case for separate independent assert len(self.inducing.inducing_variable_list) == self.num_latent_gps, \ f"Got {len(self.inducing.inducing_variable_list)} inducing variables, " \ f"but expected {self.num_latent_gps} gps from kernel. These should match." self.in_features = self.inducing.inducing_variable_list[0].Z.shape[-1] self.num_inducing = self.inducing.inducing_variable_list[0].Z.shape[-2] elif hasattr(self.inducing, 'inducing_variable'): # case for shared independent self.in_features = self.inducing.inducing_variable.Z.shape[-1] self.num_inducing = self.inducing.inducing_variable.Z.shape[-2] else: self.in_features = self.inducing.Z.shape[-1] self.num_inducing = self.inducing.Z.shape[-2] assert issubclass(type(mean_func), gpflow.mean_functions.MeanFunction) self.mean = mean_func if type(mean_func) is gpflow.mean_functions.Linear: # more consistency checking assert self.mean.A.shape[-1] == self.output_dim # Now for the storage of variational parameters self.q_mu = gpflow.Parameter(np.zeros((self.num_inducing, self.num_latent_gps)), transform=None) init_sqrt = np.tile(np.eye(self.num_inducing)[None, :, :], [self.num_latent_gps, 1, 1]) if 'scale_init_q_sqrt' in kwargs: init_sqrt *= kwargs['scale_init_q_sqrt'] self.q_sqrt = gpflow.Parameter(init_sqrt, transform=gpflow.utilities.triangular()) def propagate(self, F, num_samples=None, full_cov=False, **kwargs): # In Hugh's code, he forces one to use full_cov = False for the case of a MoK. This has the effect # that only the final layer uses full covariance (as his code uses a single output kernel for the # final layer). This is inspite of the fact that he passes full_cov=True to all layers in the IWVI # case. Since I don't want to hack GPFlow's conditional system, I will let the full_cov pass through # and manually implement his behavior in the model. samples, mean, cov = gpflow.conditionals.sample_conditional(F, self.inducing, self.kernel, self.q_mu, full_cov=full_cov, q_sqrt=self.q_sqrt, white=True, num_samples=num_samples, ) kl = gauss_kl(self.q_mu, self.q_sqrt) mf = self.mean(F) if num_samples is not None: samples = samples + mf[...,None,:,:] else: samples = samples + mf mean = mean + mf return samples, mean, cov, kl def components(self, F, num_samples=None, full_cov=False, **kwargs): # In Hugh's code, he forces one to use full_cov = False for the case of a MoK. This has the effect # that only the final layer uses full covariance (as his code uses a single output kernel for the # final layer). This is inspite of the fact that he passes full_cov=True to all layers in the IWVI # case. Since I don't want to hack GPFlow's conditional system, I will let the full_cov pass through # and manually implement his behavior in the model. mean, cov = gpflow.conditionals.conditional(F, self.inducing, self.kernel, self.q_mu, full_cov=full_cov, q_sqrt=self.q_sqrt, white=True, ) kl = gauss_kl(self.q_mu, self.q_sqrt) mf = self.mean(F) mean = mean + mf return mean, cov, kl class Encoder(gpflow.Module): def __init__(self, latent_dim: int, input_dim: int, network_dims: int, activation_func: Optional[Callable] = None): """ Encoder that uses GPflow params to encode the features. Creates an MLP with input dimensions `input_dim` and produces 2 * `latent_dim` outputs. :param latent_dim: dimension of the latent variable :param input_dim: the MLP acts on data of `input_dim` dimensions :param network_dims: dimensions of inner MLPs, e.g. [10, 20, 10] :param activation_func: TensorFlow operation that can be used as non-linearity between the layers (default: tanh). """ super().__init__() self.latent_dim = latent_dim self.activation_func = activation_func or tf.nn.tanh self.layer_dims = [input_dim, *network_dims, latent_dim * 2] Ws, bs = [], [] for input_dim, output_dim in zip(self.layer_dims[:-1], self.layer_dims[1:]): xavier_std = (2. / (input_dim + output_dim)) ** 0.5 W = np.random.randn(input_dim, output_dim) * xavier_std Ws.append(gpflow.Parameter(W, dtype=gpflow.config.default_float())) bs.append(gpflow.Parameter(np.zeros(output_dim), dtype=gpflow.config.default_float())) self.Ws, self.bs = Ws, bs def __call__(self, Z) -> Tuple[tf.Tensor, tf.Tensor]: o = tf.ones_like(Z)[..., :1, :1] # for correct broadcasting for i, (W, b, dim_in, dim_out) in enumerate(zip(self.Ws, self.bs, self.layer_dims[:-1], self.layer_dims[1:])): Z0 = tf.identity(Z) Z = tf.matmul(Z, o * W) + o * b if i < len(self.bs) - 1: Z = self.activation_func(Z) if dim_out == dim_in: # skip connection Z += Z0 means, log_chol_diag = tf.split(Z, 2, axis=-1) q_sqrt = tf.nn.softplus(log_chol_diag - 3.) # bias it towards small vals at first q_mu = means return q_mu, q_sqrt class SASEEncoder(gpflow.Module): def __init__(self, latent_dim: int, input_dim: int, network_dims: int, activation_func: Optional[Callable] = None): """ Encoder that uses GPflow params to encode the features. Creates an MLP with input dimensions `input_dim` and produces 2 * `latent_dim` outputs. Unlike the standard encoder, this expects an input of NR shape, and converts that to an output which is (N*R)L, where L is the latent dim. :param latent_dim: dimension of the latent variable, i.e L :param input_dim: the MLP acts on data of `input_dim` dimensions, i.e. R :param network_dims: dimensions of inner MLPs, e.g. [10, 20, 10] :param activation_func: TensorFlow operation that can be used as non-linearity between the layers (default: tanh). """ super().__init__() self.latent_dim = tf.convert_to_tensor([latent_dim], tf.int32) self.activation_func = activation_func or tf.nn.tanh self.layer_dims = [input_dim, *network_dims, input_dim * latent_dim * 2] Ws, bs = [], [] for input_dim, output_dim in zip(self.layer_dims[:-1], self.layer_dims[1:]): xavier_std = (2. / (input_dim + output_dim)) ** 0.5 W = np.random.randn(input_dim, output_dim) * xavier_std Ws.append(gpflow.Parameter(W, dtype=gpflow.config.default_float())) bs.append(gpflow.Parameter(np.zeros(output_dim), dtype=gpflow.config.default_float())) self.Ws, self.bs = Ws, bs def __call__(self, Z) -> Tuple[tf.Tensor, tf.Tensor]: N = tf.convert_to_tensor([tf.shape(Z)[-2]], dtype=tf.int32) R = tf.convert_to_tensor([tf.shape(Z)[-1]], dtype=tf.int32) batch_shape = tf.convert_to_tensor(tf.shape(Z)[:-2], dtype=tf.int32) o = tf.ones_like(Z)[..., :1, :1] # for correct broadcasting for i, (W, b, dim_in, dim_out) in enumerate(zip(self.Ws, self.bs, self.layer_dims[:-1], self.layer_dims[1:])): Z0 = tf.identity(Z) Z = tf.matmul(Z, o * W) + o * b if i < len(self.bs) - 1: Z = self.activation_func(Z) if dim_out == dim_in: # skip connection Z += Z0 means, log_chol_diag = tf.split(Z, 2, axis=-1) q_sqrt = tf.nn.softplus(log_chol_diag - 3.) # bias it towards small vals at first q_mu = means #...N(L*R) q_mu_reshaped = tf.reshape(q_mu, tf.concat([batch_shape, N*R, self.latent_dim],0)) # ...(N*R)L q_sqrt_reshaped = tf.reshape(q_sqrt, tf.concat([batch_shape, N*R, self.latent_dim],0)) return q_mu_reshaped, q_sqrt_reshaped class EmbeddingEncoder(gpflow.Module): def __init__(self, latent_dim: int, nwords: int): """ Here we simply pass a shot index to an embedding lookup. This allows us to randomly access a tensor more easily, but basically we're just storing latent values for each shot. """ super().__init__() self.latent_dim = int(latent_dim) self.embedding = gpflow.Parameter(np.random.randn(nwords, 2*latent_dim), dtype=gpflow.config.default_float()) @tf.function def __call__(self, Z: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor]: Zenc = tf.nn.embedding_lookup(self.embedding, tf.squeeze(Z,-1)) means, log_chol_diag = tf.split(Zenc, 2, axis=-1) q_sqrt = tf.nn.softplus(log_chol_diag - 3.) # bias it towards small vals at first q_mu = means return q_mu, q_sqrt class AmortizedLatentVariableLayer(gpflow.Module): regularizer_type = RegularizerType.LOCAL def __init__(self, latent_dim: int, XY_dim: Optional[int] = None, encoder: Optional[Callable] = None): super().__init__() self.latent_dim = latent_dim if encoder is None: assert XY_dim, 'must pass XY_dim or else an encoder' encoder = Encoder(latent_dim, XY_dim, [20, 20]) self.encoder = encoder def propagate(self, F: tf.Tensor, inference_amortization_inputs: Optional[tf.Tensor] = None, is_sampled_local_regularizer: bool = False, **kwargs) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: if inference_amortization_inputs is None: """ If there isn't an X and Y passed for the recognition model, this samples from the prior. Optionally, q_mu and q_sqrt can be fed via a placeholder (e.g. for plotting purposes) """ shape = tf.concat([F.shape[:-1], tf.TensorShape([self.latent_dim])], 0) q_mu = tf.zeros(shape, dtype=gpflow.config.default_float()) q_sqrt = tf.ones(shape, dtype=gpflow.config.default_float()) else: q_mu, q_sqrt = self.encoder(inference_amortization_inputs) # reparameterization trick to take a sample for W eps = tf.random.normal(tf.shape(q_mu), dtype=gpflow.config.default_float()) W = q_mu + eps * q_sqrt samples = tf.concat([F, W], -1) mean = tf.concat([F, q_mu], -1) cov = tf.concat([tf.zeros_like(F), q_sqrt ** 2], -1) # the prior regularization p = p = tfp.distributions.Normal(loc=tf.zeros(1,dtype=gpflow.config.default_float()), scale=tf.ones(1,dtype=gpflow.config.default_float())) q = tfp.distributions.Normal(loc=q_mu, scale=q_sqrt) if is_sampled_local_regularizer: # for the IW models, we need to return a log q/p for each sample W kl = q.log_prob(W) - p.log_prob(W) else: # for the VI models, we want E_q log q/p, which is closed form for Gaussians kl = tfp.distributions.kl_divergence(q, p) return samples, mean, cov, kl class AmortizedSASELatentVariableLayer(gpflow.Module): regularizer_type = RegularizerType.LOCAL def __init__(self, latent_dim: int, sase_dim: int, encoder: Optional[Callable] = None): super().__init__() if encoder is None: encoder = SASEEncoder(latent_dim, sase_dim, [50, 10, 50]) self.latent_dim = tf.convert_to_tensor([latent_dim], dtype=tf.int32) self.sase_dim = tf.convert_to_tensor([sase_dim], dtype=tf.int32) self.encoder = encoder def propagate(self, F: tf.Tensor, inference_amortization_inputs: Optional[tf.Tensor] = None, is_sampled_local_regularizer: bool = False, **kwargs) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: if inference_amortization_inputs is None: """ If there isn't a SASE spec passed for the recognition model, this samples from the prior. Optionally, q_mu and q_sqrt can be fed via a placeholder (e.g. for plotting purposes) """ batch_shape = tf.convert_to_tensor(tf.shape(F)[:-2], dtype=tf.int32) # ... N = tf.convert_to_tensor([tf.shape(F)[-2]], dtype=tf.int32) shape = tf.concat([batch_shape, N, self.latent_dim], 0) # ...(N)L q_mu = tf.zeros(shape, dtype=gpflow.config.default_float()) q_sqrt = tf.ones(shape, dtype=gpflow.config.default_float()) else: q_mu, q_sqrt = self.encoder(inference_amortization_inputs) # reparameterization trick to take a sample for W eps = tf.random.normal(tf.shape(q_mu), dtype=gpflow.config.default_float()) W = q_mu + eps * q_sqrt samples = tf.concat([F, W], -1) mean = tf.concat([F, q_mu], -1) cov = tf.concat([tf.zeros_like(F), q_sqrt ** 2], -1) # the prior regularization p = p = tfp.distributions.Normal(loc=tf.zeros(1,dtype=gpflow.config.default_float()), scale=tf.ones(1,dtype=gpflow.config.default_float())) q = tfp.distributions.Normal(loc=q_mu, scale=q_sqrt) if is_sampled_local_regularizer: # for the IW models, we need to return a log q/p for each sample W kl = q.log_prob(W) - p.log_prob(W) else: # for the VI models, we want E_q log q/p, which is closed form for Gaussians kl = tfp.distributions.kl_divergence(q, p) return samples, mean, cov, kl class AmortizedEmbeddingLatentVariableLayer(gpflow.Module): regularizer_type = RegularizerType.LOCAL def __init__(self, latent_dim: int, nwords: int, nembed: int = 10, nhidden: int = 20): super().__init__() self.latent_dim = latent_dim self.encoder = EmbeddingEncoder(latent_dim, nwords) def propagate(self, F: tf.Tensor, inference_amortization_inputs: Optional[tf.Tensor] = None, is_sampled_local_regularizer: bool = False, **kwargs) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: if inference_amortization_inputs is None: """ If there isn't an X and Y passed for the recognition model, this samples from the prior. Optionally, q_mu and q_sqrt can be fed via a placeholder (e.g. for plotting purposes) """ shape = tf.concat([F.shape[:-1], tf.TensorShape([self.latent_dim])], 0) q_mu = tf.zeros(shape, dtype=gpflow.config.default_float()) q_sqrt = tf.ones(shape, dtype=gpflow.config.default_float()) else: q_mu, q_sqrt = self.encoder(inference_amortization_inputs) # reparameterization trick to take a sample for W eps = tf.random.normal(tf.shape(q_mu), dtype=gpflow.config.default_float()) W = q_mu + eps * q_sqrt samples = tf.concat([F, W], -1) mean = tf.concat([F, q_mu], -1) cov = tf.concat([tf.zeros_like(F), q_sqrt ** 2], -1) # the prior regularization p = p = tfp.distributions.Normal(loc=tf.zeros(1,dtype=gpflow.config.default_float()), scale=tf.ones(1,dtype=gpflow.config.default_float())) q = tfp.distributions.Normal(loc=q_mu, scale=q_sqrt) if is_sampled_local_regularizer: # for the IW models, we need to return a log q/p for each sample W kl = q.log_prob(W) - p.log_prob(W) else: # for the VI models, we want E_q log q/p, which is closed form for Gaussians kl = tfp.distributions.kl_divergence(q, p) return samples, mean, cov, kl class SASEReducedEncoder(gpflow.Module): def __init__(self, latent_dim: int, input_dim: int, network_dims: int, activation_func: Optional[Callable] = None): """ Encoder that uses GPflow params to encode the features. Creates an MLP with input dimensions `input_dim` and produces 2 * `latent_dim` outputs. Unlike the standard encoder, this expects an input of NR shape, and converts that to an output which is (N*R)L, where L is the latent dim. :param latent_dim: dimension of the latent variable, i.e L :param input_dim: the MLP acts on data of `input_dim` dimensions, i.e. R :param network_dims: dimensions of inner MLPs, e.g. [10, 20, 10] :param activation_func: TensorFlow operation that can be used as non-linearity between the layers (default: tanh). """ super().__init__() self.latent_dim = tf.convert_to_tensor([latent_dim], tf.int32) self.activation_func = activation_func or tf.nn.tanh self.layer_dims = [input_dim, *network_dims, latent_dim * 2] Ws, bs = [], [] for input_dim, output_dim in zip(self.layer_dims[:-1], self.layer_dims[1:]): xavier_std = (2. / (input_dim + output_dim)) ** 0.5 W = np.random.randn(input_dim, output_dim) * xavier_std Ws.append(gpflow.Parameter(W, dtype=gpflow.config.default_float())) bs.append(gpflow.Parameter(np.zeros(output_dim), dtype=gpflow.config.default_float())) self.Ws, self.bs = Ws, bs def __call__(self, Z) -> Tuple[tf.Tensor, tf.Tensor]: N = tf.convert_to_tensor([tf.shape(Z)[-2]], dtype=tf.int32) R = tf.convert_to_tensor([tf.shape(Z)[-1]], dtype=tf.int32) batch_shape = tf.convert_to_tensor(tf.shape(Z)[:-2], dtype=tf.int32) o = tf.ones_like(Z)[..., :1, :1] # for correct broadcasting for i, (W, b, dim_in, dim_out) in enumerate(zip(self.Ws, self.bs, self.layer_dims[:-1], self.layer_dims[1:])): Z0 = tf.identity(Z) Z = tf.matmul(Z, o * W) + o * b if i < len(self.bs) - 1: Z = self.activation_func(Z) if dim_out == dim_in: # skip connection Z += Z0 means, log_chol_diag = tf.split(Z, 2, axis=-1) q_sqrt = tf.nn.softplus(log_chol_diag - 3.) # bias it towards small vals at first q_mu = means #...N(L*R) return q_mu, q_sqrt class AmortizedSASEReducedLatentVariableLayer(gpflow.Module): regularizer_type = RegularizerType.LOCAL def __init__(self, latent_dim: int, sase_dim: int, encoder: Optional[Callable] = None): super().__init__() if encoder is None: encoder = SASEReducedEncoder(latent_dim, sase_dim, [50, 10, 10]) self.latent_dim = tf.convert_to_tensor([latent_dim], dtype=tf.int32) self.sase_dim = tf.convert_to_tensor([sase_dim], dtype=tf.int32) self.encoder = encoder def propagate(self, F: tf.Tensor, inference_amortization_inputs: Optional[tf.Tensor] = None, is_sampled_local_regularizer: bool = False, **kwargs) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: if inference_amortization_inputs is None: """ If there isn't a SASE spec passed for the recognition model, this samples from the prior. Optionally, q_mu and q_sqrt can be fed via a placeholder (e.g. for plotting purposes) """ batch_shape = tf.convert_to_tensor(tf.shape(F)[:-2], dtype=tf.int32) # ... N = tf.convert_to_tensor([tf.shape(F)[-2]], dtype=tf.int32) shape = tf.concat([batch_shape, N, self.latent_dim], 0) # ...(N)L q_mu = tf.zeros(shape, dtype=gpflow.config.default_float()) q_sqrt = tf.ones(shape, dtype=gpflow.config.default_float()) else: q_mu, q_sqrt = self.encoder(inference_amortization_inputs) # reparameterization trick to take a sample for W eps = tf.random.normal(tf.shape(q_mu), dtype=gpflow.config.default_float()) W = q_mu + eps * q_sqrt samples = tf.concat([F, W], -1) mean = tf.concat([F, q_mu], -1) cov = tf.concat([tf.zeros_like(F), q_sqrt ** 2], -1) # the prior regularization p = p = tfp.distributions.Normal(loc=tf.zeros(1,dtype=gpflow.config.default_float()), scale=tf.ones(1,dtype=gpflow.config.default_float())) q = tfp.distributions.Normal(loc=q_mu, scale=q_sqrt) if is_sampled_local_regularizer: # for the IW models, we need to return a log q/p for each sample W kl = q.log_prob(W) - p.log_prob(W) else: # for the VI models, we want E_q log q/p, which is closed form for Gaussians kl = tfp.distributions.kl_divergence(q, p) return samples, mean, cov, kl class AmortizedLatentVariableLayer2(gpflow.Module): regularizer_type = RegularizerType.LOCAL def __init__(self, latent_dim: int, sase_dim: int, encoder_dims: Optional[List[int]] = None): super().__init__() if encoder_dims is None: encoder = Encoder(latent_dim, sase_dim, [50, 10, 10]) else: encoder = Encoder(latent_dim, sase_dim, encoder_dims) self.latent_dim = tf.convert_to_tensor([latent_dim], dtype=tf.int32) self.sase_dim = tf.convert_to_tensor([sase_dim], dtype=tf.int32) self.encoder = encoder def propagate(self, F: tf.Tensor, inference_amortization_inputs: Optional[tf.Tensor] = None, is_sampled_local_regularizer: bool = False, **kwargs) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: if inference_amortization_inputs is None: """ If there isn't a SASE spec passed for the recognition model, this samples from the prior. Optionally, q_mu and q_sqrt can be fed via a placeholder (e.g. for plotting purposes) """ batch_shape = tf.convert_to_tensor(tf.shape(F)[:-2], dtype=tf.int32) # ... N = tf.convert_to_tensor([tf.shape(F)[-2]], dtype=tf.int32) shape = tf.concat([batch_shape, N, self.latent_dim], 0) # ...(N)L q_mu = tf.zeros(shape, dtype=gpflow.config.default_float()) q_sqrt = tf.ones(shape, dtype=gpflow.config.default_float()) else: q_mu, q_sqrt = self.encoder(inference_amortization_inputs) # reparameterization trick to take a sample for W eps = tf.random.normal(tf.shape(q_mu), dtype=gpflow.config.default_float()) W = q_mu + eps * q_sqrt samples = tf.concat([F, W], -1) mean = tf.concat([F, q_mu], -1) cov = tf.concat([tf.zeros_like(F), q_sqrt ** 2], -1) #### HAHAHASDFDDADSF ##### AGGHHH NOTICE THE SCALE ON THE KL ##### ITS NOT 1!!!!! # the prior regularization p = p = tfp.distributions.Normal(loc=tf.zeros(1,dtype=gpflow.config.default_float()), scale=tf.ones(1,dtype=gpflow.config.default_float())) q = tfp.distributions.Normal(loc=q_mu, scale=q_sqrt) if is_sampled_local_regularizer: # for the IW models, we need to return a log q/p for each sample W kl = q.log_prob(W) - p.log_prob(W) else: # for the VI models, we want E_q log q/p, which is closed form for Gaussians kl = tfp.distributions.kl_divergence(q, p) return samples, mean, cov, kl class AmortizedLatentVariableLayerTiled(gpflow.Module): regularizer_type = RegularizerType.LOCAL def __init__(self, latent_dim: int, sase_dim: int, encoder_dims: Optional[List[int]] = None): super().__init__() if encoder_dims is None: encoder = Encoder(latent_dim, sase_dim, [50, 10, 10]) else: encoder = Encoder(latent_dim, sase_dim, encoder_dims) self.latent_dim = tf.convert_to_tensor([latent_dim], dtype=tf.int32) self.sase_dim = tf.convert_to_tensor([sase_dim], dtype=tf.int32) self.encoder = encoder def propagate(self, F: tf.Tensor, inference_amortization_inputs: Optional[tf.Tensor] = None, is_sampled_local_regularizer: bool = False, **kwargs) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: if inference_amortization_inputs is None: """ If there isn't a SASE spec passed for the recognition model, this samples from the prior. Optionally, q_mu and q_sqrt can be fed via a placeholder (e.g. for plotting purposes) """ batch_shape = tf.convert_to_tensor(tf.shape(F)[:-3], dtype=tf.int32) # ... N = tf.convert_to_tensor([tf.shape(F)[-3]], dtype=tf.int32) S = tf.convert_to_tensor([tf.shape(F)[-2]//self.sase_dim[0]], dtype=tf.int32) shape = tf.concat([batch_shape, N, S, self.latent_dim], 0) # ...(N)L q_mu = tf.zeros(shape, dtype=gpflow.config.default_float()) q_sqrt = tf.ones(shape, dtype=gpflow.config.default_float()) else: q_mu, q_sqrt = self.encoder(inference_amortization_inputs) # reparameterization trick to take a sample for W eps = tf.random.normal(tf.shape(q_mu), dtype=gpflow.config.default_float()) W = q_mu + eps * q_sqrt tile_vec = tf.concat([tf.convert_to_tensor([1], dtype=tf.int32), self.sase_dim, tf.convert_to_tensor([1], dtype=tf.int32)],0) TW = tf.tile(W,tile_vec) Tmu = tf.tile(q_mu, tile_vec) Tsqrt = tf.tile(q_sqrt, tile_vec) samples = tf.concat([F, TW], -1) mean = tf.concat([F, Tmu], -1) cov = tf.concat([tf.zeros_like(F), Tsqrt ** 2], -1) # the prior regularization p = p = tfp.distributions.Normal(loc=tf.zeros(1,dtype=gpflow.config.default_float()), scale=0.1*tf.ones(1,dtype=gpflow.config.default_float())) q = tfp.distributions.Normal(loc=Tmu, scale=Tsqrt) if is_sampled_local_regularizer: # for the IW models, we need to return a log q/p for each sample W kl = q.log_prob(TW) - p.log_prob(TW) else: # for the VI models, we want E_q log q/p, which is closed form for Gaussians kl = tfp.distributions.kl_divergence(q, p) return samples, mean, cov, kl # + @attr.s(auto_attribs=True) class GPLayer_Config(object): ngps: int ninducing: int @attr.s(auto_attribs=True) class LatentLayer_Config(object): latent_features: int xy_dim: int @attr.s(auto_attribs=True) class EmbeddingLatentLayer_Config(object): latent_features: int nwords: int # -

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4de1e0c5390d6f6fd70a58694c12c28a57150b84

61

py

Python

hubspot/hubspot.py

fakepop/hubspot-api-python

f04103a09f93f5c26c99991b25fa76801074f3d3

[ "Apache-2.0" ]

117

2020-04-06T08:22:53.000Z

2022-03-18T03:41:29.000Z

hubspot/hubspot.py

fakepop/hubspot-api-python

f04103a09f93f5c26c99991b25fa76801074f3d3

[ "Apache-2.0" ]

62

2020-04-06T16:21:06.000Z

2022-03-17T16:50:44.000Z

hubspot/hubspot.py

fakepop/hubspot-api-python

f04103a09f93f5c26c99991b25fa76801074f3d3

[ "Apache-2.0" ]

45

2020-04-06T16:13:52.000Z

2022-03-30T21:33:17.000Z

from .client import Client class HubSpot(Client): pass

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1279d9e1f4a6fabf7f044bcb6bd3cecc3d1a508c

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py

Python

midi_websocket_server/__init__.py

xy124/python-midi-websocket-server

eecc42abb308253a412639fce019c2699db5388c

[ "MIT" ]

1

2022-03-24T20:32:31.000Z

midi_websocket_server/__init__.py

xy124/python-midi-websocket-server

eecc42abb308253a412639fce019c2699db5388c

[ "MIT" ]

null

midi_websocket_server/__init__.py

xy124/python-midi-websocket-server

eecc42abb308253a412639fce019c2699db5388c

[ "MIT" ]

1

2021-12-29T16:32:11.000Z

from .midi_websocket_server import *

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6

12a095aa6a4e68dde7c08ab7de0a170eac498bf7

1,244

py

Python

mailers/plugins/base.py

alex-oleshkevich/mailers

36836ae750cd190f75c96c5a78896d4ef830260e

[ "MIT" ]

17

2020-03-13T13:06:05.000Z

2022-03-06T00:17:45.000Z

mailers/plugins/base.py

alex-oleshkevich/mailers

36836ae750cd190f75c96c5a78896d4ef830260e

[ "MIT" ]

null

mailers/plugins/base.py

alex-oleshkevich/mailers

36836ae750cd190f75c96c5a78896d4ef830260e

[ "MIT" ]

null

import typing as t from email.message import Message from mailers.message import Email from mailers.result import SentMessages class Plugin(t.Protocol): # pragma: no cover def process_email(self, email: Email) -> Email: """Mailer calls it before sending.""" async def on_before_send(self, message: Message) -> None: """Called right before sending the message.""" async def on_after_send(self, message: Message, sent_messages: SentMessages) -> None: """Called right after sending the message.""" async def on_send_error(self, message: Message, sent_messages: SentMessages) -> None: """Called if no transport has delivered a message.""" class BasePlugin: # pragma: no cover def process_email(self, email: Email) -> Email: """Mailer calls it before sending.""" async def on_before_send(self, message: Message) -> None: """Called right before sending the message.""" async def on_after_send(self, message: Message, sent_messages: SentMessages) -> None: """Called right after sending the message.""" async def on_send_error(self, message: Message, sent_messages: SentMessages) -> None: """Called if no transport has delivered a message."""

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py

Python

experiment/__init__.py

anonymoussubmissionrepo/columnar_networks

3a1ea1dc2f25e5226bc37b9239d904f19b62d7b4

[ "Apache-2.0" ]

17

2021-07-23T06:16:54.000Z

2022-03-22T06:35:07.000Z

experiment/__init__.py

anonymoussubmissionrepo/columnar_networks

3a1ea1dc2f25e5226bc37b9239d904f19b62d7b4

[ "Apache-2.0" ]

1

2022-03-12T16:26:27.000Z

experiment/__init__.py

anonymoussubmissionrepo/columnar_networks

3a1ea1dc2f25e5226bc37b9239d904f19b62d7b4

[ "Apache-2.0" ]

7

2021-08-21T11:28:32.000Z

2022-03-04T07:01:48.000Z

from experiment.experiment import *

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6

12ef2178b2fc48385cafeb9a45a9659a02ff4323

30

py

Python

gliomagrowth/experiment/__init__.py

MIC-DKFZ/image-time-series

0480d5cb6936c7d9e839b6741f18c10893d78d8a

[ "MIT" ]

1

2021-11-29T17:46:58.000Z

gliomagrowth/experiment/__init__.py

MIC-DKFZ/image-time-series

0480d5cb6936c7d9e839b6741f18c10893d78d8a

[ "MIT" ]

null

gliomagrowth/experiment/__init__.py

MIC-DKFZ/image-time-series

0480d5cb6936c7d9e839b6741f18c10893d78d8a

[ "MIT" ]

null

from . import continuous_image

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424a4fe7026af3548cf7ceef3d3934f4e25da4f5

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py

Python

tests/elf/test_equality.py

junghee/LIEF

de7492ee49ef813cd8db3a858892e4ed5a5638c5

[ "Apache-2.0" ]

2,999

2017-04-03T13:43:23.000Z

2022-03-31T15:24:27.000Z

tests/elf/test_equality.py

junghee/LIEF

de7492ee49ef813cd8db3a858892e4ed5a5638c5

[ "Apache-2.0" ]

626

2017-04-04T15:57:04.000Z

2022-03-31T19:25:18.000Z

tests/elf/test_equality.py

junghee/LIEF

de7492ee49ef813cd8db3a858892e4ed5a5638c5

[ "Apache-2.0" ]

498

2017-04-04T14:18:25.000Z

2022-03-29T19:31:38.000Z

#!/usr/bin/env python import itertools import logging import os import random import stat import subprocess import sys import tempfile import unittest from unittest import TestCase import lief from utils import get_sample lief.logging.set_level(lief.logging.LOGGING_LEVEL.INFO) class TestEquality64(TestCase): def setUp(self): self.logger = logging.getLogger(__name__) self.input = lief.parse(get_sample("ELF/ELF64_x86-64_binary_all.bin")) _, output = tempfile.mkstemp(prefix="all_bis") self.input.write(output) self.output = lief.parse(output) def test_header(self): self.assertEqual(self.input.header, self.output.header) def test_sections(self): for l, r in zip(self.input.sections, self.output.sections): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_segments(self): for l, r in zip(self.input.segments, self.output.segments): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_relocations(self): for l, r in zip(self.input.relocations, self.output.relocations): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_symbols(self): for l, r in zip(self.input.symbols, self.output.symbols): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_dynamic_entries(self): for l, r in zip(self.input.dynamic_entries, self.output.dynamic_entries): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) class TestEquality32(TestCase): def setUp(self): self.logger = logging.getLogger(__name__) self.input = lief.parse(get_sample("ELF/ELF32_x86_binary_all.bin")) _, output = tempfile.mkstemp(prefix="all_bis") self.input.write(output) self.output = lief.parse(output) def test_header(self): self.assertEqual(self.input.header, self.output.header) def test_sections(self): for l, r in zip(self.input.sections, self.output.sections): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_segments(self): for l, r in zip(self.input.segments, self.output.segments): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_relocations(self): for l, r in zip(self.input.relocations, self.output.relocations): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_symbols(self): for l, r in zip(self.input.symbols, self.output.symbols): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) def test_dynamic_entries(self): for l, r in zip(self.input.dynamic_entries, self.output.dynamic_entries): self.assertEqual(l, r, "\n{!s}\n{!s}".format(l, r)) if __name__ == '__main__': root_logger = logging.getLogger() root_logger.setLevel(logging.DEBUG) ch = logging.StreamHandler() ch.setLevel(logging.DEBUG) root_logger.addHandler(ch) unittest.main(verbosity=2)

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py

Python

WidgetAPIHttpTrigger/tests/test_tidy_widget.py

office-for-students/beta-widget-api

ce06fae0979c1f8bd0b50a77548a7c99653e251d

[ "MIT" ]

null

WidgetAPIHttpTrigger/tests/test_tidy_widget.py

office-for-students/beta-widget-api

ce06fae0979c1f8bd0b50a77548a7c99653e251d

[ "MIT" ]

null

WidgetAPIHttpTrigger/tests/test_tidy_widget.py

office-for-students/beta-widget-api

ce06fae0979c1f8bd0b50a77548a7c99653e251d

[ "MIT" ]

null

import unittest from course_fetcher import CourseFetcher class TestTidyWidgetStats(unittest.TestCase): def test_employment_in_work_or_study_is_returned(self): expected_stats = {"employment": [{"aggregation_level": 14, "in_work_or_study": 95}], "nss": []} input_stats = { "employment": [ { "aggregation_level": 14, "assumed_to_be_unemployed": 5, "in_study": 80, "in_work": 5, "in_work_and_study": 5, "in_work_or_study": 95, "not_available_for_work_or_study": 0, "number_of_students": 15, "response_rate": 100, } ] } output_course = CourseFetcher.tidy_widget_stats(input_stats) self.assertEqual(expected_stats, output_course) def test_multiple_employment_in_work_or_study_is_returned_as_empty_array(self): expected_stats = { "employment": [], "nss": [] } input_stats = { "employment": [ { "aggregation_level": 14, "assumed_to_be_unemployed": 5, "in_study": 80, "in_work": 5, "in_work_and_study": 5, "in_work_or_study": 95, "not_available_for_work_or_study": 0, "number_of_students": 15, "response_rate": 100, }, { "aggregation_level": 14, "assumed_to_be_unemployed": 5, "in_study": 70, "in_work": 5, "in_work_and_study": 5, "in_work_or_study": 85, "not_available_for_work_or_study": 0, "number_of_students": 15, "response_rate": 100, }, ] } output_course = CourseFetcher.tidy_widget_stats(input_stats) self.assertEqual(expected_stats, output_course) def test_nss_question_1_returned(self): expected_stats = { "nss": [ { "question_1": { "description": "Staff are good at explaining things", "agree_or_strongly_agree": 79, } } ], "employment": [], } input_stats = { "nss": [ { "question_1": { "description": "Staff are good at explaining things", "agree_or_strongly_agree": 79, } } ], } output_course = CourseFetcher.tidy_widget_stats(input_stats) self.assertEqual(expected_stats, output_course) def test_multiple_nss_question_1_returned_as_empty_array(self): expected_stats = { "nss": [], "employment": [] } input_stats = { "nss": [ { "question_1": { "description": "Staff are good at explaining things", "agree_or_strongly_agree": 79, } }, { "question_1": { "description": "Staff are good at explaining things", "agree_or_strongly_agree": 93, } }, ] } output_course = CourseFetcher.tidy_widget_stats(input_stats) self.assertEqual(expected_stats, output_course) def test_nss_question_27_returned(self): expected_stats = { "nss": [ { "question_27": { "description": "Overall, I am satisfied with the quality of the course", "agree_or_strongly_agree": 84, } } ], "employment": [] } input_stats = { "nss": [ { "question_27": { "description": "Overall, I am satisfied with the quality of the course", "agree_or_strongly_agree": 84, } } ] } output_course = CourseFetcher.tidy_widget_stats(input_stats) self.assertEqual(expected_stats, output_course) def test_multiple_nss_question_27_returned_as_empty_array(self): expected_stats = { "nss": [], "employment": [] } input_stats = { "nss": [ { "question_27": { "description": "Overall, I am satisfied with the quality of the course", "agree_or_strongly_agree": 84, } }, { "question_27": { "description": "Overall, I am satisfied with the quality of the course", "agree_or_strongly_agree": 73, } }, ] } output_course = CourseFetcher.tidy_widget_stats(input_stats) self.assertEqual(expected_stats, output_course) # All being question 1 and 27 from nss and in_work_or_Study from employment def test_all_stats_returned(self): expected_stats = { 'nss': [ { 'question_1': { 'description': 'Staff are good at explaining things', 'agree_or_strongly_agree': 79 }, 'question_27': { 'description': 'Overall, I am satisfied with the quality of the course', 'agree_or_strongly_agree': 84 } }], 'employment': [ { 'aggregation_level': 14, 'in_work_or_study': 95 } ] } input_stats = { "nss": [ { "question_1": { "description": "Staff are good at explaining things", "agree_or_strongly_agree": 79, }, "question_2": { "description": "Staff have made the subject interesting", "agree_or_strongly_agree": 100, }, "question_3": { "description": "The course is intellectually stimulating", "agree_or_strongly_agree": 79, }, "question_4": { "description": "My course has challenged me to achieve my best work", "agree_or_strongly_agree": 89, }, "question_27": { "description": "Overall, I am satisfied with the quality of the course", "agree_or_strongly_agree": 84, }, } ], "employment": [ { "aggregation_level": 14, "assumed_to_be_unemployed": 5, "in_study": 80, "in_work": 5, "in_work_and_study": 5, "in_work_or_study": 95, "not_available_for_work_or_study": 0, "number_of_students": 15, "response_rate": 100, } ], } output_course = CourseFetcher.tidy_widget_stats(input_stats) self.assertEqual(expected_stats, output_course)

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0.440568

645

7,883

4.992248

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0.031677

0.069876

0.093168

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null

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null

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6

42a3b6929c100bcf916f8fb080c70b6d66e905a0

138

py

Python

src/sqlalchemy_dlock/utils.py

tanbro/sqlalchemy-dlock

9deadeb89f90d2a7512e9de8b038e0261604ba20

[ "BSD-3-Clause" ]

null

src/sqlalchemy_dlock/utils.py

tanbro/sqlalchemy-dlock

9deadeb89f90d2a7512e9de8b038e0261604ba20

[ "BSD-3-Clause" ]

2

2022-03-14T08:56:06.000Z

2022-03-23T06:57:03.000Z

src/sqlalchemy_dlock/utils.py

tanbro/sqlalchemy-dlock

9deadeb89f90d2a7512e9de8b038e0261604ba20

[ "BSD-3-Clause" ]

null

import re SAFE_NAME_PATTERN = re.compile(r'[^A-Za-z0-9_]+') def safe_name(s): return SAFE_NAME_PATTERN.sub('_', s).strip().lower()

17.25

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6

35ee5f61db28acaa99370beb666c9025d1d61254

129

py

Python

pydra/tasks/TODO/__init__.py

chasejohnson3/pydra-sem

d46468236568a50dd7dacf7e9d6a698a2fe67cb6

[ "Apache-2.0" ]

1

2020-11-25T19:34:12.000Z

pydra/tasks/TODO/__init__.py

chasejohnson3/pydra-sem

d46468236568a50dd7dacf7e9d6a698a2fe67cb6

[ "Apache-2.0" ]

2

2020-06-19T00:04:43.000Z

2020-12-29T22:22:43.000Z

pydra/tasks/TODO/__init__.py

chasejohnson3/pydra-sem

d46468236568a50dd7dacf7e9d6a698a2fe67cb6

[ "Apache-2.0" ]

3

2020-06-18T20:45:08.000Z

2020-11-20T16:56:53.000Z

""" >>> import pydra.tasks.TODO """ from ._version import get_versions __version__ = get_versions()["version"] del get_versions

16.125

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0.5625

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129

7

40

18.428571

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1

0

1

0

null

0

1

0

1

0

6

67147a562f12006ee076424e40089d11533f4f41

202

py

Python

app/tube/admin.py

tuvshinot/we_tube

9982adbb19508bbfc71e14d7e23b941ba46aa7b7

[ "MIT" ]

null

app/tube/admin.py

tuvshinot/we_tube

9982adbb19508bbfc71e14d7e23b941ba46aa7b7

[ "MIT" ]

null

app/tube/admin.py

tuvshinot/we_tube

9982adbb19508bbfc71e14d7e23b941ba46aa7b7

[ "MIT" ]

null

from django.contrib import admin from .models import Video, TubeChannel, TubeUser, Tag admin.site.register(Video) admin.site.register(TubeChannel) admin.site.register(TubeUser) admin.site.register(Tag)

28.857143

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true

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null

0

1

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0

6

671b96946d9a5f6d949b20d5f3f56e9769229914

154

py

Python

temap/tenant_management_application/doctype/tenancy_agreement/test_tenancy_agreement.py

EkpoEsua/temap

5f1abc943711cf9d3caf32fdc6ca681af9392453

[ "MIT" ]

null

temap/tenant_management_application/doctype/tenancy_agreement/test_tenancy_agreement.py

EkpoEsua/temap

5f1abc943711cf9d3caf32fdc6ca681af9392453

[ "MIT" ]

null

temap/tenant_management_application/doctype/tenancy_agreement/test_tenancy_agreement.py

EkpoEsua/temap

5f1abc943711cf9d3caf32fdc6ca681af9392453

[ "MIT" ]

null

17.111111

48

0.785714

19

154

6.368421

0.894737

0

0.030303

0.142857

154

8

49

19.25

0.886364

0.493506

0

1

0

true

0.333333

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1

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null

0

1

0

null

0

1

0

1

0

6

672338b6b311d62c8b42b90d48e9bb3b1738cf45

7,761

py

Python

app/models/hermes.py

nerevu/prometheus-api

f171406c4169d45d1a83df71a76128554988259f

[ "MIT" ]

9

2016-07-22T12:56:59.000Z

2021-12-27T09:09:32.000Z

app/models/hermes.py

nerevu/prometheus-api

f171406c4169d45d1a83df71a76128554988259f

[ "MIT" ]

null

app/models/hermes.py

nerevu/prometheus-api

f171406c4169d45d1a83df71a76128554988259f

[ "MIT" ]

7

2017-09-08T02:51:25.000Z

2020-11-19T17:50:01.000Z

# -*- coding: utf-8 -*- from __future__ import ( absolute_import, division, print_function, unicode_literals) import savalidation.validators as val from pprint import pprint from datetime import datetime as dt, date as d from app import db from savalidation import ValidationMixin from flask_sqlalchemy import SQLAlchemy from sqlalchemy.orm import backref from builtins import * # Hermes models class Exchange(db.Model, ValidationMixin): # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # other keys symbol = db.Column(db.String(12), unique=True, nullable=False) name = db.Column(db.String(64), nullable=False, unique=True) # validation val.validates_constraints() def __repr__(self): return ('<Exchange(%r, %r)>' % (self.symbol, self.name)) class DataSource(db.Model, ValidationMixin): # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # other keys name = db.Column(db.String(64), nullable=False, unique=True) # validation val.validates_constraints() def __repr__(self): return ('<DataSource(%r)>' % self.name) class CommodityGroup(db.Model, ValidationMixin): # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # other keys name = db.Column(db.String(64), nullable=False, unique=True) # validation val.validates_constraints() def __repr__(self): return ('<CommodityGroup(%r)>' % self.name) class CommodityType(db.Model, ValidationMixin): # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # foreign keys group_id = db.Column( db.Integer, db.ForeignKey( 'commodity_group.id', onupdate="CASCADE", ondelete="CASCADE"), nullable=False) group = db.relationship( 'CommodityGroup', backref=backref( 'types', cascade='all, delete'), lazy='joined') # other keys name = db.Column(db.String(64), nullable=False, unique=True) # validation val.validates_constraints() def __repr__(self): return ('<CommodityType(%r)>' % self.name) class Commodity(db.Model, ValidationMixin): # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # foreign keys type_id = db.Column( db.Integer, db.ForeignKey( 'commodity_type.id', onupdate="CASCADE", ondelete="CASCADE"), nullable=False) type = db.relationship( 'CommodityType', backref=backref('commodities', cascade='all, delete'), lazy='joined') data_source_id = db.Column( db.Integer, db.ForeignKey( 'data_source.id', onupdate="CASCADE", ondelete="CASCADE"), nullable=False) data_source = db.relationship( 'DataSource', backref=backref('commodities', cascade='all, delete'), lazy='joined') exchange_id = db.Column( db.Integer, db.ForeignKey('exchange.id'), nullable=False) exchange = db.relationship( 'Exchange', backref=backref('commodities', cascade='all, delete'), lazy='joined') # other keys # cusip = db.Column(db.String(16), unique=True) symbol = db.Column(db.String(12), unique=True, nullable=False) name = db.Column(db.String(64), nullable=False, unique=True) # validation val.validates_constraints() def __repr__(self): return ('<Commodity(%r, %r)>' % (self.symbol, self.name)) class EventType(db.Model, ValidationMixin): # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # other keys name = db.Column(db.String(64), nullable=False, unique=True) # validation val.validates_constraints() def __repr__(self): return '<Type(%r)>' % (self.name) class Event(db.Model, ValidationMixin): # table constraints __table_args__ = ( db.UniqueConstraint( 'commodity_id', 'date', 'type_id', 'currency_id'), {}) # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # foreign keys commodity_id = db.Column( db.Integer, db.ForeignKey('commodity.id'), nullable=False) commodity = db.relationship( 'Commodity', backref=backref('commodity_events', cascade='all, delete'), lazy='joined', primaryjoin='Commodity.id==Event.commodity_id') currency_id = db.Column( db.Integer, db.ForeignKey('commodity.id'), nullable=False) currency = db.relationship( 'Commodity', backref=backref('currency_events', cascade='all, delete'), lazy='joined', primaryjoin='Commodity.id==Event.currency_id') type_id = db.Column( db.Integer, db.ForeignKey('event_type.id'), nullable=False) type = db.relationship( 'EventType', backref=backref('events', cascade='all, delete'), lazy='joined') # other keys value = db.Column(db.Float, nullable=False) date = db.Column(db.DateTime, nullable=False, default=d.today()) # validation val.validates_constraints() def __repr__(self): return ( '<Event(%r, %r, %r, %r)>' % ( self.commodity_id, self.currency_id, self.value, self.date)) class Price(db.Model, ValidationMixin): # constraints __table_args__ = ( db.UniqueConstraint('commodity_id', 'currency_id', 'date'), {}) # auto keys id = db.Column(db.Integer, primary_key=True) utc_created = db.Column(db.DateTime, nullable=False, default=dt.utcnow()) utc_updated = db.Column( db.DateTime, nullable=False, default=dt.utcnow(), onupdate=dt.utcnow()) # foreign keys commodity_id = db.Column( db.Integer, db.ForeignKey('commodity.id'), nullable=False) commodity = db.relationship( 'Commodity', backref=backref('commodity_prices', cascade='all, delete'), lazy='joined', primaryjoin='Commodity.id==Price.commodity_id') currency_id = db.Column( db.Integer, db.ForeignKey('commodity.id'), nullable=False) currency = db.relationship( 'Commodity', backref=backref('currency_prices', cascade='all, delete'), lazy='joined', primaryjoin='Commodity.id==Price.currency_id') # other keys close = db.Column(db.Float, nullable=False) date = db.Column(db.DateTime, nullable=False, default=d.today()) # validation val.validates_constraints() def __repr__(self): return ( '<Price(%r, %r, %r, %r)>' % ( self.close, self.commodity_id, self.currency_id, self.date))

31.168675

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0.654297

929

7,761

5.34338

0.107643

0.074134

0.092667

0.06527

0.813255

0.800967

0.799758

0.702861

0.648066

0

0.003077

0.204355

7,761

248

80

31.294355

0.80081

0.053988

0

0.606667

0

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0.017241

0

1

0.053333

false

0

0.066667

0.053333

0.6

0.013333

0

null

0

1

0

1

0

null

0

1

0

6

db2186814662b95f517fcfd650b807085d7b5490

25,555

py

Python

tests/integrations/test_code_include.py

ColinKennedy/sphinx-code-include

c9449968ac8c626448bccbc943fcc817df01efab

[ "BSD-2-Clause" ]

2

2020-11-26T20:43:58.000Z

2021-01-18T08:32:21.000Z

tests/integrations/test_code_include.py

ColinKennedy/sphinx-code-include

c9449968ac8c626448bccbc943fcc817df01efab

[ "BSD-2-Clause" ]

null

tests/integrations/test_code_include.py

ColinKennedy/sphinx-code-include

c9449968ac8c626448bccbc943fcc817df01efab

[ "BSD-2-Clause" ]

1

2021-07-15T10:49:25.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- """A series of tests that access content outside of this repository.""" import textwrap import unittest from six.moves import mock from six.moves import urllib from .. import common def _skip_from_ssl_error(url): """bool: Check if the given URL can be reached.""" # This function is mostly meant for pypy3 try: from _cffi_ssl._stdssl import error except ImportError: return False try: return urllib.request.urlopen(url).getcode() == 200 # 200 means "URL not found" except (error.SSLError, urllib.error.URLError): return True class SourceReader(unittest.TestCase): """Check that external queries work.""" @mock.patch("code_include.source_code._get_app_inventory") def _test_import(self, content, expected, _get_app_inventory): """A generic test function. It tests for some source code from an importable Python object. Args: content (list[str]): The lines that the user provides in a standard code-include block. expected (str): The converted source-code text that will be tested for. _get_app_inventory (:class:`mock.mock.MagicMock`): The function that's normally used to query a Sphinx project's inventory to find every HTML file-path and tag-able header. """ _get_app_inventory.return_value = {"non-empty": {"information": tuple()}} directive = common.make_mock_directive(content) nodes = directive.run() self.assertNotEqual([], nodes) self.assertEqual(1, len(nodes)) self.assertEqual(expected, nodes[0].astext()) @mock.patch("code_include.source_code._get_source_module_data") @mock.patch("code_include.source_code._get_source_code_from_object") @mock.patch("code_include.source_code._get_app_inventory") @unittest.skipIf( _skip_from_ssl_error("https://ways.readthedocs.io/en/latest/objects.inv"), "URL could not be reached", ) def test_url( self, _get_app_inventory, _get_source_code_from_object, _get_source_module_data ): """Get the source-code of some project from a URL. Args: _get_app_inventory (:class:`mock.mock.MagicMock`): The function that's normally used to query a Sphinx project's inventory to find every HTML file-path and tag-able header. _get_source_code_from_object (:class:`mock.mock.MagicMock`): Force this function to get the code from intersphinx. _get_source_module_data (:class:`mock.mock.MagicMock`): A function that is mocked so that we can skip some of the less important tag-parsing functions and get to the point of this function - testing generated source-code. """ path = "https://ways.readthedocs.io/en/latest/objects.inv" _get_app_inventory.return_value = common.load_cache_from_url(path) _get_source_module_data.return_value = ( "https://ways.readthedocs.io/en/latest/_modules/ways/base/plugin.html", "DataPlugin", ) _get_source_code_from_object.return_value = "" expected = textwrap.dedent( """\ class DataPlugin(Plugin): '''An add-on that was made from a serialized file (JSON/YAML/etc). This class behaves exactly like a regular Plugin object and is stored in the same space as Plugin objects. DataPlugin does not add itself to the cache automatically. It is the responsibility of some other class/function to register it to Ways. We do this so that we can have better control over the DataPlugin's args and its assignment before it hits the cache. ''' add_to_registry = False def __init__(self, name, sources, info, assignment): '''Create the object and set its sources. Args: sources (list[str]): The location(s) that defined this Plugin. info (dict[str]): The information that came from a JSON or YAML file which sets the base settings of the object. assignment (str): The grouping location where this Plugin will go. This assignment must be the same as the Context that this Plugin is meant for. Raises: ValueError: If there are missing keys in data that this class needs. ''' missing_required_keys = set(self._required_keys()) - set(info.keys()) if missing_required_keys: raise ValueError('Info: "{info}" is missing keys, "{keys}".' ''.format(info=info, keys=missing_required_keys)) # Give this plugin a UUID if none was given, for us # Data is assumed to be a core.classes.dict_class.ReadOnlyDict so we # try to unlock it, here. If it's not a custom dict, just let it pass # try: is_settable = info.settable info.settable = True except AttributeError: pass info.setdefault('uuid', str(uuid.uuid4())) try: info.settable = is_settable except AttributeError: pass self.name = name self._info = info self.sources = tuple(sources) self._data = self._info.get('data', dict()) self.assignment = assignment super(DataPlugin, self).__init__() @classmethod def _required_keys(cls): '''tuple[str]: Keys that must be set in our Plugin.''' return ('hierarchy', ) def is_path(self): '''If the mapping is a filepath or None if unsure. Returns: bool or NoneType: If the mapping is a path to a file/folder on disk. ''' try: return self._info['path'] except KeyError: return None def get_assignment(self): '''str: Where this Plugin lives in Ways, along with its hierarchy.''' return self.assignment def get_groups(self): '''Get the groups that this Plugin evaluates onto. Note: The term 'groups' is not the same as the assignment of a Plugin. They are two different things. Returns: tuple[str]: The groups. ''' value = check.force_itertype(self._info.get('groups', ('*', )), itertype=tuple) is_empty = not [val for val in value if val.strip()] if is_empty: value = ('*', ) return value def get_hierarchy(self): '''tuple[str] or str: The location that this Plugin exists within.''' return self._info['hierarchy'] def get_mapping(self): '''str: The physical location of this Plugin (on the filesystem).''' try: return self._info['mapping'] except KeyError: return '' def get_mapping_details(self): '''dict[str]: Information about the mapping, if needed.''' return self._info.get('mapping_details', dict()) def get_max_folder(self): '''str: The furthest location up that this plugin can navigate to.''' return self._info.get('max_folder', '') def get_platforms(self): '''set[str]: The platforms that this Plugin is allowed to run on.''' platforms = ways.get_known_platfoms() return set(self._info.get('platforms', platforms)) def get_uses(self): '''tuple[str]: The Context hierarchies this instance depends on.''' return self._info.get('uses', tuple()) def get_uuid(self): '''str: A unique ID for this plugin.''' return self._info.get('uuid', '') def __repr__(self): '''str: The information needed to reproduce this instance.''' return '{cls_}(sources={sources!r}, data={data})'.format( cls_=self.__class__.__name__, sources=self.sources, data=dict(self._info)) def __str__(self): '''str: A more concise print-out of this instance.''' return '{cls_}(hierarchy={hierarchy}, sources={sources!r})'.format( cls_=self.__class__.__name__, hierarchy=self.get_hierarchy(), sources=self.sources)""" ) content = [":class:`ways.base.plugin.DataPlugin`"] directive = common.make_mock_directive(content) nodes = directive.run() self.assertNotEqual([], nodes) self.assertEqual(1, len(nodes)) self.assertEqual(expected, nodes[0].astext()) def test_import(self): """Get the source-code of an importable object.""" expected = textwrap.dedent( '''\ def fill(text, width=70, **kwargs): """Fill a single paragraph of text, returning a new string. Reformat the single paragraph in 'text' to fit in lines of no more than 'width' columns, and return a new string containing the entire wrapped paragraph. As with wrap(), tabs are expanded and other whitespace characters converted to space. See TextWrapper class for available keyword args to customize wrapping behaviour. """ w = TextWrapper(width=width, **kwargs) return w.fill(text)''') content = [":func:`textwrap.fill`"] self._test_import(content, expected) # pylint: disable=no-value-for-parameter @unittest.skipIf( _skip_from_ssl_error("https://ways.readthedocs.io/en/latest/objects.inv"), "URL could not be reached", ) class InventoryReader(unittest.TestCase): """Check that external queries to Sphinx intersphinx inventtory files work.""" @mock.patch("code_include.source_code._get_source_code_from_object") @mock.patch("code_include.source_code._get_app_inventory") def _test_import( self, content, expected, _get_app_inventory, _get_source_code_from_object, ): """A generic test function. It tests for some source code from an inventory. Args: content (list[str]): The lines that the user provides in a standard code-include block. expected (str): The converted source-code text that will be tested for. _get_app_inventory (:class:`mock.mock.MagicMock`): The function that gets dictionary information (which later finds the Sphinx Python source-code). _get_source_code_from_object (:class:`mock.mock.MagicMock`): The function that's used to import a Python object to get its source-code to find every HTML file-path and tag-able header. """ _get_source_code_from_object.return_value = "" path = "https://ways.readthedocs.io/en/latest/objects.inv" _get_app_inventory.return_value = common.load_cache_from_url(path) _get_source_code_from_object.return_value = "" directive = common.make_mock_directive(content) nodes = directive.run() self.assertNotEqual([], nodes) self.assertEqual(1, len(nodes)) self.assertEqual(expected, nodes[0].astext()) @mock.patch("code_include.source_code._get_source_module_data") def test_class(self, _get_source_module_data): """Get the source-code of an importable class.""" _get_source_module_data.return_value = ( "https://ways.readthedocs.io/en/latest/_modules/ways/base/plugin.html", "Plugin", ) content = [":class:`ways.base.plugin.Plugin`"] expected = textwrap.dedent( """\ @six.add_metaclass(PluginRegistry) class Plugin(object): '''An add-on that is later retrieved by Context to gather its data.''' add_to_registry = True _data = dict() @property def data(self): '''dict[str]: The display properties (like {'color': 'red'}).''' return self._data @data.setter def data(self, value): '''Set the data on this instance with whatever value is. Args: value (dict[str]): The new values for this instance. ''' self._data = value""" ) self._test_import(content, expected) # pylint: disable=no-value-for-parameter @mock.patch("code_include.source_code._get_source_module_data") def test_function(self, _get_source_module_data): """Get the source-code of an importable function.""" _get_source_module_data.return_value = ( "https://ways.readthedocs.io/en/latest/_modules/ways/base/plugin.html", "get_assignment", ) content = [":func:`ways.base.plugin.get_assignment`"] expected = textwrap.dedent( """\ def get_assignment(obj): '''str: Get an object's assignment or fallback to ways.DEFAULT_ASSIGNMENT.''' try: return obj.get_assignment() except AttributeError: return common.DEFAULT_ASSIGNMENT""" ) self._test_import(content, expected) # pylint: disable=no-value-for-parameter @mock.patch("code_include.source_code._get_source_module_data") def test_method(self, _get_source_module_data): """Get the source-code of an importable method.""" _get_source_module_data.return_value = ( "https://ways.readthedocs.io/en/latest/_modules/ways/base/plugin.html", "DataPlugin.get_groups", ) content = [":meth:`ways.base.plugin.DataPlugin.get_groups`"] expected = textwrap.dedent( """\ def get_groups(self): '''Get the groups that this Plugin evaluates onto. Note: The term 'groups' is not the same as the assignment of a Plugin. They are two different things. Returns: tuple[str]: The groups. ''' value = check.force_itertype(self._info.get('groups', ('*', )), itertype=tuple) is_empty = not [val for val in value if val.strip()] if is_empty: value = ('*', ) return value""" ) self._test_import(content, expected) # pylint: disable=no-value-for-parameter @mock.patch("code_include.source_code._get_source_module_data") def test_module(self, _get_source_module_data): """Get the source-code of an importable module.""" _get_source_module_data.return_value = ( "https://ways.readthedocs.io/en/latest/_modules/ways/base/plugin.html", "", ) content = [":mod:`ways.base.plugin`"] expected = textwrap.dedent( """\ #!/usr/bin/env python # -*- coding: utf-8 -*- '''A module that holds Plugin classes and objects that combine into a Context.''' # IMPORT STANDARD LIBRARIES import uuid # IMPORT THIRD-PARTY LIBRARIES import six # IMPORT WAYS LIBRARIES import ways # IMPORT LOCAL LIBRARIES from ..core import check from ..helper import common class PluginRegistry(type): '''A metaclass that adds new Plugin objects to a cache.''' def __new__(mcs, clsname, bases, attrs): '''Add the created object to the HistoryCache.''' new_class = super(PluginRegistry, mcs).__new__( mcs, clsname, bases, attrs) # TODO : We still need to not be using 'Plugin' ... # If we explicitly state not to register a plugin, don't register it # If add_to_registry isn't defined for this Plugin, # assume that we should register it # try: if new_class.__name__ == 'Plugin' or not new_class.add_to_registry: return new_class except AttributeError: return new_class assignment = get_assignment(new_class) ways.add_plugin(new_class(), assignment) return new_class # pylint: disable=too-few-public-methods @six.add_metaclass(PluginRegistry) class Plugin(object): '''An add-on that is later retrieved by Context to gather its data.''' add_to_registry = True _data = dict() @property def data(self): '''dict[str]: The display properties (like {'color': 'red'}).''' return self._data @data.setter def data(self, value): '''Set the data on this instance with whatever value is. Args: value (dict[str]): The new values for this instance. ''' self._data = value class DataPlugin(Plugin): '''An add-on that was made from a serialized file (JSON/YAML/etc). This class behaves exactly like a regular Plugin object and is stored in the same space as Plugin objects. DataPlugin does not add itself to the cache automatically. It is the responsibility of some other class/function to register it to Ways. We do this so that we can have better control over the DataPlugin's args and its assignment before it hits the cache. ''' add_to_registry = False def __init__(self, name, sources, info, assignment): '''Create the object and set its sources. Args: sources (list[str]): The location(s) that defined this Plugin. info (dict[str]): The information that came from a JSON or YAML file which sets the base settings of the object. assignment (str): The grouping location where this Plugin will go. This assignment must be the same as the Context that this Plugin is meant for. Raises: ValueError: If there are missing keys in data that this class needs. ''' missing_required_keys = set(self._required_keys()) - set(info.keys()) if missing_required_keys: raise ValueError('Info: "{info}" is missing keys, "{keys}".' ''.format(info=info, keys=missing_required_keys)) # Give this plugin a UUID if none was given, for us # Data is assumed to be a core.classes.dict_class.ReadOnlyDict so we # try to unlock it, here. If it's not a custom dict, just let it pass # try: is_settable = info.settable info.settable = True except AttributeError: pass info.setdefault('uuid', str(uuid.uuid4())) try: info.settable = is_settable except AttributeError: pass self.name = name self._info = info self.sources = tuple(sources) self._data = self._info.get('data', dict()) self.assignment = assignment super(DataPlugin, self).__init__() @classmethod def _required_keys(cls): '''tuple[str]: Keys that must be set in our Plugin.''' return ('hierarchy', ) def is_path(self): '''If the mapping is a filepath or None if unsure. Returns: bool or NoneType: If the mapping is a path to a file/folder on disk. ''' try: return self._info['path'] except KeyError: return None def get_assignment(self): '''str: Where this Plugin lives in Ways, along with its hierarchy.''' return self.assignment def get_groups(self): '''Get the groups that this Plugin evaluates onto. Note: The term 'groups' is not the same as the assignment of a Plugin. They are two different things. Returns: tuple[str]: The groups. ''' value = check.force_itertype(self._info.get('groups', ('*', )), itertype=tuple) is_empty = not [val for val in value if val.strip()] if is_empty: value = ('*', ) return value def get_hierarchy(self): '''tuple[str] or str: The location that this Plugin exists within.''' return self._info['hierarchy'] def get_mapping(self): '''str: The physical location of this Plugin (on the filesystem).''' try: return self._info['mapping'] except KeyError: return '' def get_mapping_details(self): '''dict[str]: Information about the mapping, if needed.''' return self._info.get('mapping_details', dict()) def get_max_folder(self): '''str: The furthest location up that this plugin can navigate to.''' return self._info.get('max_folder', '') def get_platforms(self): '''set[str]: The platforms that this Plugin is allowed to run on.''' platforms = ways.get_known_platfoms() return set(self._info.get('platforms', platforms)) def get_uses(self): '''tuple[str]: The Context hierarchies this instance depends on.''' return self._info.get('uses', tuple()) def get_uuid(self): '''str: A unique ID for this plugin.''' return self._info.get('uuid', '') def __repr__(self): '''str: The information needed to reproduce this instance.''' return '{cls_}(sources={sources!r}, data={data})'.format( cls_=self.__class__.__name__, sources=self.sources, data=dict(self._info)) def __str__(self): '''str: A more concise print-out of this instance.''' return '{cls_}(hierarchy={hierarchy}, sources={sources!r})'.format( cls_=self.__class__.__name__, hierarchy=self.get_hierarchy(), sources=self.sources) def get_assignment(obj): '''str: Get an object's assignment or fallback to ways.DEFAULT_ASSIGNMENT.''' try: return obj.get_assignment() except AttributeError: return common.DEFAULT_ASSIGNMENT""" ) self._test_import(content, expected) # pylint: disable=no-value-for-parameter

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0.141599

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0.018439

0.023356

0.823832

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0.805009

0.796789

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25,555

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40.180818

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0.25

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null

0

1

0

null

0

6

db23d6634bd85ecd44a9b24a4dfc2d59f0fc137f

100

py

Python

straintables/PrimerEngine/__init__.py

Gab0/linkageMapper

549b292e5b6ab22e03373483cd27236aa2f635eb

[ "MIT" ]

null

straintables/PrimerEngine/__init__.py

Gab0/linkageMapper

549b292e5b6ab22e03373483cd27236aa2f635eb

[ "MIT" ]

1

2020-05-03T15:13:07.000Z

2020-05-04T03:01:59.000Z

straintables/PrimerEngine/__init__.py

Gab0/straintables

549b292e5b6ab22e03373483cd27236aa2f635eb

[ "MIT" ]

null

#!/bin/python from . import GeneticEntities, PrimerDock, PrimerDesign from . import ampliconSanity

20

55

0.8

10

100

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0.8

0.25

0

0.12

100

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25

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0.12

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true

0

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1

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1

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null

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1

0

null

0

1

0

1

0

1

0

6

c020e29df15b71d096728a4664196f0aaeedd0dd

948

py

Python

algo/mad_seat.py

calfzhou/lazy-lab

dcd67845e4bd1e0c82a05a89f53eec6912d870f8

[ "MIT" ]

null

algo/mad_seat.py

calfzhou/lazy-lab

dcd67845e4bd1e0c82a05a89f53eec6912d870f8

[ "MIT" ]

null

algo/mad_seat.py

calfzhou/lazy-lab

dcd67845e4bd1e0c82a05a89f53eec6912d870f8

[ "MIT" ]

null

import random def Sit(n): seats = [i for i in xrange(n)] mad_seat = random.choice(seats) if mad_seat == 0: return True if mad_seat == n - 1: return False seats.remove(mad_seat) for i in xrange(1, n - 1): if i in seats: seat = i else: seat = random.choice(seats) seats.remove(seat) assert(len(seats) == 1) last_seat = seats.pop() return (last_seat == n - 1) and True or False def Sit2(n): seats = [i for i in xrange(n)] mad_seat = random.choice(seats) #if mad_seat == 0: return True if mad_seat == n - 1: return False seats.remove(mad_seat) for i in xrange(1, n - 1): #if i in seats: seat = i #else: seat = random.choice(seats) seats.remove(seat) assert(len(seats) == 1) last_seat = seats.pop() return (last_seat == n - 1) and True or False play_cnt = 10000 last_inplace = 0 for i in xrange(play_cnt): if Sit2(100): last_inplace += 1 print 'Inplace:', last_inplace, '/', play_cnt

25.621622

47

0.640295

166

948

3.548193

0.204819

0.095076

0.050934

0.101868

0.797963

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0.226793

948

36

48

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0.770805

0.060127

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0.6

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0.066667

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null

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null

0.033333

0

null

0

1

0

null

0

1

0

6

c032438cd46d5216c27f2330da14701e6fdf78df

36

py

Python

richcontext/scholapi/__init__.py

HaritzPuerto/RCApi

5616ffbc2b49f143ebe4111daa2763ed3472b36a

[ "CC0-1.0" ]

8

2020-01-08T16:49:55.000Z

2021-10-20T02:12:33.000Z

richcontext/scholapi/__init__.py

srand525/RCApi

c1f3cf96d1b176cd616830e6a4563585280c12e9

[ "CC0-1.0" ]

27

2020-01-09T19:58:59.000Z

2021-01-11T18:35:28.000Z

richcontext/scholapi/__init__.py

NYU-CI/RCApi

c1f3cf96d1b176cd616830e6a4563585280c12e9

[ "CC0-1.0" ]

3

2020-01-08T20:37:23.000Z

2021-09-04T10:57:37.000Z

from .scholapi import ScholInfraAPI

18

35

0.861111

4

36

7.75

1

0

0.111111

36

1

36

0.96875

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

fbf2a4f52d3e0d9140b6d8b31ed78c21bf834d7a

13,793

py

Python

cassiopeia/datastores/riotapi/leagues.py

bangingheads/cassiopeia-1

becf9b0e4703b40d0cf1e279eeb7777c421b7f48

[ "MIT" ]

null

cassiopeia/datastores/riotapi/leagues.py

bangingheads/cassiopeia-1

becf9b0e4703b40d0cf1e279eeb7777c421b7f48

[ "MIT" ]

null

cassiopeia/datastores/riotapi/leagues.py

bangingheads/cassiopeia-1

becf9b0e4703b40d0cf1e279eeb7777c421b7f48

[ "MIT" ]

null

from typing import Type, TypeVar, MutableMapping, Any, Iterable, Generator from datapipelines import DataSource, PipelineContext, Query, NotFoundError, validate_query from .common import RiotAPIService, APINotFoundError from ...data import Platform, Queue, Tier, Division from ...dto.league import LeagueEntriesDto, LeagueEntryDto, LeagueDto, LeagueSummonerEntriesDto, ChallengerLeagueListDto, MasterLeagueListDto, GrandmasterLeagueListDto from ..uniquekeys import convert_region_to_platform T = TypeVar("T") class LeaguesAPI(RiotAPIService): @DataSource.dispatch def get(self, type: Type[T], query: MutableMapping[str, Any], context: PipelineContext = None) -> T: pass @DataSource.dispatch def get_many(self, type: Type[T], query: MutableMapping[str, Any], context: PipelineContext = None) -> Iterable[T]: pass # League Entries _validate_get_league_entries_query = Query. \ has("queue").as_(Queue).also. \ has("tier").as_(Tier).also. \ has("division").as_(Division).also. \ has("page").as_(int).also. \ has("platform").as_(Platform) @get.register(LeagueEntriesDto) @validate_query(_validate_get_league_entries_query, convert_region_to_platform) def get_league_entries_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> LeagueEntriesDto: url = "https://{platform}.api.riotgames.com/lol/league/v4/entries/{queue}/{tier}/{division}".format( platform=query["platform"].value.lower(), queue=query["queue"].value, tier=query["tier"].value, division=query["division"].value ) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "leagues/paginated-entries") data = self._get(url, parameters={"page": query["page"]}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError: data = [] region = query["platform"].region.value for entry in data: entry["region"] = region return LeagueEntriesDto(entries=data, page=query["page"], region=query["region"].value, queue=query["queue"].value, tier=query["tier"].value, division=query["division"].value) _validate_get_league_summoner_entries_query = Query. \ has("summoner.id").as_(str).also. \ has("platform").as_(Platform) @get.register(LeagueSummonerEntriesDto) @validate_query(_validate_get_league_summoner_entries_query, convert_region_to_platform) def get_league_summoner_entries_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> LeagueSummonerEntriesDto: url = "https://{platform}.api.riotgames.com/lol/league/v4/entries/by-summoner/{id}".format( platform=query["platform"].value.lower(), id=query["summoner.id"] ) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "leagues/summoner-entries") data = self._get(url, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError: data = [] region = query["platform"].region.value for entry in data: entry["region"] = region return LeagueSummonerEntriesDto(entries=data, region=region, summonerId=query["summoner.id"]) # Leagues _validate_get_league_query = Query. \ has("id").as_(str).also. \ has("platform").as_(Platform) @get.register(LeagueDto) @validate_query(_validate_get_league_query, convert_region_to_platform) def get_leagues_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> LeagueDto: url = "https://{platform}.api.riotgames.com/lol/league/v4/leagues/{leagueId}".format(platform=query["platform"].value.lower(), leagueId=query["id"]) try: endpoint = "leagues/leagueId {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["region"] = query["platform"].region.value for entry in data["entries"]: entry["region"] = data["region"] entry["tier"] = data["tier"] return LeagueDto(data) _validate_get_many_league_query = Query. \ has("ids").as_(Iterable).also. \ has("platform").as_(Platform) @get_many.register(LeagueDto) @validate_query(_validate_get_many_league_query, convert_region_to_platform) def get_many_leagues_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> Generator[LeagueDto, None, None]: def generator(): for id in query["ids"]: url = "https://{platform}.api.riotgames.com/lol/league/v4/leagues/{leagueId}".format(platform=query["platform"].value.lower(), leagueId=id) try: endpoint = "leagues/leagueId {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data = {"leagues": data} data["region"] = query["platform"].region.value for league in data["leagues"]: league["region"] = data["region"] for entry in league["entries"]: entry["region"] = data["region"] yield LeagueDto(data) return generator() _validate_get_challenger_league_query = Query. \ has("queue").as_(Queue).also. \ has("platform").as_(Platform) @get.register(ChallengerLeagueListDto) @validate_query(_validate_get_challenger_league_query, convert_region_to_platform) def get_challenger_league_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> ChallengerLeagueListDto: url = "https://{platform}.api.riotgames.com/lol/league/v4/challengerleagues/by-queue/{queueName}".format(platform=query["platform"].value.lower(), queueName=query["queue"].value) try: endpoint = "challengerleagues/by-queue {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["region"] = query["platform"].region.value data["queue"] = query["queue"].value for entry in data["entries"]: entry["region"] = data["region"] return ChallengerLeagueListDto(data) _validate_get_many_challenger_league_query = Query. \ has("queues").as_(Iterable).also. \ has("platform").as_(Platform) @get_many.register(ChallengerLeagueListDto) @validate_query(_validate_get_many_challenger_league_query, convert_region_to_platform) def get_challenger_leagues_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> Generator[ChallengerLeagueListDto, None, None]: def generator(): for queue in query["queues"]: url = "https://{platform}.api.riotgames.com/lol/league/v4/challengerleagues/by-queue/{queueName}".format(platform=query["platform"].value.lower(), queueName=queue.value) try: endpoint = "challengerleagues/by-queue {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data = {"leagues": data} data["region"] = query["platform"].region.value data["queue"] = queue.value for entry in data["entries"]: entry["region"] = data["region"] yield ChallengerLeagueListDto(data) return generator() _validate_get_grandmaster_league_query = Query. \ has("queue").as_(Queue).also. \ has("platform").as_(Platform) @get.register(GrandmasterLeagueListDto) @validate_query(_validate_get_grandmaster_league_query, convert_region_to_platform) def get_grandmaster_league_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> GrandmasterLeagueListDto: url = "https://{platform}.api.riotgames.com/lol/league/v4/grandmasterleagues/by-queue/{queueName}".format(platform=query["platform"].value.lower(), queueName=query["queue"].value) try: endpoint = "grandmasterleagues/by-queue {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["region"] = query["platform"].region.value data["queue"] = query["queue"].value for entry in data["entries"]: entry["region"] = data["region"] return GrandmasterLeagueListDto(data) _validate_get_many_grandmaster_league_query = Query. \ has("queues").as_(Iterable).also. \ has("platform").as_(Platform) @get_many.register(GrandmasterLeagueListDto) @validate_query(_validate_get_many_grandmaster_league_query, convert_region_to_platform) def get_grandmaster_leagues_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> Generator[GrandmasterLeagueListDto, None, None]: def generator(): for queue in query["queues"]: url = "https://{platform}.api.riotgames.com/lol/league/v4/grandmasterleagues/by-queue/{queueName}".format(platform=query["platform"].value.lower(), queueName=queue.value) try: endpoint = "grandmasterleagues/by-queue {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data = {"leagues": data} data["region"] = query["platform"].region.value data["queue"] = queue.value for entry in data["entries"]: entry["region"] = data["region"] yield GrandmasterLeagueListDto(data) return generator() _validate_get_master_league_query = Query. \ has("queue").as_(Queue).also. \ has("platform").as_(Platform) @get.register(MasterLeagueListDto) @validate_query(_validate_get_master_league_query, convert_region_to_platform) def get_master_league_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> MasterLeagueListDto: url = "https://{platform}.api.riotgames.com/lol/league/v4/masterleagues/by-queue/{queueName}".format(platform=query["platform"].value.lower(), queueName=query["queue"].value) try: endpoint = "masterleagues/by-queue {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["region"] = query["platform"].region.value data["queue"] = query["queue"].value for entry in data["entries"]: entry["region"] = data["region"] return MasterLeagueListDto(data) _validate_get_many_master_league_query = Query. \ has("queues").as_(Iterable).also. \ has("platform").as_(Platform) @get_many.register(MasterLeagueListDto) @validate_query(_validate_get_many_master_league_query, convert_region_to_platform) def get_master_leagues_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> Generator[MasterLeagueListDto, None, None]: def generator(): for queue in query["queues"]: url = "https://{platform}.api.riotgames.com/lol/league/v4/masterleagues/by-queue/{queueName}".format(platform=query["platform"].value.lower(), queueName=queue.value) try: endpoint = "masterleagues/by-queue {}".format(query["platform"].value) app_limiter, method_limiter = self._get_rate_limiter(query["platform"], endpoint) data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data = {"leagues": data} data["region"] = query["platform"].region.value data["queue"] = queue.value for entry in data["entries"]: entry["region"] = data["region"] yield MasterLeagueListDto(data) return generator()

52.049057

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0.655115

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13,793

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0.068744

0.052704

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0.741522

0.737053

0.724221

0.713451

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0.218227

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0.073395

false

0.009174

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0.197248

0

null

0

1

0

null

0

6

222b17d6d8f5d0e44310a252d8b182262c331e1d

101

py

Python

test/test_component_1/__init__.py

denis-itskovich/flask-composer

b847e153255ea839a922b149e37f8814b4ecc00b

[ "Apache-2.0" ]

2

2015-08-17T12:43:08.000Z

2015-09-24T06:22:02.000Z

test/test_component_1/__init__.py

denis-itskovich/flask-composer

b847e153255ea839a922b149e37f8814b4ecc00b

[ "Apache-2.0" ]

null

test/test_component_1/__init__.py

denis-itskovich/flask-composer

b847e153255ea839a922b149e37f8814b4ecc00b

[ "Apache-2.0" ]

null

from flask.ext.composer import Component test_component_1 = Component('test_component_1', __name__)

25.25

58

0.831683

14

101

5.428571

0.642857

0.342105

0.578947

0.605263

0

0.021739

0.089109

101

3

59

33.666667

0.804348

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0

1

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false

0

0.5

0

0.5

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null

1

0

1

0

null

0

1

0

6

2234f01954130342d9f554ca44c7e4af5005960e

10,929

py

Python

directord/tests/test_client.py

peznauts/directord

881eff5e4aeed40bcc229c58a2c055b193006295

[ "Apache-2.0" ]

null

directord/tests/test_client.py

peznauts/directord

881eff5e4aeed40bcc229c58a2c055b193006295

[ "Apache-2.0" ]

null

directord/tests/test_client.py

peznauts/directord

881eff5e4aeed40bcc229c58a2c055b193006295

[ "Apache-2.0" ]

null

# Copyright Peznauts <kevin@cloudnull.com>. 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. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License 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 json from unittest.mock import ANY from unittest.mock import patch from directord import client from directord import tests class TestClient(tests.TestDriverBase): def setUp(self): super(TestClient, self).setUp() self.args = tests.FakeArgs() self.client = client.Client(args=self.args) self.client.driver = self.mock_driver @patch("time.time", autospec=True) def test_run_job(self, mock_time): job_def = { "job_sha3_224": "YYY", "skip_cache": True, "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, None, json.dumps(job_def), None, None, None, ) ] mock_time.side_effect = [1, 1, 1, 1, 1, 1, 1] with patch.object(self.mock_driver, "job_check", return_value=False): self.client.run_job() @patch("time.time", autospec=True) def test_run_job_idle(self, mock_time): job_def = { "job_sha3_224": "YYY", "skip_cache": True, "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, None, json.dumps(job_def), None, None, None, ) ] mock_time.side_effect = [1, 1, 66, 1, 1, 1, 1] with patch.object(self.mock_driver, "job_check", return_value=False): self.client.run_job() @patch("time.time", autospec=True) def test_run_job_ramp(self, mock_time): job_def = { "job_sha3_224": "YYY", "skip_cache": True, "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, None, json.dumps(job_def), None, None, None, ) ] mock_time.side_effect = [1, 1, 1, 34, 1, 1, 1] with patch.object(self.mock_driver, "job_check", return_value=False): self.client.run_job() @patch("shelve.open", autospec=True) @patch("time.time", autospec=True) def test_run_job_cache_check( self, mock_time, mock_diskcache, ): job_def = { "job_sha3_224": "YYY", "skip_cache": True, "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, None, json.dumps(job_def), None, None, None, ) ] mock_time.side_effect = [1, 1, 1, 1, 5000, 1, 1, 1, 1, 1] mock_diskcache.return_value = tests.FakeCache() with patch.object(self.mock_driver, "job_check", return_value=False): self.client.run_job() @patch("shelve.open", autospec=True) @patch("logging.Logger.debug", autospec=True) @patch("time.time", autospec=True) def test_run_job_skip_skip_cache_run( self, mock_time, mock_log_info, mock_diskcache, ): job_def = { "job_sha3_224": "YYY", "skip_cache": True, "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, "RUN", json.dumps(job_def), "", None, None, ) ] mock_diskcache.return_value = tests.FakeCache() mock_time.side_effect = [1, 1, 1, 1, 1, 1, 1] with patch.object(self.mock_driver, "job_check") as mock_job_check: mock_job_check.side_effect = [True, False] self.client.run_job() mock_log_info.assert_called() @patch("shelve.open", autospec=True) @patch("logging.Logger.debug", autospec=True) @patch("time.time", autospec=True) def test_run_job_skip_ignore_cache_run( self, mock_time, mock_log_info, mock_diskcache, ): job_def = { "job_id": "XXX", "job_sha3_224": "YYY", "ignore_cache": True, "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, "RUN", json.dumps(job_def), "", None, None, ) ] mock_diskcache.return_value = tests.FakeCache() mock_time.side_effect = [1, 1, 1, 1, 1, 1, 1] with patch.object(self.mock_driver, "job_check") as mock_job_check: mock_job_check.side_effect = [True, False] self.client.run_job() mock_log_info.assert_called() @patch("shelve.open", autospec=True) @patch("logging.Logger.debug", autospec=True) @patch("time.time", autospec=True) def test_run_job_parent_failed_run( self, mock_time, mock_log_info, mock_diskcache, ): job_def = { "job_id": "XXX", "job_sha3_224": "YYY", "parent_id": "ZZZ", "command": "RUN", } self.mock_driver.job_recv.side_effect = [ ( None, None, "RUN", json.dumps(job_def), "", None, None, ) ] cache = mock_diskcache.return_value = tests.FakeCache() cache.set(key="ZZZ", value=False) mock_time.side_effect = [1, 1, 1, 1, 1, 1, 1] with patch.object(self.mock_driver, "job_check") as mock_job_check: mock_job_check.side_effect = [True, False] self.client.run_job() mock_log_info.assert_called() @patch("shelve.open", autospec=True) @patch("logging.Logger.debug", autospec=True) @patch("time.time", autospec=True) def test_run_job_cache_hit_run( self, mock_time, mock_log_info, mock_diskcache, ): job_def = { "job_id": "XXX", "job_sha3_224": "YYY", "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, "RUN", json.dumps(job_def), "", None, None, ) ] cache = mock_diskcache.return_value = tests.FakeCache() cache.set(key="YYY", value=self.mock_driver.job_end) mock_time.side_effect = [1, 1, 1, 1, 1, 1, 1] with patch.object(self.client, "cache", cache): with patch.object(self.mock_driver, "job_check") as mock_job_check: mock_job_check.side_effect = [True, False] self.client.run_job() mock_log_info.assert_called() @patch("shelve.open", autospec=True) @patch("logging.Logger.debug", autospec=True) @patch("time.time", autospec=True) def test_run_job_run( self, mock_time, mock_log_info, mock_diskcache, ): job_def = { "job_id": "XXX", "job_sha3_224": "YYY", "command": "RUN", "parent_id": "ZZZ", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, "RUN", json.dumps(job_def), "", None, None, ) ] cache = mock_diskcache.return_value = tests.FakeCache() cache.set(key="YYY", value=self.mock_driver.job_end) mock_time.side_effect = [1, 1, 1, 1, 1, 1, 1] with patch.object(self.client, "cache", cache): with patch.object(self.mock_driver, "job_check") as mock_job_check: mock_job_check.side_effect = [True, False] self.client.run_job() mock_log_info.assert_called() self.assertEqual(cache.get("YYY"), self.mock_driver.job_end) @patch("shelve.open", autospec=True) @patch("logging.Logger.debug", autospec=True) @patch("time.time", autospec=True) def test_run_job_run_outcome_false( self, mock_time, mock_log_info, mock_diskcache, ): job_def = { "job_id": "XXX", "job_sha3_224": "YYY", "command": "RUN", "job_id": "XXX", "job_sha3_224": "YYY", } self.mock_driver.job_recv.side_effect = [ ( None, None, "RUN", json.dumps(job_def), "", None, None, ) ] cache = mock_diskcache.return_value = tests.FakeCache() cache.set(key="YYY", value=self.mock_driver.job_failed) mock_time.side_effect = [1, 1, 1, 1, 1, 1, 1] with patch.object(self.mock_driver, "job_check") as mock_job_check: mock_job_check.side_effect = [True, False] self.client.run_job() mock_log_info.assert_called() self.assertEqual(cache.get("YYY"), self.mock_driver.job_failed) @patch("os.makedirs", autospec=True) @patch("directord.client.Client.run_threads", autospec=True) def test_worker_run(self, mock_run_threads, mock_makedirs): self.client.worker_run() mock_run_threads.assert_called_with(ANY, threads=[ANY], stop_event=ANY) mock_makedirs.assert_called()

31.048295

79

0.509836

1,233

10,929

4.257908

0.116788

0.021714

0.025143

0.024381

0.795619

0.79181

0.784571

0.777333

0

0.023035

0.372404

10,929

351

80

31.136752

0.742382

0.055083

0

0.767081

0

0.103385

0.003394

0

0.031056

1

0.037267

false

0

0.015528

0

0.055901

0

null

0

1

0

1

0

null

0

6

226c25292c8ca14c6cff5b7e3c63433468e01bb7

227

py

Python

p0002/test_p0002.py

th3-z/euler

cccb6b2ccb6bf443ff42b28c7a7bf1d8e3c91af2

[ "MIT" ]

null

p0002/test_p0002.py

th3-z/euler

cccb6b2ccb6bf443ff42b28c7a7bf1d8e3c91af2

[ "MIT" ]

null

p0002/test_p0002.py

th3-z/euler

cccb6b2ccb6bf443ff42b28c7a7bf1d8e3c91af2

[ "MIT" ]

null

from p0002 import fib_even def test_fib_even(): assert sum(fib_even(4000000)) == 4613732 assert sum(fib_even(0)) == 0 assert sum(fib_even(-1)) == 0 assert sum(fib_even(2)) == 2 assert sum(fib_even(3)) == 2

25.222222

44

0.643172

39

227

3.538462

0.384615

0.355072

0.434783

0.57971

0.246377

0

0.144444

0.207048

227

8

45

28.375

0.622222

0

0.714286

1

0.142857

true

0

0.142857

0

0.285714

0

null

1

0

1

0

null

0

1

0

1

0

6

227a4fecc596058e74492c76aa1863757883fec5

18,686

py

Python

nailgun/nailgun/test/unit/test_network_check.py

Axam/nsx-web

4f60d71c05e08740cbdf19b6c9bb0c4cb1e29ad5

[ "Apache-2.0" ]

1

2021-04-06T16:13:35.000Z

nailgun/nailgun/test/unit/test_network_check.py

Axam/nsx-web

4f60d71c05e08740cbdf19b6c9bb0c4cb1e29ad5

[ "Apache-2.0" ]

null

nailgun/nailgun/test/unit/test_network_check.py

Axam/nsx-web

4f60d71c05e08740cbdf19b6c9bb0c4cb1e29ad5

[ "Apache-2.0" ]

null

# Copyright 2013 Mirantis, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License 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. from nailgun.db.sqlalchemy.models import Cluster from nailgun.db.sqlalchemy.models import NetworkGroup from nailgun.db.sqlalchemy.models import node from nailgun.errors import errors from nailgun.network.checker import NetworkCheck from nailgun.task import helpers from nailgun.test.base import BaseIntegrationTest from mock import MagicMock from mock import patch class FakeTask(object): def __init__(self, cluster): self.cluster = cluster class TestNetworkCheck(BaseIntegrationTest): def setUp(self): super(TestNetworkCheck, self).setUp() self.env.create( cluster_kwargs={}, nodes_kwargs=[ {"api": True, "pending_addition": True}, ] ) self.task = FakeTask(self.env.clusters[0]) @patch.object(helpers, 'db') def test_check_untagged_intersection_failed(self, mocked_db): cluster = self.env.create( nodes_kwargs=[ {'roles': ['controller'], 'pending_addition': True} ] ) cluster_db = self.db.query(Cluster).get(cluster['id']) checker = NetworkCheck(FakeTask(cluster_db), {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'fake1', 'vlan_start': None, 'meta': {'notation': 'cidr'}}, {'id': 2, 'cidr': '192.168.0.0/26', 'name': 'fake2', 'vlan_start': None, 'meta': {'notation': 'cidr'}}] ng1 = NetworkGroup() ng1.name = 'fake1' ng1.id = 1 ng2 = NetworkGroup() ng2.name = 'fake2' ng2.id = 2 checker.cluster.nodes[0].interfaces[0].assigned_networks_list = \ [ng1, ng2] checker.cluster.nodes[0].interfaces[1].assigned_networks_list = \ [ng1, ng2] self.assertRaises(errors.NetworkCheckError, checker.check_untagged_intersection) def test_check_untagged_intersection(self): cluster = self.env.create( nodes_kwargs=[ {'roles': ['controller'], 'pending_addition': True} ] ) cluster_db = self.db.query(Cluster).get(cluster['id']) checker = NetworkCheck(FakeTask(cluster_db), {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'fake1', 'vlan_start': None, 'meta': {'notation': 'cidr'}}] ng1 = NetworkGroup() ng1.name = 'fake3' ng1.id = 3 ng2 = NetworkGroup() ng2.name = 'fake4' ng2.id = 4 checker.cluster.nodes[0].interfaces[0].assigned_networks_list = \ [ng1, ng2] self.assertNotRaises(errors.NetworkCheckError, checker.check_untagged_intersection) @patch.object(helpers, 'db') def test_check_network_address_spaces_intersection(self, mocked_db): checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'fake1', 'meta': {'notation': 'cidr'}}, {'id': 2, 'cidr': '192.168.0.0/26', 'name': 'fake2', 'meta': {'notation': 'cidr'}}] self.assertRaises(errors.NetworkCheckError, checker.check_network_address_spaces_intersection) checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'fake1', 'meta': {'notation': 'cidr'}}, {'id': 2, 'cidr': '192.168.1.0/26', 'name': 'fake2', 'meta': {'notation': 'cidr'}}] checker.network_config['fixed_networks_cidr'] = '10.20.0.0/24' self.assertNotRaises(errors.NetworkCheckError, checker.check_network_address_spaces_intersection) checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'fake1', 'meta': {'notation': 'cidr'}}, {'id': 2, 'cidr': '10.20.0.0/26', 'name': 'fake2', 'meta': {'notation': 'cidr'}}] checker.network_config['fixed_networks_cidr'] = '10.20.0.0/24' self.assertRaises(errors.NetworkCheckError, checker.check_network_address_spaces_intersection) @patch.object(helpers, 'db') def test_check_public_floating_ranges_intersection(self, mocked_db): checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'public', 'gateway': '192.168.0.1', 'ip_ranges': ['192.168.0.1', '192.168.0.100'], 'meta': {'notation': 'cidr'}}] checker.network_config['floating_ranges'] = ['192.168.0.100', '192.168.0.199'] self.assertRaises(errors.NetworkCheckError, checker.check_public_floating_ranges_intersection) checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'public', 'gateway': '192.168.0.1', 'ip_ranges': [('192.168.0.1', '192.168.0.254')], 'meta': {'notation': 'cidr'}}] checker.network_config['floating_ranges'] = ['192.168.2.0/24'] self.assertRaises(errors.NetworkCheckError, checker.check_public_floating_ranges_intersection) checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'public', 'gateway': '192.168.0.1', 'ip_ranges': [('192.168.0.2', '192.168.0.254')], 'meta': {'notation': 'cidr'}}] checker.network_config['floating_ranges'] = ['192.168.2.0/24'] self.assertNotRaises(errors.NetworkCheckError, checker.check_public_floating_ranges_intersection) @patch.object(helpers, 'db') def test_check_vlan_ids_range_and_intersection_failed(self, mocked_db): checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'fixed', 'gateway': '192.168.0.1', 'vlan_start': 1}] checker.network_config['fixed_networks_vlan_start'] = 1 checker.network_config['fixed_networks_amount'] = 10 self.assertRaises(errors.NetworkCheckError, checker.check_vlan_ids_range_and_intersection) @patch.object(helpers, 'db') def test_check_vlan_ids_range_and_intersection(self, mocked_db): checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'name': 'fixed', 'gateway': '192.168.0.1', 'vlan_start': 200}] checker.network_config['fixed_networks_vlan_start'] = 2 checker.network_config['fixed_networks_amount'] = 10 self.assertNotRaises(errors.NetworkCheckError, checker.check_vlan_ids_range_and_intersection) @patch.object(helpers, 'db') def test_check_networks_amount(self, mocked_db): checker = NetworkCheck(self.task, {}) checker.network_config['net_manager'] = 'FlatDHCPManager' checker.network_config['fixed_networks_amount'] = 2 self.assertNotRaises(errors.NetworkCheckError, checker.check_networks_amount) checker = NetworkCheck(self.task, {}) checker.network_config['net_manager'] = 'FlatDHCPManager' checker.network_config['fixed_networks_amount'] = 1 self.assertNotRaises(errors.NetworkCheckError, checker.check_networks_amount) checker = NetworkCheck(self.task, {}) checker.network_config['fixed_network_size'] = 100 checker.network_config['fixed_networks_amount'] = 3 checker.network_config['fixed_networks_cidr'] = '192.168.10.1/24' self.assertNotRaises(errors.NetworkCheckError, checker.check_networks_amount) checker = NetworkCheck(self.task, {}) checker.network_config['fixed_network_size'] = 10 checker.network_config['fixed_networks_amount'] = 1 checker.network_config['fixed_networks_cidr'] = '192.168.10.1/24' self.assertNotRaises(errors.NetworkCheckError, checker.check_networks_amount) @patch.object(helpers, 'db') def test_neutron_check_l3_addresses_not_match_subnet_and_broadcast( self, mocked_db): checker = NetworkCheck(self.task, {}) checker.network_config['floating_ranges'] = [('192.168.0.1', '192.168.0.255')] checker.network_config['internal_cidr'] = '192.168.0.0/24' checker.network_config['internal_gateway'] = '192.168.0.0' checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'gateway': '192.168.0.1', 'name': 'public'}] self.assertRaises( errors.NetworkCheckError, checker.neutron_check_l3_addresses_not_match_subnet_and_broadcast) self.assertEqual(len(checker.err_msgs), 2) def test_check_network_classes_exclude_loopback(self): checker = NetworkCheck(self.task, {}) checker.networks = [{'cidr': '192.168.0.0/24'}] self.assertNotRaises(errors.NetworkCheckError, checker.check_network_classes_exclude_loopback) @patch.object(helpers, 'db') def test_check_network_classes_exclude_loopback_fail(self, mocked_db): checker = NetworkCheck(self.task, {}) networks = ['224.0.0.0/3', '127.0.0.0/8'] for network in networks: checker.networks = [{'id': 1, 'cidr': network, 'name': 'fake'}] self.assertRaises(errors.NetworkCheckError, checker.check_network_classes_exclude_loopback) self.assertEqual(mocked_db.call_count, 4) @patch.object(helpers, 'db') def test_check_network_addresses_not_match_subnet_and_broadcast(self, mocked_db): checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'gateway': '192.168.0.1', 'name': 'fake1', 'meta': {'notation': 'ip_ranges'}}] self.assertNotRaises( errors.NetworkCheckError, checker.check_network_addresses_not_match_subnet_and_broadcast) checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'gateway': '192.168.0.0', 'name': 'fake1', 'meta': {'notation': 'ip_ranges'}}] self.assertRaises( errors.NetworkCheckError, checker.check_network_addresses_not_match_subnet_and_broadcast) checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'ip_ranges': ['192.168.0.1', '192.168.0.100'], 'gateway': '192.168.0.0', 'name': 'fake1', 'meta': {'notation': 'ip_ranges'}}] self.assertRaises( errors.NetworkCheckError, checker.check_network_addresses_not_match_subnet_and_broadcast) checker = NetworkCheck(self.task, {}) checker.networks = [{'id': 1, 'cidr': '192.168.0.0/24', 'ip_ranges': ['192.168.1.1', '192.168.1.100'], 'gateway': '192.168.0.1', 'name': 'fake1', 'meta': {'notation': 'ip_ranges'}}] self.assertNotRaises( errors.NetworkCheckError, checker.check_network_addresses_not_match_subnet_and_broadcast) def test_check_bond_slaves_speeds(self): cluster = self.env.create( nodes_kwargs=[ {'roles': ['controller'], 'pending_addition': True} ] ) cluster_db = self.db.query(Cluster).get(cluster['id']) checker = NetworkCheck(FakeTask(cluster_db), {}) checker.check_bond_slaves_speeds() self.assertEqual(checker.err_msgs, []) bond_if1 = node.NodeBondInterface() bond_if2 = node.NodeBondInterface() nic1 = node.NodeNICInterface() nic2 = node.NodeNICInterface() nic3 = node.NodeNICInterface() nic1.current_speed = 100 nic2.current_speed = 10 nic3.current_speed = None bond_if1.slaves = [nic1, nic2, nic3] bond_if2.slaves = [nic3] checker.cluster.nodes[0].bond_interfaces = [bond_if1, bond_if2] checker.check_bond_slaves_speeds() self.assertEqual(len(checker.err_msgs), 2) def test_check_configuration_neutron(self): checker = NetworkCheck(self.task, {}) checker.net_provider = 'neutron' checker.neutron_check_network_address_spaces_intersection = MagicMock() checker.neutron_check_segmentation_ids = MagicMock() checker.neutron_check_l3_addresses_not_match_subnet_and_broadcast = \ MagicMock() checker.check_public_floating_ranges_intersection = MagicMock() checker.check_network_address_spaces_intersection = MagicMock() checker.check_networks_amount = MagicMock() checker.check_vlan_ids_range_and_intersection = MagicMock() checker.check_network_classes_exclude_loopback = MagicMock() checker.check_network_addresses_not_match_subnet_and_broadcast = \ MagicMock() checker.check_configuration() not_called = [ 'check_public_floating_ranges_intersection', 'check_network_address_spaces_intersection', 'check_networks_amount', 'check_vlan_ids_range_and_intersection' ] for method in not_called: mocked = getattr(checker, method) self.assertFalse(mocked.called) called = [ 'neutron_check_network_address_spaces_intersection', 'neutron_check_segmentation_ids', 'neutron_check_l3_addresses_not_match_subnet_and_broadcast', 'check_network_classes_exclude_loopback', 'check_network_addresses_not_match_subnet_and_broadcast' ] for method in called: mocked = getattr(checker, method) mocked.assert_any_call() def test_check_configuration_nova_network(self): checker = NetworkCheck(self.task, {}) checker.net_provider = 'nova-network' checker.neutron_check_network_address_spaces_intersection = MagicMock() checker.neutron_check_segmentation_ids = MagicMock() checker.neutron_check_l3_addresses_not_match_subnet_and_broadcast = \ MagicMock() checker.check_public_floating_ranges_intersection = MagicMock() checker.check_network_address_spaces_intersection = MagicMock() checker.check_networks_amount = MagicMock() checker.check_vlan_ids_range_and_intersection = MagicMock() checker.check_network_classes_exclude_loopback = MagicMock() checker.check_network_addresses_not_match_subnet_and_broadcast = \ MagicMock() checker.check_configuration() not_called = [ 'neutron_check_network_address_spaces_intersection', 'neutron_check_segmentation_ids', 'neutron_check_l3_addresses_not_match_subnet_and_broadcast' ] for method in not_called: mocked = getattr(checker, method) self.assertFalse(mocked.called) called = [ 'check_public_floating_ranges_intersection', 'check_network_address_spaces_intersection', 'check_networks_amount', 'check_vlan_ids_range_and_intersection', 'check_network_classes_exclude_loopback', 'check_network_addresses_not_match_subnet_and_broadcast' ] for method in called: mocked = getattr(checker, method) mocked.assert_any_call() @patch.object(NetworkCheck, 'check_untagged_intersection') @patch.object(NetworkCheck, 'check_bond_slaves_speeds') def test_check_interface_mapping(self, mock_untagged, mock_bond): checker = NetworkCheck(self.task, {}) checker.check_interface_mapping() mock_untagged.assert_called_with() mock_bond.assert_called_with()

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0.559617

1,836

18,686

5.429194

0.1122

0.029494

0.017657

0.826946

0.795546

0.752307

0.723716

0.663925

0

0.049406

0.328428

18,686

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null

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6

97d962958fbc53041ec07fe757ae15567f1a6bc3

27

py

Python

delatore/outputs/telegram/__init__.py

opentelekomcloud-infra/delatore

6d16400cdfeab175ba6a7d7844d1d623d975fceb

[ "Apache-2.0" ]

1

2020-08-19T16:21:04.000Z

delatore/outputs/telegram/__init__.py

opentelekomcloud-infra/delatore

6d16400cdfeab175ba6a7d7844d1d623d975fceb

[ "Apache-2.0" ]

86

2019-12-02T21:24:20.000Z

2021-03-04T13:29:35.000Z

delatore/outputs/telegram/__init__.py

opentelekomcloud-infra/delatore

6d16400cdfeab175ba6a7d7844d1d623d975fceb

[ "Apache-2.0" ]

1

2020-03-19T09:25:07.000Z

from .bot import BotRunner

13.5

26

0.814815

4

27

5.5

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27

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97e80a5b365b04bb552d9fd8bb3d6a46e9763dc3

2,157

py

Python

NA_Project/NA_WebApp/migrations/0010_profile_allergies_profile_foodpreferences_profile_restrictedingredients_profile_restrictedlabels.py

BounSweFerhatSal/swe573

bd7e18f41a54c842db73176cf13c8e227b539be0

[ "MIT" ]

1

2020-06-23T12:14:50.000Z

NA_Project/NA_WebApp/migrations/0010_profile_allergies_profile_foodpreferences_profile_restrictedingredients_profile_restrictedlabels.py

BounSweFerhatSal/NutrAssistant

bd7e18f41a54c842db73176cf13c8e227b539be0

[ "MIT" ]

36

2020-05-03T15:45:59.000Z

2021-09-22T19:06:53.000Z

NA_Project/NA_WebApp/migrations/0010_profile_allergies_profile_foodpreferences_profile_restrictedingredients_profile_restrictedlabels.py

BounSweFerhatSal/swe573

bd7e18f41a54c842db73176cf13c8e227b539be0

[ "MIT" ]

null

# Generated by Django 3.0.5 on 2020-06-17 00:11 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('NA_WebApp', '0009_profile_diseases'), ] operations = [ migrations.CreateModel( name='Profile_RestrictedLabels', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('label', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='NA_WebApp.Labels')), ('profile', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='NA_WebApp.Profile')), ], ), migrations.CreateModel( name='Profile_RestrictedIngredients', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('Ingredient', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='NA_WebApp.Ingredient')), ('profile', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='NA_WebApp.Profile')), ], ), migrations.CreateModel( name='Profile_FoodPreferences', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('label', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='NA_WebApp.Labels')), ('profile', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='NA_WebApp.Profile')), ], ), migrations.CreateModel( name='Profile_Allergies', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('allergy', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='NA_WebApp.Allergies')), ('profile', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='NA_WebApp.Profile')), ], ), ]

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null

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6

97f7146ab1cd082f33b55d1aec123dcafbe95fe5

2,215

py

Python

scripts/slave/recipe_modules/chromium_tests/chromium_swarm.py

bopopescu/chromium-build

f8e42c70146c1b668421ee6358dc550a955770a3

[ "BSD-3-Clause" ]

null

scripts/slave/recipe_modules/chromium_tests/chromium_swarm.py

bopopescu/chromium-build

f8e42c70146c1b668421ee6358dc550a955770a3

[ "BSD-3-Clause" ]

null

scripts/slave/recipe_modules/chromium_tests/chromium_swarm.py

bopopescu/chromium-build

f8e42c70146c1b668421ee6358dc550a955770a3

[ "BSD-3-Clause" ]

1

2020-07-22T09:16:32.000Z

# Copyright 2014 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from . import steps SPEC = { 'builders': { 'Android N5 Swarm': { 'chromium_config': 'android', 'gclient_config': 'chromium', 'gclient_apply_config': ['android'], 'chromium_config_kwargs': { 'BUILD_CONFIG': 'Release', 'TARGET_BITS': 32, 'TARGET_PLATFORM': 'android', 'TARGET_ARCH': 'arm', }, 'android_config': 'main_builder_mb', 'testing': { 'platform': 'linux', }, 'bot_type': 'builder_tester', 'enable_swarming': True, }, 'Android N5X Swarm': { 'chromium_config': 'android', 'gclient_config': 'chromium', 'gclient_apply_config': ['android'], 'chromium_config_kwargs': { 'BUILD_CONFIG': 'Release', 'TARGET_BITS': 64, 'TARGET_PLATFORM': 'android', 'TARGET_ARCH': 'arm', }, 'android_config': 'main_builder_mb', 'testing': { 'platform': 'linux', }, 'bot_type': 'builder_tester', 'enable_swarming': True, }, 'Linux Swarm': { 'chromium_config': 'chromium', 'chromium_apply_config': ['mb'], 'gclient_config': 'chromium', 'chromium_config_kwargs': { 'BUILD_CONFIG': 'Release', }, 'testing': { 'platform': 'linux', }, 'bot_type': 'builder_tester', 'enable_swarming': True, }, 'Mac Swarm': { 'chromium_config': 'chromium', 'chromium_apply_config': ['mb'], 'gclient_config': 'chromium', 'chromium_config_kwargs': { 'BUILD_CONFIG': 'Release', }, 'testing': { 'platform': 'mac', }, 'bot_type': 'builder_tester', 'enable_swarming': True, }, 'Windows Swarm': { 'chromium_config': 'chromium', 'chromium_apply_config': ['mb'], 'gclient_config': 'chromium', 'chromium_config_kwargs': { 'BUILD_CONFIG': 'Release', }, 'testing': { 'platform': 'win', }, 'bot_type': 'builder_tester', 'enable_swarming': True, }, }, }

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0

null

0

1

0

null

0

6

3f1790c5cc3fa20226bc756b50c194c8ee6efe5b

260,827

py

Python

instances/passenger_demand/pas-20210422-1717-int14000000000000001e/16.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210422-1717-int14000000000000001e/16.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210422-1717-int14000000000000001e/16.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

""" PASSENGERS """ numPassengers = 26795 passenger_arriving = ( (4, 8, 6, 6, 2, 1, 1, 5, 5, 0, 0, 2, 0, 12, 5, 4, 3, 5, 7, 4, 0, 3, 4, 0, 1, 0), # 0 (12, 11, 10, 11, 6, 5, 4, 4, 3, 1, 0, 0, 0, 8, 5, 6, 5, 4, 4, 1, 2, 2, 1, 1, 0, 0), # 1 (5, 10, 9, 10, 2, 3, 5, 2, 3, 2, 1, 0, 0, 14, 11, 5, 1, 8, 3, 4, 1, 4, 4, 1, 2, 0), # 2 (6, 9, 9, 9, 7, 2, 4, 3, 6, 0, 1, 2, 0, 9, 6, 7, 4, 10, 2, 4, 3, 5, 0, 2, 3, 0), # 3 (8, 10, 8, 11, 8, 3, 2, 5, 4, 1, 4, 2, 0, 8, 8, 4, 4, 10, 0, 4, 5, 3, 2, 5, 0, 0), # 4 (8, 7, 6, 2, 7, 4, 3, 4, 3, 0, 0, 3, 0, 9, 13, 5, 7, 4, 1, 5, 3, 3, 1, 2, 1, 0), # 5 (4, 14, 9, 9, 6, 1, 6, 6, 7, 2, 4, 0, 0, 5, 9, 3, 4, 10, 7, 4, 5, 4, 2, 4, 0, 0), # 6 (9, 12, 8, 6, 7, 5, 4, 7, 5, 2, 0, 1, 0, 9, 8, 5, 7, 2, 7, 3, 1, 1, 0, 0, 3, 0), # 7 (10, 6, 7, 11, 9, 3, 4, 3, 2, 3, 0, 0, 0, 8, 9, 7, 8, 9, 6, 3, 3, 3, 2, 2, 0, 0), # 8 (12, 13, 13, 3, 7, 4, 3, 7, 5, 2, 1, 1, 0, 16, 9, 9, 4, 9, 8, 4, 3, 1, 4, 1, 2, 0), # 9 (10, 10, 16, 13, 9, 3, 2, 7, 2, 2, 2, 0, 0, 11, 14, 7, 6, 8, 6, 3, 1, 4, 2, 3, 1, 0), # 10 (9, 11, 8, 7, 8, 2, 5, 3, 4, 1, 2, 0, 0, 15, 8, 8, 13, 7, 5, 3, 4, 6, 5, 2, 2, 0), # 11 (15, 11, 6, 9, 11, 7, 1, 4, 6, 2, 4, 2, 0, 11, 8, 5, 8, 14, 6, 5, 4, 3, 4, 2, 2, 0), # 12 (11, 9, 11, 7, 12, 7, 7, 4, 6, 1, 0, 0, 0, 11, 10, 13, 9, 14, 7, 8, 2, 3, 5, 1, 2, 0), # 13 (9, 11, 8, 13, 7, 7, 4, 9, 5, 2, 4, 1, 0, 14, 8, 7, 5, 12, 6, 7, 3, 2, 2, 1, 1, 0), # 14 (11, 14, 8, 12, 12, 6, 6, 2, 5, 4, 0, 0, 0, 13, 10, 3, 7, 11, 9, 9, 2, 7, 3, 5, 0, 0), # 15 (10, 21, 14, 4, 10, 9, 5, 4, 5, 2, 2, 2, 0, 9, 11, 11, 9, 5, 6, 4, 6, 2, 4, 2, 0, 0), # 16 (13, 16, 7, 12, 11, 4, 6, 4, 5, 1, 0, 2, 0, 22, 11, 10, 11, 18, 8, 7, 2, 6, 5, 2, 1, 0), # 17 (9, 21, 12, 8, 8, 4, 11, 8, 7, 3, 2, 1, 0, 13, 18, 9, 8, 8, 9, 8, 3, 5, 5, 4, 2, 0), # 18 (14, 10, 10, 13, 6, 3, 5, 6, 6, 1, 2, 3, 0, 12, 7, 16, 8, 18, 10, 3, 3, 4, 7, 1, 1, 0), # 19 (15, 11, 15, 11, 10, 4, 4, 5, 4, 3, 2, 1, 0, 10, 16, 17, 9, 8, 4, 5, 7, 8, 2, 4, 1, 0), # 20 (16, 13, 14, 11, 11, 4, 12, 6, 7, 3, 1, 3, 0, 23, 10, 16, 8, 11, 8, 3, 2, 9, 4, 5, 1, 0), # 21 (15, 15, 9, 13, 13, 4, 6, 9, 9, 3, 1, 0, 0, 20, 12, 5, 10, 16, 7, 4, 4, 5, 2, 4, 1, 0), # 22 (16, 7, 14, 15, 14, 8, 4, 4, 8, 1, 3, 1, 0, 21, 13, 7, 9, 19, 8, 2, 4, 6, 4, 3, 1, 0), # 23 (18, 13, 7, 18, 16, 6, 5, 5, 4, 4, 5, 1, 0, 19, 10, 11, 8, 14, 9, 7, 5, 8, 5, 2, 2, 0), # 24 (17, 22, 13, 20, 13, 5, 9, 5, 6, 0, 2, 0, 0, 12, 5, 9, 3, 19, 10, 6, 4, 3, 3, 1, 0, 0), # 25 (13, 16, 21, 22, 6, 3, 4, 5, 6, 4, 1, 2, 0, 15, 10, 9, 5, 6, 5, 4, 5, 6, 1, 3, 1, 0), # 26 (10, 22, 7, 13, 12, 3, 5, 3, 7, 3, 2, 0, 0, 16, 9, 14, 5, 14, 6, 3, 7, 6, 4, 2, 1, 0), # 27 (8, 20, 6, 10, 15, 2, 4, 7, 3, 1, 1, 2, 0, 16, 15, 10, 8, 12, 8, 7, 4, 4, 4, 4, 1, 0), # 28 (12, 9, 10, 13, 16, 5, 5, 9, 3, 1, 2, 1, 0, 12, 12, 7, 6, 10, 8, 9, 6, 3, 2, 4, 1, 0), # 29 (13, 13, 8, 12, 6, 8, 3, 4, 6, 1, 0, 4, 0, 14, 24, 8, 9, 11, 6, 10, 8, 5, 4, 1, 1, 0), # 30 (11, 16, 13, 12, 13, 6, 7, 3, 4, 2, 3, 3, 0, 7, 15, 6, 8, 12, 7, 7, 2, 12, 7, 3, 1, 0), # 31 (14, 9, 25, 10, 14, 4, 2, 4, 7, 4, 2, 1, 0, 10, 10, 13, 13, 9, 5, 9, 1, 4, 5, 1, 2, 0), # 32 (11, 18, 7, 18, 11, 6, 4, 9, 5, 3, 1, 2, 0, 18, 13, 7, 9, 11, 6, 2, 4, 7, 4, 5, 0, 0), # 33 (12, 17, 7, 17, 11, 6, 2, 9, 5, 3, 3, 1, 0, 10, 7, 16, 9, 20, 8, 9, 2, 9, 2, 2, 2, 0), # 34 (18, 18, 15, 13, 14, 3, 3, 7, 6, 5, 1, 0, 0, 10, 9, 8, 9, 11, 8, 7, 3, 8, 1, 2, 2, 0), # 35 (14, 13, 18, 12, 6, 5, 4, 5, 8, 2, 2, 1, 0, 15, 17, 7, 5, 11, 7, 6, 1, 6, 6, 2, 0, 0), # 36 (14, 10, 17, 17, 11, 4, 8, 5, 3, 1, 4, 1, 0, 10, 16, 6, 4, 12, 3, 9, 2, 2, 7, 5, 0, 0), # 37 (15, 12, 18, 15, 5, 7, 3, 7, 9, 3, 1, 6, 0, 15, 9, 9, 9, 10, 8, 7, 4, 4, 5, 2, 1, 0), # 38 (13, 19, 15, 12, 9, 5, 5, 6, 7, 3, 2, 1, 0, 17, 18, 9, 6, 14, 7, 5, 4, 4, 7, 3, 4, 0), # 39 (11, 10, 10, 3, 13, 7, 12, 4, 5, 4, 3, 2, 0, 19, 17, 10, 5, 19, 5, 8, 3, 5, 7, 5, 1, 0), # 40 (14, 14, 10, 11, 12, 8, 7, 10, 5, 1, 2, 2, 0, 13, 7, 9, 5, 11, 7, 4, 1, 2, 4, 5, 2, 0), # 41 (22, 9, 11, 14, 17, 8, 5, 7, 5, 2, 1, 1, 0, 14, 9, 9, 4, 9, 3, 3, 5, 9, 5, 2, 2, 0), # 42 (20, 14, 13, 12, 17, 6, 7, 3, 5, 1, 5, 1, 0, 19, 8, 9, 7, 14, 4, 13, 5, 4, 5, 2, 0, 0), # 43 (11, 14, 7, 5, 5, 1, 3, 6, 4, 2, 2, 0, 0, 17, 15, 5, 8, 14, 11, 4, 2, 5, 1, 2, 2, 0), # 44 (19, 9, 10, 12, 6, 10, 2, 4, 8, 3, 1, 1, 0, 13, 14, 9, 4, 14, 7, 3, 2, 10, 2, 0, 1, 0), # 45 (18, 18, 14, 9, 9, 8, 7, 3, 5, 2, 2, 0, 0, 8, 13, 8, 8, 12, 1, 2, 1, 1, 1, 2, 0, 0), # 46 (17, 12, 13, 18, 12, 3, 4, 8, 4, 1, 1, 1, 0, 26, 10, 13, 9, 18, 6, 2, 5, 8, 5, 6, 1, 0), # 47 (14, 16, 16, 19, 5, 3, 7, 6, 2, 2, 2, 1, 0, 15, 9, 9, 10, 10, 9, 5, 5, 4, 6, 3, 1, 0), # 48 (11, 12, 6, 14, 11, 3, 6, 2, 4, 3, 3, 0, 0, 10, 14, 7, 10, 10, 7, 9, 4, 6, 4, 1, 1, 0), # 49 (12, 15, 11, 11, 6, 6, 2, 6, 5, 2, 3, 0, 0, 20, 17, 5, 10, 10, 4, 7, 4, 5, 5, 1, 1, 0), # 50 (14, 3, 10, 11, 11, 4, 7, 3, 7, 1, 1, 1, 0, 14, 12, 11, 4, 14, 4, 3, 2, 4, 5, 0, 1, 0), # 51 (8, 8, 12, 12, 5, 4, 6, 4, 8, 7, 1, 2, 0, 14, 17, 11, 8, 8, 6, 5, 2, 2, 7, 0, 2, 0), # 52 (13, 12, 10, 16, 9, 7, 7, 2, 10, 1, 4, 1, 0, 11, 11, 11, 8, 10, 6, 7, 5, 7, 0, 5, 1, 0), # 53 (17, 15, 11, 14, 11, 7, 5, 0, 5, 1, 0, 1, 0, 15, 6, 15, 7, 6, 9, 5, 2, 6, 5, 4, 1, 0), # 54 (14, 15, 14, 8, 11, 6, 6, 4, 5, 1, 4, 0, 0, 12, 11, 12, 7, 10, 4, 9, 3, 6, 6, 1, 2, 0), # 55 (15, 10, 9, 11, 7, 2, 6, 4, 11, 2, 1, 1, 0, 22, 13, 13, 11, 8, 7, 5, 4, 5, 6, 2, 2, 0), # 56 (12, 14, 5, 12, 9, 6, 7, 4, 6, 2, 3, 1, 0, 6, 11, 7, 8, 13, 11, 7, 7, 8, 1, 3, 3, 0), # 57 (26, 5, 8, 16, 7, 5, 4, 4, 5, 3, 4, 1, 0, 10, 20, 10, 7, 7, 6, 5, 6, 5, 2, 4, 0, 0), # 58 (7, 16, 9, 16, 9, 3, 6, 2, 7, 2, 3, 2, 0, 12, 16, 13, 7, 13, 4, 4, 3, 9, 3, 4, 1, 0), # 59 (19, 14, 9, 13, 9, 3, 5, 2, 4, 2, 0, 0, 0, 8, 12, 11, 6, 11, 2, 4, 5, 6, 4, 3, 2, 0), # 60 (14, 13, 8, 12, 6, 4, 4, 7, 3, 1, 0, 3, 0, 15, 13, 8, 9, 13, 5, 3, 3, 8, 2, 5, 0, 0), # 61 (13, 17, 19, 13, 8, 2, 5, 2, 8, 5, 2, 2, 0, 14, 12, 13, 11, 12, 3, 4, 6, 6, 5, 5, 0, 0), # 62 (21, 11, 14, 13, 12, 4, 6, 7, 10, 3, 5, 1, 0, 8, 10, 8, 3, 13, 2, 0, 4, 10, 4, 1, 0, 0), # 63 (16, 11, 14, 15, 5, 5, 9, 4, 3, 6, 0, 2, 0, 12, 9, 13, 8, 10, 10, 5, 2, 7, 4, 0, 4, 0), # 64 (19, 8, 9, 13, 7, 2, 6, 5, 8, 3, 5, 2, 0, 14, 15, 10, 9, 11, 5, 8, 4, 5, 4, 0, 1, 0), # 65 (12, 18, 10, 10, 13, 5, 2, 4, 4, 3, 4, 0, 0, 9, 11, 13, 5, 14, 12, 4, 5, 8, 2, 0, 0, 0), # 66 (13, 15, 12, 11, 9, 11, 9, 1, 7, 4, 1, 2, 0, 14, 11, 9, 9, 17, 6, 3, 4, 5, 2, 0, 0, 0), # 67 (11, 11, 12, 5, 7, 3, 4, 3, 11, 4, 4, 1, 0, 15, 13, 14, 4, 16, 6, 8, 3, 7, 4, 9, 1, 0), # 68 (21, 12, 16, 8, 10, 11, 4, 2, 9, 2, 5, 0, 0, 17, 9, 10, 7, 16, 4, 6, 6, 2, 4, 3, 0, 0), # 69 (14, 12, 10, 15, 8, 5, 5, 3, 10, 1, 1, 0, 0, 11, 14, 6, 7, 13, 6, 5, 4, 3, 4, 1, 0, 0), # 70 (13, 8, 8, 10, 10, 3, 5, 5, 4, 2, 4, 2, 0, 16, 6, 6, 8, 8, 2, 6, 1, 4, 3, 2, 2, 0), # 71 (8, 16, 8, 9, 10, 7, 5, 5, 0, 4, 3, 3, 0, 9, 15, 9, 16, 18, 7, 3, 5, 3, 3, 1, 3, 0), # 72 (14, 10, 6, 9, 10, 5, 7, 1, 7, 3, 3, 2, 0, 11, 13, 14, 12, 6, 9, 5, 3, 8, 8, 2, 1, 0), # 73 (16, 11, 17, 13, 11, 4, 4, 4, 3, 1, 2, 0, 0, 16, 17, 11, 7, 14, 5, 5, 2, 4, 8, 2, 0, 0), # 74 (15, 20, 14, 5, 12, 3, 3, 3, 4, 2, 1, 0, 0, 18, 12, 7, 11, 9, 5, 4, 5, 5, 2, 1, 1, 0), # 75 (18, 11, 12, 15, 13, 4, 8, 4, 2, 4, 5, 2, 0, 10, 18, 8, 7, 9, 10, 4, 3, 5, 5, 2, 3, 0), # 76 (17, 15, 10, 15, 7, 11, 11, 5, 3, 1, 1, 2, 0, 8, 11, 10, 11, 8, 3, 1, 4, 8, 4, 2, 1, 0), # 77 (13, 11, 10, 13, 13, 7, 7, 8, 7, 1, 2, 0, 0, 13, 12, 14, 7, 15, 6, 5, 5, 1, 5, 2, 2, 0), # 78 (18, 17, 16, 13, 7, 8, 3, 3, 5, 2, 3, 2, 0, 12, 11, 11, 3, 13, 0, 7, 5, 7, 6, 3, 1, 0), # 79 (19, 16, 15, 16, 9, 7, 4, 6, 4, 4, 5, 1, 0, 15, 14, 7, 8, 14, 9, 5, 4, 4, 3, 4, 1, 0), # 80 (18, 15, 9, 13, 6, 2, 4, 3, 7, 1, 2, 3, 0, 8, 10, 10, 12, 3, 6, 6, 2, 3, 4, 5, 1, 0), # 81 (11, 10, 14, 8, 9, 5, 7, 3, 5, 4, 2, 1, 0, 21, 10, 8, 8, 9, 8, 8, 4, 5, 4, 1, 3, 0), # 82 (14, 10, 17, 13, 13, 9, 5, 7, 9, 2, 1, 2, 0, 12, 12, 13, 8, 13, 4, 5, 3, 4, 2, 1, 1, 0), # 83 (15, 21, 11, 18, 8, 7, 2, 4, 1, 1, 0, 1, 0, 18, 11, 7, 8, 9, 6, 6, 0, 4, 4, 3, 1, 0), # 84 (11, 8, 17, 15, 12, 6, 6, 1, 9, 2, 1, 3, 0, 17, 13, 12, 5, 10, 6, 4, 2, 3, 2, 2, 1, 0), # 85 (14, 13, 15, 11, 5, 5, 3, 8, 7, 1, 0, 5, 0, 7, 20, 6, 7, 15, 6, 2, 4, 5, 3, 4, 1, 0), # 86 (17, 19, 8, 10, 8, 3, 1, 4, 1, 3, 0, 1, 0, 11, 17, 15, 6, 17, 5, 4, 4, 9, 4, 6, 1, 0), # 87 (13, 15, 9, 13, 13, 1, 5, 8, 4, 4, 2, 0, 0, 10, 13, 11, 5, 9, 3, 1, 2, 5, 7, 3, 1, 0), # 88 (20, 16, 14, 22, 11, 3, 6, 5, 4, 0, 1, 1, 0, 18, 11, 11, 8, 16, 5, 2, 10, 4, 2, 1, 0, 0), # 89 (19, 11, 8, 6, 9, 3, 6, 2, 6, 2, 0, 0, 0, 14, 15, 12, 8, 10, 6, 6, 5, 9, 7, 3, 1, 0), # 90 (10, 13, 15, 8, 7, 7, 3, 2, 6, 2, 1, 2, 0, 15, 10, 9, 5, 15, 1, 5, 2, 2, 1, 1, 2, 0), # 91 (10, 13, 11, 9, 13, 5, 5, 5, 8, 1, 1, 1, 0, 19, 10, 8, 6, 5, 9, 5, 2, 4, 4, 0, 0, 0), # 92 (10, 11, 11, 13, 4, 3, 1, 4, 4, 5, 4, 1, 0, 8, 12, 9, 8, 18, 7, 5, 2, 6, 7, 2, 0, 0), # 93 (13, 5, 9, 6, 8, 5, 7, 5, 6, 0, 0, 1, 0, 11, 6, 15, 10, 10, 8, 8, 4, 4, 3, 7, 1, 0), # 94 (21, 4, 9, 12, 8, 7, 4, 3, 7, 6, 1, 2, 0, 11, 20, 8, 8, 10, 0, 3, 4, 5, 3, 2, 0, 0), # 95 (5, 11, 7, 13, 15, 3, 5, 5, 5, 2, 1, 4, 0, 17, 9, 10, 8, 6, 4, 4, 5, 4, 2, 5, 0, 0), # 96 (19, 6, 10, 12, 15, 3, 4, 1, 5, 4, 1, 0, 0, 14, 6, 9, 4, 12, 7, 6, 4, 4, 5, 3, 1, 0), # 97 (15, 14, 6, 16, 11, 8, 4, 6, 7, 2, 0, 1, 0, 17, 8, 8, 11, 9, 3, 2, 1, 3, 1, 2, 0, 0), # 98 (14, 13, 11, 11, 17, 5, 4, 2, 6, 5, 1, 1, 0, 17, 11, 18, 12, 17, 3, 4, 7, 7, 3, 3, 0, 0), # 99 (10, 15, 11, 17, 12, 5, 5, 6, 2, 1, 1, 0, 0, 17, 10, 19, 8, 10, 6, 4, 5, 7, 2, 5, 0, 0), # 100 (13, 16, 8, 8, 7, 4, 7, 4, 6, 1, 0, 0, 0, 14, 8, 11, 6, 12, 8, 3, 2, 4, 3, 0, 1, 0), # 101 (13, 16, 5, 6, 10, 4, 4, 5, 1, 0, 4, 1, 0, 12, 11, 8, 5, 9, 7, 4, 3, 6, 3, 2, 3, 0), # 102 (16, 11, 10, 13, 13, 5, 6, 6, 5, 1, 1, 1, 0, 13, 13, 11, 9, 13, 3, 5, 3, 3, 4, 1, 1, 0), # 103 (10, 13, 16, 9, 13, 5, 4, 2, 3, 2, 2, 1, 0, 17, 10, 3, 10, 8, 4, 3, 3, 5, 4, 3, 1, 0), # 104 (16, 14, 11, 16, 15, 4, 5, 5, 9, 0, 1, 0, 0, 9, 14, 10, 9, 10, 0, 7, 6, 5, 3, 1, 1, 0), # 105 (15, 16, 10, 12, 6, 5, 3, 1, 5, 1, 0, 1, 0, 9, 9, 10, 6, 7, 5, 7, 6, 13, 7, 3, 0, 0), # 106 (9, 13, 10, 14, 12, 4, 8, 3, 6, 5, 2, 1, 0, 16, 16, 8, 6, 10, 6, 7, 6, 4, 3, 2, 2, 0), # 107 (16, 15, 8, 5, 7, 9, 3, 4, 6, 0, 2, 0, 0, 13, 12, 5, 4, 13, 2, 2, 0, 4, 4, 1, 0, 0), # 108 (11, 9, 12, 11, 8, 4, 7, 5, 5, 2, 0, 0, 0, 14, 6, 6, 2, 6, 4, 4, 3, 3, 8, 1, 0, 0), # 109 (17, 11, 13, 16, 13, 5, 4, 2, 6, 0, 0, 2, 0, 9, 13, 10, 4, 9, 5, 5, 3, 6, 2, 1, 0, 0), # 110 (17, 13, 7, 7, 7, 5, 2, 4, 4, 2, 1, 0, 0, 10, 11, 11, 9, 10, 4, 4, 2, 5, 4, 5, 0, 0), # 111 (13, 13, 11, 5, 7, 3, 3, 1, 6, 1, 2, 2, 0, 8, 15, 5, 8, 8, 6, 4, 1, 3, 3, 1, 2, 0), # 112 (10, 11, 7, 11, 9, 2, 5, 2, 6, 1, 2, 3, 0, 20, 8, 5, 4, 10, 3, 2, 7, 3, 4, 2, 0, 0), # 113 (13, 12, 12, 8, 10, 4, 5, 0, 3, 2, 2, 0, 0, 5, 15, 8, 6, 15, 3, 8, 1, 5, 3, 0, 0, 0), # 114 (9, 7, 7, 6, 15, 9, 2, 6, 5, 4, 1, 3, 0, 10, 17, 11, 3, 13, 6, 5, 4, 6, 6, 0, 0, 0), # 115 (11, 12, 9, 12, 4, 4, 6, 3, 4, 4, 2, 0, 0, 11, 17, 7, 5, 8, 5, 3, 3, 7, 1, 0, 0, 0), # 116 (7, 11, 10, 12, 13, 3, 2, 1, 6, 3, 3, 1, 0, 12, 10, 10, 1, 14, 4, 5, 7, 3, 3, 4, 1, 0), # 117 (11, 11, 8, 8, 11, 5, 3, 2, 1, 3, 0, 1, 0, 12, 15, 8, 4, 14, 3, 1, 7, 4, 4, 1, 3, 0), # 118 (8, 9, 10, 10, 8, 5, 1, 3, 5, 1, 2, 1, 0, 15, 12, 6, 5, 13, 6, 3, 4, 5, 4, 1, 2, 0), # 119 (14, 12, 10, 13, 7, 7, 5, 2, 6, 5, 1, 0, 0, 16, 15, 3, 8, 6, 3, 4, 2, 3, 3, 3, 2, 0), # 120 (14, 3, 12, 9, 13, 5, 7, 4, 4, 1, 2, 3, 0, 12, 12, 7, 7, 8, 3, 1, 3, 8, 0, 1, 0, 0), # 121 (9, 10, 9, 8, 8, 4, 6, 4, 9, 5, 3, 3, 0, 9, 9, 9, 8, 7, 7, 3, 1, 4, 4, 1, 1, 0), # 122 (14, 9, 9, 12, 7, 3, 8, 3, 3, 2, 2, 0, 0, 11, 9, 10, 8, 9, 6, 3, 6, 9, 5, 1, 0, 0), # 123 (6, 7, 11, 15, 9, 6, 5, 4, 7, 1, 2, 0, 0, 14, 15, 7, 4, 12, 6, 5, 3, 5, 4, 0, 0, 0), # 124 (11, 3, 9, 11, 11, 3, 9, 2, 5, 1, 3, 1, 0, 8, 9, 10, 8, 8, 2, 3, 7, 4, 4, 3, 0, 0), # 125 (11, 6, 11, 11, 8, 3, 3, 3, 5, 0, 2, 1, 0, 15, 8, 8, 5, 16, 5, 1, 3, 5, 3, 2, 3, 0), # 126 (10, 8, 10, 8, 12, 1, 4, 3, 8, 1, 1, 2, 0, 11, 12, 7, 3, 10, 5, 2, 1, 3, 4, 4, 0, 0), # 127 (11, 13, 13, 11, 15, 3, 3, 3, 4, 2, 3, 2, 0, 14, 12, 6, 6, 6, 3, 4, 3, 4, 6, 2, 1, 0), # 128 (14, 8, 15, 9, 8, 9, 4, 9, 5, 3, 2, 1, 0, 11, 11, 10, 6, 13, 4, 3, 4, 7, 3, 3, 1, 0), # 129 (14, 6, 7, 10, 7, 7, 3, 2, 5, 0, 5, 0, 0, 19, 6, 7, 2, 12, 6, 5, 5, 3, 5, 2, 0, 0), # 130 (16, 7, 14, 8, 7, 3, 1, 1, 4, 0, 4, 2, 0, 16, 12, 6, 11, 14, 12, 4, 2, 6, 6, 3, 1, 0), # 131 (9, 4, 9, 7, 10, 2, 5, 1, 4, 2, 3, 1, 0, 14, 11, 8, 7, 10, 3, 6, 3, 1, 2, 1, 1, 0), # 132 (14, 8, 9, 5, 12, 5, 3, 3, 6, 0, 0, 1, 0, 13, 10, 8, 9, 4, 0, 1, 4, 5, 3, 1, 2, 0), # 133 (7, 8, 7, 7, 16, 5, 2, 1, 6, 1, 3, 2, 0, 11, 14, 4, 3, 11, 2, 7, 6, 10, 2, 2, 1, 0), # 134 (10, 7, 9, 10, 10, 1, 4, 5, 3, 0, 2, 0, 0, 17, 10, 7, 9, 13, 7, 1, 5, 4, 4, 1, 0, 0), # 135 (11, 9, 9, 16, 7, 3, 0, 3, 8, 2, 4, 0, 0, 8, 11, 7, 9, 17, 3, 6, 3, 3, 2, 3, 1, 0), # 136 (20, 6, 11, 8, 7, 4, 3, 6, 3, 1, 1, 1, 0, 13, 13, 9, 5, 9, 5, 5, 5, 4, 5, 1, 1, 0), # 137 (6, 4, 11, 6, 6, 3, 4, 4, 6, 1, 4, 1, 0, 21, 9, 9, 5, 13, 4, 6, 1, 3, 4, 4, 1, 0), # 138 (10, 9, 13, 11, 8, 8, 3, 9, 7, 2, 0, 1, 0, 18, 15, 15, 1, 9, 4, 3, 5, 3, 3, 2, 0, 0), # 139 (6, 9, 7, 11, 9, 3, 4, 6, 1, 1, 1, 1, 0, 18, 10, 3, 3, 9, 2, 5, 6, 4, 4, 3, 0, 0), # 140 (8, 10, 12, 9, 8, 2, 1, 1, 5, 3, 3, 1, 0, 16, 19, 7, 6, 8, 6, 4, 2, 7, 4, 1, 0, 0), # 141 (7, 6, 11, 13, 14, 7, 0, 4, 6, 4, 2, 0, 0, 13, 8, 4, 7, 12, 3, 3, 5, 3, 3, 4, 2, 0), # 142 (7, 6, 12, 9, 7, 3, 4, 2, 3, 1, 0, 0, 0, 12, 3, 10, 4, 11, 3, 4, 0, 3, 2, 3, 1, 0), # 143 (9, 5, 14, 9, 8, 3, 1, 3, 4, 1, 1, 0, 0, 6, 12, 8, 5, 11, 5, 4, 3, 5, 1, 1, 1, 0), # 144 (17, 4, 14, 6, 11, 3, 1, 3, 4, 1, 2, 0, 0, 12, 12, 5, 5, 7, 5, 4, 2, 0, 3, 1, 0, 0), # 145 (21, 7, 6, 13, 4, 4, 4, 7, 3, 1, 2, 1, 0, 11, 11, 5, 4, 11, 2, 3, 4, 3, 7, 1, 0, 0), # 146 (9, 8, 9, 15, 11, 4, 3, 4, 1, 1, 1, 2, 0, 9, 13, 6, 3, 11, 6, 3, 4, 7, 3, 3, 1, 0), # 147 (14, 6, 8, 10, 10, 9, 1, 3, 4, 4, 1, 0, 0, 11, 12, 7, 3, 7, 6, 3, 4, 7, 2, 5, 0, 0), # 148 (10, 4, 8, 11, 7, 4, 1, 4, 5, 1, 3, 0, 0, 8, 8, 5, 5, 13, 5, 6, 5, 6, 2, 2, 0, 0), # 149 (11, 9, 7, 13, 13, 4, 0, 3, 5, 1, 1, 0, 0, 8, 12, 5, 7, 11, 4, 2, 1, 2, 2, 2, 0, 0), # 150 (10, 12, 16, 6, 10, 6, 5, 6, 6, 1, 1, 2, 0, 11, 7, 7, 6, 9, 5, 2, 4, 2, 2, 1, 0, 0), # 151 (13, 13, 12, 9, 6, 9, 3, 4, 5, 1, 2, 1, 0, 16, 14, 3, 5, 15, 4, 5, 4, 2, 3, 4, 1, 0), # 152 (8, 14, 6, 9, 11, 5, 3, 1, 4, 2, 0, 2, 0, 4, 10, 11, 4, 9, 5, 3, 1, 3, 5, 1, 1, 0), # 153 (6, 11, 9, 8, 11, 1, 5, 6, 6, 3, 4, 0, 0, 14, 9, 10, 4, 12, 2, 5, 3, 5, 3, 2, 0, 0), # 154 (9, 11, 10, 3, 11, 0, 6, 3, 2, 2, 3, 1, 0, 17, 2, 8, 3, 6, 3, 2, 5, 4, 3, 0, 1, 0), # 155 (13, 10, 4, 17, 11, 4, 2, 5, 3, 1, 1, 2, 0, 10, 10, 7, 4, 10, 4, 6, 3, 8, 3, 3, 0, 0), # 156 (10, 9, 10, 12, 6, 4, 2, 4, 5, 1, 1, 0, 0, 11, 10, 6, 5, 10, 5, 5, 2, 6, 3, 2, 1, 0), # 157 (13, 3, 7, 20, 11, 8, 2, 1, 5, 0, 0, 2, 0, 13, 12, 6, 11, 13, 5, 0, 5, 4, 5, 1, 0, 0), # 158 (15, 10, 10, 9, 8, 3, 5, 3, 3, 1, 1, 1, 0, 11, 5, 4, 7, 17, 3, 5, 5, 5, 5, 0, 0, 0), # 159 (9, 14, 8, 7, 15, 7, 1, 3, 4, 4, 1, 0, 0, 16, 4, 7, 6, 11, 4, 3, 1, 2, 2, 2, 0, 0), # 160 (10, 8, 12, 7, 13, 2, 6, 5, 1, 1, 0, 1, 0, 10, 10, 9, 5, 12, 5, 3, 4, 3, 3, 1, 1, 0), # 161 (11, 11, 15, 13, 13, 1, 4, 3, 1, 2, 1, 0, 0, 8, 4, 9, 2, 8, 4, 1, 1, 4, 5, 1, 3, 0), # 162 (15, 4, 9, 8, 4, 2, 2, 2, 5, 1, 0, 1, 0, 13, 7, 9, 4, 7, 4, 0, 3, 3, 4, 1, 1, 0), # 163 (6, 6, 9, 14, 9, 3, 4, 3, 4, 1, 2, 0, 0, 10, 5, 5, 2, 9, 1, 6, 1, 2, 5, 3, 1, 0), # 164 (9, 6, 10, 9, 13, 3, 5, 3, 2, 1, 1, 0, 0, 5, 5, 7, 4, 8, 6, 3, 2, 4, 0, 2, 1, 0), # 165 (10, 5, 8, 4, 12, 2, 3, 5, 7, 2, 1, 0, 0, 6, 8, 2, 5, 5, 3, 7, 3, 2, 4, 4, 1, 0), # 166 (12, 3, 6, 11, 4, 7, 2, 5, 3, 3, 0, 0, 0, 16, 6, 5, 1, 9, 5, 1, 2, 6, 4, 1, 0, 0), # 167 (7, 6, 5, 7, 5, 3, 2, 6, 3, 5, 2, 1, 0, 8, 5, 5, 4, 8, 1, 4, 0, 0, 3, 3, 0, 0), # 168 (2, 5, 5, 6, 8, 1, 2, 1, 4, 0, 2, 0, 0, 4, 11, 7, 2, 6, 3, 4, 1, 4, 2, 4, 2, 0), # 169 (11, 6, 9, 5, 8, 2, 5, 3, 3, 0, 1, 0, 0, 9, 6, 5, 9, 4, 1, 2, 5, 4, 4, 1, 1, 0), # 170 (12, 5, 4, 7, 6, 6, 5, 2, 2, 1, 1, 0, 0, 8, 8, 2, 6, 9, 2, 3, 0, 5, 1, 1, 1, 0), # 171 (8, 3, 7, 5, 2, 1, 2, 1, 5, 1, 0, 0, 0, 6, 2, 5, 3, 6, 3, 3, 4, 3, 3, 1, 0, 0), # 172 (10, 5, 8, 5, 13, 3, 1, 4, 3, 1, 0, 0, 0, 5, 8, 6, 4, 3, 2, 3, 4, 3, 5, 2, 2, 0), # 173 (7, 4, 1, 9, 11, 3, 2, 1, 0, 0, 2, 0, 0, 5, 7, 11, 4, 4, 3, 2, 0, 2, 0, 0, 0, 0), # 174 (5, 4, 6, 5, 5, 1, 2, 2, 9, 0, 1, 0, 0, 9, 3, 2, 2, 6, 2, 0, 2, 1, 3, 4, 1, 0), # 175 (8, 3, 2, 9, 7, 4, 2, 1, 0, 1, 3, 0, 0, 7, 7, 3, 2, 3, 3, 3, 2, 1, 2, 2, 0, 0), # 176 (9, 3, 6, 2, 5, 1, 2, 0, 7, 1, 1, 0, 0, 12, 8, 2, 3, 2, 2, 3, 1, 2, 2, 1, 0, 0), # 177 (3, 2, 10, 0, 6, 2, 0, 3, 2, 1, 2, 0, 0, 10, 2, 4, 2, 3, 3, 1, 4, 2, 2, 2, 0, 0), # 178 (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 179 ) station_arriving_intensity = ( (7.029211809720476, 7.735403983570434, 7.29579652145751, 8.700534883408807, 7.776559850653457, 4.394116904852274, 5.804449861523481, 6.514446642171193, 8.52613868703521, 5.541221021731318, 5.887371229439844, 6.857081109628643, 7.117432297609708), # 0 (7.496058012827964, 8.246084971802663, 7.777485227862214, 9.275201954587263, 8.291486472463932, 4.684377017659578, 6.187256517769172, 6.943319212067992, 9.089143456866074, 5.90657296918801, 6.2763345903385845, 7.309703325140097, 7.587708306415797), # 1 (7.9614122125716245, 8.754739239247371, 8.257259199766379, 9.847582786530712, 8.804548163249642, 4.9734791603174235, 6.568545911144986, 7.370475347066188, 9.64990152962857, 6.270479285028765, 6.663752408286839, 7.760525712874277, 8.056110759493567), # 2 (8.423460910405188, 9.259348702711026, 8.733215217047796, 10.415406970544904, 9.313726346402664, 5.260276871619158, 6.946805098307138, 7.79422162049231, 10.206189225289531, 6.631495777796654, 7.0480877765583365, 8.207759958902646, 8.520781928755916), # 3 (8.880390607782374, 9.757895279000085, 9.203450059584252, 10.976404097935598, 9.81700244531509, 5.543623690358135, 7.320521135911843, 8.212864605672882, 10.75578286381579, 6.988178256034751, 7.4278037884268056, 8.64961774929667, 8.979864086115745), # 4 (9.330387806156915, 10.248360884921025, 9.666060507253526, 11.528303760008551, 10.312357883378994, 5.822373155327701, 7.688181080615314, 8.62471087593443, 11.296458765174183, 7.339082528286129, 7.801363537165986, 9.084310770127807, 9.43149950348596), # 5 (9.771639006982534, 10.728727437280302, 10.119143339933412, 12.068835548069513, 10.79777408398646, 6.09537880532121, 8.048271989073768, 9.028067004603484, 11.825993249331543, 7.682764403093862, 8.167230116049597, 9.510050707467531, 9.87383045277945), # 6 (10.202330711712957, 11.196976852884385, 10.56079533750169, 12.595729053424249, 11.271232470529577, 6.36149417913201, 8.39928091794342, 9.421239565006573, 12.342162636254702, 8.017779689001022, 8.523866618351377, 9.925049247387301, 10.304999205909127), # 7 (10.62064942180191, 11.651091048539739, 10.989113279836156, 13.1067138673785, 11.730714466400421, 6.619572815553446, 8.739694923880478, 9.802535130470215, 12.842743245910489, 8.342684194550685, 8.86973613734505, 10.327518075958585, 10.723148034787885), # 8 (11.02478163870312, 12.089051941052832, 11.402193946814586, 13.599519581238038, 12.174201494991074, 6.868468253378878, 9.068001063541168, 10.170260274320949, 13.325511398265744, 8.65603372828592, 9.20330176630435, 10.71566887925284, 11.126419211328628), # 9 (11.412913863870306, 12.508841447230123, 11.798134118314776, 14.071875786308604, 12.599674979693622, 7.107034031401651, 9.382686393581697, 10.522721569885295, 13.7882434132873, 8.956384098749801, 9.523026598503003, 11.087713343341534, 11.512955007444255), # 10 (11.783232598757209, 12.90844148387809, 12.175030574214501, 14.521512073895957, 13.005116343900148, 7.334123688415116, 9.682237970658283, 10.85822559048978, 14.228715610941991, 9.242291114485408, 9.82737372721475, 11.441863154296136, 11.880897695047656), # 11 (12.133924344817538, 13.285833967803178, 12.530980094391557, 14.946158035305858, 13.38850701100273, 7.5485907632126175, 9.965142851427137, 11.17507890946093, 14.644704311196652, 9.512310584035802, 10.114806245713309, 11.776329998188096, 12.22838954605175), # 12 (12.463175603505027, 13.639000815811869, 12.864079458723728, 15.343543261844063, 13.747828404393443, 7.749288794587514, 10.22988809254448, 11.471588100125276, 15.033985834018106, 9.764998315944066, 10.383787247272418, 12.08932556108889, 12.55357283236943), # 13 (12.769172876273403, 13.965923944710624, 13.172425447088806, 15.71139734481631, 14.081061947464386, 7.935071321333148, 10.474960750666526, 11.746059735809345, 15.39433649937319, 9.998910118753269, 10.6327798251658, 12.379061529069986, 12.85458982591359), # 14 (13.050102664576398, 14.264585271305906, 13.45411483936456, 16.047449875528383, 14.386189063607633, 8.104791882242878, 10.698847882449478, 11.99680038983966, 15.723532627228748, 10.212601801006487, 10.860247072667189, 12.64374958820284, 13.129582798597134), # 15 (13.30415146986772, 14.532966712404187, 13.707244415428796, 16.349430445286004, 14.661191176215267, 8.257304016110044, 10.900036544549568, 12.222116635542745, 16.019350537551603, 10.404629171246796, 11.06465208305032, 12.881601424558916, 13.376694022332964), # 16 (13.529505793601107, 14.769050184811926, 13.929910955159293, 16.61506864539496, 14.904049708679375, 8.391461261728, 11.077013793622996, 12.420315046245145, 16.27956655030858, 10.573548038017254, 11.24445794958892, 13.090828724209679, 13.594065769033982), # 17 (13.724352137230287, 14.970817605335585, 14.120211238433834, 16.842094067160993, 15.112746084392025, 8.506117157890104, 11.228266686325993, 12.589702195273366, 16.501956985466535, 10.717914209860952, 11.398127765556712, 13.269643173226603, 13.779840310613086), # 18 (13.88687700220898, 15.136250890781643, 14.27624204513021, 17.02823630188984, 15.285261726745313, 8.600125243389693, 11.352282279314753, 12.728584655953943, 16.68429816299229, 10.83628349532096, 11.52412462422743, 13.416256457681136, 13.932159918983176), # 19 (14.015266889990915, 15.263331957956549, 14.396100155126206, 17.171224940887296, 15.419578059131322, 8.672339057020126, 11.44754762924551, 12.835269001613405, 16.82436640285268, 10.927211702940342, 11.62091161887481, 13.528880263644748, 14.049166866057154), # 20 (14.107708302029813, 15.350042723666784, 14.477882348299607, 17.26878957545908, 15.513676504942126, 8.72161213757475, 11.512549792774463, 12.908061805578273, 16.91993802501453, 10.989254641262178, 11.686951842772585, 13.60572627718891, 14.12900342374791), # 21 (14.162387739779412, 15.394365104718803, 14.5196854045282, 17.31865979691097, 15.565538487569807, 8.746798023846914, 11.54577582655784, 12.945269641175082, 16.968789349444684, 11.02096811882954, 11.720708389194478, 13.645006184385087, 14.16981186396836), # 22 (14.182550708679697, 15.39961303155007, 14.524892455418383, 17.324903137860087, 15.578824878445637, 8.75, 11.549725603163076, 12.949291358024693, 16.974896728395063, 11.024709181527207, 11.724941252026436, 13.649856607224509, 14.175), # 23 (14.197417378247815, 15.396551851851854, 14.524040740740743, 17.324134722222226, 15.586350659060795, 8.75, 11.547555337690634, 12.943700000000002, 16.974078333333335, 11.02241086419753, 11.724474410774413, 13.648720987654322, 14.175), # 24 (14.211970122296213, 15.390517832647463, 14.522359396433473, 17.322614454732513, 15.593710923832306, 8.75, 11.543278463648836, 12.932716049382718, 16.97246141975309, 11.01788637402835, 11.723548759196907, 13.646479195244629, 14.175), # 25 (14.226207826667249, 15.381603155006863, 14.519871467764064, 17.320359619341563, 15.600905415789548, 8.75, 11.53696140563221, 12.916546913580248, 16.97006672839506, 11.011210992226795, 11.722172677391198, 13.643161957018751, 14.175), # 26 (14.240129377203292, 15.3699, 14.5166, 17.3173875, 15.607933877961901, 8.75, 11.528670588235297, 12.895400000000002, 16.966915, 11.00246, 11.720354545454546, 13.638800000000003, 14.175), # 27 (14.253733659746702, 15.355500548696845, 14.51256803840878, 17.313715380658437, 15.614796053378763, 8.75, 11.518472436052612, 12.869482716049385, 16.963026975308644, 10.9917086785551, 11.718102743484225, 13.633424051211708, 14.175), # 28 (14.26701956013985, 15.338496982167355, 14.50779862825789, 17.30936054526749, 15.62149168506951, 8.75, 11.506433373678693, 12.839002469135803, 16.95842339506173, 10.979032309099225, 11.715425651577503, 13.627064837677183, 14.175), # 29 (14.279985964225098, 15.318981481481483, 14.502314814814815, 17.30434027777778, 15.628020516063533, 8.75, 11.492619825708061, 12.804166666666665, 16.953125, 10.964506172839508, 11.71233164983165, 13.619753086419752, 14.175), # 30 (14.292631757844802, 15.297046227709194, 14.496139643347053, 17.29867186213992, 15.634382289390214, 8.75, 11.477098216735257, 12.765182716049384, 16.947152530864198, 10.948205550983083, 11.708829118343933, 13.611519524462738, 14.175), # 31 (14.304955826841338, 15.27278340192044, 14.489296159122084, 17.29237258230453, 15.640576748078935, 8.75, 11.4599349713548, 12.72225802469136, 16.940526728395064, 10.930205724737084, 11.704926437211622, 13.602394878829449, 14.175), # 32 (14.316957057057056, 15.246285185185185, 14.481807407407409, 17.28545972222222, 15.646603635159089, 8.75, 11.441196514161222, 12.675600000000001, 16.933268333333334, 10.910581975308643, 11.700631986531986, 13.59240987654321, 14.175), # 33 (14.328634334334335, 15.217643758573388, 14.473696433470508, 17.27795056584362, 15.652462693660054, 8.75, 11.420949269749054, 12.625416049382716, 16.925398086419758, 10.889409583904893, 11.695954146402293, 13.581595244627344, 14.175), # 34 (14.339986544515531, 15.186951303155007, 14.464986282578877, 17.26986239711934, 15.65815366661122, 8.75, 11.399259662712824, 12.571913580246914, 16.916936728395065, 10.866763831732968, 11.690901296919815, 13.569981710105168, 14.175), # 35 (14.35101257344301, 15.1543, 14.455700000000002, 17.2612125, 15.663676297041972, 8.75, 11.37619411764706, 12.515300000000002, 16.907905, 10.84272, 11.685481818181819, 13.557600000000003, 14.175), # 36 (14.361711306959135, 15.119782030178326, 14.445860631001374, 17.252018158436215, 15.669030327981691, 8.75, 11.351819059146292, 12.455782716049384, 16.89832364197531, 10.817353369913125, 11.679704090285574, 13.544480841335163, 14.175), # 37 (14.372081630906267, 15.083489574759948, 14.43549122085048, 17.242296656378603, 15.674215502459768, 8.75, 11.326200911805053, 12.393569135802473, 16.88821339506173, 10.790739222679472, 11.673576493328346, 13.530654961133976, 14.175), # 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152 (10.897033588275185, 8.61712435158296, 11.482251647627416, 13.159187033792707, 13.11470454602428, 7.318791048167222, 6.929063810741687, 7.841232219061167, 14.058309087801755, 7.062929369089481, 8.316815455699683, 9.92402828118809, 11.68464226121364), # 153 (10.81262003423102, 8.534185365897834, 11.422924477189063, 13.078280853413174, 13.042726487861813, 7.288854057067317, 6.87025313968732, 7.8124531118187726, 14.009925457519413, 7.013019423465095, 8.260930064044857, 9.861181374586256, 11.6191092156515), # 154 (10.72606825993309, 8.448916964658093, 11.361703047816906, 12.99488293561833, 12.968776807822776, 7.257796941777861, 6.809664942048866, 7.782239138911491, 13.95962058285218, 6.9614650283384565, 8.203154434992767, 9.796328772892876, 11.551739314998438), # 155 (10.637327353293314, 8.361234611710243, 11.298532183655539, 12.908919102893627, 12.892813332647707, 7.225581056931246, 6.74723555776578, 7.750525284055986, 13.907325442542877, 6.9082075819648825, 8.143420671591107, 9.729406117611353, 11.48249014823076), # 156 (10.546346402223609, 8.271053770900794, 11.233356708849547, 12.820315177724513, 12.81479388907716, 7.19216775715986, 6.6829013267775075, 7.717246530968915, 13.852971015334345, 6.853188482599679, 8.08166087688757, 9.660349050245092, 11.411319304324769), # 157 (10.450553324967336, 8.176634369081162, 11.163028735463298, 12.725677414311741, 12.731153548219398, 7.155434266843955, 6.615149409299001, 7.680115733289122, 13.792326928238738, 6.794712282807602, 8.01583405355452, 9.586639389872076, 11.335080203181485), # 158 (10.335201473769764, 8.06829144743927, 11.069432945764184, 12.605568022303835, 12.62126783369428, 7.103165507209945, 6.535497868740003, 7.626098945870136, 13.700998165711002, 6.723193391738244, 7.934383709866593, 9.493907533156353, 11.235598705688274), # 159 (10.198820932866035, 7.945135419957, 10.950689341138245, 12.458008514572404, 12.482988183885514, 7.034077814466758, 6.443141247737298, 7.553838865338286, 13.576395318120113, 6.637687912608051, 7.8361633120533565, 9.380702728442985, 11.110988852451014), # 160 (10.042510876420344, 7.8079692153126565, 10.808065760674433, 12.28440150525942, 12.317750373994958, 6.94900813819844, 6.338754024409627, 7.464240746353693, 13.420161673798626, 6.5389214704393135, 7.7220383164395905, 9.248074456470599, 10.962523662746737), # 161 (9.8673704785969, 7.657595762184535, 10.642830043461695, 12.086149608506858, 12.126990179224487, 6.848793427989039, 6.223010676875733, 7.358209843576484, 13.233940521079093, 6.427619690254325, 7.592874179350069, 9.09707219797781, 10.791476155852466), # 162 (9.674498913559898, 7.494817989250934, 10.456250028588983, 11.864655438456708, 11.912143374775964, 6.734270633422602, 6.096585683254362, 7.2366514116667755, 13.019375148294069, 6.304508197075376, 7.449536357109572, 8.928745433703247, 10.599119351045232), # 163 (9.464995355473539, 7.320438825190149, 10.249593555145248, 11.621321609250947, 11.674645735851264, 6.606276704083181, 5.960153521664253, 7.100470705284697, 12.778108843776113, 6.170312615924756, 7.292890306042875, 8.744143644385526, 10.386726267602059), # 164 (9.239958978502024, 7.135261198680485, 10.024128462219437, 11.357550735031554, 11.415933037652254, 6.465648589554821, 5.814388670224151, 6.950572979090365, 12.511784895857772, 6.02575857182476, 7.123801482474756, 8.544316310763268, 10.155569924799979), # 165 (9.000488956809557, 6.940088038400237, 9.7811225889005, 11.074745429940503, 11.137441055380801, 6.313223239421572, 5.659965607052801, 6.787863487743908, 12.222046592871603, 5.871571689797677, 6.943135342729992, 8.330312913575103, 9.906923341916015), # 166 (8.747684464560333, 6.735722273027703, 9.521843774277388, 10.774308308119782, 10.840605564238773, 6.149837603267482, 5.497558810268945, 6.613247485905448, 11.91053722315016, 5.7084775948658, 6.751757343133359, 8.103182933559642, 9.642059538227196), # 167 (8.482644675918554, 6.52296683124118, 9.247559857439049, 10.457641983711365, 10.526862339428039, 5.9763286306765995, 5.327842757991326, 6.427630228235103, 11.578900075025999, 5.5372019120514215, 6.550532940009634, 7.863975851455517, 9.362251533010546), # 168 (8.206468765048422, 6.302624641718972, 8.959538677474432, 10.126149070857236, 10.197647156150468, 5.793533271232973, 5.151491928338689, 6.231916969393004, 11.228778436831673, 5.358470266376831, 6.3403275896835956, 7.613741148001342, 9.0687723455431), # 169 (7.9202559061141375, 6.0754986331393726, 8.659048073472489, 9.781232183699368, 9.854395789607928, 5.60228847452065, 4.9691807994297745, 6.027012964039266, 10.861815596899735, 5.173008282864322, 6.122006748480023, 7.353528303935743, 8.762894995101878), # 170 (7.6251052732799005, 5.842391734180682, 8.34735588452217, 9.424293936379751, 9.498544015002288, 5.403431190123678, 4.781583849383328, 5.813823466834017, 10.47965484356274, 4.981541586536184, 5.896435872723688, 7.0843867999973416, 8.445892500963913), # 171 (7.322116040709912, 5.604106873521197, 8.025729949712423, 9.056736943040356, 9.131527607535416, 5.197798367626108, 4.5893755563180925, 5.593253732437379, 10.083939465153241, 4.784795802414712, 5.664480418739371, 6.80736611692476, 8.119037882406225), # 172 (7.012387382568372, 5.3614469798392195, 7.695438108132197, 8.679963817823166, 8.754782342409182, 4.9862269566119855, 4.39323039835281, 5.366209015509473, 9.676312750003792, 4.583496555522195, 5.427005842851849, 6.523515735456615, 7.783604158705848), # 173 (6.697018473019482, 5.115214981813045, 7.357748198870443, 8.295377174870158, 8.369743994825454, 4.76955390666536, 4.193822853606226, 5.133594570710425, 9.25841798644695, 4.3783694708809255, 5.1848776013858995, 6.233885136331535, 7.440864349139807), # 174 (6.377108486227438, 4.866213808120973, 7.013928061016112, 7.904379628323315, 7.977848339986097, 4.54861616737028, 3.9918274001970815, 4.896315652700355, 8.831898462815268, 4.170140173513194, 4.938961150666297, 5.939523800288141, 7.092091472985131), # 175 (6.053756596356447, 4.615246387441302, 6.66524553365815, 7.508373792324615, 7.580531153092983, 4.324250688310793, 3.787918516244121, 4.655277516139389, 8.3983974674413, 3.959534288441294, 4.690121947017822, 5.641481208065051, 6.738558549518844), # 176 (5.7280619775707065, 4.363115648452332, 6.3129684558855095, 7.108762281016037, 7.179228209347984, 4.097294419070949, 3.582770679866088, 4.411385415687646, 7.959558288657599, 3.7472774406875144, 4.43922544676525, 5.340806840400891, 6.381538598017975), # 177 (5.401123804034416, 4.11062451983236, 5.95836466678714, 6.7069477085395635, 6.775375283952959, 3.8685843092347962, 3.3770583691817246, 4.165544606005252, 7.51702421479672, 3.5340952552741505, 4.187137106233358, 5.038550178034279, 6.022304637759553), # 178 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179 ) passenger_arriving_acc = ( (4, 8, 6, 6, 2, 1, 1, 5, 5, 0, 0, 2, 0, 12, 5, 4, 3, 5, 7, 4, 0, 3, 4, 0, 1, 0), # 0 (16, 19, 16, 17, 8, 6, 5, 9, 8, 1, 0, 2, 0, 20, 10, 10, 8, 9, 11, 5, 2, 5, 5, 1, 1, 0), # 1 (21, 29, 25, 27, 10, 9, 10, 11, 11, 3, 1, 2, 0, 34, 21, 15, 9, 17, 14, 9, 3, 9, 9, 2, 3, 0), # 2 (27, 38, 34, 36, 17, 11, 14, 14, 17, 3, 2, 4, 0, 43, 27, 22, 13, 27, 16, 13, 6, 14, 9, 4, 6, 0), # 3 (35, 48, 42, 47, 25, 14, 16, 19, 21, 4, 6, 6, 0, 51, 35, 26, 17, 37, 16, 17, 11, 17, 11, 9, 6, 0), # 4 (43, 55, 48, 49, 32, 18, 19, 23, 24, 4, 6, 9, 0, 60, 48, 31, 24, 41, 17, 22, 14, 20, 12, 11, 7, 0), # 5 (47, 69, 57, 58, 38, 19, 25, 29, 31, 6, 10, 9, 0, 65, 57, 34, 28, 51, 24, 26, 19, 24, 14, 15, 7, 0), # 6 (56, 81, 65, 64, 45, 24, 29, 36, 36, 8, 10, 10, 0, 74, 65, 39, 35, 53, 31, 29, 20, 25, 14, 15, 10, 0), # 7 (66, 87, 72, 75, 54, 27, 33, 39, 38, 11, 10, 10, 0, 82, 74, 46, 43, 62, 37, 32, 23, 28, 16, 17, 10, 0), # 8 (78, 100, 85, 78, 61, 31, 36, 46, 43, 13, 11, 11, 0, 98, 83, 55, 47, 71, 45, 36, 26, 29, 20, 18, 12, 0), # 9 (88, 110, 101, 91, 70, 34, 38, 53, 45, 15, 13, 11, 0, 109, 97, 62, 53, 79, 51, 39, 27, 33, 22, 21, 13, 0), # 10 (97, 121, 109, 98, 78, 36, 43, 56, 49, 16, 15, 11, 0, 124, 105, 70, 66, 86, 56, 42, 31, 39, 27, 23, 15, 0), # 11 (112, 132, 115, 107, 89, 43, 44, 60, 55, 18, 19, 13, 0, 135, 113, 75, 74, 100, 62, 47, 35, 42, 31, 25, 17, 0), # 12 (123, 141, 126, 114, 101, 50, 51, 64, 61, 19, 19, 13, 0, 146, 123, 88, 83, 114, 69, 55, 37, 45, 36, 26, 19, 0), # 13 (132, 152, 134, 127, 108, 57, 55, 73, 66, 21, 23, 14, 0, 160, 131, 95, 88, 126, 75, 62, 40, 47, 38, 27, 20, 0), # 14 (143, 166, 142, 139, 120, 63, 61, 75, 71, 25, 23, 14, 0, 173, 141, 98, 95, 137, 84, 71, 42, 54, 41, 32, 20, 0), # 15 (153, 187, 156, 143, 130, 72, 66, 79, 76, 27, 25, 16, 0, 182, 152, 109, 104, 142, 90, 75, 48, 56, 45, 34, 20, 0), # 16 (166, 203, 163, 155, 141, 76, 72, 83, 81, 28, 25, 18, 0, 204, 163, 119, 115, 160, 98, 82, 50, 62, 50, 36, 21, 0), # 17 (175, 224, 175, 163, 149, 80, 83, 91, 88, 31, 27, 19, 0, 217, 181, 128, 123, 168, 107, 90, 53, 67, 55, 40, 23, 0), # 18 (189, 234, 185, 176, 155, 83, 88, 97, 94, 32, 29, 22, 0, 229, 188, 144, 131, 186, 117, 93, 56, 71, 62, 41, 24, 0), # 19 (204, 245, 200, 187, 165, 87, 92, 102, 98, 35, 31, 23, 0, 239, 204, 161, 140, 194, 121, 98, 63, 79, 64, 45, 25, 0), # 20 (220, 258, 214, 198, 176, 91, 104, 108, 105, 38, 32, 26, 0, 262, 214, 177, 148, 205, 129, 101, 65, 88, 68, 50, 26, 0), # 21 (235, 273, 223, 211, 189, 95, 110, 117, 114, 41, 33, 26, 0, 282, 226, 182, 158, 221, 136, 105, 69, 93, 70, 54, 27, 0), # 22 (251, 280, 237, 226, 203, 103, 114, 121, 122, 42, 36, 27, 0, 303, 239, 189, 167, 240, 144, 107, 73, 99, 74, 57, 28, 0), # 23 (269, 293, 244, 244, 219, 109, 119, 126, 126, 46, 41, 28, 0, 322, 249, 200, 175, 254, 153, 114, 78, 107, 79, 59, 30, 0), # 24 (286, 315, 257, 264, 232, 114, 128, 131, 132, 46, 43, 28, 0, 334, 254, 209, 178, 273, 163, 120, 82, 110, 82, 60, 30, 0), # 25 (299, 331, 278, 286, 238, 117, 132, 136, 138, 50, 44, 30, 0, 349, 264, 218, 183, 279, 168, 124, 87, 116, 83, 63, 31, 0), # 26 (309, 353, 285, 299, 250, 120, 137, 139, 145, 53, 46, 30, 0, 365, 273, 232, 188, 293, 174, 127, 94, 122, 87, 65, 32, 0), # 27 (317, 373, 291, 309, 265, 122, 141, 146, 148, 54, 47, 32, 0, 381, 288, 242, 196, 305, 182, 134, 98, 126, 91, 69, 33, 0), # 28 (329, 382, 301, 322, 281, 127, 146, 155, 151, 55, 49, 33, 0, 393, 300, 249, 202, 315, 190, 143, 104, 129, 93, 73, 34, 0), # 29 (342, 395, 309, 334, 287, 135, 149, 159, 157, 56, 49, 37, 0, 407, 324, 257, 211, 326, 196, 153, 112, 134, 97, 74, 35, 0), # 30 (353, 411, 322, 346, 300, 141, 156, 162, 161, 58, 52, 40, 0, 414, 339, 263, 219, 338, 203, 160, 114, 146, 104, 77, 36, 0), # 31 (367, 420, 347, 356, 314, 145, 158, 166, 168, 62, 54, 41, 0, 424, 349, 276, 232, 347, 208, 169, 115, 150, 109, 78, 38, 0), # 32 (378, 438, 354, 374, 325, 151, 162, 175, 173, 65, 55, 43, 0, 442, 362, 283, 241, 358, 214, 171, 119, 157, 113, 83, 38, 0), # 33 (390, 455, 361, 391, 336, 157, 164, 184, 178, 68, 58, 44, 0, 452, 369, 299, 250, 378, 222, 180, 121, 166, 115, 85, 40, 0), # 34 (408, 473, 376, 404, 350, 160, 167, 191, 184, 73, 59, 44, 0, 462, 378, 307, 259, 389, 230, 187, 124, 174, 116, 87, 42, 0), # 35 (422, 486, 394, 416, 356, 165, 171, 196, 192, 75, 61, 45, 0, 477, 395, 314, 264, 400, 237, 193, 125, 180, 122, 89, 42, 0), # 36 (436, 496, 411, 433, 367, 169, 179, 201, 195, 76, 65, 46, 0, 487, 411, 320, 268, 412, 240, 202, 127, 182, 129, 94, 42, 0), # 37 (451, 508, 429, 448, 372, 176, 182, 208, 204, 79, 66, 52, 0, 502, 420, 329, 277, 422, 248, 209, 131, 186, 134, 96, 43, 0), # 38 (464, 527, 444, 460, 381, 181, 187, 214, 211, 82, 68, 53, 0, 519, 438, 338, 283, 436, 255, 214, 135, 190, 141, 99, 47, 0), # 39 (475, 537, 454, 463, 394, 188, 199, 218, 216, 86, 71, 55, 0, 538, 455, 348, 288, 455, 260, 222, 138, 195, 148, 104, 48, 0), # 40 (489, 551, 464, 474, 406, 196, 206, 228, 221, 87, 73, 57, 0, 551, 462, 357, 293, 466, 267, 226, 139, 197, 152, 109, 50, 0), # 41 (511, 560, 475, 488, 423, 204, 211, 235, 226, 89, 74, 58, 0, 565, 471, 366, 297, 475, 270, 229, 144, 206, 157, 111, 52, 0), # 42 (531, 574, 488, 500, 440, 210, 218, 238, 231, 90, 79, 59, 0, 584, 479, 375, 304, 489, 274, 242, 149, 210, 162, 113, 52, 0), # 43 (542, 588, 495, 505, 445, 211, 221, 244, 235, 92, 81, 59, 0, 601, 494, 380, 312, 503, 285, 246, 151, 215, 163, 115, 54, 0), # 44 (561, 597, 505, 517, 451, 221, 223, 248, 243, 95, 82, 60, 0, 614, 508, 389, 316, 517, 292, 249, 153, 225, 165, 115, 55, 0), # 45 (579, 615, 519, 526, 460, 229, 230, 251, 248, 97, 84, 60, 0, 622, 521, 397, 324, 529, 293, 251, 154, 226, 166, 117, 55, 0), # 46 (596, 627, 532, 544, 472, 232, 234, 259, 252, 98, 85, 61, 0, 648, 531, 410, 333, 547, 299, 253, 159, 234, 171, 123, 56, 0), # 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159 (10.198820932866035, 7.28304080162725, 9.125574450948537, 9.343506385929302, 8.321992122590341, 4.103212058438943, 3.221570623868649, 3.147432860557619, 4.525465106040038, 1.6594219781520132, 1.3060272186755595, 0.7817252273702489, 0.0, 11.110988852451014, 8.598977501072737, 6.530136093377798, 4.978265934456038, 9.050930212080075, 4.406406004780667, 3.221570623868649, 2.9308657560278157, 4.160996061295171, 3.114502128643102, 1.8251148901897079, 0.6620946183297501, 0.0), # 160 (10.042510876420344, 7.1573051140366015, 9.006721467228694, 9.213301128944565, 8.211833582663305, 4.053588080615757, 3.1693770122048135, 3.1101003109807053, 4.473387224599541, 1.6347303676098288, 1.2870063860732652, 0.77067287137255, 0.0, 10.962523662746737, 8.477401585098049, 6.435031930366326, 4.904191102829485, 8.946774449199083, 4.354140435372988, 3.1693770122048135, 2.8954200575826836, 4.105916791331652, 3.071100376314856, 1.801344293445739, 0.6506641012760548, 0.0), # 161 (9.8673704785969, 7.01946278200249, 8.86902503621808, 9.064612206380144, 8.08466011948299, 3.9951294996602726, 3.1115053384378664, 3.0659207681568685, 4.411313507026364, 1.6069049225635816, 1.2654790298916783, 0.7580893498314843, 0.0, 10.791476155852466, 8.338982848146326, 6.3273951494583915, 4.820714767690744, 8.822627014052728, 4.292289075419616, 3.1115053384378664, 2.8536639283287664, 4.042330059741495, 3.0215374021267154, 1.773805007243616, 0.6381329801820447, 0.0), # 162 (9.674498913559898, 6.870249823480022, 8.71354169049082, 8.898491578842531, 7.941428916517308, 3.928324536163185, 3.048292841627181, 3.015271421527823, 4.339791716098023, 1.5761270492688444, 1.2415893928515955, 0.7440621194752707, 0.0, 10.599119351045232, 8.184683314227977, 6.207946964257977, 4.728381147806532, 8.679583432196045, 4.221379990138953, 3.048292841627181, 2.8059460972594175, 3.970714458258654, 2.9661638596141775, 1.742708338098164, 0.6245681657709112, 0.0), # 163 (9.464995355473539, 6.710402256424303, 8.54132796262104, 8.71599120693821, 7.783097157234176, 3.853661410715189, 2.9800767608321266, 2.9585294605352903, 4.259369614592037, 1.5425781539811894, 1.2154817176738126, 0.7286786370321272, 0.0, 10.386726267602059, 8.015465007353399, 6.077408588369063, 4.627734461943566, 8.518739229184074, 4.141941244749407, 2.9800767608321266, 2.752615293367992, 3.891548578617088, 2.905330402312737, 1.7082655925242083, 0.6100365687658459, 0.0), # 164 (9.239958978502024, 6.5406560987904445, 8.353440385182864, 8.518163051273666, 7.610622025101502, 3.771628343906979, 2.9071943351120755, 2.8960720746209856, 4.1705949652859235, 1.5064396429561904, 1.1873002470791263, 0.7120263592302724, 0.0, 10.155569924799979, 7.832289951532995, 5.936501235395631, 4.51931892886857, 8.341189930571847, 4.05450090446938, 2.9071943351120755, 2.694020245647842, 3.805311012550751, 2.839387683757889, 1.670688077036573, 0.5946050998900405, 0.0), # 165 (9.000488956809557, 6.361747368533551, 8.150935490750417, 8.306059072455376, 7.4249607035872005, 3.682713556329251, 2.8299828035264003, 2.8282764532266285, 4.074015530957201, 1.4678929224494195, 1.157189223788332, 0.6941927427979253, 0.0, 9.906923341916015, 7.636120170777177, 5.78594611894166, 4.403678767348258, 8.148031061914402, 3.95958703451728, 2.8299828035264003, 2.630509683092322, 3.7124803517936003, 2.768686357485126, 1.6301870981500834, 0.5783406698666865, 0.0), # 166 (8.747684464560333, 6.174412083608727, 7.934869811897824, 8.080731231089835, 7.2270703761591815, 3.5874052685726983, 2.7487794051344725, 2.7555197857939366, 3.9701790743833865, 1.4271193987164503, 1.1252928905222266, 0.6752652444633036, 0.0, 9.642059538227196, 7.427917689096338, 5.626464452611132, 4.28135819614935, 7.940358148766773, 3.8577277001115116, 2.7487794051344725, 2.562432334694784, 3.6135351880795907, 2.693577077029946, 1.5869739623795647, 0.5613101894189753, 0.0), # 167 (8.482644675918554, 5.979386261971081, 7.706299881199207, 7.843231487783524, 7.017908226285359, 3.4861917012280164, 2.663921378995663, 2.6781792617646265, 3.8596333583419993, 1.3843004780128556, 1.0917554900016058, 0.6553313209546264, 0.0, 9.362251533010546, 7.20864453050089, 5.458777450008029, 4.152901434038566, 7.7192667166839986, 3.7494509664704774, 2.663921378995663, 2.490136929448583, 3.5089541131426794, 2.614410495927842, 1.5412599762398416, 0.5435805692700985, 0.0), # 168 (8.206468765048422, 5.777405921575724, 7.466282231228694, 7.594611803142927, 6.798431437433646, 3.3795610748859013, 2.5757459641693443, 2.5966320705804184, 3.7429261456105576, 1.339617566594208, 1.0567212649472661, 0.6344784290001119, 0.0, 9.0687723455431, 6.9792627190012295, 5.28360632473633, 4.018852699782624, 7.485852291221115, 3.635284898812586, 2.5757459641693443, 2.413972196347072, 3.399215718716823, 2.5315372677143095, 1.493256446245739, 0.5252187201432478, 0.0), # 169 (7.9202559061141375, 5.569207080377758, 7.215873394560408, 7.335924137774526, 6.569597193071951, 3.268001610137046, 2.4845903997148873, 2.5112554016830275, 3.620605198966578, 1.2932520707160806, 1.020334458080004, 0.6127940253279787, 0.0, 8.762894995101878, 6.740734278607764, 5.101672290400019, 3.879756212148241, 7.241210397933156, 3.5157575623562387, 2.4845903997148873, 2.3342868643836043, 3.2847985965359756, 2.4453080459248424, 1.4431746789120816, 0.5062915527616144, 0.0), # 170 (7.6251052732799005, 5.355525756332291, 6.956129903768475, 7.068220452284813, 6.3323626766681915, 3.152001527572146, 2.390791924691664, 2.4224264445141737, 3.4932182811875796, 1.2453853966340462, 0.9827393121206148, 0.5903655666664452, 0.0, 8.445892500963913, 6.494021233330896, 4.913696560603074, 3.736156189902138, 6.986436562375159, 3.3913970223198433, 2.390791924691664, 2.2514296625515327, 3.1661813383340958, 2.356073484094938, 1.391225980753695, 0.4868659778483902, 0.0), # 171 (7.322116040709912, 5.137097967394431, 6.688108291427019, 6.792552707280267, 6.087685071690277, 3.0320490477818964, 2.2946877781590462, 2.3305223885155746, 3.3613131550510804, 1.1961989506036783, 0.9440800697898953, 0.56728050974373, 0.0, 8.119037882406225, 6.24008560718103, 4.720400348949476, 3.588596851811034, 6.722626310102161, 3.2627313439218044, 2.2946877781590462, 2.165749319844212, 3.0438425358451386, 2.2641842357600894, 1.337621658285404, 0.4670089061267665, 0.0), # 172 (7.012387382568372, 4.914659731519285, 6.412865090110164, 6.509972863367375, 5.836521561606121, 2.9086323913569916, 2.196615199176405, 2.235920423128947, 3.225437583334597, 1.145874138880549, 0.9045009738086416, 0.5436263112880514, 0.0, 7.783604158705848, 5.979889424168563, 4.522504869043208, 3.437622416641646, 6.450875166669194, 3.130288592380526, 2.196615199176405, 2.077594565254994, 2.9182607808030605, 2.169990954455792, 1.282573018022033, 0.446787248319935, 0.0), # 173 (6.697018473019482, 4.6889470666619575, 6.131456832392036, 6.221532881152618, 5.579829329883635, 2.7822397788881266, 2.096911426803113, 2.1389977377960108, 3.08613932881565, 1.0945923677202316, 0.8641462668976501, 0.519490428027628, 0.0, 7.440864349139807, 5.7143947083039075, 4.32073133448825, 3.283777103160694, 6.1722786576313, 2.994596832914415, 2.096911426803113, 1.9873141277772333, 2.7899146649418176, 2.07384429371754, 1.2262913664784072, 0.42626791515108714, 0.0), # 174 (6.377108486227438, 4.460695990777558, 5.84494005084676, 5.928284721242486, 5.318565559990731, 2.653359430965997, 1.9959137000985407, 2.040131521958481, 2.943966154271756, 1.0425350433782987, 0.8231601917777163, 0.49496031669067847, 0.0, 7.092091472985131, 5.444563483597462, 4.115800958888581, 3.1276051301348957, 5.887932308543512, 2.8561841307418736, 1.9959137000985407, 1.8952567364042836, 2.6592827799953653, 1.9760949070808291, 1.1689880101693522, 0.40551781734341447, 0.0), # 175 (6.053756596356447, 4.230642521821194, 5.554371278048459, 5.631280344243462, 5.053687435395322, 2.5224795681812964, 1.8939592581220606, 1.9396989650580787, 2.7994658224804327, 0.9898835721103237, 0.781686991169637, 0.470123434005421, 0.0, 6.738558549518844, 5.17135777405963, 3.9084349558481852, 2.9696507163309707, 5.5989316449608655, 2.71557855108131, 1.8939592581220606, 1.8017711201294973, 2.526843717697661, 1.8770934480811543, 1.1108742556096918, 0.38460386562010856, 0.0), # 176 (5.7280619775707065, 3.9995226777479713, 5.260807046571258, 5.331571710762027, 4.786152139565322, 2.3900884111247205, 1.791385339933044, 1.8380772565365193, 2.6531860962191995, 0.9368193601718788, 0.7398709077942084, 0.4450672367000743, 0.0, 6.381538598017975, 4.895739603700816, 3.699354538971042, 2.8104580805156356, 5.306372192438399, 2.5733081591511273, 1.791385339933044, 1.707206007946229, 2.393076069782661, 1.7771905702540096, 1.0521614093142517, 0.3635929707043611, 0.0), # 177 (5.401123804034416, 3.7680724765129963, 4.9653038889892835, 5.030210781404673, 4.516916855968639, 2.2566741803869648, 1.6885291845908623, 1.7356435858355217, 2.505674738265573, 0.8835238138185378, 0.6978561843722264, 0.41987918150285664, 0.0, 6.022304637759553, 4.618670996531422, 3.489280921861132, 2.6505714414556127, 5.011349476531146, 2.4299010201697304, 1.6885291845908623, 1.611910128847832, 2.2584584279843196, 1.6767369271348913, 0.9930607777978567, 0.34255204331936334, 0.0), # 178 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179 ) passenger_allighting_rate = ( (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 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3 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 4 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 5 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 6 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 7 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 8 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 9 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 10 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 11 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 12 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 13 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 14 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 15 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 16 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 17 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 18 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 19 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 20 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 21 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 22 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 23 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 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168 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 169 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 170 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 171 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 172 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 173 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 174 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 175 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 176 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 177 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 178 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 179 ) """ parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html """ #initial entropy entropy = 8991598675325360468762009371570610170 #index for seed sequence child child_seed_index = ( 1, # 0 15, # 1 )

278.959358

492

0.771787

32,987

260,827

6.102161

0.22718

0.354112

0.339805

0.643841

0.367883

0.360928

0.359895

0.359527

0

0.851414

0.094829

260,827

934

493

279.25803

0.001182

0.015378

0

0.200873

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1

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false

0.005459

0

null

1

0

1

0

1

0

null

0

6

3f31d2bb293be6205ae663454629362d66493a43

4,755

py

Python

tests/distributed/test_against_external_daemon/test_single_instance.py

yuanl/jina

989d0689353bbbcd2c7bf11928b652224c3d4bf7

[ "Apache-2.0" ]

null

tests/distributed/test_against_external_daemon/test_single_instance.py

yuanl/jina

989d0689353bbbcd2c7bf11928b652224c3d4bf7

[ "Apache-2.0" ]

4

2020-09-01T17:47:27.000Z

2021-04-16T23:11:57.000Z

tests/distributed/test_against_external_daemon/test_single_instance.py

yuanl/jina

989d0689353bbbcd2c7bf11928b652224c3d4bf7

[ "Apache-2.0" ]

null

import os import numpy as np import pytest from jina import Flow from tests import random_docs cur_dir = os.path.dirname(os.path.abspath(__file__)) CLOUD_HOST = 'localhost:8000' # consider it as the staged version NUM_DOCS = 100 @pytest.mark.parametrize('silent_log', [True, False]) @pytest.mark.parametrize('parallels', [1, 2]) def test_r_l_simple(silent_log, parallels, mocker): response_mock = mocker.Mock() f = (Flow() .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) .add(parallel=parallels)) with f: f.index(('hello' for _ in range(NUM_DOCS)), on_done=response_mock) response_mock.assert_called() @pytest.mark.parametrize('silent_log', [True, False]) @pytest.mark.parametrize('parallels', [1, 2]) def test_l_r_simple(silent_log, parallels, mocker): response_mock = mocker.Mock() f = (Flow() .add(parallel=parallels) .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) ) with f: f.index(('hello' for _ in range(NUM_DOCS)), on_done=response_mock) response_mock.assert_called() @pytest.mark.parametrize('silent_log', [True, False]) @pytest.mark.parametrize('parallels', [1, 2]) def test_r_l_r_simple(silent_log, parallels, mocker): response_mock = mocker.Mock() f = (Flow() .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) .add() .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) ) with f: f.index(('hello' for _ in range(NUM_DOCS)), on_done=response_mock) response_mock.assert_called() @pytest.mark.parametrize('silent_log', [True, False]) @pytest.mark.parametrize('parallels', [1, 2]) def test_r_r_r_simple(silent_log, parallels, mocker): response_mock = mocker.Mock() f = (Flow() .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) ) with f: f.index(('hello' for _ in range(NUM_DOCS)), on_done=response_mock) response_mock.assert_called() @pytest.mark.parametrize('silent_log', [True, False]) @pytest.mark.parametrize('parallels', [1, 2]) def test_l_r_l_simple(silent_log, parallels, mocker): response_mock = mocker.Mock() f = (Flow() .add() .add(host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log) .add() ) with f: f.index(('hello' for _ in range(NUM_DOCS)), on_done=response_mock) response_mock.assert_called() @pytest.mark.parametrize('silent_log', [True, False]) @pytest.mark.parametrize('parallels', [1, 2]) def test_l_r_l_with_upload(silent_log, parallels, mocker): response_mock = mocker.Mock() f = (Flow() .add() .add(uses='mwu_encoder.yml', host=CLOUD_HOST, parallel=parallels, upload_files=['mwu_encoder.py'], silent_remote_logs=silent_log) .add()) with f: f.index_ndarray(np.random.random([NUM_DOCS, 100]), on_done=response_mock) response_mock.assert_called() @pytest.fixture() def docker_image(): img_name = 'test-mwu-encoder' import docker client = docker.from_env() client.images.build(path=os.path.join(cur_dir, '../../unit/mwu-encoder/'), tag=img_name) client.close() yield img_name client = docker.from_env() client.containers.prune() @pytest.mark.parametrize('silent_log', [True, False]) @pytest.mark.parametrize('parallels', [1, 2, 3]) def test_l_r_l_with_upload_remote(silent_log, parallels, docker_image, mocker): response_mock = mocker.Mock() f = (Flow() .add() .add(uses=f'docker://{docker_image}', host=CLOUD_HOST, parallel=parallels, silent_remote_logs=silent_log, timeout_ready=60000) .add()) with f: f.index_ndarray(np.random.random([NUM_DOCS, 100]), on_done=response_mock) response_mock.assert_called() @pytest.mark.parametrize('parallels', [2]) def test_create_pea_timeout(parallels): f = (Flow() .add() .add(uses='delayed_executor.yml', host=CLOUD_HOST, parallel=parallels, upload_files=['delayed_executor.py'], timeout_ready=20000) .add()) with f: f.index(random_docs(10))

29.534161

92

0.628601

597

4,755

4.735343

0.159129

0.076406

0.111426

0.081712

0.80474

0.776795

0.766183

0.735055

0

0.011398

0.243533

4,755

160

93

29.71875

0.774534

0.00694

0

0.691729

0

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0.009746

0

0.052632

1

0.067669

false

0

0.045113

0

0.112782

0

null

0

1

0

null

0

6

18cb8acc073e1a0c3244437b916e432fac5f61b8

148

py

Python

azazel/api/models/course.py

agata-project/azazel

501d55a8209e374b8f6315b9474109970f0b193a

[ "MIT" ]

4

2018-07-10T00:32:40.000Z

2018-07-12T01:22:20.000Z

azazel/api/models/course.py

agata-project/azazel

501d55a8209e374b8f6315b9474109970f0b193a

[ "MIT" ]

10

2018-07-12T14:18:34.000Z

2021-06-10T20:39:10.000Z

azazel/api/models/course.py

agata-project/azazel

501d55a8209e374b8f6315b9474109970f0b193a

[ "MIT" ]

1

2018-07-12T03:19:27.000Z

from django.db import models class Course(models.Model): initials = models.CharField(max_length=5) name = models.CharField(max_length=50)

21.142857

45

0.75

21

148

5.190476

0.714286

0.275229

0.330275

0.440367

0

0.02381

0.148649

148

6

46

24.666667

0.84127

0

1

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false

0

0.25

0

1

0

1

0

null

1

0

1

0

null

0

1

0

6

18f438bf55af321f2c442e20b7bde7ad028e6c61

309

py

Python

rpi_automator/dto/TempAndHumidityData.py

raviles/rpi_automator

8b7a1899cabed91b7c1f1be1508ab86a213776f6

[ "MIT" ]

1

2018-11-22T09:14:52.000Z

rpi_automator/dto/TempAndHumidityData.py

raviles/rpi_automator

8b7a1899cabed91b7c1f1be1508ab86a213776f6

[ "MIT" ]

null

rpi_automator/dto/TempAndHumidityData.py

raviles/rpi_automator

8b7a1899cabed91b7c1f1be1508ab86a213776f6

[ "MIT" ]

null

class TempAndHumidityData: """ Captures temperature and humidity data """ def __init__(self, temperature, humidity): self.temperature = temperature self.humidity = humidity def __str__(self): return 'temperature={}, humidity={}'.format(self.temperature, self.humidity)

25.75

84

0.679612

29

309

6.965517

0.448276

0.222772

0.227723

0

0.210356

309

11

85

28.090909

0.827869

0.122977

0

0.103448

0

1

0.333333

false

0

0.166667

0.666667

0

1

0

null

1

0

null

0

1

0

1

0

6

7a0e91998974b626e17484ae7a2c901a3e68aa53

12,669

py

Python

tests/api/v3_0_0/test_node_deployment.py

oianson/ciscoisesdk

c8fe9d80416048dd0ff2241209c4f78ab78c1a4a

[ "MIT" ]

null

tests/api/v3_0_0/test_node_deployment.py

oianson/ciscoisesdk

c8fe9d80416048dd0ff2241209c4f78ab78c1a4a

[ "MIT" ]

null

tests/api/v3_0_0/test_node_deployment.py

oianson/ciscoisesdk

c8fe9d80416048dd0ff2241209c4f78ab78c1a4a

[ "MIT" ]

null

# -*- coding: utf-8 -*- """IdentityServicesEngineAPI node_deployment API fixtures and tests. Copyright (c) 2021 Cisco and/or its affiliates. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import pytest from fastjsonschema.exceptions import JsonSchemaException from ciscoisesdk.exceptions import MalformedRequest from tests.environment import IDENTITY_SERVICES_ENGINE_VERSION pytestmark = pytest.mark.skipif(IDENTITY_SERVICES_ENGINE_VERSION != '3.0.0', reason='version does not match') def is_valid_get_all_nodes(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_fa838e78175e51b4bcfb0821c19b81b7_v3_0_0').validate(obj.response) return True def get_all_nodes(api): endpoint_result = api.node_deployment.get_all_nodes( ) return endpoint_result @pytest.mark.node_deployment def test_get_all_nodes(api, validator): try: assert is_valid_get_all_nodes( validator, get_all_nodes(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print(original_e) raise original_e def get_all_nodes_default(api): endpoint_result = api.node_deployment.get_all_nodes( ) return endpoint_result @pytest.mark.node_deployment def test_get_all_nodes_default(api, validator): try: assert is_valid_get_all_nodes( validator, get_all_nodes_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_register_node(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_e82e46732de25832a543c4640312588c_v3_0_0').validate(obj.response) return True def register_node(api): endpoint_result = api.node_deployment.register_node( active_validation=False, administration={'isEnabled': True, 'role': 'string'}, fdqn='string', general_settings={'monitoring': {'isEnabled': True, 'role': 'string', 'otherMonitoringNode': 'string', 'isMntDedicated': True, 'policyservice': {'enabled': True, 'sessionService': {'isEnabled': True, 'nodegroup': 'string'}, 'enableProfilingService': True, 'enableNACService': True, 'sxpservice': {'isEnabled': True, 'userInterface': 'string'}, 'enableDeviceAdminService': True, 'enablePassiveIdentityService': True}, 'enablePXGrid': True}}, password='string', payload=None, profile_configuration={'netflow': {'enabled': True, 'interface': 'string', 'port': {}, 'description': 'string'}, 'dhcp': {'enabled': True, 'interface': 'string', 'port': {}, 'description': 'string'}, 'dhcpSpan': {'enabled': True, 'interface': 'string', 'description': 'string'}, 'http': {'enabled': True, 'interface': 'string', 'description': 'string'}, 'radius': {'enabled': True, 'description': 'string'}, 'nmap': {'enabled': True, 'description': 'string'}, 'dns': {'enabled': True, 'description': 'string'}, 'snmpQuery': {'enabled': True, 'description': 'string', 'retries': 0, 'timeout': 0, 'eventTimeout': 0}, 'snmpTrap': {'linkTrapQuery': True, 'macTrapQuery': True, 'interface': 'string', 'port': {}, 'description': 'string'}, 'activeDirectory': {'enabled': True, 'daysBeforeRescan': 0, 'description': 'string'}, 'pxgrid': {'enabled': True, 'description': 'string'}}, user_name='string' ) return endpoint_result @pytest.mark.node_deployment def test_register_node(api, validator): try: assert is_valid_register_node( validator, register_node(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print(original_e) raise original_e def register_node_default(api): endpoint_result = api.node_deployment.register_node( active_validation=False, administration=None, fdqn=None, general_settings=None, password=None, payload=None, profile_configuration=None, user_name=None ) return endpoint_result @pytest.mark.node_deployment def test_register_node_default(api, validator): try: assert is_valid_register_node( validator, register_node_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_promote_node(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_42b11e2f1af656bcb5880a7b33720ec5_v3_0_0').validate(obj.response) return True def promote_node(api): endpoint_result = api.node_deployment.promote_node( active_validation=False, payload=None, promotion_type='string' ) return endpoint_result @pytest.mark.node_deployment def test_promote_node(api, validator): try: assert is_valid_promote_node( validator, promote_node(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print(original_e) raise original_e def promote_node_default(api): endpoint_result = api.node_deployment.promote_node( active_validation=False, payload=None, promotion_type=None ) return endpoint_result @pytest.mark.node_deployment def test_promote_node_default(api, validator): try: assert is_valid_promote_node( validator, promote_node_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_get_node_details(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_ae8d7c8f33bb52ceb04880845f2f45ba_v3_0_0').validate(obj.response) return True def get_node_details(api): endpoint_result = api.node_deployment.get_node_details( hostname='string' ) return endpoint_result @pytest.mark.node_deployment def test_get_node_details(api, validator): try: assert is_valid_get_node_details( validator, get_node_details(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print(original_e) raise original_e def get_node_details_default(api): endpoint_result = api.node_deployment.get_node_details( hostname='string' ) return endpoint_result @pytest.mark.node_deployment def test_get_node_details_default(api, validator): try: assert is_valid_get_node_details( validator, get_node_details_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_update_node(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_682c1fa3bf115c77be99b602aca1493b_v3_0_0').validate(obj.response) return True def update_node(api): endpoint_result = api.node_deployment.update_node( active_validation=False, general_settings={'monitoring': {'isEnabled': True, 'role': 'string', 'otherMonitoringNode': 'string', 'isMntDedicated': True, 'policyservice': {'enabled': True, 'sessionService': {'isEnabled': True, 'nodegroup': 'string'}, 'enableProfilingService': True, 'enableNACService': True, 'sxpservice': {'isEnabled': True, 'userInterface': 'string'}, 'enableDeviceAdminService': True, 'enablePassiveIdentityService': True}, 'enablePXGrid': True}}, hostname='string', payload=None, profile_configuration={'netflow': {'enabled': True, 'interface': 'string', 'port': {}, 'description': 'string'}, 'dhcp': {'enabled': True, 'interface': 'string', 'port': {}, 'description': 'string'}, 'dhcpSpan': {'enabled': True, 'interface': 'string', 'description': 'string'}, 'http': {'enabled': True, 'interface': 'string', 'description': 'string'}, 'radius': {'enabled': True, 'description': 'string'}, 'nmap': {'enabled': True, 'description': 'string'}, 'dns': {'enabled': True, 'description': 'string'}, 'snmpQuery': {'enabled': True, 'description': 'string', 'retries': 0, 'timeout': 0, 'eventTimeout': 0}, 'snmpTrap': {'linkTrapQuery': True, 'macTrapQuery': True, 'interface': 'string', 'port': {}, 'description': 'string'}, 'activeDirectory': {'enabled': True, 'daysBeforeRescan': 0, 'description': 'string'}, 'pxgrid': {'enabled': True, 'description': 'string'}} ) return endpoint_result @pytest.mark.node_deployment def test_update_node(api, validator): try: assert is_valid_update_node( validator, update_node(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print(original_e) raise original_e def update_node_default(api): endpoint_result = api.node_deployment.update_node( active_validation=False, hostname='string', general_settings=None, payload=None, profile_configuration=None ) return endpoint_result @pytest.mark.node_deployment def test_update_node_default(api, validator): try: assert is_valid_update_node( validator, update_node_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_delete_node(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_161d26670a205a78800cb50673027a6e_v3_0_0').validate(obj.response) return True def delete_node(api): endpoint_result = api.node_deployment.delete_node( hostname='string' ) return endpoint_result @pytest.mark.node_deployment def test_delete_node(api, validator): try: assert is_valid_delete_node( validator, delete_node(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print(original_e) raise original_e def delete_node_default(api): endpoint_result = api.node_deployment.delete_node( hostname='string' ) return endpoint_result @pytest.mark.node_deployment def test_delete_node_default(api, validator): try: assert is_valid_delete_node( validator, delete_node_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e

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false

0.01487

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0.215613

0.022305

0

null

0

1

0

null

0

6

e17fc8853b010762782b9e0e5f0885507c560a0d

10,342

py

Python

Utility/path_to_transcript_dicts.py

Vaibhavs10/IMS-Toucan

931e4ce63a4cc675cb15b72474a3c3619632a07b

[ "Apache-2.0" ]

93

2021-08-11T13:52:37.000Z

2022-03-29T23:19:07.000Z

Utility/path_to_transcript_dicts.py

Vaibhavs10/IMS-Toucan

931e4ce63a4cc675cb15b72474a3c3619632a07b

[ "Apache-2.0" ]

4

2021-12-15T17:23:14.000Z

2022-03-24T04:51:40.000Z

Utility/path_to_transcript_dicts.py

Vaibhavs10/IMS-Toucan

931e4ce63a4cc675cb15b72474a3c3619632a07b

[ "Apache-2.0" ]

25

2021-08-11T14:23:47.000Z

2022-03-28T20:23:51.000Z

import os def build_path_to_transcript_dict_karlsson(): root = "/mount/resources/speech/corpora/MAILabs_german_single_speaker_karlsson" path_to_transcript = dict() for el in os.listdir(root): if os.path.isdir(os.path.join(root, el)): with open(os.path.join(root, el, "metadata.csv"), "r", encoding="utf8") as file: lookup = file.read() for line in lookup.split("\n"): if line.strip() != "": norm_transcript = line.split("|")[2] wav_path = os.path.join(root, el, "wavs", line.split("|")[0] + ".wav") if os.path.exists(wav_path): path_to_transcript[wav_path] = norm_transcript return path_to_transcript def build_path_to_transcript_dict_eva(): root = "/mount/resources/speech/corpora/MAILabs_german_single_speaker_eva" path_to_transcript = dict() for el in os.listdir(root): if os.path.isdir(os.path.join(root, el)): with open(os.path.join(root, el, "metadata.csv"), "r", encoding="utf8") as file: lookup = file.read() for line in lookup.split("\n"): if line.strip() != "": norm_transcript = line.split("|")[2] wav_path = os.path.join(root, el, "wavs", line.split("|")[0] + ".wav") if os.path.exists(wav_path): path_to_transcript[wav_path] = norm_transcript return path_to_transcript def build_path_to_transcript_dict_elizabeth(): root = "/mount/resources/speech/corpora/MAILabs_british_single_speaker_elizabeth" path_to_transcript = dict() for el in os.listdir(root): if os.path.isdir(os.path.join(root, el)): with open(os.path.join(root, el, "metadata.csv"), "r", encoding="utf8") as file: lookup = file.read() for line in lookup.split("\n"): if line.strip() != "": norm_transcript = line.split("|")[2] wav_path = os.path.join(root, el, "wavs", line.split("|")[0] + ".wav") if os.path.exists(wav_path): path_to_transcript[wav_path] = norm_transcript return path_to_transcript def build_path_to_transcript_dict_nancy(): root = "/mount/resources/speech/corpora/NancyKrebs" path_to_transcript = dict() with open(os.path.join(root, "metadata.csv"), "r", encoding="utf8") as file: lookup = file.read() for line in lookup.split("\n"): if line.strip() != "": norm_transcript = line.split("|")[1] wav_path = os.path.join(root, "wav", line.split("|")[0] + ".wav") if os.path.exists(wav_path): path_to_transcript[wav_path] = norm_transcript return path_to_transcript def build_path_to_transcript_dict_hokuspokus(): path_to_transcript = dict() for transcript_file in os.listdir("/mount/resources/speech/corpora/LibriVox.Hokuspokus/txt"): if transcript_file.endswith(".txt"): with open("/mount/resources/speech/corpora/LibriVox.Hokuspokus/txt/" + transcript_file, 'r', encoding='utf8') as tf: transcript = tf.read() wav_path = "/mount/resources/speech/corpora/LibriVox.Hokuspokus/wav/" + transcript_file.rstrip(".txt") + ".wav" path_to_transcript[wav_path] = transcript return path_to_transcript def build_path_to_transcript_dict_libritts(): path_train = "/mount/resources/speech/corpora/LibriTTS/train-clean-100" path_to_transcript = dict() for speaker in os.listdir(path_train): for chapter in os.listdir(os.path.join(path_train, speaker)): for file in os.listdir(os.path.join(path_train, speaker, chapter)): if file.endswith("normalized.txt"): with open(os.path.join(path_train, speaker, chapter, file), 'r', encoding='utf8') as tf: transcript = tf.read() wav_file = file.split(".")[0] + ".wav" path_to_transcript[os.path.join(path_train, speaker, chapter, wav_file)] = transcript return path_to_transcript def build_path_to_transcript_dict_ljspeech(): path_to_transcript = dict() for transcript_file in os.listdir("/mount/resources/speech/corpora/LJSpeech/16kHz/txt"): with open("/mount/resources/speech/corpora/LJSpeech/16kHz/txt/" + transcript_file, 'r', encoding='utf8') as tf: transcript = tf.read() wav_path = "/mount/resources/speech/corpora/LJSpeech/16kHz/wav/" + transcript_file.rstrip(".txt") + ".wav" path_to_transcript[wav_path] = transcript return path_to_transcript def build_path_to_transcript_dict_css10de(): path_to_transcript = dict() with open("/mount/resources/speech/corpora/CSS10/german/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript["/mount/resources/speech/corpora/CSS10/german/" + line.split("|")[0]] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_thorsten(): path_to_transcript = dict() with open("/mount/resources/speech/corpora/Thorsten_DE/metadata_shuf.csv", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript["/mount/resources/speech/corpora/Thorsten_DE/wavs/" + line.split("|")[0] + ".wav"] = line.split("|")[1] return path_to_transcript def build_path_to_transcript_dict_css10el(): path_to_transcript = dict() language = "greek" with open(f"/mount/resources/speech/corpora/CSS10/{language}/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript[f"/mount/resources/speech/corpora/CSS10/{language}/{line.split('|')[0]}"] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_css10nl(): path_to_transcript = dict() language = "dutch" with open(f"/mount/resources/speech/corpora/CSS10/{language}/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript[f"/mount/resources/speech/corpora/CSS10/{language}/{line.split('|')[0]}"] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_css10fi(): path_to_transcript = dict() language = "finnish" with open(f"/mount/resources/speech/corpora/CSS10/{language}/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript[f"/mount/resources/speech/corpora/CSS10/{language}/{line.split('|')[0]}"] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_css10ru(): path_to_transcript = dict() language = "russian" with open(f"/mount/resources/speech/corpora/CSS10/{language}/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript[f"/mount/resources/speech/corpora/CSS10/{language}/{line.split('|')[0]}"] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_css10hu(): path_to_transcript = dict() language = "hungarian" with open(f"/mount/resources/speech/corpora/CSS10/{language}/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript[f"/mount/resources/speech/corpora/CSS10/{language}/{line.split('|')[0]}"] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_css10es(): path_to_transcript = dict() language = "spanish" with open(f"/mount/resources/speech/corpora/CSS10/{language}/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript[f"/mount/resources/speech/corpora/CSS10/{language}/{line.split('|')[0]}"] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_css10fr(): path_to_transcript = dict() language = "french" with open(f"/mount/resources/speech/corpora/CSS10/{language}/transcript.txt", encoding="utf8") as f: transcriptions = f.read() trans_lines = transcriptions.split("\n") for line in trans_lines: if line.strip() != "": path_to_transcript[f"/mount/resources/speech/corpora/CSS10/{language}/{line.split('|')[0]}"] = line.split("|")[2] return path_to_transcript def build_path_to_transcript_dict_nvidia_hifitts(): path_to_transcript = dict() transcripts = list() root = "/mount/resources/speech/corpora/hi_fi_tts_v0" import json for jpath in [f"{root}/6097_manifest_clean_dev.json", f"{root}/6097_manifest_clean_test.json", f"{root}/6097_manifest_clean_train.json", f"{root}/9017_manifest_clean_dev.json", f"{root}/9017_manifest_clean_test.json", f"{root}/9017_manifest_clean_train.json", f"{root}/92_manifest_clean_dev.json", f"{root}/92_manifest_clean_test.json", f"{root}/92_manifest_clean_train.json"]: with open(jpath, encoding='utf-8', mode='r') as jfile: for line in jfile.read().split("\n"): if line.strip() != "": transcripts.append(json.loads(line)) for transcript in transcripts: path = transcript["audio_filepath"] norm_text = transcript["text_normalized"] path_to_transcript[f"{root}/{path}"] = norm_text return path_to_transcript

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null

0

6

e18fbf8b3b28ae04b0046ee22253de71b7bf2ce7

177

py

Python

teste.py

isabelmussi/travis_aula01

2f8105ac7b8d2ce83776d66f94c8e96177ace2bd

[ "Apache-2.0" ]

null

teste.py

isabelmussi/travis_aula01

2f8105ac7b8d2ce83776d66f94c8e96177ace2bd

[ "Apache-2.0" ]

null

teste.py

isabelmussi/travis_aula01

2f8105ac7b8d2ce83776d66f94c8e96177ace2bd

[ "Apache-2.0" ]

null

import pytest #biblioteca pytest from principal import somar from principal import subtrair #def-função def test_somar(): #verifica se é verdadeiro assert somar(2,4)==6

19.666667

30

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0.192593

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6

e1b1a4fabea369dd027bebf796f0c080a7896e2b

52,540

py

Python

tests/column_aggregate_expectations_distributional/test_pandas_dataset_distributional_expectations.py

anhollis/great_expectations

41ccddfd2c604a0452d6ab142696f5d27c2d551f

[ "Apache-2.0" ]

1

2021-01-10T18:00:06.000Z

tests/column_aggregate_expectations_distributional/test_pandas_dataset_distributional_expectations.py

anhollis/great_expectations

41ccddfd2c604a0452d6ab142696f5d27c2d551f

[ "Apache-2.0" ]

null

tests/column_aggregate_expectations_distributional/test_pandas_dataset_distributional_expectations.py

anhollis/great_expectations

41ccddfd2c604a0452d6ab142696f5d27c2d551f

[ "Apache-2.0" ]

null

import unittest import json import numpy as np import sys import great_expectations as ge sys.path.append("./tests") from test_utils import assertDeepAlmostEqual sys.path.append("./great_expectations/dataset") from util import is_valid_continuous_partition_object class TestDistributionalExpectations(unittest.TestCase): def __init__(self, *args, **kwargs): super(TestDistributionalExpectations, self).__init__(*args, **kwargs) self.D = ge.read_csv( './tests/test_sets/distributional_expectations_data_test.csv') with open('./tests/test_sets/test_partitions.json', 'r') as infile: self.test_partitions = json.loads(infile.read()) def test_expect_column_chisquare_test_p_value_to_be_greater_than(self): T = [ { 'args': ['categorical_fixed'], 'kwargs': { 'partition_object': self.test_partitions['categorical_fixed'], 'p': 0.05 }, 'out': {'success': True, 'observed_value': 1.} }, { 'args': ['categorical_fixed'], 'kwargs': { 'partition_object': self.test_partitions['categorical_fixed_alternate'], 'p': 0.05 }, 'out': {'success': False, 'observed_value': 5.1397782097623862e-53} }, { 'args': ['categorical_fixed'], 'kwargs': { 'partition_object': self.test_partitions['categorical_fixed_alternate'], 'p': 0.05, 'result_format': 'SUMMARY' }, 'out': {'success': False, 'observed_value': 5.1397782097623862e-53, 'details': { 'observed_partition': { 'values': [u'A', u'B', u'C'], 'weights': [540, 320, 140] }, 'expected_partition': { 'values': [u'A', u'B', u'C'], 'weights': [333.3333333333333, 333.3333333333333, 333.3333333333333] } } } } ] for t in T: out = self.D.expect_column_chisquare_test_p_value_to_be_greater_than( *t['args'], **t['kwargs']) self.assertEqual(t['out']['success'], out['success']) self.assertEqual(t['out']['observed_value'], out['result']['observed_value']) if 'result_format' in t['kwargs'] and t['kwargs']['result_format'] == 'SUMMARY': self.assertDictEqual( t['out']['details'], out['result']['details']) def test_expect_column_chisquare_test_p_value_to_be_greater_than_new_categorical_val(self): # Note: Chisquare test with true zero expected could be treated subtly. Here, we tolerate a warning from stats. categorical_list = (['A'] * 25) + (['B'] * 25) + \ (['C'] * 25) + (['D'] * 25) df = ge.dataset.PandasDataset({'categorical': categorical_list}) out = df.expect_column_chisquare_test_p_value_to_be_greater_than( 'categorical', self.test_partitions['categorical_fixed_alternate']) self.assertEqual(out['success'], False) out = df.expect_column_chisquare_test_p_value_to_be_greater_than( 'categorical', self.test_partitions['categorical_fixed_alternate'], tail_weight_holdout=0.25) self.assertEqual(out['success'], True) def test_expect_column_chisquare_test_p_value_to_be_greater_than_missing_categorical_val(self): categorical_list = (['A'] * 61) + (['B'] * 39) df = ge.dataset.PandasDataset({'categorical': categorical_list}) out = df.expect_column_chisquare_test_p_value_to_be_greater_than( 'categorical', self.test_partitions['categorical_fixed']) self.assertEqual(out['success'], False) def test_expect_column_kl_divergence_to_be_less_than_discrete(self): T = [ { 'args': ['categorical_fixed'], 'kwargs': { 'partition_object': self.test_partitions['categorical_fixed'], 'threshold': 0.1 }, 'out': {'success': True, 'observed_value': 0.} }, { 'args': ['categorical_fixed'], 'kwargs': { 'partition_object': self.test_partitions['categorical_fixed_alternate'], 'threshold': 0.1 }, 'out': {'success': False, 'observed_value': 0.12599700286677529} }, { 'args': ['categorical_fixed'], 'kwargs': { 'partition_object': self.test_partitions['categorical_fixed_alternate'], 'threshold': 0.1, 'result_format': 'SUMMARY' }, 'out': {'success': False, 'observed_value': 0.12599700286677529, 'details': { 'observed_partition': { 'weights': [0.54, 0.32, 0.14], 'values': [u'A', u'B', u'C']}, 'expected_partition': { 'weights': [0.3333333333333333, 0.3333333333333333, 0.3333333333333333], 'values': [u'A', u'B', u'C'] } } } } ] for t in T: out = self.D.expect_column_kl_divergence_to_be_less_than( *t['args'], **t['kwargs']) self.assertTrue(np.allclose(out['success'], t['out']['success'])) self.assertTrue(np.allclose( out['result']['observed_value'], t['out']['observed_value'])) if 'result_format' in t['kwargs'] and t['kwargs']['result_format'] == 'SUMMARY': self.assertDictEqual( out['result']['details'], t['out']['details']) def test_expect_column_kl_divergence_to_be_less_than_discrete_holdout(self): df = ge.dataset.PandasDataset({'a': ['a', 'a', 'b', 'c']}) out = df.expect_column_kl_divergence_to_be_less_than('a', {'values': ['a', 'b'], 'weights': [ 0.6, 0.4]}, threshold=0.1, tail_weight_holdout=0.1) self.assertEqual(out['success'], True) self.assertTrue(np.allclose( out['result']['observed_value'], [0.099431384003497381])) out = df.expect_column_kl_divergence_to_be_less_than('a', {'values': ['a', 'b'], 'weights': [ 0.6, 0.4]}, threshold=0.1, tail_weight_holdout=0.05) self.assertEqual(out['success'], False) self.assertTrue(np.isclose( out['result']['observed_value'], [0.23216776319077681])) out = df.expect_column_kl_divergence_to_be_less_than('a', {'values': ['a', 'b'], 'weights': [ 0.6, 0.4]}, threshold=0.1) self.assertEqual(out['success'], False) self.assertEqual(out['result']['observed_value'], None) def test_expect_column_bootstrapped_ks_test_p_value_to_be_greater_than(self): T = [ { 'args': ['norm_0_1'], 'kwargs': {'partition_object': self.test_partitions['norm_0_1_auto'], "p": 0.05}, 'out': {'success': True, 'observed_value': "RANDOMIZED"} }, { 'args': ['norm_0_1'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_uniform'], "p": 0.05}, 'out':{'success': True, 'observed_value': "RANDOMIZED"} }, { 'args': ['norm_0_1'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_ntile'], "p": 0.05}, 'out':{'success': True, 'observed_value': "RANDOMIZED"} }, { 'args': ['norm_0_1'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_kde'], "p": 0.05}, 'out':{'success': True, 'observed_value': "RANDOMIZED"} }, { 'args': ['norm_1_1'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_auto'], "p": 0.05}, 'out':{'success': False, 'observed_value': "RANDOMIZED"} }, { 'args': ['norm_1_1'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_uniform'], "p": 0.05}, 'out':{'success': False, 'observed_value': "RANDOMIZED"} }, { 'args': ['norm_1_1'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_ntile'], "p": 0.05}, 'out':{'success': False, 'observed_value': "RANDOMIZED"} }, { 'args': ['norm_1_1'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_kde'], "p": 0.05}, 'out':{'success': False, 'observed_value': "RANDOMIZED"} }, { 'args': ['bimodal'], 'kwargs':{'partition_object': self.test_partitions['bimodal_auto'], "p": 0.05}, 'out':{'success': True, 'observed_value': "RANDOMIZED"} }, { 'args': ['bimodal'], 'kwargs':{'partition_object': self.test_partitions['bimodal_kde'], "p": 0.05}, 'out':{'success': True, 'observed_value': "RANDOMIZED"} }, { 'args': ['bimodal'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_auto'], "p": 0.05, 'include_config': True}, 'out':{'success': False, 'observed_value': "RANDOMIZED"} }, { 'args': ['bimodal'], 'kwargs':{'partition_object': self.test_partitions['norm_0_1_uniform'], "p": 0.05}, 'out':{'success': False, 'observed_value': "RANDOMIZED"} }, { 'args': ['bimodal'], 'kwargs': {'partition_object': self.test_partitions['norm_0_1_uniform'], "p": 0.05, 'result_format': 'SUMMARY'}, 'out': {'success': False, 'observed_value': "RANDOMIZED", 'details': { 'expected_cdf': { 'cdf_values': [0.0, 0.001, 0.009000000000000001, 0.056, 0.184, 0.429, 0.6779999999999999, 0.8899999999999999, 0.9689999999999999, 0.9929999999999999, 0.9999999999999999], 'x': [-3.721835843971108, -3.02304158492966, -2.324247325888213, -1.625453066846767, -0.926658807805319, -0.227864548763872, 0.470929710277574, 1.169723969319022, 1.868518228360469, 2.567312487401916, 3.266106746443364] }, 'observed_partition': { 'weights': [0.001, 0.006, 0.022, 0.07, 0.107, 0.146, 0.098, 0.04, 0.01, 0.0, 0.5], 'bins': [-3.721835843971108, -3.02304158492966, -2.324247325888213, -1.625453066846767, -0.926658807805319, -0.227864548763872, 0.470929710277574, 1.169723969319022, 1.868518228360469, 2.567312487401916, 3.266106746443364, 12.8787297644972] }, 'bootstrap_samples': 1000, 'observed_cdf': { 'cdf_values': [0, 0.001, 0.007, 0.028999999999999998, 0.099, 0.20600000000000002, 0.352, 0.44999999999999996, 0.48999999999999994, 0.49999999999999994, 0.49999999999999994, 1.0], 'x': [-3.721835843971108, -3.02304158492966, -2.324247325888213, -1.625453066846767, -0.926658807805319, -0.227864548763872, 0.470929710277574, 1.169723969319022, 1.868518228360469, 2.567312487401916, 3.266106746443364, 12.8787297644972] }, 'expected_partition': { 'weights': [0.001, 0.008, 0.047, 0.128, 0.245, 0.249, 0.212, 0.079, 0.024, 0.007], 'bins': [-3.721835843971108, -3.02304158492966, -2.324247325888213, -1.625453066846767, -0.926658807805319, -0.227864548763872, 0.470929710277574, 1.169723969319022, 1.868518228360469, 2.567312487401916, 3.266106746443364] }, 'bootstrap_sample_size': 20 } } } ] for t in T: out = self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than( *t['args'], **t['kwargs']) if out['success'] != t['out']['success']: print("Test case error:") print(t) print(out) self.assertEqual(out['success'], t['out']['success']) if 'result_format' in t['kwargs'] and t['kwargs']['result_format'] == 'SUMMARY': self.assertTrue(np.allclose( out['result']['details']['observed_cdf']['x'], t['out']['details']['observed_cdf']['x'])) self.assertTrue(np.allclose(out['result']['details']['observed_cdf'] ['cdf_values'], t['out']['details']['observed_cdf']['cdf_values'])) self.assertTrue(np.allclose( out['result']['details']['expected_cdf']['x'], t['out']['details']['expected_cdf']['x'])) self.assertTrue(np.allclose(out['result']['details']['expected_cdf'] ['cdf_values'], t['out']['details']['expected_cdf']['cdf_values'])) self.assertTrue(np.allclose( out['result']['details']['observed_partition']['bins'], t['out']['details']['observed_partition']['bins'])) self.assertTrue(np.allclose(out['result']['details']['observed_partition'] ['weights'], t['out']['details']['observed_partition']['weights'])) self.assertTrue(np.allclose( out['result']['details']['expected_partition']['bins'], t['out']['details']['expected_partition']['bins'])) self.assertTrue(np.allclose(out['result']['details']['expected_partition'] ['weights'], t['out']['details']['expected_partition']['weights'])) def test_expect_column_bootstrapped_ks_test_p_value_to_be_greater_than_expanded_partitions(self): # Extend observed above and below expected out = self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than('norm_0_1', {'bins': np.linspace(-1, 1, 11), 'weights': [0.1] * 10}, result_format='SUMMARY') self.assertTrue(out['result']['details']['observed_cdf']['x'][0] < -1) self.assertTrue(out['result']['details']['observed_cdf']['x'][-1] > 1) # Extend observed below expected out = self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than('norm_0_1', {'bins': np.linspace(-10, 1, 11), 'weights': [ 0.1] * 10}, result_format='SUMMARY') self.assertTrue(out['result']['details'] ['observed_cdf']['x'][0] == -10) self.assertTrue(out['result']['details']['observed_cdf']['x'][-1] > 1) # Extend observed above expected out = self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than('norm_0_1', {'bins': np.linspace(-1, 10, 11), 'weights': [ 0.1] * 10}, result_format='SUMMARY') self.assertTrue(out['result']['details']['observed_cdf']['x'][0] < -1) self.assertTrue(out['result']['details'] ['observed_cdf']['x'][-1] == 10) # Extend expected above and below observed out = self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than('norm_0_1', {'bins': np.linspace(-10, 10, 11), 'weights': [ 0.1] * 10}, result_format='SUMMARY') self.assertTrue(out['result']['details'] ['observed_cdf']['x'][0] == -10) self.assertTrue(out['result']['details'] ['observed_cdf']['x'][-1] == 10) def test_expect_column_bootstrapped_ks_test_p_value_to_be_greater_than_bad_partition(self): with self.assertRaises(ValueError): self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than( 'norm_0_1', {'bins': [-np.inf, 0, 1, 2, 3], 'weights': [0.25, 0.25, 0.25, 0.25]}) def test_expect_column_kl_divergence_to_be_less_than_continuous_infinite_partition(self): # Manually build a partition extending to -Inf and Inf test_partition = self.test_partitions['norm_0_1_auto'] test_partition['bins'] = [-np.inf] + test_partition['bins'] + [np.inf] scaled_weights = np.array(test_partition['weights']) * (1-0.01) test_partition['weights'] = [0.005] + scaled_weights.tolist() + [0.005] out = self.D.expect_column_kl_divergence_to_be_less_than( 'norm_0_1', test_partition, 0.5, internal_weight_holdout=0.01) self.assertTrue(out['success']) # This should fail: tails have internal weight zero, which is highly unlikely. out = self.D.expect_column_kl_divergence_to_be_less_than( 'norm_0_1', test_partition, 0.5) self.assertFalse(out['success']) # Build one-sided to infinity test partitions test_partition = { 'bins': [-np.inf, 0, 1, 2, 3], 'weights': [0.25, 0.25, 0.25, 0.25] } summary_expected_partition = { 'bins': [0, 1, 2, 3], 'weights': [0.25, 0.25, 0.25], 'tail_weights':[0.25,0] } summary_observed_partition = { 'bins': [0, 1, 2, 3], 'weights': [0.25, 0.25, 0.25], 'tail_weights':[0.25,0] } test_df = ge.dataset.PandasDataset( {'x': [-0.5, 0.5, 1.5, 2.5]}) # This should succeed: our data match the partition out = test_df.expect_column_kl_divergence_to_be_less_than( 'x', test_partition, 0.5, result_format='SUMMARY') self.assertTrue(out['success']) self.assertDictEqual( out['result']['details']['observed_partition'], summary_observed_partition) self.assertDictEqual( out['result']['details']['expected_partition'], summary_expected_partition) # Build one-sided to infinity test partitions test_partition = { 'bins': [0, 1, 2, 3, np.inf], 'weights': [0.25, 0.25, 0.25, 0.25] } summary_expected_partition = { 'bins': [0, 1, 2, 3], 'weights': [0.25, 0.25, 0.25], 'tail_weights':[0,0.25] } summary_observed_partition = { 'bins': [0, 1, 2, 3], 'weights': [0.2, 0.2, 0.2], 'tail_weights':[0.2,0.2] } test_df = ge.dataset.PandasDataset( {'x': [-0.5, 0.5, 1.5, 2.5, 3.5]}) out = test_df.expect_column_kl_divergence_to_be_less_than( 'x', test_partition, 0.5, result_format='SUMMARY') # This should fail: we expect zero weight less than 0 self.assertFalse(out['success']) self.assertDictEqual( out['result']['details']['observed_partition'], summary_observed_partition) self.assertDictEqual( out['result']['details']['expected_partition'], summary_expected_partition) # Build two-sided to infinity test partition test_partition = { 'bins': [-np.inf, 0, 1, 2, 3, np.inf], 'weights': [0.1, 0.2, 0.4, 0.2, 0.1] } summary_expected_partition = { 'bins': [ 0, 1, 2, 3], 'weights': [0.2, 0.4, 0.2], 'tail_weights':[0.1,0.1] } summary_observed_partition = { 'bins': [0, 1, 2, 3], 'weights': [0.2, 0.4, 0.2], 'tail_weights':[0.1,0.1] } test_df = ge.dataset.PandasDataset( {'x': [-0.5, 0.5, 0.5, 1.5, 1.5, 1.5, 1.5, 2.5, 2.5, 3.5]}) # This should succeed: our data match the partition out = test_df.expect_column_kl_divergence_to_be_less_than( 'x', test_partition, 0.5, result_format='SUMMARY') self.assertTrue(out['success']) self.assertDictEqual( out['result']['details']['observed_partition'], summary_observed_partition) self.assertDictEqual( out['result']['details']['expected_partition'], summary_expected_partition) # Tail weight holdout is not defined for partitions already extending to infinity: with self.assertRaises(ValueError): test_df.expect_column_kl_divergence_to_be_less_than( 'x', test_partition, 0.5, tail_weight_holdout=0.01) def test_expect_column_kl_divergence_to_be_less_than_continuous_serialized_infinite_partition(self): with open('./tests/test_sets/test_partition_serialized_infinity_bins.json', 'r') as infile: test_partition = json.loads(infile.read())['test_partition'] summary_expected_partition = { 'bins': [0, 1, 2, 3], 'weights': [0.2, 0.4, 0.2], 'tail_weights':[0.1,0.1] } summary_observed_partition = { 'bins': [0, 1, 2, 3], 'weights': [0.2, 0.4, 0.2], 'tail_weights':[0.1,0.1] } test_df = ge.dataset.PandasDataset( {'x': [-0.5, 0.5, 0.5, 1.5, 1.5, 1.5, 1.5, 2.5, 2.5, 3.5]}) # This should succeed: our data match the partition out = test_df.expect_column_kl_divergence_to_be_less_than( 'x', test_partition, 0.5, result_format='SUMMARY') self.assertTrue(out['success']) self.assertDictEqual( out['result']['details']['observed_partition'], summary_observed_partition) self.assertDictEqual( out['result']['details']['expected_partition'], summary_expected_partition) # Confirm serialization of resulting expectations config expectation_config = test_df.get_expectations_config() found_expectation = False for expectation in expectation_config['expectations']: if 'expectation_type' in expectation and expectation['expectation_type'] == 'expect_column_kl_divergence_to_be_less_than': self.assertEqual( json.dumps(expectation['kwargs'] ['partition_object']['bins']), '[-Infinity, 0, 1, 2, 3, Infinity]' ) found_expectation = True self.assertTrue(found_expectation) def test_expect_column_kl_divergence_to_be_less_than_continuous(self): T = [ { 'args': ['norm_0_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_auto'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':True, 'observed_value': 'NOTTESTED'} }, { 'args': ['norm_0_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_uniform'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':True, 'observed_value': 'NOTTESTED'} }, { 'args': ['norm_0_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_ntile'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':True, 'observed_value': 'NOTTESTED'} }, ## Note higher threshold example for kde { 'args': ['norm_0_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_kde'], "threshold": 0.3, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':True, 'observed_value': 'NOTTESTED'} }, { 'args': ['norm_1_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_auto'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':False, 'observed_value': 'NOTTESTED'} }, { 'args': ['norm_1_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_uniform'], "threshold": 0.1, "tail_weight_holdout": 1e-5, "internal_weight_holdout": 1e-5}, 'out':{'success':False, 'observed_value': 'NOTTESTED'} }, { 'args': ['norm_1_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_ntile'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':False, 'observed_value': 'NOTTESTED'} }, { 'args': ['norm_1_1'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_kde'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':False, 'observed_value': 'NOTTESTED'} }, { 'args': ['bimodal'], 'kwargs':{"partition_object": self.test_partitions['bimodal_auto'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':True, 'observed_value': 'NOTTESTED'} }, { 'args': ['bimodal'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_auto'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':False, 'observed_value': "NOTTESTED"} }, { 'args': ['bimodal'], 'kwargs':{"partition_object": self.test_partitions['norm_0_1_uniform'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01}, 'out':{'success':False, 'observed_value': "NOTTESTED"} }, { 'args': ['bimodal'], 'kwargs': {"partition_object": self.test_partitions['norm_0_1_uniform'], "threshold": 0.1, "tail_weight_holdout": 0.01, "internal_weight_holdout": 0.01, "result_format": "SUMMARY"}, 'out': {'success': False, 'observed_value': "NOTTESTED", 'details': {'observed_partition': {'weights': [0.001, 0.006, 0.022, 0.07, 0.107, 0.146, 0.098, 0.04, 0.01, 0.0], 'bins': [-3.721835843971108, -3.02304158492966, -2.324247325888213, -1.625453066846767, -0.926658807805319, -0.227864548763872, 0.470929710277574, 1.169723969319022, 1.868518228360469, 2.567312487401916, 3.266106746443364], 'tail_weights':[0.0,0.5] }, 'missing_percent': 0.0, 'element_count': 1000, 'missing_count': 0, 'expected_partition': {'bins': [-3.721835843971108, -3.02304158492966, -2.324247325888213, -1.625453066846767, -0.926658807805319, -0.227864548763872, 0.470929710277574, 1.169723969319022, 1.868518228360469, 2.567312487401916, 3.266106746443364], 'weights': [0.00098, 0.00784, 0.04606, 0.12544, 0.24009999999999998, 0.24402, 0.20776, 0.07742, 0.02352, 0.00686], 'tail_weights':[0.005,0.005] } } } } ] for t in T: out = self.D.expect_column_kl_divergence_to_be_less_than( *t['args'], **t['kwargs']) if t['out']['observed_value'] != 'NOTTESTED': if not np.allclose(out['observed_value'], t['out']['observed_value']): print("Test case error:") print(t) print(out) self.assertTrue(np.allclose( out['observed_value'], t['out']['observed_value'])) if 'result_format' in t['kwargs'] and t['kwargs']['result_format'] == 'SUMMARY': self.assertTrue(np.allclose(out['result']['details']['observed_partition']['bins'],t['out']['details']['observed_partition']['bins'])) self.assertTrue(np.allclose(out['result']['details']['observed_partition']['weights'],t['out']['details']['observed_partition']['weights'])) self.assertTrue(np.allclose(out['result']['details']['observed_partition']['tail_weights'],t['out']['details']['observed_partition']['tail_weights'])) self.assertTrue(np.allclose(out['result']['details']['expected_partition']['bins'],t['out']['details']['expected_partition']['bins'])) self.assertTrue(np.allclose(out['result']['details']['expected_partition']['weights'],t['out']['details']['expected_partition']['weights'])) self.assertTrue(np.allclose(out['result']['details']['expected_partition']['tail_weights'],t['out']['details']['expected_partition']['tail_weights'])) if not out['success'] == t['out']['success']: print("Test case error:") print(t) print(out) self.assertEqual(out['success'], t['out']['success']) def test_expect_column_kl_divergence_to_be_less_than_bad_parameters(self): with self.assertRaises(ValueError): self.D.expect_column_kl_divergence_to_be_less_than( 'norm_0_1', {}, threshold=0.1) with self.assertRaises(ValueError): self.D.expect_column_kl_divergence_to_be_less_than( 'norm_0_1', self.test_partitions['norm_0_1_auto']) with self.assertRaises(ValueError): self.D.expect_column_kl_divergence_to_be_less_than( 'norm_0_1', self.test_partitions['norm_0_1_auto'], threshold=0.1, tail_weight_holdout=2) with self.assertRaises(ValueError): self.D.expect_column_kl_divergence_to_be_less_than( 'norm_0_1', self.test_partitions['norm_0_1_auto'], threshold=0.1, internal_weight_holdout=2) with self.assertRaises(ValueError): self.D.expect_column_kl_divergence_to_be_less_than( 'categorical_fixed', self.test_partitions['categorical_fixed'], threshold=0.1, internal_weight_holdout=0.01) def test_expect_column_kl_divergence_to_be_less_than_infinite_observed_value(self): # Test with discrete distribution discrete_df = ge.dataset.PandasDataset( {"x1": ['a', 'a', 'a', 'a', 'b', 'b', 'b', 'b', 'c', 'c']}) discrete_partition_object = {"weights": [0.5, 0.5], "values": ["a", "b"]} discrete_out = discrete_df.expect_column_kl_divergence_to_be_less_than("x1", discrete_partition_object, 0.05) discrete_out_json = json.dumps( discrete_out['result']['observed_value']) self.assertEqual(discrete_out['result']['observed_value'], None) self.assertEqual(discrete_out_json, 'null') # Test with continuous distribution continuous_df = ge.dataset.PandasDataset({"x2": [-1.5, -1.5, -1.35, -1.2, -1.19, -1.12, -1.04, -1, 0, 0, 0, 0.25, 0.34, 1, 1.1, 1.13, 1.22, 1.34, 1.4, 1.46, 1.5, 1.5, 1.5]}) continuous_partition_object1 = {"weights": [0.1, 0.4, 0, 0, 0.4, 0.1], "bins": [-2, -1.5, -1, 0, 1, 1.5, 2]} # Partition sets weight to zero for to a non-empty bin continuous_out1 = continuous_df.expect_column_kl_divergence_to_be_less_than("x2", continuous_partition_object1, 0.05) continuous_out_json1 = json.dumps( continuous_out1['result']['observed_value']) self.assertEqual(continuous_out1['result']['observed_value'], None) self.assertEqual(continuous_out_json1, 'null') continuous_partition_object2 = {"weights": [0.25, 0.25, 0.25, 0.25], "bins": [-1, 0, 1, 1.5, 2]} # Partition bins do not cover all of data set continuous_out2 = continuous_df.expect_column_kl_divergence_to_be_less_than("x2", continuous_partition_object2, 0.05) continuous_out_json2 = json.dumps( continuous_out2['result']['observed_value']) self.assertEqual(continuous_out2['result']['observed_value'], None) self.assertEqual(continuous_out_json2, 'null') def test_expect_column_kl_divergence_to_be_less_than_infinite_return_bins(self): continuous_df=ge.dataset.PandasDataset({"x":[-1.95, 1.03, 1.00, 0.81, -2.27, 0.52, 2.45, -1.19, -0.17, -1.54, 2.20, -2.66, 1.71, 1.59, 2.19]}) #Both endpoints at infinity, no tail_holdout or internal_holdout continuous_partition_object={"weights":[0.3,0.15,0.05,0.05,0.2,0.25], "bins":[-np.inf,-2,-1,0,1,2,np.inf]} expected_details={ "observed_partition": { # return expected_bins, since we used those bins to compute the observed_weights "bins": [-2,-1,0,1,2], "weights": [3/15.0, 1/15.0, 2/15.0, 4/15.0], "tail_weights": [2/15.0,3/15.0] }, "expected_partition": { "bins": [-2,-1,0,1,2], "weights": [0.15,0.05,0.05,0.2], "tail_weights":[0.3,0.25] } } actual_details=continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0, internal_weight_holdout=0, result_format="COMPLETE")["result"]["details"] assertDeepAlmostEqual(expected_details,actual_details) self.assertTrue(is_valid_continuous_partition_object(actual_details["observed_partition"])) self.assertTrue(is_valid_continuous_partition_object(actual_details["expected_partition"])) #Both endpoints bounded, no tail_holdout or internal_holdout continuous_partition_object={"weights":[0.3,0.15,0.05,0.05,0.2,0.25], "bins":[-3,-2,-1,0,1,2,3]} expected_details={ "observed_partition": { # return expected_bins, since we used those bins to compute the observed_weights "bins": [-3,-2,-1,0,1,2,3], "weights": [2/15.0,3/15.0, 1/15.0, 2/15.0, 4/15.0,3/15.0], "tail_weights": [0,0] }, "expected_partition": { "bins": [-3,-2,-1,0,1,2,3], "weights": [0.3,0.15,0.05,0.05,0.2,0.25], "tail_weights":[0,0] } } actual_details=continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0, internal_weight_holdout=0, result_format="COMPLETE")["result"]["details"] assertDeepAlmostEqual(expected_details,actual_details) self.assertTrue(is_valid_continuous_partition_object(actual_details["observed_partition"])) self.assertTrue(is_valid_continuous_partition_object(actual_details["expected_partition"])) #Infinite KL Divergence, no tail_holdout or internal_holdout continuous_partition_object={"weights":[0.45,0.05,0.05,0.2,0.25], "bins":[-2,-1,0,1,2,3]} expected_details={ "observed_partition": { # return expected_bins, since we used those bins to compute the observed_weights "bins": [-2,-1,0,1,2,3], "weights": [3/15.0, 1/15.0, 2/15.0, 4/15.0,3/15.0], "tail_weights": [2/15.0,0] }, "expected_partition": { "bins": [-2,-1,0,1,2,3], "weights": [0.45,0.05,0.05,0.2,0.25], "tail_weights":[0,0] } } actual_details=continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0, internal_weight_holdout=0, result_format="COMPLETE")["result"]["details"] assertDeepAlmostEqual(expected_details,actual_details) self.assertTrue(is_valid_continuous_partition_object(actual_details["observed_partition"])) self.assertTrue(is_valid_continuous_partition_object(actual_details["expected_partition"])) #Both endpoints at infinity, non-zero tail hold_out continuous_partition_object={"weights":[0.3,0.15,0.05,0.05,0.2,0.25], "bins":[-np.inf,-2,-1,0,1,2,np.inf]} with self.assertRaises(ValueError): actual_details=continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0.01, internal_weight_holdout=0, result_format="COMPLETE")["result"]["details"] #Upper at infinity, non-zero tail hold_out continuous_partition_object={"weights":[0.3,0.15,0.05,0.05,0.2,0.25], "bins":[-3,-2,-1,0,1,2,np.inf]} expected_details={ "observed_partition": { # return expected_bins, since we used those bins to compute the observed_weights "bins": [-3,-2,-1,0,1,2], "weights": [2/15.0,3/15.0, 1/15.0, 2/15.0, 4/15.0], "tail_weights": [0,3/15.0] }, "expected_partition": { "bins": [-3,-2,-1,0,1,2], "weights": [0.3*0.98,0.15*0.98,0.05*0.98,0.05*0.98,0.2*0.98], "tail_weights":[0.02,0.98*0.25] } } actual_details=continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0.02, internal_weight_holdout=0, result_format="COMPLETE")["result"]["details"] assertDeepAlmostEqual(expected_details,actual_details) self.assertTrue(is_valid_continuous_partition_object(actual_details["observed_partition"])) self.assertTrue(is_valid_continuous_partition_object(actual_details["expected_partition"])) #Lower at infinity, non-zero tail holdout continuous_partition_object={"weights":[0.3,0.15,0.05,0.05,0.45], "bins":[-np.inf,-2,-1,0,1,2]} expected_details={ "observed_partition": { # return expected_bins, since we used those bins to compute the observed_weights "bins": [-2,-1,0,1,2], "weights": [3/15.0, 1/15.0, 2/15.0, 4/15.0], "tail_weights": [2/15.0,3/15.0] }, "expected_partition": { "bins": [-2,-1,0,1,2], "weights": [0.15*0.95,0.05*0.95,0.05*0.95,0.45*0.95], "tail_weights":[0.3*0.95,0.05] } } actual_details=continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0.05, internal_weight_holdout=0, result_format="COMPLETE")["result"]["details"] assertDeepAlmostEqual(expected_details,actual_details) self.assertTrue(is_valid_continuous_partition_object(actual_details["observed_partition"])) self.assertTrue(is_valid_continuous_partition_object(actual_details["expected_partition"])) #Bounded Endpoints, non-zero tail holdout, non-zero internal holdout continuous_partition_object={"weights":[0.3,0.15,0.0,0.10,0.45], "bins":[-3,-2,-1,0,1,2]} expected_details= { "observed_partition": { # return expected_bins, since we used those bins to compute the observed_weights "bins": [-3,-2,-1,0,1,2], "weights": [2/15.0,3/15.0, 1/15.0, 2/15.0, 4/15.0], "tail_weights": [0.0,3/15.0] }, "expected_partition": { "bins": [-3,-2,-1,0,1,2], "weights": [0.3*0.9,0.15*0.9,0.05,0.10*0.9,0.45*0.9], "tail_weights":[0.05/2,0.05/2] } } actual_details=continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0.05, internal_weight_holdout=0.05, result_format="COMPLETE")["result"]["details"] assertDeepAlmostEqual(expected_details,actual_details) self.assertTrue(is_valid_continuous_partition_object(actual_details["observed_partition"])) self.assertTrue(is_valid_continuous_partition_object(actual_details["expected_partition"])) def test_expect_column_kl_divergence_to_be_less_than_user_tail_weights(self): continuous_df=ge.dataset.PandasDataset({"x":[-1.95, 1.03, 1.00, 0.81, -2.27, 0.52, 2.45, -1.19, -0.17, -1.54, 2.20, -2.66, 1.71, 1.59, 2.19]}) #This should exit without error continuous_partition_object={"weights":[0.3,0.15,0.0,0.10,0.15], "bins":[-3,-2,-1,0,1,2], "tail_weights":[0.15,0.15]} continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05) #Error: Only one tail weight continuous_partition_object={"weights":[0.3,0.15,0.0,0.10,0.30], "bins":[-3,-2,-1,0,1,2], "tail_weights":[0.15]} self.assertFalse(is_valid_continuous_partition_object(continuous_partition_object)) #Error: Use of tail_weights with infinite end points partition continuous_partition_object={"weights":[0.3,0.15,0.0,0.10,0.15], "bins":[-3,-2,-1,0,1,np.inf], "tail_weights":[0.15,0.15]} with self.assertRaises(ValueError): continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05) #Error: Use of tail_weights and tail_weight_holdout continuous_partition_object={"weights":[0.3,0.15,0.0,0.10,0.15], "bins":[-3,-2,-1,0,1,2], "tail_weights":[0.15,0.15]} with self.assertRaises(ValueError): continuous_df.expect_column_kl_divergence_to_be_less_than("x", continuous_partition_object, 0.05, tail_weight_holdout=0.01) #Error: Tail_weights and weights don't add to one continuous_partition_object={"weights":[0.3,0.15,0.0,0.10,0.16], "bins":[-3,-2,-1,0,1,2], "tail_weights":[0.15,0.15]} self.assertFalse(is_valid_continuous_partition_object(continuous_partition_object)) def test_expect_column_bootstrapped_ks_test_p_value_to_be_greater_than_bad_parameters(self): with self.assertRaises(ValueError): self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than( 'norm_0_1', self.test_partitions['categorical_fixed']) test_partition = ge.dataset.util.kde_partition_data( self.D['norm_0_1'], estimate_tails=False) with self.assertRaises(ValueError): self.D.expect_column_bootstrapped_ks_test_p_value_to_be_greater_than( 'norm_0_1', test_partition) def test_expect_column_chisquare_test_p_value_to_be_greater_than_bad_parameters(self): with self.assertRaises(ValueError): self.D.expect_column_chisquare_test_p_value_to_be_greater_than( 'categorical_fixed', self.test_partitions['norm_0_1_auto']) if __name__ == "__main__": unittest.main()

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null

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null

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6

e1b3a0a1918c83c1a9c7807018dafc05e51d64e1

47

py

Python

scripts/portal/out_cygnusGarden.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

54

2019-04-16T23:24:48.000Z

2021-12-18T11:41:50.000Z

scripts/portal/out_cygnusGarden.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

3

2019-05-19T15:19:41.000Z

2020-04-27T16:29:16.000Z

scripts/portal/out_cygnusGarden.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

49

2020-11-25T23:29:16.000Z

2022-03-26T16:20:24.000Z

# 271040000 sm.warp(271030600, 0) sm.dispose()

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becd47d689aa7e847259be3624c0472b757d39a2

155

py

Python

users/admin.py

Mutghost01/ailms

1aaa45ad3fb3c71bc1f356069290e2ca016f0e06

[ "Apache-2.0" ]

null

users/admin.py

Mutghost01/ailms

1aaa45ad3fb3c71bc1f356069290e2ca016f0e06

[ "Apache-2.0" ]

null

users/admin.py

Mutghost01/ailms

1aaa45ad3fb3c71bc1f356069290e2ca016f0e06

[ "Apache-2.0" ]

null

from django.contrib import admin from users.models import * admin.site.register(Student) admin.site.register(Lecturer) admin.site.register(LecturerRating)

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null

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6

bef749d55344298c4f186b67758919ea2649792e

158

py

Python

robots/small/strategies/2019/test/cam_test/manje_agresivna/test3/init.py

memristor/mep2

bc5cddacba3d740f791f3454b8cb51bda83ce202

[ "MIT" ]

5

2018-11-27T15:15:00.000Z

2022-02-10T21:44:13.000Z

robots/small/strategies/2019/test/cam_test/manje_agresivna/test3/init.py

memristor/mep2

bc5cddacba3d740f791f3454b8cb51bda83ce202

[ "MIT" ]

2

2018-10-20T15:48:40.000Z

2018-11-20T05:11:33.000Z

robots/small/strategies/2019/test/cam_test/manje_agresivna/test3/init.py

memristor/mep2

bc5cddacba3d740f791f3454b8cb51bda83ce202

[ "MIT" ]

1

2020-02-07T12:44:47.000Z

def run(): @_core.listen('test') def _(): print('a test 2') @_core.on('test') def _(): print('a test') _emit('test') _emit('test') _emit('test')

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6

8320271145d18de99a0dcbc3432172454eed3dc3

22

py

Python

models/__init__.py

psui3905/CCT

637cbac130b39f02733339c79cdf1d531e339e9c

[ "MIT" ]

308

2020-06-09T13:37:17.000Z

2022-03-24T07:43:33.000Z

models/__init__.py

lesvay/CCT

cf98ea7e6aefa7091e6c375a9025ba1e0f6e53ca

[ "MIT" ]

55

2020-06-16T11:57:54.000Z

2022-03-09T12:04:58.000Z

models/__init__.py

lesvay/CCT

cf98ea7e6aefa7091e6c375a9025ba1e0f6e53ca

[ "MIT" ]

51

2020-06-08T02:42:14.000Z

2022-02-25T16:38:36.000Z

from .model import CCT

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0

1

0

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83221fed88505f657dd6938bbb9722f8a761af4a

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py

Python

lib_profiler/datamart_profiler/warning_tools.py

VIDA-NYU/auctus

49e83f9f61f3e35422b8c5fd40b9d5376b9f92a2

[ "Apache-2.0" ]

15

2020-12-22T15:28:56.000Z

2022-03-29T08:13:49.000Z

lib_profiler/datamart_profiler/warning_tools.py

VIDA-NYU/auctus

49e83f9f61f3e35422b8c5fd40b9d5376b9f92a2

[ "Apache-2.0" ]

4

2021-04-09T18:08:36.000Z

2022-03-21T17:51:05.000Z

lib_profiler/datamart_profiler/warning_tools.py

VIDA-NYU/auctus

49e83f9f61f3e35422b8c5fd40b9d5376b9f92a2

[ "Apache-2.0" ]

4

2021-08-12T09:34:29.000Z

2022-01-03T22:30:50.000Z

import contextlib import warnings @contextlib.contextmanager def ignore_warnings(*categories): """Context manager to ignore specific warning categories. """ orig_showarning = warnings.showwarning def record(message, category, filename, lineno, file=None, line=None): if not any(issubclass(category, c) for c in categories): orig_showarning(message, category, filename, lineno, file, line) try: warnings.showwarning = record yield finally: warnings.showwarning = orig_showarning @contextlib.contextmanager def raise_warnings(*categories): orig_showarning = warnings.showwarning def record(message, category, filename, lineno, file=None, line=None): if any(issubclass(category, c) for c in categories): raise category(message) orig_showarning(message, category, filename, lineno, file, line) try: warnings.showwarning = record yield finally: warnings.showwarning = orig_showarning

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py

Python

ScienceDynamics/config/__init__.py

data4goodlab/ScienceDynamics

1ba24a7a0ec64058b6095541b0ecc5d5d294b588

[ "MIT" ]

1

2020-09-29T15:41:58.000Z

ScienceDynamics/config/__init__.py

data4goodlab/ScienceDynamics

1ba24a7a0ec64058b6095541b0ecc5d5d294b588

[ "MIT" ]

null

ScienceDynamics/config/__init__.py

data4goodlab/ScienceDynamics

1ba24a7a0ec64058b6095541b0ecc5d5d294b588

[ "MIT" ]

1

2020-11-12T18:15:25.000Z

from ScienceDynamics.config.configs import *

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0.863636

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7.6

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0

0.068182

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1

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0.926829

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null

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1

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1

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1

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6

8359d18eed3e7f9abeb56933d54bde94d62ba630

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py

Python

Core/hippoSeg/__init__.py

YongLiuLab/BrainRadiomicsTools

19b440acd554ee920857c306442b6d2c411dca88

[ "Apache-2.0", "BSD-3-Clause" ]

10

2019-09-26T03:12:52.000Z

2022-02-25T06:05:38.000Z

Core/hippoSeg/__init__.py

YongLiuLab/BrainRadiomicsTools

19b440acd554ee920857c306442b6d2c411dca88

[ "Apache-2.0", "BSD-3-Clause" ]

null

Core/hippoSeg/__init__.py

YongLiuLab/BrainRadiomicsTools

19b440acd554ee920857c306442b6d2c411dca88

[ "Apache-2.0", "BSD-3-Clause" ]

8

2020-02-26T01:54:48.000Z

2022-03-19T01:23:55.000Z

from .segment import segment

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1

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6

55eee2625b86dfb724e69a47dbfde363fc1f251c

77

py

Python

slack_messages/__init__.py

joegasewicz/slack-messages

2bddb04306ba333209e38b1ff8e2247c3190e921

[ "MIT" ]

1

2021-06-17T18:40:45.000Z

slack_messages/__init__.py

joegasewicz/slack-messages

2bddb04306ba333209e38b1ff8e2247c3190e921

[ "MIT" ]

null

slack_messages/__init__.py

joegasewicz/slack-messages

2bddb04306ba333209e38b1ff8e2247c3190e921

[ "MIT" ]

null

from .slack import SlackMessages, ErrorPostingMessage, ErrorFetchingChannels

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1

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6

360f5d30e9e93c28f61b152a676dc09deb292ddf

28

py

Python

src/amuse/community/mesa/__init__.py

sibonyves/amuse

5557bf88d14df1aa02133a199b6d60c0c57dcab7

[ "Apache-2.0" ]

null

src/amuse/community/mesa/__init__.py

sibonyves/amuse

5557bf88d14df1aa02133a199b6d60c0c57dcab7

[ "Apache-2.0" ]

12

2021-11-15T09:13:03.000Z

2022-02-02T14:53:04.000Z

src/amuse/community/mesa/__init__.py

sibonyves/amuse

5557bf88d14df1aa02133a199b6d60c0c57dcab7

[ "Apache-2.0" ]

null

from .interface import Mesa

14

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null

0

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366e9336a889a39e8206a36b4afe4a8b9923eb01

176

py

Python

pyobs/comm/xmpp/xep_0009_timeout/__init__.py

pyobs/pyobs-core

e3401e63eb31587c2bc535f7346b7e4ef69d64ab

[ "MIT" ]

4

2020-02-14T10:50:03.000Z

2022-03-25T04:15:06.000Z

pyobs/comm/xmpp/xep_0009_timeout/__init__.py

pyobs/pyobs-core

e3401e63eb31587c2bc535f7346b7e4ef69d64ab

[ "MIT" ]

60

2020-09-14T09:10:20.000Z

2022-03-25T17:51:42.000Z

pyobs/comm/xmpp/xep_0009_timeout/__init__.py

pyobs/pyobs-core

e3401e63eb31587c2bc535f7346b7e4ef69d64ab

[ "MIT" ]

2

2020-10-14T09:34:57.000Z

2021-04-27T09:35:57.000Z

from sleekxmpp.plugins.base import register_plugin from . import stanza from .rpc import XEP_0009_timeout from .stanza import MethodTimeout register_plugin(XEP_0009_timeout)

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1

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6

367f2b20efff13ac34a4228d9835b126c85413e9

127

py

Python

boa3_test/test_sc/interop_test/runtime/NotifySequence.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

25

2020-07-22T19:37:43.000Z

2022-03-08T03:23:55.000Z

boa3_test/test_sc/interop_test/runtime/NotifySequence.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

419

2020-04-23T17:48:14.000Z

2022-03-31T13:17:45.000Z

boa3_test/test_sc/interop_test/runtime/NotifySequence.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

15

2020-05-21T21:54:24.000Z

2021-11-18T06:17:24.000Z

from boa3.builtin import public from boa3.builtin.interop.runtime import notify @public def Main(): notify([2, 3, 5, 7])

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127

7

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0

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1

0

1

0

6

36a94f48d3d663af6598b5688f94f57356538261

4,954

py

Python

tests/test_normal_means_scaled.py

banskt/mr-ash-pen

a9e574f66ce64265bff22cf0661d23a5706e4515

[ "MIT" ]

null

tests/test_normal_means_scaled.py

banskt/mr-ash-pen

a9e574f66ce64265bff22cf0661d23a5706e4515

[ "MIT" ]

null

tests/test_normal_means_scaled.py

banskt/mr-ash-pen

a9e574f66ce64265bff22cf0661d23a5706e4515

[ "MIT" ]

null

import unittest import numpy as np from mrashpen.models.normal_means_ash_scaled import NormalMeansASHScaled from mrashpen.utils.logs import MyLogger mlogger = MyLogger(__name__) class TestNMAshScaled(unittest.TestCase): def _NM_data(self): n = 100 s = 1.2 k = 6 np.random.seed(100) y = np.random.normal(0, 1, size = n) X = np.random.normal(0, 1, size = (n, 2000)) d = np.sum(np.square(X), axis = 1) wk = np.zeros(k) wk[1:(k-1)] = np.repeat(1/(k-1), (k - 2)) wk[k-1] = 1 - np.sum(wk) sk = np.arange(k) return y, s, wk, sk, d def test_NM_logML_derivative(self, eps = 1e-8): mlogger.info("Check derivatives of Normal Means logML (scaled prior)") y, s, wk, sk, dj = self._NM_data() nmash = NormalMeansASHScaled(y, s, wk, sk, d = dj) nmash_eps = NormalMeansASHScaled(y + eps, s, wk, sk, d = dj) deriv_analytic = nmash.logML_deriv deriv_numeric = (nmash_eps.logML - nmash.logML) / eps self.assertTrue(np.allclose(deriv_analytic, deriv_numeric, atol = 1e-8, rtol = 1e-4), msg = "Normal Means logML derivative does not match numeric results (scaled prior)") return def test_NM_logML_derivative2(self, eps = 1e-8): mlogger.info("Check second derivatives of Normal Means logML (scaled prior)") y, s, wk, sk, dj = self._NM_data() nmash = NormalMeansASHScaled(y, s, wk, sk, d = dj) nmash_eps = NormalMeansASHScaled(y + eps, s, wk, sk, d = dj) deriv_analytic = nmash.logML_deriv2 deriv_numeric = (nmash_eps.logML_deriv - nmash.logML_deriv) / eps self.assertTrue(np.allclose(deriv_analytic, deriv_numeric, atol = 1e-8, rtol = 1e-4), msg = "Normal Means logML second derivative does not match numeric results (scaled prior)") return def test_NM_logML_wderiv(self, eps = 1e-8): mlogger.info("Check derivatives of Normal Means logML with respect to w_k (scaled prior)") y, s, wk, sk, dj = self._NM_data() nmash = NormalMeansASHScaled(y, s, wk, sk, d = dj) for i in range(wk.shape[0]): wkeps = wk.copy() wkeps[i] += eps nmash_eps = NormalMeansASHScaled(y, s, wkeps, sk, d = dj) deriv_analytic = nmash.logML_wderiv[:, i] deriv_numeric = (nmash_eps.logML - nmash.logML) / eps self.assertTrue(np.allclose(deriv_analytic, deriv_numeric, atol = 1e-6, rtol = 1e-5), msg = f"Normal Means logML derivative with respect to w_k does not match numeric results (scaled prior) for k = {i}") return def test_NM_logML_deriv_wderiv(self, eps = 1e-8): mlogger.info("Check derivatives of Normal Means logML' with respect to w_k (scaled prior)") y, s, wk, sk, dj = self._NM_data() nmash = NormalMeansASHScaled(y, s, wk, sk, d = dj) for i in range(wk.shape[0]): wkeps = wk.copy() wkeps[i] += eps nmash_eps = NormalMeansASHScaled(y, s, wkeps, sk, d = dj) deriv_analytic = nmash.logML_deriv_wderiv[:, i] deriv_numeric = (nmash_eps.logML_deriv - nmash.logML_deriv) / eps self.assertTrue(np.allclose(deriv_analytic, deriv_numeric, atol = 1e-6, rtol = 1e-5), msg = f"Normal Means logML' derivative with respect to w_k does not match numeric results (scaled prior) for k = {i}") return def test_NM_logML_s2deriv(self, eps = 1e-8): mlogger.info("Check derivatives of Normal Means logML with respect to s^2 (scaled prior)") y, s, wk, sk, dj = self._NM_data() nmash = NormalMeansASHScaled(y, s, wk, sk, d = dj) nmash_eps = NormalMeansASHScaled(y, s, wk, sk, d = dj) nmash_eps.set_s2_eps(eps) deriv_analytic = nmash.logML_s2deriv deriv_numeric = (nmash_eps.logML - nmash.logML) / eps self.assertTrue(np.allclose(deriv_analytic, deriv_numeric), msg = "Normal Means logML derivative with respect to s^2 does not match numeric results (scaled prior)") return def test_NM_logML_deriv_s2deriv(self, eps = 1e-8): mlogger.info("Check derivatives of Normal Means logML' with respect to s^2 (scaled prior)") y, s, wk, sk, dj = self._NM_data() nmash = NormalMeansASHScaled(y, s, wk, sk, d = dj) nmash_eps = NormalMeansASHScaled(y, s, wk, sk, d = dj) nmash_eps.set_s2_eps(eps) deriv_analytic = nmash.logML_deriv_s2deriv deriv_numeric = (nmash_eps.logML_deriv - nmash.logML_deriv) / eps self.assertTrue(np.allclose(deriv_analytic, deriv_numeric), msg = "Normal Means logML' derivative with respect to s^2 does not match numeric results (scaled prior)") return if __name__ == '__main__': unittest.main()

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4.211731

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107

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0

null

0

1

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null

0

6

36fc913eb639f075c8664b28591690fe44372235

5,277

py

Python

tests/helpers/test_secure_boot_helper.py

keaparrot/secbootctl

a624677a8987023a3a55d7e002c3c980bdd0e0bd

[ "MIT" ]

null

tests/helpers/test_secure_boot_helper.py

keaparrot/secbootctl

a624677a8987023a3a55d7e002c3c980bdd0e0bd

[ "MIT" ]

null

tests/helpers/test_secure_boot_helper.py

keaparrot/secbootctl

a624677a8987023a3a55d7e002c3c980bdd0e0bd

[ "MIT" ]

null

import unittest from pathlib import Path from unittest.mock import MagicMock from unittest.mock import Mock from unittest.mock import patch from secbootctl.env import Env from secbootctl.helpers.secureboot import SecureBootHelper class TestSecureBootHelper(unittest.TestCase): def setUp(self) -> None: self._process_result_mock: Mock = Mock() self._file_path: Path = Path('/tmp/file.efi') self._key_path: Path = Path('/tmp/keys') self._db_key_file_path = self._key_path / (Env.SB_KEY_NAME_DB + '.key') self._db_cert_file_path = self._key_path / (Env.SB_KEY_NAME_DB + '.crt') self._sb_helper: SecureBootHelper = SecureBootHelper(self._key_path) def test_init_it_assigns_key_file_paths(self): self.assertEqual( self._db_key_file_path, self._sb_helper._db_key_file_path ) self.assertEqual( self._db_cert_file_path, self._sb_helper._db_cert_file_path ) @patch('secbootctl.helpers.secureboot.subprocess') def test_sign_file_if_signing_is_successful_it_returns_true(self, subprocess_patch_mock: MagicMock): subprocess_patch_mock.run.return_value = self._process_result_mock self._process_result_mock.configure_mock(returncode=0) self.assertTrue( self._sb_helper.sign_file(self._file_path) ) subprocess_patch_mock.run.assert_called_once_with( [ 'sbsign', f'--key={self._db_key_file_path}', f'--cert={self._db_cert_file_path}', f'--output={self._file_path}', self._file_path ], capture_output=True ) @patch('secbootctl.helpers.secureboot.subprocess') def test_sign_file_if_use_token_and_signing_is_successful_it_returns_true(self, subprocess_patch_mock: MagicMock): subprocess_patch_mock.run.return_value = self._process_result_mock self._process_result_mock.configure_mock(returncode=0) self.assertTrue( self._sb_helper.sign_file(self._file_path, True) ) subprocess_patch_mock.run.assert_called_once_with( [ 'sbsign', '--engine=pkcs11', '--key=pkcs11:manufacturer=piv_II;id=%02', f'--cert={self._db_cert_file_path}', f'--output={self._file_path}', self._file_path ], capture_output=True ) @patch('secbootctl.helpers.secureboot.subprocess') def test_sign_file_if_signing_fails_it_returns_false(self, subprocess_patch_mock: MagicMock): subprocess_patch_mock.run.return_value = self._process_result_mock self._process_result_mock.configure_mock(returncode=1) self.assertFalse( self._sb_helper.sign_file(self._file_path) ) subprocess_patch_mock.run.assert_called_once_with( [ 'sbsign', f'--key={self._db_key_file_path}', f'--cert={self._db_cert_file_path}', f'--output={self._file_path}', self._file_path ], capture_output=True ) @patch('secbootctl.helpers.secureboot.subprocess') def test_sign_file_if_use_token_and_signing_fails_it_returns_false(self, subprocess_patch_mock: MagicMock): subprocess_patch_mock.run.return_value = self._process_result_mock self._process_result_mock.configure_mock(returncode=1) self.assertFalse( self._sb_helper.sign_file(self._file_path, True) ) subprocess_patch_mock.run.assert_called_once_with( [ 'sbsign', '--engine=pkcs11', '--key=pkcs11:manufacturer=piv_II;id=%02', f'--cert={self._db_cert_file_path}', f'--output={self._file_path}', self._file_path ], capture_output=True ) @patch('secbootctl.helpers.secureboot.subprocess') def test_sign_file_if_verification_is_successful_it_returns_true(self, subprocess_patch_mock: MagicMock): subprocess_patch_mock.run.return_value = self._process_result_mock self._process_result_mock.configure_mock(returncode=0) self.assertTrue( self._sb_helper.verify_file(self._file_path) ) subprocess_patch_mock.run.assert_called_once_with( [ 'sbverify', f'--cert={self._db_cert_file_path}', self._file_path ], capture_output=True ) @patch('secbootctl.helpers.secureboot.subprocess') def test_sign_file_if_verifications_fails_it_returns_false(self, subprocess_patch_mock: MagicMock): subprocess_patch_mock.run.return_value = self._process_result_mock self._process_result_mock.configure_mock(returncode=1) self.assertFalse( self._sb_helper.verify_file(self._file_path) ) subprocess_patch_mock.run.assert_called_once_with( [ 'sbverify', f'--cert={self._db_cert_file_path}', self._file_path ], capture_output=True ) if __name__ == '__main__': unittest.main()

36.393103

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null

0

1

0

null

0

6

36fceae17c9c40b722a6e5c6f41fd603d8d2393b

75

py

Python

backend/api/utils.py

NurlykhanKairly/bus-for-everyone

04f57d73ceeeef0e90e969683409ac177f20955b

[ "MIT" ]

null

backend/api/utils.py

NurlykhanKairly/bus-for-everyone

04f57d73ceeeef0e90e969683409ac177f20955b

[ "MIT" ]

null

backend/api/utils.py

NurlykhanKairly/bus-for-everyone

04f57d73ceeeef0e90e969683409ac177f20955b

[ "MIT" ]

1

2021-09-08T04:42:23.000Z

def has_permission(created_by, user): return created_by.id == user.id

18.75

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4.333333

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0.16

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3

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0.5

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1

0

null

0

1

0

1

0

6

7fd4b6e3415c8fd3eafa5138724b4f7a5fe39c59

41

py

Python

daolilb/client/__init__.py

foruy/openflow-docker

6fa8bc3c634ccaf7ad5ab924bf31faf80887fb3a

[ "Apache-2.0" ]

null

daolilb/client/__init__.py

foruy/openflow-docker

6fa8bc3c634ccaf7ad5ab924bf31faf80887fb3a

[ "Apache-2.0" ]

null

daolilb/client/__init__.py

foruy/openflow-docker

6fa8bc3c634ccaf7ad5ab924bf31faf80887fb3a

[ "Apache-2.0" ]

null

from daolicontroller.client.api import *

20.5

40

0.829268

5

41

6.8

1

0

0.097561

41

1

41

0.918919

0

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0

null

0

1

0

1

0

1

0

6

1847cc0fe74496ff75f23469b80d5955537334e8

2,093

py

Python

benchmarks/models/layers.py

SunDoge/octconv

a1ed9f872065a8f765621e231c2419d07fe7e69a

[ "MIT" ]

17

2019-05-01T12:12:49.000Z

2021-08-11T15:17:19.000Z

benchmarks/models/layers.py

SunDoge/octconv

a1ed9f872065a8f765621e231c2419d07fe7e69a

[ "MIT" ]

3

2019-05-15T11:50:13.000Z

2021-05-26T01:45:21.000Z

benchmarks/models/layers.py

SunDoge/octconv

a1ed9f872065a8f765621e231c2419d07fe7e69a

[ "MIT" ]

3

2019-10-30T04:57:22.000Z

2020-12-12T15:28:32.000Z

import torch.nn as nn from octconv import OctConv2d class OctConvBn(nn.Module): def __init__(self, in_channels, out_channels, kernel_size, alpha=0.5, stride=1, padding=0, bias=False, norm_layer=None): super(OctConvBn, self).__init__() if norm_layer is None: norm_layer = nn.BatchNorm2d self.conv = OctConv2d(in_channels, out_channels, kernel_size=kernel_size, alpha=alpha, stride=stride, padding=padding, bias=bias) alpha_out = self.conv.alpha_out self.bn_h = None if alpha_out == 1 else norm_layer(self.conv.out_channels['high']) self.bn_l = None if alpha_out == 0 else norm_layer(self.conv.out_channels['low']) def forward(self, x): out = self.conv(x) x_h, x_l = out if isinstance(out, tuple) else (out, None) x_h = self.bn_h(x_h) x_l = self.bn_l(x_l) if x_l is not None else None return x_h, x_l class OctConvBnAct(nn.Module): def __init__(self, in_channels, out_channels, kernel_size, alpha=0.5, stride=1, padding=0, bias=False, norm_layer=None, activation_layer=None): super(OctConvBnAct, self).__init__() if norm_layer is None: norm_layer = nn.BatchNorm2d if activation_layer is None: activation_layer = nn.ReLU(inplace=True) self.conv = OctConv2d(in_channels, out_channels, kernel_size=kernel_size, alpha=alpha, stride=stride, padding=padding, bias=bias) alpha_out = self.conv.alpha_out self.bn_h = None if alpha_out == 1 else norm_layer(self.conv.out_channels['high']) self.bn_l = None if alpha_out == 0 else norm_layer(self.conv.out_channels['low']) self.act = activation_layer def forward(self, x): out = self.conv(x) x_h, x_l = out if isinstance(out, tuple) else (out, None) x_h = self.act(self.bn_h(x_h)) x_l = self.act(self.bn_l(x_l)) if x_l is not None else None return x_h, x_l if __name__ == '__main__': pass

30.779412

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3.852665

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0

0.243902

0

null

0

1

0

null

0

6

185e869f554d29bc7caba88326432861880e615e

87

py

Python

image_keras/supports/functional/__init__.py

tenkeyless/image-keras

09da179d75bb7a17d76e4fd7456b1667c8b4f62b

[ "MIT" ]

null

image_keras/supports/functional/__init__.py

tenkeyless/image-keras

09da179d75bb7a17d76e4fd7456b1667c8b4f62b

[ "MIT" ]

1

2020-06-18T06:47:32.000Z

common_py/functional/__init__.py

tenkeyless/common_py

fae49f038dacecef468a5c0972fdbe0d6a5a66b9

[ "MIT" ]

null

from .either import * from .future import * from .monad import * from .option import *

17.4

21

0.724138

12

87

5.25

0.5

0.47619

0

0.183908

87

4

22

21.75

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0

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true

0

1

0

1

0

1

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1

0

1

0

null

0

1

0

1

0

1

0

6

1881e51f643bba5d063f0ce1b3e4401fca981cb1

202

py

Python

app/widget/__init__.py

HansBug/dgdvapp

f3142d2c265afda427bbeee46c8073e1126eeef5

[ "Apache-2.0" ]

null

app/widget/__init__.py

HansBug/dgdvapp

f3142d2c265afda427bbeee46c8073e1126eeef5

[ "Apache-2.0" ]

null

app/widget/__init__.py

HansBug/dgdvapp

f3142d2c265afda427bbeee46c8073e1126eeef5

[ "Apache-2.0" ]

null

from .dialog_config import DialogConfig from .form_generate import FormGenerate from .form_log_process import FormLogProcess from .form_metrics import FormMetrics from .main_window import AppMainWindow

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43f09c545710d449af81791e0d46921fd9bf872f

221

py

Python

physics/error.py

dwahme/physics_calc_enabler

f0fc4c9214cd024344c5f0d3684b29666339395e

[ "MIT" ]

null

physics/error.py

dwahme/physics_calc_enabler

f0fc4c9214cd024344c5f0d3684b29666339395e

[ "MIT" ]

1

2018-12-31T17:49:59.000Z

physics/error.py

dwahme/physics_calc_enabler

f0fc4c9214cd024344c5f0d3684b29666339395e

[ "MIT" ]

null

''' A submodule for doing basic error analysis for experimental physics results. ''' def average(values): # TODO: add documentation pass def percent_diff(expected, actual): # TODO: add documentation pass

18.416667

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0.777778

0.089172

0.254777

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221

12

60

18.416667

0.892045

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0.5

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6

a13b27ac35b40c2fe3a4e1cf4063300bf2b1b66b

7,163

py

Python

shade/tests/functional/test_object.py

noironetworks/shade

e46878bae44e7daebf32c0aeaeffea0011542525

[ "Apache-2.0" ]

96

2015-01-29T20:12:08.000Z

2019-01-28T22:17:13.000Z

shade/tests/functional/test_object.py

noironetworks/shade

e46878bae44e7daebf32c0aeaeffea0011542525

[ "Apache-2.0" ]

7

2015-08-14T18:47:28.000Z

2019-02-18T16:32:36.000Z

shade/tests/functional/test_object.py

noironetworks/shade

e46878bae44e7daebf32c0aeaeffea0011542525

[ "Apache-2.0" ]

88

2015-05-11T17:20:52.000Z

2019-04-04T03:23:30.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License 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. """ test_object ---------------------------------- Functional tests for `shade` object methods. """ import random import string import tempfile from testtools import content from shade import exc from shade.tests.functional import base class TestObject(base.BaseFunctionalTestCase): def setUp(self): super(TestObject, self).setUp() if not self.user_cloud.has_service('object-store'): self.skipTest('Object service not supported by cloud') def test_create_object(self): '''Test uploading small and large files.''' container_name = self.getUniqueString('container') self.addDetail('container', content.text_content(container_name)) self.addCleanup(self.user_cloud.delete_container, container_name) self.user_cloud.create_container(container_name) self.assertEqual(container_name, self.user_cloud.list_containers()[0]['name']) sizes = ( (64 * 1024, 1), # 64K, one segment (64 * 1024, 5) # 64MB, 5 segments ) for size, nseg in sizes: segment_size = int(round(size / nseg)) with tempfile.NamedTemporaryFile() as fake_file: fake_content = ''.join(random.SystemRandom().choice( string.ascii_uppercase + string.digits) for _ in range(size)).encode('latin-1') fake_file.write(fake_content) fake_file.flush() name = 'test-%d' % size self.addCleanup( self.user_cloud.delete_object, container_name, name) self.user_cloud.create_object( container_name, name, fake_file.name, segment_size=segment_size, metadata={'foo': 'bar'}) self.assertFalse(self.user_cloud.is_object_stale( container_name, name, fake_file.name )) self.assertEqual( 'bar', self.user_cloud.get_object_metadata( container_name, name)['x-object-meta-foo'] ) self.user_cloud.update_object(container=container_name, name=name, metadata={'testk': 'testv'}) self.assertEqual( 'testv', self.user_cloud.get_object_metadata( container_name, name)['x-object-meta-testk'] ) try: self.assertIsNotNone( self.user_cloud.get_object(container_name, name)) except exc.OpenStackCloudException as e: self.addDetail( 'failed_response', content.text_content(str(e.response.headers))) self.addDetail( 'failed_response', content.text_content(e.response.text)) self.assertEqual( name, self.user_cloud.list_objects(container_name)[0]['name']) self.assertTrue( self.user_cloud.delete_object(container_name, name)) self.assertEqual([], self.user_cloud.list_objects(container_name)) self.assertEqual(container_name, self.user_cloud.list_containers()[0]['name']) self.user_cloud.delete_container(container_name) def test_download_object_to_file(self): '''Test uploading small and large files.''' container_name = self.getUniqueString('container') self.addDetail('container', content.text_content(container_name)) self.addCleanup(self.user_cloud.delete_container, container_name) self.user_cloud.create_container(container_name) self.assertEqual(container_name, self.user_cloud.list_containers()[0]['name']) sizes = ( (64 * 1024, 1), # 64K, one segment (64 * 1024, 5) # 64MB, 5 segments ) for size, nseg in sizes: fake_content = '' segment_size = int(round(size / nseg)) with tempfile.NamedTemporaryFile() as fake_file: fake_content = ''.join(random.SystemRandom().choice( string.ascii_uppercase + string.digits) for _ in range(size)).encode('latin-1') fake_file.write(fake_content) fake_file.flush() name = 'test-%d' % size self.addCleanup( self.user_cloud.delete_object, container_name, name) self.user_cloud.create_object( container_name, name, fake_file.name, segment_size=segment_size, metadata={'foo': 'bar'}) self.assertFalse(self.user_cloud.is_object_stale( container_name, name, fake_file.name )) self.assertEqual( 'bar', self.user_cloud.get_object_metadata( container_name, name)['x-object-meta-foo'] ) self.user_cloud.update_object(container=container_name, name=name, metadata={'testk': 'testv'}) self.assertEqual( 'testv', self.user_cloud.get_object_metadata( container_name, name)['x-object-meta-testk'] ) try: with tempfile.NamedTemporaryFile() as fake_file: self.user_cloud.get_object( container_name, name, outfile=fake_file.name) downloaded_content = open(fake_file.name, 'rb').read() self.assertEqual(fake_content, downloaded_content) except exc.OpenStackCloudException as e: self.addDetail( 'failed_response', content.text_content(str(e.response.headers))) self.addDetail( 'failed_response', content.text_content(e.response.text)) raise self.assertEqual( name, self.user_cloud.list_objects(container_name)[0]['name']) self.assertTrue( self.user_cloud.delete_object(container_name, name)) self.assertEqual([], self.user_cloud.list_objects(container_name)) self.assertEqual(container_name, self.user_cloud.list_containers()[0]['name']) self.user_cloud.delete_container(container_name)

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78

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null

0

1

0

1

0

null

0

6

a173108006ddc214ef88d92d7434f67d2c9d5464

766

py

Python

component/mobility.py

sagelga/covid-vaccine

8484393f001b31ef1bc3fb07246f6cfa33c18ee9

[ "MIT" ]

null

component/mobility.py

sagelga/covid-vaccine

8484393f001b31ef1bc3fb07246f6cfa33c18ee9

[ "MIT" ]

31

2021-03-23T08:19:55.000Z

2021-04-28T05:33:47.000Z

component/mobility.py

sagelga/covid-vaccine

8484393f001b31ef1bc3fb07246f6cfa33c18ee9

[ "MIT" ]

null

import pandas as pd def get_aapl_df(): url = 'https://raw.githubusercontent.com/ActiveConclusion/COVID19_mobility/master/apple_reports/apple_mobility_report.csv' df = pd.read_csv(url) return df def get_goog_df(): url = 'https://raw.githubusercontent.com/ActiveConclusion/COVID19_mobility/master/google_reports/mobility_report_countries.csv' df = pd.read_csv(url) return df def get_waze_df(): url = 'https://raw.githubusercontent.com/ActiveConclusion/COVID19_mobility/master/waze_reports/waze_mobility.csv' df = pd.read_csv(url) return df def get_tom_df(): url = 'https://raw.githubusercontent.com/ActiveConclusion/COVID19_mobility/master/tomtom_reports/tomtom_trafic_index.csv' df = pd.read_csv(url) return df

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0.012012

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766

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null

0

1

0

1

0

6

a1790a9de1a01844b6041ed2768afbe0185f00c5

92

py

Python

office365/sharepoint/fields/field_thumbnail.py

rikeshtailor/Office365-REST-Python-Client

ca7bfa1b22212137bb4e984c0457632163e89a43

[ "MIT" ]

544

2016-08-04T17:10:16.000Z

2022-03-31T07:17:20.000Z

office365/sharepoint/fields/field_thumbnail.py

rikeshtailor/Office365-REST-Python-Client

ca7bfa1b22212137bb4e984c0457632163e89a43

[ "MIT" ]

438

2016-10-11T12:24:22.000Z

2022-03-31T19:30:35.000Z

office365/sharepoint/fields/field_thumbnail.py

rikeshtailor/Office365-REST-Python-Client

ca7bfa1b22212137bb4e984c0457632163e89a43

[ "MIT" ]

202

2016-08-22T19:29:40.000Z

2022-03-30T20:26:15.000Z

from office365.sharepoint.fields.field import Field class FieldThumbnail(Field): pass

15.333333

51

0.793478

11

92

6.636364

0.818182

0

0.037975

0.141304

92

5

52

18.4

0.886076

0

1

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true

0.333333

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null

0

1

0

1

0

6

a1980d4135bf4d30710bd2b262964a71bba8f43f

1,014

py

Python

flexmeasures/ui/views/__init__.py

FlexMeasures/flexmeasures

a4367976d37ac5721b8eb3ce8a2414595e52c678

[ "Apache-2.0" ]

12

2021-12-18T10:41:10.000Z

2022-03-29T23:00:29.000Z

flexmeasures/ui/views/__init__.py

FlexMeasures/flexmeasures

a4367976d37ac5721b8eb3ce8a2414595e52c678

[ "Apache-2.0" ]

103

2021-12-07T08:51:15.000Z

2022-03-31T13:28:48.000Z

flexmeasures/ui/views/__init__.py

FlexMeasures/flexmeasures

a4367976d37ac5721b8eb3ce8a2414595e52c678

[ "Apache-2.0" ]

3

2022-01-18T04:45:48.000Z

2022-03-14T09:48:22.000Z

"""This module hosts the views. This file registers blueprints and hosts some helpful functions""" from flexmeasures.ui import flexmeasures_ui # Now views can register from flexmeasures.ui.views.dashboard import ( # noqa: F401 dashboard_view as legacy_dashboard_view, ) from flexmeasures.ui.views.new_dashboard import new_dashboard_view # noqa: F401 from flexmeasures.ui.views.portfolio import portfolio_view # noqa: F401 from flexmeasures.ui.views.control import control_view # noqa: F401 from flexmeasures.ui.views.analytics import analytics_view # noqa: F401 from flexmeasures.ui.views.state import sensor_state_view # noqa: F401 from flexmeasures.ui.views.logged_in_user import ( # noqa: F401 # noqa: F401 logged_in_user_view, ) from flexmeasures.ui.views.charts import get_power_chart # noqa: F401 @flexmeasures_ui.route("/docs") def docs_view(): """Render the Sphinx documentation""" # Todo: render the docs with this nicer url and include the app's navigation menu return

37.555556

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1,014

5.317241

0.372414

0.199741

0.210117

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0.143984

1,014

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99

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true

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null

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1

0

1

0

1

0

1

0

6

a1a2e9ca174a49c4b21843591f98cd0f5c868ae3

108

py

Python

tests/exog/random/random_exog_150_320.py

jmabry/pyaf

afbc15a851a2445a7824bf255af612dc429265af

[ "BSD-3-Clause" ]

null

tests/exog/random/random_exog_150_320.py

jmabry/pyaf

afbc15a851a2445a7824bf255af612dc429265af

[ "BSD-3-Clause" ]

1

2019-11-30T23:39:38.000Z

2019-12-01T04:34:35.000Z

tests/exog/random/random_exog_150_320.py

jmabry/pyaf

afbc15a851a2445a7824bf255af612dc429265af

[ "BSD-3-Clause" ]

null

import pyaf.tests.exog.test_random_exogenous as testrandexog testrandexog.test_random_exogenous( 150,320);

27

60

0.861111

15

108

5.933333

0.733333

0.224719

0.426966

0

0.059406

0.064815

108

4

61

27

0.821782

0

1

0

true

0

0.5

0

0.5

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0

null

1

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1

0

null

0

1

0

1

0

6

a1cbb13f0d829f5ecbc5ad9ac3d3f1eb4f555da7

5,772

py

Python

raiden_contracts/utils/sign.py

konradkonrad/raiden-contracts

5726f744e8d7e80f7ca61401bd3f1084de57e30c

[ "MIT" ]

null

raiden_contracts/utils/sign.py

konradkonrad/raiden-contracts

5726f744e8d7e80f7ca61401bd3f1084de57e30c

[ "MIT" ]

null

raiden_contracts/utils/sign.py

konradkonrad/raiden-contracts

5726f744e8d7e80f7ca61401bd3f1084de57e30c

[ "MIT" ]

null

from web3 import Web3 from eth_abi import encode_single from .sign_utils import sign from raiden_contracts.constants import MessageTypeId def hash_balance_data(transferred_amount, locked_amount, locksroot): return Web3.soliditySha3( ['uint256', 'uint256', 'bytes32'], [transferred_amount, locked_amount, locksroot], ) def eth_sign_hash_message(encoded_message): signature_prefix = '\x19Ethereum Signed Message:\n' return Web3.sha3( Web3.toBytes(text=signature_prefix) + Web3.toBytes(text=str(len(encoded_message))) + encoded_message, ) def hash_balance_proof( token_network_address, chain_identifier, channel_identifier, balance_hash, nonce, additional_hash, ): return eth_sign_hash_message( Web3.toBytes(hexstr=token_network_address) + encode_single('uint256', chain_identifier) + encode_single('uint256', MessageTypeId.BALANCE_PROOF) + encode_single('uint256', channel_identifier) + balance_hash + encode_single('uint256', nonce) + additional_hash, ) def hash_balance_proof_update_message( token_network_address, chain_identifier, channel_identifier, balance_hash, nonce, additional_hash, closing_signature, ): return eth_sign_hash_message( Web3.toBytes(hexstr=token_network_address) + encode_single('uint256', chain_identifier) + encode_single('uint256', MessageTypeId.BALANCE_PROOF_UPDATE) + encode_single('uint256', channel_identifier) + balance_hash + encode_single('uint256', nonce) + additional_hash + closing_signature, ) def hash_cooperative_settle_message( token_network_address, chain_identifier, channel_identifier, participant1_address, participant1_balance, participant2_address, participant2_balance, ): return eth_sign_hash_message( Web3.toBytes(hexstr=token_network_address) + encode_single('uint256', chain_identifier) + encode_single('uint256', MessageTypeId.COOPERATIVE_SETTLE) + encode_single('uint256', channel_identifier) + Web3.toBytes(hexstr=participant1_address) + encode_single('uint256', participant1_balance) + Web3.toBytes(hexstr=participant2_address) + encode_single('uint256', participant2_balance), ) def hash_withdraw_message( token_network_address, chain_identifier, channel_identifier, participant, amount_to_withdraw, ): return eth_sign_hash_message( Web3.toBytes(hexstr=token_network_address) + encode_single('uint256', chain_identifier) + encode_single('uint256', MessageTypeId.WITHDRAW) + encode_single('uint256', channel_identifier) + Web3.toBytes(hexstr=participant) + encode_single('uint256', amount_to_withdraw), ) def hash_reward_proof( channel_identifier, reward_amount, token_network_address, chain_id, nonce): return Web3.soliditySha3([ 'uint256', 'uint256', 'address', 'uint256', 'uint256', ], [ channel_identifier, reward_amount, token_network_address, chain_id, nonce, ]) def sign_balance_proof( privatekey, token_network_address, chain_identifier, channel_identifier, balance_hash, nonce, additional_hash, v=27, ): message_hash = hash_balance_proof( token_network_address, chain_identifier, channel_identifier, balance_hash, nonce, additional_hash, ) return sign(privatekey, message_hash, v) def sign_balance_proof_update_message( privatekey, token_network_address, chain_identifier, channel_identifier, balance_hash, nonce, additional_hash, closing_signature, v=27, ): message_hash = hash_balance_proof_update_message( token_network_address, chain_identifier, channel_identifier, balance_hash, nonce, additional_hash, closing_signature, ) return sign(privatekey, message_hash, v) def sign_cooperative_settle_message( privatekey, token_network_address, chain_identifier, channel_identifier, participant1_address, participant1_balance, participant2_address, participant2_balance, v=27, ): message_hash = hash_cooperative_settle_message( token_network_address, chain_identifier, channel_identifier, participant1_address, participant1_balance, participant2_address, participant2_balance, ) return sign(privatekey, message_hash, v) def sign_withdraw_message( privatekey, token_network_address, chain_identifier, channel_identifier, participant, amount_to_withdraw, v=27, ): message_hash = hash_withdraw_message( token_network_address, chain_identifier, channel_identifier, participant, amount_to_withdraw, ) return sign(privatekey, message_hash, v) def sign_reward_proof( privatekey, channel_identifier, reward_amount, token_network_address, chain_id, nonce, v=27): message_hash = hash_reward_proof( channel_identifier, reward_amount, token_network_address, chain_id, nonce, ) return sign(privatekey, message_hash, v)

25.20524

70

0.650381

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0.108905

0.819626

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0.680091

0.668463

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0.279799

5,772

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0.060302

false

0

0.020101

0.030151

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null

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1

0

1

0

1

0

null

0

6

a1ffd68b70a3e94d90d0db934d5b68551327d1d5

1,597

py

Python

tests/test_tuple_strategy.py

stortiz-lifeworks/chili

958adf88de6df995d9216b9dcf3c11f3e6885485

[ "MIT" ]

4

2021-10-01T09:50:47.000Z

2022-02-03T05:43:04.000Z

tests/test_tuple_strategy.py

stortiz-lifeworks/chili

958adf88de6df995d9216b9dcf3c11f3e6885485

[ "MIT" ]

5

2021-10-01T08:11:33.000Z

2021-12-13T18:33:37.000Z

tests/test_tuple_strategy.py

stortiz-lifeworks/chili

958adf88de6df995d9216b9dcf3c11f3e6885485

[ "MIT" ]

null

from typing import Tuple from chili import registry def test_hydrate_generic_tuple() -> None: # given strategy = registry.get_for(tuple) items = ["a", 1, 2.1, True] # when hydrated_items = strategy.hydrate(items) # then assert hydrated_items == ("a", 1, 2.1, True) def test_hydrate_typed_tuple() -> None: # given strategy = registry.get_for(Tuple[str, int, str, int]) items = ["a", 1, 2.1, True] # when hydrated_items = strategy.hydrate(items) # then assert hydrated_items == ("a", 1, "2.1", 1) def test_hydrate_ellipsis_tuple() -> None: # given strategy = registry.get_for(Tuple[str, ...]) items = ["a", 1, 2.1, True] # when hydrated_items = strategy.hydrate(items) # then assert hydrated_items == ("a", "1", "2.1", "True") def test_extract_simple_tuple() -> None: # given strategy = registry.get_for(tuple) items = ("a", 1, 2.1, True) # when extracted_items = strategy.extract(items) # then assert extracted_items == ["a", 1, 2.1, True] def test_extract_typed_tuple() -> None: # given strategy = registry.get_for(Tuple[str, int, str, int]) items = ("a", 1, 2.1, True) # when extracted_items = strategy.extract(items) # then assert extracted_items == ["a", 1, "2.1", 1] def test_extract_ellipsis_tuple() -> None: # given strategy = registry.get_for(Tuple[str, ...]) items = ("a", 1, 2.1, True) # when extracted_items = strategy.extract(items) # then assert extracted_items == ["a", "1", "2.1", "True"]

20.74026

58

0.604258

216

1,597

4.300926

0.143519

0.077503

0.09042

0.103337

0.900969

0.883746

0.861141

0

0.031327

0.240451

1,597

76

59

21.013158

0.734542

0.059487

0

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0

0.022927

0

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1

0.1875

false

0

0.0625

0

0.25

0

null

0

1

0

null

0

6

62d1d043177ddc1afdb37ce3d016cae78eb3bfe0

2,271

py

Python

photo_album_server/photos/migrations/0001_initial.py

Pu-Yongjun/photo-album

6ba662c243802e53b5df5548a36c27cc31c5cede

[ "Apache-2.0" ]

1

2020-12-11T05:46:37.000Z

photo_album_server/photos/migrations/0001_initial.py

Pu-Yongjun/photo-album

6ba662c243802e53b5df5548a36c27cc31c5cede

[ "Apache-2.0" ]

19

2020-06-05T19:51:11.000Z

2022-03-11T23:44:47.000Z

photo_album_server/photos/migrations/0001_initial.py

parker-pu/photo-album

6ba662c243802e53b5df5548a36c27cc31c5cede

[ "Apache-2.0" ]

null

# Generated by Django 2.1.5 on 2019-01-20 12:29 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='PhotoCacheModel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.TextField(verbose_name='图片名称')), ('describe', models.TextField(verbose_name='图片描述')), ('photo_url', models.TextField(verbose_name='图片的路径')), ('thumbnail', models.ImageField(upload_to='static/data/images/cache', verbose_name='缩略图')), ('insert_time', models.DateTimeField(auto_now=True, verbose_name='插入时间')), ('update_time', models.DateTimeField(auto_now=True, verbose_name='更新时间')), ('user', models.ForeignKey(default='', on_delete=django.db.models.deletion.CASCADE, related_name='cuser', to=settings.AUTH_USER_MODEL, verbose_name='用户')), ], options={ 'db_table': 'photo_cache', }, ), migrations.CreateModel( name='PhotoModel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.TextField(verbose_name='图片名称')), ('describe', models.TextField(verbose_name='图片描述')), ('photo_url', models.TextField(verbose_name='图片的路径')), ('thumbnail', models.ImageField(upload_to='static/user_img', verbose_name='缩略图')), ('insert_time', models.DateTimeField(auto_now=True, verbose_name='插入时间')), ('update_time', models.DateTimeField(auto_now=True, verbose_name='更新时间')), ('user', models.ForeignKey(default='', on_delete=django.db.models.deletion.CASCADE, related_name='user', to=settings.AUTH_USER_MODEL, verbose_name='用户')), ], options={ 'db_table': 'photo', }, ), ]

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0.600616

235

2,271

5.604255

0.331915

0.133637

0.100228

0.118451

0.733485

0

0.008855

0.254073

2,271

49

172

46.346939

0.768595

0.019815

0

0.52381

1

0

0.12455

0.010791

0

1

0

false

0

0.071429

0

0.166667

0

null

0

1

0

1

0

null

0

6

62d7ed0ea5dcd7bc76928b29927c0ebb86b865a9

19,760

py

Python

main.py

marjanin/G2P_with_fb

683aa5af45f37a7ac8537ce097ccc91c422c80ba

[ "MIT" ]

null

main.py

marjanin/G2P_with_fb

683aa5af45f37a7ac8537ce097ccc91c422c80ba

[ "MIT" ]

null

main.py

marjanin/G2P_with_fb

683aa5af45f37a7ac8537ce097ccc91c422c80ba

[ "MIT" ]

null

import numpy as np import pandas as pd from matplotlib import pyplot as plt import pickle from warnings import simplefilter from all_functions import * from feedback_functions import * simplefilter(action='ignore', category=FutureWarning) # np.random.seed(0) # [babbling_kinematics, babbling_activations] = babbling_fcn(simulation_minutes=5) # model = inverse_mapping_fcn(kinematics=babbling_kinematics, activations=babbling_activations) # cum_kinematics = babbling_kinematics # cum_activations = babbling_activations # pickle.dump([model,cum_kinematics, cum_activations],open("results/mlp_model.sav", 'wb')) [model,cum_kinematics, cum_activations] = pickle.load(open("results/mlp_model.sav", 'rb')) # loading the model P = np.array([10, 15]) I = np.array([2, 6]) np.random.seed(0) experiments_switch = np.zeros(11,) # sets which experiments should run #np.zeros(10,)#[0, 0, 0, 1, 0, 0, 0, 0, 0, 1] #experiments_switch[4]=1 trial_number = 1 plot_outputs = True Mj_render = False for ii in range(len(experiments_switch)): globals()["exp{}_average_error".format(ii+1)]=np.zeros([2,1]) exp6_average_error = np.zeros([3,1]) exp7_average_error = np.zeros([3,1]) exp9_average_error = np.zeros([3,1,1]) exp10_average_error = np.zeros([3,1,1]) if experiments_switch[0] ==1: # as a function of cycle period features=np.ones(10,) cycle_durations = np.array([2.5,2.5])#np.linspace(.5,10,trial_number) test1_no = cycle_durations.shape[0] exp1_average_error = np.zeros([2,test1_no]) # first row open-loop and second row close-loop #cycle length experiment for cycle_duration_in_seconds, ii in zip(cycle_durations, range(test1_no)): [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = cycle_duration_in_seconds, show=False) q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) exp1_average_error[0,ii], _, _ = openloop_run_fcn(model=model, desired_kinematics=desired_kinematics, plot_outputs=plot_outputs, Mj_render=False) exp1_average_error[1,ii], _, _ = closeloop_run_fcn(model=model, desired_kinematics=desired_kinematics, P=P, I=I, plot_outputs=plot_outputs, Mj_render=False) # K = [10, 15] if experiments_switch[1] ==1: # cyclical on air np.random.seed(0) test2_no = trial_number exp2_average_error = np.zeros([2,test2_no]) for ii in range(test2_no): features = np.random.rand(10) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) #import pdb; pdb.set_trace() q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) exp2_average_error[0,ii], _, _ = openloop_run_fcn(model=model, desired_kinematics=desired_kinematics, plot_outputs=plot_outputs, Mj_render=False) exp2_average_error[1,ii], _, _ = closeloop_run_fcn(model=model, desired_kinematics=desired_kinematics, P=P, I=I, plot_outputs=plot_outputs, Mj_render=False) # K = [10, 15] #print("error_without: ", exp2_average_error[0,0], "error with: ", exp2_average_error[1,0]) if experiments_switch[2] ==1: # p2p np.random.seed(0) test3_no = trial_number exp3_average_error = np.zeros([2,test3_no]) for ii in range(test3_no): q0 = p2p_positions_gen_fcn(low=-np.pi/3, high=np.pi/3, number_of_positions=10, duration_of_each_position=2.5, timestep=.005) q1 = p2p_positions_gen_fcn(low=-np.pi/2, high=0, number_of_positions=10, duration_of_each_position=2.5, timestep=.005) desired_kinematics = positions_to_kinematics_fcn(q0, q1, timestep = 0.005) exp3_average_error[0,ii], _, _ = openloop_run_fcn(model=model, desired_kinematics=desired_kinematics, plot_outputs=plot_outputs, Mj_render=False) exp3_average_error[1,ii], _, _ = closeloop_run_fcn(model=model, desired_kinematics=desired_kinematics, P=P, I=I, plot_outputs=plot_outputs, Mj_render=False) # K = [10, 15] if experiments_switch[3] ==1: # standing up against weight test4_no = 1 exp4_average_error = np.zeros([2,test4_no]) q0 = p2p_positions_gen_fcn(low=np.pi/3, high=np.pi/3, number_of_positions=1, duration_of_each_position=1, timestep=.005) q0 = np.append(q0,p2p_positions_gen_fcn(low=0, high=0, number_of_positions=1, duration_of_each_position=6, timestep=.005)) q1 = p2p_positions_gen_fcn(low=-np.pi/2, high=-np.pi/2, number_of_positions=1, duration_of_each_position=1, timestep=.005) q1 = np.append(q1,p2p_positions_gen_fcn(low=0, high=0, number_of_positions=1, duration_of_each_position=6, timestep=.005)) desired_kinematics = positions_to_kinematics_fcn(q0, q1, timestep = 0.005) exp4_average_error[0,:], _, _ = openloop_run_fcn(model=model, desired_kinematics=desired_kinematics, model_ver=3, plot_outputs=plot_outputs, Mj_render=Mj_render) q0 = p2p_positions_gen_fcn(low=np.pi/3, high=np.pi/3, number_of_positions=1, duration_of_each_position=1, timestep=.005) q0 = np.append(q0,p2p_positions_gen_fcn(low=0, high=0, number_of_positions=1, duration_of_each_position=6, timestep=.005)) q1 = p2p_positions_gen_fcn(low=-np.pi/2, high=-np.pi/2, number_of_positions=1, duration_of_each_position=1, timestep=.005) q1 = np.append(q1,p2p_positions_gen_fcn(low=0, high=0, number_of_positions=1, duration_of_each_position=6, timestep=.005)) desired_kinematics = positions_to_kinematics_fcn(q0, q1, timestep = 0.005) exp4_average_error[1,:], _, _ = closeloop_run_fcn(model=model, desired_kinematics=desired_kinematics, P=P, I=I, model_ver=3, plot_outputs=plot_outputs, Mj_render=Mj_render) if experiments_switch[4] == 1: # walking; contact dynamics np.random.seed(0) test5_no = trial_number exp5_average_error = np.zeros([2,test5_no]) for ii in range(test5_no): ########################## features = np.random.rand(10) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) exp5_average_error[0,ii], real_attempt_kinematics_ol, _ = openloop_run_fcn(model=model, desired_kinematics=desired_kinematics, model_ver=2, plot_outputs=plot_outputs, Mj_render=Mj_render) exp5_average_error[1,ii], real_attempt_kinematics_cl, _ = closeloop_run_fcn(model=model, desired_kinematics=desired_kinematics, model_ver=2, P=P, I=I, plot_outputs=plot_outputs, Mj_render=Mj_render) # K = [10, 15] #import pdb; pdb.set_trace() # np.savetxt('./results/withdynamics_desired.csv', desired_kinematics, delimiter=',') # np.savetxt('./results/withdynamics_ol.csv', real_attempt_kinematics_ol, delimiter=',') # np.savetxt('./results/withdynamics_cl.csv', real_attempt_kinematics_cl, delimiter=',') if experiments_switch[5] == 1: # everlearn ones np.random.seed(0) [babbling_kinematics_1min, babbling_activations_1min] = babbling_fcn(simulation_minutes=1) model_1min = inverse_mapping_fcn(kinematics=babbling_kinematics_1min, activations=babbling_activations_1min) cum_kinematics_ol = deepcopy(babbling_kinematics_1min) cum_activations_ol = deepcopy(babbling_activations_1min) exp6_model_ol = deepcopy(model_1min) cum_kinematics_cl = deepcopy(babbling_kinematics_1min) cum_activations_cl = deepcopy(babbling_activations_1min) exp6_model_cl = deepcopy(model_1min) test6_no = trial_number exp6_average_error = np.zeros([3,test6_no]) for ii in range(test6_no): features = np.ones(10,) print(features) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) #1sec also fine q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) exp6_average_error[0,ii], real_attempt_kinematics_ol, real_attempt_activations_ol = openloop_run_fcn(model=exp6_model_ol, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) cum_kinematics_ol, cum_activations_ol = concatinate_data_fcn( cum_kinematics_ol, cum_activations_ol, real_attempt_kinematics_ol, real_attempt_activations_ol, throw_percentage = 0.20) exp6_model_ol = inverse_mapping_fcn(cum_kinematics_ol, cum_activations_ol, prior_model = exp6_model_ol) exp6_average_error[1,ii], real_attempt_kinematics_cl, real_attempt_activations_cl = closeloop_run_fcn(model=exp6_model_cl, desired_kinematics=desired_kinematics, model_ver=0, P=P, I=I, plot_outputs=False, Mj_render=False) exp6_average_error[2,ii], _, _ = openloop_run_fcn(model=exp6_model_cl, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) cum_kinematics_cl, cum_activations_cl = concatinate_data_fcn( cum_kinematics_cl, cum_activations_cl, real_attempt_kinematics_cl, real_attempt_activations_cl, throw_percentage = 0.20) exp6_model_cl = inverse_mapping_fcn(cum_kinematics_cl, cum_activations_cl, prior_model = exp6_model_cl) if experiments_switch[6] == 1: # everlearn random multi np.random.seed(0) [babbling_kinematics_1min, babbling_activations_1min] = babbling_fcn(simulation_minutes=1) model_1min = inverse_mapping_fcn(kinematics=babbling_kinematics_1min, activations=babbling_activations_1min) cum_kinematics_ol = deepcopy(babbling_kinematics_1min) cum_activations_ol = deepcopy(babbling_activations_1min) exp7_model_ol = deepcopy(model_1min) cum_kinematics_cl = deepcopy(babbling_kinematics_1min) cum_activations_cl = deepcopy(babbling_activations_1min) exp7_model_cl = deepcopy(model_1min) test7_no = trial_number exp7_average_error = np.zeros([3,test7_no]) for ii in range(test7_no): print(ii) features = np.random.rand(10) print(features) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) #1sec also fine q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) exp7_average_error[0,ii], real_attempt_kinematics_ol, real_attempt_activations_ol = openloop_run_fcn(model=exp7_model_ol, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) cum_kinematics_ol, cum_activations_ol = concatinate_data_fcn( cum_kinematics_ol, cum_activations_ol, real_attempt_kinematics_ol, real_attempt_activations_ol, throw_percentage = 0.20) exp7_model_ol = inverse_mapping_fcn(cum_kinematics_ol, cum_activations_ol, prior_model = exp7_model_ol) exp7_average_error[1,ii], real_attempt_kinematics_cl, real_attempt_activations_cl = closeloop_run_fcn(model=exp7_model_cl, desired_kinematics=desired_kinematics, model_ver=0, P=P, I=I, plot_outputs=False, Mj_render=False) exp7_average_error[2,ii], _, _ = openloop_run_fcn(model=exp7_model_cl, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) cum_kinematics_cl, cum_activations_cl = concatinate_data_fcn( cum_kinematics_cl, cum_activations_cl, real_attempt_kinematics_cl, real_attempt_activations_cl, throw_percentage = 0.20) exp7_model_cl = inverse_mapping_fcn(cum_kinematics_cl, cum_activations_cl, prior_model = exp7_model_cl) if experiments_switch[7] ==1: # delay np.random.seed(0) test8_no = trial_number all_delays = np.arange(0, 21, 2) exp8_average_error = np.zeros([all_delays.shape[0]+1,test8_no]) for ii in range(test8_no): features = np.random.rand(10) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) #import pdb; pdb.set_trace() q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) for delay_timesteps, jj in zip(all_delays, range(all_delays.shape[0])): if jj==0: # 0 is for the open loop exp8_average_error[jj,ii], _, _ = openloop_run_fcn(model=model, desired_kinematics=desired_kinematics, plot_outputs=False, Mj_render=False) exp8_average_error[jj+1,ii], _, _ = closeloop_run_fcn(model=model, desired_kinematics=desired_kinematics, P=P, I=I, delay_timesteps=delay_timesteps, plot_outputs=False, Mj_render=False) # K = [10, 15] #print("error_without: ", exp2_average_error[0,0], "error with: ", exp2_average_error[1,0]) if experiments_switch[8] == 1: # everlearn random mesh refine_num = 25 test9_no = refine_num babbling_times = np.array([1, 2.5, 5]) num_babbling_cases = babbling_times.shape[0] #import pdb; pdb.set_trace() exp9_average_error = np.zeros([3,test9_no,num_babbling_cases]) for babbling_time, jj in zip(babbling_times, range(num_babbling_cases)): np.random.seed(0) [babbling_kinematics_1min, babbling_activations_1min] = babbling_fcn(simulation_minutes=babbling_time) model_1min = inverse_mapping_fcn(kinematics=babbling_kinematics_1min, activations=babbling_activations_1min) cum_kinematics_ol = deepcopy(babbling_kinematics_1min) cum_activations_ol = deepcopy(babbling_activations_1min) exp9_model_ol = deepcopy(model_1min) cum_kinematics_cl = deepcopy(babbling_kinematics_1min) cum_activations_cl = deepcopy(babbling_activations_1min) exp9_model_cl = deepcopy(model_1min) for ii in range(test9_no): features = np.ones(10,)#np.random.rand(10)*.8+.2 print(features) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) #1sec also fine q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) exp9_average_error[0,ii,jj], real_attempt_kinematics_ol, real_attempt_activations_ol = openloop_run_fcn(model=exp9_model_ol, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) cum_kinematics_ol, cum_activations_ol = concatinate_data_fcn( cum_kinematics_ol, cum_activations_ol, real_attempt_kinematics_ol, real_attempt_activations_ol, throw_percentage = 0.20) exp9_model_ol = inverse_mapping_fcn(cum_kinematics_ol, cum_activations_ol, prior_model = exp9_model_ol) exp9_average_error[1,ii,jj], real_attempt_kinematics_cl, real_attempt_activations_cl = closeloop_run_fcn(model=exp9_model_cl, desired_kinematics=desired_kinematics, model_ver=0, P=P, I=I, plot_outputs=False, Mj_render=False) exp9_average_error[2,ii,jj], _, _ = openloop_run_fcn(model=exp9_model_cl, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) cum_kinematics_cl, cum_activations_cl = concatinate_data_fcn( cum_kinematics_cl, cum_activations_cl, real_attempt_kinematics_cl, real_attempt_activations_cl, throw_percentage = 0.20) exp9_model_cl = inverse_mapping_fcn(cum_kinematics_cl, cum_activations_cl, prior_model = exp9_model_cl) if experiments_switch[9] == 1: # everlearn random np.random.seed(0) rep_num = trial_number refine_num=25 exp10_average_error = np.zeros([4,refine_num,rep_num]) for jj in range(rep_num): [babbling_kinematics_1min, babbling_activations_1min] = babbling_fcn(simulation_minutes=1) model_1min = inverse_mapping_fcn(kinematics=babbling_kinematics_1min, activations=babbling_activations_1min) cum_kinematics_ol = deepcopy(babbling_kinematics_1min) cum_activations_ol = deepcopy(babbling_activations_1min) exp10_model_ol = deepcopy(model_1min) cum_kinematics_cl = deepcopy(babbling_kinematics_1min) cum_activations_cl = deepcopy(babbling_activations_1min) exp10_model_cl = deepcopy(model_1min) features = np.random.rand(10) for ii in range(refine_num): print(features) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) #1sec also fine q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) exp10_average_error[0,ii,jj], real_attempt_kinematics_ol, real_attempt_activations_ol = openloop_run_fcn(model=exp10_model_ol, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) exp10_average_error[3,ii,jj], _, _ = closeloop_run_fcn(model=exp10_model_ol, desired_kinematics=desired_kinematics, model_ver=0, P=P, I=I, plot_outputs=False, Mj_render=False) cum_kinematics_ol, cum_activations_ol = concatinate_data_fcn( cum_kinematics_ol, cum_activations_ol, real_attempt_kinematics_ol, real_attempt_activations_ol, throw_percentage = 0.20) exp10_model_ol = inverse_mapping_fcn(cum_kinematics_ol, cum_activations_ol, prior_model = exp10_model_ol) exp10_average_error[1,ii,jj], real_attempt_kinematics_cl, real_attempt_activations_cl = closeloop_run_fcn(model=exp10_model_cl, desired_kinematics=desired_kinematics, model_ver=0, P=P, I=I, plot_outputs=False, Mj_render=False) exp10_average_error[2,ii,jj], _, _ = openloop_run_fcn(model=exp10_model_cl, desired_kinematics=desired_kinematics, model_ver=0, plot_outputs=False, Mj_render=False) cum_kinematics_cl, cum_activations_cl = concatinate_data_fcn( cum_kinematics_cl, cum_activations_cl, real_attempt_kinematics_cl, real_attempt_activations_cl, throw_percentage = 0.20) exp10_model_cl = inverse_mapping_fcn(cum_kinematics_cl, cum_activations_cl, prior_model = exp10_model_cl) if experiments_switch[10] ==1: # cyclical on air rep_num = trial_number powers=np.arange(-6,7,1) coefficients = np.power(2.,powers) P_exp11 = np.dot(coefficients[:,None],P[None,:]) I_exp11 = np.dot(coefficients[:,None],I[None,:]) PI_sets_no = P_exp11.shape[0] exp11_average_error = np.zeros([2,PI_sets_no]) for jj in range(PI_sets_no): np.random.seed(0) current_average_error = np.zeros([2,rep_num]) for ii in range(rep_num): features = np.random.rand(10) [q0_filtered, q1_filtered] = feat_to_positions_fcn(features, timestep=0.005, cycle_duration_in_seconds = 2.5, show=False) #import pdb; pdb.set_trace() q0_filtered_10 = np.tile(q0_filtered,10) q1_filtered_10 = np.tile(q1_filtered,10) desired_kinematics = positions_to_kinematics_fcn(q0_filtered_10, q1_filtered_10, timestep = 0.005) current_average_error[0,ii], _, _ = openloop_run_fcn(model=model, desired_kinematics=desired_kinematics, plot_outputs=False, Mj_render=False) current_average_error[1,ii], _, _ = closeloop_run_fcn(model=model, desired_kinematics=desired_kinematics, P=P_exp11[jj], I=I_exp11[jj], plot_outputs=False, Mj_render=False) # K = [10, 15] #print("error_without: ", exp2_average_error[0,0], "error with: ", exp2_average_error[1,0]) exp11_average_error[0, jj] = current_average_error[0,:].mean() exp11_average_error[1, jj] = current_average_error[1,:].mean() #import pdb; pdb.set_trace() #experiments_switch = np.ones(11,) errors_all = [exp1_average_error, exp2_average_error, exp3_average_error, exp4_average_error, exp5_average_error, exp6_average_error, exp7_average_error, exp8_average_error, exp9_average_error, exp10_average_error, exp11_average_error] #pickle.dump([errors_all, trial_number],open("results/P_I/feedback_errors_P_I_tmp.sav", 'wb')) # saving the results with only P [errors_all, trial_number] = pickle.load(open("results/P_I/feedback_errors_P_I_V8_50.sav", 'rb')) # loading the results with only P experiments_switch = np.zeros(11,) experiments_switch[0] =1 experiments_switch[3] =1 experiments_switch[7] =1 experiments_switch[9] =1 plot_comparison_figures_fcn(errors_all, experiments_switch, trial_number) #import pdb; pdb.set_trace()

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null

0

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null

0

6

a7eb527833529ec5d9540a0df0878bf3286e1e79

143

py

Python

midas_web_solution/menu/admin.py

jupiny/MIDASWebSolution

c6250bb7aeab815b3c759ae4f7b419da50c26b1c

[ "MIT" ]

null

midas_web_solution/menu/admin.py

jupiny/MIDASWebSolution

c6250bb7aeab815b3c759ae4f7b419da50c26b1c

[ "MIT" ]

null

midas_web_solution/menu/admin.py

jupiny/MIDASWebSolution

c6250bb7aeab815b3c759ae4f7b419da50c26b1c

[ "MIT" ]

null

from django.contrib import admin from .models import Menu class MenuAdmin(admin.ModelAdmin): pass admin.site.register(Menu, MenuAdmin)

14.3

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null

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6

c51277255498510c7788d0aabbaaeedc21c52724

371

py

Python

script.py

LNDHULK34/db8bot

cec34f4319b30754b273b6044e5c6eb010e6d6ff

[ "MIT" ]

null

script.py

LNDHULK34/db8bot

cec34f4319b30754b273b6044e5c6eb010e6d6ff

[ "MIT" ]

null

script.py

LNDHULK34/db8bot

cec34f4319b30754b273b6044e5c6eb010e6d6ff

[ "MIT" ]

null

import lib.scholarly as scholarly # searchstr = input() # print(searchstr) # print(next(scholarly.search_pubs_query("https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/hlr130&section=49"))) # print(next(scholarly.search_pubs_query(searchstr))) print(next(scholarly.search_pubs_query('Perception of physical stability and center of mass of 3D objects')))

53

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0.797844

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371

7

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null

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0

1

0

1

0

6

c5537a94467e96f9b8e7b0b42a11754fb8d9563a

17

py

Python

__init__.py

neonkitchen/beta-tcvae

c1903d923944a79c58b63b73a6060bf53b003443

[ "MIT" ]

null

__init__.py

neonkitchen/beta-tcvae

c1903d923944a79c58b63b73a6060bf53b003443

[ "MIT" ]

null

__init__.py

neonkitchen/beta-tcvae

c1903d923944a79c58b63b73a6060bf53b003443

[ "MIT" ]

null

import lib.dist

8.5

16

0.764706

3

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4.333333

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0

null

0

1

0

1

0

1

0

6

3d7fbc4cbbf991ea74df371a22127cbce3ff929d

137

py

Python

tests/test_import.py

GoodManWEN/bare_pypi_init_update

916b4d4d1238a1e7b60609a1103effb7e26963d2

[ "MIT" ]

null

tests/test_import.py

GoodManWEN/bare_pypi_init_update

916b4d4d1238a1e7b60609a1103effb7e26963d2

[ "MIT" ]

null

tests/test_import.py

GoodManWEN/bare_pypi_init_update

916b4d4d1238a1e7b60609a1103effb7e26963d2

[ "MIT" ]

null

import os , sys sys.path.append(os.getcwd()) import pytest from repo_name import * @pytest.mark.asyncio async def test_import(): ...

17.125

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null

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1

0

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0

1

0

6

3da4516df467db0cf1190dffee4345fa1cd2cc2f

140

py

Python

Pedigrad_py/SegmentCategory/SegmentCategory.py

remytuyeras/pedigrad-library

14846b3ddeac87f010a976f03b1b6d5245efc73b

[ "MIT" ]

8

2019-03-08T21:43:15.000Z

2021-08-12T19:43:21.000Z

Pedigrad_py/SegmentCategory/SegmentCategory.py

remytuyeras/pedigrad-library

14846b3ddeac87f010a976f03b1b6d5245efc73b

[ "MIT" ]

null

Pedigrad_py/SegmentCategory/SegmentCategory.py

remytuyeras/pedigrad-library

14846b3ddeac87f010a976f03b1b6d5245efc73b

[ "MIT" ]

1

2022-02-24T10:01:37.000Z

from cl_pro import PreOrder from cl_so import SegmentObject from cl_mos import MorphismOfSegments from cl_cos import CategoryOfSegments

15.555556

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20

140

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140

8

38

17.5

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1

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null

0

1

0

1

0

1

0

6

3dd2973cf9fe73122e008856cf206f860d61c06c

57

py

Python

2019/day_4/test_star_2.py

j-benson/advent-of-code

ec8162e769b45a54931c049daa4a0f492e773493

[ "MIT" ]

null

2019/day_4/test_star_2.py

j-benson/advent-of-code

ec8162e769b45a54931c049daa4a0f492e773493

[ "MIT" ]

null

2019/day_4/test_star_2.py

j-benson/advent-of-code

ec8162e769b45a54931c049daa4a0f492e773493

[ "MIT" ]

null

import star_2 print(star_2.contains_adjacent('224555'))

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6

9ab6c972a337a9a4794c1c1950e12141c510cb83

27,974

py

Python

code/python/FactSetEntity/v1/fds/sdk/FactSetEntity/api/entity_reference_api.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

6

2022-02-07T16:34:18.000Z

2022-03-30T08:04:57.000Z

code/python/FactSetEntity/v1/fds/sdk/FactSetEntity/api/entity_reference_api.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

2

2022-02-07T05:25:57.000Z

2022-03-07T14:18:04.000Z

code/python/FactSetEntity/v1/fds/sdk/FactSetEntity/api/entity_reference_api.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

null

""" FactSet Entity API Using an entity centric data model, FactSet's Entity API provides access to FactSet's complete security and entity level symbology, comprehensive entity reference data, and all of the necessary relationships and connections to create a foundation that tightly correlates disparate sources of information to a master entity identifier. Use this API to quickly understand the full entity structure and related securities. # noqa: E501 The version of the OpenAPI document: 1.2.0 Contact: api@factset.com Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from multiprocessing.pool import ApplyResult import typing from fds.sdk.FactSetEntity.api_client import ApiClient, Endpoint as _Endpoint from fds.sdk.FactSetEntity.model_utils import ( # noqa: F401 check_allowed_values, check_validations, date, datetime, file_type, none_type, validate_and_convert_types ) from fds.sdk.FactSetEntity.exceptions import ApiException from fds.sdk.FactSetEntity.model.entity_reference_request import EntityReferenceRequest from fds.sdk.FactSetEntity.model.entity_reference_response import EntityReferenceResponse from fds.sdk.FactSetEntity.model.error_response import ErrorResponse class EntityReferenceApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client self.get_entity_references_endpoint = _Endpoint( settings={ 'response_type': ( { 200: (EntityReferenceResponse,), 400: (ErrorResponse,), 401: (ErrorResponse,), 403: (ErrorResponse,), 415: (ErrorResponse,), 500: (ErrorResponse,), }, None ), 'auth': [ 'FactSetApiKey', 'FactSetOAuth2' ], 'endpoint_path': '/factset-entity/v1/entity-references', 'operation_id': 'get_entity_references', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'ids', ], 'required': [ 'ids', ], 'nullable': [ ], 'enum': [ ], 'validation': [ 'ids', ] }, root_map={ 'validations': { ('ids',): { 'max_items': 3000, 'min_items': 1, }, }, 'allowed_values': { }, 'openapi_types': { 'ids': ([str],), }, 'attribute_map': { 'ids': 'ids', }, 'location_map': { 'ids': 'query', }, 'collection_format_map': { 'ids': 'csv', } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.post_entity_references_endpoint = _Endpoint( settings={ 'response_type': ( { 200: (EntityReferenceResponse,), 400: (ErrorResponse,), 401: (ErrorResponse,), 403: (ErrorResponse,), 415: (ErrorResponse,), 500: (ErrorResponse,), }, None ), 'auth': [ 'FactSetApiKey', 'FactSetOAuth2' ], 'endpoint_path': '/factset-entity/v1/entity-references', 'operation_id': 'post_entity_references', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'entity_reference_request', ], 'required': [ 'entity_reference_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'entity_reference_request': (EntityReferenceRequest,), }, 'attribute_map': { }, 'location_map': { 'entity_reference_request': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) @staticmethod def apply_kwargs_defaults(kwargs, return_http_data_only, async_req): kwargs["async_req"] = async_req kwargs["_return_http_data_only"] = return_http_data_only kwargs["_preload_content"] = kwargs.get("_preload_content", True) kwargs["_request_timeout"] = kwargs.get("_request_timeout", None) kwargs["_check_input_type"] = kwargs.get("_check_input_type", True) kwargs["_check_return_type"] = kwargs.get("_check_return_type", True) kwargs["_spec_property_naming"] = kwargs.get("_spec_property_naming", False) kwargs["_content_type"] = kwargs.get("_content_type") kwargs["_host_index"] = kwargs.get("_host_index") def get_entity_references( self, ids, **kwargs ) -> EntityReferenceResponse: """Returns an entity reference profiles for an individual entity # noqa: E501 Returns an Entity reference profile for the requested Entity Id(s). Data points include - Ultimate Parent Id, Credit Parent Id, Headquarters location details, Website URL, and Business Description. # noqa: E501 This method makes a synchronous HTTP request. Returns the http data only Args: ids ([str]): The requested Market Identifier. Accepted input identifiers include Ticker-Exchange, Ticker-Regions, CUSIPs, ISINs, SEDOLs, or FactSet Permanent Ids, such as -R, -L, or -E.<p>**Max Ids Limit set to 3000 in a single request**</p> *<p>Make note, GET Method URL request lines are also limited to a total length of 8192 bytes (8KB). In cases where the service allows for thousands of ids, which may lead to exceeding this request line limit of 8KB, its advised for any requests with large request lines to be requested through the respective \\\"POST\\\" method.</p>* Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: EntityReferenceResponse Response Object """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=False) kwargs['ids'] = \ ids return self.get_entity_references_endpoint.call_with_http_info(**kwargs) def get_entity_references_with_http_info( self, ids, **kwargs ) -> typing.Tuple[EntityReferenceResponse, int, typing.MutableMapping]: """Returns an entity reference profiles for an individual entity # noqa: E501 Returns an Entity reference profile for the requested Entity Id(s). Data points include - Ultimate Parent Id, Credit Parent Id, Headquarters location details, Website URL, and Business Description. # noqa: E501 This method makes a synchronous HTTP request. Returns http data, http status and headers Args: ids ([str]): The requested Market Identifier. Accepted input identifiers include Ticker-Exchange, Ticker-Regions, CUSIPs, ISINs, SEDOLs, or FactSet Permanent Ids, such as -R, -L, or -E.<p>**Max Ids Limit set to 3000 in a single request**</p> *<p>Make note, GET Method URL request lines are also limited to a total length of 8192 bytes (8KB). In cases where the service allows for thousands of ids, which may lead to exceeding this request line limit of 8KB, its advised for any requests with large request lines to be requested through the respective \\\"POST\\\" method.</p>* Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: EntityReferenceResponse Response Object int Http Status Code dict Dictionary of the response headers """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=False) kwargs['ids'] = \ ids return self.get_entity_references_endpoint.call_with_http_info(**kwargs) def get_entity_references_async( self, ids, **kwargs ) -> "ApplyResult[EntityReferenceResponse]": """Returns an entity reference profiles for an individual entity # noqa: E501 Returns an Entity reference profile for the requested Entity Id(s). Data points include - Ultimate Parent Id, Credit Parent Id, Headquarters location details, Website URL, and Business Description. # noqa: E501 This method makes a asynchronous HTTP request. Returns the http data, wrapped in ApplyResult Args: ids ([str]): The requested Market Identifier. Accepted input identifiers include Ticker-Exchange, Ticker-Regions, CUSIPs, ISINs, SEDOLs, or FactSet Permanent Ids, such as -R, -L, or -E.<p>**Max Ids Limit set to 3000 in a single request**</p> *<p>Make note, GET Method URL request lines are also limited to a total length of 8192 bytes (8KB). In cases where the service allows for thousands of ids, which may lead to exceeding this request line limit of 8KB, its advised for any requests with large request lines to be requested through the respective \\\"POST\\\" method.</p>* Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: ApplyResult[EntityReferenceResponse] """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=True) kwargs['ids'] = \ ids return self.get_entity_references_endpoint.call_with_http_info(**kwargs) def get_entity_references_with_http_info_async( self, ids, **kwargs ) -> "ApplyResult[typing.Tuple[EntityReferenceResponse, int, typing.MutableMapping]]": """Returns an entity reference profiles for an individual entity # noqa: E501 Returns an Entity reference profile for the requested Entity Id(s). Data points include - Ultimate Parent Id, Credit Parent Id, Headquarters location details, Website URL, and Business Description. # noqa: E501 This method makes a asynchronous HTTP request. Returns http data, http status and headers, wrapped in ApplyResult Args: ids ([str]): The requested Market Identifier. Accepted input identifiers include Ticker-Exchange, Ticker-Regions, CUSIPs, ISINs, SEDOLs, or FactSet Permanent Ids, such as -R, -L, or -E.<p>**Max Ids Limit set to 3000 in a single request**</p> *<p>Make note, GET Method URL request lines are also limited to a total length of 8192 bytes (8KB). In cases where the service allows for thousands of ids, which may lead to exceeding this request line limit of 8KB, its advised for any requests with large request lines to be requested through the respective \\\"POST\\\" method.</p>* Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: ApplyResult[(EntityReferenceResponse, int, typing.Dict)] """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=True) kwargs['ids'] = \ ids return self.get_entity_references_endpoint.call_with_http_info(**kwargs) def post_entity_references( self, entity_reference_request, **kwargs ) -> EntityReferenceResponse: """Returns an entity reference data for a list of ids. # noqa: E501 Returns an entity reference object for the requested entity ids. Data points include - ultimate parent id, headquarters location details, credit parent id, website, and business description. # noqa: E501 This method makes a synchronous HTTP request. Returns the http data only Args: entity_reference_request (EntityReferenceRequest): Request Body to request a list of Entity Reference objects. Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: EntityReferenceResponse Response Object """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=False) kwargs['entity_reference_request'] = \ entity_reference_request return self.post_entity_references_endpoint.call_with_http_info(**kwargs) def post_entity_references_with_http_info( self, entity_reference_request, **kwargs ) -> typing.Tuple[EntityReferenceResponse, int, typing.MutableMapping]: """Returns an entity reference data for a list of ids. # noqa: E501 Returns an entity reference object for the requested entity ids. Data points include - ultimate parent id, headquarters location details, credit parent id, website, and business description. # noqa: E501 This method makes a synchronous HTTP request. Returns http data, http status and headers Args: entity_reference_request (EntityReferenceRequest): Request Body to request a list of Entity Reference objects. Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: EntityReferenceResponse Response Object int Http Status Code dict Dictionary of the response headers """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=False) kwargs['entity_reference_request'] = \ entity_reference_request return self.post_entity_references_endpoint.call_with_http_info(**kwargs) def post_entity_references_async( self, entity_reference_request, **kwargs ) -> "ApplyResult[EntityReferenceResponse]": """Returns an entity reference data for a list of ids. # noqa: E501 Returns an entity reference object for the requested entity ids. Data points include - ultimate parent id, headquarters location details, credit parent id, website, and business description. # noqa: E501 This method makes a asynchronous HTTP request. Returns the http data, wrapped in ApplyResult Args: entity_reference_request (EntityReferenceRequest): Request Body to request a list of Entity Reference objects. Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: ApplyResult[EntityReferenceResponse] """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=True) kwargs['entity_reference_request'] = \ entity_reference_request return self.post_entity_references_endpoint.call_with_http_info(**kwargs) def post_entity_references_with_http_info_async( self, entity_reference_request, **kwargs ) -> "ApplyResult[typing.Tuple[EntityReferenceResponse, int, typing.MutableMapping]]": """Returns an entity reference data for a list of ids. # noqa: E501 Returns an entity reference object for the requested entity ids. Data points include - ultimate parent id, headquarters location details, credit parent id, website, and business description. # noqa: E501 This method makes a asynchronous HTTP request. Returns http data, http status and headers, wrapped in ApplyResult Args: entity_reference_request (EntityReferenceRequest): Request Body to request a list of Entity Reference objects. Keyword Args: _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. Returns: ApplyResult[(EntityReferenceResponse, int, typing.Dict)] """ self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=True) kwargs['entity_reference_request'] = \ entity_reference_request return self.post_entity_references_endpoint.call_with_http_info(**kwargs)

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Python

tests/functional/test_jsonrpc_specs.py

vladcalin/pymicroservice

325a49d17621b9d45ffd2b5eca6f0de284de8ba4

[ "MIT" ]

2

2016-12-17T13:09:14.000Z

2016-12-31T18:38:57.000Z

tests/functional/test_jsonrpc_specs.py

vladcalin/pymicroservice

325a49d17621b9d45ffd2b5eca6f0de284de8ba4

[ "MIT" ]

15

2016-11-27T13:28:25.000Z

2017-01-10T09:09:30.000Z

tests/functional/test_jsonrpc_specs.py

vladcalin/pymicroservice

325a49d17621b9d45ffd2b5eca6f0de284de8ba4

[ "MIT" ]

null

""" Contains tests that assert the compliance with the JSON RPC 2.0 specifications (http://www.jsonrpc.org/specification) """ import logging import simplejson as json import pytest from tests.services.service_jsonrpc_specs import ServiceJsonRpcSpecs @pytest.fixture def app(): service = ServiceJsonRpcSpecs() service._initial_setup() return service.make_tornado_app() @pytest.mark.gen_test def test_incomplete_json(http_client, base_url): body = json.dumps({"jsonrpc": "2.0", "method": "subtract"})[:15] result = yield http_client.fetch(base_url + "/api", method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["result"] is None assert response_body["jsonrpc"] == "2.0" assert response_body["error"] == {"code": -32700, "message": "Parse error"} # examples from http://www.jsonrpc.org/specification @pytest.mark.gen_test def test_rpc_call_with_positional_parameters(http_client, base_url): base_url += "/api" body = json.dumps({"jsonrpc": "2.0", "method": "subtract", "params": [42, 23], "id": 1}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] == 19 assert response_body["id"] == 1 body = json.dumps({"jsonrpc": "2.0", "method": "subtract", "params": [23, 42], "id": 2}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] == -19 assert response_body["id"] == 2 @pytest.mark.gen_test def test_rpc_call_with_named_parameters(http_client, base_url): base_url += "/api" body = json.dumps( {"jsonrpc": "2.0", "method": "subtract", "params": {"a": 42, "b": 23}, "id": 3}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] == 19 assert response_body["id"] == 3 body = json.dumps( {"jsonrpc": "2.0", "method": "subtract", "params": {"b": 42, "a": 23}, "id": 4}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] == -19 assert response_body["id"] == 4 @pytest.mark.gen_test def test_a_notification(http_client, base_url): base_url += "/api" body = json.dumps({"jsonrpc": "2.0", "method": "update", "params": {"a": 23}}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] is None assert response_body["error"] is None @pytest.mark.gen_test def test_a_notification_inexistent_method(http_client, base_url): base_url += "/api" body = json.dumps({"jsonrpc": "2.0", "method": "does_not_exist", "params": {"a": 23}}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] is None assert response_body["error"] is None @pytest.mark.gen_test def test_rpc_call_of_non_existent_method(http_client, base_url): base_url += "/api" body = json.dumps({"jsonrpc": "2.0", "method": "does_not_exist", "params": {"a": 23}, "id": 1}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] is None assert response_body["error"] == {"code": -32601, "message": "Method not found"} assert response_body["id"] == 1 @pytest.mark.gen_test def test_rpc_call_with_invalid_json(http_client, base_url): base_url += "/api" body = '{"jsonrpc": "2.0", "method": "foobar, "params": "bar", "baz]' result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] is None assert response_body["error"] == {"code": -32700, "message": "Parse error"} @pytest.mark.gen_test def test_rpc_call_with_invalid_request_object(http_client, base_url): base_url += "/api" body = json.dumps({"jsonrpc": "2.0", "method": "subtract", "params": "foobar"}) result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] is None assert response_body["error"] == {"code": -32600, "message": "Invalid Request"} assert response_body["id"] is None @pytest.mark.gen_test def test_batch_call_with_invalid_json(http_client, base_url): base_url += "/api" body = '[{"jsonrpc": "2.0", "method": "sum", "params": [1,2,4], "id": "1"},{"jsonrpc": "2.0", "method"]' result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) print(response_body) assert isinstance(response_body, dict) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] is None assert response_body["error"] == {"code": -32700, "message": "Parse error"} @pytest.mark.gen_test def test_batch_call_empty_array(http_client, base_url): base_url += "/api" body = "[]" result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert response_body["jsonrpc"] == "2.0" assert response_body["result"] is None assert response_body["error"] == {"code": -32600, "message": "Invalid Request"} assert response_body["id"] is None @pytest.mark.gen_test def test_batch_call_invalid_batch_but_not_empty(http_client, base_url): base_url += "/api" body = "[1]" result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert isinstance(response_body, list) assert len(response_body) == 1 assert response_body[0]["jsonrpc"] == "2.0" assert response_body[0]["id"] is None assert response_body[0]["result"] is None assert response_body[0]["error"] == {"code": -32600, "message": "Invalid Request"} @pytest.mark.gen_test def test_batch_call_invalid_batch(http_client, base_url): base_url += "/api" body = "[1,2,3]" result = yield http_client.fetch(base_url, method="POST", body=body, headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert isinstance(response_body, list) assert len(response_body) == 3 for i in range(3): assert response_body[i]["jsonrpc"] == "2.0" assert response_body[i]["id"] is None assert response_body[i]["result"] is None assert response_body[i]["error"] == {"code": -32600, "message": "Invalid Request"} @pytest.mark.gen_test def test_batch_big_batch(http_client, base_url): base_url += "/api" body = [ {"jsonrpc": "2.0", "method": "sum", "params": [1, 2, 4], "id": "1"}, # valid {"jsonrpc": "2.0", "method": "notify_hello", "params": [7]}, # notification {"jsonrpc": "2.0", "method": "subtract", "params": [42, 23], "id": "2"}, # valid {"foo": "boo"}, # invalid request {"jsonrpc": "2.0", "method": "foo.get", "params": {"name": "myself"}, "id": "5"}, # method not found {"jsonrpc": "2.0", "method": "get_data", "id": "9"} # valid no params ] expected_results = { "1": {"jsonrpc": "2.0", "result": 7, "id": "1", "error": None}, "2": {"jsonrpc": "2.0", "result": 19, "id": "2", "error": None}, "5": {"jsonrpc": "2.0", "error": {"code": -32601, "message": "Method not found"}, "id": "5", "result": None}, "9": {"jsonrpc": "2.0", "result": ["hello", 5], "id": "9", "error": None} } result = yield http_client.fetch(base_url, method="POST", body=json.dumps(body), headers={"content-type": "application/json"}) assert result.code == 200 response_body = json.loads(result.body) assert isinstance(response_body, list) print(response_body) for request in body: req_id = request.get("id") if not req_id: continue expected = expected_results.get(req_id) actual_response = [x for x in response_body if x["id"] == req_id][0] assert expected == actual_response

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9af6789ad7c7cb5f1a6419706656130eb737a52c

253

py

Python

server/constants.py

Shnitselon/torque-vs-code-extensions

c53fe0b777d86b90f0c8dd7a3e3dda531316267e

[ "Apache-2.0" ]

null

server/constants.py

Shnitselon/torque-vs-code-extensions

c53fe0b777d86b90f0c8dd7a3e3dda531316267e

[ "Apache-2.0" ]

null

server/constants.py

Shnitselon/torque-vs-code-extensions

c53fe0b777d86b90f0c8dd7a3e3dda531316267e

[ "Apache-2.0" ]

null

PREDEFINED_TORQUE_INPUTS = [ "$torque.environment.id", "$torque.environment.virtual_network_id", "$torque.environment.public_address", "$torque.repos.current.current", "$torque.repos.current.url", "$torque.repos.current.token" ]

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py

Python

boa3_test/test_sc/neo_type_test/UInt256ConcatWithBytes.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

25

2020-07-22T19:37:43.000Z

2022-03-08T03:23:55.000Z

boa3_test/test_sc/neo_type_test/UInt256ConcatWithBytes.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

419

2020-04-23T17:48:14.000Z

2022-03-31T13:17:45.000Z

boa3_test/test_sc/neo_type_test/UInt256ConcatWithBytes.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

15

2020-05-21T21:54:24.000Z

2021-11-18T06:17:24.000Z

from boa3.builtin import public from boa3.builtin.type import UInt256 @public def uint256_method(arg: UInt256) -> bytes: return arg + b'123'

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py

Python

pyhiveapi/apyhiveapi/helper/__init__.py

ms32035/Pyhiveapi

c84389aa8118acd006a4b228e58b6a966e49e7dc

[ "MIT" ]

10

2020-10-11T20:50:36.000Z

2021-05-01T16:11:19.000Z

pyhiveapi/apyhiveapi/helper/__init__.py

ms32035/Pyhiveapi

c84389aa8118acd006a4b228e58b6a966e49e7dc

[ "MIT" ]

11

2020-10-27T19:34:12.000Z

2021-03-11T22:30:13.000Z

pyhiveapi/apyhiveapi/helper/__init__.py

ms32035/Pyhiveapi

c84389aa8118acd006a4b228e58b6a966e49e7dc

[ "MIT" ]

8

2020-10-05T18:55:41.000Z

2021-03-04T23:45:05.000Z

"""__init__.py file.""" from .hive_helper import HiveHelper # noqa: F401 from .logger import Logger # noqa: F401

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173

py

Python

moveit_commander/src/moveit_commander/__init__.py

Bhavam/moveit

6b56cd68d76ae29d1ceb255d06be35543dd3f830

[ "BSD-3-Clause" ]

1,116

2016-07-29T06:39:49.000Z

2022-03-31T08:42:14.000Z

moveit_commander/src/moveit_commander/__init__.py

Bhavam/moveit

6b56cd68d76ae29d1ceb255d06be35543dd3f830

[ "BSD-3-Clause" ]

2,784

2016-07-29T15:19:38.000Z

2022-03-31T01:35:59.000Z

moveit_commander/src/moveit_commander/__init__.py

Bhavam/moveit

6b56cd68d76ae29d1ceb255d06be35543dd3f830

[ "BSD-3-Clause" ]

956

2016-07-30T17:03:44.000Z

2022-03-31T15:48:31.000Z

from .exception import * from .roscpp_initializer import * from .planning_scene_interface import * from .move_group import * from .robot import * from .interpreter import *

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py

Python

ssacc/utils/utils.py

tomwillis608/ssacc

f716357fba9383c75b98c3ffdb241d790e204a4b

[ "MIT" ]

1

2021-07-18T20:25:24.000Z

ssacc/utils/utils.py

tomwillis608/ssacc

f716357fba9383c75b98c3ffdb241d790e204a4b

[ "MIT" ]

314

2020-08-29T18:58:58.000Z

2022-03-29T01:19:54.000Z

ssacc/utils/utils.py

tomwillis608/ssacc

f716357fba9383c75b98c3ffdb241d790e204a4b

[ "MIT" ]

null

"""Utility functions.""" from pathlib import Path def get_project_root() -> Path: """Consistently get the project root for any module in source tree.""" return Path(__file__).parent.parent.parent

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773131c7c59b08517ed46d312140b62122e7da23

56,144

py

Python

osm_nbi/tests/test_descriptor_topics.py

CrossStream/etsi_nbi

9fe58b17a7d58efbf87df1ae119907b9071ecf2f

[ "Apache-2.0" ]

null

osm_nbi/tests/test_descriptor_topics.py

CrossStream/etsi_nbi

9fe58b17a7d58efbf87df1ae119907b9071ecf2f

[ "Apache-2.0" ]

null

osm_nbi/tests/test_descriptor_topics.py

CrossStream/etsi_nbi

9fe58b17a7d58efbf87df1ae119907b9071ecf2f

[ "Apache-2.0" ]

null

#! /usr/bin/python3 # -*- coding: utf-8 -*- # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License 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. __author__ = "Pedro de la Cruz Ramos, pedro.delacruzramos@altran.com" __date__ = "2019-11-20" import unittest from unittest import TestCase from unittest.mock import Mock from uuid import uuid4 from http import HTTPStatus from copy import deepcopy from time import time from osm_common import dbbase, fsbase, msgbase from osm_nbi import authconn from osm_nbi.tests.test_pkg_descriptors import db_vnfds_text, db_nsds_text from osm_nbi.descriptor_topics import VnfdTopic, NsdTopic from osm_nbi.engine import EngineException from osm_common.dbbase import DbException import yaml test_pid = str(uuid4()) test_name = "test-user" fake_session = {"username": test_name, "project_id": (test_pid,), "method": None, "admin": True, "force": False, "public": False, "allow_show_user_project_role": True} db_vnfd_content = yaml.load(db_vnfds_text, Loader=yaml.Loader)[0] db_nsd_content = yaml.load(db_nsds_text, Loader=yaml.Loader)[0] def norm(str): """Normalize string for checking""" return ' '.join(str.strip().split()).lower() def compare_desc(tc, d1, d2, k): """ Compare two descriptors We need this function because some methods are adding/removing items to/from the descriptors before they are stored in the database, so the original and stored versions will differ What we check is that COMMON LEAF ITEMS are equal Lists of different length are not compared :param tc: Test Case wich provides context (in particular the assert* methods) :param d1,d2: Descriptors to be compared :param key/item being compared :return: Nothing """ if isinstance(d1, dict) and isinstance(d2, dict): for key in d1.keys(): if key in d2: compare_desc(tc, d1[key], d2[key], k+"[{}]".format(key)) elif isinstance(d1, list) and isinstance(d2, list) and len(d1) == len(d2): for i in range(len(d1)): compare_desc(tc, d1[i], d2[i], k+"[{}]".format(i)) else: tc.assertEqual(d1, d2, "Wrong descriptor content: {}".format(k)) class Test_VnfdTopic(TestCase): @classmethod def setUpClass(cls): cls.test_name = "test-vnfd-topic" @classmethod def tearDownClass(cls): pass def setUp(self): self.db = Mock(dbbase.DbBase()) self.fs = Mock(fsbase.FsBase()) self.msg = Mock(msgbase.MsgBase()) self.auth = Mock(authconn.Authconn(None, None, None)) self.topic = VnfdTopic(self.db, self.fs, self.msg, self.auth) def test_new_vnfd(self): did = db_vnfd_content["_id"] self.fs.get_params.return_value = {} self.fs.file_exists.return_value = False self.fs.file_open.side_effect = lambda path, mode: open("/tmp/" + str(uuid4()), "a+b") test_vnfd = deepcopy(db_vnfd_content) del test_vnfd["_id"] del test_vnfd["_admin"] with self.subTest(i=1, t='Normal Creation'): self.db.create.return_value = did rollback = [] did2, oid = self.topic.new(rollback, fake_session, {}) db_args = self.db.create.call_args[0] msg_args = self.msg.write.call_args[0] self.assertEqual(len(rollback), 1, "Wrong rollback length") self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "created", "Wrong message action") self.assertEqual(msg_args[2], {"_id": did}, "Wrong message content") self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(did2, did, "Wrong DB VNFD id") self.assertIsNotNone(db_args[1]["_admin"]["created"], "Wrong creation time") self.assertEqual(db_args[1]["_admin"]["modified"], db_args[1]["_admin"]["created"], "Wrong modification time") self.assertEqual(db_args[1]["_admin"]["projects_read"], [test_pid], "Wrong read-only project list") self.assertEqual(db_args[1]["_admin"]["projects_write"], [test_pid], "Wrong read-write project list") tmp1 = test_vnfd["vdu"][0]["cloud-init-file"] tmp2 = test_vnfd["vnf-configuration"]["juju"] del test_vnfd["vdu"][0]["cloud-init-file"] del test_vnfd["vnf-configuration"]["juju"] try: self.db.get_one.side_effect = [{"_id": did, "_admin": db_vnfd_content["_admin"]}, None] self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) msg_args = self.msg.write.call_args[0] test_vnfd["_id"] = did self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "edited", "Wrong message action") self.assertEqual(msg_args[2], test_vnfd, "Wrong message content") db_args = self.db.get_one.mock_calls[0][1] self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1]["_id"], did, "Wrong DB VNFD id") db_args = self.db.replace.call_args[0] self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1], did, "Wrong DB VNFD id") admin = db_args[2]["_admin"] db_admin = db_vnfd_content["_admin"] self.assertEqual(admin["type"], "vnfd", "Wrong descriptor type") self.assertEqual(admin["created"], db_admin["created"], "Wrong creation time") self.assertGreater(admin["modified"], db_admin["created"], "Wrong modification time") self.assertEqual(admin["projects_read"], db_admin["projects_read"], "Wrong read-only project list") self.assertEqual(admin["projects_write"], db_admin["projects_write"], "Wrong read-write project list") self.assertEqual(admin["onboardingState"], "ONBOARDED", "Wrong onboarding state") self.assertEqual(admin["operationalState"], "ENABLED", "Wrong operational state") self.assertEqual(admin["usageState"], "NOT_IN_USE", "Wrong usage state") storage = admin["storage"] self.assertEqual(storage["folder"], did, "Wrong storage folder") self.assertEqual(storage["descriptor"], "package", "Wrong storage descriptor") compare_desc(self, test_vnfd, db_args[2], "VNFD") finally: test_vnfd["vdu"][0]["cloud-init-file"] = tmp1 test_vnfd["vnf-configuration"]["juju"] = tmp2 self.db.get_one.side_effect = lambda table, filter, fail_on_empty=None, fail_on_more=None:\ {"_id": did, "_admin": db_vnfd_content["_admin"]} with self.subTest(i=2, t='Check Pyangbind Validation: required properties'): tmp = test_vnfd["id"] del test_vnfd["id"] try: with self.assertRaises(EngineException, msg="Accepted VNFD with a missing required property") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error in pyangbind validation: '{}'".format("id")), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["id"] = tmp with self.subTest(i=3, t='Check Pyangbind Validation: additional properties'): test_vnfd["extra-property"] = 0 try: with self.assertRaises(EngineException, msg="Accepted VNFD with an additional property") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error in pyangbind validation: {} ({})" .format("json object contained a key that did not exist", "extra-property")), norm(str(e.exception)), "Wrong exception text") finally: del test_vnfd["extra-property"] with self.subTest(i=4, t='Check Pyangbind Validation: property types'): tmp = test_vnfd["short-name"] test_vnfd["short-name"] = {"key": 0} try: with self.assertRaises(EngineException, msg="Accepted VNFD with a wrongly typed property") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error in pyangbind validation: {} ({})" .format("json object contained a key that did not exist", "key")), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["short-name"] = tmp with self.subTest(i=5, t='Check Input Validation: cloud-init'): with self.assertRaises(EngineException, msg="Accepted non-existent cloud_init file") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.BAD_REQUEST, "Wrong HTTP status code") self.assertIn(norm("{} defined in vnf[id={}]:vdu[id={}] but not present in package" .format("cloud-init", test_vnfd["id"], test_vnfd["vdu"][0]["id"])), norm(str(e.exception)), "Wrong exception text") with self.subTest(i=6, t='Check Input Validation: vnf-configuration[juju]'): del test_vnfd["vdu"][0]["cloud-init-file"] with self.assertRaises(EngineException, msg="Accepted non-existent charm in VNF configuration") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.BAD_REQUEST, "Wrong HTTP status code") self.assertIn(norm("{} defined in vnf[id={}] but not present in package".format("charm", test_vnfd["id"])), norm(str(e.exception)), "Wrong exception text") with self.subTest(i=7, t='Check Input Validation: mgmt-interface'): del test_vnfd["vnf-configuration"]["juju"] tmp = test_vnfd["mgmt-interface"] del test_vnfd["mgmt-interface"] try: with self.assertRaises(EngineException, msg="Accepted VNFD without management interface") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("'{}' is a mandatory field and it is not defined".format("mgmt-interface")), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["mgmt-interface"] = tmp with self.subTest(i=8, t='Check Input Validation: mgmt-interface[cp]'): tmp = test_vnfd["mgmt-interface"]["cp"] test_vnfd["mgmt-interface"]["cp"] = "wrong-cp" try: with self.assertRaises(EngineException, msg="Accepted wrong management interface connection point") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("mgmt-interface:cp='{}' must match an existing connection-point" .format(test_vnfd["mgmt-interface"]["cp"])), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["mgmt-interface"]["cp"] = tmp with self.subTest(i=9, t='Check Input Validation: vdu[interface][external-connection-point-ref]'): tmp = test_vnfd["vdu"][0]["interface"][0]["external-connection-point-ref"] test_vnfd["vdu"][0]["interface"][0]["external-connection-point-ref"] = "wrong-cp" try: with self.assertRaises(EngineException, msg="Accepted wrong VDU interface external connection point reference") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("vdu[id='{}']:interface[name='{}']:external-connection-point-ref='{}'" " must match an existing connection-point" .format(test_vnfd["vdu"][0]["id"], test_vnfd["vdu"][0]["interface"][0]["name"], test_vnfd["vdu"][0]["interface"][0]["external-connection-point-ref"])), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["vdu"][0]["interface"][0]["external-connection-point-ref"] = tmp with self.subTest(i=10, t='Check Input Validation: vdu[interface][internal-connection-point-ref]'): tmp = test_vnfd["vdu"][1]["interface"][0]["internal-connection-point-ref"] test_vnfd["vdu"][1]["interface"][0]["internal-connection-point-ref"] = "wrong-cp" try: with self.assertRaises(EngineException, msg="Accepted wrong VDU interface internal connection point reference") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("vdu[id='{}']:interface[name='{}']:internal-connection-point-ref='{}'" " must match an existing vdu:internal-connection-point" .format(test_vnfd["vdu"][1]["id"], test_vnfd["vdu"][1]["interface"][0]["name"], test_vnfd["vdu"][1]["interface"][0]["internal-connection-point-ref"])), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["vdu"][1]["interface"][0]["internal-connection-point-ref"] = tmp with self.subTest(i=11, t='Check Input Validation: vdu[vdu-configuration][juju]'): test_vnfd["vdu"][0]["vdu-configuration"] = {"juju": {"charm": "wrong-charm"}} try: with self.assertRaises(EngineException, msg="Accepted non-existent charm in VDU configuration") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.BAD_REQUEST, "Wrong HTTP status code") self.assertIn(norm("{} defined in vnf[id={}]:vdu[id={}] but not present in package" .format("charm", test_vnfd["id"], test_vnfd["vdu"][0]["id"])), norm(str(e.exception)), "Wrong exception text") finally: del test_vnfd["vdu"][0]["vdu-configuration"] with self.subTest(i=12, t='Check Input Validation: Duplicated VLD name'): test_vnfd["internal-vld"].append(deepcopy(test_vnfd["internal-vld"][0])) test_vnfd["internal-vld"][1]["id"] = "wrong-internal-vld" try: with self.assertRaises(EngineException, msg="Accepted duplicated VLD name") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Duplicated VLD name '{}' in vnfd[id={}]:internal-vld[id={}]" .format(test_vnfd["internal-vld"][1]["name"], test_vnfd["id"], test_vnfd["internal-vld"][1]["id"])), norm(str(e.exception)), "Wrong exception text") finally: del test_vnfd["internal-vld"][1] with self.subTest(i=13, t='Check Input Validation: internal-vld[internal-connection-point][id-ref])'): tmp = test_vnfd["internal-vld"][0]["internal-connection-point"][0]["id-ref"] test_vnfd["internal-vld"][0]["internal-connection-point"][0]["id-ref"] = "wrong-icp-id-ref" try: with self.assertRaises(EngineException, msg="Accepted non-existent internal VLD ICP id-ref") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("internal-vld[id='{}']:internal-connection-point='{}' must match an existing " "vdu:internal-connection-point" .format(test_vnfd["internal-vld"][0]["id"], test_vnfd["internal-vld"][0]["internal-connection-point"][0]["id-ref"])), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["internal-vld"][0]["internal-connection-point"][0]["id-ref"] = tmp with self.subTest(i=14, t='Check Input Validation: internal-vld[ip-profile-ref])'): test_vnfd["ip-profiles"] = [{"name": "fake-ip-profile-ref"}] test_vnfd["internal-vld"][0]["ip-profile-ref"] = "wrong-ip-profile-ref" try: with self.assertRaises(EngineException, msg="Accepted non-existent IP Profile Ref") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("internal-vld[id='{}']:ip-profile-ref='{}' does not exist" .format(test_vnfd["internal-vld"][0]["id"], test_vnfd["internal-vld"][0]["ip-profile-ref"])), norm(str(e.exception)), "Wrong exception text") finally: del test_vnfd["ip-profiles"] del test_vnfd["internal-vld"][0]["ip-profile-ref"] with self.subTest(i=15, t='Check Input Validation: vdu[monitoring-param])'): test_vnfd["monitoring-param"] = [{"id": "fake-mp-id", "vdu-monitoring-param": { "vdu-monitoring-param-ref": "fake-vdu-mp-ref", "vdu-ref": "fake-vdu-ref"}}] test_vnfd["vdu"][0]["monitoring-param"] = [{"id": "wrong-vdu-mp-id"}] try: with self.assertRaises(EngineException, msg="Accepted non-existent VDU Monitorimg Param") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") mp = test_vnfd["monitoring-param"][0]["vdu-monitoring-param"] self.assertIn(norm("monitoring-param:vdu-monitoring-param:vdu-monitoring-param-ref='{}' not defined" " at vdu[id='{}'] or vdu does not exist" .format(mp["vdu-monitoring-param-ref"], mp["vdu-ref"])), norm(str(e.exception)), "Wrong exception text") finally: del test_vnfd["monitoring-param"] del test_vnfd["vdu"][0]["monitoring-param"] with self.subTest(i=16, t='Check Input Validation: vdu[vdu-configuration][metrics]'): test_vnfd["monitoring-param"] = [{"id": "fake-mp-id", "vdu-metric": { "vdu-metric-name-ref": "fake-vdu-mp-ref", "vdu-ref": "fake-vdu-ref"}}] test_vnfd["vdu"][0]["vdu-configuration"] = {"metrics": [{"name": "wrong-vdu-mp-id"}]} try: with self.assertRaises(EngineException, msg="Accepted non-existent VDU Configuration Metric") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") mp = test_vnfd["monitoring-param"][0]["vdu-metric"] self.assertIn(norm("monitoring-param:vdu-metric:vdu-metric-name-ref='{}' not defined" " at vdu[id='{}'] or vdu does not exist" .format(mp["vdu-metric-name-ref"], mp["vdu-ref"])), norm(str(e.exception)), "Wrong exception text") finally: del test_vnfd["monitoring-param"] del test_vnfd["vdu"][0]["vdu-configuration"] with self.subTest(i=17, t='Check Input Validation: scaling-group-descriptor[scaling-policy][scaling-criteria]'): test_vnfd["monitoring-param"] = [{"id": "fake-mp-id"}] test_vnfd["scaling-group-descriptor"] = [{ "name": "fake-vnf-sg-name", "vdu": [{"vdu-id-ref": "wrong-vdu-id-ref"}], "scaling-policy": [{"name": "fake-vnf-sp-name", "scaling-criteria": [{ "name": "fake-vnf-sc-name", "vnf-monitoring-param-ref": "wrong-vnf-mp-id"}]}]}] with self.assertRaises(EngineException, msg="Accepted non-existent Scaling Group Policy Criteria") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") sg = test_vnfd["scaling-group-descriptor"][0] sc = sg["scaling-policy"][0]["scaling-criteria"][0] self.assertIn(norm("scaling-group-descriptor[name='{}']:scaling-criteria[name='{}']:" "vnf-monitoring-param-ref='{}' not defined in any monitoring-param" .format(sg["name"], sc["name"], sc["vnf-monitoring-param-ref"])), norm(str(e.exception)), "Wrong exception text") with self.subTest(i=18, t='Check Input Validation: scaling-group-descriptor[vdu][vdu-id-ref]'): sc["vnf-monitoring-param-ref"] = "fake-mp-id" with self.assertRaises(EngineException, msg="Accepted non-existent Scaling Group VDU ID Reference") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("scaling-group-descriptor[name='{}']:vdu-id-ref={} does not match any vdu" .format(sg["name"], sg["vdu"][0]["vdu-id-ref"])), norm(str(e.exception)), "Wrong exception text") with self.subTest(i=19, t='Check Input Validation: scaling-group-descriptor[scaling-config-action]'): tmp = test_vnfd["vnf-configuration"] del test_vnfd["vnf-configuration"] sg["vdu"][0]["vdu-id-ref"] = test_vnfd["vdu"][0]["id"] sg["scaling-config-action"] = [{"trigger": "pre-scale-in"}] try: with self.assertRaises(EngineException, msg="Accepted non-existent Scaling Group VDU ID Reference")\ as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("'vnf-configuration' not defined in the descriptor but it is referenced" " by scaling-group-descriptor[name='{}']:scaling-config-action" .format(sg["name"])), norm(str(e.exception)), "Wrong exception text") finally: test_vnfd["vnf-configuration"] = tmp with self.subTest(i=20, t='Check Input Validation: scaling-group-descriptor[scaling-config-action]' '[vnf-config-primitive-name-ref]'): sg["scaling-config-action"][0]["vnf-config-primitive-name-ref"] = "wrong-sca-prim-name" with self.assertRaises(EngineException, msg="Accepted non-existent Scaling Group VDU ID Reference") as e: self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("scaling-group-descriptor[name='{}']:scaling-config-action:" "vnf-config-primitive-name-ref='{}' does not match" " any vnf-configuration:config-primitive:name" .format(sg["name"], sg["scaling-config-action"][0]["vnf-config-primitive-name-ref"])), norm(str(e.exception)), "Wrong exception text") # del test_vnfd["monitoring-param"] # del test_vnfd["scaling-group-descriptor"] with self.subTest(i=21, t='Check Input Validation: everything right'): sg["scaling-config-action"][0]["vnf-config-primitive-name-ref"] = "touch" test_vnfd["id"] = "fake-vnfd-id" self.db.get_one.side_effect = [{"_id": did, "_admin": db_vnfd_content["_admin"]}, None] rc = self.topic.upload_content(fake_session, did, test_vnfd, {}, {"Content-Type": []}) self.assertTrue(rc, "Input Validation: Unexpected failure") return def test_edit_vnfd(self): did = db_vnfd_content["_id"] self.fs.file_exists.return_value = True self.fs.dir_ls.return_value = True with self.subTest(i=1, t='Normal Edition'): now = time() self.db.get_one.side_effect = [db_vnfd_content, None] data = {"id": "new-vnfd-id", "name": "new-vnfd-name"} self.topic.edit(fake_session, did, data) db_args = self.db.replace.call_args[0] msg_args = self.msg.write.call_args[0] data["_id"] = did self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "edited", "Wrong message action") self.assertEqual(msg_args[2], data, "Wrong message content") self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1], did, "Wrong DB ID") self.assertEqual(db_args[2]["_admin"]["created"], db_vnfd_content["_admin"]["created"], "Wrong creation time") self.assertGreater(db_args[2]["_admin"]["modified"], now, "Wrong modification time") self.assertEqual(db_args[2]["_admin"]["projects_read"], db_vnfd_content["_admin"]["projects_read"], "Wrong read-only project list") self.assertEqual(db_args[2]["_admin"]["projects_write"], db_vnfd_content["_admin"]["projects_write"], "Wrong read-write project list") self.assertEqual(db_args[2]["id"], data["id"], "Wrong VNFD ID") self.assertEqual(db_args[2]["name"], data["name"], "Wrong VNFD Name") with self.subTest(i=2, t='Conflict on Edit'): data = {"id": "fake-vnfd-id", "name": "new-vnfd-name"} self.db.get_one.side_effect = [db_vnfd_content, {"_id": str(uuid4()), "id": data["id"]}] with self.assertRaises(EngineException, msg="Accepted existing VNFD ID") as e: self.topic.edit(fake_session, did, data) self.assertEqual(e.exception.http_code, HTTPStatus.CONFLICT, "Wrong HTTP status code") self.assertIn(norm("{} with id '{}' already exists for this project".format("vnfd", data["id"])), norm(str(e.exception)), "Wrong exception text") with self.subTest(i=3, t='Check Envelope'): data = {"vnfd": {"id": "new-vnfd-id-1", "name": "new-vnfd-name"}} with self.assertRaises(EngineException, msg="Accepted VNFD with wrong envelope") as e: self.topic.edit(fake_session, did, data) self.assertEqual(e.exception.http_code, HTTPStatus.BAD_REQUEST, "Wrong HTTP status code") self.assertIn("'vnfd' must be a list of only one element", norm(str(e.exception)), "Wrong exception text") return def test_delete_vnfd(self): did = db_vnfd_content["_id"] self.db.get_one.return_value = db_vnfd_content with self.subTest(i=1, t='Normal Deletion'): self.db.get_list.return_value = [] self.db.del_one.return_value = {"deleted": 1} self.topic.delete(fake_session, did) db_args = self.db.del_one.call_args[0] msg_args = self.msg.write.call_args[0] self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "deleted", "Wrong message action") self.assertEqual(msg_args[2], {"_id": did}, "Wrong message content") self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1]["_id"], did, "Wrong DB ID") self.assertEqual(db_args[1]["_admin.projects_read"], [[], ['ANY']], "Wrong DB filter") db_g1_args = self.db.get_one.call_args[0] self.assertEqual(db_g1_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_g1_args[1]["_id"], did, "Wrong DB VNFD ID") db_gl_calls = self.db.get_list.call_args_list self.assertEqual(db_gl_calls[0][0][0], "vnfrs", "Wrong DB topic") # self.assertEqual(db_gl_calls[0][0][1]["vnfd-id"], did, "Wrong DB VNFD ID") # Filter changed after call self.assertEqual(db_gl_calls[1][0][0], "nsds", "Wrong DB topic") self.assertEqual(db_gl_calls[1][0][1]["constituent-vnfd.ANYINDEX.vnfd-id-ref"], db_vnfd_content["id"], "Wrong DB NSD constituent-vnfd id-ref") db_s1_args = self.db.set_one.call_args self.assertEqual(db_s1_args[0][0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_s1_args[0][1]["_id"], did, "Wrong DB ID") self.assertIn(test_pid, db_s1_args[0][1]["_admin.projects_write.cont"], "Wrong DB filter") self.assertIsNone(db_s1_args[1]["update_dict"], "Wrong DB update dictionary") self.assertEqual(db_s1_args[1]["pull"]["_admin.projects_read"]["$in"], fake_session["project_id"], "Wrong DB pull dictionary") fs_del_calls = self.fs.file_delete.call_args_list self.assertEqual(fs_del_calls[0][0][0], did, "Wrong FS file id") self.assertEqual(fs_del_calls[1][0][0], did+'_', "Wrong FS folder id") with self.subTest(i=2, t='Conflict on Delete - VNFD in use by VNFR'): self.db.get_list.return_value = [{"_id": str(uuid4()), "name": "fake-vnfr"}] with self.assertRaises(EngineException, msg="Accepted VNFD in use by VNFR") as e: self.topic.delete(fake_session, did) self.assertEqual(e.exception.http_code, HTTPStatus.CONFLICT, "Wrong HTTP status code") self.assertIn("there is at least one vnf using this descriptor", norm(str(e.exception)), "Wrong exception text") with self.subTest(i=3, t='Conflict on Delete - VNFD in use by NSD'): self.db.get_list.side_effect = [[], [{"_id": str(uuid4()), "name": "fake-nsd"}]] with self.assertRaises(EngineException, msg="Accepted VNFD in use by NSD") as e: self.topic.delete(fake_session, did) self.assertEqual(e.exception.http_code, HTTPStatus.CONFLICT, "Wrong HTTP status code") self.assertIn("there is at least one nsd referencing this descriptor", norm(str(e.exception)), "Wrong exception text") with self.subTest(i=4, t='Non-existent VNFD'): excp_msg = "Not found any {} with filter='{}'".format("VNFD", {"_id": did}) self.db.get_one.side_effect = DbException(excp_msg, HTTPStatus.NOT_FOUND) with self.assertRaises(DbException, msg="Accepted non-existent VNFD ID") as e: self.topic.delete(fake_session, did) self.assertEqual(e.exception.http_code, HTTPStatus.NOT_FOUND, "Wrong HTTP status code") self.assertIn(norm(excp_msg), norm(str(e.exception)), "Wrong exception text") return class Test_NsdTopic(TestCase): @classmethod def setUpClass(cls): cls.test_name = "test-nsd-topic" @classmethod def tearDownClass(cls): pass def setUp(self): self.db = Mock(dbbase.DbBase()) self.fs = Mock(fsbase.FsBase()) self.msg = Mock(msgbase.MsgBase()) self.auth = Mock(authconn.Authconn(None, None, None)) self.topic = NsdTopic(self.db, self.fs, self.msg, self.auth) def test_new_nsd(self): did = db_nsd_content["_id"] self.fs.get_params.return_value = {} self.fs.file_exists.return_value = False self.fs.file_open.side_effect = lambda path, mode: open("/tmp/" + str(uuid4()), "a+b") test_nsd = deepcopy(db_nsd_content) del test_nsd["_id"] del test_nsd["_admin"] with self.subTest(i=1, t='Normal Creation'): self.db.create.return_value = did rollback = [] did2, oid = self.topic.new(rollback, fake_session, {}) db_args = self.db.create.call_args[0] msg_args = self.msg.write.call_args[0] self.assertEqual(len(rollback), 1, "Wrong rollback length") self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "created", "Wrong message action") self.assertEqual(msg_args[2], {"_id": did}, "Wrong message content") self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(did2, did, "Wrong DB NSD id") self.assertIsNotNone(db_args[1]["_admin"]["created"], "Wrong creation time") self.assertEqual(db_args[1]["_admin"]["modified"], db_args[1]["_admin"]["created"], "Wrong modification time") self.assertEqual(db_args[1]["_admin"]["projects_read"], [test_pid], "Wrong read-only project list") self.assertEqual(db_args[1]["_admin"]["projects_write"], [test_pid], "Wrong read-write project list") try: self.db.get_one.side_effect = [{"_id": did, "_admin": db_nsd_content["_admin"]}, None] self.db.get_list.return_value = [db_vnfd_content] self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) msg_args = self.msg.write.call_args[0] test_nsd["_id"] = did self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "edited", "Wrong message action") self.assertEqual(msg_args[2], test_nsd, "Wrong message content") db_args = self.db.get_one.mock_calls[0][1] self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1]["_id"], did, "Wrong DB NSD id") db_args = self.db.replace.call_args[0] self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1], did, "Wrong DB NSD id") admin = db_args[2]["_admin"] db_admin = db_nsd_content["_admin"] self.assertEqual(admin["created"], db_admin["created"], "Wrong creation time") self.assertGreater(admin["modified"], db_admin["created"], "Wrong modification time") self.assertEqual(admin["projects_read"], db_admin["projects_read"], "Wrong read-only project list") self.assertEqual(admin["projects_write"], db_admin["projects_write"], "Wrong read-write project list") self.assertEqual(admin["onboardingState"], "ONBOARDED", "Wrong onboarding state") self.assertEqual(admin["operationalState"], "ENABLED", "Wrong operational state") self.assertEqual(admin["usageState"], "NOT_IN_USE", "Wrong usage state") storage = admin["storage"] self.assertEqual(storage["folder"], did, "Wrong storage folder") self.assertEqual(storage["descriptor"], "package", "Wrong storage descriptor") compare_desc(self, test_nsd, db_args[2], "NSD") finally: pass self.db.get_one.side_effect = lambda table, filter, fail_on_empty=None, fail_on_more=None:\ {"_id": did, "_admin": db_nsd_content["_admin"]} with self.subTest(i=2, t='Check Pyangbind Validation: required properties'): tmp = test_nsd["id"] del test_nsd["id"] try: with self.assertRaises(EngineException, msg="Accepted NSD with a missing required property") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error in pyangbind validation: '{}'".format("id")), norm(str(e.exception)), "Wrong exception text") finally: test_nsd["id"] = tmp with self.subTest(i=3, t='Check Pyangbind Validation: additional properties'): test_nsd["extra-property"] = 0 try: with self.assertRaises(EngineException, msg="Accepted NSD with an additional property") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error in pyangbind validation: {} ({})" .format("json object contained a key that did not exist", "extra-property")), norm(str(e.exception)), "Wrong exception text") finally: del test_nsd["extra-property"] with self.subTest(i=4, t='Check Pyangbind Validation: property types'): tmp = test_nsd["short-name"] test_nsd["short-name"] = {"key": 0} try: with self.assertRaises(EngineException, msg="Accepted NSD with a wrongly typed property") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error in pyangbind validation: {} ({})" .format("json object contained a key that did not exist", "key")), norm(str(e.exception)), "Wrong exception text") finally: test_nsd["short-name"] = tmp with self.subTest(i=5, t='Check Input Validation: vld[mgmt-network+ip-profile]'): tmp = test_nsd["vld"][0]["vim-network-name"] del test_nsd["vld"][0]["vim-network-name"] test_nsd["vld"][0]["ip-profile-ref"] = "fake-ip-profile" try: with self.assertRaises(EngineException, msg="Accepted VLD with mgmt-network+ip-profile") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error at vld[id='{}']:ip-profile-ref" " You cannot set an ip-profile when mgmt-network is True" .format(test_nsd["vld"][0]["id"])), norm(str(e.exception)), "Wrong exception text") finally: test_nsd["vld"][0]["vim-network-name"] = tmp del test_nsd["vld"][0]["ip-profile-ref"] with self.subTest(i=6, t='Check Input Validation: vld[vnfd-connection-point-ref][vnfd-id-ref]'): tmp = test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["vnfd-id-ref"] test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["vnfd-id-ref"] = "wrong-vnfd-id-ref" try: with self.assertRaises(EngineException, msg="Accepted VLD with wrong vnfd-connection-point-ref") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error at vld[id='{}']:vnfd-connection-point-ref[vnfd-id-ref='{}']" " does not match constituent-vnfd[member-vnf-index='{}']:vnfd-id-ref '{}'" .format(test_nsd["vld"][0]["id"], test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["vnfd-id-ref"], test_nsd["constituent-vnfd"][0]["member-vnf-index"], test_nsd["constituent-vnfd"][0]["vnfd-id-ref"])), norm(str(e.exception)), "Wrong exception text") finally: test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["vnfd-id-ref"] = tmp with self.subTest(i=7, t='Check Input Validation: vld[vnfd-connection-point-ref][member-vnf-index-ref]'): tmp = test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["member-vnf-index-ref"] test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["member-vnf-index-ref"] = "wrong-member-vnf-index-ref" try: with self.assertRaises(EngineException, msg="Accepted VLD with wrong vnfd-connection-point-ref") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error at vld[id='{}']:vnfd-connection-point-ref[member-vnf-index-ref='{}']" " does not match any constituent-vnfd:member-vnf-index" .format(test_nsd["vld"][0]["id"], test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["member-vnf-index-ref"])), norm(str(e.exception)), "Wrong exception text") finally: test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["member-vnf-index-ref"] = tmp with self.subTest(i=8, t='Check Input Validation: vnffgd[classifier][rsp-id-ref]'): test_nsd["vnffgd"] = [{"id": "fake-vnffgd-id", "rsp": [{"id": "fake-rsp-id"}], "classifier": [{"id": "fake-vnffgd-classifier-id", "rsp-id-ref": "wrong-rsp-id"}]}] try: with self.assertRaises(EngineException, msg="Accepted VNF FGD with wrong classifier rsp-id-ref") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error at vnffgd[id='{}']:classifier[id='{}']:rsp-id-ref '{}'" " does not match any rsp:id" .format(test_nsd["vnffgd"][0]["id"], test_nsd["vnffgd"][0]["classifier"][0]["id"], test_nsd["vnffgd"][0]["classifier"][0]["rsp-id-ref"])), norm(str(e.exception)), "Wrong exception text") finally: test_nsd["vnffgd"][0]["classifier"][0]["rsp-id-ref"] = "fake-rsp-id" with self.subTest(i=9, t='Check Descriptor Dependencies: constituent-vnfd[vnfd-id-ref]'): self.db.get_one.side_effect = [{"_id": did, "_admin": db_nsd_content["_admin"]}, None] self.db.get_list.return_value = [] try: with self.assertRaises(EngineException, msg="Accepted wrong constituent VNFD ID reference") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.CONFLICT, "Wrong HTTP status code") self.assertIn(norm("Descriptor error at 'constituent-vnfd':'vnfd-id-ref'='{}'" " references a non existing vnfd" .format(test_nsd["constituent-vnfd"][0]["vnfd-id-ref"])), norm(str(e.exception)), "Wrong exception text") finally: pass with self.subTest(i=10, t='Check Descriptor Dependencies: ' 'vld[vnfd-connection-point-ref][vnfd-connection-point-ref]'): tmp = test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["vnfd-connection-point-ref"] test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["vnfd-connection-point-ref"] = "wrong-vnfd-cp-ref" self.db.get_one.side_effect = [{"_id": did, "_admin": db_nsd_content["_admin"]}, None] self.db.get_list.return_value = [db_vnfd_content] try: with self.assertRaises(EngineException, msg="Accepted wrong VLD CP reference") as e: self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertEqual(e.exception.http_code, HTTPStatus.UNPROCESSABLE_ENTITY, "Wrong HTTP status code") self.assertIn(norm("Error at vld[id='{}']:vnfd-connection-point-ref[member-vnf-index-ref='{}']:" "vnfd-connection-point-ref='{}' references a non existing conection-point:name" " inside vnfd '{}'" .format(test_nsd["vld"][0]["id"], test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["member-vnf-index-ref"], test_nsd["vld"][0]["vnfd-connection-point-ref"][0] ["vnfd-connection-point-ref"], db_vnfd_content["id"])), norm(str(e.exception)), "Wrong exception text") finally: test_nsd["vld"][0]["vnfd-connection-point-ref"][0]["vnfd-connection-point-ref"] = tmp return with self.subTest(i=11, t='Check Input Validation: everything right'): test_nsd["id"] = "fake-nsd-id" self.db.get_one.side_effect = [{"_id": did, "_admin": db_nsd_content["_admin"]}, None] self.db.get_list.return_value = [db_vnfd_content] rc = self.topic.upload_content(fake_session, did, test_nsd, {}, {"Content-Type": []}) self.assertTrue(rc, "Input Validation: Unexpected failure") return def test_edit_nsd(self): did = db_nsd_content["_id"] self.fs.file_exists.return_value = True self.fs.dir_ls.return_value = True with self.subTest(i=1, t='Normal Edition'): now = time() self.db.get_one.side_effect = [db_nsd_content, None] self.db.get_list.return_value = [db_vnfd_content] data = {"id": "new-nsd-id", "name": "new-nsd-name"} self.topic.edit(fake_session, did, data) db_args = self.db.replace.call_args[0] msg_args = self.msg.write.call_args[0] data["_id"] = did self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "edited", "Wrong message action") self.assertEqual(msg_args[2], data, "Wrong message content") self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1], did, "Wrong DB ID") self.assertEqual(db_args[2]["_admin"]["created"], db_nsd_content["_admin"]["created"], "Wrong creation time") self.assertGreater(db_args[2]["_admin"]["modified"], now, "Wrong modification time") self.assertEqual(db_args[2]["_admin"]["projects_read"], db_nsd_content["_admin"]["projects_read"], "Wrong read-only project list") self.assertEqual(db_args[2]["_admin"]["projects_write"], db_nsd_content["_admin"]["projects_write"], "Wrong read-write project list") self.assertEqual(db_args[2]["id"], data["id"], "Wrong NSD ID") self.assertEqual(db_args[2]["name"], data["name"], "Wrong NSD Name") with self.subTest(i=2, t='Conflict on Edit'): data = {"id": "fake-nsd-id", "name": "new-nsd-name"} self.db.get_one.side_effect = [db_nsd_content, {"_id": str(uuid4()), "id": data["id"]}] with self.assertRaises(EngineException, msg="Accepted existing NSD ID") as e: self.topic.edit(fake_session, did, data) self.assertEqual(e.exception.http_code, HTTPStatus.CONFLICT, "Wrong HTTP status code") self.assertIn(norm("{} with id '{}' already exists for this project".format("nsd", data["id"])), norm(str(e.exception)), "Wrong exception text") with self.subTest(i=3, t='Check Envelope'): data = {"nsd": {"id": "new-nsd-id", "name": "new-nsd-name"}} with self.assertRaises(EngineException, msg="Accepted NSD with wrong envelope") as e: self.topic.edit(fake_session, did, data) self.assertEqual(e.exception.http_code, HTTPStatus.BAD_REQUEST, "Wrong HTTP status code") self.assertIn("'nsd' must be a list of only one element", norm(str(e.exception)), "Wrong exception text") return def test_delete_nsd(self): did = db_nsd_content["_id"] self.db.get_one.return_value = db_nsd_content with self.subTest(i=1, t='Normal Deletion'): self.db.get_list.return_value = [] self.db.del_one.return_value = {"deleted": 1} self.topic.delete(fake_session, did) db_args = self.db.del_one.call_args[0] msg_args = self.msg.write.call_args[0] self.assertEqual(msg_args[0], self.topic.topic_msg, "Wrong message topic") self.assertEqual(msg_args[1], "deleted", "Wrong message action") self.assertEqual(msg_args[2], {"_id": did}, "Wrong message content") self.assertEqual(db_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_args[1]["_id"], did, "Wrong DB ID") self.assertEqual(db_args[1]["_admin.projects_read"], [[], ['ANY']], "Wrong DB filter") db_g1_args = self.db.get_one.call_args[0] self.assertEqual(db_g1_args[0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_g1_args[1]["_id"], did, "Wrong DB NSD ID") db_gl_calls = self.db.get_list.call_args_list self.assertEqual(db_gl_calls[0][0][0], "nsrs", "Wrong DB topic") # self.assertEqual(db_gl_calls[0][0][1]["nsd-id"], did, "Wrong DB NSD ID") # Filter changed after call self.assertEqual(db_gl_calls[1][0][0], "nsts", "Wrong DB topic") self.assertEqual(db_gl_calls[1][0][1]["netslice-subnet.ANYINDEX.nsd-ref"], db_nsd_content["id"], "Wrong DB NSD netslice-subnet nsd-ref") db_s1_args = self.db.set_one.call_args self.assertEqual(db_s1_args[0][0], self.topic.topic, "Wrong DB topic") self.assertEqual(db_s1_args[0][1]["_id"], did, "Wrong DB ID") self.assertIn(test_pid, db_s1_args[0][1]["_admin.projects_write.cont"], "Wrong DB filter") self.assertIsNone(db_s1_args[1]["update_dict"], "Wrong DB update dictionary") self.assertEqual(db_s1_args[1]["pull"]["_admin.projects_read"]["$in"], fake_session["project_id"], "Wrong DB pull dictionary") fs_del_calls = self.fs.file_delete.call_args_list self.assertEqual(fs_del_calls[0][0][0], did, "Wrong FS file id") self.assertEqual(fs_del_calls[1][0][0], did+'_', "Wrong FS folder id") return # TO REMOVE with self.subTest(i=2, t='Conflict on Delete - NSD in use by nsr'): self.db.get_list.return_value = [{"_id": str(uuid4()), "name": "fake-nsr"}] with self.assertRaises(EngineException, msg="Accepted NSD in use by NSR") as e: self.topic.delete(fake_session, did) self.assertEqual(e.exception.http_code, HTTPStatus.CONFLICT, "Wrong HTTP status code") self.assertIn("there is at least one ns using this descriptor", norm(str(e.exception)), "Wrong exception text") with self.subTest(i=3, t='Conflict on Delete - NSD in use by NST'): self.db.get_list.side_effect = [[], [{"_id": str(uuid4()), "name": "fake-nst"}]] with self.assertRaises(EngineException, msg="Accepted NSD in use by NST") as e: self.topic.delete(fake_session, did) self.assertEqual(e.exception.http_code, HTTPStatus.CONFLICT, "Wrong HTTP status code") self.assertIn("there is at least one netslice template referencing this descriptor", norm(str(e.exception)), "Wrong exception text") with self.subTest(i=4, t='Non-existent NSD'): excp_msg = "Not found any {} with filter='{}'".format("NSD", {"_id": did}) self.db.get_one.side_effect = DbException(excp_msg, HTTPStatus.NOT_FOUND) with self.assertRaises(DbException, msg="Accepted non-existent NSD ID") as e: self.topic.delete(fake_session, did) self.assertEqual(e.exception.http_code, HTTPStatus.NOT_FOUND, "Wrong HTTP status code") self.assertIn(norm(excp_msg), norm(str(e.exception)), "Wrong exception text") return if __name__ == '__main__': unittest.main()

68.719706

120

0.585174

6,844

56,144

4.668469

0.065167

0.066195

0.028732

0.023035

0.874621

0.840819

0.81697

0.796125

0.766017

0.733592

0

0.009644

0.268648

56,144

816

121

68.803922

0.768491

0.024028

0

0.551451

0

0.003958

0.297193

0.061675

0

0.300792

1

0.01847

false

0.005277

0.01847

0

0.051451

0

null

0

1

0

null

0

6

91f94cb8899bc5a2c28e3da16e4835cedf777204

155

py

Python

mainapp/admin.py

DBarthe/chatbox

f0a467cb5c24594e1bad14cc0f2c94a91a57ff48

[ "MIT" ]

null

mainapp/admin.py

DBarthe/chatbox

f0a467cb5c24594e1bad14cc0f2c94a91a57ff48

[ "MIT" ]

null

mainapp/admin.py

DBarthe/chatbox

f0a467cb5c24594e1bad14cc0f2c94a91a57ff48

[ "MIT" ]

null

from django.contrib import admin from .models import Message class MessageAdmin(admin.ModelAdmin): pass admin.site.register(Message, MessageAdmin)

15.5

42

0.793548

19

155

6.473684

0.684211

0

0.135484

155

9

43

17.222222

0.91791

0

1

0

true

0.2

0.4

0

0.6

0

1

0

null

0

1

0

null

0

1

0

1

0

6

6207946af6e25d6cfcbffae495c23d8e40decda2

29

py

Python

registry/signup/__init__.py

HTPhenotyping/registration

07d224e6bc537c20f9428e81bbac09bad012d64c

[ "Apache-2.0" ]

null

registry/signup/__init__.py

HTPhenotyping/registration

07d224e6bc537c20f9428e81bbac09bad012d64c

[ "Apache-2.0" ]

46

2020-05-11T14:20:41.000Z

2020-09-18T18:15:17.000Z

registry/signup/__init__.py

HTPhenotyping/registration

07d224e6bc537c20f9428e81bbac09bad012d64c

[ "Apache-2.0" ]

null

from .views import signup_bp

14.5

28

0.827586

5

29

4.6

1

0

0.137931

29

1

29

0.92

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

6260edef6b6eefb3032d565eaed97623b61ccbcd

2,222

py

Python

tests/resources/test_wallets.py

danielcoker/embedpy

6af5a794a50e3b9b03efb03eadb0ba46dca2cd8d

[ "MIT" ]

null

tests/resources/test_wallets.py

danielcoker/embedpy

6af5a794a50e3b9b03efb03eadb0ba46dca2cd8d

[ "MIT" ]

1

2022-01-12T14:13:39.000Z

2022-01-12T14:35:43.000Z

tests/resources/test_wallets.py

danielcoker/embedpy

6af5a794a50e3b9b03efb03eadb0ba46dca2cd8d

[ "MIT" ]

2

2021-07-15T11:16:29.000Z

2022-03-28T01:07:31.000Z

from embed.resources.wallet import Wallet from unittest.mock import MagicMock, patch import json @patch("embed.common.APIResponse.get_essential_details") def test_can_get_wallets(mock_get_essential_details, api_session): wallet = Wallet(api_session) mock_get_essential_details.return_value = MagicMock() wallet.list_wallets() wallet.get_essential_details.assert_called_with( "GET", f"{api_session.base_url}/api/{api_session.api_version}/wallets", ) @patch("embed.common.APIResponse.get_essential_details") def test_can_get_single_wallet(mock_get_essential_details, api_session): wallet = Wallet(api_session) mock_get_essential_details.return_value = MagicMock() wallet.get_wallet("fake-id") wallet.get_essential_details.assert_called_with( "GET", f"{api_session.base_url}/api/{api_session.api_version}/wallets/fake-id", ) @patch("embed.common.APIResponse.get_essential_details") def test_can_create_wallet(mock_get_essential_details, api_session): wallet = Wallet(api_session) mock_get_essential_details.return_value = MagicMock() test_data = {"account_id": "fake-id", "currency_code": "NGN"} wallet.create_wallet( account_id=test_data.get("account_id"), currency_code=test_data.get("currency_code"), ) wallet.get_essential_details.assert_called_with( "POST", f"{api_session.base_url}/api/{api_session.api_version}/wallets", json.dumps(test_data), ) @patch("embed.common.APIResponse.get_essential_details") def test_can_transfer(mock_get_essential_details, api_session): wallet = Wallet(api_session) mock_get_essential_details.return_value = MagicMock() test_data = { "wallet_id": "fake-id", "product_code": "PRCD", "amount": "100000", } wallet.transfer( wallet_id=test_data.get("wallet_id"), product_code=test_data.get("product_code"), amount=test_data.get("amount"), ) wallet.get_essential_details.assert_called_with( "POST", f"{api_session.base_url}/api/{api_session.api_version}/wallets/fake-id/transfer", json.dumps({"product_code": "PRCD", "amount": "100000"}), )

35.269841

89

0.720972

288

2,222

5.173611

0.163194

0.128859

0.204027

0.12349

0.736913

0.700671

0

0.006414

0.157966

2,222

62

90

35.83871

0.789952

0

0.407407

0

0.281278

0.20207

0

0.074074

1

0.074074

false

0

0.055556

0

0.12963

0

null

0

1

0

1

0

null

0

6

627e1ccdf29677cc3b8227775fcbdd7a3441ce36

27

py

Python

code/model/__init__.py

wukailu/EDSR-PyTorch

5625cf83ce88050b68e649beb4155b32c38018fa

[ "MIT" ]

74

2020-03-08T15:29:00.000Z

2022-03-05T14:57:33.000Z

code/model/__init__.py

wukailu/EDSR-PyTorch

5625cf83ce88050b68e649beb4155b32c38018fa

[ "MIT" ]

19

2020-03-06T08:56:51.000Z

2022-03-27T05:07:35.000Z

code/model/__init__.py

wukailu/EDSR-PyTorch

5625cf83ce88050b68e649beb4155b32c38018fa

[ "MIT" ]

23

2020-03-20T08:19:55.000Z

2022-03-16T17:40:09.000Z

from .model_utils import *

13.5

26

0.777778

4

27

5

1

0

0.148148

27

1

27

0.869565

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

6550cd169424597d8ffd211318ef2b3ff2d55504

14

py

Python

login.py

fmk-0309/git_ssh

c0122f61ca62143172b20646897d173bb6207da3

[ "MIT" ]

3

2018-09-27T07:27:13.000Z

2019-04-02T13:39:03.000Z

login.py

fmk-0309/git_ssh

c0122f61ca62143172b20646897d173bb6207da3

[ "MIT" ]

null

login.py

fmk-0309/git_ssh

c0122f61ca62143172b20646897d173bb6207da3

[ "MIT" ]

null

a = 10 b = 20

4.666667

6

0.428571

4

14

1.5

1

0

0.5

0.428571

14

2

7

0.25

0

1

0

false

0

1

null

0

1

0

1

0

1

0

null

0

6

65894989dfdbf1aceef7deb331666e5d3466ba07

47

py

Python

scan_models/niagara/__init__.py

ssdemajia/ids-backend

188af247befa44596f62c660c24b05474d1ba29f

[ "MIT" ]

1

2020-05-22T09:52:33.000Z

scan_models/niagara/__init__.py

ssdemajia/ids-backend

188af247befa44596f62c660c24b05474d1ba29f

[ "MIT" ]

8

2021-03-18T21:22:40.000Z

2022-03-11T23:32:48.000Z

scan_models/niagara/__init__.py

ssdemajia/ids-backend

188af247befa44596f62c660c24b05474d1ba29f

[ "MIT" ]

null

from .scan import niagara_resolve, niagara_scan

47

0.87234

7

47

5.571429

0.714286

0

0.085106

47

1

47

0.906977

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

65a52c09452b8d62f53f896d08045672061495c1

44

py

Python

hs/__init__.py

Fawers/horriblesubs-hourly-notifier

b8c610d9fdd6494976e00e5a7fad746013669280

[ "MIT" ]

10

2019-01-14T10:24:53.000Z

2022-03-29T02:39:09.000Z

hs/__init__.py

Fawers/horriblesubs-hourly-notifier

b8c610d9fdd6494976e00e5a7fad746013669280

[ "MIT" ]

null

hs/__init__.py

Fawers/horriblesubs-hourly-notifier

b8c610d9fdd6494976e00e5a7fad746013669280

[ "MIT" ]

null

from . import rss, frontpage, links # noqa

22

43

0.704545

6

44

5.166667

1

0

0.204545

44

1

44

0.885714

0.090909

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

65ddf8e65929af3f40881f87fcf1bbb545ce5239

49

py

Python

test.py

ellastyko/Widowmaker-1917-1922

2d9d2b8f273ea210997223193b6b9426ada3d738

[ "MIT" ]

null

test.py

ellastyko/Widowmaker-1917-1922

2d9d2b8f273ea210997223193b6b9426ada3d738

[ "MIT" ]

null

test.py

ellastyko/Widowmaker-1917-1922

2d9d2b8f273ea210997223193b6b9426ada3d738

[ "MIT" ]

null

from config import Config print(Config.BASEDIR)

12.25

25

0.816327

7

49

5.714286

0.714286

0

0.122449

49

3

26

16.333333

0.930233

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

65e3f279390edc9cb38d4856ec86ef2938ac77e6

12,157

py

Python

GoogleDorker.py

artech-git/GHDB-googleDorker

e238b9f11deee119ea493c80d5636ec74dd1776b

[ "MIT" ]

null

GoogleDorker.py

artech-git/GHDB-googleDorker

e238b9f11deee119ea493c80d5636ec74dd1776b

[ "MIT" ]

null

GoogleDorker.py

artech-git/GHDB-googleDorker

e238b9f11deee119ea493c80d5636ec74dd1776b

[ "MIT" ]

1

2020-08-17T00:10:37.000Z

#!usr/bin/env python3 import requests import re import optparse import subprocess import time def get_arguments(): parser = optparse.OptionParser() parser.add_option("-u", "--url", dest="url", help="Target URL") parser.add_option('-m', '--manual', help="Enables manual mode", action="store_true") (option, arguments) = parser.parse_args() if not option.url: parser.error("[-] Please specify an URL, use --help for more info") return option options = get_arguments() url = options.url print("\n\n") subprocess.call(["chmod", "777", url + ".html"]) subprocess.call(["rm", url + ".html"]) subprocess.call(["clear"]) #--------------------------------------------------------------------------------------------------------------------------------- print(" ______ _ _____ _ ") print(" / _____) | | (____ \ | | ") print(" | / ___ ___ ___ ____ | | ____ _ \ \ ___ ____ | | _ ____ ____ ") print(" | | (___) / _ \ / _ \ / _ || | / _ )| | | | / _ \ / ___)| | / ) / _ ) / ___)") print(" | \____/|| |_| || |_| |( ( | || |( (/ / | |__/ / | |_| || | | |< ( ( (/ / | | ") print(" \_____/ \___/ \___/ \_|| ||_| \____)|_____/ \___/ |_| |_| \_) \____)|_| ") print(" (_____| ") print("\n\n") #-------------------------------------------------------------------------------------------------------------------------------- f = open(str(url) + ".html", "at") f.write( '<!DOCTYPE html><html lang="en"><head><meta charset="utf-8"> <title>Results from GoogleDorker by nerrorsec</title> </head> <body><br>') if options.manual: def manual(): global f print("[+]Registering data into the file.\n") time.sleep(2) f.write("<h2>Manual mode - Check the links manually.</h2>") f.write("<br>") f.write('<h2>Possible Directory listing</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+intitle:index.of&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>Possible Configuration files</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+ext:xml+|+ext:conf+|+ext:cnf+|+ext:reg+|+ext:inf+|+ext:rdp+|+ext:cfg+|+ext:txt+|+ext:ora+|+ext:ini&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>Possible Database files</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+ext:sql+|+ext:dbf+|+ext:mdb&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>Possible Log files</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+ext:log&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>Possible Backup and Old files</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+ext:bkf+|+ext:bkp+|+ext:bak+|+ext:old+|+ext:backup&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>Possible Login pages</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+inurl:login&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>Possible SQL Errors</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+intext:%22sql+syntax+near%22+|+intext:%22syntax+error+has+occurred%22+|+intext:%22incorrect+syntax+near%22+|+intext:%22unexpected+end+of+SQL+command%22+|+intext:%22Warning:+mysql_connect()%22+|+intext:%22Warning:+mysql_query()%22+|+intext:%22Warning:+pg_connect()%22&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>Possible Publicly Exposed Documents</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+ext:doc+|+ext:docx+|+ext:odt+|+ext:pdf+|+ext:rtf+|+ext:sxw+|+ext:psw+|+ext:ppt+|+ext:pptx+|+ext:pps+|+ext:csv&hl=en">Click Here</a>') f.write("<br>") f.write('<h2>phpinfo()</h2>') f.write('<a href="https://www.google.com/search?q=site:'+ url +'+ext:php+intitle:phpinfo+%22published+by+the+PHP+Group%22&hl=en">Click Here</a>') f.write("<br>") f.close() print("File successfully created.\n") manual() else: def process_google(): global f print("Dorking via Google") print("\n") f.write("<h1>Results from Google</h1>") f.write("<br>") print ("[#]Checking for Directory listing vulnerabilities") requesturl = 'https://www.google.com/search?q=site:'+ url +'+intitle:index.of&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible Directory listing</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print ("[#]Checking for Configuration files exposed") requesturl = 'https://www.google.com/search?q=site:'+ url +'+ext:xml+|+ext:conf+|+ext:cnf+|+ext:reg+|+ext:inf+|+ext:rdp+|+ext:cfg+|+ext:txt+|+ext:ora+|+ext:ini&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible Configuration files</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print ("[#]Checking for Database files exposed") requesturl = 'https://www.google.com/search?q=site:'+ url +'+ext:sql+|+ext:dbf+|+ext:mdb&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible Database files</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print ("[#]Checking for Log files exposed") requesturl = 'https://www.google.com/search?q=site:'+ url +'+ext:log&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible Log files</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print ("[#]Checking for Backup and old files") requesturl = 'https://www.google.com/search?q=site:'+ url +'+ext:bkf+|+ext:bkp+|+ext:bak+|+ext:old+|+ext:backup&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible Backup and Old files</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print ("[#]Checking for Login pages") requesturl = 'https://www.google.com/search?q=site:'+ url +'+inurl:login&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible Login pages</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print ("[#]Checking for SQL errors") requesturl = 'https://www.google.com/search?q=site:'+ url +'+intext:%22sql+syntax+near%22+|+intext:%22syntax+error+has+occurred%22+|+intext:%22incorrect+syntax+near%22+|+intext:%22unexpected+end+of+SQL+command%22+|+intext:%22Warning:+mysql_connect()%22+|+intext:%22Warning:+mysql_query()%22+|+intext:%22Warning:+pg_connect()%22&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible SQL Errors</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print("[#]Checking for Publicly exposed documents ") requesturl = 'https://www.google.com/search?q=site:'+ url +'+ext:doc+|+ext:docx+|+ext:odt+|+ext:pdf+|+ext:rtf+|+ext:sxw+|+ext:psw+|+ext:ppt+|+ext:pptx+|+ext:pps+|+ext:csv&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>Possible Publicly Exposed Documents</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") print("[#]Checking for phpinfo() ") requesturl = 'https://www.google.com/search?q=site:'+ url +'+ext:php+intitle:phpinfo+%22published+by+the+PHP+Group%22&hl=en' response = requests.get(requesturl) notfound = re.search('\s-\sdid not match any documents.', response.text) captcha = re.search(',\ssolving the above CAPTCHA will let you continue\s', response.text) if notfound: print("[-]No results found\n") elif captcha: print("[-]Captcha triggered. Please try after some time.\n") else: print("[+]Registering data into the file.\n") f.write('<h2>phpinfo()</h2>') f.write('<a href="' + requesturl + '">Click Here</a>') f.write("<br>") f.close() process_google()

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null

0

1

0

null

0

6

02c07dc9c7f18ffb84f402d85b98df384f7004f6

216

py

Python

tests/data/plugins_project/libs/multiple_plugin_files/plugins/handlers.py

inmanta/inmanta-core

ae2153d57f124d00ad1b58e6d4bc6818364be4a8

[ "Apache-2.0" ]

6

2021-03-09T10:24:02.000Z

2022-01-16T03:52:11.000Z

tests/data/plugins_project/libs/multiple_plugin_files/plugins/handlers.py

inmanta/inmanta-core

ae2153d57f124d00ad1b58e6d4bc6818364be4a8

[ "Apache-2.0" ]

1,319

2020-12-18T08:52:29.000Z

2022-03-31T18:17:32.000Z

tests/data/plugins_project/libs/multiple_plugin_files/plugins/handlers.py

inmanta/inmanta-core

ae2153d57f124d00ad1b58e6d4bc6818364be4a8

[ "Apache-2.0" ]

4

2021-03-03T15:36:50.000Z

2022-03-11T11:41:51.000Z

from inmanta.agent.handler import ResourceHandler, provider from inmanta_plugins.multiple_plugin_files.helpers import helper @provider("std::Directory", name="myhandler") class MyHandler(ResourceHandler): pass

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0

1

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6

02c33c0602a6a04145c3ecdff47775fcd5dfeafb

24,201

py

Python

src/parser/PyxellLexer.py

ThatXliner/Pyxell

72c58fd26fe1eded038ba5bf11c327c9b33cdd31

[ "MIT" ]

null

src/parser/PyxellLexer.py

ThatXliner/Pyxell

72c58fd26fe1eded038ba5bf11c327c9b33cdd31

[ "MIT" ]

null

src/parser/PyxellLexer.py

ThatXliner/Pyxell

72c58fd26fe1eded038ba5bf11c327c9b33cdd31

[ "MIT" ]

null

# Generated from Pyxell.g4 by ANTLR 4.9.1 from antlr4 import * from io import StringIO from typing.io import TextIO import sys def serializedATN(): with StringIO() as buf: buf.write("\3\u608b\ua72a\u8133\ub9ed\u417c\u3be7\u7786\u5964\2S") buf.write("\u025d\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6\t\6\4\7") buf.write("\t\7\4\b\t\b\4\t\t\t\4\n\t\n\4\13\t\13\4\f\t\f\4\r\t\r") buf.write("\4\16\t\16\4\17\t\17\4\20\t\20\4\21\t\21\4\22\t\22\4\23") buf.write("\t\23\4\24\t\24\4\25\t\25\4\26\t\26\4\27\t\27\4\30\t\30") buf.write("\4\31\t\31\4\32\t\32\4\33\t\33\4\34\t\34\4\35\t\35\4\36") buf.write("\t\36\4\37\t\37\4 \t \4!\t!\4\"\t\"\4#\t#\4$\t$\4%\t%") buf.write("\4&\t&\4\'\t\'\4(\t(\4)\t)\4*\t*\4+\t+\4,\t,\4-\t-\4.") buf.write("\t.\4/\t/\4\60\t\60\4\61\t\61\4\62\t\62\4\63\t\63\4\64") buf.write("\t\64\4\65\t\65\4\66\t\66\4\67\t\67\48\t8\49\t9\4:\t:") buf.write("\4;\t;\4<\t<\4=\t=\4>\t>\4?\t?\4@\t@\4A\tA\4B\tB\4C\t") buf.write("C\4D\tD\4E\tE\4F\tF\4G\tG\4H\tH\4I\tI\4J\tJ\4K\tK\4L\t") buf.write("L\4M\tM\4N\tN\4O\tO\4P\tP\4Q\tQ\4R\tR\4S\tS\4T\tT\4U\t") buf.write("U\4V\tV\4W\tW\4X\tX\4Y\tY\4Z\tZ\3\2\3\2\3\3\3\3\3\4\3") buf.write("\4\3\5\3\5\3\5\3\5\3\6\3\6\3\6\3\6\3\6\3\6\3\6\3\7\3\7") buf.write("\3\7\3\7\3\7\3\b\3\b\3\b\3\b\3\b\3\b\3\t\3\t\3\n\3\n\3") buf.write("\13\3\13\3\f\3\f\3\r\3\r\3\r\3\16\3\16\3\17\3\17\3\17") buf.write("\3\20\3\20\3\21\3\21\3\22\3\22\3\23\3\23\3\24\3\24\3\25") buf.write("\3\25\3\25\3\26\3\26\3\26\3\26\3\26\3\26\3\27\3\27\3\27") buf.write("\3\27\3\27\3\27\3\27\3\27\3\27\3\30\3\30\3\30\3\30\3\30") buf.write("\3\30\3\30\3\31\3\31\3\31\3\31\3\31\3\31\3\32\3\32\3\32") buf.write("\3\33\3\33\3\33\3\34\3\34\3\34\3\34\3\34\3\35\3\35\3\35") buf.write("\3\35\3\35\3\36\3\36\3\36\3\36\3\36\3\36\3\37\3\37\3\37") buf.write("\3\37\3\37\3\37\3 \3 \3 \3 \3 \3 \3!\3!\3!\3!\3\"\3\"") buf.write("\3\"\3#\3#\3#\3#\3$\3$\3$\3$\3$\3$\3$\3%\3%\3%\3%\3%\3") buf.write("%\3&\3&\3\'\3\'\3(\3(\3(\3(\3(\3)\3)\3*\3*\3+\3+\3+\3") buf.write("+\3,\3,\3,\3,\3,\3,\3,\3,\3,\3-\3-\3-\3-\3-\3-\3-\3-\3") buf.write("-\3-\3-\3-\3.\3.\3.\3.\3.\3.\3.\3.\3.\3.\3.\3/\3/\3\60") buf.write("\3\60\3\61\3\61\3\62\3\62\3\63\3\63\3\64\3\64\3\65\3\65") buf.write("\3\65\3\66\3\66\3\66\3\67\3\67\3\67\38\38\38\39\39\39") buf.write("\3:\3:\3:\3;\3;\3;\3<\3<\3<\3<\3=\3=\3=\3>\3>\3>\3>\3") buf.write(">\3?\3?\3?\3?\3@\3@\3@\3A\3A\3A\3A\3A\3A\3A\3B\3B\3B\3") buf.write("B\3B\3C\3C\3C\3C\3C\3D\3D\3D\3D\3D\3D\3E\3E\3E\3E\3E\3") buf.write("F\3F\3F\3F\3F\3F\3G\3G\3G\3H\3H\7H\u01d1\nH\fH\16H\u01d4") buf.write("\13H\3I\3I\3I\3I\6I\u01da\nI\rI\16I\u01db\3J\3J\3J\3J") buf.write("\6J\u01e2\nJ\rJ\16J\u01e3\3K\3K\3K\3K\6K\u01ea\nK\rK\16") buf.write("K\u01eb\3L\3L\7L\u01f0\nL\fL\16L\u01f3\13L\3L\3L\6L\u01f7") buf.write("\nL\rL\16L\u01f8\3L\5L\u01fc\nL\3M\3M\7M\u0200\nM\fM\16") buf.write("M\u0203\13M\3M\3M\6M\u0207\nM\rM\16M\u0208\5M\u020b\n") buf.write("M\3M\3M\5M\u020f\nM\3M\6M\u0212\nM\rM\16M\u0213\3M\5M") buf.write("\u0217\nM\3N\3N\3N\3N\3N\5N\u021e\nN\5N\u0220\nN\3N\3") buf.write("N\3O\3O\3O\3O\3O\5O\u0229\nO\7O\u022b\nO\fO\16O\u022e") buf.write("\13O\3O\3O\3P\3P\7P\u0234\nP\fP\16P\u0237\13P\3Q\3Q\3") buf.write("R\3R\5R\u023d\nR\3S\3S\3T\3T\3U\3U\3V\3V\3V\6V\u0248\n") buf.write("V\rV\16V\u0249\5V\u024c\nV\3W\3W\3X\3X\3X\5X\u0253\nX") buf.write("\3Y\6Y\u0256\nY\rY\16Y\u0257\3Y\3Y\3Z\3Z\2\2[\3\3\5\4") buf.write("\7\5\t\6\13\7\r\b\17\t\21\n\23\13\25\f\27\r\31\16\33\17") buf.write("\35\20\37\21!\22#\23%\24\'\25)\26+\27-\30/\31\61\32\63") buf.write("\33\65\34\67\359\36;\37= ?!A\"C#E$G%I&K\'M(O)Q*S+U,W-") buf.write("Y.[/]\60_\61a\62c\63e\64g\65i\66k\67m8o9q:s;u<w=y>{?}") buf.write("@\177A\u0081B\u0083C\u0085D\u0087E\u0089F\u008bG\u008d") buf.write("H\u008fI\u0091J\u0093K\u0095L\u0097M\u0099N\u009bO\u009d") buf.write("P\u009fQ\u00a1\2\u00a3\2\u00a5\2\u00a7\2\u00a9\2\u00ab") buf.write("\2\u00ad\2\u00af\2\u00b1R\u00b3S\3\2\22\4\2GGgg\4\2--") buf.write("//\3\2))\4\2))^^\3\2^^\3\2$$\4\2$$^^\3\2\62;\3\2aa\4\2") buf.write("\62\63aa\4\2\629aa\6\2\62;CHaach\b\2^^cdhhppttvv\5\2\62") buf.write(";CHch\5\2C\\aac|\5\2\f\f\17\17\"\"\2\u026d\2\3\3\2\2\2") buf.write("\2\5\3\2\2\2\2\7\3\2\2\2\2\t\3\2\2\2\2\13\3\2\2\2\2\r") buf.write("\3\2\2\2\2\17\3\2\2\2\2\21\3\2\2\2\2\23\3\2\2\2\2\25\3") buf.write("\2\2\2\2\27\3\2\2\2\2\31\3\2\2\2\2\33\3\2\2\2\2\35\3\2") buf.write("\2\2\2\37\3\2\2\2\2!\3\2\2\2\2#\3\2\2\2\2%\3\2\2\2\2\'") buf.write("\3\2\2\2\2)\3\2\2\2\2+\3\2\2\2\2-\3\2\2\2\2/\3\2\2\2\2") buf.write("\61\3\2\2\2\2\63\3\2\2\2\2\65\3\2\2\2\2\67\3\2\2\2\29") buf.write("\3\2\2\2\2;\3\2\2\2\2=\3\2\2\2\2?\3\2\2\2\2A\3\2\2\2\2") buf.write("C\3\2\2\2\2E\3\2\2\2\2G\3\2\2\2\2I\3\2\2\2\2K\3\2\2\2") buf.write("\2M\3\2\2\2\2O\3\2\2\2\2Q\3\2\2\2\2S\3\2\2\2\2U\3\2\2") buf.write("\2\2W\3\2\2\2\2Y\3\2\2\2\2[\3\2\2\2\2]\3\2\2\2\2_\3\2") buf.write("\2\2\2a\3\2\2\2\2c\3\2\2\2\2e\3\2\2\2\2g\3\2\2\2\2i\3") buf.write("\2\2\2\2k\3\2\2\2\2m\3\2\2\2\2o\3\2\2\2\2q\3\2\2\2\2s") buf.write("\3\2\2\2\2u\3\2\2\2\2w\3\2\2\2\2y\3\2\2\2\2{\3\2\2\2\2") buf.write("}\3\2\2\2\2\177\3\2\2\2\2\u0081\3\2\2\2\2\u0083\3\2\2") buf.write("\2\2\u0085\3\2\2\2\2\u0087\3\2\2\2\2\u0089\3\2\2\2\2\u008b") buf.write("\3\2\2\2\2\u008d\3\2\2\2\2\u008f\3\2\2\2\2\u0091\3\2\2") buf.write("\2\2\u0093\3\2\2\2\2\u0095\3\2\2\2\2\u0097\3\2\2\2\2\u0099") buf.write("\3\2\2\2\2\u009b\3\2\2\2\2\u009d\3\2\2\2\2\u009f\3\2\2") buf.write("\2\2\u00b1\3\2\2\2\2\u00b3\3\2\2\2\3\u00b5\3\2\2\2\5\u00b7") buf.write("\3\2\2\2\7\u00b9\3\2\2\2\t\u00bb\3\2\2\2\13\u00bf\3\2") buf.write("\2\2\r\u00c6\3\2\2\2\17\u00cb\3\2\2\2\21\u00d1\3\2\2\2") buf.write("\23\u00d3\3\2\2\2\25\u00d5\3\2\2\2\27\u00d7\3\2\2\2\31") buf.write("\u00d9\3\2\2\2\33\u00dc\3\2\2\2\35\u00de\3\2\2\2\37\u00e1") buf.write("\3\2\2\2!\u00e3\3\2\2\2#\u00e5\3\2\2\2%\u00e7\3\2\2\2") buf.write("\'\u00e9\3\2\2\2)\u00eb\3\2\2\2+\u00ee\3\2\2\2-\u00f4") 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enumerate(atn.decisionToState) ] T__0 = 1 T__1 = 2 T__2 = 3 T__3 = 4 T__4 = 5 T__5 = 6 T__6 = 7 T__7 = 8 T__8 = 9 T__9 = 10 T__10 = 11 T__11 = 12 T__12 = 13 T__13 = 14 T__14 = 15 T__15 = 16 T__16 = 17 T__17 = 18 T__18 = 19 T__19 = 20 T__20 = 21 T__21 = 22 T__22 = 23 T__23 = 24 T__24 = 25 T__25 = 26 T__26 = 27 T__27 = 28 T__28 = 29 T__29 = 30 T__30 = 31 T__31 = 32 T__32 = 33 T__33 = 34 T__34 = 35 T__35 = 36 T__36 = 37 T__37 = 38 T__38 = 39 T__39 = 40 T__40 = 41 T__41 = 42 T__42 = 43 T__43 = 44 T__44 = 45 T__45 = 46 T__46 = 47 T__47 = 48 T__48 = 49 T__49 = 50 T__50 = 51 T__51 = 52 T__52 = 53 T__53 = 54 T__54 = 55 T__55 = 56 T__56 = 57 T__57 = 58 T__58 = 59 T__59 = 60 T__60 = 61 T__61 = 62 T__62 = 63 T__63 = 64 T__64 = 65 T__65 = 66 T__66 = 67 T__67 = 68 T__68 = 69 T__69 = 70 INT_DEC = 71 INT_BIN = 72 INT_OCT = 73 INT_HEX = 74 RAT = 75 FLOAT = 76 CHAR = 77 STRING = 78 ID = 79 WS = 80 ERR = 81 channelNames = [ u"DEFAULT_TOKEN_CHANNEL", u"HIDDEN" ] modeNames = [ "DEFAULT_MODE" ] literalNames = [ "<INVALID>", "';'", "'{'", "'}'", "'use'", "'hiding'", "'skip'", "'print'", "','", "':'", "'='", "'^'", "'^^'", "'/'", "'//'", "'%'", "'*'", "'&'", "'+'", "'-'", "'??'", "'break'", "'continue'", "'return'", "'yield'", "'if'", "'do'", "'elif'", "'else'", "'while'", "'label'", "'until'", "'for'", "'in'", "'def'", "'extern'", "'class'", "'('", "')'", "'func'", "'<'", "'>'", "'...'", "'abstract'", "'constructor'", "'destructor'", "'['", "']'", "'?'", "'.'", "'@'", "'!'", "'%%'", "'..'", "'by'", "'=='", "'!='", "'<='", "'>='", "'not'", "'is'", "'null'", "'and'", "'or'", "'lambda'", "'...:'", "'true'", "'false'", "'this'", "'super'", "'->'" ] symbolicNames = [ "<INVALID>", "INT_DEC", "INT_BIN", "INT_OCT", "INT_HEX", "RAT", "FLOAT", "CHAR", "STRING", "ID", "WS", "ERR" ] ruleNames = [ "T__0", "T__1", "T__2", "T__3", "T__4", "T__5", "T__6", "T__7", "T__8", "T__9", "T__10", "T__11", "T__12", "T__13", "T__14", "T__15", "T__16", "T__17", "T__18", "T__19", "T__20", "T__21", "T__22", "T__23", "T__24", "T__25", "T__26", "T__27", "T__28", "T__29", "T__30", "T__31", "T__32", "T__33", "T__34", "T__35", "T__36", "T__37", "T__38", "T__39", "T__40", "T__41", "T__42", "T__43", "T__44", "T__45", "T__46", "T__47", "T__48", "T__49", "T__50", "T__51", "T__52", "T__53", "T__54", "T__55", "T__56", "T__57", "T__58", "T__59", "T__60", "T__61", "T__62", "T__63", "T__64", "T__65", "T__66", "T__67", "T__68", "T__69", "INT_DEC", "INT_BIN", "INT_OCT", "INT_HEX", "RAT", "FLOAT", "CHAR", "STRING", "ID", "DIGIT", "NUMBER_DEC_CONT", "NUMBER_BIN_CONT", "NUMBER_OCT_CONT", "NUMBER_HEX_CONT", "ESCAPE_CHAR", "ID_START", "ID_CONT", "WS", "ERR" ] grammarFileName = "Pyxell.g4" def __init__(self, input=None, output:TextIO = sys.stdout): super().__init__(input, output) self.checkVersion("4.9.1") self._interp = LexerATNSimulator(self, self.atn, self.decisionsToDFA, PredictionContextCache()) self._actions = None self._predicates = None

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02e184776feb00f7f15454f39e42354325d8a0cd

196

py

Python

fabfile.py

ZimGreen/edbo-connector-py

2787c5a43af1229d93591b735cd14cebaf792c39

[ "MIT" ]

2

2017-08-05T17:20:58.000Z

2017-08-13T09:44:13.000Z

fabfile.py

ZimGreen/edbo-connector-py

2787c5a43af1229d93591b735cd14cebaf792c39

[ "MIT" ]

1

2017-12-14T05:00:56.000Z

fabfile.py

EldarAliiev/python-edbo-connector

2787c5a43af1229d93591b735cd14cebaf792c39

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from fabric.api import run def publish(): """Publish package to PyPi repository""" run('python3 setup.py bdist_wheel sdist upload --sign')

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f3011e9cb2694b55cc81c37cc91b855f9ebdc747

134

py

Python

tests/test_init.py

dendisuhubdy/datamine_python

22ca2a580b3f6360cef9f6219a43bae935294353

[ "BSD-3-Clause" ]

null

tests/test_init.py

dendisuhubdy/datamine_python

22ca2a580b3f6360cef9f6219a43bae935294353

[ "BSD-3-Clause" ]

null

tests/test_init.py

dendisuhubdy/datamine_python

22ca2a580b3f6360cef9f6219a43bae935294353

[ "BSD-3-Clause" ]

null

import datamine def test_package_has_version(): assert hasattr(datamine, '__version__') assert len(datamine.__version__) > 0

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6

b831a1d83c386ff35d888e82700fbc234a4bb809

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py

Python

05_restapi_argumentParser/caculator.py

choisungwook/practice_flask

a2059d8d7c011e3d560f7bb042575a7ff080c235

[ "MIT" ]

null

05_restapi_argumentParser/caculator.py

choisungwook/practice_flask

a2059d8d7c011e3d560f7bb042575a7ff080c235

[ "MIT" ]

null

05_restapi_argumentParser/caculator.py

choisungwook/practice_flask

a2059d8d7c011e3d560f7bb042575a7ff080c235

[ "MIT" ]

null

from flask_restful import Resource, reqparse from flask import jsonify class Add(Resource): def get(self): parser = reqparse.RequestParser(bundle_errors=True) parser.add_argument('operand1', type=int, required=True, help='operand1 is required The detail error is{error_msg}') parser.add_argument('operand2', type=int, required=True, help='operand2 is required. The detail error is {error_msg}') args = parser.parse_args() operand1 = args['operand1'] operand2 = args['operand2'] return jsonify({'result': operand1+operand2}) class Sub(Resource): def get(self): parser = reqparse.RequestParser(bundle_errors=True) parser.add_argument('operand1', type=int, required=True, help='operand1 is required The detail error is{error_msg}') parser.add_argument('operand2', type=int, required=True, help='operand2 is required. The detail error is {error_msg}') args = parser.parse_args() operand1 = args['operand1'] operand2 = args['operand2'] return jsonify({'result': operand1 - operand2})

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py

Python

venv/lib/python3.8/site-packages/numpy/f2py/common_rules.py

GiulianaPola/select_repeats

17a0d053d4f874e42cf654dd142168c2ec8fbd11

[ "MIT" ]

2

2022-03-13T01:58:52.000Z

2022-03-31T06:07:54.000Z

venv/lib/python3.8/site-packages/numpy/f2py/common_rules.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

19

2021-11-20T04:09:18.000Z

2022-03-23T15:05:55.000Z

venv/lib/python3.8/site-packages/numpy/f2py/common_rules.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

null

/home/runner/.cache/pip/pool/21/67/d1/41f865482ce20e7fb7846a08a481c643bc82f84682d162b1f58ad7b3a2

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6

b843393ab79b4d575a1e1b2c1e57ea34cffb25ff

297

py

Python

tests/test_cos_matrix2.py

ffreemt/freemt-utils

25bf192033235bb783005795f8c0bcdd8a79610f

[ "MIT" ]

null

tests/test_cos_matrix2.py

ffreemt/freemt-utils

25bf192033235bb783005795f8c0bcdd8a79610f

[ "MIT" ]

null

tests/test_cos_matrix2.py

ffreemt/freemt-utils

25bf192033235bb783005795f8c0bcdd8a79610f

[ "MIT" ]

null

# from freemt_utils.make_url import make_url from freemt_utils import cos_matrix2 def test_cos_matrix2(): ''' test cos_matrix2. ''' assert cos_matrix2([[1, 1]], [[1, 1]])[0, 0] > 0.9 def test_cos_matrix2a(): ''' test cos_matrix2. ''' assert cos_matrix2([[1, 1]])[0, 0] > 0.9

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b89454fc4303b4272285f2699649796ed1343439

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Python

learning/tests/views/test_activity_views.py

dbcaturra/django-koala-azure

7b79b7484e3530513b97ed148333ba0778f38a3e

[ "MIT" ]

null

learning/tests/views/test_activity_views.py

dbcaturra/django-koala-azure

7b79b7484e3530513b97ed148333ba0778f38a3e

[ "MIT" ]

null

learning/tests/views/test_activity_views.py

dbcaturra/django-koala-azure

7b79b7484e3530513b97ed148333ba0778f38a3e

[ "MIT" ]

null

# # Copyright (C) 2019 Guillaume Bernard <guillaume.bernard@koala-lms.org> # Copyright (C) 2020 Raphaël Penault <raphael.penault@etudiant.univ-lr.fr> # Copyright (C) 2020 Nolwenn Machon <nolwenn.machon@etudiant.univ-lr.fr> # # This file is part of Koala LMS (Learning Management system) # Koala LMS is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <https://www.gnu.org/licenses/>. # # We make an extensive use of the Django framework, https://www.djangoproject.com/ # import tempfile from django.contrib.auth import get_user_model from django.core.exceptions import ObjectDoesNotExist from django.test import TestCase, Client, override_settings from django.urls import reverse from learning.forms import BasicSearchForm from learning.models import Resource, ResourceAccess, ResourceReuse, Activity, ActivityAccess, ActivityReuse, Course, \ CourseActivity, Duration, Licences, ResourceType from learning.tests.views.helpers import ClientFactory from learning.tests.views.test_resource_views import get_temporary_file class ActivityViews(TestCase): def setUp(self): for initials in ["ws", "acd", "lt", "ed"]: setattr(self, initials, get_user_model().objects.create_user(username=initials, password="pwd")) self.anon_client = Client() self.ws_activity = Activity.objects.create( id=1, name="A sample activity", description="A sample description", access=ResourceAccess.PUBLIC.name, reuse=ResourceReuse.NO_RESTRICTION.name, author=self.ws, language="en", ) self.acd_activity = Activity.objects.create(author=self.acd, name="activity1", language="en") self.lt_activity = Activity.objects.create(author=self.lt, name="activity2", language="en") self.resource1 = Resource.objects.create( id=1, name="resource1", author=self.ws, language="en" ) """ ActivityDetailView """ def test_get_resource_view(self): response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(200, response.status_code) the_object = response.context.get('object') activity = response.context.get('activity') self.assertEqual(the_object, self.ws_activity) self.assertEqual(activity, self.ws_activity) self.assertTemplateUsed(response, "learning/activity/detail.html") def test_post_detail_resource_view_method_not_allowed(self): response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(405, response.status_code) def test_get_detail_activity_view_as_author_private_resource_no_resource(self): self.ws_activity.access = ActivityAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) self.assertContains(response, "link-activity-usage", count=1) self.assertContains(response, "link-activity-similar", count=1) self.assertContains(response, "link-activity-add-resource", count=2) self.assertContains(response, "link-activity-attach-resource", count=1) self.assertContains(response, "btn-change-activity", count=1) self.assertContains(response, "btn-delete-activity", count=1) self.assertContains(response, "activity-no-resource", count=2) activity = response.context.get('activity') self.assertEqual(activity, self.ws_activity) def test_get_detail_activity_view_as_author_private_resource_one_resource(self): self.ws_activity.resources.add(self.resource1) self.ws_activity.access = ActivityAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) self.assertContains(response, "link-activity-usage", count=1) self.assertContains(response, "link-activity-similar", count=1) self.assertContains(response, "link-activity-add-resource", count=2) self.assertContains(response, "link-activity-attach-resource", count=1) self.assertContains(response, "btn-change-activity", count=1) self.assertContains(response, "btn-delete-activity", count=1) self.assertNotContains(response, "activity-no-resource") activity = response.context.get('activity') self.assertContains(response, "resource-block-for-{}".format(self.resource1.slug)) self.assertEqual(activity, self.ws_activity) def test_get_detail_activity_view_registered_user_private_activity(self): self.ws_activity.access = ActivityAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) self.assertNotIn("view_activity", self.ws_activity.get_user_perms(self.acd)) self.assertEqual(403, response.status_code) def test_get_detail_activity_view_registered_user_public_activity(self): self.ws_activity.resources.add(self.resource1) self.ws_activity.access = ActivityAccess.PUBLIC.name self.ws_activity.save() response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_activity", self.ws_activity.get_user_perms(self.acd)) self.assertEqual(200, response.status_code) self.assertNotContains(response, "link-activity-usage") self.assertNotContains(response, "link-activity-similar") self.assertNotContains(response, "link-activity-add-resource") self.assertNotContains(response, "btn-change-activity") self.assertNotContains(response, "btn-delete-activity") self.assertNotContains(response, "activity-no-resource") activity = response.context.get('activity') self.assertContains(response, "resource-block-for-{}".format(self.resource1.slug)) self.assertEqual(activity, self.ws_activity) """ ActivityCreateView """ def test_get_create_activity_view(self): response = ClientFactory.get_client_for_user("ws").get(reverse("learning:activity/add")) self.assertEqual(200, response.status_code) self.assertTemplateUsed(response, "learning/activity/add.html") def test_post_create_activity_error_missing_tags_name_description_language(self): form_data = { 'reuse': ActivityReuse.NO_RESTRICTION.name, 'access': ActivityAccess.PUBLIC.name } response = ClientFactory.get_client_for_user("ws").post(reverse("learning:activity/add"), form_data) self.assertEqual(200, response.status_code) self.assertTemplateUsed(response, "learning/activity/add.html") self.assertContains(response, "is-invalid", count=4) def test_post_create_activity_error_missing_all_fields(self): response = ClientFactory.get_client_for_user("ws").post(reverse("learning:activity/add")) self.assertEqual(200, response.status_code) self.assertTemplateUsed(response, "learning/activity/add.html") self.assertContains(response, "is-invalid", count=6) def test_post_create_activity(self): form_data = { 'name': "A sample name", 'description': "A short description", 'language': 'fr', 'reuse': ActivityReuse.NO_RESTRICTION.name, 'access': ActivityAccess.PUBLIC.name, 'tags': "A", } response = ClientFactory.get_client_for_user("ws").post(reverse("learning:activity/add"), form_data) # Check redirection after resource creation self.assertRedirects( response, status_code=302, target_status_code=200, expected_url=reverse("learning:activity/detail", kwargs={'slug': "a-sample-name"}) ) # The author is the request sender resource = Activity.objects.get(pk=4) self.assertEqual(self.ws, resource.author) """ ActivityUpdateView """ def test_update_get_activity_as_author(self): response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/update", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(200, response.status_code) self.assertTemplateUsed(response, "learning/activity/details/change.html") def test_update_post_activity_as_author(self): form_data = { 'name': "A sample name that changed", 'description': "A short description", 'language': 'fr', 'access': ActivityAccess.PUBLIC.name, 'reuse': ActivityReuse.ONLY_AUTHOR.name, 'tags': "A" } response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/update", kwargs={'slug': self.ws_activity.slug}), form_data ) self.assertRedirects( response, status_code=302, target_status_code=200, expected_url=reverse("learning:activity/detail", kwargs={'slug': "a-sample-name-that-changed"}) ) def test_update_post_activity_as_author_errors(self): form_data = { 'name': "", 'description': "", 'language': 'fakelanguage', 'access': ActivityAccess.PUBLIC.name, 'reuse': ActivityReuse.ONLY_AUTHOR.name, 'tags': "A" } response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/update", kwargs={'slug': self.ws_activity.slug}), form_data ) self.assertEqual(200, response.status_code) self.assertContains(response, "is-invalid", count=3) def test_update_get_activity_without_being_author_forbidden(self): response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/update", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(403, response.status_code) def test_update_post_activity_without_being_author_forbidden(self): form_data = { 'name': "A sample name that changed", 'description': "A short description", } response = ClientFactory.get_client_for_user("acd").post( reverse("learning:activity/update", kwargs={'slug': self.ws_activity.slug}), form_data ) self.assertEqual(403, response.status_code) """ ActivityDeleteView """ def test_delete_activity_get_as_author(self): response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/delete", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(200, response.status_code) self.assertTemplateUsed(response, "learning/activity/delete.html") def test_delete_resource_post_as_author(self): response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/delete", kwargs={'slug': self.ws_activity.slug}) ) self.assertRedirects( response, status_code=302, target_status_code=200, expected_url=reverse("learning:activity/my") ) with self.assertRaises(ObjectDoesNotExist): Activity.objects.get(pk=self.ws_activity.id) def test_delete_resource_get_without_being_author_forbidden(self): response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/delete", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(403, response.status_code) def test_delete_activity_post_without_being_author_forbidden(self): response = ClientFactory.get_client_for_user("acd").post( reverse("learning:activity/delete", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(403, response.status_code) """ ActivityDetailUsageView """ def test_post_detail_usage_activity_view_method_not_allowed(self): response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail/usage", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(405, response.status_code) def test_get_detail_usage_activity_view_as_author_private_not_used(self): self.ws_activity.access = ActivityAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/usage", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_usage_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) activity = response.context.get('activity') self.assertEqual(activity, self.ws_activity) self.assertNotContains(response, "table-activity-usage") self.assertContains(response, "alert-not-used") def test_get_detail_usage_activity_view_as_author_public_not_used(self): self.ws_activity.access = ResourceAccess.PUBLIC.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/usage", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_usage_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) activity = response.context.get('activity') self.assertEqual(activity, self.ws_activity) self.assertNotContains(response, "table-activity-usage") self.assertContains(response, "alert-not-used") def test_get_detail_usage_activity_view_as_author_public_resource_used_twice(self): c1 = Course.objects.create(author=self.ws, name="test1", language="en") c2 = Course.objects.create(author=self.acd, name="test2", language="en") CourseActivity.objects.create(activity=self.ws_activity, rank=1, course=c1) CourseActivity.objects.create(activity=self.ws_activity, rank=1, course=c2) self.assertEqual(2, self.ws_activity.course_activities.count()) self.ws_activity.access = ResourceAccess.PUBLIC.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/usage", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_usage_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) activity = response.context.get('activity') self.assertEqual(activity, self.ws_activity) self.assertContains(response, "table-activity-usage") self.assertContains(response, "usage-activity-row", count=2) self.assertNotContains(response, "alert-not-used") page_obj = response.context.get('page_obj') self.assertIsNotNone(page_obj) self.assertEqual(2, len(page_obj.object_list)) def test_get_detail_usage_activity_view_as_author_private_resource_used_three_times(self): c1 = Course.objects.create(author=self.ws, name="test1", language="en") c2 = Course.objects.create(author=self.acd, name="test2", language="en") c3 = Course.objects.create(author=self.acd, name="test3", language="en") CourseActivity.objects.create(activity=self.ws_activity, rank=1, course=c1) CourseActivity.objects.create(activity=self.ws_activity, rank=1, course=c2) CourseActivity.objects.create(activity=self.ws_activity, rank=1, course=c3) self.assertEqual(3, self.ws_activity.course_activities.count()) self.ws_activity.access = ResourceAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/usage", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_usage_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) activity = response.context.get('activity') self.assertIsNotNone(activity) self.assertEqual(activity, self.ws_activity) self.assertContains(response, "table-activity-usage") self.assertContains(response, "usage-activity-row", count=3) self.assertNotContains(response, "alert-not-used") page_obj = response.context.get('page_obj') self.assertIsNotNone(page_obj) self.assertEqual(3, len(page_obj.object_list)) def test_get_detail_usage_activity_view_user_private_resource_forbidden(self): self.ws_activity.access = ResourceAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail/usage", kwargs={'slug': self.ws_activity.slug}) ) self.assertNotIn("view_usage_activity", self.ws_activity.get_user_perms(self.acd)) self.assertEqual(403, response.status_code) def test_get_detail_usage_resource_view_user_public_resource(self): self.ws_activity.access = ResourceAccess.PUBLIC.name self.ws_activity.save() response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail/usage", kwargs={'slug': self.ws_activity.slug}) ) self.assertNotIn("view_usage_activity", self.ws_activity.get_user_perms(self.acd)) self.assertEqual(403, response.status_code) """ activityDetailSimilarView """ def test_post_detail_similar_activity_view_method_not_allowed(self): response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail/similar", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(405, response.status_code) def test_get_detail_similar_activity_view_as_author_private_activity_empty(self): self.ws_activity.access = ActivityAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/similar", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_similar_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) activity = response.context.get('activity') self.assertEqual(activity, self.ws_activity) self.assertNotContains(response, "similar-activities") self.assertContains(response, "alert-no-similar-activity") def test_get_detail_similar_activity_view_as_author_public_activity_empty(self): self.ws_activity.access = ActivityAccess.PUBLIC.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/similar", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_similar_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) activity = response.context.get('activity') self.assertEqual(activity, self.ws_activity) self.assertNotContains(response, "similar-activities") self.assertContains(response, "alert-no-similar-activity") def test_get_detail_similar_activity_view_as_author_public_activity_used_twice(self): self.ws_activity.tags.add("tag1") self.ws_activity.tags.add("tag2") for tag in self.ws_activity.tags.all(): self.acd_activity.tags.add(tag) self.lt_activity.tags.add(tag) self.acd_activity.save() self.lt_activity.save() self.ws_activity.access = ActivityAccess.PUBLIC.name self.ws_activity.save() response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/similar", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn("view_similar_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(200, response.status_code) activity = response.context.get('activity') self.assertEqual(activity, self.ws_activity) self.assertNotContains(response, "alert-no-similar-activity") self.assertContains(response, "similar-activities") page_obj = response.context.get('page_obj') self.assertIsNotNone(page_obj) self.assertEqual(2, len(page_obj.object_list)) def test_get_detail_similar_activity_view_user_private_activity_forbidden(self): self.ws_activity.access = ActivityAccess.PRIVATE.name self.ws_activity.save() response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail/similar", kwargs={'slug': self.ws_activity.slug}) ) self.assertNotIn("view_similar_activity", self.ws_activity.get_user_perms(self.acd)) self.assertEqual(403, response.status_code) def test_get_detail_similar_activity_view_user_public_activity(self): self.ws_activity.access = ActivityAccess.PUBLIC.name self.ws_activity.save() response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail/similar", kwargs={'slug': self.ws_activity.slug}) ) self.assertNotIn("view_similar_activity", self.ws_activity.get_user_perms(self.acd)) self.assertEqual(403, response.status_code) """ ResourceOnActivityDetailView """ def test_get_resource_on_activity(self): r1 = Resource.objects.create(author=self.ws, name="A first resource", language="en") self.ws_activity.resources.add(r1) response = ClientFactory.get_client_for_user("ws").get( reverse( "learning:activity/resource/detail", kwargs={'slug': self.ws_activity.slug, 'resource_slug': r1.slug} ) ) self.assertEqual(200, response.status_code) self.assertContains(response, self.ws_activity.name, count=3) self.assertContains(response, "A first resource", count=3) self.assertEqual(self.ws_activity, response.context.get('object')) self.assertEqual(self.ws_activity, response.context.get('activity')) self.assertEqual(r1, response.context.get('resource')) def test_get_resource_on_activity_no_perm_on_resource(self): r1 = Resource.objects.create( author=self.acd, name="A first resource", access=ResourceAccess.PRIVATE.name, language="en" ) self.ws_activity.resources.add(r1) self.assertNotIn("view_resource", r1.get_user_perms(self.ws)) self.assertIn("view_activity", self.ws_activity.get_user_perms(self.ws)) response = ClientFactory.get_client_for_user("ws").get( reverse( "learning:activity/resource/detail", kwargs={'slug': self.ws_activity.slug, 'resource_slug': r1.slug} ) ) self.assertEqual(403, response.status_code) def test_get_resource_on_activity_no_perm_on_activity(self): r1 = Resource.objects.create( author=self.acd, name="A first resource", access=ResourceAccess.PUBLIC.name, language="en" ) self.ws_activity.author = self.acd self.ws_activity.access = ActivityAccess.PRIVATE.name self.ws_activity.save() self.ws_activity.resources.add(r1) self.assertIn("view_resource", r1.get_user_perms(self.ws)) self.assertNotIn("view_activity", self.ws_activity.get_user_perms(self.ws)) response = ClientFactory.get_client_for_user("ws").get( reverse( "learning:activity/resource/detail", kwargs={'slug': self.ws_activity.slug, 'resource_slug': r1.slug} ) ) self.assertEqual(403, response.status_code) """ ActivityCreateResourceView """ def test_get_create_resource_on_activity_as_author(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/resource/add", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(200, response.status_code) self.assertTemplateUsed(response, "learning/activity/details/add_resource.html") def test_get_create_resource_on_activity_no_perm(self): self.assertNotIn("change_activity", self.ws_activity.get_user_perms(self.acd)) response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail/resource/add", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(403, response.status_code) def test_post_create_resource_on_activity_no_perm(self): self.assertNotIn("change_activity", self.ws_activity.get_user_perms(self.acd)) response = ClientFactory.get_client_for_user("acd").post( reverse("learning:activity/detail/resource/add", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(403, response.status_code) @override_settings(MEDIA_ROOT=tempfile.gettempdir()) def test_post_create_resource_on_activity_as_author(self): form_data = { 'name': "A sample name", 'description': "A short description", 'type': ResourceType.FILE.name, 'language': 'fr', 'licence': Licences.CC_BY.name, 'access': ResourceAccess.PUBLIC.name, 'reuse': ResourceReuse.ONLY_AUTHOR.name, 'duration': Duration.NOT_SPECIFIED.name, 'tags': "A", "media": get_temporary_file() } response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail/resource/add", kwargs={'slug': self.ws_activity.slug}), form_data ) resource = Resource.objects.get(slug="a-sample-name") self.assertRedirects( response, status_code=302, target_status_code=200, expected_url=reverse("learning:resource/detail", kwargs={'slug': resource.slug}) ) self.assertIsNotNone(resource) self.assertEqual(1, resource.activities.count()) self.assertIn(resource, self.ws_activity.resources.all()) self.assertEqual(resource.author, self.ws) @override_settings(MEDIA_ROOT=tempfile.gettempdir()) def test_post_create_resource_on_activity_as_author_not_reusable_resource_not_saved(self): form_data = { 'name': "A sample name", 'description': "A short description", 'type': ResourceType.FILE.name, 'language': 'fr', 'licence': Licences.CC_BY.name, 'access': ResourceAccess.PUBLIC.name, 'reuse': ResourceReuse.NON_REUSABLE.name, 'duration': Duration.NOT_SPECIFIED.name, 'tags': "A", "media": get_temporary_file() } response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail/resource/add", kwargs={'slug': self.ws_activity.slug}), form_data ) self.assertEqual(200, response.status_code) self.assertFalse(Resource.objects.filter(name="A sample name").exists()) self.assertEqual(0, self.ws_activity.resources.count()) self.assertEqual(0, len(response.context.get('form').errors.as_data())) self.assertEqual(0, self.ws_activity.resources.count()) @override_settings(MEDIA_ROOT=tempfile.gettempdir()) def test_post_create_resource_on_activity_invalid_form(self): form_data = { 'description': "A short description", 'type': ResourceType.FILE.name, 'language': 'fr', 'licence': Licences.CC_BY.name, 'access': ResourceAccess.PUBLIC.name, 'reuse': ResourceReuse.NO_RESTRICTION.name, 'duration': Duration.NOT_SPECIFIED.name, 'tags': "A", "media": get_temporary_file() } response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail/resource/add", kwargs={'slug': self.ws_activity.slug}), form_data ) self.assertEqual(200, response.status_code) self.assertFalse(Resource.objects.filter(name="A sample name").exists()) self.assertEqual(0, self.ws_activity.resources.count()) self.assertEqual(1, len(response.context.get('form').errors.as_data())) self.assertEqual(0, self.ws_activity.resources.count()) """ ResourceUnlinkOnActivityView """ def test_unlink_on_activity_no_perm(self): self.assertNotIn("change_activity", self.ws_activity.get_user_perms(self.acd)) response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail/resource/unlink", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(403, response.status_code) def test_get_unlink_on_activity_view(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/resource/unlink", kwargs={'slug': self.ws_activity.slug}) ) self.assertRedirects( response, status_code=302, target_status_code=200, expected_url=reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) def test_post_unlink_on_activity_view(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) r1 = Resource.objects.create(name="A sample resource", author=self.acd, language="en") self.ws_activity.resources.add(r1) self.assertIn(r1, self.ws_activity.resources.all()) response = ClientFactory.get_client_for_user("ws").post( reverse( "learning:activity/detail/resource/unlink", kwargs={'slug': self.ws_activity.slug, }, ), {'resource': r1.id} ) self.assertRedirects( response, status_code=302, target_status_code=200, expected_url=reverse("learning:activity/detail", kwargs={'slug': self.ws_activity.slug}) ) self.assertNotIn(r1, self.ws_activity.resources.all()) def test_post_unlink_resource_not_linked_on_activity_view(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) r1 = Resource.objects.create(name="A sample resource", author=self.acd, language="en") r2 = Resource.objects.create(name="A sample resource 2", author=self.lt, language="en") self.ws_activity.resources.add(r1) self.assertIn(r1, self.ws_activity.resources.all()) self.assertNotIn(r2, self.ws_activity.resources.all()) response = ClientFactory.get_client_for_user("ws").post( reverse( "learning:activity/detail/resource/unlink", kwargs={'slug': self.ws_activity.slug, }, ), {'resource': r2.id} ) self.assertEqual(302, response.status_code) self.assertIn(r1, self.ws_activity.resources.all()) self.assertNotIn(r2, self.ws_activity.resources.all()) def test_post_unlink_does_not_exist_on_activity_view(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) r1 = Resource.objects.create(name="A sample resource", author=self.acd) self.ws_activity.resources.add(r1) self.assertIn(r1, self.ws_activity.resources.all()) response = ClientFactory.get_client_for_user("ws").post( reverse( "learning:activity/detail/resource/unlink", kwargs={'slug': self.ws_activity.slug, }, ), {'resource': r1.id + 1} ) self.assertEqual(404, response.status_code) self.assertIn(r1, self.ws_activity.resources.all()) """ ResourceAttachOnActivityView """ def test_attach_on_activity_no_perm(self): self.assertNotIn("change_activity", self.ws_activity.get_user_perms(self.acd)) response = ClientFactory.get_client_for_user("acd").get( reverse("learning:activity/detail/resource/attach", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(403, response.status_code) def test_get_attach_on_activity_view(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) response = ClientFactory.get_client_for_user("ws").get( reverse("learning:activity/detail/resource/attach", kwargs={'slug': self.ws_activity.slug}) ) self.assertEqual(200, response.status_code) self.assertTemplateUsed("learning/activity/details/attach_resource.html") self.assertIsNotNone(response.context.get('form')) self.assertIsInstance(response.context.get('form'), BasicSearchForm) def test_post_attach_on_activity_view(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) r1 = Resource.objects.create( name="A sample resource", author=self.acd, reuse=ResourceReuse.NO_RESTRICTION.name, language="en" ) self.assertTrue(r1.is_reusable(self.ws_activity)) self.assertNotIn(r1, self.ws_activity.resources.all()) response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail/resource/attach", kwargs={'slug': self.ws_activity.slug}), {'resource': r1.id} ) self.assertRedirects( response, status_code=302, target_status_code=200, expected_url=reverse("learning:activity/detail/resource/attach", kwargs={'slug': self.ws_activity.slug}) ) self.assertIn(r1, self.ws_activity.resources.all()) def test_post_attach_on_activity_view_not_exists(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) self.assertEqual(0, self.ws_activity.resources.count()) response = ClientFactory.get_client_for_user("ws").post( reverse("learning:activity/detail/resource/attach", kwargs={'slug': self.ws_activity.slug}), {'resource': 99} ) self.assertEqual(404, response.status_code) self.assertEqual(0, self.ws_activity.resources.count()) def test_post_attach_on_activity_view_already_linked(self): self.assertIn("change_activity", self.ws_activity.get_user_perms(self.ws)) r1 = Resource.objects.create(name="A sample resource", author=self.acd, language="en") r2 = Resource.objects.create(name="A sample resource 2", author=self.lt, language="en") self.ws_activity.resources.add(r1) self.assertIn(r1, self.ws_activity.resources.all()) self.assertNotIn(r2, self.ws_activity.resources.all()) response = ClientFactory.get_client_for_user("ws").post( reverse( "learning:activity/detail/resource/attach", kwargs={'slug': self.ws_activity.slug, }, ), {'resource': r1.id} ) self.assertEqual(302, response.status_code) self.assertIn(r1, self.ws_activity.resources.all()) self.assertNotIn(r2, self.ws_activity.resources.all())

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null

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6

b230dbbdc6a44cea06c6ae7a88c00dba082a275b

192

py

Python

enumtables/alembic_ops/__init__.py

gazorby/gino-enum-tables

68e43530d07b9fa81551c400639956cbe43b3ba2

[ "Apache-2.0" ]

null

enumtables/alembic_ops/__init__.py

gazorby/gino-enum-tables

68e43530d07b9fa81551c400639956cbe43b3ba2

[ "Apache-2.0" ]

null

enumtables/alembic_ops/__init__.py

gazorby/gino-enum-tables

68e43530d07b9fa81551c400639956cbe43b3ba2

[ "Apache-2.0" ]

null

try: import alembic except ModuleNotFoundError: pass # Expected exception else: from .alembic_ops import EnumInsertOp, EnumDeleteOp from .alembic_autogen import compare_enums

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b257f6717a2f3bd580e8c2a281e46b3b574a4629

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py

Python

notebooks/Sophie1/project_functions2.py

data301-2021-winter1/project-group42-project

a1177177f0620657315ebed7822598fc6c0f4dd8

[ "MIT" ]

null

notebooks/Sophie1/project_functions2.py

data301-2021-winter1/project-group42-project

a1177177f0620657315ebed7822598fc6c0f4dd8

[ "MIT" ]

null

notebooks/Sophie1/project_functions2.py

data301-2021-winter1/project-group42-project

a1177177f0620657315ebed7822598fc6c0f4dd8

[ "MIT" ]

null

import pandas as pd import numpy as np def load_and_process(url_or_path_to_csv_file): #Method Chain 1 - loading data df_0=(pd.read_csv(url_or_path_to_csv_file, encoding='unicode_escape')) #Method Chain 2 - dropping columns and processing data for df1 df_1=(df_0 .drop(columns=['INCIDENT_NUMBER', 'OFFENSE_CODE', 'REPORTING_AREA', 'SHOOTING', 'OCCURRED_ON_DATE' , 'YEAR', 'MONTH', 'DAY_OF_WEEK', 'HOUR', 'UCR_PART', 'Lat', 'Long']) .replace(np.nan, 'N', regex=True) .dropna() ) #Ensure it returns to the lastest dataframe return df_1 def load_and_process(url_or_path_to_csv_file): #Method Chain 1 - loading data df_0=(pd.read_csv(url_or_path_to_csv_file, encoding='unicode_escape')) #Method Chain 2 - dropping columns and processing data for df2 df_2=(df_0 .drop(columns=['INCIDENT_NUMBER', 'OFFENSE_CODE', 'REPORTING_AREA', 'SHOOTING', 'OCCURRED_ON_DATE', 'UCR_PART', 'Lat', 'Long', 'Location', 'STREET', 'DISTRICT']) .replace(np.nan, 'N', regex=True) .dropna() ) #Ensure it returns to the lastest dataframe return df_2

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b2b13afb7bf942e050ae1c191a343164698f5859

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py

Python

fmpsdk/company_valuation.py

ipl31/fmpsdk

fba494ee7c123d8ca12a2b456c27655edfa24455

[ "BSD-3-Clause" ]

null

fmpsdk/company_valuation.py

ipl31/fmpsdk

fba494ee7c123d8ca12a2b456c27655edfa24455

[ "BSD-3-Clause" ]

null

fmpsdk/company_valuation.py

ipl31/fmpsdk

fba494ee7c123d8ca12a2b456c27655edfa24455

[ "BSD-3-Clause" ]

null

import typing import logging import requests from .settings import ( BASE_URL_v3, DEFAULT_LIMIT, FINANCIAL_STATEMENT_FILENAME, CASH_FLOW_STATEMENT_FILENAME, INCOME_STATEMENT_FILENAME, BALANCE_SHEET_STATEMENT_FILENAME, INCOME_STATEMENT_AS_REPORTED_FILENAME, BALANCE_SHEET_STATEMENT_AS_REPORTED_FILENAME, CASH_FLOW_STATEMENT_AS_REPORTED_FILENAME, ) from .url_methods import ( __return_json_v3, __validate_sector, __validate_period, __validate_industry, __validate_exchange, ) def company_profile(apikey: str, symbol: str) -> typing.List[typing.Dict]: """ Query FMP /profile/ API. Gather this company's information. :param apikey: Your API key. :param symbol: Ticker of Company. :return: A list of dictionaries. """ path = f"profile/{symbol}" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def key_executives(apikey: str, symbol: str) -> typing.List[typing.Dict]: """ Query FMP /key-executives/ API. Gather info about company's key executives. :param apikey: Your API Key. :param symbol: Ticker of company. :return: A list of dictionaries. """ path = f"key-executives/{symbol}" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def search( apikey: str, query: str = "", limit: int = DEFAULT_LIMIT, exchange: str = "" ) -> typing.List[typing.Dict]: """ Query FMP /search/ API. Search via ticker and company name. :param apikey: Your API key. :param query: Whole or fragment of Ticker or Name of company. :param limit: Number of rows to return. :param exchange: Stock exchange to search. :return: A list of dictionaries. """ path = f"search/" query_vars = { "apikey": apikey, "limit": limit, "query": query, "exchange": __validate_exchange(value=exchange), } return __return_json_v3(path=path, query_vars=query_vars) def search_ticker( apikey: str, query: str = "", limit: int = DEFAULT_LIMIT, exchange: str = "" ) -> typing.List[typing.Dict]: """ Query FMP /search-ticker/ API. Search only via ticker. :param apikey: Your API key. :param query: Whole or fragment of Ticker. :param limit: Number of rows to return. :param exchange:Stock exchange to search. :return: A list of dictionaries. """ path = f"search-ticker/" query_vars = { "apikey": apikey, "limit": limit, "query": query, "exchange": __validate_exchange(value=exchange), } return __return_json_v3(path=path, query_vars=query_vars) def financial_statement( apikey: str, symbol: str, filename: str = FINANCIAL_STATEMENT_FILENAME ) -> None: """ Query FMP /financial-statements/ API. Download company's financial statement. :param apikey: Your API key. :param symbol: Ticker of company. :param filename: Name of saved file. :return: A list of dictionaries. """ path = f"financial-statements/{symbol}" query_vars = { "apikey": apikey, "datatype": "zip", # Only ZIP format is supported. } response = requests.get(f"{BASE_URL_v3}{path}", params=query_vars) open(filename, "wb").write(response.content) logging.info(f"Saving {symbol} financial statement as {filename}.") def income_statement( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, download: bool = False, filename: str = INCOME_STATEMENT_FILENAME, ) -> typing.Union[typing.List[typing.Dict], None]: """ Query FMP /income-statement/ API. Display or download company's income statement. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'quarter' or 'annual'. :param limit: Number of rows to return. :param download: True/False :param filename: Name of saved file. :return: A list of dictionaries. """ path = f"income-statement/{symbol}" query_vars = {"apikey": apikey, "limit": limit, "period": __validate_period(period)} if download: query_vars["datatype"] = "csv" # Only CSV is supported. response = requests.get(f"{BASE_URL_v3}{path}", params=query_vars) open(filename, "wb").write(response.content) logging.info(f"Saving {symbol} financial statement as {filename}.") else: return __return_json_v3(path=path, query_vars=query_vars) def balance_sheet_statement( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, download: bool = False, filename: str = BALANCE_SHEET_STATEMENT_FILENAME, ) -> typing.Union[typing.List[typing.Dict], None]: """ Query FMP /balance-sheet-statement/ API. Display or download company's balance sheet statement. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'quarter' or 'annual'. :param limit: Number of rows to return. :param download: True/False :param filename: Name of saved file. :return: A list of dictionaries. """ path = f"balance-sheet-statement/{symbol}" query_vars = {"apikey": apikey, "limit": limit, "period": __validate_period(period)} if download: query_vars["datatype"] = "csv" # Only CSV is supported. response = requests.get(f"{BASE_URL_v3}{path}", params=query_vars) open(filename, "wb").write(response.content) logging.info(f"Saving {symbol} financial statement as {filename}.") else: return __return_json_v3(path=path, query_vars=query_vars) def cash_flow_statement( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, download: bool = False, filename: str = CASH_FLOW_STATEMENT_FILENAME, ) -> typing.Union[typing.List[typing.Dict], None]: """ Query FMP /cash-flow-statement/ API. Display or download company's cash flow statement. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'quarter' or 'annual'. :param limit: Number of rows to return. :param download: True/False :param filename: Name of saved file. :return: A list of dictionaries. """ path = f"cash-flow-statement/{symbol}" query_vars = {"apikey": apikey, "limit": limit, "period": __validate_period(period)} if download: query_vars["datatype"] = "csv" # Only CSV is supported. response = requests.get(f"{BASE_URL_v3}{path}", params=query_vars) open(filename, "wb").write(response.content) logging.info(f"Saving {symbol} financial statement as {filename}.") else: return __return_json_v3(path=path, query_vars=query_vars) def financial_statement_symbol_lists(apikey: str) -> typing.List[typing.Dict]: """ Query FMP /financial-statement-symbol-lists/ API. List of symbols that have financial statements. :param apikey: Your API key. :return: A list of dictionaries. """ path = f"financial-statement-symbol-lists" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def income_statement_growth( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /income-statement-growth/ API. Growth stats for company's income statement. :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"income-statement-growth/{symbol}" query_vars = { "apikey": apikey, "limit": limit, } return __return_json_v3(path=path, query_vars=query_vars) def balance_sheet_statement_growth( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT ) -> typing.List[typing.Dict]: """ Query FMP /balance-sheet-statement-growth/ API. Growth stats for company's balance sheet statement. :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"balance-sheet-statement-growth/{symbol}" query_vars = { "apikey": apikey, "limit": limit, } return __return_json_v3(path=path, query_vars=query_vars) def cash_flow_statement_growth( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT ) -> typing.List[typing.Dict]: """ Query FMP /cash-flow-statement-growth/ API. Growth stats for company's cash flow statement. :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"cash-flow-statement-growth/{symbol}" query_vars = { "apikey": apikey, "limit": limit, } return __return_json_v3(path=path, query_vars=query_vars) def income_statement_as_reported( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, download: bool = False, filename: str = INCOME_STATEMENT_AS_REPORTED_FILENAME, ) -> typing.Union[typing.List[typing.Dict], None]: """ Query FMP /income-statement-as-reported/ API. Company's "as reported" income statement. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :param download: True/False :param filename: Name of saved file. :return: A list of dictionaries. """ path = f"income-statement-as-reported/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } if download: query_vars["datatype"] = "csv" # Only CSV is supported. response = requests.get(f"{BASE_URL_v3}{path}", params=query_vars) open(filename, "wb").write(response.content) logging.info(f"Saving {symbol} financial statement as {filename}.") else: return __return_json_v3(path=path, query_vars=query_vars) def balance_sheet_statement_as_reported( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, download: bool = False, filename: str = BALANCE_SHEET_STATEMENT_AS_REPORTED_FILENAME, ) -> typing.Union[typing.List[typing.Dict], None]: """ Query FMP /balance-sheet-statement-as-reported/ API. Company's "as reported" balance sheet statement. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :param download: True/False :param filename: Name of saved file. :return: A list of dictionaries. """ path = f"balance-sheet-statement-as-reported/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } if download: query_vars["datatype"] = "csv" # Only CSV is supported. response = requests.get(f"{BASE_URL_v3}{path}", params=query_vars) open(filename, "wb").write(response.content) logging.info(f"Saving {symbol} financial statement as {filename}.") else: return __return_json_v3(path=path, query_vars=query_vars) def cash_flow_statement_as_reported( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, download: bool = False, filename: str = CASH_FLOW_STATEMENT_AS_REPORTED_FILENAME, ) -> typing.Union[typing.List[typing.Dict], None]: """ Query FMP /cash-flow-statement-as-reported/ API. Company's "as reported" cash flow statement. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :param download: True/False :param filename: Name of saved file. :return: A list of dictionaries. """ path = f"cash-flow-statement-as-reported/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } if download: query_vars["datatype"] = "csv" # Only CSV is supported. response = requests.get(f"{BASE_URL_v3}{path}", params=query_vars) open(filename, "wb").write(response.content) logging.info(f"Saving {symbol} financial statement as {filename}.") else: return __return_json_v3(path=path, query_vars=query_vars) def financial_statement_full_as_reported( apikey: str, symbol: str, period: str = "annual", ) -> typing.List[typing.Dict]: """ Query FMP /financial-statement-full-as-reported/ API. Company's "as reported" full income statement. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :return: A list of dictionaries. """ path = f"financial-statement-full-as-reported/{symbol}" query_vars = {"apikey": apikey, "period": __validate_period(value=period)} return __return_json_v3(path=path, query_vars=query_vars) def financial_ratios_ttm(apikey: str, symbol: str) -> typing.List[typing.Dict]: """ Query FmP /ratios-ttm/ API. :param apikey: Your API key :param symbol: Company ticker :return: A list of dictionaries. """ path = f"ratios-ttm/{symbol}" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def financial_ratios( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FmP /ratios/ API. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"ratios/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } return __return_json_v3(path=path, query_vars=query_vars) def enterprise_values( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /enterprise-values/ API. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"enterprise-values/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } return __return_json_v3(path=path, query_vars=query_vars) def key_metrics_ttm( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /key-metrics-ttm/ API :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"key-metrics-ttm/{symbol}" query_vars = {"apikey": apikey, "limit": limit} return __return_json_v3(path=path, query_vars=query_vars) def key_metrics( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /key-metrics/ API :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"key-metrics/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } return __return_json_v3(path=path, query_vars=query_vars) def financial_growth( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /financial-growth/ API. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"financial-growth/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } return __return_json_v3(path=path, query_vars=query_vars) def rating(apikey: str, symbol: str) -> typing.List[typing.Dict]: """ Query FMP /rating/ API. :param apikey: Your API key. :param symbol: Company ticker. :return: A list of dictionaries. """ path = f"rating/{symbol}" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def historical_rating( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /financial-growth/ API. :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"financial-growth/{symbol}" query_vars = {"apikey": apikey, "limit": limit} return __return_json_v3(path=path, query_vars=query_vars) def discounted_cash_flow(apikey: str, symbol: str) -> typing.List[typing.Dict]: """ Query FMP /discounted-cash-flow/ API. :param apikey: Your API key. :param symbol: Company ticker. :return: A list of dictionaries. """ path = f"discounted-cash-flow/{symbol}" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def historical_discounted_cash_flow( apikey: str, symbol: str, period: str = "annual", limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /historical-discounted-cash-flow/ API. :param apikey: Your API key. :param symbol: Company ticker. :param period: 'annual' or 'quarter' :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"historical-discounted-cash-flow/{symbol}" query_vars = { "apikey": apikey, "limit": limit, "period": __validate_period(value=period), } return __return_json_v3(path=path, query_vars=query_vars) def historical_daily_discounted_cash_flow( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT ) -> typing.List[typing.Dict]: """ Query FMP /historical-daily-discounted-cash-flow/ API. :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"historical-daily-discounted-cash-flow/{symbol}" query_vars = {"apikey": apikey, "limit": limit} return __return_json_v3(path=path, query_vars=query_vars) def market_capitalization(apikey: str, symbol: str) -> typing.List[typing.Dict]: """ Query FMP /market-capitalization/ API. :param apikey: Your API key. :param symbol: Company ticker. :return: A list of dictionaries. """ path = f"market-capitalization/{symbol}" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def historical_market_capitalization( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT ) -> typing.List[typing.Dict]: """ Query FMP /historical-market-capitalization/ API. :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"historical-market-capitalization/{symbol}" query_vars = {"apikey": apikey, "limit": limit} return __return_json_v3(path=path, query_vars=query_vars) def symbols_list(apikey: str) -> typing.List[typing.Dict]: """ Query FMP /stock/list/ API :param apikey: Your API key. :return: A list of dictionaries. """ path = f"stock/list" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def etf_list(apikey: str) -> typing.List[typing.Dict]: """ Query FMP /etf/list/ API All ETF symbols :param apikey: Your API key. :return: A list of dictionaries. """ path = f"etf/list" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def available_traded_list(apikey: str) -> typing.List[typing.Dict]: """ Query FMP /available-traded/list/ API All tradable symbols :param apikey: Your API key. :return: A list of dictionaries. """ path = f"available-traded/list" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def stock_screener( apikey: str, market_cap_more_than: typing.Union[float, int] = None, market_cap_lower_than: typing.Union[float, int] = None, beta_more_than: typing.Union[float, int] = None, beta_lower_than: typing.Union[float, int] = None, volume_more_than: typing.Union[float, int] = None, volume_lower_than: typing.Union[float, int] = None, dividend_more_than: typing.Union[float, int] = None, dividend_lower_than: typing.Union[float, int] = None, price_more_than: typing.Union[float, int] = None, price_lower_than: typing.Union[float, int] = None, is_etf: bool = None, is_actively_trading: bool = None, sector: str = None, industry: str = None, country: str = None, exchange: typing.Union[str, typing.List[str]] = None, limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /stock-screener/ API. :param apikey: Your API key. :param market_cap_more_than: Numeric Value :param market_cap_lower_than: Numeric Value :param beta_more_than: Numeric Value :param beta_lower_than: Numeric Value :param volume_more_than: Numeric Value :param volume_lower_than: Numeric Value :param dividend_more_than: Numeric Value :param dividend_lower_than: Numeric Value :param price_more_than: Numeric Value :param price_lower_than: Numeric Value :param price_more_than: Numeric Value :param price_lower_than: Numeric Value :param is_etf: bool :param is_actively_trading: bool :param sector: Valid sector name. :param industry: Valid industry name. :param country: 2 digit country code as string. :param exchange: Stock exchange symbol. :param limit: Number of rows to return. :return: A list of dicitonaries. """ path = f"stock-screener" query_vars = {"apikey": apikey, "limit": limit} if market_cap_more_than: query_vars["marketCapMoreThan"] = market_cap_more_than if market_cap_lower_than: query_vars["marketCapLowerThan"] = market_cap_lower_than if beta_more_than: query_vars["betaMoreThan"] = beta_more_than if beta_lower_than: query_vars["betaLowerThan"] = beta_lower_than if volume_more_than: query_vars["volumeMoreThan"] = volume_more_than if volume_lower_than: query_vars["volumeLowerThan"] = volume_lower_than if dividend_more_than: query_vars["dividendMoreThan"] = dividend_more_than if dividend_lower_than: query_vars["dividendLowerThan"] = dividend_lower_than if price_more_than: query_vars["priceMoreThan"] = price_more_than if price_lower_than: query_vars["priceLowerThan"] = price_lower_than if is_etf: query_vars["isEtf"] = is_etf if is_actively_trading: query_vars["isActivelyTrading"] = is_actively_trading if sector: query_vars["sector"] = __validate_sector(sector) if industry: query_vars["industry"] = __validate_industry(industry) if country: query_vars["country"] = country if exchange: if type(exchange) is list: for item in exchange: if item != __validate_exchange(item): logging.error(f"Invalid Exchange value: {exchange}.") exit(1) query_vars["exchange"] = ",".join(exchange) else: query_vars["exchange"] = __validate_exchange(exchange) return __return_json_v3(path=path, query_vars=query_vars) def delisted_companies( apikey: str, limit: int = DEFAULT_LIMIT ) -> typing.List[typing.Dict]: """ Query FMP /delisted-companies/ API. :param apikey: Your API key. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"delisted-companies" query_vars = {"apikey": apikey, "limt": limit} return __return_json_v3(path=path, query_vars=query_vars) def stock_news( apikey: str, tickers: typing.Union[str, typing.List] = "", limit: int = DEFAULT_LIMIT, ) -> typing.List[typing.Dict]: """ Query FMP /stock_news/ API. :param apikey: Your API key. :param tickers: List of ticker symbols. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"stock_news" query_vars = {"apikey": apikey, "limt": limit} if tickers: if type(tickers) is list: tickers = ",".join(tickers) query_vars["tickers"] = tickers return __return_json_v3(path=path, query_vars=query_vars) def earnings_surprises(apikey: str, symbol: str) -> typing.List[typing.Dict]: """ Query FMP /earnings-surprises/ API. :param apikey: Your API key. :param symbol: Company ticker. :return: A list of dictionaries. """ path = f"earnings-surprises/{symbol}" query_vars = {"apikey": apikey} return __return_json_v3(path=path, query_vars=query_vars) def sec_filings( apikey: str, symbol: str, filing_type: str = "", limit: int = DEFAULT_LIMIT ) -> typing.List[typing.Dict]: """ Query FMP /sec_filings/ API. :param apikey: Your API key. :param symbol: Company ticker. :param filing_type: Name of filing. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"sec_filings/{symbol}" query_vars = {"apikey": apikey, "type": filing_type, "limit": limit} return __return_json_v3(path=path, query_vars=query_vars) def press_releases( apikey: str, symbol: str, limit: int = DEFAULT_LIMIT ) -> typing.List[typing.Dict]: """ Query FMP /press-releases/ API. :param apikey: Your API key. :param symbol: Company ticker. :param limit: Number of rows to return. :return: A list of dictionaries. """ path = f"press-releases/{symbol}" query_vars = {"apikey": apikey, "limit": limit} return __return_json_v3(path=path, query_vars=query_vars)

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a24afb1247a1ee3eec101b00a6f34bf2ddc4a700

160

py

Python

tests/urls.py

lenarother/django-critical-css

15c12ea02f7ea049e59efba4d963c35f41f26d78

[ "MIT" ]

2

2020-06-06T06:50:38.000Z

2022-02-03T08:54:28.000Z

tests/urls.py

lenarother/django-critical-css

15c12ea02f7ea049e59efba4d963c35f41f26d78

[ "MIT" ]

5

2018-12-17T11:12:20.000Z

2020-11-27T10:28:51.000Z

tests/urls.py

lenarother/django-critical-css

15c12ea02f7ea049e59efba4d963c35f41f26d78

[ "MIT" ]

1

2021-08-19T06:02:44.000Z

try: from django.urls import include, url except ImportError: from django.conf.urls import include, url urlpatterns = [url(r'', include('cms.urls'))]

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a254a7aeef1e4efe256a6460a82f662dc6b9a927

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py

Python

GPErks/serialization/labels.py

stelong/GPErks

7e8e0e4561c10ad21fba2079619418e416a167b6

[ "MIT" ]

null

GPErks/serialization/labels.py

stelong/GPErks

7e8e0e4561c10ad21fba2079619418e416a167b6

[ "MIT" ]

6

2021-12-10T14:16:51.000Z

2022-03-25T16:26:50.000Z

GPErks/serialization/labels.py

stelong/GPErks

7e8e0e4561c10ad21fba2079619418e416a167b6

[ "MIT" ]

1

2022-01-28T11:12:33.000Z

def read_labels_from_file(labels_file_path): with open(labels_file_path, "r") as f: return f.read().splitlines()

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a2dafd326fe659346652f4e6498ea2553021c151

26

py

Python

utils/__init__.py

jackklys/wake-sleep-modifications

f3e515eea8f683bf32bf3cfeed31a237bfcc2347

[ "MIT" ]

2

2018-06-11T03:41:09.000Z

2019-11-25T09:39:01.000Z

utils/__init__.py

jackklys/wake-sleep-modifications

f3e515eea8f683bf32bf3cfeed31a237bfcc2347

[ "MIT" ]

null

utils/__init__.py

jackklys/wake-sleep-modifications

f3e515eea8f683bf32bf3cfeed31a237bfcc2347

[ "MIT" ]

3

2017-07-21T08:40:21.000Z

2020-10-04T21:15:53.000Z

from utils.misc import *

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