xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

f509afecc5073874e0a289659f496d3e2b4334c5

1,104

py

Python

tests/test_label_maximum_extension_map.py

elsandal/pyclesperanto_prototype

7bda828813b86b44b63d73d5e8f466d9769cded1

[ "BSD-3-Clause" ]

64

2020-03-18T12:11:22.000Z

2022-03-31T08:19:18.000Z

tests/test_label_maximum_extension_map.py

elsandal/pyclesperanto_prototype

7bda828813b86b44b63d73d5e8f466d9769cded1

[ "BSD-3-Clause" ]

148

2020-05-14T06:14:11.000Z

2022-03-26T15:02:31.000Z

tests/test_label_maximum_extension_map.py

elsandal/pyclesperanto_prototype

7bda828813b86b44b63d73d5e8f466d9769cded1

[ "BSD-3-Clause" ]

16

2020-05-31T00:53:44.000Z

2022-03-23T13:20:57.000Z

import pyclesperanto_prototype as cle import numpy as np def test_label_label_maximum_extension_map_2d(): labels = cle.push(np.asarray([ [1, 1, 2], [1, 0, 0], [3, 3, 0] ])) reference = cle.push(np.asarray([ [0.74535596, 0.74535596, 0], [0.74535596, 0, 0], [0.5, 0.5, 0] ] )) result = cle.label_maximum_extension_map(labels) a = cle.pull(result) b = cle.pull(reference) print(a) print(b) assert (np.allclose(a, b, 0.001)) def test_label_label_maximum_extension_map_3d(): labels = cle.push(np.asarray([ [ [1, 1, 2], ], [ [1, 0, 0], ], [ [3, 3, 0] ] ])) reference = cle.push(np.asarray([ [ [0.74535596, 0.74535596, 0], ], [ [0.74535596, 0, 0], ], [ [0.5, 0.5, 0] ] ] )) result = cle.label_maximum_extension_map(labels) a = cle.pull(result) b = cle.pull(reference) print(a) print(b) assert (np.allclose(a, b, 0.001))

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1,104

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8

f567d64ec46f5d65ead03fc1b3e27aded528c123

655

py

Python

user/vistas/widgets/widget-marker.py

ZerpaTechnology/occoa

a8c0bd2657bc058801a883109c0ec0d608d04ccc

[ "Apache-2.0" ]

null

user/vistas/widgets/widget-marker.py

ZerpaTechnology/occoa

a8c0bd2657bc058801a883109c0ec0d608d04ccc

[ "Apache-2.0" ]

null

user/vistas/widgets/widget-marker.py

ZerpaTechnology/occoa

a8c0bd2657bc058801a883109c0ec0d608d04ccc

[ "Apache-2.0" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- print '''<div class="bg-ubuntu_jet d-inline-block text-center"><img src="'''+str(data['base_url']+'static/imgs/marker/institucion-default.png')+'''"><h3 class="white">Tiempo restante: </h3><span class="ubuntu_green">1:00</span><h3 class="white">Marcador:</h3><div> <h4 class="white">Partido</h4> <img src="'''+str(data['base_url']+'static/imgs/marker/partido-default.png')+'''" class="shauto-5"><span class="white"> Votos: 0</span> <h4 class="white">Partido</h4> <img src="'''+str(data['base_url']+'static/imgs/marker/partido-default.png')+'''" class="shauto-5"><span class="white"> Votos: 0</span></div></div>'''

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0.139211

0.062645

0.090487

0.593968

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655

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null

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1

0

7

1936a5712a4d4b8d19eddb85360a3e7a4305626f

37

py

Python

annotmpl/__init__.py

mwaskom/annotmpl

f2a2d213bc0bb95bbff6bc90b4eeae9cc069968e

[ "BSD-3-Clause" ]

null

annotmpl/__init__.py

mwaskom/annotmpl

f2a2d213bc0bb95bbff6bc90b4eeae9cc069968e

[ "BSD-3-Clause" ]

null

annotmpl/__init__.py

mwaskom/annotmpl

f2a2d213bc0bb95bbff6bc90b4eeae9cc069968e

[ "BSD-3-Clause" ]

null

from api import * # noqa: F401,F403

18.5

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0

7

193ccce92a9589bf0c167414dc73fdd932ed83f4

60,764

py

Python

stable_baselines/mdal/adversary.py

shanlior/OAL

39c9eb24f64a27d3da09e92b6da9bf60326baabe

[ "MIT" ]

3

2021-04-08T12:49:16.000Z

2022-03-11T00:53:47.000Z

stable_baselines/mdal/adversary.py

shanlior/OAL

39c9eb24f64a27d3da09e92b6da9bf60326baabe

[ "MIT" ]

null

stable_baselines/mdal/adversary.py

shanlior/OAL

39c9eb24f64a27d3da09e92b6da9bf60326baabe

[ "MIT" ]

null

""" Reference: https://github.com/openai/imitation I follow the architecture from the official repository """ import gym import tensorflow as tf import numpy as np from stable_baselines.common.mpi_running_mean_std import RunningMeanStd as MpiRunningMeanStd from stable_baselines.common.running_mean_std import RunningMeanStd, RunningMinMax from stable_baselines.common import tf_util as tf_util from stable_baselines.common import zipsame def logsigmoid(input_tensor): """ Equivalent to tf.log(tf.sigmoid(a)) :param input_tensor: (tf.Tensor) :return: (tf.Tensor) """ return -tf.nn.softplus(-input_tensor) def logit_bernoulli_entropy(logits): """ Reference: https://github.com/openai/imitation/blob/99fbccf3e060b6e6c739bdf209758620fcdefd3c/policyopt/thutil.py#L48-L51 :param logits: (tf.Tensor) the logits :return: (tf.Tensor) the Bernoulli entropy """ ent = (1. - tf.nn.sigmoid(logits)) * logits - logsigmoid(logits) return ent # class TabularAdversary(object): def __init__(self, observation_space, action_space, hidden_size, entcoeff=0.00, scope="adversary", normalize=True, expert_features=None, exploration_bonus=False, bonus_coef=0.01, t_c=0.1): """ Reward regression from observations and transitions :param observation_space: (gym.spaces) :param action_space: (gym.spaces) :param hidden_size: ([int]) the hidden dimension for the MLP :param entcoeff: (float) the entropy loss weight :param scope: (str) tensorflow variable scope :param normalize: (bool) Whether to normalize the reward or not """ # TODO: support images properly (using a CNN) self.scope = scope self.observation_shape = observation_space.shape self.actions_shape = action_space.shape if isinstance(action_space, gym.spaces.Box): # Continuous action space self.discrete_actions = False self.n_actions = action_space.shape[0] elif isinstance(action_space, gym.spaces.Discrete): self.n_actions = action_space.n self.discrete_actions = True else: raise ValueError('Action space not supported: {}'.format(action_space)) self.hidden_size = hidden_size self.normalize = normalize self.obs_rms = None self.expert_features = expert_features self.reward = expert_features normalization = np.linalg.norm(self.reward) self.norm_factor = np.sqrt(float(self.observation_shape[0])) if normalization > 1: self.reward = self.reward / (self.norm_factor * normalization) self.exploration_bonus = exploration_bonus self.t_c = t_c self.bonus_coef = bonus_coef if self.exploration_bonus: self.covariance_lambda = np.identity(self.observation_shape[0]) else: self.covariance_lambda = None def update_reward(self, features): t_c = self.t_c # self.reward = (1-t_c) * self.reward + t_c * (self.expert_features - features) self.reward = self.reward + t_c * (self.expert_features - features) / self.norm_factor normalization = np.linalg.norm(self.reward) if normalization > 1: self.reward = self.reward / normalization def get_reward(self, observation): """ Predict the reward using the observation and action :param obs: (tf.Tensor or np.ndarray) the observation :param actions: (tf.Tensor or np.ndarray) the action :return: (np.ndarray) the reward """ if self.exploration_bonus: self.covariance_lambda = self.covariance_lambda \ + np.matmul(np.expand_dims(observation, axis=1), np.expand_dims(observation, axis=0)) inverse_covariance = np.linalg.inv(self.covariance_lambda) reward = np.matmul(observation, np.reshape(self.reward, (self.reward.shape[0], 1))).squeeze() bonus = np.sqrt(np.matmul(np.matmul(observation,inverse_covariance), observation)) return reward + self.bonus_coef * bonus else: reward = np.matmul(observation, np.reshape(self.reward, (self.reward.shape[0], 1))).squeeze() return reward class TabularAdversaryTF(object): def __init__(self, sess, observation_space, action_space, hidden_size, entcoeff=0.00, scope="adversary", normalize=True, expert_features=None, exploration_bonus=False, is_action_features=True, bonus_coef=0.01, t_c=0.1): """ Reward regression from observations and transitions :param observation_space: (gym.spaces) :param action_space: (gym.spaces) :param hidden_size: ([int]) the hidden dimension for the MLP :param entcoeff: (float) the entropy loss weight :param scope: (str) tensorflow variable scope :param normalize: (bool) Whether to normalize the reward or not """ # TODO: support images properly (using a CNN) self.scope = scope self.sess = sess self.observation_shape = observation_space.shape self.actions_shape = action_space.shape self.is_action_features = is_action_features if isinstance(action_space, gym.spaces.Box): # Continuous action space self.discrete_actions = False self.n_actions = action_space.shape[0] elif isinstance(action_space, gym.spaces.Discrete): self.n_actions = action_space.n self.discrete_actions = True else: raise ValueError('Action space not supported: {}'.format(action_space)) if self.is_action_features: self.n_features = self.observation_shape[0] + self.n_actions else: self.n_features = self.observation_shape[0] expert_features = expert_features[:self.n_features] self.hidden_size = hidden_size self.normalize = normalize self.obs_rms = None self.expert_features = tf.constant(expert_features, dtype=tf.float32) self.norm_factor = tf.sqrt(float(self.n_features)) # self.normalization = tf.square(float(np.linalg.norm(expert_features))) self.normalization = np.linalg.norm(expert_features) expert_normalization = np.linalg.norm(expert_features) # if expert_normalization > 1: # self.reward_vec = tf.Variable(expert_features / (self.norm_factor * expert_normalization), dtype=tf.float32) self.reward_vec = tf.Variable(expert_features, dtype=tf.float32) # else: # self.reward_vec = tf.Variable(expert_features / self.norm_factor) # self.reward_vec = tf.Variable(expert_features, dtype=tf.float32) # self.reward_vec = tf.Variable(expert_features / self.normalization, dtype=tf.float32) # if normalization > 1: # self.reward_vec = tf.Variable(expert_features / normalization, dtype=tf.float32) # else: # self.reward_vec = tf.Variable(expert_features, dtype=tf.float32) # self.exploration_bonus = exploration_bonus self.t_c = t_c self.bonus_coef = bonus_coef if self.exploration_bonus: self.covariance_lambda = tf.Variable(tf.eye(self.n_features), dtype=tf.float32) self.inverse_covariance = tf.eye(self.n_features) else: self.covariance_lambda = None self.inverse_covariance = None # Placeholders self.features_ph = tf.placeholder(tf.float32, (None,) + (self.n_features, ), name="observations_ph") self.successor_features_ph = tf.placeholder(tf.float32, (self.n_features, ), name="successor_features_ph") # Build graph with tf.variable_scope(self.scope, reuse=False): if self.normalize: with tf.variable_scope("obfilter"): self.obs_rms = RunningMeanStd(shape=self.n_features) # self.obs_rms = RunningMinMax(shape=self.observation_shape) obs_scaled = (tf.cast(self.features_ph, tf.float32) - self.obs_rms.mean)\ / tf.cast(tf.sqrt(self.obs_rms.var), tf.float32) reward_vec_scaled = (tf.cast(self.reward_vec, tf.float32) - self.obs_rms.mean)\ / (tf.cast(tf.sqrt(self.obs_rms.var), tf.float32)) # obs_scaled = (tf.cast(self.features_ph, tf.float32)) / tf.cast(self.obs_rms.scale, tf.float32) obs = obs_scaled # reward_vec_scaled = (tf.cast(self.reward_vec, tf.float32)) / tf.cast(self.obs_rms.scale, # tf.float32) reward_vec = reward_vec_scaled / tf.norm(reward_vec_scaled) else: obs = self.features_ph reward_vec = self.reward_vec if self.exploration_bonus: self.new_covariance_lambda = self.covariance_lambda \ + tf.reduce_sum( tf.matmul(tf.expand_dims(tf.cast(self.features_ph, tf.float32), axis=2), tf.expand_dims(tf.cast(self.features_ph, tf.float32), axis=1)), axis=0) self.update_covariance_op = tf.assign(self.covariance_lambda, self.new_covariance_lambda) bonus = tf.squeeze(tf.sqrt(tf.matmul(tf.matmul(tf.expand_dims(obs, axis=1), self.inverse_covariance), tf.expand_dims(obs, axis=2)))) reward = tf.squeeze(tf.matmul(obs, tf.expand_dims(reward_vec, 1))) self.reward_op = reward + self.bonus_coef * bonus else: self.reward_op = tf.squeeze(tf.matmul(obs, tf.expand_dims(reward_vec, 1))) # Update reward self.new_reward_vec = self.reward_vec + self.t_c * (self.expert_features - self.successor_features_ph) # self.new_reward_vec = self.reward_vec\ # + self.t_c * (self.expert_features - self.successor_features_ph)\ # / (self.normalization * self.norm_factor) # normalization = tf.norm(self.new_reward_vec) * self.normalization # normalization = tf.norm(self.new_reward_vec) # self.new_reward_vec = tf.cond(normalization > 1.0, # true_fn=lambda: self.new_reward_vec / normalization, # false_fn=lambda: self.new_reward_vec) # self.new_reward_vec = self.new_reward_vec / normalization # reward_vec_unnormalized = self.reward_vec + self.t_c * (self.expert_features - self.successor_features_ph) # reward_vec_scaled = (tf.cast(reward_vec_unnormalized, tf.float32)) / tf.cast(self.obs_rms.scale, tf.float32) # self.new_reward_vec = reward_vec_scaled / tf.norm(reward_vec_scaled) self.update_reward_op = tf.assign(self.reward_vec, self.new_reward_vec) def update_reward(self, successor_features): # # sess = tf.get_default_session() # if len(features.shape) == 1: # features = np.expand_dims(features, 0) if not self.is_action_features: successor_features = successor_features[:self.observation_shape[0]] feed_dict = {self.successor_features_ph: successor_features} if self.exploration_bonus: self.inverse_covariance = tf.linalg.inv(self.covariance_lambda) self.sess.run(self.update_reward_op, feed_dict) def get_reward(self, obs, action=None): """ Predict the reward using the observation and action :param obs: (tf.Tensor or np.ndarray) the observation :param actions: (tf.Tensor or np.ndarray) the action :return: (np.ndarray) the reward """ # sess = tf.get_default_session() if len(obs.shape) == 1: obs = np.expand_dims(obs, 0) if len(action.shape) == 1: action = np.expand_dims(action, 0) if self.is_action_features: features = np.concatenate((obs, action), axis=1) else: features = obs feed_dict = {self.features_ph: features} if self.exploration_bonus: reward, _ = self.sess.run([self.reward_op, self.update_covariance_op], feed_dict) else: reward = self.sess.run(self.reward_op, feed_dict) return reward class NeuralAdversary(object): def __init__(self, sess, observation_space, action_space, hidden_size=64, lipschitz_reg_coef=1.0, scope="adversary", normalize=True): """ Reward regression from observations and transitions :param observation_space: (gym.spaces) :param action_space: (gym.spaces) :param hidden_size: ([int]) the hidden dimension for the MLP :param entcoeff: (float) the entropy loss weight :param scope: (str) tensorflow variable scope :param normalize: (bool) Whether to normalize the reward or not """ # TODO: support images properly (using a CNN) self.sess = sess self.scope = scope self.observation_shape = observation_space.shape self.actions_shape = action_space.shape if isinstance(action_space, gym.spaces.Box): # Continuous action space self.discrete_actions = False self.n_actions = action_space.shape[0] elif isinstance(action_space, gym.spaces.Discrete): self.n_actions = action_space.n self.discrete_actions = True else: raise ValueError('Action space not supported: {}'.format(action_space)) self.hidden_size = hidden_size self.normalize = normalize self.obs_rms = None # Placeholders self.policy_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="observations_ph") self.policy_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="actions_ph") self.policy_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="gammas_ph") self.expert_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.expert_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") self.expert_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="gammas_ph") self.mix_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.mix_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") # Build graph policy_rewards = self.build_graph(self.policy_obs_ph, self.policy_acs_ph, reuse=False) expert_rewards = self.build_graph(self.expert_obs_ph, self.expert_acs_ph, reuse=True) # generator_rewards = tf.math.sigmoid(generator_logits) # expert_rewards = tf.math.sigmoid(expert_logits) # policy_scaled_rewards = tf.multiply(policy_rewards, self.policy_gammas_ph) policy_scaled_rewards = policy_rewards # policy_value = (1-0.99) * tf.reduce_sum(policy_scaled_rewards) policy_value = tf.reduce_mean(policy_scaled_rewards) # expert_scaled_rewards = tf.multiply(expert_rewards, self.expert_gammas_ph) expert_scaled_rewards = expert_rewards # expert_value = (1-0.99) * tf.reduce_sum(expert_scaled_rewards) expert_value = tf.reduce_mean(expert_scaled_rewards) # alpha = tf.random.uniform([], 0.0, 1.0, observation_space.dtype) # generator_obs_mix = tf.reduce_mean(self.generator_obs_ph, axis=0, keepdims=True) # generator_acs_mix = tf.reduce_mean(self.generator_acs_ph, axis=0, keepdims=True) # expert_obs_mix = tf.reduce_mean(self.expert_obs_ph, axis=0, keepdims=True) # expert_acs_mix = tf.reduce_mean(self.expert_acs_ph, axis=0, keepdims=True) # generator_obs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.generator_gammas_ph, observation_space.dtype) * self.generator_obs_ph, axis=0, keepdims=True) # generator_acs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.generator_gammas_ph, action_space.dtype) * self.generator_acs_ph, axis=0, keepdims=True) # expert_obs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.expert_gammas_ph, observation_space.dtype) * self.expert_obs_ph, axis=0, keepdims=True) # expert_acs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.expert_gammas_ph, action_space.dtype) * self.expert_acs_ph, axis=0, keepdims=True) # mixture_obs = alpha * generator_obs_mix + (1 - alpha) * tf.reduce_mean(expert_obs_mix) # mixture_acs = tf.cast(alpha, action_space.dtype) * generator_acs_mix\ # + tf.cast((1 - alpha), action_space.dtype) * expert_acs_mix mixture_rewards = self.build_graph(self.mix_obs_ph, self.mix_acs_ph, reuse=True) grads = tf.gradients(mixture_rewards, [self.mix_obs_ph, self.mix_acs_ph])[0] norm = tf.cast(tf.sqrt(tf.reduce_sum(tf.square(grads), axis=1)), tf.float32) lipschitz_reg = tf.reduce_mean(tf.square(norm - 1.0)) lipschitz_reg_loss = lipschitz_reg_coef * lipschitz_reg rewards = tf.concat([policy_rewards, expert_rewards], 0) rewards_reg = - tf.reduce_mean(logit_bernoulli_entropy(rewards)) rewards_reg_coef = 0.001 # rewards_reg = tf.reduce_sum(tf.square(rewards)) # rewards_reg_coef = 0.01 rewards_reg_loss = rewards_reg_coef * rewards_reg policy_loss = policy_value - expert_value loss = policy_loss + lipschitz_reg_loss + rewards_reg_loss # Loss + Accuracy terms self.losses = [loss] self.loss_name = ["generator_loss", "expert_loss", "entropy", "entropy_loss", "generator_acc", "expert_acc"] # self.total_loss = loss # Build Reward for policy self.reward_op = tf.clip_by_value(policy_rewards, -10.0, 10.0) # self.reward_op = tf.stop_gradient(policy_rewards) # self.reward_op = generator_rewards var_list = self.get_trainable_variables() rewards_optimizer = tf.train.AdamOptimizer(learning_rate=3e-4) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=1e-5) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=3e-4, beta1=0) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=1e-3, beta1=0.5) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=1e-2) # grads, vars = zip(*rewards_optimizer.compute_gradients(loss, var_list=var_list)) # accum_vars = [tf.Variable(tf.zeros_like(var.initialized_value()), trainable=False) for var in var_list] # accumulation_counter = tf.Variable(0.0, trainable=False) # zero_ops = [var.assign(tf.zeros_like(var)) for var in accum_vars] # zero_ops.append(accumulation_counter.assign(0.0)) # gvs = rewards_optimizer.compute_gradients(loss, var_list) # accumulate_ops = [accum_vars[i].assign_add(gv[0]) for i, gv in enumerate(gvs)] # accumulate_ops.append(accumulation_counter.assign_add(1.0)) # train_step = rewards_optimizer.apply_gradients([(accum_vars[i] / accumulation_counter, gv[1]) for i, gv in enumerate(gvs)]) # grads, vars = list(zip(*grads_and_vars)) # grads, norm = tf.clip_by_global_norm(grads, 300.0) # rewards_train_op = rewards_optimizer.apply_gradients(zip(grads, vars)) # norm = tf.constant(0.) rewards_train_op = rewards_optimizer.minimize(loss, var_list=var_list) # rewards_train_op = [rewards_train_op, norm] # self.zero_grad = tf_util.function([], zero_ops) # self.compute_grads = tf_util.function( # [self.generator_obs_ph, self.generator_acs_ph, self.generator_gammas_ph, # self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph], accumulate_ops) # self.train = tf_util.function([], train_step) # print_op = tf.print("Value diff:", policy_value - expert_value, "Grad Regularizer:", lipschitz_reg) print_op = tf.no_op() self.train = tf_util.function( [self.policy_obs_ph, self.policy_acs_ph, self.policy_gammas_ph, self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph, self.mix_obs_ph, self.mix_acs_ph], [rewards_train_op, print_op]) def build_graph(self, obs_ph, acs_ph, reuse=False): """ build the graph :param obs_ph: (tf.Tensor) the observation placeholder :param acs_ph: (tf.Tensor) the action placeholder :param reuse: (bool) :return: (tf.Tensor) the graph output """ with tf.variable_scope(self.scope): if reuse: tf.get_variable_scope().reuse_variables() if self.normalize: with tf.variable_scope("obfilter"): self.obs_rms = RunningMeanStd(shape=self.observation_shape) obs = (tf.cast(obs_ph, tf.float32) - self.obs_rms.mean) / tf.cast(tf.sqrt(self.obs_rms.var), tf.float32) else: obs = tf.cast(obs_ph, tf.float32) if self.discrete_actions: one_hot_actions = tf.one_hot(acs_ph, self.n_actions) actions_ph = tf.cast(one_hot_actions, tf.float32) else: actions_ph = acs_ph _input = tf.concat([obs, actions_ph], axis=1) # concatenate the two input -> form a transition p_h1 = tf.contrib.layers.fully_connected(_input, self.hidden_size, activation_fn=tf.nn.tanh) p_h2 = tf.contrib.layers.fully_connected(p_h1, self.hidden_size, activation_fn=tf.nn.tanh) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.nn.tanh) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.math.sigmoid) rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.identity) return rewards def get_trainable_variables(self): """ Get all the trainable variables from the graph :return: ([tf.Tensor]) the variables """ return tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, self.scope) def get_reward(self, obs, actions): """ Predict the reward using the observation and action :param obs: (tf.Tensor or np.ndarray) the observation :param actions: (tf.Tensor or np.ndarray) the action :return: (np.ndarray) the reward """ # sess = tf.get_default_session() if len(obs.shape) == 1: obs = np.expand_dims(obs, 0) if len(actions.shape) == 1: actions = np.expand_dims(actions, 0) elif len(actions.shape) == 0: # one discrete action actions = np.expand_dims(actions, 0) feed_dict = {self.policy_obs_ph: obs, self.policy_acs_ph: actions} reward = self.sess.run(self.reward_op, feed_dict) return reward class NeuralAdversaryTRPO(object): def __init__(self, sess, observation_space, action_space, hidden_size=64, entcoeff=0.001, scope="adversary", normalize=True): """ Reward regression from observations and transitions :param observation_space: (gym.spaces) :param action_space: (gym.spaces) :param hidden_size: ([int]) the hidden dimension for the MLP :param entcoeff: (float) the entropy loss weight :param scope: (str) tensorflow variable scope :param normalize: (bool) Whether to normalize the reward or not """ # TODO: support images properly (using a CNN) self.sess = sess self.scope = scope self.observation_shape = observation_space.shape self.actions_shape = action_space.shape if isinstance(action_space, gym.spaces.Box): # Continuous action space self.discrete_actions = False self.n_actions = action_space.shape[0] elif isinstance(action_space, gym.spaces.Discrete): self.n_actions = action_space.n self.discrete_actions = True else: raise ValueError('Action space not supported: {}'.format(action_space)) self.hidden_size = hidden_size self.normalize = normalize self.obs_rms = None # Placeholders self.policy_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="observations_ph") self.policy_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="actions_ph") self.policy_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="gammas_ph") self.expert_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.expert_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") self.expert_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="gammas_ph") self.mix_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.mix_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") # Build graph policy_rewards = self.build_graph(self.policy_obs_ph, self.policy_acs_ph, reuse=False) expert_rewards = self.build_graph(self.expert_obs_ph, self.expert_acs_ph, reuse=True) # policy_rewards = tf.math.sigmoid(policy_logits) # expert_rewards = tf.math.sigmoid(expert_logits) # policy_scaled_rewards = tf.multiply(policy_rewards, self.policy_gammas_ph) policy_scaled_rewards = policy_rewards # policy_value = tf.reduce_sum(policy_scaled_rewards) policy_value = tf.reduce_mean(policy_scaled_rewards) # expert_scaled_rewards = tf.multiply(expert_rewards, self.expert_gammas_ph) expert_scaled_rewards = expert_rewards # expert_value = tf.reduce_sum(expert_scaled_rewards) expert_value = tf.reduce_mean(expert_scaled_rewards) # alpha = tf.random.uniform([], 0.0, 1.0, observation_space.dtype) # generator_obs_mix = tf.reduce_mean(self.generator_obs_ph, axis=0, keepdims=True) # generator_acs_mix = tf.reduce_mean(self.generator_acs_ph, axis=0, keepdims=True) # expert_obs_mix = tf.reduce_mean(self.expert_obs_ph, axis=0, keepdims=True) # expert_acs_mix = tf.reduce_mean(self.expert_acs_ph, axis=0, keepdims=True) # generator_obs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.generator_gammas_ph, observation_space.dtype) * self.generator_obs_ph, axis=0, keepdims=True) # generator_acs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.generator_gammas_ph, action_space.dtype) * self.generator_acs_ph, axis=0, keepdims=True) # expert_obs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.expert_gammas_ph, observation_space.dtype) * self.expert_obs_ph, axis=0, keepdims=True) # expert_acs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.expert_gammas_ph, action_space.dtype) * self.expert_acs_ph, axis=0, keepdims=True) # mixture_obs = alpha * generator_obs_mix + (1 - alpha) * tf.reduce_mean(expert_obs_mix) # mixture_acs = tf.cast(alpha, action_space.dtype) * generator_acs_mix\ # + tf.cast((1 - alpha), action_space.dtype) * expert_acs_mix mixture_rewards = self.build_graph(self.mix_obs_ph, self.mix_acs_ph, reuse=True) grads = tf.gradients(mixture_rewards, [self.mix_obs_ph, self.mix_acs_ph])[0] norm = tf.cast(tf.sqrt(tf.reduce_sum(tf.square(grads), axis=1)), tf.float32) lipschitz_reg = tf.reduce_mean(tf.square(norm - 1.0)) lipschitz_reg_coef = 0.0 lipschitz_reg_loss = lipschitz_reg_coef * lipschitz_reg rewards = tf.concat([policy_rewards, expert_rewards], 0) rewards_reg = - tf.reduce_mean(logit_bernoulli_entropy(rewards)) # rewards_reg = tf.reduce_sum(tf.square(rewards)) rewards_reg_coef = 0.0 rewards_reg_loss = rewards_reg_coef * rewards_reg policy_loss = policy_value - expert_value self.total_loss = policy_loss + lipschitz_reg_loss + rewards_reg_loss # Loss + Accuracy terms self.losses = [] self.loss_name = ["generator_loss", "expert_loss", "entropy", "entropy_loss", "generator_acc", "expert_acc"] # self.total_loss = loss # Build Reward for policy # self.reward_op = tf.stop_gradient(policy_rewards) self.reward_op = tf.stop_gradient(tf.clip_by_value(policy_rewards, -1.0, 1.0)) # self.reward_op = generator_rewards print_op = tf.print("Policy loss:", policy_loss, "GradReg", lipschitz_reg, "rewards_abs_mean", tf.reduce_mean(tf.abs(rewards)), "rewards_std", tf.math.reduce_std(rewards), "abs_max", tf.math.reduce_max(tf.abs(rewards))) var_list = self.get_trainable_variables() self.lossandgrad = tf_util.function( [self.policy_obs_ph, self.policy_acs_ph, self.policy_gammas_ph, self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph, self.mix_obs_ph, self.mix_acs_ph], self.losses + [print_op] + [tf_util.flatgrad(self.total_loss, var_list)]) # print_op = tf.print("Value diff:", policy_value - expert_value, "Grad Regularizer:", lipschitz_reg) # print_op = tf.no_op() # self.train = tf_util.function( # [self.policy_obs_ph, self.policy_acs_ph, self.policy_gammas_ph, # self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph, # self.mix_obs_ph, self.mix_acs_ph], [rewards_train_op, print_op]) def build_graph(self, obs_ph, acs_ph, reuse=False): """ build the graph :param obs_ph: (tf.Tensor) the observation placeholder :param acs_ph: (tf.Tensor) the action placeholder :param reuse: (bool) :return: (tf.Tensor) the graph output """ with tf.variable_scope(self.scope): if reuse: tf.get_variable_scope().reuse_variables() if self.normalize: with tf.variable_scope("obfilter"): self.obs_rms = MpiRunningMeanStd(shape=self.observation_shape) obs = (tf.cast(obs_ph, tf.float32) - self.obs_rms.mean) / tf.cast(self.obs_rms.std, tf.float32) else: obs = tf.cast(obs_ph, tf.float32) if self.discrete_actions: one_hot_actions = tf.one_hot(acs_ph, self.n_actions) actions_ph = tf.cast(one_hot_actions, tf.float32) else: actions_ph = acs_ph _input = tf.concat([obs, actions_ph], axis=1) # concatenate the two input -> form a transition p_h1 = tf.contrib.layers.fully_connected(_input, self.hidden_size, activation_fn=tf.nn.tanh) p_h2 = tf.contrib.layers.fully_connected(p_h1, self.hidden_size, activation_fn=tf.nn.tanh) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.nn.tanh) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.math.sigmoid) rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.identity) # last_layer_init = tf.contrib.layers.variance_scaling_initializer(factor=0.1, mode='FAN_AVG', uniform=True) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.identity, weights_initializer=last_layer_init) return rewards def get_trainable_variables(self): """ Get all the trainable variables from the graph :return: ([tf.Tensor]) the variables """ return tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, self.scope) def get_reward(self, obs, actions): """ Predict the reward using the observation and action :param obs: (tf.Tensor or np.ndarray) the observation :param actions: (tf.Tensor or np.ndarray) the action :return: (np.ndarray) the reward """ # sess = tf.get_default_session() if len(obs.shape) == 1: obs = np.expand_dims(obs, 0) if len(actions.shape) == 1: actions = np.expand_dims(actions, 0) elif len(actions.shape) == 0: # one discrete action actions = np.expand_dims(actions, 0) feed_dict = {self.policy_obs_ph: obs, self.policy_acs_ph: actions} reward = self.sess.run(self.reward_op, feed_dict) return reward class NeuralAdversaryMDPO(object): def __init__(self, sess, observation_space, action_space, hidden_size=64, scope="adversary", normalize=True): """ Reward regression from observations and transitions :param observation_space: (gym.spaces) :param action_space: (gym.spaces) :param hidden_size: ([int]) the hidden dimension for the MLP :param entcoeff: (float) the entropy loss weight :param scope: (str) tensorflow variable scope :param normalize: (bool) Whether to normalize the reward or not """ # TODO: support images properly (using a CNN) self.sess = sess self.scope = scope self.observation_shape = observation_space.shape self.actions_shape = action_space.shape if isinstance(action_space, gym.spaces.Box): # Continuous action space self.discrete_actions = False self.n_actions = action_space.shape[0] elif isinstance(action_space, gym.spaces.Discrete): self.n_actions = action_space.n self.discrete_actions = True else: raise ValueError('Action space not supported: {}'.format(action_space)) self.hidden_size = hidden_size self.normalize = normalize self.obs_rms = None # Placeholders self.policy_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="observations_ph") self.policy_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="actions_ph") self.policy_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="gammas_ph") self.expert_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.expert_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") self.expert_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="gammas_ph") self.mix_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.mix_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") # Build graph policy_rewards = self.build_graph(self.policy_obs_ph, self.policy_acs_ph, reuse=False, scope=self.scope) expert_rewards = self.build_graph(self.expert_obs_ph, self.expert_acs_ph, reuse=True, scope=self.scope) old_policy_rewards = self.build_graph(self.policy_obs_ph, self.policy_acs_ph, reuse=False, scope="oldreward") old_expert_rewards = self.build_graph(self.expert_obs_ph, self.expert_acs_ph, reuse=True, scope="oldreward") # generator_rewards = tf.math.sigmoid(generator_logits) # expert_rewards = tf.math.sigmoid(expert_logits) # policy_scaled_rewards = tf.multiply(policy_rewards, self.policy_gammas_ph) policy_scaled_rewards = policy_rewards # policy_value = (1-0.99) * tf.reduce_sum(policy_scaled_rewards) policy_value = tf.reduce_mean(policy_scaled_rewards) # expert_scaled_rewards = tf.multiply(expert_rewards, self.expert_gammas_ph) expert_scaled_rewards = expert_rewards # expert_value = (1-0.99) * tf.reduce_sum(expert_scaled_rewards) expert_value = tf.reduce_mean(expert_scaled_rewards) # alpha = tf.random.uniform([], 0.0, 1.0, observation_space.dtype) # generator_obs_mix = tf.reduce_mean(self.generator_obs_ph, axis=0, keepdims=True) # generator_acs_mix = tf.reduce_mean(self.generator_acs_ph, axis=0, keepdims=True) # expert_obs_mix = tf.reduce_mean(self.expert_obs_ph, axis=0, keepdims=True) # expert_acs_mix = tf.reduce_mean(self.expert_acs_ph, axis=0, keepdims=True) # generator_obs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.generator_gammas_ph, observation_space.dtype) * self.generator_obs_ph, axis=0, keepdims=True) # generator_acs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.generator_gammas_ph, action_space.dtype) * self.generator_acs_ph, axis=0, keepdims=True) # expert_obs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.expert_gammas_ph, observation_space.dtype) * self.expert_obs_ph, axis=0, keepdims=True) # expert_acs_mix = (1-0.99) * tf.reduce_sum(tf.cast(self.expert_gammas_ph, action_space.dtype) * self.expert_acs_ph, axis=0, keepdims=True) # mixture_obs = alpha * generator_obs_mix + (1 - alpha) * tf.reduce_mean(expert_obs_mix) # mixture_acs = tf.cast(alpha, action_space.dtype) * generator_acs_mix\ # + tf.cast((1 - alpha), action_space.dtype) * expert_acs_mix mixture_rewards = self.build_graph(self.mix_obs_ph, self.mix_acs_ph, reuse=True, scope=self.scope) grads = tf.gradients(mixture_rewards, [self.mix_obs_ph, self.mix_acs_ph])[0] norm = tf.cast(tf.sqrt(tf.reduce_sum(tf.square(grads), axis=1)), tf.float32) lipschitz_reg = tf.reduce_mean(tf.square(norm - 1.0)) lipschitz_reg_coef = 10 lipschitz_reg_loss = lipschitz_reg_coef * lipschitz_reg # # rewards = tf.concat([policy_rewards, expert_rewards], 0) # # rewards_reg = - tf.reduce_mean(logit_bernoulli_entropy(rewards)) # rewards_reg_coef = 0.001 # rewards = tf.concat([policy_rewards, expert_rewards], 0) policy_clipped_rewards = tf.clip_by_value(policy_rewards, -10.0, 10.0) expert_clipped_rewards = tf.clip_by_value(expert_rewards, -10.0, 10.0) clipped_rewards = tf.concat([policy_clipped_rewards, expert_clipped_rewards], 0) # rewards_reg_loss = rewards_reg_coef * rewards_reg old_rewards = tf.concat([old_policy_rewards, old_expert_rewards], 0) old_policy_clipped_rewards = tf.clip_by_value(old_policy_rewards, -10.0, 10.0) old_expert_clipped_rewards = tf.clip_by_value(old_expert_rewards, -10.0, 10.0) old_clipped_rewards = tf.concat([old_policy_clipped_rewards, old_expert_clipped_rewards], 0) # rewards_reg_coef = 0.01 # bregman = tf.reduce_mean(tf_util.huber_loss(old_rewards - rewards)) bregman = tf.reduce_mean(tf.square(tf.stop_gradient(old_clipped_rewards) - rewards)) bregman_coeff = 100 bregman_loss = bregman_coeff * bregman # # stepsize = 0.001 rewards_reg = - tf.reduce_mean(logit_bernoulli_entropy(rewards)) rewards_reg_coeff = 0.00 # rewards_reg = tf.reduce_mean(tf.square(rewards)) # rewards_reg_coeff = 1 rewards_reg_loss = rewards_reg_coeff * rewards_reg # rewards_reg_loss = rewards_reg_coef * rewards_reg # policy_loss = policy_value - expert_value # rewards_gradient = (tf.gradients(tf.reduce_mean(old_policy_clipped_rewards), [old_policy_rewards])[0] # - tf.gradients(tf.reduce_mean(old_expert_clipped_rewards), [old_expert_rewards])[0]) old_policy_loss = tf.reduce_mean(old_policy_rewards) - tf.reduce_mean(old_expert_rewards) old_rewards_gradient = tf.concat(tf.gradients(old_policy_loss, [old_policy_rewards, old_expert_rewards]), axis=0) policy_loss = tf.reduce_sum(tf.multiply(tf.stop_gradient(old_rewards_gradient), clipped_rewards)) loss = policy_loss + bregman_loss + rewards_reg_loss + lipschitz_reg_loss # Loss + Accuracy terms self.losses = [loss] self.loss_name = ["generator_loss", "expert_loss", "entropy", "entropy_loss", "generator_acc", "expert_acc"] # self.total_loss = loss # Build Reward for policy self.reward_op = old_policy_clipped_rewards # self.reward_op = tf.stop_gradient(tf.clip_by_value(policy_rewards, -1.0, 1.0)) # self.reward_op = generator_rewards self.update_old_rewards = \ tf_util.function([], [], updates=[tf.assign(oldv, newv) for (oldv, newv) in zipsame(tf_util.get_globals_vars("oldreward"), tf_util.get_globals_vars(self.scope))]) var_list = self.get_trainable_variables() # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=1e-5, epsilon=1e-5) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=3e-4, beta1=0.9895193, beta2=0.9999, epsilon=1e-5) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=3e-4, beta1=0, beta2=0.9) rewards_optimizer = tf.train.AdamOptimizer(learning_rate=3e-4) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=1e-3, beta1=0.5) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=1e-2) # accum_vars = [tf.Variable(tf.zeros_like(var.initialized_value()), trainable=False) for var in var_list] # accumulation_counter = tf.Variable(0.0, trainable=False) # zero_ops = [var.assign(tf.zeros_like(var)) for var in accum_vars] # zero_ops.append(accumulation_counter.assign(0.0)) # gvs = rewards_optimizer.compute_gradients(loss, var_list) # accumulate_ops = [accum_vars[i].assign_add(gv[0]) for i, gv in enumerate(gvs)] # accumulate_ops.append(accumulation_counter.assign_add(1.0)) # train_step = rewards_optimizer.apply_gradients([(accum_vars[i] / accumulation_counter, gv[1]) for i, gv in enumerate(gvs)]) grads, vars = zip(*rewards_optimizer.compute_gradients(loss, var_list=var_list)) grads, norm = tf.clip_by_global_norm(grads, 1e7) # grads, norm = tf.clip_by_global_norm(grads, 5.0) rewards_train_op = rewards_optimizer.apply_gradients(zip(grads, vars)) # norm = tf.constant(0.) # rewards_train_op = rewards_optimizer.minimize(loss, var_list=var_list) # rewards_train_op = [rewards_train_op, norm] # self.zero_grad = tf_util.function([], zero_ops) # self.compute_grads = tf_util.function( # [self.generator_obs_ph, self.generator_acs_ph, self.generator_gammas_ph, # self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph], accumulate_ops) # self.train = tf_util.function([], train_step) linear_approximation = tf.stop_gradient(tf.reduce_sum(tf.multiply(old_rewards_gradient, rewards - old_rewards))) # print_op = tf.print("Value diff:", linear_approximation, "Bregman:", bregman_loss, # "MD objective", linear_approximation + bregman_loss, # "Weight GradNorm:", norm, "Loss norm", tf.norm(old_rewards_gradient), # "rewards_mean", tf.reduce_mean(rewards), "rewards_std", tf.math.reduce_std(rewards), # "rewards_abs_max", tf.math.reduce_max(rewards)) # print_op = tf.print("old_rewards_gradient", tf.shape(old_rewards_gradient), "rewards",tf.shape(rewards)) print_op = tf.no_op() # var_list = self.get_trainable_variables() # grads, vars = zip(*rewards_optimizer.compute_gradients(loss, var_list=var_list)) # grads, norm = tf.clip_by_global_norm(grads, 300.0) # rewards_train_op = rewards_optimizer.apply_gradients(zip(grads, vars)) self.train = tf_util.function( [self.policy_obs_ph, self.policy_acs_ph, self.policy_gammas_ph, self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph, self.mix_obs_ph, self.mix_acs_ph], [rewards_train_op, print_op]) def build_graph(self, obs_ph, acs_ph, reuse=False, scope=None): """ build the graph :param obs_ph: (tf.Tensor) the observation placeholder :param acs_ph: (tf.Tensor) the action placeholder :param reuse: (bool) :return: (tf.Tensor) the graph output """ with tf.variable_scope(scope): if reuse: tf.get_variable_scope().reuse_variables() if self.normalize: with tf.variable_scope("obfilter"): self.obs_rms = RunningMeanStd(shape=self.observation_shape) obs = (tf.cast(obs_ph, tf.float32) - self.obs_rms.mean) / tf.cast(tf.sqrt(self.obs_rms.var), tf.float32) else: obs = tf.cast(obs_ph, tf.float32) if self.discrete_actions: one_hot_actions = tf.one_hot(acs_ph, self.n_actions) actions_ph = tf.cast(one_hot_actions, tf.float32) else: actions_ph = acs_ph _input = tf.concat([obs, actions_ph], axis=1) # concatenate the two input -> form a transition p_h1 = tf.contrib.layers.fully_connected(_input, self.hidden_size, activation_fn=tf.nn.tanh) p_h2 = tf.contrib.layers.fully_connected(p_h1, self.hidden_size, activation_fn=tf.nn.tanh) rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.identity) return rewards def get_trainable_variables(self): """ Get all the trainable variables from the graph :return: ([tf.Tensor]) the variables """ return tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, self.scope) def get_reward(self, obs, actions): """ Predict the reward using the observation and action :param obs: (tf.Tensor or np.ndarray) the observation :param actions: (tf.Tensor or np.ndarray) the action :return: (np.ndarray) the reward """ # sess = tf.get_default_session() if len(obs.shape) == 1: obs = np.expand_dims(obs, 0) if len(actions.shape) == 1: actions = np.expand_dims(actions, 0) elif len(actions.shape) == 0: # one discrete action actions = np.expand_dims(actions, 0) feed_dict = {self.policy_obs_ph: obs, self.policy_acs_ph: actions} reward = self.sess.run(self.reward_op, feed_dict) return reward class NeuralAdversaryMD(object): def __init__(self, sess, observation_space, action_space, hidden_size=64, entcoeff=0.001, lipschitz_reg_coef=0.0, scope="adversary", normalize=True): """ Reward regression from observations and transitions :param observation_space: (gym.spaces) :param action_space: (gym.spaces) :param hidden_size: ([int]) the hidden dimension for the MLP :param entcoeff: (float) the entropy loss weight :param scope: (str) tensorflow variable scope :param normalize: (bool) Whether to normalize the reward or not """ # TODO: support images properly (using a CNN) self.sess = sess self.scope = scope self.observation_shape = observation_space.shape self.actions_shape = action_space.shape if isinstance(action_space, gym.spaces.Box): # Continuous action space self.discrete_actions = False self.n_actions = action_space.shape[0] elif isinstance(action_space, gym.spaces.Discrete): self.n_actions = action_space.n self.discrete_actions = True else: raise ValueError('Action space not supported: {}'.format(action_space)) self.hidden_size = hidden_size self.normalize = normalize self.obs_rms = None # Placeholders self.policy_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="observations_ph") self.policy_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="actions_ph") self.policy_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="gammas_ph") self.expert_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.expert_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") self.expert_gammas_ph = tf.placeholder(tf.float32, (None, 1), name="expert_gammas_ph") self.mix_obs_ph = tf.placeholder(observation_space.dtype, (None,) + self.observation_shape, name="expert_observations_ph") self.mix_acs_ph = tf.placeholder(action_space.dtype, (None,) + self.actions_shape, name="expert_actions_ph") if self.normalize: with tf.variable_scope("obfilter"): self.obs_rms = MpiRunningMeanStd(shape=self.observation_shape) # Build graph policy_rewards = self.build_graph(self.policy_obs_ph, self.policy_acs_ph, reuse=False, scope=self.scope) expert_rewards = self.build_graph(self.expert_obs_ph, self.expert_acs_ph, reuse=True, scope=self.scope) old_policy_rewards = self.build_graph(self.policy_obs_ph, self.policy_acs_ph, reuse=False, scope="oldreward") old_expert_rewards = self.build_graph(self.expert_obs_ph, self.expert_acs_ph, reuse=True, scope="oldreward") # policy_scaled_rewards = tf.multiply(policy_rewards, self.policy_gammas_ph) policy_scaled_rewards = policy_rewards # policy_value = tf.reduce_sum(policy_scaled_rewards) policy_value = tf.reduce_mean(policy_scaled_rewards) # expert_scaled_rewards = tf.multiply(expert_rewards, self.expert_gammas_ph) expert_scaled_rewards = expert_rewards # expert_value = tf.reduce_sum(expert_scaled_rewards) expert_value = tf.reduce_mean(expert_scaled_rewards) mixture_rewards = self.build_graph(self.mix_obs_ph, self.mix_acs_ph, reuse=True, scope=self.scope) grads = tf.gradients(mixture_rewards, [self.mix_obs_ph, self.mix_acs_ph])[0] norm = tf.cast(tf.sqrt(tf.reduce_sum(tf.square(grads), axis=1)), tf.float32) lipschitz_reg = tf.reduce_mean(tf.square(norm - 1.0)) lipschitz_loss = lipschitz_reg_coef * lipschitz_reg # rewards = tf.concat([policy_rewards, expert_rewards], 0) policy_clipped_rewards = tf.clip_by_value(policy_rewards, -10.0, 10.0) expert_clipped_rewards = tf.clip_by_value(expert_rewards, -10.0, 10.0) clipped_rewards = tf.concat([policy_clipped_rewards, expert_clipped_rewards], 0) # # rewards_reg = - tf.reduce_mean(logit_bernoulli_entropy(rewards)) # rewards_reg_coef = 0.001 # # rewards_reg = tf.reduce_sum(tf.square(rewards)) # rewards_reg_coef = 0.01 old_rewards = tf.concat([old_policy_rewards, old_expert_rewards], 0) old_policy_clipped_rewards = tf.clip_by_value(old_policy_rewards, -10.0, 10.0) old_expert_clipped_rewards = tf.clip_by_value(old_expert_rewards, -10.0, 10.0) old_clipped_rewards = tf.concat([old_policy_clipped_rewards, old_expert_clipped_rewards], 0) # bregman = tf.reduce_mean(tf_util.huber_loss(old_clipped_rewards - rewards)) bregman = tf.reduce_mean(tf.square(tf.stop_gradient(old_clipped_rewards) - rewards)) bregman_coeff = 100 bregman_loss = bregman_coeff * bregman # # stepsize = 0.001 # old_policy_loss = tf.reduce_mean(tf.multiply(old_policy_rewards, self.policy_gammas_ph))\ # - tf.reduce_mean(tf.multiply(old_expert_rewards, self.expert_gammas_ph)) new_policy_loss = tf.reduce_mean(tf.multiply(policy_rewards, self.policy_gammas_ph))\ - tf.reduce_mean(tf.multiply(expert_rewards, self.expert_gammas_ph)) old_policy_loss = tf.reduce_mean(old_policy_rewards) - tf.reduce_mean(old_expert_rewards) old_rewards_gradient = tf.concat(tf.gradients(old_policy_loss, [old_policy_rewards, old_expert_rewards]), axis=0) policy_loss = tf.reduce_sum(tf.multiply(tf.stop_gradient(old_rewards_gradient), clipped_rewards)) rewards_reg = - tf.reduce_mean(logit_bernoulli_entropy(rewards)) rewards_reg_coeff = 0.001 # rewards_reg = tf.reduce_mean(tf.square(rewards)) # rewards_reg = tf.reduce_mean(tf_util.huber_loss(rewards)) # rewards_reg_coeff = 0 rewards_reg_loss = rewards_reg_coeff * rewards_reg # rewards_reg_loss = rewards_reg_coef * rewards_reg # policy_loss = policy_value - exp ert_value self.total_loss = policy_loss + bregman_loss + rewards_reg_loss + lipschitz_loss # Loss + Accuracy terms self.losses = [] self.loss_name = ["generator_loss", "expert_loss", "entropy", "entropy_loss", "generator_acc", "expert_acc"] # Build Reward for policy self.reward_op = tf.stop_gradient(old_policy_clipped_rewards) # self.reward_op = old_policy_rewards # self.reward_op = tf.clip_by_value(policy_rewards, -1.0, 1.0) # self.reward_op = generator_rewards self.update_old_rewards = \ tf_util.function([], [], updates=[tf.assign(oldv, newv) for (oldv, newv) in zipsame(tf_util.get_globals_vars("oldreward"), tf_util.get_globals_vars(self.scope))]) var_list = self.get_trainable_variables() # clip_weights = [tf.assign(var, tf.clip_by_value(var, -0.5, 0.5)) for var in var_list] clip_weights = tf.no_op() self.clip_weights = tf_util.function([], [clip_weights]) # rewards_optimizer = tf.train.AdamOptimizer(learning_rate=3e-5) # grads, vars = zip(*rewards_optimizer.compute_gradients(self.total_loss, var_list=var_list)) # rewards_train_op = rewards_optimizer.apply_gradients(zip(grads, vars)) linear_approximation = tf.stop_gradient(tf.reduce_sum(tf.multiply(old_rewards_gradient, rewards - old_rewards))) grads = tf.gradients(self.total_loss, var_list) grads, norm = tf.clip_by_global_norm(grads, 1e7) # self.train = tf_util.function( # [self.policy_obs_ph, self.policy_acs_ph, self.policy_gammas_ph, # self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph, # self.mix_obs_ph, self.mix_acs_ph], [rewards_train_op, print_op]) loss_op = tf.concat(axis=0, values=[tf.reshape(grad if grad is not None else tf.zeros_like(v), [tf_util.numel(v)]) for (v, grad) in zip(var_list, grads)]) print_op = tf.print("Policy Loss:", new_policy_loss, "Bregman:", bregman_loss, "MD objective", linear_approximation + bregman_loss, "GradNorm", norm, "Loss norm", tf.norm(old_rewards_gradient), "averageEnt", rewards_reg_loss, "mean", tf.reduce_mean(tf.abs(rewards)), "std", tf.math.reduce_std(rewards), "max", tf.math.reduce_max(tf.abs(rewards))) self.lossandgrad = tf_util.function( [self.policy_obs_ph, self.policy_acs_ph, self.policy_gammas_ph, self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph, self.mix_obs_ph, self.mix_acs_ph], # self.losses + [tf_util.flatgrad(self.total_loss, var_list)]) #, clip_norm=0.5, clip_by_global_norm=True)]) self.losses + [print_op] + [loss_op]) # print_op = tf.print("Value diff:", policy_value - expert_value, "Grad Regularizer:", lipschitz_reg) # print_op = tf.no_op() # self.train = tf_util.function( # [self.policy_obs_ph, self.policy_acs_ph, self.policy_gammas_ph, # self.expert_obs_ph, self.expert_acs_ph, self.expert_gammas_ph, # s, [rewards_train_op, print_op]) def build_graph(self, obs_ph, acs_ph, reuse=False, scope=None): """ build the graph :param obs_ph: (tf.Tensor) the observation placeholder :param acs_ph: (tf.Tensor) the action placeholder :param reuse: (bool) :return: (tf.Tensor) the graph output """ with tf.variable_scope(scope): if reuse: tf.get_variable_scope().reuse_variables() if self.normalize: obs = (tf.cast(obs_ph, tf.float32) - self.obs_rms.mean) / tf.cast(self.obs_rms.std, tf.float32) else: obs = tf.cast(obs_ph, tf.float32) if self.discrete_actions: one_hot_actions = tf.one_hot(acs_ph, self.n_actions) actions_ph = tf.cast(one_hot_actions, tf.float32) else: actions_ph = acs_ph _input = tf.concat([obs, actions_ph], axis=1) # concatenate the two input -> form a transition p_h1 = tf.contrib.layers.fully_connected(_input, self.hidden_size, activation_fn=tf.nn.tanh) p_h2 = tf.contrib.layers.fully_connected(p_h1, self.hidden_size, activation_fn=tf.nn.tanh) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.nn.tanh) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.math.sigmoid) rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.identity) # last_layer_init = tf.contrib.layers.variance_scaling_initializer(factor=0.01, mode='FAN_AVG', uniform=True) # rewards = tf.contrib.layers.fully_connected(p_h2, 1, activation_fn=tf.identity, weights_initializer=last_layer_init) return rewards def get_trainable_variables(self): """ Get all the trainable variables from the graph :return: ([tf.Tensor]) the variables """ return tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, self.scope)# + tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, "oldreward") def get_reward(self, obs, actions): """ Predict the reward using the observation and action :param obs: (tf.Tensor or np.ndarray) the observation :param actions: (tf.Tensor or np.ndarray) the action :return: (np.ndarray) the reward """ # sess = tf.get_default_session() if len(obs.shape) == 1: obs = np.expand_dims(obs, 0) if len(actions.shape) == 1: actions = np.expand_dims(actions, 0) elif len(actions.shape) == 0: # one discrete action actions = np.expand_dims(actions, 0) feed_dict = {self.policy_obs_ph: obs, self.policy_acs_ph: actions} reward = self.sess.run(self.reward_op, feed_dict) return reward

49.161812

161

0.644461

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4.73517

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null

0

7

196cb152cdaf8fd68a64a57a0c255684bc13e4be

5,514

py

Python

tests/test_api.py

brunocroh/wifidog-auth-flask

a215cd9ccebc061723a56ce05db62821354f6785

[ "MIT" ]

18

2016-04-19T08:04:46.000Z

2021-12-15T06:45:04.000Z

tests/test_api.py

brunocroh/wifidog-auth-flask

a215cd9ccebc061723a56ce05db62821354f6785

[ "MIT" ]

3

2016-12-02T14:40:52.000Z

2022-01-15T01:03:45.000Z

tests/test_api.py

brunocroh/wifidog-auth-flask

a215cd9ccebc061723a56ce05db62821354f6785

[ "MIT" ]

8

2015-11-30T13:21:44.000Z

2018-12-31T05:56:41.000Z

import json from tests import TestCase class TestApi(TestCase): def test_api_networks_index_as_anonymous(self): response = self.client.get('/api/networks') self.assertEqual(403, response.status_code) def test_api_networks_index_as_gateway(self): self.login('main-gateway1@example.com', 'admin') response = self.client.get('/api/networks') self.assertEqual(200, response.status_code) networks = json.loads(response.get_data(True)) self.assertEqual(1, len(networks)) self.assertEqual('main-network', networks[0]['id']) def test_api_networks_index_as_network(self): self.login('main-network@example.com', 'admin') response = self.client.get('/api/networks') self.assertEqual(200, response.status_code) networks = json.loads(response.get_data(True)) self.assertEqual(1, len(networks)) self.assertEqual('main-network', networks[0]['id']) def test_api_networks_index_as_super(self): self.login('super-admin@example.com', 'admin') response = self.client.get('/api/networks') self.assertEqual(200, response.status_code) networks = json.loads(response.get_data(True)) self.assertEqual(2, len(networks)) self.assertEqual('main-network', networks[0]['id']) self.assertEqual('other-network', networks[1]['id']) def test_api_gateways_index_as_anonymous(self): response = self.client.get('/api/gateways') self.assertEqual(403, response.status_code) def test_api_gateways_index_as_gateway(self): self.login('main-gateway1@example.com', 'admin') response = self.client.get('/api/gateways', follow_redirects=True) self.assertEqual(200, response.status_code) gateways = json.loads(response.get_data(True)) self.assertEqual(1, len(gateways)) self.assertEqual('main-gateway1', gateways[0]['id']) def test_api_gateways_index_as_network(self): self.login('main-network@example.com', 'admin') response = self.client.get('/api/gateways') self.assertEqual(200, response.status_code) gateways = json.loads(response.get_data(True)) self.assertEqual(2, len(gateways)) self.assertEqual('main-gateway1', gateways[0]['id']) self.assertEqual('main-gateway2', gateways[1]['id']) def test_api_gateways_index_as_super(self): self.login('super-admin@example.com', 'admin') response = self.client.get('/api/gateways') self.assertEqual(200, response.status_code) gateways = json.loads(response.get_data(True)) self.assertEqual(4, len(gateways)) self.assertEqual('main-gateway1', gateways[0]['id']) self.assertEqual('main-gateway2', gateways[1]['id']) self.assertEqual('other-gateway1', gateways[2]['id']) self.assertEqual('other-gateway2', gateways[3]['id']) def test_api_users_index_as_anonymous(self): response = self.client.get('/api/users') self.assertEqual(403, response.status_code) def test_api_users_index_as_gateway(self): self.login('main-gateway1@example.com', 'admin') response = self.client.get('/api/users') self.assertEqual(200, response.status_code) users = json.loads(response.get_data(True)) self.assertEqual(1, len(users)) self.assertEqual('main-gateway1@example.com', users[0]['email']) def test_api_users_index_as_network(self): self.login('main-network@example.com', 'admin') response = self.client.get('/api/users?sort={"email":false}') self.assertEqual(200, response.status_code) users = json.loads(response.get_data(True)) self.assertEqual(3, len(users)) self.assertEqual('main-gateway1@example.com', users[0]['email']) self.assertEqual('main-gateway2@example.com', users[1]['email']) self.assertEqual('main-network@example.com', users[2]['email']) def test_api_users_index_as_super(self): self.login('super-admin@example.com', 'admin') response = self.client.get('/api/users') self.assertEqual(200, response.status_code) users = json.loads(response.get_data(True)) self.assertEqual(7, len(users)) def test_api_vouchers_index_as_anonymous(self): response = self.client.get('/api/vouchers') self.assertEqual(403, response.status_code) def test_api_vouchers_index_as_gateway(self): self.login('main-gateway1@example.com', 'admin') response = self.client.get('/api/vouchers') self.assertEqual(200, response.status_code) vouchers = json.loads(response.get_data(True)) self.assertEqual(2, len(vouchers)) self.assertEqual('main-1-2', vouchers[0]['code']) self.assertEqual('main-1-1', vouchers[1]['code']) def test_api_vouchers_index_as_network(self): self.login('main-network@example.com', 'admin') response = self.client.get('/api/vouchers?sort={"code":false}') self.assertEqual(200, response.status_code) vouchers = json.loads(response.get_data(True)) self.assertEqual(4, len(vouchers)) def test_api_users_index_as_super(self): self.login('super-admin@example.com', 'admin') response = self.client.get('/api/users') self.assertEqual(200, response.status_code) users = json.loads(response.get_data(True)) self.assertEqual(7, len(users))

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null

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1

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null

0

1

0

7

1970d5705201c51095be6346c7b2ee83f6519f47

142

py

Python

codewars/hello-world-without-strings.py

andraantariksa/code-exercise-answer

69b7dbdc081cdb094cb110a72bc0c9242d3d344d

[ "MIT" ]

1

2019-11-06T15:17:48.000Z

codewars/hello-world-without-strings.py

andraantariksa/code-exercise-answer

69b7dbdc081cdb094cb110a72bc0c9242d3d344d

[ "MIT" ]

null

codewars/hello-world-without-strings.py

andraantariksa/code-exercise-answer

69b7dbdc081cdb094cb110a72bc0c9242d3d344d

[ "MIT" ]

1

2018-11-13T08:43:26.000Z

def hello_world(): return chr(72)+chr(101)+chr(108)+chr(108)+chr(111)+chr(44)+chr(32)+chr(87)+chr(111)+chr(114)+chr(108)+chr(100)+chr(33)

47.333333

122

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null

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0

1

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8

1990e7f7d5d0158dcbdab2f22bc4e8c777471c9a

8,336

py

Python

src/genie/libs/parser/nxos/tests/ShowRoutingIpv6VrfAll/cli/equal/golden_output_1_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

204

2018-06-27T00:55:27.000Z

2022-03-06T21:12:18.000Z

src/genie/libs/parser/nxos/tests/ShowRoutingIpv6VrfAll/cli/equal/golden_output_1_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

468

2018-06-19T00:33:18.000Z

2022-03-31T23:23:35.000Z

src/genie/libs/parser/nxos/tests/ShowRoutingIpv6VrfAll/cli/equal/golden_output_1_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

309

2019-01-16T20:21:07.000Z

2022-03-30T12:56:41.000Z

expected_output = { "vrf": { "default": { "address_family": { "ipv6 unicast": { "bgp_distance_internal_as": 200, "ip": { "2001:db8:1:1::1/128": { "attach": "attached", "best_route": { "unicast": { "nexthop": { "2001:db8:1:1::1": { "protocol": { "local": { "interface": "Ethernet1/1", "metric": "0", "uptime": "00:15:46", "preference": "0"}}}}}}, "mbest_num": "0", "ubest_num": "1" }, "2001:db8:1:1::/64": { "attach": "attached", "best_route": { "unicast": { "nexthop": { "2001:db8:1:1::1": { "protocol": { "direct": { "interface": "Ethernet1/1", "metric": "0", "uptime": "00:15:46", "preference": "0"}}}}}}, "mbest_num": "0", "ubest_num": "1" }, "2001:db8:2:2::2/128": { "attach": "attached", "best_route": { "unicast": { "nexthop": { "2001:db8:2:2::2": { "protocol": { "local": { "interface": "Ethernet1/1", "metric": "0", "tag": "222", "uptime": "00:15:46", "preference": "0"}}}}}}, "mbest_num": "0", "ubest_num": "1" }, "2001:db8::5054:ff:fed5:63f9/128": { "attach": "attached", "best_route": { "unicast": { "nexthop": { "2001:db8::5054:ff:fed5:63f9": { "protocol": { "local": { "interface": "Ethernet1/1", "metric": "0", "uptime": "00:15:46", "preference": "0"}}}}}}, "mbest_num": "0", "ubest_num": "1" }, "2001:db8::/64": { "attach": "attached", "best_route": { "unicast": { "nexthop": { "2001:db8::5054:ff:fed5:63f9": { "protocol": { "direct": { "interface": "Ethernet1/1", "metric": "0", "uptime": "00:15:46", "preference": "0"}}}}}}, "mbest_num": "0", "ubest_num": "1" }, "2001:db8:cdc9:121::/64": { "mbest_num": "0", "ubest_num": "1", "best_route": { "unicast": { "nexthop": { "::ffff:10.4.1.1": { "protocol": { "bgp": { "uptime": "00:35:51", "tag": "200", "route_table": "default:IPv4", "attribute": "internal", "mpls": True, "metric": "2219", "preference": "200", "protocol_id": "100"}}}}}}}, "2001:db8:2:2::/64": { "attach": "attached", "best_route": { "unicast": { "nexthop": { "2001:db8:2:2::2": { "protocol": { "direct": { "interface": "Ethernet1/1", "metric": "0", "tag": "222", "uptime": "00:15:46", "preference": "0"}}}}}}, "mbest_num": "0", "ubest_num": "1"}}}}}, "VRF1": { "address_family": { "vpnv6 unicast": { "bgp_distance_internal_as": 200, "ip": { "2001:db8:cdc9:144::/64": { "mbest_num": "0", "ubest_num": "1", "best_route": { "unicast": { "nexthop": { "::ffff:10.4.1.1": { "protocol": { "bgp": { "uptime": "00:35:51", "tag": "200", "mpls_vpn": True, "attribute": "internal", "route_table": "default:IPv4", "metric": "2219", "preference": "200", "protocol_id": "100"}}}}}}}}}}}} }

59.542857

93

0.168426

330

8,336

4.139394

0.19697

0.071742

0.093704

0.1347

0.866032

0.86164

0.851391

0.79063

0.721083

0

0.127126

0.732006

8,336

139

94

59.971223

0.484333

0

0.818841

0

0.179004

0.021236

0

1

0

false

0

null

0

1

0

1

0

1

0

1

0

null

0

9

5fffb5e57c2d1e75e947723c18968bb19ba6172b

64

py

Python

sphinx_data_viewer/__init__.py

useblocks/sphinx-dataa-viewer

b4bf9f6cd1eff729268728b892b4108ff1df9dd2

[ "MIT" ]

4

2021-11-26T10:19:50.000Z

2021-12-10T06:19:39.000Z

sphinx_data_viewer/__init__.py

useblocks/sphinx-dataa-viewer

b4bf9f6cd1eff729268728b892b4108ff1df9dd2

[ "MIT" ]

3

2021-12-01T15:31:51.000Z

2021-12-08T09:00:19.000Z

sphinx_data_viewer/__init__.py

useblocks/sphinx-dataa-viewer

b4bf9f6cd1eff729268728b892b4108ff1df9dd2

[ "MIT" ]

1

2021-12-02T20:54:47.000Z

from sphinx_data_viewer.sphinx_data_viewer import setup # NOQA

32

63

0.859375

10

64

5.1

0.7

0.392157

0.627451

0

0.109375

64

1

64

0.894737

0.0625

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

2714cfeca1b2d8c339d6adaa8faad855e888e738

133

py

Python

src/blueprints/telegram_bot/__init__.py

primeithard/yandex-disk-telegram-bot

21aecdecd503d0ac441c6ef7f1980ff52370d9aa

[ "MIT" ]

15

2020-05-12T23:23:38.000Z

2022-02-22T00:44:06.000Z

src/blueprints/telegram_bot/__init__.py

primeithard/yandex-disk-telegram-bot

21aecdecd503d0ac441c6ef7f1980ff52370d9aa

[ "MIT" ]

5

2020-08-03T08:57:37.000Z

2022-01-31T08:30:03.000Z

src/blueprints/telegram_bot/__init__.py

primeithard/yandex-disk-telegram-bot

21aecdecd503d0ac441c6ef7f1980ff52370d9aa

[ "MIT" ]

7

2020-08-15T20:24:56.000Z

2021-09-26T21:43:46.000Z

from .bp import bp as telegram_bot_blueprint from .webhook import views as webhook_views from .yd_auth import views as yd_auth_views

33.25

44

0.842105

24

133

4.416667

0.458333

0.207547

0.245283

0

0.135338

133

3

45

44.333333

0.921739

0

1

0

true

0

1

0

1

0.333333

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

27d44a4dfae9bc7fcacabae119d4378082f27b8b

7,523

py

Python

tests/test_pagination_tags.py

ralfzosel/django-pagination-bootstrap

20d431bb9950269626ff88fa6be7b2f27faf1c29

[ "MIT" ]

27

2015-03-06T22:19:40.000Z

2021-11-14T22:04:11.000Z

tests/test_pagination_tags.py

ralfzosel/django-pagination-bootstrap

20d431bb9950269626ff88fa6be7b2f27faf1c29

[ "MIT" ]

90

2015-04-16T12:00:16.000Z

2021-01-23T21:51:11.000Z

tests/test_pagination_tags.py

ralfzosel/django-pagination-bootstrap

20d431bb9950269626ff88fa6be7b2f27faf1c29

[ "MIT" ]

20

2015-03-28T19:24:48.000Z

2022-03-03T09:11:09.000Z

from django import template from django.test import TestCase from .test_http_request import TestHttpRequest class TestTemplatePaginateTags(TestCase): def test_render_range_by_two(self) -> None: t = template.Template( "{% load pagination_tags %}{% autopaginate var 2 %}{% paginate %}" ) c = template.Context({"var": range(21), "request": TestHttpRequest()}) self.assertEqual( t.render(c), '\n\n\n<nav aria-label="Page pagination">\n <ul class="pagination">\n \n <li class="page-item disabled"><a class="page-link" href="#" onclick="javascript: return false;">«</a></li>\n \n \n \n \n <li class="page-item active"><a class="page-link" href="#" onclick="javascript: return false;">1</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">2</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=3">3</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=4">4</a></li>\n \n \n \n \n <li class="page-item disabled"><a class="page-link" href="#" onclick="javascript: return false;">...</a></li>\n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=8">8</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=9">9</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=10">10</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=11">11</a></li>\n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">»</a></li>\n \n </ul>\n \n</nav>\n', ) def test_render_range_by_two_one_orphan(self) -> None: t = template.Template( "{% load pagination_tags %}{% autopaginate var 2 1 %}{% paginate %}" ) c = template.Context({"var": range(20), "request": TestHttpRequest()}) self.assertEqual( t.render(c), '\n\n\n<nav aria-label="Page pagination">\n <ul class="pagination">\n \n <li class="page-item disabled"><a class="page-link" href="#" onclick="javascript: return false;">«</a></li>\n \n \n \n \n <li class="page-item active"><a class="page-link" href="#" onclick="javascript: return false;">1</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">2</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=3">3</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=4">4</a></li>\n \n \n \n \n <li class="page-item disabled"><a class="page-link" href="#" onclick="javascript: return false;">...</a></li>\n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=7">7</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=8">8</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=9">9</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=10">10</a></li>\n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">»</a></li>\n \n </ul>\n \n</nav>\n', ) def test_render_range_by_one(self) -> None: t = template.Template( "{% load pagination_tags %}{% autopaginate var %}{% paginate %}" ) c = template.Context({"var": range(21), "request": TestHttpRequest()}) self.assertEqual( t.render(c), '\n\n\n<nav aria-label="Page pagination">\n <ul class="pagination">\n \n <li class="page-item disabled"><a class="page-link" href="#" onclick="javascript: return false;">«</a></li>\n \n \n \n \n <li class="page-item active"><a class="page-link" href="#" onclick="javascript: return false;">1</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">2</a></li>\n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">»</a></li>\n \n </ul>\n \n</nav>\n', ) def test_render_range_by_twenty(self) -> None: t = template.Template( "{% load pagination_tags %}{% autopaginate var 20 %}{% paginate %}" ) c = template.Context({"var": range(21), "request": TestHttpRequest()}) self.assertEqual( t.render(c), '\n\n\n<nav aria-label="Page pagination">\n <ul class="pagination">\n \n <li class="page-item disabled"><a class="page-link" href="#" onclick="javascript: return false;">«</a></li>\n \n \n \n \n <li class="page-item active"><a class="page-link" href="#" onclick="javascript: return false;">1</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">2</a></li>\n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">»</a></li>\n \n </ul>\n \n</nav>\n', ) def test_render_range_by_var(self) -> None: t = template.Template( "{% load pagination_tags %}{% autopaginate var by %}{% paginate %}" ) c = template.Context({"var": range(21), "by": 20, "request": TestHttpRequest()}) self.assertEqual( t.render(c), '\n\n\n<nav aria-label="Page pagination">\n <ul class="pagination">\n \n <li class="page-item disabled"><a class="page-link" href="#" onclick="javascript: return false;">«</a></li>\n \n \n \n \n <li class="page-item active"><a class="page-link" href="#" onclick="javascript: return false;">1</a></li>\n \n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">2</a></li>\n \n \n \n \n <li class="page-item"><a class="page-link" href="?page=2">»</a></li>\n \n </ul>\n \n</nav>\n', ) def test_render_range_by_var_as_name(self) -> None: t = template.Template( "{% load pagination_tags %}{% autopaginate var by as foo %}{{ foo }}" ) c = template.Context( {"var": list(range(21)), "by": 20, "request": TestHttpRequest()} ) self.assertEqual( t.render(c), "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]", ) def test_render_invalid_arguments(self) -> None: with self.assertRaisesMessage( template.TemplateSyntaxError, "autopaginate tag takes one required argument and one optional argument", ): template.Template("{% load pagination_tags %}{% autopaginate %}") def test_render_invalid_orphans(self) -> None: with self.assertRaisesMessage( template.TemplateSyntaxError, "Got a, but expected integer." ): template.Template("{% load pagination_tags %}{% autopaginate var 2 a %}") def test_render_range_by_var_as_index_error(self) -> None: with self.assertRaisesMessage( template.TemplateSyntaxError, "Context variable assignment must take the form of {% autopaginate object.example_set.all ... as context_var_name %}", ): template.Template("{% load pagination_tags %}{% autopaginate var by as %}")

84.52809

1,344

0.545128

1,106

7,523

3.658228

0.094937

0.077113

0.079338

0.07217

0.886802

0.861097

0.80178

0.789422

0.775828

0

0.017945

0.24445

7,523

88

1,345

85.488636

0.693878

0

0.415584

0

0.077922

0.69334

0.123754

0

0.116883

1

0.116883

false

0

0.038961

0

0.168831

0

null

0

1

0

1

0

1

0

null

0

8

fd7f95b8e5cd5e33f452f0755937d6a7c59e71d7

75,317

py

Python

dlkit/services/authorization.py

UOC/dlkit

a9d265db67e81b9e0f405457464e762e2c03f769

[ "MIT" ]

2

2018-02-23T12:16:11.000Z

2020-10-08T17:54:24.000Z

dlkit/services/authorization.py

UOC/dlkit

a9d265db67e81b9e0f405457464e762e2c03f769

[ "MIT" ]

87

2017-04-21T18:57:15.000Z

2021-12-13T19:43:57.000Z

dlkit/services/authorization.py

UOC/dlkit

a9d265db67e81b9e0f405457464e762e2c03f769

[ "MIT" ]

1

2018-03-01T16:44:25.000Z

"""DLKit Services implementations of authorization service.""" # pylint: disable=no-init # osid specification includes some 'marker' interfaces. # pylint: disable=too-many-ancestors # number of ancestors defined in spec. # pylint: disable=too-few-public-methods,too-many-public-methods # number of methods defined in spec. Worse yet, these are aggregates. # pylint: disable=invalid-name # method and class names defined in spec. # pylint: disable=no-self-use,unused-argument # to catch unimplemented methods. # pylint: disable=super-init-not-called # it just isn't. from . import osid from .osid_errors import Unimplemented, IllegalState, InvalidArgument from dlkit.abstract_osid.authorization import objects as abc_authorization_objects from dlkit.manager_impls.authorization import managers as authorization_managers DEFAULT = 0 COMPARATIVE = 0 PLENARY = 1 FEDERATED = 0 ISOLATED = 1 ANY_STATUS = 0 ACTIVE = 1 UNSEQUESTERED = 0 SEQUESTERED = 1 AUTOMATIC = 0 MANDATORY = 1 DISABLED = -1 class AuthorizationProfile(osid.OsidProfile, authorization_managers.AuthorizationProfile): """AuthorizationProfile convenience adapter including related Session methods.""" def __init__(self): self._provider_manager = None def supports_authorization(self): """Pass through to provider supports_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_authorization() def supports_authorization_lookup(self): """Pass through to provider supports_authorization_lookup""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_authorization_lookup() def supports_authorization_query(self): """Pass through to provider supports_authorization_query""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_authorization_query() def supports_authorization_admin(self): """Pass through to provider supports_authorization_admin""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_authorization_admin() def supports_authorization_vault(self): """Pass through to provider supports_authorization_vault""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_authorization_vault() def supports_authorization_vault_assignment(self): """Pass through to provider supports_authorization_vault_assignment""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_authorization_vault_assignment() def supports_vault_lookup(self): """Pass through to provider supports_vault_lookup""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_vault_lookup() def supports_vault_query(self): """Pass through to provider supports_vault_query""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_vault_query() def supports_vault_admin(self): """Pass through to provider supports_vault_admin""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_vault_admin() def supports_vault_hierarchy(self): """Pass through to provider supports_vault_hierarchy""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_vault_hierarchy() def supports_vault_hierarchy_design(self): """Pass through to provider supports_vault_hierarchy_design""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.supports_resource_lookup return self._provider_manager.supports_vault_hierarchy_design() def get_authorization_record_types(self): """Pass through to provider get_authorization_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_authorization_record_types() authorization_record_types = property(fget=get_authorization_record_types) def get_authorization_search_record_types(self): """Pass through to provider get_authorization_search_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_authorization_search_record_types() authorization_search_record_types = property(fget=get_authorization_search_record_types) def get_function_record_types(self): """Pass through to provider get_function_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_function_record_types() function_record_types = property(fget=get_function_record_types) def get_function_search_record_types(self): """Pass through to provider get_function_search_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_function_search_record_types() function_search_record_types = property(fget=get_function_search_record_types) def get_qualifier_record_types(self): """Pass through to provider get_qualifier_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_qualifier_record_types() qualifier_record_types = property(fget=get_qualifier_record_types) def get_qualifier_search_record_types(self): """Pass through to provider get_qualifier_search_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_qualifier_search_record_types() qualifier_search_record_types = property(fget=get_qualifier_search_record_types) def get_vault_record_types(self): """Pass through to provider get_vault_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_vault_record_types() vault_record_types = property(fget=get_vault_record_types) def get_vault_search_record_types(self): """Pass through to provider get_vault_search_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_vault_search_record_types() vault_search_record_types = property(fget=get_vault_search_record_types) def get_authorization_condition_record_types(self): """Pass through to provider get_authorization_condition_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceProfile.get_resource_record_types return self._provider_manager.get_authorization_condition_record_types() authorization_condition_record_types = property(fget=get_authorization_condition_record_types) class AuthorizationManager(osid.OsidManager, osid.OsidSession, AuthorizationProfile, authorization_managers.AuthorizationManager): """AuthorizationManager convenience adapter including related Session methods.""" def __init__(self, proxy=None): self._runtime = None self._provider_manager = None self._provider_sessions = dict() self._session_management = AUTOMATIC self._vault_view = DEFAULT # This is to initialize self._proxy osid.OsidSession.__init__(self, proxy) self._sub_package_provider_managers = dict() def _set_vault_view(self, session): """Sets the underlying vault view to match current view""" if self._vault_view == COMPARATIVE: try: session.use_comparative_vault_view() except AttributeError: pass else: try: session.use_plenary_vault_view() except AttributeError: pass def _get_provider_session(self, session_name, proxy=None): """Gets the session for the provider""" agent_key = self._get_agent_key(proxy) if session_name in self._provider_sessions[agent_key]: return self._provider_sessions[agent_key][session_name] else: session = self._instantiate_session('get_' + session_name, self._proxy) self._set_vault_view(session) if self._session_management != DISABLED: self._provider_sessions[agent_key][session_name] = session return session def _get_sub_package_provider_manager(self, sub_package_name): if sub_package_name in self._sub_package_provider_managers: return self._sub_package_provider_managers[sub_package_name] config = self._runtime.get_configuration() parameter_id = Id('parameter:{0}ProviderImpl@dlkit_service'.format(sub_package_name)) provider_impl = config.get_value_by_parameter(parameter_id).get_string_value() if self._proxy is None: # need to add version argument sub_package = self._runtime.get_manager(sub_package_name.upper(), provider_impl) else: # need to add version argument sub_package = self._runtime.get_proxy_manager(sub_package_name.upper(), provider_impl) self._sub_package_provider_managers[sub_package_name] = sub_package return sub_package def _get_sub_package_provider_session(self, sub_package, session_name, proxy=None): """Gets the session from a sub-package""" agent_key = self._get_agent_key(proxy) if session_name in self._provider_sessions[agent_key]: return self._provider_sessions[agent_key][session_name] else: manager = self._get_sub_package_provider_manager(sub_package) try: session = self._instantiate_session('get_' + session_name + '_for_bank', proxy=self._proxy, manager=manager) except AttributeError: session = self._instantiate_session('get_' + session_name, proxy=self._proxy, manager=manager) self._set_bank_view(session) if self._session_management != DISABLED: self._provider_sessions[agent_key][session_name] = session return session def _instantiate_session(self, method_name, proxy=None, *args, **kwargs): """Instantiates a provider session""" if 'manager' in kwargs: session_class = getattr(kwargs['manager'], method_name) del kwargs['manager'] else: session_class = getattr(self._provider_manager, method_name) if proxy is None: try: return session_class(bank_id=self._catalog_id, *args, **kwargs) except AttributeError: return session_class(*args, **kwargs) else: try: return session_class(bank_id=self._catalog_id, proxy=proxy, *args, **kwargs) except AttributeError: return session_class(proxy=proxy, *args, **kwargs) def initialize(self, runtime): """OSID Manager initialize""" from .primitives import Id if self._runtime is not None: raise IllegalState('Manager has already been initialized') self._runtime = runtime config = runtime.get_configuration() parameter_id = Id('parameter:authorizationProviderImpl@dlkit_service') provider_impl = config.get_value_by_parameter(parameter_id).get_string_value() if self._proxy is None: # need to add version argument self._provider_manager = runtime.get_manager('AUTHORIZATION', provider_impl) else: # need to add version argument self._provider_manager = runtime.get_proxy_manager('AUTHORIZATION', provider_impl) def close_sessions(self): """Close all sessions, unless session management is set to MANDATORY""" if self._session_management != MANDATORY: self._provider_sessions = dict() def use_automatic_session_management(self): """Session state will be saved unless closed by consumers""" self._session_management = AUTOMATIC def use_mandatory_session_management(self): """Session state will be saved and can not be closed by consumers""" self._session_management = MANDATORY def disable_session_management(self): """Session state will never be saved""" self._session_management = DISABLED self.close_sessions() def get_authorization_session(self, *args, **kwargs): """Pass through to provider get_authorization_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_catalog_template return self._provider_manager.get_authorization_session(*args, **kwargs) authorization_session = property(fget=get_authorization_session) def get_authorization_session_for_vault(self, *args, **kwargs): """Pass through to provider get_authorization_session_for_vault""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template return self._provider_manager.get_authorization_session_for_vault(*args, **kwargs) def get_authorization_lookup_session(self, *args, **kwargs): """Pass through to provider get_authorization_lookup_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_catalog_template return self._provider_manager.get_authorization_lookup_session(*args, **kwargs) authorization_lookup_session = property(fget=get_authorization_lookup_session) def get_authorization_lookup_session_for_vault(self, *args, **kwargs): """Pass through to provider get_authorization_lookup_session_for_vault""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template return self._provider_manager.get_authorization_lookup_session_for_vault(*args, **kwargs) def get_authorization_query_session(self, *args, **kwargs): """Pass through to provider get_authorization_query_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_catalog_template return self._provider_manager.get_authorization_query_session(*args, **kwargs) authorization_query_session = property(fget=get_authorization_query_session) def get_authorization_query_session_for_vault(self, *args, **kwargs): """Pass through to provider get_authorization_query_session_for_vault""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template return self._provider_manager.get_authorization_query_session_for_vault(*args, **kwargs) def get_authorization_admin_session(self, *args, **kwargs): """Pass through to provider get_authorization_admin_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_catalog_template return self._provider_manager.get_authorization_admin_session(*args, **kwargs) authorization_admin_session = property(fget=get_authorization_admin_session) def get_authorization_admin_session_for_vault(self, *args, **kwargs): """Pass through to provider get_authorization_admin_session_for_vault""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template return self._provider_manager.get_authorization_admin_session_for_vault(*args, **kwargs) def get_authorization_vault_session(self, *args, **kwargs): """Pass through to provider get_authorization_vault_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_manager_template return self._provider_manager.get_authorization_vault_session(*args, **kwargs) authorization_vault_session = property(fget=get_authorization_vault_session) def get_authorization_vault_assignment_session(self, *args, **kwargs): """Pass through to provider get_authorization_vault_assignment_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_manager_template return self._provider_manager.get_authorization_vault_assignment_session(*args, **kwargs) authorization_vault_assignment_session = property(fget=get_authorization_vault_assignment_session) def get_vault_lookup_session(self, *args, **kwargs): """Pass through to provider get_vault_lookup_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_manager_template return self._provider_manager.get_vault_lookup_session(*args, **kwargs) vault_lookup_session = property(fget=get_vault_lookup_session) def get_vault_query_session(self, *args, **kwargs): """Pass through to provider get_vault_query_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_manager_template return self._provider_manager.get_vault_query_session(*args, **kwargs) vault_query_session = property(fget=get_vault_query_session) def get_vault_admin_session(self, *args, **kwargs): """Pass through to provider get_vault_admin_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_manager_template return self._provider_manager.get_vault_admin_session(*args, **kwargs) vault_admin_session = property(fget=get_vault_admin_session) def get_vault_hierarchy_session(self, *args, **kwargs): """Pass through to provider get_vault_hierarchy_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_manager_template return self._provider_manager.get_vault_hierarchy_session(*args, **kwargs) vault_hierarchy_session = property(fget=get_vault_hierarchy_session) def get_vault_hierarchy_design_session(self, *args, **kwargs): """Pass through to provider get_vault_hierarchy_design_session""" # Implemented from kitosid template for - # osid.resource.ResourceManager.get_resource_lookup_session_manager_template return self._provider_manager.get_vault_hierarchy_design_session(*args, **kwargs) vault_hierarchy_design_session = property(fget=get_vault_hierarchy_design_session) def get_authorization_batch_manager(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') authorization_batch_manager = property(fget=get_authorization_batch_manager) def get_authorization_rules_manager(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') authorization_rules_manager = property(fget=get_authorization_rules_manager) ## # The following methods are from osid.authorization.AuthorizationVaultSession def use_comparative_vault_view(self): """Pass through to provider AuthorizationVaultSession.use_comparative_vault_view""" self._vault_view = COMPARATIVE # self._get_provider_session('authorization_vault_session') # To make sure the session is tracked for session in self._get_provider_sessions(): try: session.use_comparative_vault_view() except AttributeError: pass def use_plenary_vault_view(self): """Pass through to provider AuthorizationVaultSession.use_plenary_vault_view""" self._vault_view = PLENARY # self._get_provider_session('authorization_vault_session') # To make sure the session is tracked for session in self._get_provider_sessions(): try: session.use_plenary_vault_view() except AttributeError: pass def can_lookup_authorization_vault_mappings(self): """Pass through to provider AuthorizationVaultSession.can_lookup_authorization_vault_mappings""" # Implemented from kitosid template for - # osid.resource.ResourceBinSession.can_lookup_resource_bin_mappings return self._get_provider_session('authorization_vault_session').can_lookup_authorization_vault_mappings() def get_authorization_ids_by_vault(self, *args, **kwargs): """Pass through to provider AuthorizationVaultSession.get_authorization_ids_by_vault""" # Implemented from kitosid template for - # osid.resource.ResourceBinSession.get_resource_ids_by_bin return self._get_provider_session('authorization_vault_session').get_authorization_ids_by_vault(*args, **kwargs) def get_authorizations_by_vault(self, *args, **kwargs): """Pass through to provider AuthorizationVaultSession.get_authorizations_by_vault""" # Implemented from kitosid template for - # osid.resource.ResourceBinSession.get_resources_by_bin return self._get_provider_session('authorization_vault_session').get_authorizations_by_vault(*args, **kwargs) def get_authorizations_ids_by_vault(self, *args, **kwargs): """Pass through to provider AuthorizationVaultSession.get_authorizations_ids_by_vault""" # Implemented from kitosid template for - # osid.resource.ResourceBinSession.get_resource_ids_by_bin return self._get_provider_session('authorization_vault_session').get_authorizations_ids_by_vault(*args, **kwargs) def get_vault_ids_by_authorization(self, *args, **kwargs): """Pass through to provider AuthorizationVaultSession.get_vault_ids_by_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceBinSession.get_bin_ids_by_resource return self._get_provider_session('authorization_vault_session').get_vault_ids_by_authorization(*args, **kwargs) def get_vault_by_authorization(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) ## # The following methods are from osid.authorization.AuthorizationVaultAssignmentSession def can_assign_authorizations(self): """Pass through to provider AuthorizationVaultAssignmentSession.can_assign_authorizations""" # Implemented from kitosid template for - # osid.resource.ResourceBinAssignmentSession.can_assign_resources return self._get_provider_session('authorization_vault_assignment_session').can_assign_authorizations() def can_assign_authorizations_to_vault(self, *args, **kwargs): """Pass through to provider AuthorizationVaultAssignmentSession.can_assign_authorizations_to_vault""" # Implemented from kitosid template for - # osid.resource.ResourceBinAssignmentSession.can_assign_resources_to_bin return self._get_provider_session('authorization_vault_assignment_session').can_assign_authorizations_to_vault(*args, **kwargs) def get_assignable_vault_ids(self, *args, **kwargs): """Pass through to provider AuthorizationVaultAssignmentSession.get_assignable_vault_ids""" # Implemented from kitosid template for - # osid.resource.ResourceBinAssignmentSession.get_assignable_bin_ids return self._get_provider_session('authorization_vault_assignment_session').get_assignable_vault_ids(*args, **kwargs) def get_assignable_vault_ids_for_authorization(self, *args, **kwargs): """Pass through to provider AuthorizationVaultAssignmentSession.get_assignable_vault_ids_for_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceBinAssignmentSession.get_assignable_bin_ids_for_resource return self._get_provider_session('authorization_vault_assignment_session').get_assignable_vault_ids_for_authorization(*args, **kwargs) def assign_authorization_to_vault(self, *args, **kwargs): """Pass through to provider AuthorizationVaultAssignmentSession.assign_authorization_to_vault""" # Implemented from kitosid template for - # osid.resource.ResourceBinAssignmentSession.assign_resource_to_bin self._get_provider_session('authorization_vault_assignment_session').assign_authorization_to_vault(*args, **kwargs) def unassign_authorization_from_vault(self, *args, **kwargs): """Pass through to provider AuthorizationVaultAssignmentSession.unassign_authorization_from_vault""" # Implemented from kitosid template for - # osid.resource.ResourceBinAssignmentSession.unassign_resource_from_bin self._get_provider_session('authorization_vault_assignment_session').unassign_authorization_from_vault(*args, **kwargs) def reassign_authorization_to_vault(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) ## # The following methods are from osid.authorization.VaultLookupSession def can_lookup_vaults(self): """Pass through to provider VaultLookupSession.can_lookup_vaults""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.can_lookup_bins_template return self._get_provider_session('vault_lookup_session').can_lookup_vaults() def get_vault(self, *args, **kwargs): """Pass through to provider VaultLookupSession.get_vault""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.get_bin return Vault( self._provider_manager, self._get_provider_session('vault_lookup_session').get_vault(*args, **kwargs), self._runtime, self._proxy) def get_vaults_by_ids(self, *args, **kwargs): """Pass through to provider VaultLookupSession.get_vaults_by_ids""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.get_bins_by_ids catalogs = self._get_provider_session('vault_lookup_session').get_vaults_by_ids(*args, **kwargs) cat_list = [] for cat in catalogs: cat_list.append(Vault(self._provider_manager, cat, self._runtime, self._proxy)) return VaultList(cat_list) def get_vaults_by_genus_type(self, *args, **kwargs): """Pass through to provider VaultLookupSession.get_vaults_by_genus_type""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.get_bins_by_genus_type catalogs = self._get_provider_session('vault_lookup_session').get_vaults_by_genus_type(*args, **kwargs) cat_list = [] for cat in catalogs: cat_list.append(Vault(self._provider_manager, cat, self._runtime, self._proxy)) return VaultList(cat_list) def get_vaults_by_parent_genus_type(self, *args, **kwargs): """Pass through to provider VaultLookupSession.get_vaults_by_parent_genus_type""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.get_bins_by_parent_genus_type catalogs = self._get_provider_session('vault_lookup_session').get_vaults_by_parent_genus_type(*args, **kwargs) cat_list = [] for cat in catalogs: cat_list.append(Vault(self._provider_manager, cat, self._runtime, self._proxy)) return VaultList(cat_list) def get_vaults_by_record_type(self, *args, **kwargs): """Pass through to provider VaultLookupSession.get_vaults_by_record_type""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.get_bins_by_record_type catalogs = self._get_provider_session('vault_lookup_session').get_vaults_by_record_type(*args, **kwargs) cat_list = [] for cat in catalogs: cat_list.append(Vault(self._provider_manager, cat, self._runtime, self._proxy)) return VaultList(cat_list) def get_vaults_by_provider(self, *args, **kwargs): """Pass through to provider VaultLookupSession.get_vaults_by_provider""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.get_bins_by_provider catalogs = self._get_provider_session('vault_lookup_session').get_vaults_by_provider(*args, **kwargs) cat_list = [] for cat in catalogs: cat_list.append(Vault(self._provider_manager, cat, self._runtime, self._proxy)) return VaultList(cat_list) def get_vaults(self): """Pass through to provider VaultLookupSession.get_vaults""" # Implemented from kitosid template for - # osid.resource.BinLookupSession.get_bins_template catalogs = self._get_provider_session('vault_lookup_session').get_vaults() cat_list = [] for cat in catalogs: cat_list.append(Vault(self._provider_manager, cat, self._runtime, self._proxy)) return VaultList(cat_list) vaults = property(fget=get_vaults) ## # The following methods are from osid.authorization.VaultQuerySession def can_search_vaults(self): """Pass through to provider VaultQuerySession.can_search_vaults""" # Implemented from kitosid template for - # osid.resource.BinQuerySession.can_search_bins_template return self._get_provider_session('vault_query_session').can_search_vaults() def get_vault_query(self): """Pass through to provider VaultQuerySession.get_vault_query""" # Implemented from kitosid template for - # osid.resource.BinQuerySession.get_bin_query_template return self._get_provider_session('vault_query_session').get_vault_query() vault_query = property(fget=get_vault_query) def get_vaults_by_query(self, *args, **kwargs): """Pass through to provider VaultQuerySession.get_vaults_by_query""" # Implemented from kitosid template for - # osid.resource.BinQuerySession.get_bins_by_query_template return self._get_provider_session('vault_query_session').get_vaults_by_query(*args, **kwargs) ## # The following methods are from osid.authorization.VaultAdminSession def can_create_vaults(self): """Pass through to provider VaultAdminSession.can_create_vaults""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.can_create_bins return self._get_provider_session('vault_admin_session').can_create_vaults() def can_create_vault_with_record_types(self, *args, **kwargs): """Pass through to provider VaultAdminSession.can_create_vault_with_record_types""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.can_create_bin_with_record_types return self._get_provider_session('vault_admin_session').can_create_vault_with_record_types(*args, **kwargs) def get_vault_form_for_create(self, *args, **kwargs): """Pass through to provider VaultAdminSession.get_vault_form_for_create""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.get_bin_form_for_create return self._get_provider_session('vault_admin_session').get_vault_form_for_create(*args, **kwargs) def create_vault(self, *args, **kwargs): """Pass through to provider VaultAdminSession.create_vault""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.create_bin return Vault( self._provider_manager, self._get_provider_session('vault_admin_session').create_vault(*args, **kwargs), self._runtime, self._proxy) def can_update_vaults(self): """Pass through to provider VaultAdminSession.can_update_vaults""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.can_update_bins return self._get_provider_session('vault_admin_session').can_update_vaults() def get_vault_form_for_update(self, *args, **kwargs): """Pass through to provider VaultAdminSession.get_vault_form_for_update""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.get_bin_form_for_update return self._get_provider_session('vault_admin_session').get_vault_form_for_update(*args, **kwargs) def get_vault_form(self, *args, **kwargs): """Pass through to provider VaultAdminSession.get_vault_form_for_update""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.get_bin_form_for_update_template # This method might be a bit sketchy. Time will tell. if isinstance(args[-1], list) or 'vault_record_types' in kwargs: return self.get_vault_form_for_create(*args, **kwargs) else: return self.get_vault_form_for_update(*args, **kwargs) def update_vault(self, *args, **kwargs): """Pass through to provider VaultAdminSession.update_vault""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.update_bin # OSID spec does not require returning updated catalog return Vault( self._provider_manager, self._get_provider_session('vault_admin_session').update_vault(*args, **kwargs), self._runtime, self._proxy) def save_vault(self, vault_form, *args, **kwargs): """Pass through to provider VaultAdminSession.update_vault""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.update_bin if vault_form.is_for_update(): return self.update_vault(vault_form, *args, **kwargs) else: return self.create_vault(vault_form, *args, **kwargs) def can_delete_vaults(self): """Pass through to provider VaultAdminSession.can_delete_vaults""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.can_delete_bins return self._get_provider_session('vault_admin_session').can_delete_vaults() def delete_vault(self, *args, **kwargs): """Pass through to provider VaultAdminSession.delete_vault""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.delete_bin self._get_provider_session('vault_admin_session').delete_vault(*args, **kwargs) def can_manage_vault_aliases(self): """Pass through to provider VaultAdminSession.can_manage_vault_aliases""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.can_manage_resource_aliases_template return self._get_provider_session('vault_admin_session').can_manage_vault_aliases() def alias_vault(self, *args, **kwargs): """Pass through to provider VaultAdminSession.alias_vault""" # Implemented from kitosid template for - # osid.resource.BinAdminSession.alias_bin self._get_provider_session('vault_admin_session').alias_vault(*args, **kwargs) ## # The following methods are from osid.authorization.VaultHierarchySession def get_vault_hierarchy_id(self): """Pass through to provider VaultHierarchySession.get_vault_hierarchy_id""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_bin_hierarchy_id return self._get_provider_session('vault_hierarchy_session').get_vault_hierarchy_id() vault_hierarchy_id = property(fget=get_vault_hierarchy_id) def get_vault_hierarchy(self): """Pass through to provider VaultHierarchySession.get_vault_hierarchy""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_bin_hierarchy return self._get_provider_session('vault_hierarchy_session').get_vault_hierarchy() vault_hierarchy = property(fget=get_vault_hierarchy) def can_access_vault_hierarchy(self): """Pass through to provider VaultHierarchySession.can_access_vault_hierarchy""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.can_access_bin_hierarchy return self._get_provider_session('vault_hierarchy_session').can_access_vault_hierarchy() def get_root_vault_ids(self): """Pass through to provider VaultHierarchySession.get_root_vault_ids""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_root_bin_ids return self._get_provider_session('vault_hierarchy_session').get_root_vault_ids() root_vault_ids = property(fget=get_root_vault_ids) def get_root_vaults(self): """Pass through to provider VaultHierarchySession.get_root_vaults""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_root_bins return self._get_provider_session('vault_hierarchy_session').get_root_vaults() root_vaults = property(fget=get_root_vaults) def has_parent_vaults(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.has_parent_vaults""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.has_parent_bins return self._get_provider_session('vault_hierarchy_session').has_parent_vaults(*args, **kwargs) def is_parent_of_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.is_parent_of_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.is_parent_of_bin return self._get_provider_session('vault_hierarchy_session').is_parent_of_vault(*args, **kwargs) def get_parent_vault_ids(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.get_parent_vault_ids""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_parent_bin_ids return self._get_provider_session('vault_hierarchy_session').get_parent_vault_ids(*args, **kwargs) def get_parent_vaults(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.get_parent_vaults""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_parent_bins return self._get_provider_session('vault_hierarchy_session').get_parent_vaults(*args, **kwargs) def is_ancestor_of_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.is_ancestor_of_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.is_ancestor_of_bin return self._get_provider_session('vault_hierarchy_session').is_ancestor_of_vault(*args, **kwargs) def has_child_vaults(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.has_child_vaults""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.has_child_bins return self._get_provider_session('vault_hierarchy_session').has_child_vaults(*args, **kwargs) def is_child_of_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.is_child_of_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.is_child_of_bin return self._get_provider_session('vault_hierarchy_session').is_child_of_vault(*args, **kwargs) def get_child_vault_ids(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.get_child_vault_ids""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_child_bin_ids return self._get_provider_session('vault_hierarchy_session').get_child_vault_ids(*args, **kwargs) def get_child_vaults(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.get_child_vaults""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_child_bins return self._get_provider_session('vault_hierarchy_session').get_child_vaults(*args, **kwargs) def is_descendant_of_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.is_descendant_of_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.is_descendant_of_bin return self._get_provider_session('vault_hierarchy_session').is_descendant_of_vault(*args, **kwargs) def get_vault_node_ids(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.get_vault_node_ids""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_bin_node_ids return self._get_provider_session('vault_hierarchy_session').get_vault_node_ids(*args, **kwargs) def get_vault_nodes(self, *args, **kwargs): """Pass through to provider VaultHierarchySession.get_vault_nodes""" # Implemented from kitosid template for - # osid.resource.BinHierarchySession.get_bin_nodes return self._get_provider_session('vault_hierarchy_session').get_vault_nodes(*args, **kwargs) ## # The following methods are from osid.authorization.VaultHierarchyDesignSession def can_modify_vault_hierarchy(self): """Pass through to provider VaultHierarchyDesignSession.can_modify_vault_hierarchy""" # Implemented from kitosid template for - # osid.resource.BinHierarchyDesignSession.can_modify_bin_hierarchy return self._get_provider_session('vault_hierarchy_design_session').can_modify_vault_hierarchy() def create_vault_hierarchy(self, *args, **kwargs): """Pass through to provider VaultHierarchyDesignSession.can_modify_vault_hierarchy""" # Patched in by cjshaw@mit.edu, Jul 23, 2014, added by birdland to template on Aug 8, 2014 # Is not part of specs for catalog hierarchy design sessions, but may want to be in hierarchy service instead # Will not return an actual object, just JSON # since a BankHierarchy does not seem to be an OSID thing. return self._get_provider_session('vault_hierarchy_design_session').create_vault_hierarchy(*args, **kwargs) def delete_vault_hierarchy(self, *args, **kwargs): """Pass through to provider VaultHierarchyDesignSession.can_modify_vault_hierarchy""" # Patched in by cjshaw@mit.edu, Jul 23, 2014, added by birdland to template on Aug 8, 2014 # Is not part of specs for catalog hierarchy design sessions, but may want to be in hierarchy service instead # Will not return an actual object, just JSON # since a BankHierarchy does not seem to be an OSID thing. return self._get_provider_session('vault_hierarchy_design_session').delete_vault_hierarchy(*args, **kwargs) def add_root_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchyDesignSession.add_root_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchyDesignSession.add_root_bin self._get_provider_session('vault_hierarchy_design_session').add_root_vault(*args, **kwargs) def remove_root_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchyDesignSession.remove_root_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchyDesignSession.remove_root_bin self._get_provider_session('vault_hierarchy_design_session').remove_root_vault(*args, **kwargs) def add_child_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchyDesignSession.add_child_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchyDesignSession.add_child_bin self._get_provider_session('vault_hierarchy_design_session').add_child_vault(*args, **kwargs) def remove_child_vault(self, *args, **kwargs): """Pass through to provider VaultHierarchyDesignSession.remove_child_vault""" # Implemented from kitosid template for - # osid.resource.BinHierarchyDesignSession.remove_child_bin self._get_provider_session('vault_hierarchy_design_session').remove_child_vault(*args, **kwargs) def remove_child_vaults(self, *args, **kwargs): """Pass through to provider VaultHierarchyDesignSession.remove_child_vaults""" # Implemented from kitosid template for - # osid.resource.BinHierarchyDesignSession.remove_child_bins self._get_provider_session('vault_hierarchy_design_session').remove_child_vaults(*args, **kwargs) class AuthorizationProxyManager(osid.OsidProxyManager, AuthorizationProfile, authorization_managers.AuthorizationProxyManager): """AuthorizationProxyManager convenience adapter including related Session methods.""" def get_authorization_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorization_session_for_vault(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorization_lookup_session(self, *args, **kwargs): """Sends control to Manager""" # Implemented from kitosid template for - # osid.resource.ResourceProxyManager.get_resource_lookup_session_template return AuthorizationManager.get_authorization_lookup_session(*args, **kwargs) def get_authorization_lookup_session_for_vault(self, *args, **kwargs): """Sends control to Manager""" # Implemented from kitosid template for - # osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template return AuthorizationManager.get_authorization_lookup_session_for_vault(*args, **kwargs) def get_authorization_query_session(self, *args, **kwargs): """Sends control to Manager""" # Implemented from kitosid template for - # osid.resource.ResourceProxyManager.get_resource_lookup_session_template return AuthorizationManager.get_authorization_query_session(*args, **kwargs) def get_authorization_query_session_for_vault(self, *args, **kwargs): """Sends control to Manager""" # Implemented from kitosid template for - # osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template return AuthorizationManager.get_authorization_query_session_for_vault(*args, **kwargs) def get_authorization_admin_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorization_admin_session_for_vault(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorization_vault_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorization_vault_assignment_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_vault_lookup_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_vault_query_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_vault_admin_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_vault_hierarchy_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_vault_hierarchy_design_session(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorization_batch_proxy_manager(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') authorization_batch_proxy_manager = property(fget=get_authorization_batch_proxy_manager) def get_authorization_rules_proxy_manager(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') authorization_rules_proxy_manager = property(fget=get_authorization_rules_proxy_manager) class Vault(abc_authorization_objects.Vault, osid.OsidSession, osid.OsidCatalog): """Vault convenience adapter including related Session methods.""" # WILL THIS EVER BE CALLED DIRECTLY - OUTSIDE OF A MANAGER? def __init__(self, provider_manager, catalog, runtime, proxy, **kwargs): self._provider_manager = provider_manager self._catalog = catalog self._runtime = runtime osid.OsidObject.__init__(self, self._catalog) # This is to initialize self._object osid.OsidSession.__init__(self, proxy) # This is to initialize self._proxy self._catalog_id = catalog.get_id() self._provider_sessions = kwargs self._session_management = AUTOMATIC self._vault_view = DEFAULT self._object_views = dict() self._operable_views = dict() self._containable_views = dict() def _set_vault_view(self, session): """Sets the underlying vault view to match current view""" if self._vault_view == FEDERATED: try: session.use_federated_vault_view() except AttributeError: pass else: try: session.use_isolated_vault_view() except AttributeError: pass def _set_object_view(self, session): """Sets the underlying object views to match current view""" for obj_name in self._object_views: if self._object_views[obj_name] == PLENARY: try: getattr(session, 'use_plenary_' + obj_name + '_view')() except AttributeError: pass else: try: getattr(session, 'use_comparative_' + obj_name + '_view')() except AttributeError: pass def _set_operable_view(self, session): """Sets the underlying operable views to match current view""" for obj_name in self._operable_views: if self._operable_views[obj_name] == ACTIVE: try: getattr(session, 'use_active_' + obj_name + '_view')() except AttributeError: pass else: try: getattr(session, 'use_any_status_' + obj_name + '_view')() except AttributeError: pass def _set_containable_view(self, session): """Sets the underlying containable views to match current view""" for obj_name in self._containable_views: if self._containable_views[obj_name] == SEQUESTERED: try: getattr(session, 'use_sequestered_' + obj_name + '_view')() except AttributeError: pass else: try: getattr(session, 'use_unsequestered_' + obj_name + '_view')() except AttributeError: pass def _get_provider_session(self, session_name): """Returns the requested provider session. Instantiates a new one if the named session is not already known. """ agent_key = self._get_agent_key() if session_name in self._provider_sessions[agent_key]: return self._provider_sessions[agent_key][session_name] else: session_class = getattr(self._provider_manager, 'get_' + session_name + '_for_vault') if self._proxy is None: if 'notification_session' in session_name: # Is there something else we should do about the receiver field? session = session_class('fake receiver', self._catalog.get_id()) else: session = session_class(self._catalog.get_id()) else: if 'notification_session' in session_name: # Is there something else we should do about the receiver field? session = session_class('fake receiver', self._catalog.get_id(), self._proxy) else: session = session_class(self._catalog.get_id(), self._proxy) self._set_vault_view(session) self._set_object_view(session) self._set_operable_view(session) self._set_containable_view(session) if self._session_management != DISABLED: self._provider_sessions[agent_key][session_name] = session return session def get_vault_id(self): """Gets the Id of this vault.""" return self._catalog_id def get_vault(self): """Strange little method to assure conformance for inherited Sessions.""" return self def __getattr__(self, name): if '_catalog' in self.__dict__: try: return self._catalog[name] except AttributeError: pass raise AttributeError def close_sessions(self): """Close all sessions currently being managed by this Manager to save memory.""" if self._session_management != MANDATORY: self._provider_sessions = dict() else: raise IllegalState() def use_automatic_session_management(self): """Session state will be saved until closed by consumers.""" self._session_management = AUTOMATIC def use_mandatory_session_management(self): """Session state will always be saved and can not be closed by consumers.""" # Session state will be saved and can not be closed by consumers self._session_management = MANDATORY def disable_session_management(self): """Session state will never be saved.""" self._session_management = DISABLED self.close_sessions() def get_vault_record(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) ## # The following methods are from osid.authorization.AuthorizationSession def can_access_authorizations(self): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') def is_authorized(self, *args, **kwargs): """Pass through to provider AuthorizationSession.is_authorized""" return self._get_provider_session('authorization_session').is_authorized(*args, **kwargs) def get_authorization_condition(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def is_authorized_on_condition(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) ## # The following methods are from osid.authorization.AuthorizationLookupSession def can_lookup_authorizations(self): """Pass through to provider AuthorizationLookupSession.can_lookup_authorizations""" # Implemented from kitosid template for - # osid.resource.ResourceLookupSession.can_lookup_resources_template return self._get_provider_session('authorization_lookup_session').can_lookup_authorizations() def use_comparative_authorization_view(self): """Pass through to provider AuthorizationLookupSession.use_comparative_authorization_view""" self._object_views['authorization'] = COMPARATIVE # self._get_provider_session('authorization_lookup_session') # To make sure the session is tracked for session in self._get_provider_sessions(): try: session.use_comparative_authorization_view() except AttributeError: pass def use_plenary_authorization_view(self): """Pass through to provider AuthorizationLookupSession.use_plenary_authorization_view""" self._object_views['authorization'] = PLENARY # self._get_provider_session('authorization_lookup_session') # To make sure the session is tracked for session in self._get_provider_sessions(): try: session.use_plenary_authorization_view() except AttributeError: pass def use_federated_vault_view(self): """Pass through to provider AuthorizationLookupSession.use_federated_vault_view""" self._vault_view = FEDERATED # self._get_provider_session('authorization_lookup_session') # To make sure the session is tracked for session in self._get_provider_sessions(): try: session.use_federated_vault_view() except AttributeError: pass def use_isolated_vault_view(self): """Pass through to provider AuthorizationLookupSession.use_isolated_vault_view""" self._vault_view = ISOLATED # self._get_provider_session('authorization_lookup_session') # To make sure the session is tracked for session in self._get_provider_sessions(): try: session.use_isolated_vault_view() except AttributeError: pass def use_effective_authorization_view(self): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') def use_any_effective_authorization_view(self): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') def use_implicit_authorization_view(self): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') def use_explicit_authorization_view(self): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services') def get_authorization(self, *args, **kwargs): """Pass through to provider AuthorizationLookupSession.get_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceLookupSession.get_resource_template return self._get_provider_session('authorization_lookup_session').get_authorization(*args, **kwargs) def get_authorizations_by_ids(self, *args, **kwargs): """Pass through to provider AuthorizationLookupSession.get_authorizations_by_ids""" # Implemented from kitosid template for - # osid.resource.ResourceLookupSession.get_resources_by_ids_template return self._get_provider_session('authorization_lookup_session').get_authorizations_by_ids(*args, **kwargs) def get_authorizations_by_genus_type(self, *args, **kwargs): """Pass through to provider AuthorizationLookupSession.get_authorizations_by_genus_type""" # Implemented from kitosid template for - # osid.resource.ResourceLookupSession.get_resources_by_genus_type_template return self._get_provider_session('authorization_lookup_session').get_authorizations_by_genus_type(*args, **kwargs) def get_authorizations_by_parent_genus_type(self, *args, **kwargs): """Pass through to provider AuthorizationLookupSession.get_authorizations_by_parent_genus_type""" # Implemented from kitosid template for - # osid.resource.ResourceLookupSession.get_resources_by_parent_genus_type_template return self._get_provider_session('authorization_lookup_session').get_authorizations_by_parent_genus_type(*args, **kwargs) def get_authorizations_by_record_type(self, *args, **kwargs): """Pass through to provider AuthorizationLookupSession.get_authorizations_by_record_type""" # Implemented from kitosid template for - # osid.resource.ResourceLookupSession.get_resources_by_record_type_template return self._get_provider_session('authorization_lookup_session').get_authorizations_by_record_type(*args, **kwargs) def get_authorizations_on_date(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_resource(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_resource_on_date(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_agent(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_agent_on_date(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_function(self, *args, **kwargs): """Pass through to provider AuthorizationLookupSession.get_authorizations_for_function""" # Implemented from kitosid template for - # osid.resource.ActivityLookupSession.get_activities_for_objective return self._get_provider_session('authorization_lookup_session').get_authorizations_for_function(*args, **kwargs) def get_authorizations_for_function_on_date(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_resource_and_function(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_resource_and_function_on_date(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_agent_and_function(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_for_agent_and_function_on_date(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations_by_qualifier(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_explicit_authorization(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def get_authorizations(self): """Pass through to provider AuthorizationLookupSession.get_authorizations""" # Implemented from kitosid template for - # osid.resource.ResourceLookupSession.get_resources_template return self._get_provider_session('authorization_lookup_session').get_authorizations() authorizations = property(fget=get_authorizations) ## # The following methods are from osid.authorization.AuthorizationQuerySession def can_search_authorizations(self): """Pass through to provider AuthorizationQuerySession.can_search_authorizations""" # Implemented from kitosid template for - # osid.resource.ResourceQuerySession.can_search_resources_template return self._get_provider_session('authorization_query_session').can_search_authorizations() def get_authorization_query(self): """Pass through to provider AuthorizationQuerySession.get_authorization_query""" # Implemented from kitosid template for - # osid.resource.ResourceQuerySession.get_item_query_template return self._get_provider_session('authorization_query_session').get_authorization_query() authorization_query = property(fget=get_authorization_query) def get_authorizations_by_query(self, *args, **kwargs): """Pass through to provider AuthorizationQuerySession.get_authorizations_by_query""" # Implemented from kitosid template for - # osid.resource.ResourceQuerySession.get_items_by_query_template return self._get_provider_session('authorization_query_session').get_authorizations_by_query(*args, **kwargs) ## # The following methods are from osid.authorization.AuthorizationAdminSession def can_create_authorizations(self): """Pass through to provider AuthorizationAdminSession.can_create_authorizations""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.can_create_resources return self._get_provider_session('authorization_admin_session').can_create_authorizations() def can_create_authorization_with_record_types(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.can_create_authorization_with_record_types""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.can_create_resource_with_record_types return self._get_provider_session('authorization_admin_session').can_create_authorization_with_record_types(*args, **kwargs) def get_authorization_form_for_create_for_agent(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.get_authorization_form_for_create_for_agent""" return self._get_provider_session('authorization_admin_session').get_authorization_form_for_create_for_agent(*args, **kwargs) def get_authorization_form_for_create_for_resource(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.get_authorization_form_for_create_for_resource""" return self._get_provider_session('authorization_admin_session').get_authorization_form_for_create_for_resource(*args, **kwargs) def get_authorization_form_for_create_for_resource_and_trust(self, *args, **kwargs): """Pass through to provider unimplemented""" raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs)) def create_authorization(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.create_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.create_resource return self._get_provider_session('authorization_admin_session').create_authorization(*args, **kwargs) def can_update_authorizations(self): """Pass through to provider AuthorizationAdminSession.can_update_authorizations""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.can_update_resources return self._get_provider_session('authorization_admin_session').can_update_authorizations() def get_authorization_form_for_update(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.get_authorization_form_for_update""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.get_resource_form_for_update return self._get_provider_session('authorization_admin_session').get_authorization_form_for_update(*args, **kwargs) def get_authorization_form(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.get_authorization_form_for_update""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.get_resource_form_for_update # This method might be a bit sketchy. Time will tell. if isinstance(args[-1], list) or 'authorization_record_types' in kwargs: return self.get_authorization_form_for_create(*args, **kwargs) else: return self.get_authorization_form_for_update(*args, **kwargs) def duplicate_authorization(self, authorization_id): # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.get_resource_form_for_update return self._get_provider_session('authorization_admin_session').duplicate_authorization(authorization_id) def update_authorization(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.update_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.update_resource # Note: The OSID spec does not require returning updated object return self._get_provider_session('authorization_admin_session').update_authorization(*args, **kwargs) def save_authorization(self, authorization_form, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.update_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.update_resource if authorization_form.is_for_update(): return self.update_authorization(authorization_form, *args, **kwargs) else: return self.create_authorization(authorization_form, *args, **kwargs) def can_delete_authorizations(self): """Pass through to provider AuthorizationAdminSession.can_delete_authorizations""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.can_delete_resources return self._get_provider_session('authorization_admin_session').can_delete_authorizations() def delete_authorization(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.delete_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.delete_resource self._get_provider_session('authorization_admin_session').delete_authorization(*args, **kwargs) def can_manage_authorization_aliases(self): """Pass through to provider AuthorizationAdminSession.can_manage_authorization_aliases""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.can_manage_resource_aliases_template return self._get_provider_session('authorization_admin_session').can_manage_authorization_aliases() def alias_authorization(self, *args, **kwargs): """Pass through to provider AuthorizationAdminSession.alias_authorization""" # Implemented from kitosid template for - # osid.resource.ResourceAdminSession.alias_resources self._get_provider_session('authorization_admin_session').alias_authorization(*args, **kwargs) class VaultList(abc_authorization_objects.VaultList, osid.OsidList): """VaultList convenience adapter including related Session methods.""" def get_next_vault(self): """Gets next object""" # Implemented from kitosid template for - # osid.resource.ResourceList.get_next_resource try: next_item = next(self) except StopIteration: raise IllegalState('no more elements available in this list') else: return next_item def next(self): """next method for enumerator""" # Implemented from kitosid template for - # osid.resource.ResourceList.get_next_resource next_item = osid.OsidList.next(self) return next_item __next__ = next next_vault = property(fget=get_next_vault) def get_next_vaults(self, n): """gets next n objects from list""" # Implemented from kitosid template for - # osid.resource.ResourceList.get_next_resources if n > self.available(): # !!! This is not quite as specified (see method docs) !!! raise IllegalState('not enough elements available in this list') else: next_list = [] i = 0 while i < n: try: next_list.append(next(self)) except StopIteration: break i += 1 return next_list

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fd95acd15a454445711cd382b39c61c451a78b4a

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py

Python

code/get_model.py

SIAT-code/Multi-PLI

073cc65d8562261d5e43500d76e8f13363f936db

[ "Apache-2.0" ]

4

2021-07-04T01:49:22.000Z

2022-01-11T12:51:42.000Z

code/get_model.py

SIAT-code/Multi-PLI

073cc65d8562261d5e43500d76e8f13363f936db

[ "Apache-2.0" ]

null

code/get_model.py

SIAT-code/Multi-PLI

073cc65d8562261d5e43500d76e8f13363f936db

[ "Apache-2.0" ]

1

2021-12-20T12:54:17.000Z

import keras from keras.models import Model from keras.layers import Input,Dense, Dropout, Activation, Flatten,Reshape,concatenate,LSTM,Bidirectional, Average from keras.layers import Conv2D, MaxPooling2D,Conv1D,MaxPooling1D,AveragePooling2D from keras.layers import Lambda, dot import tensorflow as tf #import string from keras.utils import multi_gpu_model from keras.utils import plot_model import numpy as np import os from keras import regularizers from keras import initializers import tensorflow def attention_3d_block(hidden_states,out_shape=128,name='pro_'): hidden_size = int(hidden_states.shape[2]) # Inside dense layer # hidden_states dot W => score_first_part # (batch_size, time_steps, hidden_size) dot (hidden_size, hidden_size) => (batch_size, time_steps, hidden_size) # W is the trainable weight matrix of attention Luong's multiplicative style score score_first_part = Dense(hidden_size, use_bias=False, name=name+'attention_score_vec')(hidden_states) # score_first_part dot last_hidden_state => attention_weights # (batch_size, time_steps, hidden_size) dot (batch_size, hidden_size) => (batch_size, time_steps) h_t = Lambda(lambda x: x[:, -1, :], output_shape=(hidden_size,), name=name+'last_hidden_state')(hidden_states) score = dot([score_first_part, h_t], [2, 1], name=name+'attention_score') attention_weights = Activation('softmax', name=name+'attention_weight')(score) # (batch_size, time_steps, hidden_size) dot (batch_size, time_steps) => (batch_size, hidden_size) context_vector = dot([hidden_states, attention_weights], [1, 1], name=name+'context_vector') pre_activation = concatenate([context_vector, h_t], name=name+'attention_output') attention_vector = Dense(out_shape, use_bias=False, activation='tanh', name=name+'attention_vector')(pre_activation) return attention_vector def conv2d_bn(x, nb_filter, num_row, num_col,name, padding='same', strides=(1, 1), use_bias=False): x = Conv2D(nb_filter, (num_row, num_col), name=name, strides=strides, padding=padding, use_bias=use_bias, kernel_regularizer=regularizers.l2(0.00004), kernel_initializer=initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='normal', seed=None))(x) x = Activation('relu')(x) return x def block_inception(input,filters_1x1, filters_3x3_reduce, filters_3x3, filters_5x5_reduce, filters_5x5, filters_pool_proj,layer_name): branch_0 = conv2d_bn(input, filters_1x1, 1, 1,name=layer_name+'_branch_0') branch_1 = conv2d_bn(input, filters_3x3_reduce, 1, 1,name=layer_name+'_branch_1_3x3_reduce') branch_1 = conv2d_bn(branch_1, filters_3x3, 3, 3,name=layer_name+'_branch_1_3x3') branch_2 = conv2d_bn(input, filters_5x5_reduce, 1, 1,name=layer_name+'_branch_2_5x5_reduce') branch_2 = conv2d_bn(branch_2, filters_5x5, 3, 3,name=layer_name+'_branch_2_3x3_0') branch_2 = conv2d_bn(branch_2, filters_5x5, 3, 3,name=layer_name+'_branch_2_3x3_1') branch_3 = MaxPooling2D((3,3), strides=(1,1), padding='same',name=layer_name+'_branch_3_maxpooling')(input)#AveragePooling2D branch_3 = conv2d_bn(branch_3, filters_pool_proj, 1, 1,name=layer_name+'_branch_3_pool_proj') x = concatenate([branch_0, branch_1, branch_2, branch_3], axis=-1,name=layer_name+'_concat') return x def block_inception_b(input,filters_1x1, filters_5x5_reduce, filters_5x5, filters_7x7_reduce, filters_1x7,filters_7x1,filters_pool_proj,layer_name): branch_0 = conv2d_bn(input, filters_1x1, 1, 1,name=layer_name+'_branch_0') branch_1 = conv2d_bn(input,filters_7x7_reduce, 1, 1,name=layer_name+'_branch_1_7x7_reduce') branch_1 = conv2d_bn(branch_1,filters_1x7, 1, 7,name=layer_name+'_branch_1_7x7_0') branch_1 = conv2d_bn(branch_1,filters_7x1, 7, 1,name=layer_name+'_branch_1_7x7_1') branch_2 = conv2d_bn(input, filters_5x5_reduce, 1, 1,name=layer_name+'_branch_2_5x5_reduce') branch_2 = conv2d_bn(branch_2, filters_5x5, 3, 3,name=layer_name+'_branch_2_3x3_0') branch_2 = conv2d_bn(branch_2, filters_5x5, 3, 3,name=layer_name+'_branch_2_3x3_1') branch_3 = AveragePooling2D((3,3), strides=(1,1), padding='same')(input) branch_3 = conv2d_bn(branch_3, filters_pool_proj, 1, 1,name=layer_name+'_branch_3_pool_proj') x = concatenate([branch_0, branch_1, branch_2, branch_3], axis=-1)#branch_2, return x def simple_block(input,nb_filter,num_row,num_col,layer_name): input = Conv2D(nb_filter, (num_row, num_col), padding='same', activation='relu', name=layer_name+'_conv0')(input) input = Conv2D(nb_filter, (num_row, num_col), padding='same', activation='relu', name=layer_name+'_conv1')(input) return input def get_model_classification(save_dir,alpha, pro_branch_switch1='',pro_branch_switch2='', pro_branch_switch3='',pro_add_attention=False, comp_branch_switch1='',comp_branch_switch2='', comp_branch_switch3='',comp_add_attention=False, ): ###MODEL ##input protein_input = Input(shape=(1200, 20, 1), name='protein_input') comp_input = Input(shape=(200, 67, 1), name='comp_input') ##protein branch # layer1 with tf.device('/gpu:0'): if pro_branch_switch1 == 'inception_block': pro_layer1 = block_inception(protein_input, filters_1x1=8, filters_3x3_reduce=1, filters_3x3=32, filters_5x5_reduce=1, filters_5x5=32, filters_pool_proj=16,layer_name='pro_layer1') else: pro_layer1 = simple_block(protein_input, nb_filter=32, num_row=3, num_col=3, layer_name='pro_layer1') pro_layer1 = MaxPooling2D(pool_size=(3, 3),padding='same', name='pro_layer1_poll')(pro_layer1) # layer2 if pro_branch_switch2=='inception_block': pro_layer2 = block_inception(pro_layer1, filters_1x1=16, filters_3x3_reduce=16, filters_3x3=64, filters_5x5_reduce=16, filters_5x5=64, filters_pool_proj=32,layer_name='pro_layer2') else: pro_layer2=simple_block(pro_layer1,nb_filter=64,num_row=3,num_col=3,layer_name='pro_layer2') pro_layer2 = MaxPooling2D(pool_size=(3, 3), padding='same',name='pro_layer2_poll')(pro_layer2) # layer3 if pro_branch_switch3=='inception_block': pro_layer3 = block_inception(pro_layer2, filters_1x1=32, filters_3x3_reduce=64, filters_3x3=128, filters_5x5_reduce=64, filters_5x5=128, filters_pool_proj=64,layer_name='pro_layer3') elif pro_branch_switch3=='inception_block_b': pro_layer3 = block_inception_b(pro_layer2, filters_1x1=32, filters_5x5_reduce=64, filters_5x5=128, filters_7x7_reduce=64, filters_1x7=128,filters_7x1=128, filters_pool_proj=64,layer_name='pro_layer3') else: pro_layer3 = simple_block(pro_layer2, nb_filter=128, num_row=3, num_col=3, layer_name='pro_layer3') pro_layer3 = MaxPooling2D(pool_size=(3, 3), padding='same',name='pro_layer3_pool')(pro_layer3) # layer4 if pro_add_attention: h_t = Lambda(tf.reshape,output_shape=[45,352,], arguments={'shape': [-1, 45, 352]}, name='pro_convert_to_timestep')(pro_layer3) pro_layer_tran_result = attention_3d_block(h_t,1024,'pro_')#batch*1024 else: pro_layer_tran_result = Flatten(name='pro_layer4_flatten')(pro_layer3) pro_layer_tran_result = Dense(1024, activation='relu', name='pro_layer5_den')(pro_layer_tran_result) pro_layer_tran_result = Dropout(alpha, name='pro_drop1')(pro_layer_tran_result) ##compound branch # layer1 with tf.device('/gpu:1'): if comp_branch_switch1=='inception_block': comp_layer1 = block_inception(comp_input, filters_1x1=8, filters_3x3_reduce=1, filters_3x3=16, filters_5x5_reduce=1, filters_5x5=16, filters_pool_proj=16, layer_name='comp_layer1') else: comp_layer1 = simple_block(comp_input, 32, 3, 3, 'comp_layer1') comp_layer1 = MaxPooling2D(pool_size=(2, 2),padding='same', name='comp_layer1_poll')(comp_layer1) # layer2 if comp_branch_switch2=='inception_block': comp_layer2 = block_inception(comp_layer1, filters_1x1=16, filters_3x3_reduce=16, filters_3x3=64, filters_5x5_reduce=16, filters_5x5=64, filters_pool_proj=32,layer_name='comp_layer2') else: comp_layer2=simple_block(comp_layer1,64,3,3,'comp_layer2') comp_layer2 = MaxPooling2D(pool_size=(2, 2), padding='same',name='comp_layer2_poll')(comp_layer2) # layer3 if comp_branch_switch3=='inception_block': comp_layer3 = block_inception(comp_layer2, filters_1x1=32, filters_3x3_reduce=32, filters_3x3=128, filters_5x5_reduce=32, filters_5x5=128, filters_pool_proj=32,layer_name='comp_layer3') elif comp_branch_switch3=='inception_block_b': comp_layer3 = block_inception_b(comp_layer2, filters_1x1=32, filters_5x5_reduce=32, filters_5x5=128, filters_7x7_reduce=32, filters_1x7=128, filters_7x1=128, filters_pool_proj=32, layer_name='comp_layer3') else: comp_layer3=simple_block(comp_layer2,128,3,3,'comp_layer3') comp_layer3 = MaxPooling2D(pool_size=(2, 2), padding='same',name='comp_layer3_pool')(comp_layer3) # layer4 if comp_add_attention: h_t = Lambda(tf.reshape,output_shape=[25*8,320,], arguments={'shape': [-1, 25*8, 320]}, name='comp_convert_to_timestep')(comp_layer3) comp_layer_tran_result = attention_3d_block(h_t,1024,'comp_')#batch*1024 else: comp_layer_tran_result = Flatten(name='comp_layer4_flatten')(comp_layer3) comp_layer_tran_result = Dense(640, activation='relu', name='comp_layer5_den')(comp_layer_tran_result) # layer5 comp_layer_tran_result = Dropout(alpha, name='comp_drop1')(comp_layer_tran_result) with tf.device('/gpu:2'): pro_com = keras.layers.concatenate([pro_layer_tran_result, comp_layer_tran_result]) # We stack a deep densely-connected network on top fc_pro_com = Dense(512, activation='relu', name='den1')(pro_com) fc_pro_com = Dropout(alpha, name='drop1')(fc_pro_com) dense1 = [] FC1 = Dense(64, activation='relu') for p in np.linspace(0.1,0.5, 5): x = Dropout(p)(fc_pro_com) x = FC1(x) x = Dense(1,activation='sigmoid')(x) dense1.append(x) class_out = Average()(dense1) classification_model = Model([protein_input, comp_input],class_out) plot_model(classification_model, to_file=save_dir + '/model_with_classification.png', show_shapes=True) return classification_model def get_model_regression(save_dir,alpha, pro_branch_switch1='',pro_branch_switch2='', pro_branch_switch3='',pro_add_attention=False, comp_branch_switch1='',comp_branch_switch2='', comp_branch_switch3='',comp_add_attention=False, ): ###MODEL ##input protein_input = Input(shape=(1200, 20, 1), name='protein_input') comp_input = Input(shape=(200, 67, 1), name='comp_input') ##protein branch # layer1 with tf.device('/gpu:0'): if pro_branch_switch1 == 'inception_block': pro_layer1 = block_inception(protein_input, filters_1x1=8, filters_3x3_reduce=1, filters_3x3=32, filters_5x5_reduce=1, filters_5x5=32, filters_pool_proj=16,layer_name='pro_layer1') else: pro_layer1 = simple_block(protein_input, nb_filter=32, num_row=3, num_col=3, layer_name='pro_layer1') pro_layer1 = MaxPooling2D(pool_size=(3, 3),padding='same', name='pro_layer1_poll')(pro_layer1) # layer2 if pro_branch_switch2=='inception_block': pro_layer2 = block_inception(pro_layer1, filters_1x1=16, filters_3x3_reduce=16, filters_3x3=64, filters_5x5_reduce=16, filters_5x5=64, filters_pool_proj=32,layer_name='pro_layer2') else: pro_layer2=simple_block(pro_layer1,nb_filter=64,num_row=3,num_col=3,layer_name='pro_layer2') pro_layer2 = MaxPooling2D(pool_size=(3, 3), padding='same',name='pro_layer2_poll')(pro_layer2) # layer3 if pro_branch_switch3=='inception_block': pro_layer3 = block_inception(pro_layer2, filters_1x1=32, filters_3x3_reduce=64, filters_3x3=128, filters_5x5_reduce=64, filters_5x5=128, filters_pool_proj=64,layer_name='pro_layer3') elif pro_branch_switch3=='inception_block_b': pro_layer3 = block_inception_b(pro_layer2, filters_1x1=32, filters_5x5_reduce=64, filters_5x5=128, filters_7x7_reduce=64, filters_1x7=128,filters_7x1=128, filters_pool_proj=64,layer_name='pro_layer3') else: pro_layer3 = simple_block(pro_layer2, nb_filter=128, num_row=3, num_col=3, layer_name='pro_layer3') pro_layer3 = MaxPooling2D(pool_size=(3, 3), padding='same',name='pro_layer3_pool')(pro_layer3) # layer4 if pro_add_attention: h_t = Lambda(tf.reshape,output_shape=[45,352,], arguments={'shape': [-1, 45, 352]}, name='pro_convert_to_timestep')(pro_layer3)#0000000000128 # h_t = Bidirectional(LSTM(100, return_sequences=True),input_shape=(45,128))(h_t) #batch*tmiestep*100 pro_layer_tran_result = attention_3d_block(h_t,1024,'pro_')#batch*1024 else: pro_layer_tran_result = Flatten(name='pro_layer4_flatten')(pro_layer3) pro_layer_tran_result = Dense(1024, activation='relu', name='pro_layer5_den')(pro_layer_tran_result) pro_layer_tran_result = Dropout(alpha, name='pro_drop1')(pro_layer_tran_result) ##compound branch # layer1 with tf.device('/gpu:1'): if comp_branch_switch1=='inception_block': comp_layer1 = block_inception(comp_input, filters_1x1=8, filters_3x3_reduce=1, filters_3x3=16, filters_5x5_reduce=1, filters_5x5=16, filters_pool_proj=16, layer_name='comp_layer1') else: comp_layer1 = simple_block(comp_input, 32, 3, 3, 'comp_layer1') comp_layer1 = MaxPooling2D(pool_size=(2, 2),padding='same', name='comp_layer1_poll')(comp_layer1) # layer2 if comp_branch_switch2=='inception_block': comp_layer2 = block_inception(comp_layer1, filters_1x1=16, filters_3x3_reduce=16, filters_3x3=64, filters_5x5_reduce=16, filters_5x5=64, filters_pool_proj=32,layer_name='comp_layer2') else: comp_layer2=simple_block(comp_layer1,64,3,3,'comp_layer2') comp_layer2 = MaxPooling2D(pool_size=(2, 2), padding='same',name='comp_layer2_poll')(comp_layer2) # layer3 if comp_branch_switch3=='inception_block': comp_layer3 = block_inception(comp_layer2, filters_1x1=32, filters_3x3_reduce=32, filters_3x3=128, filters_5x5_reduce=32, filters_5x5=128, filters_pool_proj=32,layer_name='comp_layer3') elif comp_branch_switch3=='inception_block_b': comp_layer3 = block_inception_b(comp_layer2, filters_1x1=32, filters_5x5_reduce=32, filters_5x5=128, filters_7x7_reduce=32, filters_1x7=128, filters_7x1=128, filters_pool_proj=32, layer_name='comp_layer3') else: comp_layer3=simple_block(comp_layer2,128,3,3,'comp_layer3') comp_layer3 = MaxPooling2D(pool_size=(2, 2), padding='same',name='comp_layer3_pool')(comp_layer3) # layer4 if comp_add_attention: h_t = Lambda(tf.reshape,output_shape=[25*8,320,], arguments={'shape': [-1, 25*8, 320]}, name='comp_convert_to_timestep')(comp_layer3)#@@@@@@@@@128 # h_t = Bidirectional(LSTM(100, return_sequences=True),input_shape=(25*8,128))(h_t) #batch*tmiestep*100 comp_layer_tran_result = attention_3d_block(h_t,1024,'comp_')#batch*1024 else: comp_layer_tran_result = Flatten(name='comp_layer4_flatten')(comp_layer3) comp_layer_tran_result = Dense(640, activation='relu', name='comp_layer5_den')(comp_layer_tran_result) # layer5 # comp_layer_tran_result = Dense(256, activation='relu', name='comp_layer4_den')(comp_layer_tran_result) comp_layer_tran_result = Dropout(alpha, name='comp_drop1')(comp_layer_tran_result) with tf.device('/gpu:2'): pro_com = keras.layers.concatenate([pro_layer_tran_result, comp_layer_tran_result]) # We stack a deep densely-connected network on top fc_pro_com = Dense(512, activation='relu', name='den1')(pro_com) fc_pro_com = Dropout(alpha, name='drop1')(fc_pro_com) dense1 = [] FC1 = Dense(64, activation='relu') for p in np.linspace(0.1,0.5, 5): x = Dropout(p)(fc_pro_com) x = FC1(x) x = Dense(1)(x) dense1.append(x) class_out = Average()(dense1) regression_model = Model([protein_input, comp_input],class_out) plot_model(classification_model, to_file=save_dir + '/model_with_regression.png', show_shapes=True) return regression_model def get_model_multi(save_dir,alpha, pro_branch_switch1='',pro_branch_switch2='', pro_branch_switch3='',pro_add_attention=False, comp_branch_switch1='',comp_branch_switch2='', comp_branch_switch3='',comp_add_attention=False, ): ###MODEL ##input protein_input = Input(shape=(1200, 20, 1), name='protein_input') comp_input = Input(shape=(200, 67, 1), name='comp_input') with tf.device('/gpu:0'): ##protein branch # layer1 if pro_branch_switch1 == 'inception_block': pro_layer1 = block_inception(protein_input, filters_1x1=8, filters_3x3_reduce=1, filters_3x3=32, filters_5x5_reduce=1, filters_5x5=32, filters_pool_proj=16,layer_name='pro_layer1') else: pro_layer1 = simple_block(protein_input, nb_filter=32, num_row=3, num_col=3, layer_name='pro_layer1') pro_layer1 = MaxPooling2D(pool_size=(3, 3),padding='same', name='pro_layer1_poll')(pro_layer1) # layer2 if pro_branch_switch2=='inception_block': pro_layer2 = block_inception(pro_layer1, filters_1x1=16, filters_3x3_reduce=16, filters_3x3=64, filters_5x5_reduce=16, filters_5x5=64, filters_pool_proj=32,layer_name='pro_layer2') else: pro_layer2=simple_block(pro_layer1,nb_filter=64,num_row=3,num_col=3,layer_name='pro_layer2') pro_layer2 = MaxPooling2D(pool_size=(3, 3), padding='same',name='pro_layer2_poll')(pro_layer2) # layer3 if pro_branch_switch3=='inception_block': pro_layer3 = block_inception(pro_layer2, filters_1x1=32, filters_3x3_reduce=64, filters_3x3=128, filters_5x5_reduce=64, filters_5x5=128, filters_pool_proj=64,layer_name='pro_layer3') elif pro_branch_switch3=='inception_block_b': pro_layer3 = block_inception_b(pro_layer2, filters_1x1=32, filters_5x5_reduce=64, filters_5x5=128, filters_7x7_reduce=64, filters_1x7=128,filters_7x1=128, filters_pool_proj=64,layer_name='pro_layer3') else: pro_layer3 = simple_block(pro_layer2, nb_filter=128, num_row=3, num_col=3, layer_name='pro_layer3') pro_layer3 = MaxPooling2D(pool_size=(3, 3), padding='same',name='pro_layer3_pool')(pro_layer3) # layer4 if pro_add_attention: h_t = Lambda(tf.reshape,output_shape=[45,352,], arguments={'shape': [-1, 45, 352]}, name='pro_convert_to_timestep')(pro_layer3) pro_layer_tran_result = attention_3d_block(h_t,1024,'pro_')#batch*1024 else: pro_layer_tran_result = Flatten(name='pro_layer4_flatten')(pro_layer3) pro_layer_tran_result = Dense(1024, activation='relu', name='pro_layer5_den')(pro_layer_tran_result) pro_layer_tran_result = Dropout(alpha, name='pro_drop1')(pro_layer_tran_result) with tf.device('/gpu:1'): ##compound branch # layer1 if comp_branch_switch1=='inception_block': comp_layer1 = block_inception(comp_input, filters_1x1=8, filters_3x3_reduce=1, filters_3x3=16, filters_5x5_reduce=1, filters_5x5=16, filters_pool_proj=16, layer_name='comp_layer1') else: comp_layer1 = simple_block(comp_input, 32, 3, 3, 'comp_layer1') comp_layer1 = MaxPooling2D(pool_size=(2, 2),padding='same', name='comp_layer1_poll')(comp_layer1) # layer2 if comp_branch_switch2=='inception_block': comp_layer2 = block_inception(comp_layer1, filters_1x1=16, filters_3x3_reduce=16, filters_3x3=64, filters_5x5_reduce=16, filters_5x5=64, filters_pool_proj=32,layer_name='comp_layer2') else: comp_layer2=simple_block(comp_layer1,64,3,3,'comp_layer2') comp_layer2 = MaxPooling2D(pool_size=(2, 2), padding='same',name='comp_layer2_poll')(comp_layer2) # layer3 if comp_branch_switch3=='inception_block': comp_layer3 = block_inception(comp_layer2, filters_1x1=32, filters_3x3_reduce=32, filters_3x3=128, filters_5x5_reduce=32, filters_5x5=128, filters_pool_proj=32,layer_name='comp_layer3') elif comp_branch_switch3=='inception_block_b': comp_layer3 = block_inception_b(comp_layer2, filters_1x1=32, filters_5x5_reduce=32, filters_5x5=128, filters_7x7_reduce=32, filters_1x7=128, filters_7x1=128, filters_pool_proj=32, layer_name='comp_layer3') else: comp_layer3=simple_block(comp_layer2,128,3,3,'comp_layer3') comp_layer3 = MaxPooling2D(pool_size=(2, 2), padding='same',name='comp_layer3_pool')(comp_layer3) # layer4 if comp_add_attention: h_t = Lambda(tf.reshape,output_shape=[25*8,320,], arguments={'shape': [-1, 25*8, 320]}, name='comp_convert_to_timestep')(comp_layer3) comp_layer_tran_result = attention_3d_block(h_t,1024,'comp_')#batch*1024 else: comp_layer_tran_result = Flatten(name='comp_layer4_flatten')(comp_layer3) comp_layer_tran_result = Dense(640, activation='relu', name='comp_layer5_den')(comp_layer_tran_result) # layer5 comp_layer_tran_result = Dropout(alpha, name='comp_drop1')(comp_layer_tran_result) with tf.device('/gpu:2'): pro_com = keras.layers.concatenate([pro_layer_tran_result, comp_layer_tran_result]) # We stack a deep densely-connected network on top fc_pro_com = Dense(512, activation='relu', name='den1')(pro_com) fc_pro_com = Dropout(alpha, name='drop1')(fc_pro_com) # classification task dense1 = [] FC1 = Dense(64, activation='relu') for p in np.linspace(0.1,0.5, 5): x = Dropout(p)(fc_pro_com) x = FC1(x) x = Dense(1,activation='sigmoid')(x) dense1.append(x) class_out = Average()(dense1) # regression task dense2 = [] FC2 = Dense(64, activation='relu') for p in np.linspace(0.1,0.5, 5): x = Dropout(p)(fc_pro_com) x = FC2(x) x = Dense(1)(x) dense2.append(x) regree_out = Average()(dense2) class_model = Model(inputs=[protein_input, comp_input], outputs=class_out) reg_model = Model(inputs=[protein_input, comp_input], outputs=regree_out) plot_model(class_model, to_file=save_dir + "/multitask_training_respectively_class.png") plot_model(reg_model, to_file=save_dir + "/multitask_training_respectively_reg.png") return class_model, reg_model

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fdd0e35328955d65772be9b2c0f8cc995918a85f

47,152

py

Python

47/swagger_client/api/wordnet_similarity_controller_api.py

apitore/apitore-sdk-python

c0814c5635ddd09e9a20fcb155b62122bee41d33

[ "Apache-2.0" ]

3

2018-08-21T06:14:33.000Z

2019-10-18T23:05:50.000Z

47/swagger_client/api/wordnet_similarity_controller_api.py

apitore/apitore-sdk-python

c0814c5635ddd09e9a20fcb155b62122bee41d33

[ "Apache-2.0" ]

null

47/swagger_client/api/wordnet_similarity_controller_api.py

apitore/apitore-sdk-python

c0814c5635ddd09e9a20fcb155b62122bee41d33

[ "Apache-2.0" ]

null

# coding: utf-8 """ WordNet Similarity APIs Calculate word similarity.<BR />[Endpoint] https://api.apitore.com/api/47 # noqa: E501 OpenAPI spec version: 0.0.1 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from swagger_client.api_client import ApiClient class WordnetSimilarityControllerApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def hirststonge_using_get(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/hirststonge', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def hirststonge_using_get1(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get1(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get1_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get1_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get1_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get1_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get1" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get1`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get1`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get1`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/jiangconrath', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def hirststonge_using_get2(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get2(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get2_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get2_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get2_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get2_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get2" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get2`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get2`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get2`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/leacockchodorow', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def hirststonge_using_get3(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get3(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get3_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get3_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get3_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get3_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get3" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get3`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get3`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get3`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/lesk', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def hirststonge_using_get4(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get4(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get4_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get4_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get4_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get4_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get4" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get4`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get4`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get4`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/lin', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def hirststonge_using_get5(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get5(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get5_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get5_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get5_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get5_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get5" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get5`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get5`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get5`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/path', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def hirststonge_using_get6(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get6(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get6_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get6_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get6_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get6_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get6" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get6`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get6`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get6`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/resnik', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def hirststonge_using_get7(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get7(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.hirststonge_using_get7_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 else: (data) = self.hirststonge_using_get7_with_http_info(access_token, word1, word2, **kwargs) # noqa: E501 return data def hirststonge_using_get7_with_http_info(self, access_token, word1, word2, **kwargs): # noqa: E501 """WordNet Similarity WebAPI. # noqa: E501 WordNet similarity.<BR />Response<BR />  Github: <a href=\"https://github.com/keigohtr/apitore-response-parent/tree/master/wordnet-response\">wordnet-response</a><BR /> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.hirststonge_using_get7_with_http_info(access_token, word1, word2, async=True) >>> result = thread.get() :param async bool :param str access_token: Access Token (required) :param str word1: Word1 (required) :param str word2: Word2 (required) :param str pos1: Part-of-speech1. [n:noun,v:verb,a:adjective,r:adverb] :param str pos2: Part-of-speech2. [n:noun,v:verb,a:adjective,r:adverb] :return: WordnetSimilarityResponseEntity If the method is called asynchronously, returns the request thread. """ all_params = ['access_token', 'word1', 'word2', 'pos1', 'pos2'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method hirststonge_using_get7" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'access_token' is set if ('access_token' not in params or params['access_token'] is None): raise ValueError("Missing the required parameter `access_token` when calling `hirststonge_using_get7`") # noqa: E501 # verify the required parameter 'word1' is set if ('word1' not in params or params['word1'] is None): raise ValueError("Missing the required parameter `word1` when calling `hirststonge_using_get7`") # noqa: E501 # verify the required parameter 'word2' is set if ('word2' not in params or params['word2'] is None): raise ValueError("Missing the required parameter `word2` when calling `hirststonge_using_get7`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'access_token' in params: query_params.append(('access_token', params['access_token'])) # noqa: E501 if 'word1' in params: query_params.append(('word1', params['word1'])) # noqa: E501 if 'pos1' in params: query_params.append(('pos1', params['pos1'])) # noqa: E501 if 'word2' in params: query_params.append(('word2', params['word2'])) # noqa: E501 if 'pos2' in params: query_params.append(('pos2', params['pos2'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/wordnet-similarity/wupalmer', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WordnetSimilarityResponseEntity', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

46.272816

195

0.621861

5,500

47,152

5.153818

0.033818

0.049954

0.031609

0.041487

0.978233

0.97714

0.973365

0

0.029853

0.269702

47,152

1,018

196

46.318271

0.793321

0.071174

0

0.83906

1

0

0.216841

0.064044

0

null

0

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null

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null

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1

0

null

0

1

0

9

fde8789b955bc5a6cc82428718cf49d05e74f49e

8,900

py

Python

worker/HaiNanCrawler.py

xfrzrcj/SCCrawler

cbb6163f73f6a47eccffec481ff2fdf869ba5eb2

[ "MIT" ]

1

2021-05-18T00:46:30.000Z

worker/HaiNanCrawler.py

xfrzrcj/SCCrawler

cbb6163f73f6a47eccffec481ff2fdf869ba5eb2

[ "MIT" ]

null

worker/HaiNanCrawler.py

xfrzrcj/SCCrawler

cbb6163f73f6a47eccffec481ff2fdf869ba5eb2

[ "MIT" ]

null

from worker import Crawler import pymysql from selenium import webdriver import time import re baseUrl = "http://www.hnlzw.net" indexUrl = "http://www.hnlzw.net/jlsc_sggb.php" djcf_sggbUrl = "http://www.hnlzw.net/djcf_sggb.php" jlsc_sxgbUrl = "http://www.hnlzw.net/jlsc_sxgb.php" djcf_sxgbUrl = "http://www.hnlzw.net/djcf_sxgb.php" browser = webdriver.Chrome("d:/chromedriver.exe") class HN_jlsc_sggb_Crawler(Crawler.CrawlerInterface): def get_num(self): soup = self.get_soup(indexUrl) a = soup.find("a", text="末页").get("href") pages = a.replace('/jlsc_sggb.php?ncount=8&nbegin=', "") return int(pages)//8+1 def get_index(self): return indexUrl def join_url(self, i): url = baseUrl+"/jlsc_sggb.php?ncount=8&nbegin="+str(i*8) return url def get_urls(self, url): soup = self.get_soup(url) lists = soup.find("div", id="mainrconlist") tags = lists.find_all("li") urls = [] for tag in tags: ss = tag.find("a").get("href") if ss.startswith("http"): urls.append(tag.find("a").get("href")) else: urls.append(baseUrl + "/" + tag.find("a").get("href")) return urls def get_info(self, url): if url == "http://www.hnlzw.net/page.php?xuh=44175" or url == \ "http://www.hnlzw.net/page.php?xuh=39496": return None info_result = Crawler.Info() info_result.url = url soup = self.get_soup(url) title = soup.find("div", id="arttitl") info_result.title = title.text time_source = soup.find("div", id="artdes").text ts = time_source.split(" ") info_result.time = ts[0] info_result.source = ts[1] article = soup.find("div", id="artcon") ps = article.find_all("p") text = "" for p in ps: text = text + p.text + "\n" self.get_resum_description_from_text(text, info_result) return info_result def process_info(self, info): info.province = "海南" info.source = info.source.replace("来源：", "") info.time = info.time.replace("发布时间：", "") info.postion = "审查调查(省一级党和国家机关、国企干部)" return info class HN_djcf_sggb_Crawler(Crawler.CrawlerInterface): def get_num(self): soup = self.get_soup(djcf_sggbUrl) a = soup.find("a", text="末页").get("href") pages = a.replace('/djcf_sggb.php?ncount=8&nbegin=', "") return int(pages)//8+1 def get_index(self): return djcf_sggbUrl def join_url(self, i): url = baseUrl+"/djcf_sggb.php?ncount=8&nbegin="+str(i*8) return url def get_urls(self, url): soup = self.get_soup(url) lists = soup.find("div", id="mainrconlist") tags = lists.find_all("li") urls = [] for tag in tags: ss = tag.find("a").get("href") if ss.startswith("http"): urls.append(tag.find("a").get("href")) else: urls.append(baseUrl + "/" + tag.find("a").get("href")) return urls def get_info(self, url): info_result = Crawler.Info() info_result.url = url browser.get(url) time.sleep(0.5) title = browser.find_element_by_id("arttitl").text info_result.title = title time_source = browser.find_element_by_id("artdes").text tt = re.findall("\d{4}-\d{2}-\d{2}\s+\d{2}:\d{2}:\d{2}", time_source) if len(tt) != 0: info_result.time = tt[0] source = re.findall("来源：.*?作者", time_source) if len(source) == 0: source = re.findall("来源：.*?编辑", time_source) if len(source) > 0: info_result.source = source[0] article = browser.find_element_by_id("artcon") ps = article.find_elements_by_tag_name("p") text = "" for p in ps: text = text + p.text + "\n" self.get_resum_description_from_text(text, info_result) return info_result def process_info(self, info): info.province = "海南" info.source = info.source.replace("来源：", "").replace("作者", "").replace("编辑", "") info.time = info.time.replace("发布时间：", "") info.postion = "纪律处分(省一级党和国家机关、国企干部)" return info class HN_jlsc_sxgb_Crawler(Crawler.CrawlerInterface): def get_num(self): soup = self.get_soup(jlsc_sxgbUrl) a = soup.find("a", text="末页").get("href") pages = a.replace('/jlsc_sxgb.php?ncount=8&nbegin=', "") return int(pages)//8+1 def get_index(self): return indexUrl def join_url(self, i): url = baseUrl+"/jlsc_sxgb.php?ncount=8&nbegin="+str(i*8) return url def get_urls(self, url): soup = self.get_soup(url) lists = soup.find("div", id="mainrconlist") tags = lists.find_all("li") urls = [] for tag in tags: ss = tag.find("a").get("href") if ss.startswith("http"): urls.append(tag.find("a").get("href")) else: urls.append(baseUrl + "/" + tag.find("a").get("href")) return urls def get_info(self, url): info_result = Crawler.Info() info_result.url = url browser.get(url) time.sleep(0.5) title = browser.find_element_by_id("arttitl").text info_result.title = title time_source = browser.find_element_by_id("artdes").text tt = re.findall("\d{4}-\d{2}-\d{2}\s+\d{2}:\d{2}:\d{2}", time_source) if len(tt) != 0: info_result.time = tt[0] source = re.findall("来源：.*?作者", time_source) if len(source) == 0: source = re.findall("来源：.*?编辑", time_source) if len(source) > 0: info_result.source = source[0] article = browser.find_element_by_id("artcon") ps = article.find_elements_by_tag_name("p") text = "" for p in ps: text = text + p.text + "\n" self.get_resum_description_from_text(text, info_result) return info_result def process_info(self, info): info.province = "海南" info.source = info.source.replace("来源：", "").replace("作者", "").replace("编辑", "") info.time = info.time.replace("发布时间：", "") info.postion = "审查调查(市县干部)" return info class HN_djcf_sxgb_Crawler(Crawler.CrawlerInterface): def get_num(self): soup = self.get_soup(djcf_sxgbUrl) a = soup.find("a", text="末页").get("href") pages = a.replace('/djcf_sxgb.php?ncount=8&nbegin=', "") return int(pages)//8+1 def get_index(self): return indexUrl def join_url(self, i): url = baseUrl+"/djcf_sxgb.php?ncount=8&nbegin="+str(i*8) return url def get_urls(self, url): soup = self.get_soup(url) lists = soup.find("div", id="mainrconlist") tags = lists.find_all("li") urls = [] for tag in tags: ss = tag.find("a").get("href") if ss.startswith("http"): urls.append(tag.find("a").get("href")) else: urls.append(baseUrl + "/" + tag.find("a").get("href")) return urls def get_info(self, url): info_result = Crawler.Info() info_result.url = url browser.get(url) time.sleep(0.5) title = browser.find_element_by_id("arttitl").text info_result.title = title time_source = browser.find_element_by_id("artdes").text tt = re.findall("\d{4}-\d{2}-\d{2}\s+\d{2}:\d{2}:\d{2}", time_source) if len(tt) != 0: info_result.time = tt[0] source = re.findall("来源：.*?作者", time_source) if len(source) == 0: source = re.findall("来源：.*?编辑", time_source) if len(source) > 0: info_result.source = source[0] article = browser.find_element_by_id("artcon") ps = article.find_elements_by_tag_name("p") text = "" for p in ps: text = text + p.text + "\n" self.get_resum_description_from_text(text, info_result) return info_result def process_info(self, info): info.province = "海南" info.source = info.source.replace("来源：", "").replace("作者", "").replace("编辑", "") info.time = info.time.replace("发布时间：", "") info.postion = "纪律处分(市县干部)" return info c = HN_djcf_sxgb_Crawler() conns = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='123456', db='data', charset='utf8') c.start(conns) conns.close() browser.quit() # print(c.get_num()) # print(c.join_url(1)) # print(c.get_urls("http://www.hnlzw.net/jlsc_sggb.php?ncount=8&nbegin=8")) # c.get_info("http://www.hnlzw.net/page.php?xuh=45930")

33.584906

109

0.560337

1,213

8,900

3.967848

0.112119

0.058176

0.019946

0.027426

0.873468

0.849159

0.830251

0.814253

0.788074

0.778517

0

0.014944

0.278202

8,900

264

110

33.712121

0.734278

0.018764

0

0.78125

0

0.013393

0.123052

0.041132

0

1

0.107143

false

0.004464

0.022321

0.017857

0.258929

0

null

0

1

0

1

0

null

0

7

e31a4de4931a56e3eaf32b8673c48b765163782a

14,967

py

Python

src/meterpreter_traffic_parser/enums/tlv_type.py

SpartaEN/meterpreter-traffic-parser

5681c3973ac8fc3bbd478c82fdc27de4ab6c447a

[ "MIT" ]

1

2021-12-22T15:14:54.000Z

src/meterpreter_traffic_parser/enums/tlv_type.py

SpartaEN/meterpreter-traffic-parser

5681c3973ac8fc3bbd478c82fdc27de4ab6c447a

[ "MIT" ]

null

src/meterpreter_traffic_parser/enums/tlv_type.py

SpartaEN/meterpreter-traffic-parser

5681c3973ac8fc3bbd478c82fdc27de4ab6c447a

[ "MIT" ]

null

from enum import Enum from ..exceptions import UnknowType class TLVType(Enum): # Base # Represents an undefined/arbitrary value. TLV_TYPE_ANY = 0 # Represents a command identifier. TLV_TYPE_COMMAND_ID = 1 # Represents a request identifier value. TLV_TYPE_REQUEST_ID = 2 # Represents an exception value. TLV_TYPE_EXCEPTION = 3 # Represents a result value. TLV_TYPE_RESULT = 4 # Argument basic types # Represents a string value. TLV_TYPE_STRING = 10 # Represents an unsigned integer value. TLV_TYPE_UINT = 11 # Represents a boolean value. TLV_TYPE_BOOL = 12 # Extended types # Represents a length (unsigned integer). TLV_TYPE_LENGTH = 25 # Represents arbitrary data (raw). TLV_TYPE_DATA = 26 # Represents a set of flags (unsigned integer). TLV_TYPE_FLAGS = 27 # Channel types # Represents a channel identifier (unsigned integer). TLV_TYPE_CHANNEL_ID = 50 # Represents a channel type (string). TLV_TYPE_CHANNEL_TYPE = 51 # Represents channel data (raw). TLV_TYPE_CHANNEL_DATA = 52 # Represents a channel data group (group). TLV_TYPE_CHANNEL_DATA_GROUP = 53 # Represents a channel class (unsigned integer). TLV_TYPE_CHANNEL_CLASS = 54 # Represents a channel parent identifier (unsigned integer). TLV_TYPE_CHANNEL_PARENTID = 55 # Channel extended types TLV_TYPE_SEEK_WHENCE = 70 TLV_TYPE_SEEK_OFFSET = 71 TLV_TYPE_SEEK_POS = 72 # Grouped identifiers # Represents an exception code value (unsigned in). TLV_TYPE_EXCEPTION_CODE = 300 # Represents an exception message value (string). TLV_TYPE_EXCEPTION_STRING = 301 # Library loading # Represents a path to the library to be loaded (string). TLV_TYPE_LIBRARY_PATH = 400 # Represents a target path (string). TLV_TYPE_TARGET_PATH = 401 # Represents a process identifier of the migration target (unsigned integer). TLV_TYPE_MIGRATE_PID = 402 # Represents a migration payload (raw). TLV_TYPE_MIGRATE_PAYLOAD = 404 # Represents a migration target architecture. TLV_TYPE_MIGRATE_ARCH = 405 # Represents a migration technique (unsigned int). TLV_TYPE_MIGRATE_TECHNIQUE = 406 # Represents a migration payload base address (unsigned int). TLV_TYPE_MIGRATE_BASE_ADDR = 407 # Represents a migration payload entry point (unsigned int). TLV_TYPE_MIGRATE_ENTRY_POINT = 408 # Represents a unix domain socket path, used to migrate on linux (string) TLV_TYPE_MIGRATE_SOCKET_PATH = 409 # Represents a migration stub (raw). TLV_TYPE_MIGRATE_STUB = 411 # Represents the name of the ReflectiveLoader function (string). TLV_TYPE_LIB_LOADER_NAME = 412 # Represents the ordinal of the ReflectiveLoader function (int). TLV_TYPE_LIB_LOADER_ORDINAL = 413 # Transport switching # Represents the type of transport to switch to. TLV_TYPE_TRANS_TYPE = 430 # Represents the new URL of the transport to use. TLV_TYPE_TRANS_URL = 431 # Represents the user agent (for http). TLV_TYPE_TRANS_UA = 432 # Represents the communications timeout. TLV_TYPE_TRANS_COMM_TIMEOUT = 433 # Represents the session expiration. TLV_TYPE_TRANS_SESSION_EXP = 434 # Represents the certificate hash (for https). TLV_TYPE_TRANS_CERT_HASH = 435 # Represents the proxy host string (for http/s). TLV_TYPE_TRANS_PROXY_HOST = 436 # Represents the proxy user name (for http/s). TLV_TYPE_TRANS_PROXY_USER = 437 # Represents the proxy password (for http/s). TLV_TYPE_TRANS_PROXY_PASS = 438 # Total time (seconds) to continue retrying comms. TLV_TYPE_TRANS_RETRY_TOTAL = 439 # Time (seconds) to wait between reconnect attempts. TLV_TYPE_TRANS_RETRY_WAIT = 440 # List of custom headers to send with the requests. TLV_TYPE_TRANS_HEADERS = 441 # A single transport grouping. TLV_TYPE_TRANS_GROUP = 442 # session/machine identification # Represents a machine identifier. TLV_TYPE_MACHINE_ID = 460 # Represents a UUID. TLV_TYPE_UUID = 461 # Represents a Session GUID. TLV_TYPE_SESSION_GUID = 462 # Packet encryption # Represents DER-encoded RSA public key TLV_TYPE_RSA_PUB_KEY = 550 # Represents the type of symmetric key TLV_TYPE_SYM_KEY_TYPE = 551 # Represents the symmetric key TLV_TYPE_SYM_KEY = 552 # Represents and RSA-encrypted symmetric key TLV_TYPE_ENC_SYM_KEY = 553 # Pivots # Represents the id of the pivot listener TLV_TYPE_PIVOT_ID = 650 # Represents the data to be staged on new connections. TLV_TYPE_PIVOT_STAGE_DATA = 651 # Represents named pipe name. TLV_TYPE_PIVOT_NAMED_PIPE_NAME = 653 # Represents an extension value. TLV_TYPE_EXTENSIONS = 20000 # Represents a user value. TLV_TYPE_USER = 40000 # Represents a temporary value. TLV_TYPE_TEMP = 60000 @staticmethod def get_by_value(value): for packet_type in TLVType: if packet_type.value == value: return packet_type.name raise UnknowType(f"Unknow packet type, got {value}") # Not working on some versions :( # class TLVType(Enum): # # Base # # Represents an undefined/arbitrary value. # TLV_TYPE_ANY = get_tlv_value( # PacketMetaType.TLV_META_TYPE_NONE.value, 0) # # Represents a command identifier. # TLV_TYPE_COMMAND_ID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 1) # # Represents a request identifier value. # TLV_TYPE_REQUEST_ID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 2) # # Represents an exception value. # TLV_TYPE_EXCEPTION = get_tlv_value( # PacketMetaType.TLV_META_TYPE_GROUP.value, 3) # # Represents a result value. # TLV_TYPE_RESULT = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 4) # # Argument basic types # # Represents a string value. # TLV_TYPE_STRING = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 10) # # Represents an unsigned integer value. # TLV_TYPE_UINT = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 11) # # Represents a boolean value. # TLV_TYPE_BOOL = get_tlv_value( # PacketMetaType.TLV_META_TYPE_BOOL.value, 12) # # Extended types # # Represents a length (unsigned integer). # TLV_TYPE_LENGTH = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 25) # # Represents arbitrary data (raw). # TLV_TYPE_DATA = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 26) # # Represents a set of flags (unsigned integer). # TLV_TYPE_FLAGS = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 27) # # Channel types # # Represents a channel identifier (unsigned integer). # TLV_TYPE_CHANNEL_ID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 50) # # Represents a channel type (string). # TLV_TYPE_CHANNEL_TYPE = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 51) # # Represents channel data (raw). # TLV_TYPE_CHANNEL_DATA = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 52) # # Represents a channel data group (group). # TLV_TYPE_CHANNEL_DATA_GROUP = get_tlv_value( # PacketMetaType.TLV_META_TYPE_GROUP.value, 53) # # Represents a channel class (unsigned integer). # TLV_TYPE_CHANNEL_CLASS = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 54) # # Represents a channel parent identifier (unsigned integer). # TLV_TYPE_CHANNEL_PARENTID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 55) # # Channel extended types # TLV_TYPE_SEEK_WHENCE = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 70) # TLV_TYPE_SEEK_OFFSET = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 71) # TLV_TYPE_SEEK_POS = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 72) # # Grouped identifiers # # Represents an exception code value (unsigned in). # TLV_TYPE_EXCEPTION_CODE = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 300) # # Represents an exception message value (string). # TLV_TYPE_EXCEPTION_STRING = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 301) # # Library loading # # Represents a path to the library to be loaded (string). # TLV_TYPE_LIBRARY_PATH = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 400) # # Represents a target path (string). # TLV_TYPE_TARGET_PATH = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 401) # # Represents a process identifier of the migration target (unsigned integer). # TLV_TYPE_MIGRATE_PID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 402) # # Represents a migration payload (raw). # TLV_TYPE_MIGRATE_PAYLOAD = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 404) # # Represents a migration target architecture. # TLV_TYPE_MIGRATE_ARCH = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 405) # # Represents a migration technique (unsigned int). # TLV_TYPE_MIGRATE_TECHNIQUE = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 406) # # Represents a migration payload base address (unsigned int). # TLV_TYPE_MIGRATE_BASE_ADDR = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 407) # # Represents a migration payload entry point (unsigned int). # TLV_TYPE_MIGRATE_ENTRY_POINT = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 408) # # Represents a unix domain socket path, used to migrate on linux (string) # TLV_TYPE_MIGRATE_SOCKET_PATH = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 409) # # Represents a migration stub (raw). # TLV_TYPE_MIGRATE_STUB = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 411) # # Represents the name of the ReflectiveLoader function (string). # TLV_TYPE_LIB_LOADER_NAME = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 412) # # Represents the ordinal of the ReflectiveLoader function (int). # TLV_TYPE_LIB_LOADER_ORDINAL = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 413) # # Transport switching # # Represents the type of transport to switch to. # TLV_TYPE_TRANS_TYPE = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 430) # # Represents the new URL of the transport to use. # TLV_TYPE_TRANS_URL = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 431) # # Represents the user agent (for http). # TLV_TYPE_TRANS_UA = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 432) # # Represents the communications timeout. # TLV_TYPE_TRANS_COMM_TIMEOUT = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 433) # # Represents the session expiration. # TLV_TYPE_TRANS_SESSION_EXP = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 434) # # Represents the certificate hash (for https). # TLV_TYPE_TRANS_CERT_HASH = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 435) # # Represents the proxy host string (for http/s). # TLV_TYPE_TRANS_PROXY_HOST = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 436) # # Represents the proxy user name (for http/s). # TLV_TYPE_TRANS_PROXY_USER = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 437) # # Represents the proxy password (for http/s). # TLV_TYPE_TRANS_PROXY_PASS = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 438) # # Total time (seconds) to continue retrying comms. # TLV_TYPE_TRANS_RETRY_TOTAL = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 439) # # Time (seconds) to wait between reconnect attempts. # TLV_TYPE_TRANS_RETRY_WAIT = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 440) # # List of custom headers to send with the requests. # TLV_TYPE_TRANS_HEADERS = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 441) # # A single transport grouping. # TLV_TYPE_TRANS_GROUP = get_tlv_value( # PacketMetaType.TLV_META_TYPE_GROUP.value, 442) # # session/machine identification # # Represents a machine identifier. # TLV_TYPE_MACHINE_ID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 460) # # Represents a UUID. # TLV_TYPE_UUID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 461) # # Represents a Session GUID. # TLV_TYPE_SESSION_GUID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 462) # # Packet encryption # # Represents DER-encoded RSA public key # TLV_TYPE_RSA_PUB_KEY = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 550) # # Represents the type of symmetric key # TLV_TYPE_SYM_KEY_TYPE = get_tlv_value( # PacketMetaType.TLV_META_TYPE_UINT.value, 551) # # Represents the symmetric key # TLV_TYPE_SYM_KEY = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 552) # # Represents and RSA-encrypted symmetric key # TLV_TYPE_ENC_SYM_KEY = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 553) # # Pivots # # Represents the id of the pivot listener # TLV_TYPE_PIVOT_ID = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 650) # # Represents the data to be staged on new connections. # TLV_TYPE_PIVOT_STAGE_DATA = get_tlv_value( # PacketMetaType.TLV_META_TYPE_RAW.value, 651) # # Represents named pipe name. # TLV_TYPE_PIVOT_NAMED_PIPE_NAME = get_tlv_value( # PacketMetaType.TLV_META_TYPE_STRING.value, 653) # # Represents an extension value. # TLV_TYPE_EXTENSIONS = get_tlv_value( # PacketMetaType.TLV_META_TYPE_COMPLEX.value, 20000) # # Represents a user value. # TLV_TYPE_USER = get_tlv_value( # PacketMetaType.TLV_META_TYPE_COMPLEX.value, 40000) # # Represents a temporary value. # TLV_TYPE_TEMP = get_tlv_value( # PacketMetaType.TLV_META_TYPE_COMPLEX.value, 60000) # @staticmethod # def get_by_value(value): # for packet_type in TLVType: # if packet_type.value == value: # return packet_type.name # raise UnknowType(f"Unknow packet type, got {value}")

41.345304

83

0.697535

1,955

14,967

4.990281

0.122251

0.086101

0.067651

0.153752

0.990775

0.9836

0.970275

0.905904

0.681427

0

0.028073

0.233647

14,967

361

84

41.459834

0.822493

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0

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false

0.014493

0.028986

0

0.942029

0

null

0

1

0

null

0

1

0

7

e37a55ccb07a05c843d24ea7d41d7fde3c6ca824

500

py

Python

eval_medseg_timm-regnetx_002_Emboss.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

eval_medseg_timm-regnetx_002_Emboss.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

eval_medseg_timm-regnetx_002_Emboss.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

import os ls=["python main.py --configs configs/eval_medseg_unetplusplus_timm-regnetx_002_0_Emboss.yml", "python main.py --configs configs/eval_medseg_unetplusplus_timm-regnetx_002_1_Emboss.yml", "python main.py --configs configs/eval_medseg_unetplusplus_timm-regnetx_002_2_Emboss.yml", "python main.py --configs configs/eval_medseg_unetplusplus_timm-regnetx_002_3_Emboss.yml", "python main.py --configs configs/eval_medseg_unetplusplus_timm-regnetx_002_4_Emboss.yml", ] for l in ls: os.system(l)

45.454545

94

0.834

80

500

4.8375

0.3

0.129199

0.155039

0.245478

0.894057

0

0.042644

0.062

500

11

95

45.454545

0.782516

0

0.868263

0.618762

0

1

0

false

0

0.111111

0

0.111111

0

null

0

1

0

1

null

0

9

e37cc8bfa606ab7201d6e330ec5b02b888bcc3a1

54

py

Python

tests/test_key_point_extraction.py

fitternaveen15/key_point_extraction

f2af4dfa86fe5336556f2294109f74321ae41555

[ "MIT" ]

null

tests/test_key_point_extraction.py

fitternaveen15/key_point_extraction

f2af4dfa86fe5336556f2294109f74321ae41555

[ "MIT" ]

null

tests/test_key_point_extraction.py

fitternaveen15/key_point_extraction

f2af4dfa86fe5336556f2294109f74321ae41555

[ "MIT" ]

null

from key_point_extraction import key_point_extraction

27

53

0.925926

8

54

5.75

0.625

0.347826

0.782609

0

0.074074

54

1

54

0.92

0

1

0

true

0

1

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1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

479aa116fdef14fec4b5622028331183e16b0017

10,734

py

Python

performance_test.py

andrew732/EAS499

a0b1435913a11a999cc83df475eb875d45e51ce1

[ "MIT" ]

1

2020-06-04T00:07:42.000Z

performance_test.py

andrew732/EAS499

a0b1435913a11a999cc83df475eb875d45e51ce1

[ "MIT" ]

null

performance_test.py

andrew732/EAS499

a0b1435913a11a999cc83df475eb875d45e51ce1

[ "MIT" ]

null

import poker_bot import time import numpy as np import random import itertools # runtime of preflop_action def test_preflop(): positions = ["bb", "sb", "btn", "co", "hj", "lj", "utg2", "utg1", "utg"] numbers = ['A', 'K', 'Q', 'J', 'T', '9', '8', '7', '6', '5', '4', '3', '2'] bets = [2, 6, 20] no_limpers = 2 times = [] for last_bet in bets: three_bet = last_bet == 20 for position in positions: for i in range(len(numbers)): for j in range(i, len(numbers)): cards = numbers[i]+numbers[j] if i == j: hand = cards start = time.time() poker_bot.preflop_action(hand, position, last_bet, no_limpers, three_bet=three_bet) length = time.time()-start times.append(length) else: hand = cards+'o' start = time.time() poker_bot.preflop_action(hand, position, last_bet, no_limpers, three_bet=three_bet) length = time.time() - start times.append(length) hand = cards+'s' start = time.time() poker_bot.preflop_action(hand, position, last_bet, no_limpers, three_bet=three_bet) length = time.time() - start times.append(length) print("Number of iterations: "+str(len(times))) print("Average runtime: "+str(np.mean(times))) print("Standard Deviation runtime: "+str(np.std(times))) # runtime of preflop_action def test_betting_round_1(opponents): numbers = ['A', 'K', 'Q', 'J', 'T', '9', '8', '7', '6', '5', '4', '3', '2'] suits = ['h', 'c', 's', 'd'] times = [] pot = 50 bets = [0, 30] types = [2, 3, 4] for bet in bets: for pot_type in types: for i in range(len(numbers)): for j in range(i, len(numbers)): if i == j: for suit1, suit2 in itertools.combinations(suits, 2): cards = numbers[i]+suit1+numbers[j]+suit2 used = {numbers[i]+suit1, numbers[j]+suit2} for i in range(10): board_cards = "" while len(board_cards) < 6: candidate_number = random.randint(0, 12) candidate_suit = random.randint(0, 3) card = numbers[candidate_number]+suits[candidate_suit] if card not in used: used.add(card) board_cards += card # if len(times) % 1000 == 0: # print(len(times)) start = time.time() poker_bot.betting_round_1(cards, board_cards, opponents, bet, pot, pot_type=pot_type) length = time.time()-start times.append(length) else: for suit1, suit2 in zip(suits, suits): cards = numbers[i]+suit1+numbers[j]+suit2 used = {numbers[i]+suit1, numbers[j]+suit2} for i in range(10): board_cards = "" while len(board_cards) < 6: candidate_number = random.randint(0, 12) candidate_suit = random.randint(0, 3) card = numbers[candidate_number]+suits[candidate_suit] if card not in used: used.add(card) board_cards += card # if len(times) % 1000 == 0: # print(len(times)) start = time.time() poker_bot.betting_round_1(cards, board_cards, opponents, bet, pot, pot_type=pot_type) length = time.time()-start times.append(length) print("Number of iterations: "+str(len(times))) print("Average runtime: "+str(np.mean(times))) print("Standard Deviation runtime: "+str(np.std(times))) # runtime of preflop_action def test_betting_round_2(opponents): numbers = ['A', 'K', 'Q', 'J', 'T', '9', '8', '7', '6', '5', '4', '3', '2'] suits = ['h', 'c', 's', 'd'] times = [] pot = 50 bets = [0, 30] types = [2, 3, 4] for bet in bets: for pot_type in types: for i in range(len(numbers)): for j in range(i, len(numbers)): if i == j: for suit1, suit2 in itertools.combinations(suits, 2): cards = numbers[i]+suit1+numbers[j]+suit2 used = {numbers[i]+suit1, numbers[j]+suit2} for i in range(10): board_cards = "" while len(board_cards) < 8: candidate_number = random.randint(0, 12) candidate_suit = random.randint(0, 3) card = numbers[candidate_number]+suits[candidate_suit] if card not in used: used.add(card) board_cards += card # if len(times) % 1000 == 0: # print(len(times)) start = time.time() poker_bot.betting_round_2(cards, board_cards, opponents, bet, pot, pot_type=pot_type) length = time.time()-start times.append(length) else: for suit1, suit2 in zip(suits, suits): cards = numbers[i]+suit1+numbers[j]+suit2 used = {numbers[i]+suit1, numbers[j]+suit2} for i in range(10): board_cards = "" while len(board_cards) < 8: candidate_number = random.randint(0, 12) candidate_suit = random.randint(0, 3) card = numbers[candidate_number]+suits[candidate_suit] if card not in used: used.add(card) board_cards += card # if len(times) % 1000 == 0: # print(len(times)) start = time.time() poker_bot.betting_round_2(cards, board_cards, opponents, bet, pot, pot_type=pot_type) length = time.time()-start times.append(length) print("Number of iterations: "+str(len(times))) print("Average runtime: "+str(np.mean(times))) print("Standard Deviation runtime: "+str(np.std(times))) # runtime of preflop_action def test_river(opponents): numbers = ['A', 'K', 'Q', 'J', 'T', '9', '8', '7', '6', '5', '4', '3', '2'] suits = ['h', 'c', 's', 'd'] times = [] pot = 50 bets = [0, 30] types = [2, 3, 4] for bet in bets: for pot_type in types: for i in range(len(numbers)): for j in range(i, len(numbers)): if i == j: for suit1, suit2 in itertools.combinations(suits, 2): cards = numbers[i]+suit1+numbers[j]+suit2 used = {numbers[i]+suit1, numbers[j]+suit2} for i in range(10): board_cards = "" while len(board_cards) < 10: candidate_number = random.randint(0, 12) candidate_suit = random.randint(0, 3) card = numbers[candidate_number]+suits[candidate_suit] if card not in used: used.add(card) board_cards += card # if len(times) % 1000 == 0: # print(len(times)) start = time.time() poker_bot.river_action(cards, board_cards, opponents, bet, pot, pot_type=pot_type) length = time.time()-start times.append(length) else: for suit1, suit2 in zip(suits, suits): cards = numbers[i]+suit1+numbers[j]+suit2 used = {numbers[i]+suit1, numbers[j]+suit2} for i in range(10): board_cards = "" while len(board_cards) < 10: candidate_number = random.randint(0, 12) candidate_suit = random.randint(0, 3) card = numbers[candidate_number]+suits[candidate_suit] if card not in used: used.add(card) board_cards += card # if len(times) % 1000 == 0: # print(len(times)) start = time.time() poker_bot.river_action(cards, board_cards, opponents, bet, pot, pot_type=pot_type) length = time.time()-start times.append(length) print("Number of iterations: "+str(len(times))) print("Average runtime: "+str(np.mean(times))) print("Standard Deviation runtime: "+str(np.std(times))) test_preflop() test_betting_round_1(1) test_betting_round_1(2) test_betting_round_2(1) test_betting_round_2(2) test_river(1) test_river(2)

48.570136

117

0.412428

1,054

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0.096774

0.05584

0.036296

0.05584

0.919032

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0.911354

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0.036069

0.483417

10,734

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48.570136

0.739044

0.036985

0

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0

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1

0.021277

false

0

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0

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null

0

1

0

1

0

null

0

7

479f6d026e2b162a76d5ccd86d3f06c3cba275ef

68,568

py

Python

benchmarks/SimResults/combinations_spec_mylocality/cmp_calculixlibquantumzeusmpsjeng/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/combinations_spec_mylocality/cmp_calculixlibquantumzeusmpsjeng/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/combinations_spec_mylocality/cmp_calculixlibquantumzeusmpsjeng/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

power = {'BUSES': {'Area': 1.33155, 'Bus/Area': 1.33155, 'Bus/Gate Leakage': 0.00662954, 'Bus/Peak Dynamic': 0.0, 'Bus/Runtime Dynamic': 0.0, 'Bus/Subthreshold Leakage': 0.0691322, 'Bus/Subthreshold Leakage with power gating': 0.0259246, 'Gate Leakage': 0.00662954, 'Peak Dynamic': 0.0, 'Runtime Dynamic': 0.0, 'Subthreshold Leakage': 0.0691322, 'Subthreshold Leakage with power gating': 0.0259246}, 'Core': [{'Area': 32.6082, 'Execution Unit/Area': 8.2042, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.266951, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.412364, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 1.38304, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.122718, 'Execution Unit/Instruction Scheduler/Area': 2.17927, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.635667, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 1.10075, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.631309, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 2.36772, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.41629, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 8.22407, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788, 'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.261285, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0230434, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968, 'Execution Unit/Register Files/Gate Leakage': 0.000622708, 'Execution Unit/Register Files/Integer RF/Area': 0.362673, 'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.268957, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.17042, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.530242, 'Execution Unit/Register Files/Runtime Dynamic': 0.193464, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.723044, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 1.55743, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155, 'Execution Unit/Runtime Dynamic': 4.93636, 'Execution Unit/Subthreshold Leakage': 1.83518, 'Execution Unit/Subthreshold Leakage with power gating': 0.709678, 'Gate Leakage': 0.372997, 'Instruction Fetch Unit/Area': 5.86007, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00188641, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00188641, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00164681, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000639555, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.0024481, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00786772, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0179528, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0590479, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.163829, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 6.43323, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.402046, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386, 'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799, 'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493, 'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404, 'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.556438, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104, 'Instruction Fetch Unit/Peak Dynamic': 8.96874, 'Instruction Fetch Unit/Runtime Dynamic': 1.14813, 'Instruction Fetch Unit/Subthreshold Leakage': 0.932587, 'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542, 'L2/Area': 4.53318, 'L2/Gate Leakage': 0.015464, 'L2/Peak Dynamic': 0.155315, 'L2/Runtime Dynamic': 0.0314597, 'L2/Subthreshold Leakage': 0.834142, 'L2/Subthreshold Leakage with power gating': 0.401066, 'Load Store Unit/Area': 8.80969, 'Load Store Unit/Data Cache/Area': 6.84535, 'Load Store Unit/Data Cache/Gate Leakage': 0.0279261, 'Load Store Unit/Data Cache/Peak Dynamic': 4.58364, 'Load Store Unit/Data Cache/Runtime Dynamic': 1.68203, 'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675, 'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085, 'Load Store Unit/Gate Leakage': 0.0351387, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.108268, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.108268, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 5.09698, 'Load Store Unit/Runtime Dynamic': 2.32423, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate Leakage': 0.00329971, 'Load Store Unit/StoreQ/Peak Dynamic': 0.26697, 'Load Store Unit/StoreQ/Runtime Dynamic': 0.53394, 'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621, 'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004, 'Load Store Unit/Subthreshold Leakage': 0.591622, 'Load Store Unit/Subthreshold Leakage with power gating': 0.283406, 'Memory Management Unit/Area': 0.434579, 'Memory Management Unit/Dtlb/Area': 0.0879726, 'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729, 'Memory Management Unit/Dtlb/Peak Dynamic': 0.0947485, 'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0970608, 'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699, 'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485, 'Memory Management Unit/Gate Leakage': 0.00813591, 'Memory Management Unit/Itlb/Area': 0.301552, 'Memory Management Unit/Itlb/Gate Leakage': 0.00393464, 'Memory Management Unit/Itlb/Peak Dynamic': 0.399995, 'Memory Management Unit/Itlb/Runtime Dynamic': 0.0659695, 'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758, 'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842, 'Memory Management Unit/Peak Dynamic': 0.722295, 'Memory Management Unit/Runtime Dynamic': 0.16303, 'Memory Management Unit/Subthreshold Leakage': 0.0769113, 'Memory Management Unit/Subthreshold Leakage with power gating': 0.0399462, 'Peak Dynamic': 27.7291, 'Renaming Unit/Area': 0.369768, 'Renaming Unit/FP Front End RAT/Area': 0.168486, 'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731, 'Renaming Unit/FP Front End RAT/Peak Dynamic': 3.33511, 'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.911566, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0437281, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925, 'Renaming Unit/Free List/Area': 0.0414755, 'Renaming Unit/Free List/Gate Leakage': 4.15911e-05, 'Renaming Unit/Free List/Peak Dynamic': 0.0401324, 'Renaming Unit/Free List/Runtime Dynamic': 0.0434736, 'Renaming Unit/Free List/Subthreshold Leakage': 0.000670426, 'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987, 'Renaming Unit/Gate Leakage': 0.00863632, 'Renaming Unit/Int Front End RAT/Area': 0.114751, 'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343, 'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945, 'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.312977, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781, 'Renaming Unit/Peak Dynamic': 4.56169, 'Renaming Unit/Runtime Dynamic': 1.26802, 'Renaming Unit/Subthreshold Leakage': 0.070483, 'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779, 'Runtime Dynamic': 9.87124, 'Subthreshold Leakage': 6.21877, 'Subthreshold Leakage with power gating': 2.58311}, {'Area': 32.0201, 'Execution Unit/Area': 7.68434, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.112822, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.291304, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.592092, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.120359, 'Execution Unit/Instruction Scheduler/Area': 1.66526, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.252481, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.407243, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.205563, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.865287, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.19799, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 5.26347, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788, 'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.111859, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0105902, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968, 'Execution Unit/Register Files/Gate Leakage': 0.000622708, 'Execution Unit/Register Files/Integer RF/Area': 0.362673, 'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.119518, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.078321, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.231377, 'Execution Unit/Register Files/Runtime Dynamic': 0.0889112, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.280003, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.604376, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543, 'Execution Unit/Runtime Dynamic': 2.25526, 'Execution Unit/Subthreshold Leakage': 1.79543, 'Execution Unit/Subthreshold Leakage with power gating': 0.688821, 'Gate Leakage': 0.368936, 'Instruction Fetch Unit/Area': 5.85939, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00128101, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00128101, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.0011453, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000459521, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00112509, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00483242, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0112269, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0589979, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.075292, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 4.78922, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.196589, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386, 'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799, 'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493, 'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404, 'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.255726, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104, 'Instruction Fetch Unit/Peak Dynamic': 7.24016, 'Instruction Fetch Unit/Runtime Dynamic': 0.543666, 'Instruction Fetch Unit/Subthreshold Leakage': 0.932286, 'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843, 'L2/Area': 4.53318, 'L2/Gate Leakage': 0.015464, 'L2/Peak Dynamic': 0.055677, 'L2/Runtime Dynamic': 0.0100731, 'L2/Subthreshold Leakage': 0.834142, 'L2/Subthreshold Leakage with power gating': 0.401066, 'Load Store Unit/Area': 8.80901, 'Load Store Unit/Data Cache/Area': 6.84535, 'Load Store Unit/Data Cache/Gate Leakage': 0.0279261, 'Load Store Unit/Data Cache/Peak Dynamic': 2.77853, 'Load Store Unit/Data Cache/Runtime Dynamic': 0.76309, 'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675, 'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085, 'Load Store Unit/Gate Leakage': 0.0350888, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.0498683, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.0498683, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 3.01402, 'Load Store Unit/Runtime Dynamic': 1.05889, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate Leakage': 0.00329971, 'Load Store 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'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.103663, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.28411, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.54496, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.120359, 'Execution Unit/Instruction Scheduler/Area': 1.66526, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433, 'Execution Unit/Instruction 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'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00138975, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00138975, 'Instruction Fetch Unit/Branch Predictor/Global 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Predictor/L2_Local Predictor/Runtime Dynamic': 0.000500937, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00109937, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00512397, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold 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'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 4.67975, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.196965, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386, 'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799, 'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493, 'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404, 'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.249881, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104, 'Instruction Fetch Unit/Peak Dynamic': 7.12538, 'Instruction Fetch Unit/Runtime Dynamic': 0.537629, 'Instruction Fetch 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'Memory Management Unit/Dtlb/Peak Dynamic': 0.00897453, 'Memory Management Unit/Dtlb/Runtime Dynamic': 0.00941403, 'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699, 'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485, 'Memory Management Unit/Gate Leakage': 0.00808595, 'Memory Management Unit/Itlb/Area': 0.301552, 'Memory Management Unit/Itlb/Gate Leakage': 0.00393464, 'Memory Management Unit/Itlb/Peak Dynamic': 0.0726686, 'Memory Management Unit/Itlb/Runtime Dynamic': 0.0135644, 'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758, 'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842, 'Memory Management Unit/Peak Dynamic': 0.244194, 'Memory Management Unit/Runtime Dynamic': 0.0229784, 'Memory Management Unit/Subthreshold Leakage': 0.0766103, 'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333, 'Peak Dynamic': 12.8701, 'Renaming Unit/Area': 0.303608, 'Renaming Unit/FP Front End 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models/models.py

sfcurre/aedes_model

101fb8f49868bf3b2421cff7b14e89aab69b9c64

[ "MIT" ]

null

models/models.py

sfcurre/aedes_model

101fb8f49868bf3b2421cff7b14e89aab69b9c64

[ "MIT" ]

1

2021-01-08T17:07:12.000Z

models/models.py

sfcurre/aedes_model

101fb8f49868bf3b2421cff7b14e89aab69b9c64

[ "MIT" ]

null

import tensorflow as tf def ff_model(input_shape): xin = tf.keras.layers.Input(input_shape) c1 = tf.keras.layers.Conv1D(64, 3, activation = 'relu', data_format = 'channels_last')(xin) c2 = tf.keras.layers.Conv1D(64, 3, activation = 'relu', data_format = 'channels_last')(c1) h1 = tf.keras.layers.BatchNormalization()(c2) h2 = tf.keras.layers.Flatten()(h1) h3 = tf.keras.layers.Dense(64, activation = 'relu')(h2) #h3 = tf.keras.layers.Dropout(0.2)(h3) h4 = tf.keras.layers.Dense(64, activation = 'relu')(h3) #h4 = tf.keras.layers.Dropout(0.2)(h4) xout = tf.keras.layers.Dense(1, activation = 'relu', kernel_regularizer = tf.keras.regularizers.l2(0.001))(h4) return tf.keras.models.Model(xin, xout) def lstm_model(input_shape): xin = tf.keras.layers.Input(input_shape) c1 = tf.keras.layers.Conv1D(64, 3, activation = 'relu', data_format = 'channels_last')(xin) #c1 = tf.keras.layers.Dropout(0.2)(c1) c2 = tf.keras.layers.Conv1D(64, 3, activation = 'relu', data_format = 'channels_last')(c1) #c2 = tf.keras.layers.Dropout(0.2)(c2) h1 = tf.keras.layers.BatchNormalization()(c2) r1 = tf.keras.layers.LSTM(64, return_sequences = True)(h1) r2 = tf.keras.layers.LSTM(64)(r1) xout = tf.keras.layers.Dense(1, activation = 'relu', kernel_regularizer = tf.keras.regularizers.l2(0.001))(r2) return tf.keras.models.Model(xin, xout) def gru_model(input_shape): xin = tf.keras.layers.Input(input_shape) c1 = tf.keras.layers.Conv1D(64, 3, activation = 'relu', data_format = 'channels_last')(xin) c2 = tf.keras.layers.Conv1D(64, 3, activation = 'relu', data_format = 'channels_last')(c1) h1 = tf.keras.layers.BatchNormalization()(c2) r1 = tf.keras.layers.GRU(64, return_sequences = True)(h1) r2 = tf.keras.layers.GRU(64)(r1) xout = tf.keras.layers.Dense(1, activation = 'relu', kernel_regularizer = tf.keras.regularizers.l2(0.001))(r2) return tf.keras.models.Model(xin, xout)

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Python

face_recognition/api_aws/migrations/0003_auto_20200616_1247.py

Fabriciooml/AWS-Rekognition-with-Django

9a30015dbf8334fe7d2c3fd25e8c32dc4bc9358f

[ "MIT" ]

null

face_recognition/api_aws/migrations/0003_auto_20200616_1247.py

Fabriciooml/AWS-Rekognition-with-Django

9a30015dbf8334fe7d2c3fd25e8c32dc4bc9358f

[ "MIT" ]

null

face_recognition/api_aws/migrations/0003_auto_20200616_1247.py

Fabriciooml/AWS-Rekognition-with-Django

9a30015dbf8334fe7d2c3fd25e8c32dc4bc9358f

[ "MIT" ]

1

2021-11-05T19:32:16.000Z

# Generated by Django 3.0.3 on 2020-06-16 15:47 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('api_aws', '0002_auto_20200616_1244'), ] operations = [ migrations.AddField( model_name='face', name='faceId', field=models.CharField(default=100, max_length=50), preserve_default=False, ), migrations.AddField( model_name='face', name='height', field=models.FloatField(default=0, max_length=15), preserve_default=False, ), migrations.AddField( model_name='face', name='imageId', field=models.CharField(default=0, max_length=50), preserve_default=False, ), migrations.AddField( model_name='face', name='left', field=models.FloatField(default=0, max_length=15), preserve_default=False, ), migrations.AddField( model_name='face', name='name', field=models.CharField(default=0, max_length=50), preserve_default=False, ), migrations.AddField( model_name='face', name='similarity', field=models.FloatField(default=0, max_length=15), preserve_default=False, ), migrations.AddField( model_name='face', name='top', field=models.FloatField(default=0, max_length=15), preserve_default=False, ), migrations.AddField( model_name='face', name='width', field=models.FloatField(default=0, max_length=15), preserve_default=False, ), ]

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py

Python

listmaker/inputManager.py

vsuley/listmaker

ffd115e5d4cd184e8f3f9e6b2a4e279a512456fc

[ "MIT" ]

null

listmaker/inputManager.py

vsuley/listmaker

ffd115e5d4cd184e8f3f9e6b2a4e279a512456fc

[ "MIT" ]

null

listmaker/inputManager.py

vsuley/listmaker

ffd115e5d4cd184e8f3f9e6b2a4e279a512456fc

[ "MIT" ]

null

import sys class InputManager(object): pass

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py

Python

core/tests/data/image_constants.py

Tim810306/oppia

6f90044d12dbe0979c999265cbe46f267c4c592d

[ "Apache-2.0" ]

5,422

2015-08-14T01:56:44.000Z

2022-03-31T23:31:56.000Z

core/tests/data/image_constants.py

Tim810306/oppia

6f90044d12dbe0979c999265cbe46f267c4c592d

[ "Apache-2.0" ]

14,178

2015-08-14T05:21:45.000Z

2022-03-31T23:54:10.000Z

core/tests/data/image_constants.py

Tim810306/oppia

6f90044d12dbe0979c999265cbe46f267c4c592d

[ "Apache-2.0" ]

3,574

2015-08-14T04:20:06.000Z

2022-03-29T01:52:37.000Z

# Copyright 2020 The Oppia Authors. 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. PNG_IMAGE_WRONG_DIMENSIONS_BASE64 = ( 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py

Python

anthill/exec/admin.py

anthill-services/anthill-exec

a5f6e6d78e157ec8e5715fc44f646c56f4fda46b

[ "MIT" ]

null

anthill/exec/admin.py

anthill-services/anthill-exec

a5f6e6d78e157ec8e5715fc44f646c56f4fda46b

[ "MIT" ]

null

anthill/exec/admin.py

anthill-services/anthill-exec

a5f6e6d78e157ec8e5715fc44f646c56f4fda46b

[ "MIT" ]

1

2017-12-03T22:05:20.000Z

from tornado.gen import with_timeout, TimeoutError from anthill.common import admin as a from . model.sources import NoSuchSourceError, SourceCodeError, JavascriptSourceError from . model.build import JavascriptBuildError, NoSuchClass, NoSuchMethod from . model.session import APIError, JavascriptSessionError from anthill.common.environment import EnvironmentClient, AppNotFound from anthill.common.access import AccessToken from anthill.common.internal import Internal, InternalError from anthill.common.validate import validate from anthill.common import ElapsedTime from anthill.common.jsonrpc import JsonRPCError from anthill.common.source import NoSuchProjectError, SourceCodeRoot from datetime import datetime, timedelta import traceback import logging import ujson class ApplicationController(a.AdminController): @validate(app_id="str") async def get(self, app_id): environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources try: app = await environment_client.get_app_info(app_id) except AppNotFound: raise a.ActionError("App was not found.") try: await sources.get_project(self.gamespace, app_id) except NoSuchProjectError: has_no_settings = True commits = {} else: has_no_settings = False try: commits = await sources.list_versions(self.gamespace, app_id) except SourceCodeError: commits = {} result = { "app_id": app_id, "app_record_id": app.id, "app_name": app.title, "versions": app.versions, "commits": commits, "has_no_settings": has_no_settings } return result def render(self, data): r = [ a.breadcrumbs([ a.link("apps", "Applications") ], data["app_name"]) ] if data["has_no_settings"]: r.append(ApplicationSettingsController.no_settings_notice()) commits = data["commits"] def get_version_commit(version): commit = commits.get(version, None) if commit is not None: return commit.repository_commit[:7] return None r.extend([ a.links("Application '{0}' versions".format(data["app_name"]), links=[ a.link("app_version", v_name, icon="tags", badge=get_version_commit(v_name), app_id=self.context.get("app_id"), app_version=v_name) for v_name, v_id in data["versions"].items() ]), a.links("Navigate", [ a.link("app_settings", "Application Settings", icon="cogs", app_id=self.context.get("app_id")), a.link("apps", "Go back", icon="chevron-left"), a.link("/environment/app", "Manage app '{0}' at 'Environment' service.".format(data["app_name"]), icon="link text-danger", record_id=data["app_record_id"]), ]) ]) return r def access_scopes(self): return ["exec_admin"] class ApplicationSettingsController(a.AdminController): @validate(app_id="str") async def get(self, app_id): environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources try: app = await environment_client.get_app_info(app_id) except AppNotFound as e: raise a.ActionError("App was not found.") try: project = await sources.get_project(self.gamespace, app_id) except NoSuchProjectError as e: repository_url = "" ssh_private_key = "" repository_branch = SourceCodeRoot.DEFAULT_BRANCH else: repository_url = project.repository_url repository_branch = project.repository_branch ssh_private_key = project.ssh_private_key result = { "app_id": app_id, "app_record_id": app.id, "app_name": app.title, "repository_url": repository_url, "repository_branch": repository_branch, "ssh_private_key": ssh_private_key } return result @validate(repository_url="str", repository_branch="str", ssh_private_key="str") async def update_settings(self, repository_url, repository_branch, ssh_private_key, *ignored): app_id = self.context.get("app_id") environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources builds = self.application.builds try: await environment_client.get_app_info(app_id) except AppNotFound as e: raise a.ActionError("App was not found.") if not (await builds.validate_repository_url(repository_url, ssh_private_key)): raise a.ActionError("Error: \"{0}\" is not a valid Git repository URL, or " "the repository does not exist, or the ssh key is wrong.".format(repository_url)) await sources.update_project(self.gamespace, app_id, repository_url, repository_branch, ssh_private_key) raise a.Redirect("app_settings", message="Application settings have been updated.", app_id=app_id) @staticmethod def no_settings_notice(): return a.notice( "Source Code Repository Is Not Configured", """ You have not defined your source code repository yet. <br> To deploy your codebase to the Exec service, you must use a Git repository. <br> Please create one if you don't have it and define it in the settings below. """, style="danger") def render(self, data): r = [ a.breadcrumbs([ a.link("apps", "Applications"), a.link("app", data["app_name"], app_id=self.context.get("app_id")), ], "Application Settings")] if not data["repository_url"]: r.append(ApplicationSettingsController.no_settings_notice()) r.extend([ a.form("Application Settings", fields={ "repository_url": a.field( "Git source code repository url (ssh only)", "text", "primary", description=""" You need to use SSH remote url in order to deploy source code to this service. See <a href="https://help.github.com/articles/which-remote-url-should-i-use/#cloning-with-ssh-urls" target="_blank">this</a>. """, order=1), "repository_branch": a.field( "Git branch to use on the source code repository", "text", "primary", order=2), "ssh_private_key": a.field( "Private SSH key", "text", "primary", multiline=6, description=""" Please generate SSH key pair, paste private key (for example, <span class="label label-default">id_rsa</span>) here, and add public key (for example, <span class="label label-default">id_rsa.pub</span>) into user's SSH keys with read access to the repository above. For example, on GitHub, it can be done <a href="https://github.com/settings/keys" target="_blank">here</a>. """, order=3) }, methods={ "update_settings": a.method("Update Settings", "primary") }, data=data), a.links("Navigate", [ a.link("app", "Go back", icon="chevron-left", app_id=self.context.get("app_id")), a.link("/environment/app", "Manage app '{0}' at 'Environment' service.".format(data["app_name"]), icon="link text-danger", record_id=data["app_record_id"]), ]) ]) return r def access_scopes(self): return ["exec_admin"] class ServerCodeSettingsController(a.AdminController): async def get(self): sources = self.application.sources try: project = await sources.get_server_project(self.gamespace) except NoSuchProjectError as e: repository_url = "" ssh_private_key = "" repository_branch = SourceCodeRoot.DEFAULT_BRANCH else: repository_url = project.repository_url repository_branch = project.repository_branch ssh_private_key = project.ssh_private_key result = { "repository_url": repository_url, "repository_branch": repository_branch, "ssh_private_key": ssh_private_key } return result @validate(repository_url="str", repository_branch="str", ssh_private_key="str") async def update_settings(self, repository_url, repository_branch, ssh_private_key, *ignored): sources = self.application.sources builds = self.application.builds if not (await builds.validate_repository_url(repository_url, ssh_private_key)): raise a.ActionError("Error: \"{0}\" is not a valid Git repository URL, or " "the repository does not exist, or the ssh key is wrong.".format(repository_url)) await sources.update_server_project(self.gamespace, repository_url, repository_branch, ssh_private_key) raise a.Redirect("server", message="Server Code settings have been updated.") @staticmethod def no_settings_notice(): return a.notice( "Server Code Repository Is Not Configured", """ You have not defined your source code repository yet. <br> To deploy your codebase to the Exec service, you must use a Git repository. <br> Please create one if you don't have it and define it in the settings below. """, style="danger") def render(self, data): r = [ a.breadcrumbs([ a.link("server", "Server Code"), ], "Server Code Settings"), ServerCodeController.about_notice() ] if not data["repository_url"]: r.append(ServerCodeSettingsController.no_settings_notice()) r.extend([ a.form("Server Code Settings", fields={ "repository_url": a.field( "Git source code repository url (ssh only)", "text", "primary", description=""" You need to use SSH remote url in order to deploy source code to this service. See <a href="https://help.github.com/articles/which-remote-url-should-i-use/#cloning-with-ssh-urls" target="_blank">this</a>. """, order=1), "repository_branch": a.field( "Git branch to use on the source code repository", "text", "primary", order=2), "ssh_private_key": a.field( "Private SSH key", "text", "primary", multiline=6, description=""" Please generate SSH key pair, paste private key (for example, <span class="label label-default">id_rsa</span>) here, and add public key (for example, <span class="label label-default">id_rsa.pub</span>) into user's SSH keys with read access to the repository above. For example, on GitHub, it can be done <a href="https://github.com/settings/keys" target="_blank">here</a>. """, order=3) }, methods={ "update_settings": a.method("Update Settings", "primary") }, data=data), a.links("Navigate", [ a.link("server", "Go back", icon="chevron-left"), ]) ]) return r def access_scopes(self): return ["exec_admin"] class ApplicationVersionController(a.AdminController): @validate(app_id="str", app_version="str") async def get(self, app_id, app_version): environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources builds = self.application.builds try: app = await environment_client.get_app_info(app_id) except AppNotFound: raise a.ActionError("App was not found.") try: project_settings = await sources.get_project(self.gamespace, app_id) except NoSuchProjectError as e: raise a.Redirect("app_settings", message="Please define project settings first", app_id=app_id) try: commit = await sources.get_version_commit(self.gamespace, app_id, app_version) except NoSuchSourceError: current_commit = None else: current_commit = commit.repository_commit try: project = builds.get_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError as e: commits_history = None else: try: commits_history = await project.get_commits_history(50) except SourceCodeError as e: raise a.ActionError(e.message) result = { "app_id": app_id, "app_record_id": app.id, "app_name": app.title, "versions": app.versions, "current_commit": current_commit, "commits_history": commits_history } return result @staticmethod def no_commit_notice(app_version): return a.notice( "This version ({0}) is disabled".format(app_version), """ The version {0} is not attached to any commit for the Git repository. <br> Therefore, running source code for this version is not possible. <br> Please attach the version to a commit using either "Update To The Last Commit", or by clicking "Use This" on a commit of the resent commits history. """.format(app_version), style="danger") async def switch_commit_context(self): commit = self.context.get("commit") await self.switch_commit(commit) async def switch_to_latest_commit(self): app_id = self.context.get("app_id") app_version = self.context.get("app_version") environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources builds = self.application.builds try: await environment_client.get_app_info(app_id) except AppNotFound: raise a.ActionError("App was not found.") try: project_settings = await sources.get_project(self.gamespace, app_id) except NoSuchProjectError as e: raise a.Redirect("app_settings", message="Please define project settings first", app_id=app_id) try: project = builds.get_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError: raise a.ActionError("Repository has not updated itself yet.") try: latest_commit = await project.pull_and_get_latest_commit() except SourceCodeError as e: raise a.ActionError(e.message) if not latest_commit: raise a.ActionError("Failed to check the latest commit") try: updated = await sources.update_commit(self.gamespace, app_id, app_version, latest_commit) except SourceCodeError as e: raise a.ActionError(e.message) if updated: raise a.Redirect( "app_version", message="Version has been updated", app_id=app_id, app_version=app_version) raise a.Redirect( "app_version", message="Already up-to-date.", app_id=app_id, app_version=app_version) async def detach_version(self): app_id = self.context.get("app_id") app_version = self.context.get("app_version") environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources builds = self.application.builds try: await environment_client.get_app_info(app_id) except AppNotFound: raise a.ActionError("App was not found.") try: deleted = await sources.delete_commit(self.gamespace, app_id, app_version) except SourceCodeError as e: raise a.ActionError(e.message) if deleted: raise a.Redirect( "app_version", message="Version has been disabled", app_id=app_id, app_version=app_version) raise a.Redirect( "app_version", message="Version was already disabled", app_id=app_id, app_version=app_version) async def pull_updates(self): app_id = self.context.get("app_id") app_version = self.context.get("app_version") environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources builds = self.application.builds try: await environment_client.get_app_info(app_id) except AppNotFound: raise a.ActionError("App was not found.") try: project_settings = await sources.get_project(self.gamespace, app_id) except NoSuchProjectError as e: raise a.Redirect("app_settings", message="Please define project settings first", app_id=app_id) try: project = builds.get_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError: raise a.ActionError("Repository has not updated itself yet.") try: pulled = await project.pull() except SourceCodeError as e: raise a.ActionError(e.message) if not pulled: raise a.ActionError("Failed to pull updates") raise a.Redirect( "app_version", message="Updates has been pulled.", app_id=app_id, app_version=app_version) @validate(commit="str_name") async def switch_commit(self, commit): app_id = self.context.get("app_id") app_version = self.context.get("app_version") environment_client = EnvironmentClient(self.application.cache) sources = self.application.sources builds = self.application.builds try: await environment_client.get_app_info(app_id) except AppNotFound: raise a.ActionError("App was not found.") try: project_settings = await sources.get_project(self.gamespace, app_id) except NoSuchProjectError as e: raise a.Redirect("app_settings", message="Please define project settings first", app_id=app_id) try: project = builds.get_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError: raise a.ActionError("Repository has not updated itself yet.") try: commit_exists = await project.check_commit(commit) except SourceCodeError as e: raise a.ActionError(e.message) if not commit_exists: raise a.ActionError("No such commit") try: await sources.update_commit(self.gamespace, app_id, app_version, commit) except SourceCodeError as e: raise a.ActionError(e.message) raise a.Redirect("app_version", message="Version has been updated", app_id=app_id, app_version=app_version) def render(self, data): r = [ a.breadcrumbs([ a.link("apps", "Applications"), a.link("app", data["app_name"], app_id=self.context.get("app_id")), ], self.context.get("app_version")) ] if data["commits_history"] is None: r.append(a.notice("Repository is in progress", "Please wait until repository is updated")) else: methods = { "switch_to_latest_commit": a.method("Update To The Last Commit", "primary", order=1), "pull_updates": a.method("Pull Updates", "default", order=2), } if data["current_commit"]: methods["detach_version"] = a.method( "Disable This Version", "danger", order=3, danger="Are you sure you would like to disable this version from launching? After this action, " "users would not be able to open sessions on this version.") else: r.append(ApplicationVersionController.no_commit_notice(self.context.get("app_version"))) r.extend([ a.form("Actions", fields={}, methods=methods, data=data), a.content(title="Recent Commits History", headers=[ { "id": "actions", "title": "Actions" }, { "id": "message", "title": "Commit Message" }, { "id": "hash", "title": "Commit Hash" }, { "id": "date", "title": "Commit Date" }, { "id": "author", "title": "Commit Author" } ], items=[ { "hash": [ a.status(commit.hexsha[:7], "default") ], "message": commit.message[:48], "date": str(commit.committed_datetime), "author": str(commit.author.name) + " (" + commit.author.email + ")", "actions": [ a.status("Current Commit", "success", "check") if data["current_commit"] == commit.hexsha else a.button("app_version", "Use This", "primary", _method="switch_commit_context", commit=str(commit.hexsha), app_id=self.context.get("app_id"), app_version=self.context.get("app_version")) ] } for commit in data["commits_history"] ], style="primary") ]) r.extend([ a.links("Navigate", [ a.link("app", "Go back", icon="chevron-left", app_id=self.context.get("app_id")) ]) ]) return r def access_scopes(self): return ["exec_admin"] class ServerCodeController(a.AdminController): async def get(self): sources = self.application.sources builds = self.application.builds try: project_settings = await sources.get_server_project(self.gamespace) except NoSuchProjectError: raise a.Redirect("server_settings", message="Please define project settings first") try: commit = await sources.get_server_commit(self.gamespace) except NoSuchSourceError: current_commit = None else: current_commit = commit.repository_commit server_fetch_error = None try: project = builds.get_server_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError: commits_history = None except SourceCodeError as e: commits_history = None server_fetch_error = str(e.message) except Exception as e: commits_history = None server_fetch_error = str(e) else: try: commits_history = await project.get_commits_history(50) except SourceCodeError as e: raise a.ActionError(e.message) result = { "current_commit": current_commit, "commits_history": commits_history, "server_fetch_error": server_fetch_error, } return result @staticmethod def no_commit_notice(): return a.notice( "The Server Code is disabled", """ The server code is not attached to any commit for the Git repository. <br> Therefore, running source code for the server code is not possible. <br> Please attach the version to a commit using either "Update To The Last Commit", or by clicking "Use This" on a commit of the resent commits history. """, style="danger") @staticmethod def about_notice(): return a.notice( "About The Server Code", """ The Server Code is a way to deploy restricted application-independent code to the exec service. <br> Users cannot call the Server Code, but other services can. Therefore, services that have no application context can call functions on exec service with Server Code. <br> Please refer to the API for more information. """, style="info") async def switch_commit_context(self): commit = self.context.get("commit") await self.switch_commit(commit) async def switch_to_latest_commit(self): sources = self.application.sources builds = self.application.builds try: project_settings = await sources.get_server_project(self.gamespace) except NoSuchProjectError: raise a.Redirect("server_settings", message="Please define project settings first") try: project = builds.get_server_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError: raise a.ActionError("Repository has not updated itself yet.") try: latest_commit = await project.pull_and_get_latest_commit() except SourceCodeError as e: raise a.ActionError(e.message) if not latest_commit: raise a.ActionError("Failed to check the latest commit") try: updated = await sources.update_server_commit(self.gamespace, latest_commit) except SourceCodeError as e: raise a.ActionError(e.message) if updated: raise a.Redirect("server", message="Server Code has been updated") raise a.Redirect("server", message="Already up-to-date.") async def detach_version(self): sources = self.application.sources try: deleted = await sources.delete_server_commit(self.gamespace) except SourceCodeError as e: raise a.ActionError(e.message) if deleted: raise a.Redirect("server", message="Server code has been disabled") raise a.Redirect("server", message="Server code was already disabled") async def pull_updates(self): sources = self.application.sources builds = self.application.builds try: project_settings = await sources.get_server_project(self.gamespace) except NoSuchProjectError: raise a.Redirect("server_settings", message="Please define project settings first") try: project = builds.get_server_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError: raise a.ActionError("Repository has not updated itself yet.") try: pulled = await project.pull() except SourceCodeError as e: raise a.ActionError(e.message) if not pulled: raise a.ActionError("Failed to pull updates") raise a.Redirect("server", message="Updates has been pulled.") @validate(commit="str_name") async def switch_commit(self, commit): sources = self.application.sources builds = self.application.builds try: project_settings = await sources.get_server_project(self.gamespace) except NoSuchProjectError as e: raise a.Redirect("server_settings", message="Please define project settings first") try: project = builds.get_server_project(project_settings) await with_timeout(timedelta(seconds=10), project.init()) except JavascriptBuildError as e: raise a.ActionError(e.message) except TimeoutError: raise a.ActionError("Repository has not updated itself yet.") try: commit_exists = await project.check_commit(commit) except SourceCodeError as e: raise a.ActionError(e.message) if not commit_exists: raise a.ActionError("No such commit") try: await sources.update_server_commit(self.gamespace, commit) except SourceCodeError as e: raise a.ActionError(e.message) raise a.Redirect("server", message="Server code commit has been updated") def render(self, data): r = [ a.breadcrumbs([], "Server Code") ] if data["commits_history"] is None: if data["server_fetch_error"]: r.append(a.notice("Failed to update repository", "Please check repository settings: {0}".format(data["server_fetch_error"]), "danger")) else: r.append(a.notice("Repository is in progress", "Please wait until repository is updated")) else: methods = { "switch_to_latest_commit": a.method("Update To The Last Commit", "primary", order=1), "pull_updates": a.method("Pull Updates", "default", order=2), } if data["current_commit"]: methods["detach_version"] = a.method( "Disable Server Code", "danger", order=3, danger="Are you sure you would like to disable the Server Code from launching? After this action, " "services would not be able to call functions on the Server Code.") else: r.append(ServerCodeController.no_commit_notice()) r.extend([ a.form("Actions", fields={}, methods=methods, data=data), a.content(title="Recent Commits History", headers=[ { "id": "actions", "title": "Actions" }, { "id": "message", "title": "Commit Message" }, { "id": "hash", "title": "Commit Hash" }, { "id": "date", "title": "Commit Date" }, { "id": "author", "title": "Commit Author" } ], items=[ { "hash": [ a.status(commit.hexsha[:7], "default") ], "message": commit.message[:48], "date": str(commit.committed_datetime), "author": str(commit.author.name) + " (" + commit.author.email + ")", "actions": [ a.status("Current Commit", "success", "check") if data["current_commit"] == commit.hexsha else a.button("server", "Use This", "primary", _method="switch_commit_context", commit=str(commit.hexsha)) ] } for commit in data["commits_history"] ], style="primary") ]) r.extend([ ServerCodeController.about_notice(), a.links("Navigate", [ a.link("index", "Go back", icon="chevron-left"), a.link("server_settings", "Server Code Settings", icon="cogs") ]) ]) return r def access_scopes(self): return ["exec_admin"] class ApplicationsController(a.AdminController): async def get(self): environment_client = EnvironmentClient(self.application.cache) apps = await environment_client.list_apps() result = { "apps": apps } return result def render(self, data): return [ a.breadcrumbs([], "Applications"), a.links("Select application", links=[ a.link("app", app_name, icon="mobile", app_id=app_id) for app_id, app_name in data["apps"].items() ]), a.links("Navigate", [ a.link("index", "Go back", icon="chevron-left"), a.link("/environment/apps", "Manage apps", icon="link text-danger"), ]) ] def access_scopes(self): return ["exec_admin"] class RootAdminController(a.AdminController): def render(self, data): return [ a.links("Exec service", [ a.link("apps", "Applications", icon="mobile"), a.link("server", "Server Code", icon="server"), ]) ] def access_scopes(self): return ["exec_admin"] class FunctionsController(a.AdminController): def render(self, data): return [ a.breadcrumbs([], "Functions"), a.links("Functions", [ a.link("function", f.name, icon="code", function_name=f.name) for f in data["functions"] ]), a.notice("Notice", "Please note that the function should be bound " "to the application in order to be called."), a.links("Navigate", [ a.link("index", "Go back", icon="chevron-left"), a.link("new_function", "New function", icon="plus"), ]) ] async def get(self): functions = self.application.functions return { "functions": (await functions.list_functions(self.gamespace)) } def access_scopes(self): return ["exec_admin"]

37.541361

120

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35,852

954

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37.580713

0.83037

0

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false

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null

0

1

0

1

0

null

0

7

08e9bc060b5ddd7d0e88b04b56360d13ada5fd9b

143

py

Python

jupyter/jupyter_notebook_config.py

IIAT-MR-LL/CPI_prediction

498775e7e0803f041c175a1af5c8c6efbeed705f

[ "Apache-2.0" ]

null

jupyter/jupyter_notebook_config.py

IIAT-MR-LL/CPI_prediction

498775e7e0803f041c175a1af5c8c6efbeed705f

[ "Apache-2.0" ]

9

2020-01-28T22:16:53.000Z

2022-02-10T00:35:39.000Z

jupyter/jupyter_notebook_config.py

IIAT-MR-LL/CPI_prediction

498775e7e0803f041c175a1af5c8c6efbeed705f

[ "Apache-2.0" ]

null

c.NotebookApp.open_browser = True c.NotebookApp.ip = '*' c.NotebookApp.password = u'sha1:a488dc80584d:5c33900ec1f5e4f7b658dca101166d3cad7c9e58'

47.666667

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143

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0.733333

0.305085

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0.244444

0.055944

143

3

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47.666667

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0

0.409722

0.402778

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true

0.333333

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1

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null

1

0

1

0

1

0

1

null

0

1

0

7

08f15c82a1e2d2e0b54254f60efea2f0019d9f1c

130

py

Python

app/ui/commands.py

ExiledNarwal28/cardbot

1e0fa1e9c08b512056c2af0b408eded224c9adbb

[ "MIT" ]

null

app/ui/commands.py

ExiledNarwal28/cardbot

1e0fa1e9c08b512056c2af0b408eded224c9adbb

[ "MIT" ]

41

2020-05-10T20:18:19.000Z

2020-12-08T10:42:31.000Z

app/ui/commands.py

ExiledNarwal28/cardbot

1e0fa1e9c08b512056c2af0b408eded224c9adbb

[ "MIT" ]

null

from app.sessions.ui.commands import register_sessions_commands def register_commands(bot): register_sessions_commands(bot)

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4101e0360527aa63617594756ffa1206f403ba45

254

py

Python

parameters_8000.py

ziming9/Said-it

ce9f3047940af9e3b380edcc142c9ca1e72b43d0

[ "BSD-3-Clause" ]

null

parameters_8000.py

ziming9/Said-it

ce9f3047940af9e3b380edcc142c9ca1e72b43d0

[ "BSD-3-Clause" ]

null

parameters_8000.py

ziming9/Said-it

ce9f3047940af9e3b380edcc142c9ca1e72b43d0

[ "BSD-3-Clause" ]

1

2019-04-12T23:26:03.000Z

<<<<<<< HEAD password="pbkdf2(1000,20,sha512)$b2f536b4dddadf3d$f4c32852252c006499e0ad416c2250c1437a4f0d" ======= password="pbkdf2(1000,20,sha512)$80fc4cfa56d6c3e8$aaeace46c9a63dc83936eea458b2e2d46e418452" >>>>>>> ac107c2232ef7d609545d2dd50d64d79d81a428f

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f5cdc39d10fdbf5e4da2bcd1b6763b715faf0ccc

405

py

Python

src/graph_transpiler/webdnn/backend/webgl/optimize_rules/split_texture/__init__.py

steerapi/webdnn

1df51cc094e5a528cfd3452c264905708eadb491

[ "MIT" ]

1

2021-04-09T15:55:35.000Z

src/graph_transpiler/webdnn/backend/webgl/optimize_rules/split_texture/__init__.py

steerapi/webdnn

1df51cc094e5a528cfd3452c264905708eadb491

[ "MIT" ]

null

src/graph_transpiler/webdnn/backend/webgl/optimize_rules/split_texture/__init__.py

steerapi/webdnn

1df51cc094e5a528cfd3452c264905708eadb491

[ "MIT" ]

null

from webdnn.backend.webgl.optimize_rules.split_texture import assert_texture_size from webdnn.backend.webgl.optimize_rules.split_texture import check_texture_size from webdnn.backend.webgl.optimize_rules.split_texture import split_input_texture from webdnn.backend.webgl.optimize_rules.split_texture import split_output_texture from webdnn.backend.webgl.optimize_rules.split_texture import split_variable

67.5

82

0.901235

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405

5.864407

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0.144509

0.245665

0.317919

0.913295

0.760116

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405

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12

eb24c159d391cba0a51bb9d12e362ecac7f013ad

138

py

Python

networkx/drawing/__init__.py

jdrudolph/networkx

d49733b61fb7dedfbbbdd9c04464adf6beb5db07

[ "BSD-3-Clause" ]

1

2020-11-10T08:15:23.000Z

networkx/drawing/__init__.py

jdrudolph/networkx

d49733b61fb7dedfbbbdd9c04464adf6beb5db07

[ "BSD-3-Clause" ]

null

networkx/drawing/__init__.py

jdrudolph/networkx

d49733b61fb7dedfbbbdd9c04464adf6beb5db07

[ "BSD-3-Clause" ]

1

2022-03-31T20:55:28.000Z

# graph drawing and interface to graphviz from .layout import * from .nx_pylab import * from .nx_agraph import * from .nx_pydot import *

19.714286

41

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138

4.857143

0.619048

0.294118

0.352941

0

0.173913

138

6

42

23

0.894737

0.282609

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true

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null

0

1

0

1

0

1

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7

dee379caadfe39249a6d939393b1343c5191097b

698

py

Python

fuel_tank.py

GYosifov88/Python-Basics

f4290061264aebc417bde4948948e4a64739fec9

[ "MIT" ]

null

fuel_tank.py

GYosifov88/Python-Basics

f4290061264aebc417bde4948948e4a64739fec9

[ "MIT" ]

null

fuel_tank.py

GYosifov88/Python-Basics

f4290061264aebc417bde4948948e4a64739fec9

[ "MIT" ]

null

fuel_type = input() litres_of_fuel = int(input()) if fuel_type == 'Diesel': if litres_of_fuel >=25: print(f'You have enough {str.lower(fuel_type)}.') elif litres_of_fuel < 25: print(f'Fill your tank with {str.lower(fuel_type)}!') elif fuel_type == 'Gasoline': if litres_of_fuel >=25: print(f'You have enough {str.lower(fuel_type)}.') elif litres_of_fuel < 25: print(f'Fill your tank with {str.lower(fuel_type)}!') elif fuel_type == 'Gas': if litres_of_fuel >=25: print(f'You have enough {str.lower(fuel_type)}.') elif litres_of_fuel < 25: print(f'Fill your tank with {str.lower(fuel_type)}!') else: print('Invalid fuel!')

34.9

61

0.643266

111

698

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698

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null

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null

0

8

7200a7baeba64c173e82d210e9cc9bb711f4b69b

16,666

py

Python

sdk/python/pulumi_databricks/cluster_policy.py

pulumi/pulumi-databricks

43580d4adbd04b72558f368ff0eef3d03432ebc1

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_databricks/cluster_policy.py

pulumi/pulumi-databricks

43580d4adbd04b72558f368ff0eef3d03432ebc1

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_databricks/cluster_policy.py

pulumi/pulumi-databricks

43580d4adbd04b72558f368ff0eef3d03432ebc1

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from . import _utilities __all__ = ['ClusterPolicyArgs', 'ClusterPolicy'] @pulumi.input_type class ClusterPolicyArgs: def __init__(__self__, *, definition: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a ClusterPolicy resource. :param pulumi.Input[str] definition: Policy definition JSON document expressed in [Databricks Policy Definition Language](https://docs.databricks.com/administration-guide/clusters/policies.html#cluster-policy-definition). :param pulumi.Input[str] name: Cluster policy name. This must be unique. Length must be between 1 and 100 characters. """ if definition is not None: pulumi.set(__self__, "definition", definition) if name is not None: pulumi.set(__self__, "name", name) @property @pulumi.getter def definition(self) -> Optional[pulumi.Input[str]]: """ Policy definition JSON document expressed in [Databricks Policy Definition Language](https://docs.databricks.com/administration-guide/clusters/policies.html#cluster-policy-definition). """ return pulumi.get(self, "definition") @definition.setter def definition(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "definition", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ Cluster policy name. This must be unique. Length must be between 1 and 100 characters. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @pulumi.input_type class _ClusterPolicyState: def __init__(__self__, *, definition: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, policy_id: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering ClusterPolicy resources. :param pulumi.Input[str] definition: Policy definition JSON document expressed in [Databricks Policy Definition Language](https://docs.databricks.com/administration-guide/clusters/policies.html#cluster-policy-definition). :param pulumi.Input[str] name: Cluster policy name. This must be unique. Length must be between 1 and 100 characters. :param pulumi.Input[str] policy_id: Canonical unique identifier for the cluster policy. """ if definition is not None: pulumi.set(__self__, "definition", definition) if name is not None: pulumi.set(__self__, "name", name) if policy_id is not None: pulumi.set(__self__, "policy_id", policy_id) @property @pulumi.getter def definition(self) -> Optional[pulumi.Input[str]]: """ Policy definition JSON document expressed in [Databricks Policy Definition Language](https://docs.databricks.com/administration-guide/clusters/policies.html#cluster-policy-definition). """ return pulumi.get(self, "definition") @definition.setter def definition(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "definition", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ Cluster policy name. This must be unique. Length must be between 1 and 100 characters. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="policyId") def policy_id(self) -> Optional[pulumi.Input[str]]: """ Canonical unique identifier for the cluster policy. """ return pulumi.get(self, "policy_id") @policy_id.setter def policy_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "policy_id", value) class ClusterPolicy(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, definition: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, __props__=None): """ This resource creates a cluster policy, which limits the ability to create clusters based on a set of rules. The policy rules limit the attributes or attribute values available for cluster creation. cluster policies have ACLs that limit their use to specific users and groups. Only admin users can create, edit, and delete policies. Admin users also have access to all policies. Cluster policies let you: * Limit users to create clusters with prescribed settings. * Simplify the user interface and enable more users to create their own clusters (by fixing and hiding some values). * Control cost by limiting per cluster maximum cost (by setting limits on attributes whose values contribute to hourly price). Cluster policy permissions limit which policies a user can select in the Policy drop-down when the user creates a cluster: * If no policies have been created in the workspace, the Policy drop-down does not display. * A user who has cluster create permission can select the `Free form` policy and create fully-configurable clusters. * A user who has both cluster create permission and access to cluster policies can select the Free form policy and policies they have access to. * A user that has access to only cluster policies, can select the policies they have access to. ## Related Resources The following resources are often used in the same context: * Dynamic Passthrough Clusters for a Group guide * End to end workspace management guide * get_clusters data to retrieve a list of Cluster ids. * Cluster to create [Databricks Clusters](https://docs.databricks.com/clusters/index.html). * get_current_user data to retrieve information about User or databricks_service_principal, that is calling Databricks REST API. * GlobalInitScript to manage [global init scripts](https://docs.databricks.com/clusters/init-scripts.html#global-init-scripts), which are run on all Cluster and databricks_job. * InstancePool to manage [instance pools](https://docs.databricks.com/clusters/instance-pools/index.html) to reduce cluster start and auto-scaling times by maintaining a set of idle, ready-to-use instances. * InstanceProfile to manage AWS EC2 instance profiles that users can launch Cluster and access data, like databricks_mount. * IpAccessList to allow access from [predefined IP ranges](https://docs.databricks.com/security/network/ip-access-list.html). * Library to install a [library](https://docs.databricks.com/libraries/index.html) on databricks_cluster. * get_node_type data to get the smallest node type for Cluster that fits search criteria, like amount of RAM or number of cores. * Permissions to manage [access control](https://docs.databricks.com/security/access-control/index.html) in Databricks workspace. * get_spark_version data to get [Databricks Runtime (DBR)](https://docs.databricks.com/runtime/dbr.html) version that could be used for `spark_version` parameter in Cluster and other resources. * UserInstanceProfile to attach InstanceProfile (AWS) to databricks_user. * WorkspaceConf to manage workspace configuration for expert usage. ## Import The resource cluster policy can be imported using the policy idbash ```sh $ pulumi import databricks:index/clusterPolicy:ClusterPolicy this <cluster-policy-id> ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] definition: Policy definition JSON document expressed in [Databricks Policy Definition Language](https://docs.databricks.com/administration-guide/clusters/policies.html#cluster-policy-definition). :param pulumi.Input[str] name: Cluster policy name. This must be unique. Length must be between 1 and 100 characters. """ ... @overload def __init__(__self__, resource_name: str, args: Optional[ClusterPolicyArgs] = None, opts: Optional[pulumi.ResourceOptions] = None): """ This resource creates a cluster policy, which limits the ability to create clusters based on a set of rules. The policy rules limit the attributes or attribute values available for cluster creation. cluster policies have ACLs that limit their use to specific users and groups. Only admin users can create, edit, and delete policies. Admin users also have access to all policies. Cluster policies let you: * Limit users to create clusters with prescribed settings. * Simplify the user interface and enable more users to create their own clusters (by fixing and hiding some values). * Control cost by limiting per cluster maximum cost (by setting limits on attributes whose values contribute to hourly price). Cluster policy permissions limit which policies a user can select in the Policy drop-down when the user creates a cluster: * If no policies have been created in the workspace, the Policy drop-down does not display. * A user who has cluster create permission can select the `Free form` policy and create fully-configurable clusters. * A user who has both cluster create permission and access to cluster policies can select the Free form policy and policies they have access to. * A user that has access to only cluster policies, can select the policies they have access to. ## Related Resources The following resources are often used in the same context: * Dynamic Passthrough Clusters for a Group guide * End to end workspace management guide * get_clusters data to retrieve a list of Cluster ids. * Cluster to create [Databricks Clusters](https://docs.databricks.com/clusters/index.html). * get_current_user data to retrieve information about User or databricks_service_principal, that is calling Databricks REST API. * GlobalInitScript to manage [global init scripts](https://docs.databricks.com/clusters/init-scripts.html#global-init-scripts), which are run on all Cluster and databricks_job. * InstancePool to manage [instance pools](https://docs.databricks.com/clusters/instance-pools/index.html) to reduce cluster start and auto-scaling times by maintaining a set of idle, ready-to-use instances. * InstanceProfile to manage AWS EC2 instance profiles that users can launch Cluster and access data, like databricks_mount. * IpAccessList to allow access from [predefined IP ranges](https://docs.databricks.com/security/network/ip-access-list.html). * Library to install a [library](https://docs.databricks.com/libraries/index.html) on databricks_cluster. * get_node_type data to get the smallest node type for Cluster that fits search criteria, like amount of RAM or number of cores. * Permissions to manage [access control](https://docs.databricks.com/security/access-control/index.html) in Databricks workspace. * get_spark_version data to get [Databricks Runtime (DBR)](https://docs.databricks.com/runtime/dbr.html) version that could be used for `spark_version` parameter in Cluster and other resources. * UserInstanceProfile to attach InstanceProfile (AWS) to databricks_user. * WorkspaceConf to manage workspace configuration for expert usage. ## Import The resource cluster policy can be imported using the policy idbash ```sh $ pulumi import databricks:index/clusterPolicy:ClusterPolicy this <cluster-policy-id> ``` :param str resource_name: The name of the resource. :param ClusterPolicyArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(ClusterPolicyArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, definition: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = ClusterPolicyArgs.__new__(ClusterPolicyArgs) __props__.__dict__["definition"] = definition __props__.__dict__["name"] = name __props__.__dict__["policy_id"] = None super(ClusterPolicy, __self__).__init__( 'databricks:index/clusterPolicy:ClusterPolicy', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, definition: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, policy_id: Optional[pulumi.Input[str]] = None) -> 'ClusterPolicy': """ Get an existing ClusterPolicy resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] definition: Policy definition JSON document expressed in [Databricks Policy Definition Language](https://docs.databricks.com/administration-guide/clusters/policies.html#cluster-policy-definition). :param pulumi.Input[str] name: Cluster policy name. This must be unique. Length must be between 1 and 100 characters. :param pulumi.Input[str] policy_id: Canonical unique identifier for the cluster policy. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _ClusterPolicyState.__new__(_ClusterPolicyState) __props__.__dict__["definition"] = definition __props__.__dict__["name"] = name __props__.__dict__["policy_id"] = policy_id return ClusterPolicy(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter def definition(self) -> pulumi.Output[Optional[str]]: """ Policy definition JSON document expressed in [Databricks Policy Definition Language](https://docs.databricks.com/administration-guide/clusters/policies.html#cluster-policy-definition). """ return pulumi.get(self, "definition") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ Cluster policy name. This must be unique. Length must be between 1 and 100 characters. """ return pulumi.get(self, "name") @property @pulumi.getter(name="policyId") def policy_id(self) -> pulumi.Output[str]: """ Canonical unique identifier for the cluster policy. """ return pulumi.get(self, "policy_id")

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null

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7

7222e9e5d68f07f50abb5c66e79c73ead5357524

193

py

Python

views.py

To-Gia-Hao/testing-01

a2deee4156c2cf82f9df88c0adb2f8b81d22f97c

[ "MIT" ]

null

views.py

To-Gia-Hao/testing-01

a2deee4156c2cf82f9df88c0adb2f8b81d22f97c

[ "MIT" ]

null

views.py

To-Gia-Hao/testing-01

a2deee4156c2cf82f9df88c0adb2f8b81d22f97c

[ "MIT" ]

null

from app import app from auth.views import * from upload_image.views import * from user.views import * @app.route("/", methods = ['GET', 'POST']) def index(): return 'hello world';

19.3

43

0.658031

27

193

4.666667

0.62963

0.261905

0.238095

0

0.196891

193

9

44

21.444444

0.812903

0

0.103261

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0.142857

0.857143

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null

0

1

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1

0

8

9d3bfa75ad32423e4d49ad1b538f61059f921607

94

py

Python

lib/nier/constructs/__main__.py

dskrypa/nier_replicant

c3d1fd3d58beafc19e3a0286f57ab09a3e91d8e1

[ "MIT" ]

null

lib/nier/constructs/__main__.py

dskrypa/nier_replicant

c3d1fd3d58beafc19e3a0286f57ab09a3e91d8e1

[ "MIT" ]

null

lib/nier/constructs/__main__.py

dskrypa/nier_replicant

c3d1fd3d58beafc19e3a0286f57ab09a3e91d8e1

[ "MIT" ]

null

from .adapters import * # noqa from .game_data import * # noqa from .utils import * # noqa

23.5

32

0.680851

13

94

4.846154

0.538462

0.47619

0.444444

0

0.223404

94

3

33

31.333333

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0.148936

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null

0

1

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0

7

9d546953004461b5d2843148012c3c41e3a47a8c

21,226

py

Python

restraintlib/lib/ribose_purine_terminal_C5.py

mkowiel/restraintlib

32de01d67ae290a45f3199e90c729acc258a6249

[ "BSD-3-Clause" ]

null

restraintlib/lib/ribose_purine_terminal_C5.py

mkowiel/restraintlib

32de01d67ae290a45f3199e90c729acc258a6249

[ "BSD-3-Clause" ]

1

2021-11-11T18:45:10.000Z

restraintlib/lib/ribose_purine_terminal_C5.py

mkowiel/restraintlib

32de01d67ae290a45f3199e90c729acc258a6249

[ "BSD-3-Clause" ]

null

RIBOSE_PURINE_TERMINAL_C5_PDB_CODES = ['A', 'G', 'IG'] RIBOSE_PURINE_TERMINAL_C5_ALL_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_CHI_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_SUGAR_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_GAMMA_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_PDB_CODES = RIBOSE_PURINE_TERMINAL_C5_PDB_CODES RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES = { "C1'": "C1'", "C1*": "C1'", "C2'": "C2'", "C2*": "C2'", "C3'": "C3'", "C3*": "C3'", "C4": "C4", "C4'": "C4'", "C4*": "C4'", "C5'": "C5'", "C5*": "C5'", "C8": "C8", "N9": "N9", "O2'": "O2'", "O2*": "O2'", "O3'": "O3'", "O3*": "O3'", "O4'": "O4'", "O4*": "O4'", "O5'": "O5'", "O5*": "O5'", "P": "P" } RIBOSE_PURINE_TERMINAL_C5_ALL_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_CHI_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_SUGAR_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_GAMMA_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_ATOM_NAMES = RIBOSE_PURINE_TERMINAL_C5_ATOM_NAMES RIBOSE_PURINE_TERMINAL_C5_ATOM_RES = { "C1'": 0, "C2'": 0, "C3'": 0, "C4": 0, "C4'": 0, "C5'": 0, "C8": 0, "N9": 0, "O2'": 0, "O3'": 0, "O4'": 0, "O5'": 0 } RIBOSE_PURINE_TERMINAL_C5_ALL_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_CHI_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_SUGAR_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_GAMMA_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_ATOM_RES = RIBOSE_PURINE_TERMINAL_C5_ATOM_RES RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION = [ ("C1'", "C2'", 2.0, 0, 0), ("C2'", "C3'", 2.0, 0, 0), ("C3'", "C4'", 2.0, 0, 0), ("C4'", "O4'", 2.0, 0, 0), ("C1'", "O4'", 2.0, 0, 0), ("C3'", "O3'", 2.0, 0, 0), ("C4'", "C5'", 2.0, 0, 0), ("C5'", "O5'", 2.0, 0, 0), ("C2'", "O2'", 2.0, 0, 0), ("C1'", 'N9', 2.0, 0, 0), ("O3'", 'P', 2.5, 0, 1) ] RIBOSE_PURINE_TERMINAL_C5_ALL_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CHI_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_SUGAR_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_GAMMA_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_REQUIRED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_REQUIRED_CONDITION RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION = [ ("O5'", 'P', 2.5, 0, 0) ] RIBOSE_PURINE_TERMINAL_C5_ALL_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CHI_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_SUGAR_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_GAMMA_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_DISALLOWED_CONDITION = RIBOSE_PURINE_TERMINAL_C5_DISALLOWED_CONDITION RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE = { 'measure': 'euclidean_angles', 'restraint_names': ["aC4'C5'O5'", "aC4'C3'O3'", "aN9C1'C2'", "aC1'N9C4", "aC1'N9C8", "aN9C1'O4'", "aC2'C1'O4'", "aC1'C2'O2'", "aC3'C2'O2'", "aC2'C3'O3'", "aC1'C2'C3'", "aC2'C3'C4'", "aC3'C4'O4'", "aC1'O4'C4'", "aC3'C4'C5'", "aC5'C4'O4'"] } RIBOSE_PURINE_TERMINAL_C5_ALL_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CHI_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_SUGAR_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_GAMMA_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE = { 'measure': 'euclidean_angles', 'restraint_names': ["tO4'C1'N9C4", "tC3'C4'C5'O5'", "pC1'C2'C3'C4'O4'"] } RIBOSE_PURINE_TERMINAL_C5_ALL_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CHI_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_GAMMA_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_CONDITION_DISTANCE_MEASURE = RIBOSE_PURINE_TERMINAL_C5_CONDITION_DISTANCE_MEASURE RIBOSE_PURINE_TERMINAL_C5_ALL_RESTRAINTS = [ { 'conditions': [], 'name': 'ribose_purine_terminal_C5==All=All', 'restraints': [['dist', "dC5'O5'", ["C5'", "O5'"], 1.421, 0.011], ['dist', "dC1'C2'", ["C1'", "C2'"], 1.525, 0.012], ['dist', "dC2'C3'", ["C2'", "C3'"], 1.523, 0.011]] } ] RIBOSE_PURINE_TERMINAL_C5_CHI_GAMMA_RESTRAINTS = [ { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 180, 22.5], ['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], 60, 8.75]], 'name': 'ribose_purine_terminal_C5==Chi=anti__Gamma=gauche+', 'restraints': [['angle', "aC4'C5'O5'", ["C4'", "C5'", "O5'"], 111.5, 1.7]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 180, 22.5], ['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], -60, 8.75]], 'name': 'ribose_purine_terminal_C5==Chi=anti__Gamma=gauche-', 'restraints': [['angle', "aC4'C5'O5'", ["C4'", "C5'", "O5'"], 109.7, 1.8]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 180, 22.5], ['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], 180, 21.25]], 'name': 'ribose_purine_terminal_C5==Chi=anti__Gamma=trans', 'restraints': [['angle', "aC4'C5'O5'", ["C4'", "C5'", "O5'"], 110.0, 1.9]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 0, 22.5], ['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], 60, 8.75]], 'name': 'ribose_purine_terminal_C5==Chi=syn__Gamma=gauche+', 'restraints': [['angle', "aC4'C5'O5'", ["C4'", "C5'", "O5'"], 112.8, 1.7]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 0, 22.5], ['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], -60, 8.75]], 'name': 'ribose_purine_terminal_C5==Chi=syn__Gamma=gauche-', 'restraints': [['angle', "aC4'C5'O5'", ["C4'", "C5'", "O5'"], 111.0, 0.8]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 0, 22.5], ['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], 180, 21.25]], 'name': 'ribose_purine_terminal_C5==Chi=syn__Gamma=trans', 'restraints': [['angle', "aC4'C5'O5'", ["C4'", "C5'", "O5'"], 111.1, 1.6]] } ] RIBOSE_PURINE_TERMINAL_C5_CHI_RESTRAINTS = [ { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 180, 22.5]], 'name': 'ribose_purine_terminal_C5==Chi=anti', 'restraints': [['angle', "aC4'C3'O3'", ["C4'", "C3'", "O3'"], 110.7, 2.3]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 0, 22.5]], 'name': 'ribose_purine_terminal_C5==Chi=syn', 'restraints': [['angle', "aC4'C3'O3'", ["C4'", "C3'", "O3'"], 109.8, 2.1]] } ] RIBOSE_PURINE_TERMINAL_C5_BASE_FUNC_OF_TORSION_CHI_RESTRAINTS = [ { 'conditions': [], 'name': 'ribose_purine_terminal_C5==Base=purine', 'restraints': [ ['angle', "aN9C1'C2'", ['N9', "C1'", "C2'"], None, None, None, None, "purine-N1-C1'-C2' or N9-C1'-C2'.pickle", ['torsion_chi', ["O4'", "C1'", 'N9', 'C4']]], ['angle', "aC1'N9C4", ["C1'", 'N9', 'C4'], None, None, None, None, "purine-C1'-N1-C2 or C1'-N9-C4.pickle", ['torsion_chi', ["O4'", "C1'", 'N9', 'C4']]], ['angle', "aC1'N9C8", ["C1'", 'N9', 'C8'], None, None, None, None, "purine-C1'-N1-C6 or C1'-N9-C8.pickle", ['torsion_chi', ["O4'", "C1'", 'N9', 'C4']]], ['angle', "aN9C1'O4'", ['N9', "C1'", "O4'"], None, None, None, None, "purine-N1-C1'-O4' or N9-C1'-O4'.pickle", ['torsion_chi', ["O4'", "C1'", 'N9', 'C4']]]] } ] RIBOSE_PURINE_TERMINAL_C5_CONFORMATION_RESTRAINTS = [ { 'conditions': [['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 162, 4.5]], 'name': "ribose_purine_terminal_C5==Conformation=C2'-endo", 'restraints': [['dist', "dC3'C4'", ["C3'", "C4'"], 1.527, 0.01], ['dist', "dC2'O2'", ["C2'", "O2'"], 1.41, 0.009], ['angle', "aC2'C1'O4'", ["C2'", "C1'", "O4'"], 106.0, 0.8]] }, { 'conditions': [['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 18, 4.5]], 'name': "ribose_purine_terminal_C5==Conformation=C3'-endo", 'restraints': [['dist', "dC3'C4'", ["C3'", "C4'"], 1.52, 0.009], ['dist', "dC2'O2'", ["C2'", "O2'"], 1.416, 0.008], ['angle', "aC2'C1'O4'", ["C2'", "C1'", "O4'"], 107.3, 0.6]] }, { 'conditions': [], 'name': 'ribose_purine_terminal_C5==Conformation=Other', 'restraints': [['dist', "dC3'C4'", ["C3'", "C4'"], 1.531, 0.009], ['dist', "dC2'O2'", ["C2'", "O2'"], 1.413, 0.008], ['angle', "aC2'C1'O4'", ["C2'", "C1'", "O4'"], 106.2, 1.3]] } ] RIBOSE_PURINE_TERMINAL_C5_SUGAR_RESTRAINTS = [{ 'conditions': [], 'name': 'ribose_purine_terminal_C5==Sugar=ribose', 'restraints': [['dist', "dC4'O4'", ["C4'", "O4'"], 1.45, 0.009]] } ] RIBOSE_PURINE_TERMINAL_C5_CHI_CONFORMATION_RESTRAINTS = [ { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 180, 22.5], ['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 162, 4.5]], 'name': "ribose_purine_terminal_C5==Chi=anti__Conformation=C2'-endo", 'restraints': [ ['angle', "aC1'C2'O2'", ["C1'", "C2'", "O2'"], 112.0, 2.1], ['angle', "aC3'C2'O2'", ["C3'", "C2'", "O2'"], 113.6, 2.5], ['angle', "aC2'C3'O3'", ["C2'", "C3'", "O3'"], 109.4, 2.4]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 180, 22.5], ['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 18, 4.5]], 'name': "ribose_purine_terminal_C5==Chi=anti__Conformation=C3'-endo", 'restraints': [ ['angle', "aC1'C2'O2'", ["C1'", "C2'", "O2'"], 108.7, 2.3], ['angle', "aC3'C2'O2'", ["C3'", "C2'", "O2'"], 110.4, 2.1], ['angle', "aC2'C3'O3'", ["C2'", "C3'", "O3'"], 113.4, 2.1]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 180, 22.5]], 'name': 'ribose_purine_terminal_C5==Chi=anti__Conformation=Other', 'restraints': [ ['angle', "aC1'C2'O2'", ["C1'", "C2'", "O2'"], 112.9, 1.4], ['angle', "aC3'C2'O2'", ["C3'", "C2'", "O2'"], 113.3, 0.9], ['angle', "aC2'C3'O3'", ["C2'", "C3'", "O3'"], 111.9, 2.5]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 0, 22.5], ['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 162, 4.5]], 'name': "ribose_purine_terminal_C5==Chi=syn__Conformation=C2'-endo", 'restraints': [ ['angle', "aC1'C2'O2'", ["C1'", "C2'", "O2'"], 112.5, 2.1], ['angle', "aC3'C2'O2'", ["C3'", "C2'", "O2'"], 114.1, 1.9], ['angle', "aC2'C3'O3'", ["C2'", "C3'", "O3'"], 110.1, 2.2]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 0, 22.5], ['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 18, 4.5]], 'name': "ribose_purine_terminal_C5==Chi=syn__Conformation=C3'-endo", 'restraints': [ ['angle', "aC1'C2'O2'", ["C1'", "C2'", "O2'"], 109.9, 2.7], ['angle', "aC3'C2'O2'", ["C3'", "C2'", "O2'"], 110.0, 2.0], ['angle', "aC2'C3'O3'", ["C2'", "C3'", "O3'"], 114.2, 0.9]] }, { 'conditions': [['torsion', "tO4'C1'N9C4", ["O4'", "C1'", 'N9', 'C4'], 0, 22.5]], 'name': 'ribose_purine_terminal_C5==Chi=syn__Conformation=Other', 'restraints': [ ['angle', "aC1'C2'O2'", ["C1'", "C2'", "O2'"], 107.7, 1.6], ['angle', "aC3'C2'O2'", ["C3'", "C2'", "O2'"], 111.9, 1.1], ['angle', "aC2'C3'O3'", ["C2'", "C3'", "O3'"], 113.0, 1.7]] } ] RIBOSE_PURINE_TERMINAL_C5_SUGAR_CONFORMATION_FUNC_OF_TAU_MAX_RESTRAINTS = [ { 'conditions': [['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 162, 4.5]], 'name': "ribose_purine_terminal_C5==Sugar=ribose__Conformation=C2'-endo", 'restraints': [ ['angle', "aC1'C2'C3'", ["C1'", "C2'", "C3'"], None, None, None, None, "ribose-C2'-endo-C1'-C2'-C3'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC2'C3'C4'", ["C2'", "C3'", "C4'"], None, None, None, None, "ribose-C2'-endo-C2'-C3'-C4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC3'C4'O4'", ["C3'", "C4'", "O4'"], None, None, None, None, "ribose-C2'-endo-C3'-C4'-O4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC1'O4'C4'", ["C1'", "O4'", "C4'"], None, None, None, None, "ribose-C2'-endo-C1'-O4'-C4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]]] }, { 'conditions': [['pseudorotation', "pC1'C2'C3'C4'O4'", ["C1'", "C2'", "C3'", "C4'", "O4'"], 18, 4.5]], 'name': "ribose_purine_terminal_C5==Sugar=ribose__Conformation=C3'-endo", 'restraints': [ ['angle', "aC1'C2'C3'", ["C1'", "C2'", "C3'"], None, None, None, None, "ribose-C3'-endo-C1'-C2'-C3'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC2'C3'C4'", ["C2'", "C3'", "C4'"], None, None, None, None, "ribose-C3'-endo-C2'-C3'-C4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC3'C4'O4'", ["C3'", "C4'", "O4'"], None, None, None, None, "ribose-C3'-endo-C3'-C4'-O4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC1'O4'C4'", ["C1'", "O4'", "C4'"], None, None, None, None, "ribose-C3'-endo-C1'-O4'-C4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]]] }, { 'conditions': [], 'name': 'ribose_purine_terminal_C5==Sugar=ribose__Conformation=Other', 'restraints': [ ['angle', "aC1'C2'C3'", ["C1'", "C2'", "C3'"], None, None, None, None, "ribose-Other-C1'-C2'-C3'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC2'C3'C4'", ["C2'", "C3'", "C4'"], None, None, None, None, "ribose-Other-C2'-C3'-C4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC3'C4'O4'", ["C3'", "C4'", "O4'"], None, None, None, None, "ribose-Other-C3'-C4'-O4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]], ['angle', "aC1'O4'C4'", ["C1'", "O4'", "C4'"], None, None, None, None, "ribose-Other-C1'-O4'-C4'.pickle", ['tau_max', ["C1'", "C2'", "C3'", "C4'", "O4'"]]]] } ] RIBOSE_PURINE_TERMINAL_C5_GAMMA_RESTRAINTS = [ { 'conditions': [['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], 60, 8.75]], 'name': 'ribose_purine_terminal_C5==Gamma=gauche+', 'restraints': [['dist', "dC4'C5'", ["C4'", "C5'"], 1.508, 0.009], ['angle', "aC3'C4'C5'", ["C3'", "C4'", "C5'"], 115.7, 1.2], ['angle', "aC5'C4'O4'", ["C5'", "C4'", "O4'"], 109.4, 1.0]] }, { 'conditions': [['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], -60, 8.75]], 'name': 'ribose_purine_terminal_C5==Gamma=gauche-', 'restraints': [['dist', "dC4'C5'", ["C4'", "C5'"], 1.518, 0.009], ['angle', "aC3'C4'C5'", ["C3'", "C4'", "C5'"], 114.5, 1.2], ['angle', "aC5'C4'O4'", ["C5'", "C4'", "O4'"], 107.8, 0.9]] }, { 'conditions': [['torsion', "tC3'C4'C5'O5'", ["C3'", "C4'", "C5'", "O5'"], 180, 21.25]], 'name': 'ribose_purine_terminal_C5==Gamma=trans', 'restraints': [['dist', "dC4'C5'", ["C4'", "C5'"], 1.509, 0.01], ['angle', "aC3'C4'C5'", ["C3'", "C4'", "C5'"], 113.8, 1.3], ['angle', "aC5'C4'O4'", ["C5'", "C4'", "O4'"], 109.9, 1.2]] } ] RIBOSE_PURINE_TERMINAL_C5_ALL_FUNC_OF_TORSION_CHI_RESTRAINTS = [ { 'conditions': [], 'name': 'ribose_purine_terminal_C5==All=All', 'restraints': [ ['dist', "dC1'N9", ["C1'", 'N9'], None, None, None, None, "All-C1'-N1 or C1'-N9.pickle", ['torsion_chi', ["O4'", "C1'", 'N9', 'C4']]], ['dist', "dC1'O4'", ["C1'", "O4'"], None, None, None, None, "All-C1'-O4'.pickle", ['torsion_chi', ["O4'", "C1'", 'N9', 'C4']]]] } ]

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c21661a85d7577ee8bc6405c5c73c7162c9572a4

4,144

py

Python

tests/functional/rpc/test_chain.py

btclib-org/btclib_node

3e5b2a55195e60e1d30505b52bc1ddd8d51c74cf

[ "MIT" ]

4

2021-01-25T23:39:13.000Z

2021-08-08T06:27:53.000Z

tests/functional/rpc/test_chain.py

btclib-org/btclib_node

3e5b2a55195e60e1d30505b52bc1ddd8d51c74cf

[ "MIT" ]

null

tests/functional/rpc/test_chain.py

btclib-org/btclib_node

3e5b2a55195e60e1d30505b52bc1ddd8d51c74cf

[ "MIT" ]

1

2020-12-18T06:28:18.000Z

import json import requests from btclib_node import Node from btclib_node.chains import RegTest from btclib_node.config import Config from tests.helpers import generate_random_header_chain, get_random_port, wait_until def test_best_block_hash(tmp_path): node = Node( config=Config( chain="regtest", data_dir=tmp_path, allow_p2p=False, rpc_port=get_random_port(), ) ) node.start() wait_until(lambda: node.rpc_manager.is_alive()) chain = generate_random_header_chain(2000, RegTest().genesis.hash) node.index.add_headers(chain) response = json.loads( requests.post( url=f"http://127.0.0.1:{node.rpc_port}", data=json.dumps( { "jsonrpc": "1.0", "id": "pytest", "method": "getbestblockhash", } ).encode(), headers={"Content-Type": "text/plain"}, ).text ) assert response["result"] == chain[-1].hash node.stop() def test_block_hash(tmp_path): node = Node( config=Config( chain="regtest", data_dir=tmp_path, allow_p2p=False, rpc_port=get_random_port(), ) ) node.start() wait_until(lambda: node.rpc_manager.is_alive()) chain = generate_random_header_chain(2000, RegTest().genesis.hash) node.index.add_headers(chain) response = json.loads( requests.post( url=f"http://127.0.0.1:{node.rpc_port}", data=json.dumps( { "jsonrpc": "1.0", "id": "pytest", "method": "getblockhash", "params": [2000], } ).encode(), headers={"Content-Type": "text/plain"}, ).text ) assert response["result"] == chain[-1].hash node.stop() def test_block_header_last(tmp_path): node = Node( config=Config( chain="regtest", data_dir=tmp_path, allow_p2p=False, rpc_port=get_random_port(), ) ) node.start() wait_until(lambda: node.rpc_manager.is_alive()) chain = generate_random_header_chain(2000, RegTest().genesis.hash) node.index.add_headers(chain) response = json.loads( requests.post( url=f"http://127.0.0.1:{node.rpc_port}", data=json.dumps( { "jsonrpc": "1.0", "id": "pytest", "method": "getblockheader", "params": [chain[-1].hash], } ).encode(), headers={"Content-Type": "text/plain"}, ).text ) assert response["result"]["hash"] == chain[-1].hash assert response["result"]["height"] == 2000 assert response["result"]["previousblockhash"] == chain[-2].hash assert "nextblockhash" not in response["result"] node.stop() def test_block_header_middle(tmp_path): node = Node( config=Config( chain="regtest", data_dir=tmp_path, allow_p2p=False, rpc_port=get_random_port(), ) ) node.start() wait_until(lambda: node.rpc_manager.is_alive()) chain = generate_random_header_chain(2000, RegTest().genesis.hash) node.index.add_headers(chain) response = json.loads( requests.post( url=f"http://127.0.0.1:{node.rpc_port}", data=json.dumps( { "jsonrpc": "1.0", "id": "pytest", "method": "getblockheader", "params": [chain[-1001].hash], } ).encode(), headers={"Content-Type": "text/plain"}, ).text ) assert response["result"]["hash"] == chain[-1001].hash assert response["result"]["height"] == 1000 assert response["result"]["previousblockhash"] == chain[-1002].hash assert response["result"]["nextblockhash"] == chain[-1000].hash node.stop()

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null

0

1

0

1

0

null

0

7

c22f29803112b1be49d56ce4cd56e3e69b29feee

17,969

py

Python

functions/score_calc.py

adisen99/srfp

836059c942b396a5e70d36a0d544d0fa4a36272d

[ "MIT" ]

null

functions/score_calc.py

adisen99/srfp

836059c942b396a5e70d36a0d544d0fa4a36272d

[ "MIT" ]

null

functions/score_calc.py

adisen99/srfp

836059c942b396a5e70d36a0d544d0fa4a36272d

[ "MIT" ]

null

""" Python module to calculate the score for critical, very unhealthy and unhealthy air quality """ import numpy as np import pandas as pd # SCore calc for Critical Conditions (severe conditions only) def get_critical_score(data): temp = data.copy(deep=True) conditions1 = [ (temp['quality_mod_pm25'] == 5) & (temp['quality_obs_pm25'] == 5), (temp['quality_mod_pm25'] == 5) & (temp['quality_obs_pm25'] != 5), (temp['quality_mod_pm25'] != 5) & (temp['quality_obs_pm25'] == 5), (temp['quality_mod_pm25'] != 5) & (temp['quality_obs_pm25'] != 5)] choices1 = ['a', 'b', 'c', 'd'] conditions2 = [ (temp['quality_mod_pm10'] == 5) & (temp['quality_obs_pm10'] == 5), (temp['quality_mod_pm10'] == 5) & (temp['quality_obs_pm10'] != 5), (temp['quality_mod_pm10'] != 5) & (temp['quality_obs_pm10'] == 5), (temp['quality_mod_pm10'] != 5) & (temp['quality_obs_pm10'] != 5)] choices2 = ['a', 'b', 'c', 'd'] temp['category_pm25'] = np.select(conditions1, choices1, default=np.nan) temp['category_pm10'] = np.select(conditions2, choices2, default=np.nan) test1 = temp.groupby('category_pm25') test2 = temp.groupby('category_pm10') # Need to write a program to give appropriate values to a,b,c and d key25 = [] key10 = [] for i in range(0, len(list(test1))): key25.append(list(test1)[i][0]) for i in range(0, len(list(test2))): key10.append(list(test2)[i][0]) val25 = [] val10 = [] for i in range(0, len(key25)): val25.append(list(test1)[i][1].shape[0]) for i in range(0, len(key10)): val10.append(list(test2)[i][1].shape[0]) res25 = dict(zip(key25, val25)) res10 = dict(zip(key10, val10)) expected = ['a', 'b', 'c', 'd'] for j in expected: if j not in res25.keys(): new25 = {j: 0} res25.update(new25) else: pass for j in expected: if j not in res10.keys(): new10 = {j: 0} res10.update(new10) else: pass print("Key25 is : ", key25) print("The list25 from algorithm is : ", res25.keys()) print("val25 is : ", res25.values()) print("Key10 is : ", key10) print("The list10 from algorithm is : ", res10.keys()) print("Val10 is : ", res10.values()) a = res25['a'] b = res25['b'] c = res25['c'] d = res25['d'] A = ((a + d)/(a+b+c+d)) * 100 # Accuracy of events if a != 0 or b != 0: FAR = ((b)/(a+b)) * 100 # False event forecase if a != 0 or c != 0: POD = ((a)/(a+c)) * 100 # Expected events try: CSI = ((a)/(a+b+c)) * 100 # Events and event forecasts that were hits pointer1 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer1 = 1 if a != 0 or c != 0: FOM = ((c)/(a+c))*100 # Surprise events if a != 0 or b != 0: FOH = ((a)/(a+b))*100 # Correct event forecasts if b != 0 or d != 0: PON = ((d)/(b+d))*100 # Expected non events POFD = ((b)/(b+d))*100 # Unexpected non events if c != 0 or d != 0: DFR = ((c)/(c+d))*100 # False non-event forecasts FOCN = ((d)/(c+d))*100 # Correct non-event forecasts try: # True skill statistic (Expected events - unexpected non-events) TSS = ((a)/(a+c)) - ((b)/(b+d)) Heidke = (((a+c)*(d-b))+((a-c)*(d+b)))/(((a+c)*(c+d))+((a+b)*(b+d))) pointer2 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer2 = 1 print("Performance metrics or Skill score for Critical PM2.5 are:\n") print("A = ", A) if a != 0 or b != 0: print("FAR = ", FAR) if a != 0 or c != 0: print("POD = ", POD) if pointer1 == 0: print("CSI = ", CSI) if a != 0 or c != 0: print("FOM = ", FOM) if a != 0 or b != 0: print("FOH = ", FOH) if b != 0 or d != 0: print("PON = ", PON) print("POFD = ", POFD) if c != 0 or d != 0: print("DFR = ", DFR) print("FOCN = ", FOCN) if pointer2 == 0: print("TSS = ", TSS) print("Heidke = ", Heidke, "\n") a = res10['a'] b = res10['b'] c = res10['c'] d = res10['d'] A = ((a + d)/(a+b+c+d)) * 100 # Accuracy of events if a != 0 or b != 0: FAR = ((b)/(a+b)) * 100 # False event forecase if a != 0 or c != 0: POD = ((a)/(a+c)) * 100 # Expected events try: CSI = ((a)/(a+b+c)) * 100 # Events and event forecasts that were hits pointer1 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer1 = 1 if a != 0 or c != 0: FOM = ((c)/(a+c))*100 # Surprise events if a != 0 or b != 0: FOH = ((a)/(a+b))*100 # Correct event forecasts if b != 0 or d != 0: PON = ((d)/(b+d))*100 # Expected non events POFD = ((b)/(b+d))*100 # Unexpected non events if c != 0 or d != 0: DFR = ((c)/(c+d))*100 # False non-event forecasts FOCN = ((d)/(c+d))*100 # Correct non-event forecasts try: # True skill statistic (Expected events - unexpected non-events) TSS = ((a)/(a+c)) - ((b)/(b+d)) Heidke = (((a+c)*(d-b))+((a-c)*(d+b)))/(((a+c)*(c+d))+((a+b)*(b+d))) pointer2 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer2 = 1 print("Performance metrics or Skill score for Critical PM10 are:\n") print("A = ", A) if a != 0 or b != 0: print("FAR = ", FAR) if a != 0 or c != 0: print("POD = ", POD) if pointer1 == 0: print("CSI = ", CSI) if a != 0 or c != 0: print("FOM = ", FOM) if a != 0 or b != 0: print("FOH = ", FOH) if b != 0 or d != 0: print("PON = ", PON) print("POFD = ", POFD) if c != 0 or d != 0: print("DFR = ", DFR) print("FOCN = ", FOCN) if pointer2 == 0: print("TSS = ", TSS) print("Heidke = ", Heidke, "\n") # SCore calc for Very Unhealthy Conditions (very poor, severe conditions only) def get_veryunhealthy_score(data): temp = data.copy(deep=True) conditions1 = [ (temp['quality_mod_pm25'] >= 4) & (temp['quality_obs_pm25'] >= 4), (temp['quality_mod_pm25'] >= 4) & (temp['quality_obs_pm25'] < 4), (temp['quality_mod_pm25'] < 4) & (temp['quality_obs_pm25'] >= 4), (temp['quality_mod_pm25'] < 4) & (temp['quality_obs_pm25'] < 4)] choices1 = ['a', 'b', 'c', 'd'] conditions2 = [ (temp['quality_mod_pm10'] >= 4) & (temp['quality_obs_pm10'] >= 4), (temp['quality_mod_pm10'] >= 4) & (temp['quality_obs_pm10'] < 4), (temp['quality_mod_pm10'] < 4) & (temp['quality_obs_pm10'] >= 4), (temp['quality_mod_pm10'] < 4) & (temp['quality_obs_pm10'] < 4)] choices2 = ['a', 'b', 'c', 'd'] temp['category_pm25'] = np.select(conditions1, choices1, default=np.nan) temp['category_pm10'] = np.select(conditions2, choices2, default=np.nan) test1 = temp.groupby('category_pm25') test2 = temp.groupby('category_pm10') # Need to write a program to give appropriate values to a,b,c and d key25 = [] key10 = [] for i in range(0, len(list(test1))): key25.append(list(test1)[i][0]) for i in range(0, len(list(test2))): key10.append(list(test2)[i][0]) val25 = [] val10 = [] for i in range(0, len(key25)): val25.append(list(test1)[i][1].shape[0]) for i in range(0, len(key10)): val10.append(list(test2)[i][1].shape[0]) res25 = dict(zip(key25, val25)) res10 = dict(zip(key10, val10)) expected = ['a', 'b', 'c', 'd'] for j in expected: if j not in res25.keys(): new25 = {j: 0} res25.update(new25) else: pass for j in expected: if j not in res10.keys(): new10 = {j: 0} res10.update(new10) else: pass print("Key25 is : ", key25) print("The list25 from algorithm is : ", res25.keys()) print("val25 is : ", res25.values()) print("Key10 is : ", key10) print("The list10 from algorithm is : ", res10.keys()) print("Val10 is : ", res10.values()) a = res25['a'] b = res25['b'] c = res25['c'] d = res25['d'] A = ((a + d)/(a+b+c+d)) * 100 # Accuracy of events if a != 0 or b != 0: FAR = ((b)/(a+b)) * 100 # False event forecase if a != 0 or c != 0: POD = ((a)/(a+c)) * 100 # Expected events try: CSI = ((a)/(a+b+c)) * 100 # Events and event forecasts that were hits pointer1 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer1 = 1 if a != 0 or c != 0: FOM = ((c)/(a+c))*100 # Surprise events if a != 0 or b != 0: FOH = ((a)/(a+b))*100 # Correct event forecasts if b != 0 or d != 0: PON = ((d)/(b+d))*100 # Expected non events POFD = ((b)/(b+d))*100 # Unexpected non events if c != 0 or d != 0: DFR = ((c)/(c+d))*100 # False non-event forecasts FOCN = ((d)/(c+d))*100 # Correct non-event forecasts try: # True skill statistic (Expected events - unexpected non-events) TSS = ((a)/(a+c)) - ((b)/(b+d)) Heidke = (((a+c)*(d-b))+((a-c)*(d+b)))/(((a+c)*(c+d))+((a+b)*(b+d))) pointer2 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer2 = 1 print("Performance metrics or Skill score for Very Unhealthy PM2.5 are:\n") print("A = ", A) if a != 0 or b != 0: print("FAR = ", FAR) if a != 0 or c != 0: print("POD = ", POD) if pointer1 == 0: print("CSI = ", CSI) if a != 0 or c != 0: print("FOM = ", FOM) if a != 0 or b != 0: print("FOH = ", FOH) if b != 0 or d != 0: print("PON = ", PON) print("POFD = ", POFD) if c != 0 or d != 0: print("DFR = ", DFR) print("FOCN = ", FOCN) if pointer2 == 0: print("TSS = ", TSS) print("Heidke = ", Heidke, "\n") a = res10['a'] b = res10['b'] c = res10['c'] d = res10['d'] A = ((a + d)/(a+b+c+d)) * 100 # Accuracy of events if a != 0 or b != 0: FAR = ((b)/(a+b)) * 100 # False event forecase if a != 0 or c != 0: POD = ((a)/(a+c)) * 100 # Expected events try: CSI = ((a)/(a+b+c)) * 100 # Events and event forecasts that were hits pointer1 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer1 = 1 if a != 0 or c != 0: FOM = ((c)/(a+c))*100 # Surprise events if a != 0 or b != 0: FOH = ((a)/(a+b))*100 # Correct event forecasts if b != 0 or d != 0: PON = ((d)/(b+d))*100 # Expected non events POFD = ((b)/(b+d))*100 # Unexpected non events if c != 0 or d != 0: DFR = ((c)/(c+d))*100 # False non-event forecasts FOCN = ((d)/(c+d))*100 # Correct non-event forecasts try: # True skill statistic (Expected events - unexpected non-events) TSS = ((a)/(a+c)) - ((b)/(b+d)) Heidke = (((a+c)*(d-b))+((a-c)*(d+b)))/(((a+c)*(c+d))+((a+b)*(b+d))) pointer2 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer2 = 1 print("Performance metrics or Skill score for Very Unhealthy PM10 are:\n") print("A = ", A) if a != 0 or b != 0: print("FAR = ", FAR) if a != 0 or c != 0: print("POD = ", POD) if pointer1 == 0: print("CSI = ", CSI) if a != 0 or c != 0: print("FOM = ", FOM) if a != 0 or b != 0: print("FOH = ", FOH) if b != 0 or d != 0: print("PON = ", PON) print("POFD = ", POFD) if c != 0 or d != 0: print("DFR = ", DFR) print("FOCN = ", FOCN) if pointer2 == 0: print("TSS = ", TSS) print("Heidke = ", Heidke, "\n") # SCore calc for Unhealthy Conditions (very poor, severe conditions only) def get_unhealthy_score(data): temp = data.copy(deep=True) conditions1 = [ (temp['quality_mod_pm25'] >= 3) & (temp['quality_obs_pm25'] >= 3), (temp['quality_mod_pm25'] >= 3) & (temp['quality_obs_pm25'] < 3), (temp['quality_mod_pm25'] < 3) & (temp['quality_obs_pm25'] >= 3), (temp['quality_mod_pm25'] < 3) & (temp['quality_obs_pm25'] < 3)] choices1 = ['a', 'b', 'c', 'd'] conditions2 = [ (temp['quality_mod_pm10'] >= 3) & (temp['quality_obs_pm10'] >= 3), (temp['quality_mod_pm10'] >= 3) & (temp['quality_obs_pm10'] < 3), (temp['quality_mod_pm10'] < 3) & (temp['quality_obs_pm10'] >= 3), (temp['quality_mod_pm10'] < 3) & (temp['quality_obs_pm10'] < 3)] choices2 = ['a', 'b', 'c', 'd'] temp['category_pm25'] = np.select(conditions1, choices1, default=np.nan) temp['category_pm10'] = np.select(conditions2, choices2, default=np.nan) test1 = temp.groupby('category_pm25') test2 = temp.groupby('category_pm10') # Need to write a program to give appropriate values to a,b,c and d key25 = [] key10 = [] for i in range(0, len(list(test1))): key25.append(list(test1)[i][0]) for i in range(0, len(list(test2))): key10.append(list(test2)[i][0]) val25 = [] val10 = [] for i in range(0, len(key25)): val25.append(list(test1)[i][1].shape[0]) for i in range(0, len(key10)): val10.append(list(test2)[i][1].shape[0]) res25 = dict(zip(key25, val25)) res10 = dict(zip(key10, val10)) expected = ['a', 'b', 'c', 'd'] for j in expected: if j not in res25.keys(): new25 = {j: 0} res25.update(new25) else: pass for j in expected: if j not in res10.keys(): new10 = {j: 0} res10.update(new10) else: pass print("Key25 is : ", key25) print("The list25 from algorithm is : ", res25.keys()) print("val25 is : ", res25.values()) print("Key10 is : ", key10) print("The list10 from algorithm is : ", res10.keys()) print("Val10 is : ", res10.values()) a = res25['a'] b = res25['b'] c = res25['c'] d = res25['d'] A = ((a + d)/(a+b+c+d)) * 100 # Accuracy of events if a != 0 or b != 0: FAR = ((b)/(a+b)) * 100 # False event forecase if a != 0 or c != 0: POD = ((a)/(a+c)) * 100 # Expected events try: CSI = ((a)/(a+b+c)) * 100 # Events and event forecasts that were hits pointer1 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer1 = 1 if a != 0 or c != 0: FOM = ((c)/(a+c))*100 # Surprise events if a != 0 or b != 0: FOH = ((a)/(a+b))*100 # Correct event forecasts if b != 0 or d != 0: PON = ((d)/(b+d))*100 # Expected non events POFD = ((b)/(b+d))*100 # Unexpected non events if c != 0 or d != 0: DFR = ((c)/(c+d))*100 # False non-event forecasts FOCN = ((d)/(c+d))*100 # Correct non-event forecasts try: # True skill statistic (Expected events - unexpected non-events) TSS = ((a)/(a+c)) - ((b)/(b+d)) Heidke = (((a+c)*(d-b))+((a-c)*(d+b)))/(((a+c)*(c+d))+((a+b)*(b+d))) pointer2 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer2 = 1 print("Performance metrics or Skill score for Unhealthy PM2.5 are:\n") print("A = ", A) if a != 0 or b != 0: print("FAR = ", FAR) if a != 0 or c != 0: print("POD = ", POD) if pointer1 == 0: print("CSI = ", CSI) if a != 0 or c != 0: print("FOM = ", FOM) if a != 0 or b != 0: print("FOH = ", FOH) if b != 0 or d != 0: print("PON = ", PON) print("POFD = ", POFD) if c != 0 or d != 0: print("DFR = ", DFR) print("FOCN = ", FOCN) if pointer2 == 0: print("TSS = ", TSS) print("Heidke = ", Heidke, "\n") a = res10['a'] b = res10['b'] c = res10['c'] d = res10['d'] A = ((a + d)/(a+b+c+d)) * 100 # Accuracy of events if a != 0 or b != 0: FAR = ((b)/(a+b)) * 100 # False event forecase if a != 0 or c != 0: POD = ((a)/(a+c)) * 100 # Expected events try: CSI = ((a)/(a+b+c)) * 100 # Events and event forecasts that were hits pointer1 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer1 = 1 if a != 0 or c != 0: FOM = ((c)/(a+c))*100 # Surprise events if a != 0 or b != 0: FOH = ((a)/(a+b))*100 # Correct event forecasts if b != 0 or d != 0: PON = ((d)/(b+d))*100 # Expected non events POFD = ((b)/(b+d))*100 # Unexpected non events if c != 0 or d != 0: DFR = ((c)/(c+d))*100 # False non-event forecasts FOCN = ((d)/(c+d))*100 # Correct non-event forecasts try: # True skill statistic (Expected events - unexpected non-events) TSS = ((a)/(a+c)) - ((b)/(b+d)) Heidke = (((a+c)*(d-b))+((a-c)*(d+b)))/(((a+c)*(c+d))+((a+b)*(b+d))) pointer2 = 0 except ZeroDivisionError: print("ZeroDivisionError") pointer2 = 1 print("Performance metrics or Skill score for Unhealthy PM10 are:\n") print("A = ", A) if a != 0 or b != 0: print("FAR = ", FAR) if a != 0 or c != 0: print("POD = ", POD) if pointer1 == 0: print("CSI = ", CSI) if a != 0 or c != 0: print("FOM = ", FOM) if a != 0 or b != 0: print("FOH = ", FOH) if b != 0 or d != 0: print("PON = ", PON) print("POFD = ", POFD) if c != 0 or d != 0: print("DFR = ", DFR) print("FOCN = ", FOCN) if pointer2 == 0: print("TSS = ", TSS) print("Heidke = ", Heidke, "\n")

31.088235

79

0.498414

2,594

17,969

3.408635

0.050887

0.024429

0.021715

0.032572

0.980547

0.977607

0.965619

0

0.074649

0.311147

17,969

577

80

31.142114

0.639683

0.127275

0

0.926004

0

0.149907

0

1

0.006342

false

0.012685

0.004228

0

0.010571

0.22833

0

null

0

1

0

1

0

null

0

7

c24aae6a3d48138a9eb9158cb37a42cd9d3087c4

4,566

py

Python

Sampling.py

GrzegorzMika/Markov-Chains-Monte-Carlo

29754eab860036d518d36a9654f904b3a2f59647

[ "MIT" ]

null

Sampling.py

GrzegorzMika/Markov-Chains-Monte-Carlo

29754eab860036d518d36a9654f904b3a2f59647

[ "MIT" ]

null

Sampling.py

GrzegorzMika/Markov-Chains-Monte-Carlo

29754eab860036d518d36a9654f904b3a2f59647

[ "MIT" ]

null

from typing import Optional, List, Tuple, Union, Callable import numpy as np from ProposalDistribution import ProposalDistribution # TODO: deal with overflow class MetropolisHastingsSymmetric: def __init__(self, target: Callable, proposal: ProposalDistribution, initial: Optional[Union[float, np.ndarray]] = None, shape: Optional[Union[Tuple[int], List[int]]] = None): self.target: Callable = target self.proposal: ProposalDistribution = proposal self.accepted: float = 0 self.sample: Optional[np.ndarray] = None self.used: bool = False assert initial is not None or shape, 'At least one of the initial or shape arguments must be specified!' if initial is not None: self.initial: np.ndarray = np.array(initial) else: self.initial: np.ndarray = np.random.uniform(low=-1, high=1, size=shape) def run(self, size: int, burnin: Optional[int] = 1000, thinning: Optional[int] = None, verbose: int = 0): if self.used: self.initial = self.sample[-1] burnin = 0 self.sample = np.empty((size + burnin, *self.initial.shape)) self.sample[0] = self.initial u = np.random.uniform(0, 1, size + burnin) counter = 0 for i in range(1, burnin): current_x = self.sample[i - 1] proposed = self.proposal.sample(current_x) a = np.min([1, self.target(proposed) / self.target(current_x)]) if u[i] < a: self.sample[i] = proposed else: self.sample[i] = current_x for i in range(burnin + 1, size + burnin): current_x = self.sample[i - 1] proposed = self.proposal.sample(current_x) a = np.min([1, self.target(proposed) / self.target(current_x)]) if u[i] < a: counter += 1 self.sample[i] = proposed else: self.sample[i] = current_x self.accepted = counter / size * 100 if verbose > 0: print("Proportion of samples accepted: {}%".format(round(counter / size * 100, 2))) self.used = True return self.sample[burnin:][::thinning] class MetropolisHastings: def __init__(self, target: Callable, proposal: ProposalDistribution, initial: Optional[Union[float, np.ndarray]] = None, shape: Optional[Union[Tuple[int], List[int]]] = None): self.target: Callable = target self.proposal: ProposalDistribution = proposal self.accepted: float = 0 self.sample: Optional[np.ndarray] = None self.used: bool = False assert initial is not None or shape, 'At least one of the initial or shape arguments must be specified!' if initial is not None: self.initial: np.ndarray = np.array(initial) else: self.initial: np.ndarray = np.random.uniform(low=-1, high=1, size=shape) def run(self, size: int, burnin: Optional[int] = 1000, thinning: Optional[int] = None, verbose: int = 0): if self.used: self.initial = self.sample[-1] burnin = 0 self.sample = np.empty((size + burnin, *self.initial.shape)) self.sample[0] = self.initial u = np.random.uniform(0, 1, size + burnin) counter = 0 for i in range(1, burnin): current_x = self.sample[i - 1] proposed = self.proposal.sample(current_x) a = np.min([1, (self.target(proposed) * self.proposal.pdf(current_x, proposed)) / (self.target(current_x) * self.proposal.pdf(proposed, current_x))]) if u[i] < a: self.sample[i] = proposed else: self.sample[i] = current_x for i in range(burnin + 1, size + burnin): current_x = self.sample[i - 1] proposed = self.proposal.sample(current_x) a = np.min([1, (self.target(proposed) * self.proposal.pdf(current_x, proposed)) / (self.target(current_x) * self.proposal.pdf(proposed, current_x))]) if u[i] < a: counter += 1 self.sample[i] = proposed else: self.sample[i] = current_x self.accepted = counter / size * 100 if verbose > 0: print("Proportion of samples accepted: {}%".format(round(counter / size * 100, 2))) self.used = True return self.sample[burnin:][::thinning]

41.509091

112

0.57293

560

4,566

4.621429

0.151786

0.085008

0.051005

0.02473

0.92813

0

0.018448

0.311432

4,566

109

113

41.889908

0.804707

0.005256

0

0.946237

0

0.044053

0

0.009174

0.021505

1

0.043011

false

0

0.032258

0

0.11828

0.021505

0

null

0

1

0

1

0

null

0

7

dfd5ee3106f080860b3472d12a3f41e6e0189730

212

py

Python

trapper/metrics/__init__.py

obss/trapper

40e6fc25a2d8c1ece8bf006c362a9cb163c4355c

[ "MIT" ]

36

2021-11-01T19:29:31.000Z

2022-02-25T15:19:08.000Z

trapper/metrics/__init__.py

obss/trapper

40e6fc25a2d8c1ece8bf006c362a9cb163c4355c

[ "MIT" ]

7

2021-11-01T14:33:21.000Z

2022-03-22T09:01:36.000Z

trapper/metrics/__init__.py

obss/trapper

40e6fc25a2d8c1ece8bf006c362a9cb163c4355c

[ "MIT" ]

4

2021-11-30T00:34:20.000Z

2022-03-31T21:06:30.000Z

from trapper.metrics.input_handlers import MetricInputHandler from trapper.metrics.jury import JuryMetric from trapper.metrics.metric import Metric from trapper.metrics.output_handlers import MetricOutputHandler

42.4

63

0.886792

26

212

7.153846

0.461538

0.236559

0.387097

0

0.075472

212

4

64

53

0.94898

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

a075a1c48293e06b5c08b8b728230567b57b9b80

18,868

py

Python

ckanext-hdx_org_group/ckanext/hdx_org_group/tests/test_org_custom_fields.py

OCHA-DAP/hdx-ckan

202e0c44adc4ea8d0b90141e69365b65cce68672

[ "Apache-2.0" ]

58

2015-01-11T09:05:15.000Z

2022-03-17T23:44:07.000Z

ckanext-hdx_org_group/ckanext/hdx_org_group/tests/test_org_custom_fields.py

OCHA-DAP/hdx-ckan

202e0c44adc4ea8d0b90141e69365b65cce68672

[ "Apache-2.0" ]

1,467

2015-01-01T16:47:44.000Z

2022-02-28T16:51:20.000Z

ckanext-hdx_org_group/ckanext/hdx_org_group/tests/test_org_custom_fields.py

OCHA-DAP/hdx-ckan

202e0c44adc4ea8d0b90141e69365b65cce68672

[ "Apache-2.0" ]

17

2015-05-06T14:04:21.000Z

2021-11-11T19:58:16.000Z

''' Created on May 18, 2020 @author: dan mihaila ''' import logging as logging import ckan.model as model import ckan.tests.legacy as tests import ckan.lib.helpers as h import ckan.plugins.toolkit as tk import ckanext.hdx_theme.tests.hdx_test_base as hdx_test_base import ckanext.hdx_org_group.tests as org_group_base log = logging.getLogger(__name__) from ckanext.hdx_org_group.helpers.static_lists import ORGANIZATION_TYPE_LIST class TestOrgFTSIDAPI(org_group_base.OrgGroupBaseTest): @classmethod def _load_plugins(cls): hdx_test_base.load_plugin('ytp_request hdx_org_group hdx_theme') @classmethod def _get_action(cls, action_name): return tk.get_action(action_name) def test_create_org_api(self): context_sysadmin = {'model': model, 'session': model.Session, 'user': 'testsysadmin', 'allow_partial_update': True} new_org_dict = { 'name': 'test_org_dd', 'title': 'Test Org D', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1] } try: org_dict = self._get_action('organization_create')(context_sysadmin, new_org_dict) assert org_dict.get('name') == 'test_org_dd' except Exception as ex: assert False edit_org_dict = { 'id': org_dict.get('id'), 'name': 'test_org_dd', 'title': 'Test Org DD', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1] } try: org_dict = self._get_action('organization_update')(context_sysadmin, edit_org_dict) assert org_dict.get('title') == 'Test Org DD' except Exception as ex: assert False def test_fts_id_api(self): context_usr = {'model': model, 'session': model.Session, 'user': 'tester', 'allow_partial_update': True} context_sysadmin = {'model': model, 'session': model.Session, 'user': 'testsysadmin'} new_org_dict = { 'name': 'test_org_d', 'title': 'Test Org D', 'fts_id': '123456', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1] } try: org_dict = self._get_action('organization_create')(context_sysadmin, new_org_dict) assert 'fts_id' in org_dict assert org_dict.get('fts_id') == '123456' except Exception as ex: assert False try: _org_update_dict = { 'id': org_dict.get('id'), 'name': org_dict.get('name'), 'title': org_dict.get('title'), 'fts_id': '1234567', 'org_url': org_dict.get('org_url'), 'description': org_dict.get('description'), 'hdx_org_type': org_dict.get('hdx_org_type'), } self._get_action('organization_update')(context_sysadmin, _org_update_dict) org_updated_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert 'fts_id' in org_updated_dict assert org_updated_dict.get('fts_id') == '1234567' except Exception as ex: assert False try: member_dict = {'id': org_dict.get('id'), 'username': 'tester', 'role': 'admin'} self._get_action('organization_member_create')(context_sysadmin, member_dict) _org_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert True except Exception as ex: assert False try: _org_update_dict = { 'id': org_updated_dict.get('id'), 'name': org_updated_dict.get('name'), 'title': org_updated_dict.get('title'), 'org_url': org_updated_dict.get('org_url'), 'description': org_updated_dict.get('description'), 'hdx_org_type': org_updated_dict.get('hdx_org_type'), } self._get_action('organization_update')(context_usr, _org_update_dict) org_updated_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert 'fts_id' in org_updated_dict assert org_updated_dict.get('fts_id') == '1234567' except Exception as ex: assert False try: _org_update_dict = { 'id': org_dict.get('id'), 'name': org_dict.get('name'), 'fts_id': '12345678', 'title': org_dict.get('title'), 'org_url': org_dict.get('org_url'), 'description': org_dict.get('description'), 'hdx_org_type': org_dict.get('hdx_org_type'), } self._get_action('organization_update')(context_usr, _org_update_dict) org_updated_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert 'fts_id' in org_updated_dict assert org_updated_dict.get('fts_id') == '1234567' except Exception as ex: assert False assert True class TestOrgFTSIDController(org_group_base.OrgGroupBaseTest): @classmethod def _load_plugins(cls): hdx_test_base.load_plugin('ytp_request hdx_org_group hdx_theme') @classmethod def _get_action(cls, action_name): return tk.get_action(action_name) def test_fts_is_controller(self): context_usr = {'model': model, 'session': model.Session, 'user': 'tester', 'allow_partial_update': True} context_sysadmin = {'model': model, 'session': model.Session, 'user': 'testsysadmin', 'allow_partial_update': True} testsysadmin = model.User.by_name('testsysadmin') sysadmin_auth = {'Authorization': str(testsysadmin.apikey)} tester = model.User.by_name('tester') tester_auth = {'Authorization': str(tester.apikey)} test_client = self.get_backwards_compatible_test_client() new_org_url = h.url_for( controller='ckanext.hdx_org_group.controllers.organization_controller:HDXOrganizationController', action='new') new_org_params = { 'name': 'test_org_d', 'title': 'Test Org D', 'fts_id': '123456', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1], 'save': 'save' } try: result = test_client.post(new_org_url, data=new_org_params, extra_environ=sysadmin_auth) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': 'test_org_d'}) assert '123456' == org_dict.get('fts_id') assert '302 Found' in result.body except Exception as ex: assert False try: member_dict = {'id': org_dict.get('id'), 'username': 'tester', 'role': 'admin'} self._get_action('organization_member_create')(context_sysadmin, member_dict) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert True except Exception as ex: assert False edit_org_url = h.url_for( controller='ckanext.hdx_org_group.controllers.organization_controller:HDXOrganizationController', action='edit', id=org_dict.get('id')) edit_org_params = { 'id': org_dict.get('id'), 'name': 'test_org_d', 'title': 'Test Org E', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1], 'save': 'save' } try: result = test_client.post(edit_org_url, data=edit_org_params, extra_environ=tester_auth) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': 'test_org_d'}) assert '123456' == org_dict.get('fts_id') assert 'Test Org E' == org_dict.get('title') except Exception as ex: assert False edit_org_params = { 'id': org_dict.get('id'), 'name': 'test_org_d', 'title': 'Test Org E', 'fts_id': '789', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1], 'save': 'save' } try: result = test_client.post(edit_org_url, data=edit_org_params, extra_environ=tester_auth) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': 'test_org_d'}) assert '123456' == org_dict.get('fts_id') assert 'Test Org E' == org_dict.get('title') except Exception as ex: assert False assert True class TestOrgUserSurveyUrlAPI(org_group_base.OrgGroupBaseTest): USER_SURVEY_URL = 'https://google.com' USER_SURVEY_UPDATED_URL = 'https://google.org' @classmethod def _load_plugins(cls): hdx_test_base.load_plugin('ytp_request hdx_org_group hdx_theme') @classmethod def _get_action(cls, action_name): return tk.get_action(action_name) def test_create_org_api(self): context_sysadmin = {'model': model, 'session': model.Session, 'user': 'testsysadmin', 'allow_partial_update': True} new_org_dict = { 'name': 'test_org_dd', 'title': 'Test Org D', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1] } try: org_dict = self._get_action('organization_create')(context_sysadmin, new_org_dict) assert org_dict.get('name') == 'test_org_dd' except Exception as ex: assert False edit_org_dict = { 'id': org_dict.get('id'), 'name': 'test_org_dd', 'title': 'Test Org DD', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1] } try: org_dict = self._get_action('organization_update')(context_sysadmin, edit_org_dict) assert org_dict.get('title') == 'Test Org DD' except Exception as ex: assert False def test_user_survey_url_api(self): context_usr = {'model': model, 'session': model.Session, 'user': 'tester', 'allow_partial_update': True} context_sysadmin = {'model': model, 'session': model.Session, 'user': 'testsysadmin'} new_org_dict = { 'name': 'test_org_d', 'title': 'Test Org D', 'user_survey_url': self.USER_SURVEY_URL, 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1] } try: org_dict = self._get_action('organization_create')(context_sysadmin, new_org_dict) assert 'user_survey_url' in org_dict assert org_dict.get('user_survey_url') == self.USER_SURVEY_URL except Exception as ex: assert False try: _org_update_dict = { 'id': org_dict.get('id'), 'name': org_dict.get('name'), 'title': org_dict.get('title'), 'user_survey_url': self.USER_SURVEY_UPDATED_URL, 'org_url': org_dict.get('org_url'), 'description': org_dict.get('description'), 'hdx_org_type': org_dict.get('hdx_org_type'), } self._get_action('organization_update')(context_sysadmin, _org_update_dict) org_updated_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert 'user_survey_url' in org_updated_dict assert org_updated_dict.get('user_survey_url') == self.USER_SURVEY_UPDATED_URL except Exception as ex: assert False try: member_dict = {'id': org_dict.get('id'), 'username': 'tester', 'role': 'admin'} self._get_action('organization_member_create')(context_sysadmin, member_dict) _org_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert True except Exception as ex: assert False try: _org_update_dict = { 'id': org_updated_dict.get('id'), 'name': org_updated_dict.get('name'), 'title': org_updated_dict.get('title'), 'org_url': org_updated_dict.get('org_url'), 'description': org_updated_dict.get('description'), 'hdx_org_type': org_updated_dict.get('hdx_org_type'), } self._get_action('organization_update')(context_usr, _org_update_dict) org_updated_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert 'user_survey_url' in org_updated_dict assert org_updated_dict.get('user_survey_url') == self.USER_SURVEY_UPDATED_URL except Exception as ex: assert False try: _org_update_dict = { 'id': org_dict.get('id'), 'name': org_dict.get('name'), 'user_survey_url': 'https://yahoo.com', 'title': org_dict.get('title'), 'org_url': org_dict.get('org_url'), 'description': org_dict.get('description'), 'hdx_org_type': org_dict.get('hdx_org_type'), } self._get_action('organization_update')(context_usr, _org_update_dict) org_updated_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert 'user_survey_url' in org_updated_dict assert org_updated_dict.get('user_survey_url') == self.USER_SURVEY_UPDATED_URL except Exception as ex: assert False assert True class TestOrgUserSurveyUrlController(org_group_base.OrgGroupBaseTest): USER_SURVEY_URL = 'https://google.com' USER_SURVEY_UPDATED_URL = 'https://google.org' @classmethod def _load_plugins(cls): hdx_test_base.load_plugin('ytp_request hdx_org_group hdx_theme') @classmethod def _get_action(cls, action_name): return tk.get_action(action_name) def test_user_survey_url_controller(self): context_usr = {'model': model, 'session': model.Session, 'user': 'tester', 'allow_partial_update': True} context_sysadmin = {'model': model, 'session': model.Session, 'user': 'testsysadmin', 'allow_partial_update': True} testsysadmin = model.User.by_name('testsysadmin') sysadmin_auth = {'Authorization': str(testsysadmin.apikey)} tester = model.User.by_name('tester') tester_auth = {'Authorization': str(tester.apikey)} test_client = self.get_backwards_compatible_test_client() new_org_url = h.url_for( controller='ckanext.hdx_org_group.controllers.organization_controller:HDXOrganizationController', action='new') new_org_params = { 'name': 'test_org_d', 'title': 'Test Org D', 'user_survey_url': self.USER_SURVEY_URL, 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1], 'save': 'save' } try: result = test_client.post(new_org_url, data=new_org_params, extra_environ=sysadmin_auth) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': 'test_org_d'}) assert self.USER_SURVEY_URL == org_dict.get('user_survey_url') assert '302 Found' in result.body except Exception as ex: assert False try: member_dict = {'id': org_dict.get('id'), 'username': 'tester', 'role': 'admin'} self._get_action('organization_member_create')(context_sysadmin, member_dict) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': org_dict.get('id')}) assert True except Exception as ex: assert False edit_org_url = h.url_for( controller='ckanext.hdx_org_group.controllers.organization_controller:HDXOrganizationController', action='edit', id=org_dict.get('id')) edit_org_params = { 'id': org_dict.get('id'), 'name': 'test_org_d', 'title': 'Test Org E', 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1], 'save': 'save' } try: result = test_client.get(edit_org_url, extra_environ=sysadmin_auth) assert self.USER_SURVEY_URL in result.body result = test_client.post(edit_org_url, data=edit_org_params, extra_environ=tester_auth) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': 'test_org_d'}) assert self.USER_SURVEY_URL == org_dict.get('user_survey_url') assert 'Test Org E' == org_dict.get('title') except Exception as ex: assert False edit_org_params = { 'id': org_dict.get('id'), 'name': 'test_org_d', 'title': 'Test Org E', 'user_survey_url': self.USER_SURVEY_UPDATED_URL, 'org_url': 'www.exampleorganization.org', 'description': 'just a simple description', 'hdx_org_type': ORGANIZATION_TYPE_LIST[0][1], 'save': 'save' } try: result = test_client.post(edit_org_url, data=edit_org_params, extra_environ=tester_auth) org_dict = self._get_action('organization_show')(context_sysadmin, {'id': 'test_org_d'}) assert self.USER_SURVEY_URL == org_dict.get('user_survey_url') assert 'Test Org E' == org_dict.get('title') except Exception as ex: assert False assert True

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null

0

7

2656a77bf830e28b8189f113da970d45e42c2283

13

py

Python

ex004.py

ClevertonCodev/Python

5fc9c372ba9053cdbeefcae110b3f32474ce8f74

[ "MIT" ]

null

ex004.py

ClevertonCodev/Python

5fc9c372ba9053cdbeefcae110b3f32474ce8f74

[ "MIT" ]

null

ex004.py

ClevertonCodev/Python

5fc9c372ba9053cdbeefcae110b3f32474ce8f74

[ "MIT" ]

null

print (5+5*2)

13

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4

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7

2670a766baa4b3d23975af940bf1335c780e025b

108

py

Python

matcher/__init__.py

gianscarpe/vipm-project

2d9384173a8741e4e56439a06f2fd837b5e1ce4e

[ "MIT" ]

1

2020-08-02T12:26:38.000Z

matcher/__init__.py

gianscarpe/vipm-project

2d9384173a8741e4e56439a06f2fd837b5e1ce4e

[ "MIT" ]

2

2022-01-13T02:16:33.000Z

2022-03-12T00:24:48.000Z

matcher/__init__.py

gianscarpe/vipm-project

2d9384173a8741e4e56439a06f2fd837b5e1ce4e

[ "MIT" ]

null

import os def match(image): return os.path.abspath("data/fashion-product-images-small/images/1163.jpg")

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268f6cf6854198d27ba698382a05c16eab92eac0

12,491

py

Python

src/offazure/azext_offazure/generated/_help.py

Mannan2812/azure-cli-extensions

e2b34efe23795f6db9c59100534a40f0813c3d95

[ "MIT" ]

207

2017-11-29T06:59:41.000Z

2022-03-31T10:00:53.000Z

src/offazure/azext_offazure/generated/_help.py

Mannan2812/azure-cli-extensions

e2b34efe23795f6db9c59100534a40f0813c3d95

[ "MIT" ]

4,061

2017-10-27T23:19:56.000Z

2022-03-31T23:18:30.000Z

src/offazure/azext_offazure/generated/_help.py

Mannan2812/azure-cli-extensions

e2b34efe23795f6db9c59100534a40f0813c3d95

[ "MIT" ]

802

2017-10-11T17:36:26.000Z

2022-03-31T22:24:32.000Z

# -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- # pylint: disable=too-many-lines from knack.help_files import helps helps['offazure hyperv cluster'] = """ type: group short-summary: Manage hyper v cluster with offazure """ helps['offazure hyperv cluster list'] = """ type: command short-summary: "Method to get all clusters in a site." examples: - name: List cluster by site text: |- az offazure hyperv cluster list --resource-group "ipsahoo-RI-121119" --site-name "hyperv121319c813site" \ --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv cluster show'] = """ type: command short-summary: "Method to get a Hyper-V cluster." examples: - name: Get cluster text: |- az offazure hyperv cluster show --cluster-name "hypgqlclusrs1-ntdev-corp-micros-11e77b27-67cc-5e46-a5d8-\ 0ff3dc2ef179" --resource-group "ipsahoo-RI-121119" --site-name "hyperv121319c813site" --subscription-id \ "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv host'] = """ type: group short-summary: Manage hyper v host with offazure """ helps['offazure hyperv host list'] = """ type: command short-summary: "Method to get all hosts in a site." examples: - name: List hosts by site text: |- az offazure hyperv host list --resource-group "pajindTest" --site-name "appliance1e39site" \ --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv host show'] = """ type: command short-summary: "Method to get a Hyper-V host." examples: - name: Get host text: |- az offazure hyperv host show --host-name "bcdr-ewlab-46-ntdev-corp-micros-e4638031-3b19-5642-926d-385da6\ 0cfb8a" --resource-group "pajindTest" --site-name "appliance1e39site" --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533\ d58600" """ helps['offazure hyperv machine'] = """ type: group short-summary: Manage hyper v machine with offazure """ helps['offazure hyperv machine list'] = """ type: command short-summary: "Method to get machine." examples: - name: List hosts by site text: |- az offazure hyperv machine list --resource-group "pajindTest" --site-name "appliance1e39site" \ --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv machine show'] = """ type: command short-summary: "Method to get machine." examples: - name: Get machine. text: |- az offazure hyperv machine show --machine-name "96d27052-052b-48db-aa84-b9978eddbf5d" --resource-group \ "pajindTest" --site-name "appliance1e39site" --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv run-as-account'] = """ type: group short-summary: Manage hyper v run as account with offazure """ helps['offazure hyperv run-as-account list'] = """ type: command short-summary: "Method to get run as accounts." examples: - name: List Run As Accounts by site text: |- az offazure hyperv run-as-account list --resource-group "pajindTest" --site-name "appliance1e39site" \ --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv run-as-account show'] = """ type: command short-summary: "Method to get run as account." examples: - name: Get run as account. text: |- az offazure hyperv run-as-account show --account-name "account1" --resource-group "pajindTest" \ --site-name "appliance1e39site" --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv site'] = """ type: group short-summary: Manage hyper v site with offazure """ helps['offazure hyperv site show'] = """ type: command short-summary: "Method to get a site." examples: - name: Get Hyper-V site text: |- az offazure hyperv site show --resource-group "pajindTest" --site-name "appliance1e39site" \ --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv site create'] = """ type: command short-summary: "Method to create or update a site." parameters: - name: --service-principal-identity-details short-summary: "Service principal identity details used by agent for communication to the service." long-summary: | Usage: --service-principal-identity-details tenant-id=XX application-id=XX object-id=XX audience=XX \ aad-authority=XX raw-cert-data=XX tenant-id: Tenant Id for the service principal with which the on-premise management/data plane components \ would communicate with our Azure services. application-id: Application/client Id for the service principal with which the on-premise management/data \ plane components would communicate with our Azure services. object-id: Object Id of the service principal with which the on-premise management/data plane components \ would communicate with our Azure services. audience: Intended audience for the service principal. aad-authority: AAD Authority URL which was used to request the token for the service principal. raw-cert-data: Raw certificate data for building certificate expiry flows. - name: --agent-details short-summary: "On-premises agent details." long-summary: | Usage: --agent-details key-vault-uri=XX key-vault-id=XX key-vault-uri: Key vault URI. key-vault-id: Key vault ARM Id. examples: - name: Create Hyper-V site text: |- az offazure hyperv site create --location "eastus" --service-principal-identity-details \ aad-authority="https://login.windows.net/72f988bf-86f1-41af-91ab-2d7cd011db47" application-id="e9f013df-2a2a-4871-b766-\ e79867f30348" audience="https://72f988bf-86f1-41af-91ab-2d7cd011db47/MaheshSite17ac9agentauthaadapp" \ object-id="2cd492bc-7ef3-4ee0-b301-59a88108b47b" tenant-id="72f988bf-86f1-41af-91ab-2d7cd011db47" --resource-group \ "pajindTest" --site-name "appliance1e39site" --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure hyperv site delete'] = """ type: command short-summary: "Method to delete a site." examples: - name: Delete Hyper-V site. text: |- az offazure hyperv site delete --resource-group "pajindTest" --site-name "appliance1e39site" \ --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure vmware machine'] = """ type: group short-summary: Manage machine with offazure """ helps['offazure vmware machine list'] = """ type: command short-summary: "Method to get machine." examples: - name: Get VMware machines text: |- az offazure vmware machine list --resource-group "myResourceGroup" --site-name "pajind_site1" \ --subscription-id "75dd7e42-4fd1-4512-af04-83ad9864335b" """ helps['offazure vmware machine show'] = """ type: command short-summary: "Method to get machine." examples: - name: Get VMware machine. text: |- az offazure vmware machine show --name "machine1" --resource-group "myResourceGroup" --site-name \ "pajind_site1" --subscription-id "75dd7e42-4fd1-4512-af04-83ad9864335b" """ helps['offazure vmware run-as-account'] = """ type: group short-summary: Manage run as account with offazure """ helps['offazure vmware run-as-account list'] = """ type: command short-summary: "Method to get run as accounts." examples: - name: List VMware run as account by site. text: |- az offazure vmware run-as-account list --resource-group "myResourceGroup" --site-name "pajind_site1" \ --subscription-id "75dd7e42-4fd1-4512-af04-83ad9864335b" """ helps['offazure vmware run-as-account show'] = """ type: command short-summary: "Method to get run as account." examples: - name: Get VMware run as account. text: |- az offazure vmware run-as-account show --account-name "account1" --resource-group "myResourceGroup" \ --site-name "pajind_site1" --subscription-id "75dd7e42-4fd1-4512-af04-83ad9864335b" """ helps['offazure vmware site'] = """ type: group short-summary: Manage site with offazure """ helps['offazure vmware site show'] = """ type: command short-summary: "Method to get a site." examples: - name: Get VMware site text: |- az offazure vmware site show --resource-group "myResourceGroup" --name "pajind_site1" --subscription-id \ "75dd7e42-4fd1-4512-af04-83ad9864335b" """ helps['offazure vmware site create'] = """ type: command short-summary: "Method to create or update a site." parameters: - name: --service-principal-identity-details short-summary: "Service principal identity details used by agent for communication to the service." long-summary: | Usage: --service-principal-identity-details tenant-id=XX application-id=XX object-id=XX audience=XX \ aad-authority=XX raw-cert-data=XX tenant-id: Tenant Id for the service principal with which the on-premise management/data plane components \ would communicate with our Azure services. application-id: Application/client Id for the service principal with which the on-premise management/data \ plane components would communicate with our Azure services. object-id: Object Id of the service principal with which the on-premise management/data plane components \ would communicate with our Azure services. audience: Intended audience for the service principal. aad-authority: AAD Authority URL which was used to request the token for the service principal. raw-cert-data: Raw certificate data for building certificate expiry flows. - name: --agent-details short-summary: "On-premises agent details." long-summary: | Usage: --agent-details key-vault-uri=XX key-vault-id=XX key-vault-uri: Key vault URI. key-vault-id: Key vault ARM Id. examples: - name: Create VMware site text: |- az offazure vmware site create --location "eastus" --service-principal-identity-details \ aad-authority="https://login.windows.net/72f988bf-86f1-41af-91ab-2d7cd011db47" application-id="e9f013df-2a2a-4871-b766-\ e79867f30348" audience="https://72f988bf-86f1-41af-91ab-2d7cd011db47/MaheshSite17ac9agentauthaadapp" \ object-id="2cd492bc-7ef3-4ee0-b301-59a88108b47b" tenant-id="72f988bf-86f1-41af-91ab-2d7cd011db47" --resource-group \ "pajindTest" --site-name "appliance1e39site" --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure vmware site delete'] = """ type: command short-summary: "Method to delete a site." examples: - name: Delete VMware site text: |- az offazure vmware site delete --resource-group "myResourceGroup" --name "pajind_site1" \ --subscription-id "75dd7e42-4fd1-4512-af04-83ad9864335b" """ helps['offazure vmware vcenter'] = """ type: group short-summary: Manage v center with offazure """ helps['offazure vmware vcenter list'] = """ type: command short-summary: "Method to get all vCenters in a site." examples: - name: List VMware vCenters by site text: |- az offazure vmware vcenter list --resource-group "rahasijaBugBash050919" --site-name \ "rahasapp122119d37csite" --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" """ helps['offazure vmware vcenter show'] = """ type: command short-summary: "Method to get a vCenter." examples: - name: Get VMware Vcenter. text: |- az offazure vmware vcenter show --resource-group "rahasijaBugBash050919" --site-name \ "rahasapp122119d37csite" --subscription-id "4bd2aa0f-2bd2-4d67-91a8-5a4533d58600" --name \ "10-150-8-50-6af5f800-e9f6-56ff-9c3c-7be56d242c31" """

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1

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null

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1

0

8

cd9c3894adf807197dec564b12648b5992d0e4dc

22,105

py

Python

epm_client/apis/po_p_api.py

tub-elastest/epm-client-python

4e708a7e8c80334337d2f05c0baec46fdd581b8f

[ "Apache-2.0" ]

1

2019-05-23T12:51:18.000Z

epm_client/apis/po_p_api.py

tub-elastest/epm-client-python

4e708a7e8c80334337d2f05c0baec46fdd581b8f

[ "Apache-2.0" ]

null

epm_client/apis/po_p_api.py

tub-elastest/epm-client-python

4e708a7e8c80334337d2f05c0baec46fdd581b8f

[ "Apache-2.0" ]

null

# coding: utf-8 """ EPM REST API REST API description of the ElasTest Platform Manager Module. OpenAPI spec version: 0.1.2 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import sys import os import re # python 2 and python 3 compatibility library from six import iteritems from ..configuration import Configuration from ..api_client import ApiClient class PoPApi(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient() self.api_client = config.api_client def get_all_po_ps(self, **kwargs): """ Returns all PoPs. Returns all PoPs with all its details. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_po_ps(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: list[PoP] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_all_po_ps_with_http_info(**kwargs) else: (data) = self.get_all_po_ps_with_http_info(**kwargs) return data def get_all_po_ps_with_http_info(self, **kwargs): """ Returns all PoPs. Returns all PoPs with all its details. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_po_ps_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: list[PoP] If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_all_po_ps" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/pop'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[PoP]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_po_p_by_id(self, id, **kwargs): """ Returns a PoP. Returns the PoP with the given ID. Returns all its details. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_po_p_by_id(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: ID of PoP (required) :return: PoP If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_po_p_by_id_with_http_info(id, **kwargs) else: (data) = self.get_po_p_by_id_with_http_info(id, **kwargs) return data def get_po_p_by_id_with_http_info(self, id, **kwargs): """ Returns a PoP. Returns the PoP with the given ID. Returns all its details. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_po_p_by_id_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: ID of PoP (required) :return: PoP If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_po_p_by_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `get_po_p_by_id`") collection_formats = {} resource_path = '/pop/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PoP', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def register_po_p(self, body, **kwargs): """ Registers a new PoP Registers a new Point-of-Presence represented by a PoP This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.register_po_p(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param PoP body: Defintion of a PoP which defines a Point-of-Presence used to host resources (required) :return: PoP If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.register_po_p_with_http_info(body, **kwargs) else: (data) = self.register_po_p_with_http_info(body, **kwargs) return data def register_po_p_with_http_info(self, body, **kwargs): """ Registers a new PoP Registers a new Point-of-Presence represented by a PoP This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.register_po_p_with_http_info(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param PoP body: Defintion of a PoP which defines a Point-of-Presence used to host resources (required) :return: PoP If the method is called asynchronously, returns the request thread. """ all_params = ['body'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method register_po_p" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `register_po_p`") collection_formats = {} resource_path = '/pop'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PoP', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def unregister_po_p(self, id, **kwargs): """ Unregisters a PoP. Unregisters the PoP that matches with a given ID. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.unregister_po_p(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: ID of PoP (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.unregister_po_p_with_http_info(id, **kwargs) else: (data) = self.unregister_po_p_with_http_info(id, **kwargs) return data def unregister_po_p_with_http_info(self, id, **kwargs): """ Unregisters a PoP. Unregisters the PoP that matches with a given ID. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.unregister_po_p_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: ID of PoP (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method unregister_po_p" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `unregister_po_p`") collection_formats = {} resource_path = '/pop/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['*/*']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_po_p(self, id, body, **kwargs): """ Updates a PoP. Updates an already registered PoP. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_po_p(id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: ID of PoP (required) :param PoP body: PoP object that needs to be updated. (required) :return: PoP If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.update_po_p_with_http_info(id, body, **kwargs) else: (data) = self.update_po_p_with_http_info(id, body, **kwargs) return data def update_po_p_with_http_info(self, id, body, **kwargs): """ Updates a PoP. Updates an already registered PoP. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_po_p_with_http_info(id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: ID of PoP (required) :param PoP body: PoP object that needs to be updated. (required) :return: PoP If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'body'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_po_p" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `update_po_p`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `update_po_p`") collection_formats = {} resource_path = '/pop/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PoP', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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0.030986

0.948528

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0

1

0

1

0

null

0

8

26ec5b106ccbe44d39e9ae71df90d157386958c4

345,962

py

Python

functions/utility_functions.py

mtasa-typescript/mtasa-wiki-dump

edea1746850fb6c99d6155d1d7891e2cceb33a5c

[ "MIT" ]

null

functions/utility_functions.py

mtasa-typescript/mtasa-wiki-dump

edea1746850fb6c99d6155d1d7891e2cceb33a5c

[ "MIT" ]

1

2021-02-24T21:50:18.000Z

functions/utility_functions.py

mtasa-typescript/mtasa-wiki-dump

edea1746850fb6c99d6155d1d7891e2cceb33a5c

[ "MIT" ]

null

# Autogenerated file. ANY CHANGES WILL BE OVERWRITTEN from to_python.core.types import FunctionType, \ FunctionArgument, \ FunctionArgumentValues, \ FunctionReturnTypes, \ FunctionSignature, \ FunctionDoc, \ FunctionData, \ CompoundFunctionData DUMP_PARTIAL = [ CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='addDebugHook', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='hookType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callbackFunction', argument_type=FunctionType( names=['function'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='nameList', argument_type=FunctionType( names=['table'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows tracing of MTA functions and events. It should only be used when debugging scripts as it may degrade script performance.\nDebug hooks are not recursive, so functions and events triggered inside the hook callback will not be traced.' , arguments={ "hookType": """The type of hook to add. This can be: ** preEvent ** postEvent ** preFunction ** postFunction * preEventFunction * postEventFunction """, "callbackFunction": """The function to call ** Returning the string "skip" from the callback function will cause the original function/event to be skipped """, "nameList": """Table of strings for restricting which functions and events the hook will be triggered on ** addDebugHook and removeDebugHook will only be hooked if they are specified in the name list """ }, result='returns true if the hook was successfully added, or false otherwise.' , ), url='addDebugHook', ) ], client=[ FunctionData( signature=FunctionSignature( name='addDebugHook', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='hookType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callbackFunction', argument_type=FunctionType( names=['function'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='nameList', argument_type=FunctionType( names=['table'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows tracing of MTA functions and events. It should only be used when debugging scripts as it may degrade script performance.\nDebug hooks are not recursive, so functions and events triggered inside the hook callback will not be traced.' , arguments={ "hookType": """The type of hook to add. This can be: ** preEvent ** postEvent ** preFunction ** postFunction * preEventFunction * postEventFunction """, "callbackFunction": """The function to call ** Returning the string "skip" from the callback function will cause the original function/event to be skipped """, "nameList": """Table of strings for restricting which functions and events the hook will be triggered on ** addDebugHook and removeDebugHook will only be hooked if they are specified in the name list """ }, result='returns true if the hook was successfully added, or false otherwise.' , ), url='addDebugHook', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='base64Decode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='data', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the decrypted data from https://en.wikipedia.org/wiki/Base64 base64 representation of the encrypted block' , arguments={ "data": """The block of data you want to decrypt """ }, result='returns the decrypted data from https://en.wikipedia.org/wiki/base64 base64 representation of the encrypted block if the decryption process was successfully completed, false otherwise.' , ), url='base64Decode', ) ], client=[ FunctionData( signature=FunctionSignature( name='base64Decode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='data', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the decrypted data from https://en.wikipedia.org/wiki/Base64 base64 representation of the encrypted block' , arguments={ "data": """The block of data you want to decrypt """ }, result='returns the decrypted data from https://en.wikipedia.org/wiki/base64 base64 representation of the encrypted block if the decryption process was successfully completed, false otherwise.' , ), url='base64Decode', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='base64Encode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='data', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the https://en.wikipedia.org/wiki/Base64 base64 representation of the encoded block of data' , arguments={ "data": """The block of data you want to encode """ }, result='returns the https://en.wikipedia.org/wiki/base64 base64 representation of the encoded data if the encoding process was successfully completed, false otherwise.' , ), url='base64Encode', ) ], client=[ FunctionData( signature=FunctionSignature( name='base64Encode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='data', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the https://en.wikipedia.org/wiki/Base64 base64 representation of the encoded block of data' , arguments={ "data": """The block of data you want to encode """ }, result='returns the https://en.wikipedia.org/wiki/base64 base64 representation of the encoded data if the encoding process was successfully completed, false otherwise.' , ), url='base64Encode', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitAnd', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise AND-conjunction on two or more (unsigned) 32-bit Int|integers. See http://en.wikipedia.org/wiki/Bitwise_operation#AND Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform an AND-conjunction on """ }, result='returns the conjuncted value.' , ), url='bitAnd', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitAnd', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise AND-conjunction on two or more (unsigned) 32-bit Int|integers. See http://en.wikipedia.org/wiki/Bitwise_operation#AND Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform an AND-conjunction on """ }, result='returns the conjuncted value.' , ), url='bitAnd', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitArShift', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs an arithmetic shift on the integer value by integer n positions. In an arithmetic shift, zeros are shifted in to replace the discarded bits. In a right arithmetic shift, the https://en.wikipedia.org/wiki/Sign_bit sign bit is shifted in on the left, thus preserving the sign of the operand.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Arithmetic_shift Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the arithmetic shift on. """, "n": """The amount of positions to shift the value by. """ }, result='returns the arithmetic shifted value as integer.' , ), url='bitArShift', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitArShift', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs an arithmetic shift on the integer value by integer n positions. In an arithmetic shift, zeros are shifted in to replace the discarded bits. In a right arithmetic shift, the https://en.wikipedia.org/wiki/Sign_bit sign bit is shifted in on the left, thus preserving the sign of the operand.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Arithmetic_shift Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the arithmetic shift on. """, "n": """The amount of positions to shift the value by. """ }, result='returns the arithmetic shifted value as integer.' , ), url='bitArShift', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitExtract', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='field', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='width', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='1', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the unsigned number formed by the bits field to field + width - 1 (range: 0-31).' , arguments={ "var": """The value """, "field": """The field number """, "width": """Number of bits to extract """ }, result='returns the extracted value/bit sequence.' , ), url='bitExtract', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitExtract', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='field', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='width', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='1', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the unsigned number formed by the bits field to field + width - 1 (range: 0-31).' , arguments={ "var": """The value """, "field": """The field number """, "width": """Number of bits to extract """ }, result='returns the extracted value/bit sequence.' , ), url='bitExtract', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitLRotate', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a bitwise circular left-rotation on the integer value by integer n positions.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Rotate_no_carry Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the rotation on. """, "n": """The amount of positions to rotate the value by. """ }, result='returns the circular left-rotated value as integer.' , ), url='bitLRotate', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitLRotate', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a bitwise circular left-rotation on the integer value by integer n positions.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Rotate_no_carry Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the rotation on. """, "n": """The amount of positions to rotate the value by. """ }, result='returns the circular left-rotated value as integer.' , ), url='bitLRotate', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitLShift', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a logical left shift on the integer value by integer n positions. In a logical shift, zeros are shifted in to replace the discarded bits.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Logical_shift Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the shift on. """, "n": """The amount of positions to shift the value by. """ }, result='returns the logical left shifted value as integer.' , ), url='bitLShift', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitLShift', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a logical left shift on the integer value by integer n positions. In a logical shift, zeros are shifted in to replace the discarded bits.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Logical_shift Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the shift on. """, "n": """The amount of positions to shift the value by. """ }, result='returns the logical left shifted value as integer.' , ), url='bitLShift', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitNot', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise NOT on an (unsigned) 32-bit Int|integer. See http://en.wikipedia.org/wiki/Bitwise_operation#NOT Bitwise operation for more details.' , arguments={ "var": """The value you want to perform a bitwise NOT on """ }, result='returns the value on which the operation has been performed.' , ), url='bitNot', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitNot', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise NOT on an (unsigned) 32-bit Int|integer. See http://en.wikipedia.org/wiki/Bitwise_operation#NOT Bitwise operation for more details.' , arguments={ "var": """The value you want to perform a bitwise NOT on """ }, result='returns the value on which the operation has been performed.' , ), url='bitNot', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitOr', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise OR-conjunction on two or more (unsigned) 32-bit Int|integers. See http://en.wikipedia.org/wiki/Bitwise_operation#OR Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform an OR-conjunction on """ }, result='returns the conjuncted value.' , ), url='bitOr', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitOr', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise OR-conjunction on two or more (unsigned) 32-bit Int|integers. See http://en.wikipedia.org/wiki/Bitwise_operation#OR Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform an OR-conjunction on """ }, result='returns the conjuncted value.' , ), url='bitOr', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitReplace', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='replaceValue', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='field', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='width', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='1', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the unsigned number formed by var value with replacement specified at bits field to field + width - 1' , arguments={ "var": """The value """, "replaceValue": """The replaceValue """, "field": """The field number """, "width": """Number of bits to extract """ }, result='returns the replaced value/bit sequence.' , ), url='bitReplace', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitReplace', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='replaceValue', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='field', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='width', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='1', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the unsigned number formed by var value with replacement specified at bits field to field + width - 1' , arguments={ "var": """The value """, "replaceValue": """The replaceValue """, "field": """The field number """, "width": """Number of bits to extract """ }, result='returns the replaced value/bit sequence.' , ), url='bitReplace', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitRRotate', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a bitwise circular right-rotation on the integer value by integer n positions.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Rotate_no_carry Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the rotation on. """, "n": """The amount of positions to rotate the value by. """ }, result='returns the circular right-rotated value as integer.' , ), url='bitRRotate', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitRRotate', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a bitwise circular right-rotation on the integer value by integer n positions.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Rotate_no_carry Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the rotation on. """, "n": """The amount of positions to rotate the value by. """ }, result='returns the circular right-rotated value as integer.' , ), url='bitRRotate', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitRShift', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a logical right shift on the integer value by integer n positions. In a logical shift, zeros are shifted in to replace the discarded bits.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Logical_shift Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the shift on. """, "n": """The amount of positions to shift the value by. """ }, result='returns the logical right shifted value as integer.' , ), url='bitRShift', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitRShift', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='n', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs a logical right shift on the integer value by integer n positions. In a logical shift, zeros are shifted in to replace the discarded bits.\nSee https://en.wikipedia.org/wiki/Bitwise_operation#Logical_shift Bitwise operation for more details.' , arguments={ "value": """The value you want to perform the shift on. """, "n": """The amount of positions to shift the value by. """ }, result='returns the logical right shifted value as integer.' , ), url='bitRShift', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitTest', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs an AND-conjunction on two or more (unsigned) 32-bit Int|integers and checks, whether the conjuncted value is zero or not. See http://en.wikipedia.org/wiki/Bitwise_operation#AND Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform the operation on (see above) """ }, result='returns true if the conjuncted value is not zero, false otherwise. if a bad argument was passed to bittest, youll get nil.' , ), url='bitTest', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitTest', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs an AND-conjunction on two or more (unsigned) 32-bit Int|integers and checks, whether the conjuncted value is zero or not. See http://en.wikipedia.org/wiki/Bitwise_operation#AND Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform the operation on (see above) """ }, result='returns true if the conjuncted value is not zero, false otherwise. if a bad argument was passed to bittest, youll get nil.' , ), url='bitTest', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='bitXor', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise XOR-conjunction (exclusive OR) on two or more (unsigned) 32-bit Int|integers. See http://en.wikipedia.org/wiki/Bitwise_operation#XOR Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform a XOR-conjunction on """ }, result='returns the conjuncted value.' , ), url='bitXor', ) ], client=[ FunctionData( signature=FunctionSignature( name='bitXor', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['uint'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['uint'], is_optional=False, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a bitwise XOR-conjunction (exclusive OR) on two or more (unsigned) 32-bit Int|integers. See http://en.wikipedia.org/wiki/Bitwise_operation#XOR Bitwise operation for more details.' , arguments={ "varN": """The value you want to perform a XOR-conjunction on """ }, result='returns the conjuncted value.' , ), url='bitXor', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='createTrayNotification', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='notificationText', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='iconType', argument_type=FunctionType( names=['string'], is_optional=True, ), default_value='"default"', ) ], [ FunctionArgument( name='useSound', argument_type=FunctionType( names=['bool'], is_optional=True, ), default_value='true', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions creates a notification ballon on the desktop.' , arguments={ "notificationText": """The text to send in the notification. """, "iconType": """The notification icon type. Possible values are: default (the MTA icon), info, warning, error """, "useSound": """A boolean value indicating whether or not to play a sound when receiving the notification. """ }, result='returns true if the notification is correctly created, false otherwise.' , ), url='createTrayNotification', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='debugSleep', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='sleep', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='debugSleep freezes the client/server for the specified time. This means that all synchronization, rendering and script execution will stop except HTTP processing invoked by fetchRemote. This function only works, if development mode is enabled by setDevelopmentMode and can be utilised to build a debugger that communicates via HTTP requests with the editor/IDE.' , arguments={ "sleep": """: An integer value in milliseconds. """ }, result='returns true if the development mode is enabled and arguments are correct, false otherwise.' , ), url='debugSleep', ) ], client=[ FunctionData( signature=FunctionSignature( name='debugSleep', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='sleep', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='debugSleep freezes the client/server for the specified time. This means that all synchronization, rendering and script execution will stop except HTTP processing invoked by fetchRemote. This function only works, if development mode is enabled by setDevelopmentMode and can be utilised to build a debugger that communicates via HTTP requests with the editor/IDE.' , arguments={ "sleep": """: An integer value in milliseconds. """ }, result='returns true if the development mode is enabled and arguments are correct, false otherwise.' , ), url='debugSleep', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='decodeString', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='input', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function decodes an encoded string using the specified algorithm. The counterpart of this function is encodeString.' , arguments={ "algorithm": """The algorithm to use. """, "input": """The input to decode. """, "options": """A table with options and other necessary data for the algorithm, as detailed below. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. """ }, result='returns the decoded string if successful, false otherwise. if a callback was provided, the decoded string is argument to the callback.' , ), url='decodeString', ) ], client=[ FunctionData( signature=FunctionSignature( name='decodeString', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='input', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function decodes an encoded string using the specified algorithm. The counterpart of this function is encodeString.' , arguments={ "algorithm": """The algorithm to use. """, "input": """The input to decode. """, "options": """A table with options and other necessary data for the algorithm, as detailed below. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. """ }, result='returns the decoded string if successful, false otherwise. if a callback was provided, the decoded string is argument to the callback.' , ), url='decodeString', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='deref', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['mixed'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='reference', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function will take a reference obtained by the ref function and returns its Lua element.' , arguments={ "reference": """The valid reference, which you want to dereference """ }, result='returns mixed if the reference were valid. returns false if the reference were invalid.' , ), url='deref', ) ], client=[ FunctionData( signature=FunctionSignature( name='deref', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['mixed'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='reference', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function will take a reference obtained by the ref function and returns its Lua element.' , arguments={ "reference": """The valid reference, which you want to dereference """ }, result='returns mixed if the reference were valid. returns false if the reference were invalid.' , ), url='deref', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='downloadFile', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='fileName', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function ensures the requested resource file is correct and then triggers onClientFileDownloadComplete. If the file has been previously downloaded and the CRC matches, the file will not be downloaded again but onClientFileDownloadComplete will still run. The file should also be included in the resource meta.xml with the download attribute set to false, see meta.xml for more details.' , arguments={ "fileName": """: A string referencing the name of the file to download """ }, result='returns true if file download has been queued, false otherwise.' , ), url='downloadFile', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='encodeString', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='input', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function encodes a string using the specified algorithm. The counterpart of this function is decodeString.' , arguments={ "algorithm": """The algorithm to use. """, "input": """The input to encode. """, "options": """A table with options and other necessary data for the algorithm, as detailed below. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. """ }, result='* tea\n** encodedstring: the encoded string if successful, false otherwise. if a callback was provided, true is returned immediately, and the encoded string is passed as an argument to the callback.\n* aes128\n** encodedstring: the encoded string if successful, false otherwise. if a callback was provided, true is returned immediately, and the encoded string is passed as an argument to the callback.\n** iv (https://en.wikipedia.org/wiki/initialization_vector initialization vector): this is a string generated by the encryption algorithm that is needed to decrypt the message by decodestring. if a callback was provided, true is returned immediately, and the iv is passed as an argument to the callback.\n|20898}}' , ), url='encodeString', ) ], client=[ FunctionData( signature=FunctionSignature( name='encodeString', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='input', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function encodes a string using the specified algorithm. The counterpart of this function is decodeString.' , arguments={ "algorithm": """The algorithm to use. """, "input": """The input to encode. """, "options": """A table with options and other necessary data for the algorithm, as detailed below. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. """ }, result='* tea\n** encodedstring: the encoded string if successful, false otherwise. if a callback was provided, true is returned immediately, and the encoded string is passed as an argument to the callback.\n* aes128\n** encodedstring: the encoded string if successful, false otherwise. if a callback was provided, true is returned immediately, and the encoded string is passed as an argument to the callback.\n** iv (https://en.wikipedia.org/wiki/initialization_vector initialization vector): this is a string generated by the encryption algorithm that is needed to decrypt the message by decodestring. if a callback was provided, true is returned immediately, and the iv is passed as an argument to the callback.\n|20898}}' , ), url='encodeString', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='fromJSON', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['var'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='json', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function parses a JSON formatted string into variables. You can use toJSON to encode variables into a JSON string that can be read by this function.' , arguments={ "json": """A JSON formatted string """ }, result='returns variables read from the json string.\nnote: indices of a json object such as 1: cat are being returned as string, not as integer.' , ), url='fromJSON', ) ], client=[ FunctionData( signature=FunctionSignature( name='fromJSON', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['var'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='json', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function parses a JSON formatted string into variables. You can use toJSON to encode variables into a JSON string that can be read by this function.' , arguments={ "json": """A JSON formatted string """ }, result='returns variables read from the json string.\nnote: indices of a json object such as 1: cat are being returned as string, not as integer.' , ), url='fromJSON', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getColorFromString', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theColor', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function will extract Red, Green, Blue and Alpha values from a hex string you provide it. These strings follow the same format as used in HTML, with addition of the Alpha values.' , arguments={ "theColor": """A string containing a valid color code. :Valid strings are: """, "#RRGGBB": """: Colors specified, Alpha assumed to be 255. """, "#RRGGBBAA": """: All values specified. """, "#RGB": """: Shortened form, will be expanded internally to RRGGBB, as such it provides a smaller number of colors. """, "#RGBA": """: As above, shortened - each character is duplicated. :For example: """, "#FF00FF": """is Red: 255, Green: 0, Blue: 255, Alpha: 255 """, "#F0F": """is Red: 255, Green: 0, Blue: 255, Alpha: 255 (the same as the example above) """, "#34455699": """is Red: 52, Green: 69, Blue: 86, Alpha: 153 All colors used must begin with a # sign. """ }, result='returns four integers in rgba format, with a maximum value of 255 for each. each stands for red, green, blue, and alpha. alpha decides transparancy where 255 is opaque and 0 is transparent. false is returned if the string passed is invalid (for example, is missing the preceeding # sign).' , ), url='getColorFromString', ) ], client=[ FunctionData( signature=FunctionSignature( name='getColorFromString', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theColor', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function will extract Red, Green, Blue and Alpha values from a hex string you provide it. These strings follow the same format as used in HTML, with addition of the Alpha values.' , arguments={ "theColor": """A string containing a valid color code. :Valid strings are: """, "#RRGGBB": """: Colors specified, Alpha assumed to be 255. """, "#RRGGBBAA": """: All values specified. """, "#RGB": """: Shortened form, will be expanded internally to RRGGBB, as such it provides a smaller number of colors. """, "#RGBA": """: As above, shortened - each character is duplicated. :For example: """, "#FF00FF": """is Red: 255, Green: 0, Blue: 255, Alpha: 255 """, "#F0F": """is Red: 255, Green: 0, Blue: 255, Alpha: 255 (the same as the example above) """, "#34455699": """is Red: 52, Green: 69, Blue: 86, Alpha: 153 All colors used must begin with a # sign. """ }, result='returns four integers in rgba format, with a maximum value of 255 for each. each stands for red, green, blue, and alpha. alpha decides transparancy where 255 is opaque and 0 is transparent. false is returned if the string passed is invalid (for example, is missing the preceeding # sign).' , ), url='getColorFromString', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='getDevelopmentMode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function is used to get the development mode of the client. For more information see setDevelopmentMode' , arguments={ }, result='returns true if the development mode is on, false if off.' , ), url='getDevelopmentMode', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getDistanceBetweenPoints2D', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='x1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='x2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the distance between two 2 dimensional points using the pythagorean theorem.' , arguments={ "x1": """: The X position of the first point """, "y1": """: The Y position of the first point """, "x2": """: The X position of the second point """, "y2": """: The Y position of the second point """ }, result='returns a float containing the 2d distance between the two points. returns false if invalid parameters are passed.' , ), url='getDistanceBetweenPoints2D', ) ], client=[ FunctionData( signature=FunctionSignature( name='getDistanceBetweenPoints2D', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='x1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='x2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the distance between two 2 dimensional points using the pythagorean theorem.' , arguments={ "x1": """: The X position of the first point """, "y1": """: The Y position of the first point """, "x2": """: The X position of the second point """, "y2": """: The Y position of the second point """ }, result='returns a float containing the 2d distance between the two points. returns false if invalid parameters are passed.' , ), url='getDistanceBetweenPoints2D', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getDistanceBetweenPoints3D', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='x1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='x2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the distance between two 3 dimensional points using the pythagorean theorem.' , arguments={ "x1": """: The X position of the first point """, "y1": """: The Y position of the first point """, "z1": """: The Z position of the first point """, "x2": """: The X position of the second point """, "y2": """: The Y position of the second point """, "z2": """: The Z position of the second point """ }, result='returns a float containing the distance between the two points as a float. returns false if an argument passed was invalid.' , ), url='getDistanceBetweenPoints3D', ) ], client=[ FunctionData( signature=FunctionSignature( name='getDistanceBetweenPoints3D', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='x1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='x2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns the distance between two 3 dimensional points using the pythagorean theorem.' , arguments={ "x1": """: The X position of the first point """, "y1": """: The Y position of the first point """, "z1": """: The Z position of the first point """, "x2": """: The X position of the second point """, "y2": """: The Y position of the second point """, "z2": """: The Z position of the second point """ }, result='returns a float containing the distance between the two points as a float. returns false if an argument passed was invalid.' , ), url='getDistanceBetweenPoints3D', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getEasingValue', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='fProgress', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='strEasingType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='fEasingPeriod', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingAmplitude', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingOvershoot', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='Used for custom Lua based interpolation, returns the easing value (animation time to use in your custom interpolation) given a progress and an Easing|easing function.\nIn most cases, either moveObject or interpolateBetween can do the job. getEasingValue is only provided in case you want to do your own custom interpolation based on easing.' , arguments={ "fProgress": """float between 0 and 1 indicating the interpolation progress (0 at the beginning of the interpolation, 1 at the end). """, "strEasingType": """the Easing|easing function to use for the interpolation """, "fEasingPeriod": """the period of the Easing|easing function (only some easing functions use this parameter) """, "fEasingAmplitude": """the amplitude of the Easing|easing function (only some easing functions use this parameter) """, "fEasingOvershoot": """the overshoot of the Easing|easing function (only some easing functions use this parameter) """ }, result='returns fanimationtime the animation time given by the easing function (can be < 0 or > 1 since some easing|easing functions have overshoot or bounce/spring effects, false otherwise (error in parameters).' , ), url='getEasingValue', ) ], client=[ FunctionData( signature=FunctionSignature( name='getEasingValue', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='fProgress', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='strEasingType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='fEasingPeriod', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingAmplitude', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingOvershoot', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='Used for custom Lua based interpolation, returns the easing value (animation time to use in your custom interpolation) given a progress and an Easing|easing function.\nIn most cases, either moveObject or interpolateBetween can do the job. getEasingValue is only provided in case you want to do your own custom interpolation based on easing.' , arguments={ "fProgress": """float between 0 and 1 indicating the interpolation progress (0 at the beginning of the interpolation, 1 at the end). """, "strEasingType": """the Easing|easing function to use for the interpolation """, "fEasingPeriod": """the period of the Easing|easing function (only some easing functions use this parameter) """, "fEasingAmplitude": """the amplitude of the Easing|easing function (only some easing functions use this parameter) """, "fEasingOvershoot": """the overshoot of the Easing|easing function (only some easing functions use this parameter) """ }, result='returns fanimationtime the animation time given by the easing function (can be < 0 or > 1 since some easing|easing functions have overshoot or bounce/spring effects, false otherwise (error in parameters).' , ), url='getEasingValue', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getFPSLimit', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function retrieves the maximum http://en.wikipedia.org/wiki/Frame_rate FPS (Frames per second) that players on the server can run their game at.' , arguments={ }, result='returns an integer between 25 and 100 of the maximum fps that players can run their game at.' , ), url='getFPSLimit', ) ], client=[ FunctionData( signature=FunctionSignature( name='getFPSLimit', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function retrieves the maximum http://en.wikipedia.org/wiki/Frame_rate FPS (Frames per second) that players on the server can run their game at.' , arguments={ }, result='returns an integer between 25 and 100 of the maximum fps that players can run their game at.' , ), url='getFPSLimit', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='getKeyboardLayout', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ }, result='returns a table with keyboard layout properties:\n{| class=wikitable style=cellpadding: 10px;\n|-\n! property || values and description\n|-\n| <code>readinglayout</code> ||\n{| class=prettytable\n|-\n| <code>ltr</code> || left to right (english)\n|-\n| <code>rtl</code> || right to left (arabic, hebrew)\n|-\n| <code>ttb-rtl-ltr</code> || either read vertically from top to bottom with columns going from right to left, or read in horizontal rows from left to right, as for the japanese (japan) locale.\n|-\n| <code>ttb-ltr</code> || read vertically from top to bottom with columns going from left to right, as for the mongolian (mongolian) locale.\n|}\n|}' , ), url='getKeyboardLayout', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='getLocalization', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function gets the players localization setting as set in the MTA client.' , arguments={ }, result='returns a table with the following entries:\n*code : the language code (eg. en_us for english (united states) or ar for arabic).\n*name : the name of the language (eg. english (united states) or arabic).' , ), url='getLocalization', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getNetworkStats', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='thePlayer', argument_type=FunctionType( names=['element'], is_optional=True, ), default_value='nil', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns network status information.' , arguments={ }, result='' , ), url='getNetworkStats', ) ], client=[ FunctionData( signature=FunctionSignature( name='getNetworkStats', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns network status information.' , arguments={ }, result='' , ), url='getNetworkStats', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getNetworkUsageData', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns a table containing network usage information about inbound and outbound packets.' , arguments={ }, result='returns a table with two fields: in and out. each of these contain a table with two fields: bits and count. each of these contain a table with 256 numeric fields ranging from 0 to 255, containing the appropriate network usage data for such packet id.' , ), url='getNetworkUsageData', ) ], client=[ FunctionData( signature=FunctionSignature( name='getNetworkUsageData', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns a table containing network usage information about inbound and outbound packets.' , arguments={ }, result='returns a table with two fields: in and out. each of these contain a table with two fields: bits and count. each of these contain a table with 256 numeric fields ranging from 0 to 255, containing the appropriate network usage data for such packet id.' , ), url='getNetworkUsageData', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getPerformanceStats', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ), FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='category', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['string'], is_optional=True, ), default_value='""', ) ], [ FunctionArgument( name='filter', argument_type=FunctionType( names=['string'], is_optional=True, ), default_value='""', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns performance information.' , arguments={ "category": """Performance statistics category. If empty string is given, list of all categories is returned.See categories for more information. """, "options": """Category specific , separated options. All categories supports h option for help. """, "filter": """Case-sensitive filter used to select returned rows. Only name column is filtered. """ }, result='returns two tables. first contains column names. the second contains result rows. each row is table of cells.' , ), url='getPerformanceStats', ) ], client=[ FunctionData( signature=FunctionSignature( name='getPerformanceStats', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ), FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='category', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['string'], is_optional=True, ), default_value='""', ) ], [ FunctionArgument( name='filter', argument_type=FunctionType( names=['string'], is_optional=True, ), default_value='""', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns performance information.' , arguments={ "category": """Performance statistics category. If empty string is given, list of all categories is returned.See categories for more information. """, "options": """Category specific , separated options. All categories supports h option for help. """, "filter": """Case-sensitive filter used to select returned rows. Only name column is filtered. """ }, result='returns two tables. first contains column names. the second contains result rows. each row is table of cells.' , ), url='getPerformanceStats', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getRealTime', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='seconds', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='current', ) ], [ FunctionArgument( name='localTime', argument_type=FunctionType( names=['bool'], is_optional=True, ), default_value='true', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function gets the server or client (if used client sided it returns time as set on clients computer) real time and returns it in a table. If you want to get the in-game time (shown on GTAs clock) use getTime.' , arguments={ "seconds": """A count in seconds from the year 1970. Useful for storing points in time, or for retrieving time information for getBanTime. The valid range of this argument is 0 to 32,000,000,000 """, "localTime": """Set to true to adjust for the locally set timezone. """ }, result='returns a table of substrings with different time format or false if the seconds argument is out of range.\n{| border=2 cellpadding=2 cellspacing=0 style=margin: 1em 1em 1em 0; background: #f9f9f9; border: 1px #aaa solid; border-collapse: collapse; font-size: 95%;\n|member\n|meaning\n|range\n|-\n|second\n|seconds after the minute\n|0-61*\n|-\n|minute\n|minutes after the hour\n|0-59\n|-\n|hour\n|hours since midnight\n|0-23\n|-\n|monthday\n|day of the month\n|1-31\n|-\n|month\n|months since january\n|0-11\n|-\n|year\n|years since 1900\n|-\n|weekday\n|days since sunday\n|0-6\n|-\n|yearday\n|days since january 1\n|0-365\n|-\n|isdst\n|daylight saving time flag\n|-\n|timestamp\n|seconds since 1970 (ignoring set timezone)\n|\n|}\n* second is generally 0-59. extra range to accommodate for leap seconds in certain systems.' , ), url='getRealTime', ) ], client=[ FunctionData( signature=FunctionSignature( name='getRealTime', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='seconds', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='current', ) ], [ FunctionArgument( name='localTime', argument_type=FunctionType( names=['bool'], is_optional=True, ), default_value='true', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function gets the server or client (if used client sided it returns time as set on clients computer) real time and returns it in a table. If you want to get the in-game time (shown on GTAs clock) use getTime.' , arguments={ "seconds": """A count in seconds from the year 1970. Useful for storing points in time, or for retrieving time information for getBanTime. The valid range of this argument is 0 to 32,000,000,000 """, "localTime": """Set to true to adjust for the locally set timezone. """ }, result='returns a table of substrings with different time format or false if the seconds argument is out of range.\n{| border=2 cellpadding=2 cellspacing=0 style=margin: 1em 1em 1em 0; background: #f9f9f9; border: 1px #aaa solid; border-collapse: collapse; font-size: 95%;\n|member\n|meaning\n|range\n|-\n|second\n|seconds after the minute\n|0-61*\n|-\n|minute\n|minutes after the hour\n|0-59\n|-\n|hour\n|hours since midnight\n|0-23\n|-\n|monthday\n|day of the month\n|1-31\n|-\n|month\n|months since january\n|0-11\n|-\n|year\n|years since 1900\n|-\n|weekday\n|days since sunday\n|0-6\n|-\n|yearday\n|days since january 1\n|0-365\n|-\n|isdst\n|daylight saving time flag\n|-\n|timestamp\n|seconds since 1970 (ignoring set timezone)\n|\n|}\n* second is generally 0-59. extra range to accommodate for leap seconds in certain systems.' , ), url='getRealTime', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getServerConfigSetting', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='name', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function retrieves server settings which are usually stored in the mtaserver.conf file.\nAvailable in 1.1 and onwards' , arguments={ "name": """The name of the setting (setting names can be found Server_mtaserver.conf|here) """ }, result='returns a string containing the current value for the named setting, or false if the setting does not exist.<br>\nif the setting name is serverip, may return the string auto on local servers.' , ), url='getServerConfigSetting', ) ], client=[ ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getTickCount', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns amount of time that your system has been running in milliseconds. By comparing two values of getTickCount, you can determine how much time has passed (in milliseconds) between two events. This could be used to determine how efficient your code is, or to time how long a player takes to complete a task.' , arguments={ }, result='returns an integer containing the number of milliseconds since the system the server is running on started. this has the potential to wrap-around.' , ), url='getTickCount', ) ], client=[ FunctionData( signature=FunctionSignature( name='getTickCount', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns amount of time that your system has been running in milliseconds. By comparing two values of getTickCount, you can determine how much time has passed (in milliseconds) between two events. This could be used to determine how efficient your code is, or to time how long a player takes to complete a task.' , arguments={ }, result='returns an integer containing the number of milliseconds since the system the server is running on started. this has the potential to wrap-around.' , ), url='getTickCount', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getTimerDetails', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function is for getting the details of a running timer.' , arguments={ "theTimer": """A timer element. """ }, result='* integer one represents the time left in miliseconds (1000th of a second) of the current time left in the loop.\n* integer two represents the amount of times the timer has left to execute.\n* integer three represents the time interval of timer.\n* returns false if the timer doesnt exist or stopped running. also, debugscript will say bad argument @ gettimerdetails. to prevent this, you can check if the timer exists with istimer().' , ), url='getTimerDetails', ) ], client=[ FunctionData( signature=FunctionSignature( name='getTimerDetails', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ), FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function is for getting the details of a running timer.' , arguments={ "theTimer": """A timer element. """ }, result='* integer one represents the time left in miliseconds (1000th of a second) of the current time left in the loop.\n* integer two represents the amount of times the timer has left to execute.\n* integer three represents the time interval of timer.\n* returns false if the timer doesnt exist or stopped running. also, debugscript will say bad argument @ gettimerdetails. to prevent this, you can check if the timer exists with istimer().' , ), url='getTimerDetails', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getTimers', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTime', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='nil', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns a table of all active timers that the resource that calls it has created. Alternatively, only the timers with a remaining time less than or equal to a certain value can be retrieved.' , arguments={ "theTime": """The maximum time left (in milliseconds) on the timers you wish to retrieve. """ }, result='returns a table of all the active timers.' , ), url='getTimers', ) ], client=[ FunctionData( signature=FunctionSignature( name='getTimers', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTime', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='nil', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns a table of all active timers that the resource that calls it has created. Alternatively, only the timers with a remaining time less than or equal to a certain value can be retrieved.' , arguments={ "theTime": """The maximum time left (in milliseconds) on the timers you wish to retrieve. """ }, result='returns a table of all the active timers.' , ), url='getTimers', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='gettok', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='text', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='tokenNumber', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='separatingCharacter', argument_type=FunctionType( names=['string', 'int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function splits a string using the given separating character and returns one specified substring.' , arguments={ "text": """the string that should be split. """, "tokenNumber": """which token should be returned (1 for the first, 2 for the second, and so on). """, "separatingCharacter": """the ASCII|ASCII number representing the character you want to use to separate the tokens. You can easily retrieve this by running string.byte on a string containing the separating character. """ }, result='returns a string containing the token if it exists, false otherwise.' , ), url='gettok', ) ], client=[ FunctionData( signature=FunctionSignature( name='gettok', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='text', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='tokenNumber', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='separatingCharacter', argument_type=FunctionType( names=['string', 'int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function splits a string using the given separating character and returns one specified substring.' , arguments={ "text": """the string that should be split. """, "tokenNumber": """which token should be returned (1 for the first, 2 for the second, and so on). """, "separatingCharacter": """the ASCII|ASCII number representing the character you want to use to separate the tokens. You can easily retrieve this by running string.byte on a string containing the separating character. """ }, result='returns a string containing the token if it exists, false otherwise.' , ), url='gettok', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getUserdataType', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['userdata'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ "value": """: A userdata value to get the type of. Userdata types can be: """, "Shared": """ """, "resource-data": """: a Resource|resource pointer. """, "xml-node": """: a Xmlnode|XML node. """, "lua-timer": """: a timer. """, "vector2": """: a 2D vector, used in the Vector/Vector2|Vector2 class. """, "vector3": """: a 3D vector, used in the Vector/Vector3|Vector3 class. """, "vector4": """: a 4D vector, used in the Vector/Vector4|Vector4 class. """, "matrix": """: a matrix, used in the Matrix class. """, "userdata": """: a fallback userdata type return value, when no other type could be found for the object. """, "Server only": """ """, "account": """: a Account|player account. """, "db-query": """: a dbQuery|database query handle. """, "acl": """: an ACL|ACL entry. """, "acl-group": """: an Aclgroup|ACL group. """, "ban": """: a Ban|player ban. """, "text-item": """: a Textitem|text display item. """, "text-display": """: a Textdisplay|text display item. Source code commit: https://github.com/multitheftauto/mtasa-blue/commit/df8576fc3f80fa2d7a73e70a68e8f116b591cb68#diff-09a3546021ff952dc0f94a99aae11356R297 """, "weapon": """: a Weapon|custom weapon. """ }, result='returns a string containing the specified userdatas type, or false plus an error message if the given value is not userdata.' , ), url='getUserdataType', ) ], client=[ FunctionData( signature=FunctionSignature( name='getUserdataType', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['userdata'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ "value": """: A userdata value to get the type of. Userdata types can be: """, "Shared": """ """, "resource-data": """: a Resource|resource pointer. """, "xml-node": """: a Xmlnode|XML node. """, "lua-timer": """: a timer. """, "vector2": """: a 2D vector, used in the Vector/Vector2|Vector2 class. """, "vector3": """: a 3D vector, used in the Vector/Vector3|Vector3 class. """, "vector4": """: a 4D vector, used in the Vector/Vector4|Vector4 class. """, "matrix": """: a matrix, used in the Matrix class. """, "userdata": """: a fallback userdata type return value, when no other type could be found for the object. """, "Server only": """ """, "account": """: a Account|player account. """, "db-query": """: a dbQuery|database query handle. """, "acl": """: an ACL|ACL entry. """, "acl-group": """: an Aclgroup|ACL group. """, "ban": """: a Ban|player ban. """, "text-item": """: a Textitem|text display item. """, "text-display": """: a Textdisplay|text display item. Source code commit: https://github.com/multitheftauto/mtasa-blue/commit/df8576fc3f80fa2d7a73e70a68e8f116b591cb68#diff-09a3546021ff952dc0f94a99aae11356R297 """, "weapon": """: a Weapon|custom weapon. """ }, result='returns a string containing the specified userdatas type, or false plus an error message if the given value is not userdata.' , ), url='getUserdataType', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='getVersion', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function gives you various version information about MTA and the operating system.' , arguments={ }, result='returns a table with version information. specifically these keys are present in the table:\n*number: the mta server or client version (depending where the function was called) in pure numerical form, e.g. 256\n*mta: the mta server or client version (depending where the function was called) in textual form, e.g. 1.0\n*name: the full mta product name, either mta:sa server or mta:sa client.\n*netcode: the netcode version number.\n*os: returns the operating system on which the server or client is running\n*type: the type of build. can be:\n**nightly rx - a nightly development build. x represents the nightly build revision.\n**custom - a build compiled manually\n**release - a build that is publicly released (provisional).\n*tag: the build tag (from 1.0.3 onwards). contains infomation about the underlying version used. i.e. the final version of 1.0.3 has the build tag of 1.0.3 rc-9. (this can be confirmed by using the console command ver.)\n*sortable: a 15 character sortable version string (from 1.0.4 onwards). format of the string is described in getplayerversion.' , ), url='getVersion', ) ], client=[ FunctionData( signature=FunctionSignature( name='getVersion', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function gives you various version information about MTA and the operating system.' , arguments={ }, result='returns a table with version information. specifically these keys are present in the table:\n*number: the mta server or client version (depending where the function was called) in pure numerical form, e.g. 256\n*mta: the mta server or client version (depending where the function was called) in textual form, e.g. 1.0\n*name: the full mta product name, either mta:sa server or mta:sa client.\n*netcode: the netcode version number.\n*os: returns the operating system on which the server or client is running\n*type: the type of build. can be:\n**nightly rx - a nightly development build. x represents the nightly build revision.\n**custom - a build compiled manually\n**release - a build that is publicly released (provisional).\n*tag: the build tag (from 1.0.3 onwards). contains infomation about the underlying version used. i.e. the final version of 1.0.3 has the build tag of 1.0.3 rc-9. (this can be confirmed by using the console command ver.)\n*sortable: a 15 character sortable version string (from 1.0.4 onwards). format of the string is described in getplayerversion.' , ), url='getVersion', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='hash', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='dataToHash', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns a hash of the specified string in the specified algorithm.' , arguments={ "algorithm": """: A string which must be one of these: md5, sha1, sha224, sha256, sha384, sha512 """, "dataToHash": """: A string of the data to hash. """ }, result='returns the hash of the data, false if an invalid argument was used.' , ), url='hash', ) ], client=[ FunctionData( signature=FunctionSignature( name='hash', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='dataToHash', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns a hash of the specified string in the specified algorithm.' , arguments={ "algorithm": """: A string which must be one of these: md5, sha1, sha224, sha256, sha384, sha512 """, "dataToHash": """: A string of the data to hash. """ }, result='returns the hash of the data, false if an invalid argument was used.' , ), url='hash', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='inspect', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['mixed'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns human-readable representations of tables and MTA datatypes as a string.' , arguments={ "var": """A variable of any datatype. """, "options": """A table of options. It is not mandatory, but when it is provided, it must be a table. For a list of options, see the https://github.com/kikito/inspect.lua#options Inspects GitHub page. """ }, result='always returns a string. the contents can change if we update the inspect library, so it is not expected to be consistent across lua versions.' , ), url='inspect', ) ], client=[ FunctionData( signature=FunctionSignature( name='inspect', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var', argument_type=FunctionType( names=['mixed'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns human-readable representations of tables and MTA datatypes as a string.' , arguments={ "var": """A variable of any datatype. """, "options": """A table of options. It is not mandatory, but when it is provided, it must be a table. For a list of options, see the https://github.com/kikito/inspect.lua#options Inspects GitHub page. """ }, result='always returns a string. the contents can change if we update the inspect library, so it is not expected to be consistent across lua versions.' , ), url='inspect', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='interpolateBetween', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ), FunctionType( names=['float'], is_optional=False, ), FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='x1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='x2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='fProgress', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='strEasingType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='fEasingPeriod', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingAmplitude', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingOvershoot', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='Interpolates a 3D Vector between a source value and a target value using either linear interpolation or any other Easing|easing function.\nIt can also be used to interpolate 2D vectors or scalars by only setting some of the x, y, z values and putting 0 to the others.' , arguments={ "x1, y1, z1": """3D coordinates of source vector/value """, "x2, y2, z2": """3D coordinates of target vector/value """, "fProgress": """float between 0 and 1 indicating the interpolation progress (0 at the beginning of the interpolation, 1 at the end). If it is higher than 1, it will start from the beginning. """, "strEasingType": """the Easing|easing function to use for the interpolation """, "fEasingPeriod": """the period of the Easing|easing function (only some easing functions use this parameter) """, "fEasingAmplitude": """the amplitude of the Easing|easing function (only some easing functions use this parameter) """, "fEasingOvershoot": """the overshoot of the Easing|easing function (only some easing functions use this parameter) """ }, result='returns x, y, z the interpolated 3d vector/value if successful, false otherwise (error in parameters).\nas mentioned before, interpolatebetween can be used on 2d vectors or scalars in which case only some (x, y or just x) of the returned values are to be used (cf. alpha interpolation in marker example or size interpolation in window example).' , ), url='interpolateBetween', ) ], client=[ FunctionData( signature=FunctionSignature( name='interpolateBetween', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['float'], is_optional=False, ), FunctionType( names=['float'], is_optional=False, ), FunctionType( names=['float'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='x1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z1', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='x2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='y2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='z2', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='fProgress', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='strEasingType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='fEasingPeriod', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingAmplitude', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='fEasingOvershoot', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='Interpolates a 3D Vector between a source value and a target value using either linear interpolation or any other Easing|easing function.\nIt can also be used to interpolate 2D vectors or scalars by only setting some of the x, y, z values and putting 0 to the others.' , arguments={ "x1, y1, z1": """3D coordinates of source vector/value """, "x2, y2, z2": """3D coordinates of target vector/value """, "fProgress": """float between 0 and 1 indicating the interpolation progress (0 at the beginning of the interpolation, 1 at the end). If it is higher than 1, it will start from the beginning. """, "strEasingType": """the Easing|easing function to use for the interpolation """, "fEasingPeriod": """the period of the Easing|easing function (only some easing functions use this parameter) """, "fEasingAmplitude": """the amplitude of the Easing|easing function (only some easing functions use this parameter) """, "fEasingOvershoot": """the overshoot of the Easing|easing function (only some easing functions use this parameter) """ }, result='returns x, y, z the interpolated 3d vector/value if successful, false otherwise (error in parameters).\nas mentioned before, interpolatebetween can be used on 2d vectors or scalars in which case only some (x, y or just x) of the returned values are to be used (cf. alpha interpolation in marker example or size interpolation in window example).' , ), url='interpolateBetween', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='iprint', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['mixed'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['mixed'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='var3', argument_type=FunctionType( names=['mixed'], is_optional=True, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function intelligently outputs debug messages into the Debug Console. It is similar to outputDebugString, but outputs useful information for any variable type, and does not require use of Luas tostring. This includes information about element types, and table structures. It is especially useful for quick debug tasks.' , arguments={ "var1": """A variable of any type to print intelligent information for. """, "var2+": """Another variable to be output. An unlimited number of arguments can be supplied """ }, result='always returns nil.' , ), url='iprint', ) ], client=[ FunctionData( signature=FunctionSignature( name='iprint', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='var1', argument_type=FunctionType( names=['mixed'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='var2', argument_type=FunctionType( names=['mixed'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='var3', argument_type=FunctionType( names=['mixed'], is_optional=True, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function intelligently outputs debug messages into the Debug Console. It is similar to outputDebugString, but outputs useful information for any variable type, and does not require use of Luas tostring. This includes information about element types, and table structures. It is especially useful for quick debug tasks.' , arguments={ "var1": """A variable of any type to print intelligent information for. """, "var2+": """Another variable to be output. An unlimited number of arguments can be supplied """ }, result='always returns nil.' , ), url='iprint', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='isOOPEnabled', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ }, result='returns true or false if oop is enabled or not. returns nil if an error arised.' , ), url='isOOPEnabled', ) ], client=[ FunctionData( signature=FunctionSignature( name='isOOPEnabled', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ }, result='returns true or false if oop is enabled or not. returns nil if an error arised.' , ), url='isOOPEnabled', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='isShowCollisionsEnabled', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ }, result='* returns true if the collision previews are enabled, false otherwise.' , ), url='isShowCollisionsEnabled', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='isShowSoundEnabled', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ }, result='* returns true if world sound ids should be printed in the debug window, false otherwise.' , ), url='isShowSoundEnabled', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='isTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function checks if a variable is a timer.' , arguments={ "theTimer": """: The variable that we want to check. """ }, result='returns true if the passed value is a timer, false otherwise.' , ), url='isTimer', ) ], client=[ FunctionData( signature=FunctionSignature( name='isTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function checks if a variable is a timer.' , arguments={ "theTimer": """: The variable that we want to check. """ }, result='returns true if the passed value is a timer, false otherwise.' , ), url='isTimer', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='isTrayNotificationEnabled', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns a boolean value whether the client has enabled tray notifications in his settings or not.' , arguments={ }, result='returns true if the tray notifications are enabled in the settings, false otherwise.' , ), url='isTrayNotificationEnabled', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='killTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows you to kill/halt existing timers.' , arguments={ "theTimer": """The timer you wish to halt. """ }, result='returns true if the timer was successfully killed, false if no such timer existed.' , ), url='killTimer', ) ], client=[ FunctionData( signature=FunctionSignature( name='killTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows you to kill/halt existing timers.' , arguments={ "theTimer": """The timer you wish to halt. """ }, result='returns true if the timer was successfully killed, false if no such timer existed.' , ), url='killTimer', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='md5', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='str', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='Calculates the MD5 hash of the specified string and returns its hexadecimal representation.' , arguments={ "str": """the string to hash. """ }, result='returns the md5 hash of the input string if successful, false otherwise.' , ), url='md5', ) ], client=[ FunctionData( signature=FunctionSignature( name='md5', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='str', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='Calculates the MD5 hash of the specified string and returns its hexadecimal representation.' , arguments={ "str": """the string to hash. """ }, result='returns the md5 hash of the input string if successful, false otherwise.' , ), url='md5', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='passwordHash', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='password', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function creates a new password hash using a specified hashing algorithm.' , arguments={ "password": """The password to hash. """, "algorithm": """The algorithm to use: """, "bcrypt": """: use the bcrypt hashing algorithm. Hash length: 60 characters. <span style=color:red>Note that only the prefix $2y$ is supported (older prefixes can cause security issues).</span> """, "options": """table with options for the hashing algorithm, as detailed below. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. """ }, result='returns the hash as a string if hashing was successful, false otherwise. if a callback was provided, the aforementioned values are arguments to the callback, and this function will always return true.' , ), url='passwordHash', ) ], client=[ FunctionData( signature=FunctionSignature( name='passwordHash', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='password', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='algorithm', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function creates a new password hash using a specified hashing algorithm.' , arguments={ "password": """The password to hash. """, "algorithm": """The algorithm to use: """, "bcrypt": """: use the bcrypt hashing algorithm. Hash length: 60 characters. <span style=color:red>Note that only the prefix $2y$ is supported (older prefixes can cause security issues).</span> """, "options": """table with options for the hashing algorithm, as detailed below. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. """ }, result='returns the hash as a string if hashing was successful, false otherwise. if a callback was provided, the aforementioned values are arguments to the callback, and this function will always return true.' , ), url='passwordHash', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='passwordVerify', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='password', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='hash', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function verifies whether a password matches a password hash.' , arguments={ "password": """The password to check. """, "hash": """A supported hash (see passwordHash). <span style=color:red>Note that only the prefix $2y$ is supported for type bcrypt (older prefixes can cause security issues).</span> """, "options": """advanced options """, "insecureBcrypt": """If set to true, you can use the $2a$ prefix for bcrypt hashes as well. It is strongly not recommended to use it though, because the underlying implementation has a bug that leads to such hashes being relatively easy to crack. This bug was fixed for $2y$. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. |11281}} """ }, result='returns true if the password matches the hash. returns false if the password does not match, or if an unknown hash was passed. if a callback was provided, the aforementioned values are arguments to the callback, and this function will always return true.' , ), url='passwordVerify', ) ], client=[ FunctionData( signature=FunctionSignature( name='passwordVerify', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='password', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='hash', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='options', argument_type=FunctionType( names=['table'], is_optional=True, ), default_value=None, ) ], [ FunctionArgument( name='callback', argument_type=FunctionType( names=['function'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function verifies whether a password matches a password hash.' , arguments={ "password": """The password to check. """, "hash": """A supported hash (see passwordHash). <span style=color:red>Note that only the prefix $2y$ is supported for type bcrypt (older prefixes can cause security issues).</span> """, "options": """advanced options """, "insecureBcrypt": """If set to true, you can use the $2a$ prefix for bcrypt hashes as well. It is strongly not recommended to use it though, because the underlying implementation has a bug that leads to such hashes being relatively easy to crack. This bug was fixed for $2y$. """, "callback": """providing a callback will run this function asynchronously, the arguments to the callback are the same as the returned values below. |11281}} """ }, result='returns true if the password matches the hash. returns false if the password does not match, or if an unknown hash was passed. if a callback was provided, the aforementioned values are arguments to the callback, and this function will always return true.' , ), url='passwordVerify', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='pregFind', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='subject', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='pattern', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='flags', argument_type=FunctionType( names=['int', 'string'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function stops at the first occurrence of the pattern in the input string and returns the result of the search.' , arguments={ "subject": """The input string """, "pattern": """The pattern string to search for in the input string. """, "flags": """Conjuncted value that contains flags ( 1 - ignorecase, 2 - multiline, 4 - dotall, 8 - extended, 16 - unicode ) or ( i - Ignore case, m - Multiline, d - Dotall, e - Extended, u - Unicode ) """ }, result='returns true if the pattern was found in the input string, false otherwise.' , ), url='pregFind', ) ], client=[ FunctionData( signature=FunctionSignature( name='pregFind', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='subject', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='pattern', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='flags', argument_type=FunctionType( names=['int', 'string'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function stops at the first occurrence of the pattern in the input string and returns the result of the search.' , arguments={ "subject": """The input string """, "pattern": """The pattern string to search for in the input string. """, "flags": """Conjuncted value that contains flags ( 1 - ignorecase, 2 - multiline, 4 - dotall, 8 - extended, 16 - unicode ) or ( i - Ignore case, m - Multiline, d - Dotall, e - Extended, u - Unicode ) """ }, result='returns true if the pattern was found in the input string, false otherwise.' , ), url='pregFind', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='pregMatch', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='base', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='pattern', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='flags', argument_type=FunctionType( names=['int', 'string'], is_optional=True, ), default_value='0', ) ], [ FunctionArgument( name='maxResults', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='100000', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns all matches.' , arguments={ "base": """The base string for replace. """, "pattern": """The pattern for match in base string. """, "flags": """Conjuncted value that contains flags ( 1 - ignorecase, 2 - multiline, 4 - dotall, 8 - extended, 16 - unicode ) or ( i - Ignore case, m - Multiline, d - Dotall, e - Extended, u - Unicode ) """, "maxResults": """Maximum number of results to return """ }, result='returns a table if one or more match is found, false otherwise.' , ), url='pregMatch', ) ], client=[ FunctionData( signature=FunctionSignature( name='pregMatch', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='base', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='pattern', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='flags', argument_type=FunctionType( names=['int', 'string'], is_optional=True, ), default_value='0', ) ], [ FunctionArgument( name='maxResults', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='100000', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function returns all matches.' , arguments={ "base": """The base string for replace. """, "pattern": """The pattern for match in base string. """, "flags": """Conjuncted value that contains flags ( 1 - ignorecase, 2 - multiline, 4 - dotall, 8 - extended, 16 - unicode ) or ( i - Ignore case, m - Multiline, d - Dotall, e - Extended, u - Unicode ) """, "maxResults": """Maximum number of results to return """ }, result='returns a table if one or more match is found, false otherwise.' , ), url='pregMatch', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='pregReplace', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='subject', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='pattern', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='replacement', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='flags', argument_type=FunctionType( names=['int', 'string'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a regular expression search and replace and returns the replaced string.' , arguments={ "subject": """The input string. """, "pattern": """The pattern string to search for in the input string. """, "replacement": """The replacement string to replace all matches within the input string. """, "flags": """Conjuncted value that contains flags ( 1 - ignorecase, 2 - multiline, 4 - dotall, 8 - extended, 16 - unicode ) or ( i - Ignore case, m - Multiline, d - Dotall, e - Extended, u - Unicode ) """ }, result='returns the replaced string, or bool false otherwise.' , ), url='pregReplace', ) ], client=[ FunctionData( signature=FunctionSignature( name='pregReplace', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='subject', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='pattern', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='replacement', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='flags', argument_type=FunctionType( names=['int', 'string'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function performs a regular expression search and replace and returns the replaced string.' , arguments={ "subject": """The input string. """, "pattern": """The pattern string to search for in the input string. """, "replacement": """The replacement string to replace all matches within the input string. """, "flags": """Conjuncted value that contains flags ( 1 - ignorecase, 2 - multiline, 4 - dotall, 8 - extended, 16 - unicode ) or ( i - Ignore case, m - Multiline, d - Dotall, e - Extended, u - Unicode ) """ }, result='returns the replaced string, or bool false otherwise.' , ), url='pregReplace', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='ref', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='objectToReference', argument_type=FunctionType( names=['mixed'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function will create a reference to the given argument.' , arguments={ "objectToReference": """The Lua element, which you want to reference """ }, result='returns an int if the reference were successfully created. returns false if the parameter were invalid.' , ), url='ref', ) ], client=[ FunctionData( signature=FunctionSignature( name='ref', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='objectToReference', argument_type=FunctionType( names=['mixed'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function will create a reference to the given argument.' , arguments={ "objectToReference": """The Lua element, which you want to reference """ }, result='returns an int if the reference were successfully created. returns false if the parameter were invalid.' , ), url='ref', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='removeDebugHook', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='hookType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callbackFunction', argument_type=FunctionType( names=['function'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function removes hooks added by addDebugHook' , arguments={ "hookType": """The type of hook to remove. This can be: ** preEvent ** postEvent ** preFunction ** postFunction """, "callbackFunction": """The callback function to remove """ }, result='returns true if the hook was successfully removed, or false otherwise.' , ), url='removeDebugHook', ) ], client=[ FunctionData( signature=FunctionSignature( name='removeDebugHook', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='hookType', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='callbackFunction', argument_type=FunctionType( names=['function'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function removes hooks added by addDebugHook' , arguments={ "hookType": """The type of hook to remove. This can be: ** preEvent ** postEvent ** preFunction ** postFunction """, "callbackFunction": """The callback function to remove """ }, result='returns true if the hook was successfully removed, or false otherwise.' , ), url='removeDebugHook', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='resetTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows you to reset the elapsed time in existing timers to zero. The function does not reset the times to execute count on timers which have a limited amout of repetitions.' , arguments={ "theTimer": """The timer whose elapsed time you wish to reset. """ }, result='returns true if the timer was successfully reset, false otherwise.' , ), url='resetTimer', ) ], client=[ FunctionData( signature=FunctionSignature( name='resetTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theTimer', argument_type=FunctionType( names=['timer'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows you to reset the elapsed time in existing timers to zero. The function does not reset the times to execute count on timers which have a limited amout of repetitions.' , arguments={ "theTimer": """The timer whose elapsed time you wish to reset. """ }, result='returns true if the timer was successfully reset, false otherwise.' , ), url='resetTimer', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='setClipboard', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theText', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function sets the players clipboard text (what appears when you paste with CTRL + V)' , arguments={ "theText": """The new text to be in the players clipboard when the player pastes with CTRL + V. """ }, result='returns true if the text in the clip board was set correctly.' , ), url='setClipboard', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='setDevelopmentMode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='enable', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='enableWeb', argument_type=FunctionType( names=['bool'], is_optional=True, ), default_value='false', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function is used to set the development mode. Setting development mode allows access to special commands which can assist with script debugging.\nClient-side development mode commands:\n* Client_Commands#showcol|showcol: Enables colshapes to be viewed as a wireframe object.\n* Client_Commands#showsound|showsound: Enables world sound ids to be printed in the debug output window.\nShared development mode functions:\n* debugSleep: Sets the freeze time for the client/server.' , arguments={ "enable": """: A boolean to indicate whether development mode is on (true) or off (false) """, "enableWeb": """: A boolean to indicate whether browser debug messages will be filtered (false) or not (true) """ }, result='returns true if the mode was set correctly, false otherwise.' , ), url='setDevelopmentMode', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='setFPSLimit', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='fpsLimit', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function sets the maximum http://en.wikipedia.org/wiki/Frame_rate FPS (Frames per second) that players on the server can run their game at.' , arguments={ "fpsLimit": """An integer value representing the maximum FPS. This value may be between 25 and 100 FPS. You can also pass 0 or false, in which case the FPS limit will be the one set in the client settings (by default, 100 FPS and the client fps limit should also be manually changed via fps_limit=0 in console or MTA San Andreas 1.5\MTA\config\coreconfig.xml). """ }, result='returns true if successful, or false if it was not possible to set the limit or an invalid value was passed.' , ), url='setFPSLimit', ) ], client=[ FunctionData( signature=FunctionSignature( name='setFPSLimit', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='fpsLimit', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function sets the maximum http://en.wikipedia.org/wiki/Frame_rate FPS (Frames per second) that players on the server can run their game at.' , arguments={ "fpsLimit": """An integer value representing the maximum FPS. This value may be between 25 and 100 FPS. You can also pass 0 or false, in which case the FPS limit will be the one set in the client settings (by default, 100 FPS and the client fps limit should also be manually changed via fps_limit=0 in console or MTA San Andreas 1.5\MTA\config\coreconfig.xml). """ }, result='returns true if successful, or false if it was not possible to set the limit or an invalid value was passed.' , ), url='setFPSLimit', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='setServerConfigSetting', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='name', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='value', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='bSave', argument_type=FunctionType( names=['bool'], is_optional=True, ), default_value='false', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function sets server settings which are stored in the Server mtaserver.conf|mtaserver.conf file.' , arguments={ "name": """The name of the setting. Only certain settings from Server mtaserver.conf|mtaserver.conf can be changed with this function. These are: ** minclientversion ** recommendedclientversion ** password ** fpslimit - (0-100) ** networkencryption - 0 for off, 1 for on ** bandwidth_reduction - "none", "medium", "maximum" Set to maximum for less bandwidth usage (medium is recommended for race servers) ** player_sync_interval - See [[Sync_interval_settings]] for all *_sync_interval settings ** lightweight_sync_interval ** camera_sync_interval ** ped_sync_interval ** unoccupied_vehicle_sync_interval ** keysync_mouse_sync_interval ** keysync_analog_sync_interval ** bullet_sync """, "value": """The value of the setting """, "bSave": """Set to true to make the setting permanent, or false for use only until the next server restart. """ }, result='returns true if the setting was successfully set, or false otherwise.' , ), url='setServerConfigSetting', ) ], client=[ ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='setTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['timer'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theFunction', argument_type=FunctionType( names=['function'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='timeInterval', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='timesToExecute', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='arguments', argument_type=FunctionType( names=['var'], is_optional=True, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows you to trigger a function after a number of milliseconds have elapsed. You can call one of your own functions or a built-in function. For example, you could set a timer to spawn a player after a number of seconds have elapsed.\nOnce a timer has finished repeating, it no longer exists.\nThe minimum accepted interval is 0ms.\nMulti Theft Auto guarantees that the timer will be triggered after at least the interval you specify. The resolution of the timer is tied to the frame rate (server side and client-side). All the overdue timers are triggered at a single point each frame. This means that if, for example, the player is running at 30 frames per second, then two timers specified to occur after 100ms and 110ms would more than likely occur during the same frame, as the difference in time between the two timers (10ms) is less than half the length of the frame (33ms). As with most timers provided by other languages, you shouldnt rely on the timer triggering at an exact point in the future.' , arguments={ "theFunction": """The function you wish the timer to call. """, "timeInterval": """The number of milliseconds that should elapse before the function is called. (the minimum is 50 (0 on 1.5.6 r16715); 1000 milliseconds = 1 second) """, "timesToExecute": """The number of times you want the timer to execute, or 0 for infinite repetitions. """, "arguments": """Any arguments you wish to pass to the function can be listed after the timesToExecute argument. Note that any tables you want to pass will get cloned, whereas metatables and functions/function references in that passed table will get lost. Also changes you make in the original table before the function gets called wont get transferred. """ }, result='returns a timer pointer if the timer was set successfully, false if the arguments are invalid or the timer could not be set.' , ), url='setTimer', ) ], client=[ FunctionData( signature=FunctionSignature( name='setTimer', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['timer'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theFunction', argument_type=FunctionType( names=['function'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='timeInterval', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='timesToExecute', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='arguments', argument_type=FunctionType( names=['var'], is_optional=True, ), default_value=None, ) ] ], variable_length=True, ), generic_types=[ ], ), docs=FunctionDoc( description='This function allows you to trigger a function after a number of milliseconds have elapsed. You can call one of your own functions or a built-in function. For example, you could set a timer to spawn a player after a number of seconds have elapsed.\nOnce a timer has finished repeating, it no longer exists.\nThe minimum accepted interval is 0ms.\nMulti Theft Auto guarantees that the timer will be triggered after at least the interval you specify. The resolution of the timer is tied to the frame rate (server side and client-side). All the overdue timers are triggered at a single point each frame. This means that if, for example, the player is running at 30 frames per second, then two timers specified to occur after 100ms and 110ms would more than likely occur during the same frame, as the difference in time between the two timers (10ms) is less than half the length of the frame (33ms). As with most timers provided by other languages, you shouldnt rely on the timer triggering at an exact point in the future.' , arguments={ "theFunction": """The function you wish the timer to call. """, "timeInterval": """The number of milliseconds that should elapse before the function is called. (the minimum is 50 (0 on 1.5.6 r16715); 1000 milliseconds = 1 second) """, "timesToExecute": """The number of times you want the timer to execute, or 0 for infinite repetitions. """, "arguments": """Any arguments you wish to pass to the function can be listed after the timesToExecute argument. Note that any tables you want to pass will get cloned, whereas metatables and functions/function references in that passed table will get lost. Also changes you make in the original table before the function gets called wont get transferred. """ }, result='returns a timer pointer if the timer was set successfully, false if the arguments are invalid or the timer could not be set.' , ), url='setTimer', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='setWindowFlashing', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='shouldFlash', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='count', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='10', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ "shouldFlash": """whether the window should flash """, "count": """the number of times the window should flash, defaults to 10 times """ }, result='returns false if:\n* the window is already in focus\n* the client has disabled this feature\nreturns true otherwise' , ), url='setWindowFlashing', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='sha256', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='str', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='* The sha module and this function may conflict with eachother, if you use this function uninstall the module!\n* This function returns an uppercase string, so make sure you string.upper() anything else you are checking against that has been sha256d elsewhere.}}\nCalculates the sha256 hash of the specified string.' , arguments={ "str": """the string to hash. """ }, result='returns the sha256 hash of the input string if successful, false otherwise.' , ), url='sha256', ) ], client=[ FunctionData( signature=FunctionSignature( name='sha256', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='str', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='* The sha module and this function may conflict with eachother, if you use this function uninstall the module!\n* This function returns an uppercase string, so make sure you string.upper() anything else you are checking against that has been sha256d elsewhere.}}\nCalculates the sha256 hash of the specified string.' , arguments={ "str": """the string to hash. """ }, result='returns the sha256 hash of the input string if successful, false otherwise.' , ), url='sha256', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='showCol', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='state', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ "state": """A boolean indicating if the collision previews should be enabled or disabled. """ }, result='* returns true if the function is successful, false otherwise.' , ), url='showCol', ) ], ), CompoundFunctionData( server=[ ], client=[ FunctionData( signature=FunctionSignature( name='showSound', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['bool'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='state', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='' , arguments={ "state": """A boolean indicating if the world sound IDs should be printed in the debug window or not. """ }, result='* returns true if the function is successful, false otherwise.' , ), url='showSound', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='split', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='stringToSplit', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='separatingChar', argument_type=FunctionType( names=['string', 'int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function splits a string into substrings. You specify a character that will act as a separating character; this will determine where to split the sub-strings. For example, it can split the string Hello World into two strings containing the two words, by spliting using a space as a separator.\nNote: You can use the function gettok to retrieve a single token from the string at a specific index. This may be faster for one-off lookups, but considerably slower if you are going to check each token in a long string.' , arguments={ "stringToSplit": """The string you wish to split into parts. """, "separatingChar": """A string of the character you want to split, or the ASCII|ASCII number representing the character you want to use to split. """ }, result='returns a table of substrings split from the original string if successful, false otherwise.' , ), url='split', ) ], client=[ FunctionData( signature=FunctionSignature( name='split', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['table'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='stringToSplit', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='separatingChar', argument_type=FunctionType( names=['string', 'int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function splits a string into substrings. You specify a character that will act as a separating character; this will determine where to split the sub-strings. For example, it can split the string Hello World into two strings containing the two words, by spliting using a space as a separator.\nNote: You can use the function gettok to retrieve a single token from the string at a specific index. This may be faster for one-off lookups, but considerably slower if you are going to check each token in a long string.' , arguments={ "stringToSplit": """The string you wish to split into parts. """, "separatingChar": """A string of the character you want to split, or the ASCII|ASCII number representing the character you want to use to split. """ }, result='returns a table of substrings split from the original string if successful, false otherwise.' , ), url='split', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='teaDecode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='data', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='key', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function decrypts given https://en.wikipedia.org/wiki/Base64 base64 representation of encrypted data using the https://en.wikipedia.org/wiki/Tiny_Encryption_Algorithm Tiny Encryption Algorithm.' , arguments={ "data": """The block of data you want to decrypt """, "key": """The key that should be used for decryption (Only first 16 characters are used) """ }, result='returns string containing the decrypted data if the decryption process was successfully completed, false otherwise.' , ), url='teaDecode', ) ], client=[ FunctionData( signature=FunctionSignature( name='teaDecode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='data', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='key', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function decrypts given https://en.wikipedia.org/wiki/Base64 base64 representation of encrypted data using the https://en.wikipedia.org/wiki/Tiny_Encryption_Algorithm Tiny Encryption Algorithm.' , arguments={ "data": """The block of data you want to decrypt """, "key": """The key that should be used for decryption (Only first 16 characters are used) """ }, result='returns string containing the decrypted data if the decryption process was successfully completed, false otherwise.' , ), url='teaDecode', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='teaEncode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='text', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='key', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs the https://en.wikipedia.org/wiki/Tiny_Encryption_Algorithm Tiny Encryption Algorithm on the given string and returns the https://en.wikipedia.org/wiki/Base64 base64 representation of the encrypted string.' , arguments={ "text": """The string you want to encrypt. (See second example if you want to encode binary data) """, "key": """The key that should be used for encryption (Only first 16 characters are used) """ }, result='returns the https://en.wikipedia.org/wiki/base64 base64 representation of the encrypted string if the encryption process was successfully completed, false otherwise.' , ), url='teaEncode', ) ], client=[ FunctionData( signature=FunctionSignature( name='teaEncode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='text', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='key', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This functions performs the https://en.wikipedia.org/wiki/Tiny_Encryption_Algorithm Tiny Encryption Algorithm on the given string and returns the https://en.wikipedia.org/wiki/Base64 base64 representation of the encrypted string.' , arguments={ "text": """The string you want to encrypt. (See second example if you want to encode binary data) """, "key": """The key that should be used for encryption (Only first 16 characters are used) """ }, result='returns the https://en.wikipedia.org/wiki/base64 base64 representation of the encrypted string if the encryption process was successfully completed, false otherwise.' , ), url='teaEncode', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='tocolor', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='red', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='green', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='blue', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='alpha', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='255', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function retrieves the hex number of a specified color, useful for the dx functions.' , arguments={ "red": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space red in the color (0-255). """, "green": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space green in the color (0-255). """, "blue": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space blue in the color (0-255). """, "alpha": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space alpha in the color (0-255). """ }, result='returns a single value representing the color.' , ), url='tocolor', ) ], client=[ FunctionData( signature=FunctionSignature( name='tocolor', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='red', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='green', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='blue', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='alpha', argument_type=FunctionType( names=['int'], is_optional=True, ), default_value='255', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function retrieves the hex number of a specified color, useful for the dx functions.' , arguments={ "red": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space red in the color (0-255). """, "green": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space green in the color (0-255). """, "blue": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space blue in the color (0-255). """, "alpha": """The amount of http://en.wikipedia.org/wiki/RGBA_color_space alpha in the color (0-255). """ }, result='returns a single value representing the color.' , ), url='tocolor', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='toJSON', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['var'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='compact', argument_type=FunctionType( names=['bool'], is_optional=True, ), default_value='false', ) ], [ FunctionArgument( name='prettyType', argument_type=FunctionType( names=['string'], is_optional=True, ), default_value='"none"', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function converts a single value (preferably a Lua table) into a JSON encoded string. You can use this to store the data and then load it again using fromJSON.' , arguments={ "var": """An argument of any type. Arguments that are elements will be stored as element IDs that are liable to change between sessions. As such, do not save elements across sessions as you will get unpredictable results. """, "compact": """a boolean representing whether the string will contain whitespaces. To remove whitespaces from JSON string, use true. String will contain whitespaces per default. """, "prettyType": """a type string from below: ** spaces ** tabs """ }, result='returns a json formatted string.' , ), url='toJSON', ) ], client=[ FunctionData( signature=FunctionSignature( name='toJSON', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='value', argument_type=FunctionType( names=['var'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='compact', argument_type=FunctionType( names=['bool'], is_optional=True, ), default_value='false', ) ], [ FunctionArgument( name='prettyType', argument_type=FunctionType( names=['string'], is_optional=True, ), default_value='"none"', ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='This function converts a single value (preferably a Lua table) into a JSON encoded string. You can use this to store the data and then load it again using fromJSON.' , arguments={ "var": """An argument of any type. Arguments that are elements will be stored as element IDs that are liable to change between sessions. As such, do not save elements across sessions as you will get unpredictable results. """, "compact": """a boolean representing whether the string will contain whitespaces. To remove whitespaces from JSON string, use true. String will contain whitespaces per default. """, "prettyType": """a type string from below: ** spaces ** tabs """ }, result='returns a json formatted string.' , ), url='toJSON', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='utfChar', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='characterCode', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns the string of the specified UTF code.' , arguments={ "characterCode": """The UTF code, to get the string of. """ }, result='returns a string if the function was successful, false otherwise.' , ), url='utfChar', ) ], client=[ FunctionData( signature=FunctionSignature( name='utfChar', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='characterCode', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns the string of the specified UTF code.' , arguments={ "characterCode": """The UTF code, to get the string of. """ }, result='returns a string if the function was successful, false otherwise.' , ), url='utfChar', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='utfCode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns the UTF codes of the given string.' , arguments={ "theString": """The string to get the UTF code of. """ }, result='returns an int if the function was successful, false otherwise.' , ), url='utfCode', ) ], client=[ FunctionData( signature=FunctionSignature( name='utfCode', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns the UTF codes of the given string.' , arguments={ "theString": """The string to get the UTF code of. """ }, result='returns an int if the function was successful, false otherwise.' , ), url='utfCode', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='utfLen', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function gets the real length of a string, in characters.' , arguments={ "theString": """The string to get the length of. """ }, result='returns an int if the function was successful, false otherwise.' , ), url='utfLen', ) ], client=[ FunctionData( signature=FunctionSignature( name='utfLen', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function gets the real length of a string, in characters.' , arguments={ "theString": """The string to get the length of. """ }, result='returns an int if the function was successful, false otherwise.' , ), url='utfLen', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='utfSeek', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='position', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns the byte position at specified character position.' , arguments={ "theString": """The string. """, "position": """An int with the specified charachter position. """ }, result='returns an int if the function was successful, false otherwise.' , ), url='utfSeek', ) ], client=[ FunctionData( signature=FunctionSignature( name='utfSeek', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['int'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='position', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns the byte position at specified character position.' , arguments={ "theString": """The string. """, "position": """An int with the specified charachter position. """ }, result='returns an int if the function was successful, false otherwise.' , ), url='utfSeek', ) ], ), CompoundFunctionData( server=[ FunctionData( signature=FunctionSignature( name='utfSub', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='Start', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='End', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns a sub string, from the specified positions on a character.' , arguments={ "theString": """The string. """, "Start": """An int with the start position. """, "End": """An int with the end position. """ }, result='returns a string if the function was successful, false otherwise.' , ), url='utfSub', ) ], client=[ FunctionData( signature=FunctionSignature( name='utfSub', return_types=FunctionReturnTypes( return_types=[ FunctionType( names=['string'], is_optional=False, ) ], variable_length=False, ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theString', argument_type=FunctionType( names=['string'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='Start', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='End', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), generic_types=[ ], ), docs=FunctionDoc( description='The function returns a sub string, from the specified positions on a character.' , arguments={ "theString": """The string. """, "Start": """An int with the start position. """, "End": """An int with the end position. """ }, result='returns a string if the function was successful, false otherwise.' , ), url='utfSub', ) ], ) ]

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1

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null

0

10

f82982b1e2f475912ca0263f1303c2459e5192a8

4,876

py

Python

pyaz/network/application_gateway/rewrite_rule/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/network/application_gateway/rewrite_rule/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/network/application_gateway/rewrite_rule/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

1

2022-02-03T09:12:01.000Z

from .... pyaz_utils import _call_az from . import condition, set def create(gateway_name, name, resource_group, rule_set_name, enable_reroute=None, modified_path=None, modified_query_string=None, no_wait=None, request_headers=None, response_headers=None, sequence=None): ''' Create a rewrite rule. Required Parameters: - gateway_name -- Name of the application gateway. - name -- Name of the rewrite rule. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - rule_set_name -- Name of the rewrite rule set. Optional Parameters: - enable_reroute -- If set as true, it will re-evaluate the url path map provided in path based request routing rules using modified path. - modified_path -- Url path for url rewrite - modified_query_string -- Query string for url rewrite. - no_wait -- Do not wait for the long-running operation to finish. - request_headers -- Space-separated list of HEADER=VALUE pairs. - response_headers -- Space-separated list of HEADER=VALUE pairs. - sequence -- Determines the execution order of the rule in the rule set. ''' return _call_az("az network application-gateway rewrite-rule create", locals()) def show(gateway_name, name, resource_group, rule_set_name): ''' Get the details of a rewrite rule. Required Parameters: - gateway_name -- Name of the application gateway. - name -- Name of the rewrite rule. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - rule_set_name -- Name of the rewrite rule set. ''' return _call_az("az network application-gateway rewrite-rule show", locals()) def list(gateway_name, resource_group, rule_set_name): ''' List rewrite rules. Required Parameters: - gateway_name -- Name of the application gateway. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - rule_set_name -- Name of the rewrite rule set. ''' return _call_az("az network application-gateway rewrite-rule list", locals()) def delete(gateway_name, name, resource_group, rule_set_name, no_wait=None): ''' Delete a rewrite rule. Required Parameters: - gateway_name -- Name of the application gateway. - name -- Name of the rewrite rule. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - rule_set_name -- Name of the rewrite rule set. Optional Parameters: - no_wait -- Do not wait for the long-running operation to finish. ''' return _call_az("az network application-gateway rewrite-rule delete", locals()) def update(gateway_name, name, resource_group, rule_set_name, add=None, enable_reroute=None, force_string=None, modified_path=None, modified_query_string=None, no_wait=None, remove=None, request_headers=None, response_headers=None, sequence=None, set=None): ''' Update a rewrite rule. Required Parameters: - gateway_name -- Name of the application gateway. - name -- Name of the rewrite rule. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - rule_set_name -- Name of the rewrite rule set. Optional Parameters: - add -- Add an object to a list of objects by specifying a path and key value pairs. Example: --add property.listProperty <key=value, string or JSON string> - enable_reroute -- If set as true, it will re-evaluate the url path map provided in path based request routing rules using modified path. - force_string -- When using 'set' or 'add', preserve string literals instead of attempting to convert to JSON. - modified_path -- Url path for url rewrite - modified_query_string -- Query string for url rewrite. - no_wait -- Do not wait for the long-running operation to finish. - remove -- Remove a property or an element from a list. Example: --remove property.list <indexToRemove> OR --remove propertyToRemove - request_headers -- Space-separated list of HEADER=VALUE pairs. - response_headers -- Space-separated list of HEADER=VALUE pairs. - sequence -- Determines the execution order of the rule in the rule set. - set -- Update an object by specifying a property path and value to set. Example: --set property1.property2=<value> ''' return _call_az("az network application-gateway rewrite-rule update", locals()) def list_request_headers(): return _call_az("az network application-gateway rewrite-rule list-request-headers", locals()) def list_response_headers(): return _call_az("az network application-gateway rewrite-rule list-response-headers", locals())

48.277228

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null

0

1

0

1

0

8

f871773bd1e1f967ed06309d12127860fa36cd84

159

py

Python

__init__.py

kloudtrader-github/libkloudtrader

abf5500e544e4f7b8834aacbd1dacf37ce11d023

[ "Apache-2.0" ]

null

__init__.py

kloudtrader-github/libkloudtrader

abf5500e544e4f7b8834aacbd1dacf37ce11d023

[ "Apache-2.0" ]

null

__init__.py

kloudtrader-github/libkloudtrader

abf5500e544e4f7b8834aacbd1dacf37ce11d023

[ "Apache-2.0" ]

null

from libkloudtrader.equities.data import * from libkloudtrader.equities.trade import * from libkloudtrader.user import * from libkloudtrader.alert_me import *

31.8

43

0.836478

19

159

6.947368

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0

0.100629

159

4

44

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1

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null

0

1

0

1

0

1

0

7

f8cca8d5cc4e8123cd4a6ecc0898b89123bea1be

106

py

Python

tests/utils/utils.py

LucaCappelletti94/compress_json

27d0c8e568327d10790ee0387fbc90bceed3c74f

[ "MIT" ]

7

2020-04-11T00:08:34.000Z

2021-06-09T17:36:31.000Z

tests/utils/utils.py

LucaCappelletti94/compress_json

27d0c8e568327d10790ee0387fbc90bceed3c74f

[ "MIT" ]

2

2021-03-19T08:29:19.000Z

2021-10-05T14:23:13.000Z

tests/utils/utils.py

LucaCappelletti94/compress_json

27d0c8e568327d10790ee0387fbc90bceed3c74f

[ "MIT" ]

null

from compress_json.compress_json import local_path def local_call(): return local_path("object.json")

26.5

50

0.801887

16

106

5

0.625

0.3

0

0.113208

106

4

51

26.5

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1

0

1

0

null

0

1

0

1

0

8

3e1fd8eb8e4bda56f97bc143e65d0ccca0883479

34

py

Python

dont-nsesso/nsesso/utils/__init__.py

rishikesh67/django-tenant-oracle-schemas

918a64e842b678fc506eadbb4d7e51b0b38ab0a2

[ "MIT" ]

null

dont-nsesso/nsesso/utils/__init__.py

rishikesh67/django-tenant-oracle-schemas

918a64e842b678fc506eadbb4d7e51b0b38ab0a2

[ "MIT" ]

8

2019-12-04T23:26:11.000Z

2022-02-10T09:42:18.000Z

dont-nsesso/nsesso/utils/__init__.py

rishikesh67/django-tenant-oracle-schemas

918a64e842b678fc506eadbb4d7e51b0b38ab0a2

[ "MIT" ]

2

2019-06-26T05:31:16.000Z

2019-07-01T12:22:50.000Z

from .get_tenant import get_tenant

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3e2acb11d1ace7c3de1d9c17024a8d47bac39cff

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py

Python

src/interpolation_robustness/models/__init__.py

michaelaerni/interpolation_robustness

be18c37a55b6ae1669391fe21e4aba3584fc9882

[ "MIT" ]

1

2022-02-16T19:24:36.000Z

src/interpolation_robustness/models/__init__.py

michaelaerni/interpolation_robustness

be18c37a55b6ae1669391fe21e4aba3584fc9882

[ "MIT" ]

null

src/interpolation_robustness/models/__init__.py

michaelaerni/interpolation_robustness

be18c37a55b6ae1669391fe21e4aba3584fc9882

[ "MIT" ]

null

from . import jax from . import pytorch

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7

e41c06d5502e52811712c020329f2e079db9062e

13,830

py

Python

container_sdk/api/service/service_client.py

easyopsapis/easyops-api-python

adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0

[ "Apache-2.0" ]

5

2019-07-31T04:11:05.000Z

2021-01-07T03:23:20.000Z

container_sdk/api/service/service_client.py

easyopsapis/easyops-api-python

adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0

[ "Apache-2.0" ]

null

container_sdk/api/service/service_client.py

easyopsapis/easyops-api-python

adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import os import sys import container_sdk.api.service.create_pb2 import container_sdk.model.container.service_pb2 import container_sdk.api.service.create_from_yaml_pb2 import container_sdk.api.service.delete_service_pb2 import google.protobuf.empty_pb2 import container_sdk.api.service.get_pb2 import container_sdk.api.service.get_status_pb2 import container_sdk.api.service.list_pb2 import container_sdk.api.service.update_pb2 import container_sdk.api.service.update_resource_spec_pb2 import container_sdk.utils.http_util import google.protobuf.json_format class ServiceClient(object): def __init__(self, server_ip="", server_port=0, service_name="", host=""): """ 初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，server_ip优先级更高 :param host: 指定sdk请求服务的host名称, 如cmdb.easyops-only.com """ if server_ip == "" and server_port != 0 or server_ip != "" and server_port == 0: raise Exception("server_ip和server_port必须同时指定") self._server_ip = server_ip self._server_port = server_port self._service_name = service_name self._host = host def create(self, request, org, user, timeout=10): # type: (container_sdk.api.service.create_pb2.CreateRequest, int, str, int) -> container_sdk.model.container.service_pb2.Service """ 创建 service 负载均衡 :param request: create请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: container_sdk.model.container.service_pb2.Service """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.Create" uri = "/api/container/v1/services" requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="POST", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = container_sdk.model.container.service_pb2.Service() google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True) return rsp def create_from_yaml(self, request, org, user, timeout=10): # type: (container_sdk.api.service.create_from_yaml_pb2.CreateFromYamlRequest, int, str, int) -> container_sdk.model.container.service_pb2.Service """ 通过 yaml 创建 service :param request: create_from_yaml请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: container_sdk.model.container.service_pb2.Service """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.CreateFromYaml" uri = "/api/container/v1/services/yaml" requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="POST", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = container_sdk.model.container.service_pb2.Service() google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True) return rsp def delete_service(self, request, org, user, timeout=10): # type: (container_sdk.api.service.delete_service_pb2.DeleteServiceRequest, int, str, int) -> google.protobuf.empty_pb2.Empty """ 删除 Service :param request: delete_service请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: google.protobuf.empty_pb2.Empty """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.DeleteService" uri = "/api/container/v1/services/{instanceId}".format( instanceId=request.instanceId, ) requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="DELETE", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = google.protobuf.empty_pb2.Empty() google.protobuf.json_format.ParseDict(rsp_obj, rsp, ignore_unknown_fields=True) return rsp def get(self, request, org, user, timeout=10): # type: (container_sdk.api.service.get_pb2.GetRequest, int, str, int) -> container_sdk.api.service.get_pb2.GetResponse """ 获取 Service 配置 :param request: get请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: container_sdk.api.service.get_pb2.GetResponse """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.Get" uri = "/api/container/v1/services/{instanceId}".format( instanceId=request.instanceId, ) requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="GET", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = container_sdk.api.service.get_pb2.GetResponse() google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True) return rsp def get_status(self, request, org, user, timeout=10): # type: (container_sdk.api.service.get_status_pb2.GetStatusRequest, int, str, int) -> container_sdk.model.container.service_pb2.Service """ 获取 Service, 信息来源于现网 :param request: get_status请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: container_sdk.model.container.service_pb2.Service """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.GetStatus" uri = "/api/container/v1/services/{instanceId}/status".format( instanceId=request.instanceId, ) requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="GET", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = container_sdk.model.container.service_pb2.Service() google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True) return rsp def list(self, request, org, user, timeout=10): # type: (container_sdk.api.service.list_pb2.ListRequest, int, str, int) -> container_sdk.api.service.list_pb2.ListResponse """ 获取 Service 列表 :param request: list请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: container_sdk.api.service.list_pb2.ListResponse """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.List" uri = "/api/container/v1/services" requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="GET", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = container_sdk.api.service.list_pb2.ListResponse() google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True) return rsp def update(self, request, org, user, timeout=10): # type: (container_sdk.api.service.update_pb2.UpdateRequest, int, str, int) -> container_sdk.model.container.service_pb2.Service """ 更新 Service :param request: update请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: container_sdk.model.container.service_pb2.Service """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.Update" uri = "/api/container/v1/services/{instanceId}".format( instanceId=request.instanceId, ) requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="PUT", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = container_sdk.model.container.service_pb2.Service() google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True) return rsp def update_resource_spec(self, request, org, user, timeout=10): # type: (container_sdk.api.service.update_resource_spec_pb2.UpdateResourceSpecRequest, int, str, int) -> container_sdk.model.container.service_pb2.Service """ 更新 Service yaml 文件定义 :param request: update_resource_spec请求 :param org: 客户的org编号，为数字 :param user: 调用api使用的用户名 :param timeout: 调用超时时间，单位秒 :return: container_sdk.model.container.service_pb2.Service """ headers = {"org": org, "user": user} route_name = "" server_ip = self._server_ip if self._service_name != "": route_name = self._service_name elif self._server_ip != "": route_name = "easyops.api.container.service.UpdateResourceSpec" uri = "/api/container/v1/services/{instanceId}/yaml".format( instanceId=request.instanceId, ) requestParam = request rsp_obj = container_sdk.utils.http_util.do_api_request( method="PUT", src_name="logic.container_sdk", dst_name=route_name, server_ip=server_ip, server_port=self._server_port, host=self._host, uri=uri, params=google.protobuf.json_format.MessageToDict( requestParam, preserving_proto_field_name=True), headers=headers, timeout=timeout, ) rsp = container_sdk.model.container.service_pb2.Service() google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True) return rsp

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13,830

5.288147

0.091683

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0.040867

0.059938

0.866625

0.850402

0.819814

0.770898

0.757523

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0

0.007108

0.287925

13,830

371

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37.277628

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false

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0

null

0

1

0

1

0

null

0

7

e41e86008401ac8e73c0b1d318f608eaaae649d0

126

py

Python

tests/test_pyeasytries.py

rainbowxyt0305/pyeasytries

ac21c37d453319214417414facd5325d0538fc30

[ "MIT" ]

null

tests/test_pyeasytries.py

rainbowxyt0305/pyeasytries

ac21c37d453319214417414facd5325d0538fc30

[ "MIT" ]

null

tests/test_pyeasytries.py

rainbowxyt0305/pyeasytries

ac21c37d453319214417414facd5325d0538fc30

[ "MIT" ]

null

from pyeasytries import __version__ from pyeasytries import pyeasytries def test_version(): assert __version__ == '0.1.0'

25.2

35

0.785714

16

126

5.625

0.5625

0.333333

0.466667

0

0.027778

0.142857

126

5

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25.2

0.805556

0

0.03937

0

0.25

1

0.25

true

0

0.5

0

0.75

0

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null

1

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null

0

1

0

1

0

7

e4e1f3a4a4dfec4d2e1fedb3d08f35ef1ce38ff7

49,868

py

Python

PythonFights/Game Creator/pythonfights_game_creator.py

adnmaster2008/python-code-fights

9540873c20526728fcdad5efa943617d43f7c36f

[ "MIT" ]

null

PythonFights/Game Creator/pythonfights_game_creator.py

adnmaster2008/python-code-fights

9540873c20526728fcdad5efa943617d43f7c36f

[ "MIT" ]

null

PythonFights/Game Creator/pythonfights_game_creator.py

adnmaster2008/python-code-fights

9540873c20526728fcdad5efa943617d43f7c36f

[ "MIT" ]

null

import os import multiprocessing import time # Get Game Properties____________________________________ system_game_properties_file = open("game.properties", "r") exec(system_game_properties_file.read()) system_game_properties_file.close() system_frame_limit = system_frame_limit system_pythonfights_space_x = system_pythonfights_space_x system_pythonfights_space_y = system_pythonfights_space_y system_player1_position = system_player1_position system_player2_position = system_player2_position system_player_build_delay = system_player_build_delay system_player_bullet_delay = system_player_bullet_delay # Get Game Properties____________________________________ # Create GameSpace___________________________________ system_pythonfights_space = [] system_pythonfights_space_x_backup = system_pythonfights_space_x system_pythonfights_space_y_backup = system_pythonfights_space_y while True: if(system_pythonfights_space_y_backup == 0): break else: system_pythonfights_space.append([]) system_pythonfights_space_y_backup -= 1 del system_pythonfights_space_y_backup for x in range(0, len(system_pythonfights_space)): while True: if(system_pythonfights_space_x_backup == 0): break else: system_pythonfights_space[x].append(" ") system_pythonfights_space_x_backup -= 1 system_pythonfights_space_x_backup = system_pythonfights_space_x del system_pythonfights_space_x_backup # Create GameSpace____________________________________ print("Creating game...") system_frame = 0 # Create Game____________________________________________________________________ if(system_player1_is_alive): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = "#" if(system_player2_is_alive): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = "#" if(system_player3_is_alive): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = "#" if(system_player4_is_alive): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = "#" system_player1_bullet_delay = system_player_bullet_delay system_player2_bullet_delay = system_player_bullet_delay system_player3_bullet_delay = system_player_bullet_delay system_player4_bullet_delay = system_player_bullet_delay system_player1_build_delay = system_player_build_delay system_player2_build_delay = system_player_build_delay system_player3_build_delay = system_player_build_delay system_player4_build_delay = system_player_build_delay system_bullet_data = [] system_player1_data = [] system_player2_data = [] system_player3_data = [] system_player4_data = [] while True: system_player1_output = "" system_player2_output = "" system_player3_output = "" system_player4_output = "" system_player1_action = "" system_player2_action = "" system_player3_action = "" system_player4_action = "" # Player 1 Turn if(not system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] == "#"): system_player1_is_alive = False if(system_player1_is_alive): system_player1_turn_file = open("player1_code.py") exec(system_player1_turn_file.read()) system_player1_turn_file.close() system_tmp_data_list = [system_pythonfights_space.copy(), system_player1_position[0], system_player1_position[1], system_player1_build_delay, system_player1_bullet_delay] system_tmp_data = player1_code(system_player1_data, system_tmp_data_list) system_player1_output = system_tmp_data[0] system_player1_data = system_tmp_data[1] del system_tmp_data_list del system_tmp_data del player1_code # Player 1 Turn # Player 2 Turn if(not system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] == "#"): system_player2_is_alive = False if(system_player2_is_alive): system_player2_turn_file = open("player2_code.py") exec(system_player2_turn_file.read()) system_player2_turn_file.close() system_tmp_data_list = [system_pythonfights_space.copy(), system_player2_position[0], system_player2_position[1], system_player2_build_delay, system_player2_bullet_delay] system_tmp_data = player2_code(system_player2_data, system_tmp_data_list) system_player2_output = system_tmp_data[0] system_player2_data = system_tmp_data[1] del system_tmp_data_list del system_tmp_data del player2_code # Player 2 Turn # Player 3 Turn if(not system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] == "#"): system_player3_is_alive = False if(system_player3_is_alive): system_player3_turn_file = open("player3_code.py") exec(system_player3_turn_file.read()) system_player3_turn_file.close() system_tmp_data_list = [system_pythonfights_space.copy(), system_player3_position[0], system_player3_position[1], system_player3_build_delay, system_player3_bullet_delay] system_tmp_data = player3_code(system_player3_data, system_tmp_data_list) system_player3_output = system_tmp_data[0] system_player3_data = system_tmp_data[1] del system_tmp_data_list del system_tmp_data del player3_code # Player 3 Turn # Player 4 Turn if(not system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] == "#"): system_player4_is_alive = False if(system_player4_is_alive): system_player4_turn_file = open("player4_code.py") exec(system_player4_turn_file.read()) system_player4_turn_file.close() system_tmp_data_list = [system_pythonfights_space.copy(), system_player4_position[0], system_player4_position[1], system_player4_build_delay, system_player4_bullet_delay] system_tmp_data = player4_code(system_player4_data, system_tmp_data_list) system_player4_output = system_tmp_data[0] system_player4_data = system_tmp_data[1] del system_tmp_data_list del system_tmp_data del player4_code # Player 4 Turn # Process Current Frame if("m" in system_player1_output and system_player1_is_alive): system_player1_output = system_player1_output.replace("m", "") try: if(system_player1_output == ">"): if(system_pythonfights_space[system_player1_position[1]][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]][system_player1_position[0]+1] = "#" system_player1_position[0] += 1 if(system_player1_output == "<"): if(system_pythonfights_space[system_player1_position[1]][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]][system_player1_position[0]-1] = "#" system_player1_position[0] -= 1 if(system_player1_output == "+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]] = "#" system_player1_position[1] -= 1 if(system_player1_output == "-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]] = "#" system_player1_position[1] += 1 if(system_player1_output == ">+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]+1] = "#" system_player1_position[0] += 1 system_player1_position[1] -= 1 if(system_player1_output == ">-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]+1] = "#" system_player1_position[0] += 1 system_player1_position[1] += 1 if(system_player1_output == "<+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]-1] = "#" system_player1_position[0] -= 1 system_player1_position[1] -= 1 if(system_player1_output == "<-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]] = " " system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]-1] = "#" system_player1_position[0] -= 1 system_player1_position[1] += 1 except: pass if("m" in system_player2_output and system_player2_is_alive): system_player2_output = system_player2_output.replace("m", "") try: if(system_player2_output == ">"): if(system_pythonfights_space[system_player2_position[1]][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]][system_player2_position[0]+1] = "#" system_player2_position[0] += 1 if(system_player2_output == "<"): if(system_pythonfights_space[system_player2_position[1]][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]][system_player2_position[0]-1] = "#" system_player2_position[0] -= 1 if(system_player2_output == "+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]] = "#" system_player2_position[1] -= 1 if(system_player2_output == "-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]] = "#" system_player2_position[1] += 1 if(system_player2_output == ">+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]+1] = "#" system_player2_position[0] += 1 system_player2_position[1] -= 1 if(system_player2_output == ">-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]+1] = "#" system_player2_position[0] += 1 system_player2_position[1] += 1 if(system_player2_output == "<+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]-1] = "#" system_player2_position[0] -= 1 system_player2_position[1] -= 1 if(system_player2_output == "<-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]] = " " system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]-1] = "#" system_player2_position[0] -= 1 system_player2_position[1] += 1 except: pass if("m" in system_player3_output and system_player3_is_alive): system_player3_output = system_player3_output.replace("m", "") try: if(system_player3_output == ">"): if(system_pythonfights_space[system_player3_position[1]][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]][system_player3_position[0]+1] = "#" system_player3_position[0] += 1 if(system_player3_output == "<"): if(system_pythonfights_space[system_player3_position[1]][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]][system_player3_position[0]-1] = "#" system_player3_position[0] -= 1 if(system_player3_output == "+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]] = "#" system_player3_position[1] -= 1 if(system_player3_output == "-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]] = "#" system_player3_position[1] += 1 if(system_player3_output == ">+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]+1] = "#" system_player3_position[0] += 1 system_player3_position[1] -= 1 if(system_player3_output == ">-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]+1] = "#" system_player3_position[0] += 1 system_player3_position[1] += 1 if(system_player3_output == "<+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]-1] = "#" system_player3_position[0] -= 1 system_player3_position[1] -= 1 if(system_player3_output == "<-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]] = " " system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]-1] = "#" system_player3_position[0] -= 1 system_player3_position[1] += 1 except: pass if("m" in system_player4_output and system_player4_is_alive): system_player4_output = system_player4_output.replace("m", "") try: if(system_player4_output == ">"): if(system_pythonfights_space[system_player4_position[1]][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]][system_player4_position[0]+1] = "#" system_player4_position[0] += 1 if(system_player4_output == "<"): if(system_pythonfights_space[system_player4_position[1]][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]][system_player4_position[0]-1] = "#" system_player4_position[0] -= 1 if(system_player4_output == "+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]] = "#" system_player4_position[1] -= 1 if(system_player4_output == "-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]] = "#" system_player3_position[1] += 1 if(system_player4_output == ">+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]+1] = "#" system_player4_position[0] += 1 system_player4_position[1] -= 1 if(system_player4_output == ">-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]+1] = "#" system_player4_position[0] += 1 system_player4_position[1] += 1 if(system_player4_output == "<+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]-1] = "#" system_player4_position[0] -= 1 system_player4_position[1] -= 1 if(system_player4_output == "<-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]] = " " system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]-1] = "#" system_player4_position[0] -= 1 system_player4_position[1] += 1 except: pass if("b" in system_player1_output and system_player1_is_alive): system_player1_output = system_player1_output.replace("b", "") try: if(system_player1_build_delay == 0): system_player1_build_delay = system_player_build_delay if(system_player1_output == ">"): if(system_pythonfights_space[system_player1_position[1]][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]+1] = "*" if(system_player1_output == "<"): if(system_pythonfights_space[system_player1_position[1]][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]-1] = "*" if(system_player1_output == "+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]] == " "): system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]] = "*" if(system_player1_output == "-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]] == " "): system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]] = "*" if(system_player1_output == ">+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]+1] = "*" if(system_player1_output == ">-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]+1] = "*" if(system_player1_output == "<+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]-1] = "*" if(system_player1_output == "<-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]-1] = "*" except: pass if("b" in system_player2_output and system_player2_is_alive): system_player2_output = system_player2_output.replace("b", "") try: if(system_player2_build_delay == 0): system_player2_build_delay = system_player_build_delay if(system_player2_output == ">"): if(system_pythonfights_space[system_player2_position[1]][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]+1] = "*" if(system_player2_output == "<"): if(system_pythonfights_space[system_player2_position[1]][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]-1] = "*" if(system_player2_output == "+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]] == " "): system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]] = "*" if(system_player2_output == "-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]] == " "): system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]] = "*" if(system_player2_output == ">+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]+1] = "*" if(system_player2_output == ">-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]+1] = "*" if(system_player2_output == "<+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]-1] = "*" if(system_player2_output == "<-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]-1] = "*" except: pass if("b" in system_player3_output and system_player3_is_alive): system_player3_output = system_player3_output.replace("b", "") try: if(system_player3_build_delay == 0): system_player3_build_delay = system_player_build_delay if(system_player3_output == ">"): if(system_pythonfights_space[system_player3_position[1]][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]+1] = "*" if(system_player3_output == "<"): if(system_pythonfights_space[system_player3_position[1]][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]-1] = "*" if(system_player3_output == "+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]] == " "): system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]] = "*" if(system_player3_output == "-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]] == " "): system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]] = "*" if(system_player3_output == ">+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]+1] = "*" if(system_player3_output == ">-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]+1] = "*" if(system_player3_output == "<+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]-1] = "*" if(system_player3_output == "<-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]-1] = "*" except: pass if("b" in system_player4_output and system_player4_is_alive): system_player4_output = system_player4_output.replace("b", "") try: if(system_player4_build_delay == 0): system_player4_build_delay = system_player_build_delay if(system_player4_output == ">"): if(system_pythonfights_space[system_player4_position[1]][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]+1] = "*" if(system_player4_output == "<"): if(system_pythonfights_space[system_player4_position[1]][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]-1] = "*" if(system_player4_output == "+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]] == " "): system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]] = "*" if(system_player4_output == "-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]] == " "): system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]] = "*" if(system_player4_output == ">+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]+1] = "*" if(system_player4_output == ">-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]+1] = "*" if(system_player4_output == "<+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]-1] = "*" if(system_player4_output == "<-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]-1] = "*" except: pass system_gonna_be_popped = [] if(len(system_bullet_data) > 0): for x in range(0, len(system_bullet_data)): if(not system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] == "*"): system_gonna_be_popped.append(x) else: if(system_bullet_data[x][2] == ">"): try: if(system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]+1] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]+1] = "*" system_bullet_data[x][0] += 1 elif(system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]+1] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]+1] = " " elif(system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]+1] == "#"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]+1] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " if(system_bullet_data[x][2] == "<"): try: if(system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]-1] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]-1] = "*" system_bullet_data[x][0] -= 1 elif(system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]-1] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]-1] = " " elif(system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]-1] == "#"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]-1] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " if(system_bullet_data[x][2] == "+"): try: if(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]] = "*" system_bullet_data[x][1] -= 1 elif(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]] = " " elif(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]] == "#"): system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " if(system_bullet_data[x][2] == "-"): try: if(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]] = "*" system_bullet_data[x][1] += 1 elif(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]] = " " elif(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]] == "#"): system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " if(system_bullet_data[x][2] == ">+"): try: if(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]+1] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]+1] = "*" system_bullet_data[x][0] += 1 system_bullet_data[x][1] -= 1 elif(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]+1] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]+1] = " " elif(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]+1] == "#"): system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]+1] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " if(system_bullet_data[x][2] == ">-"): try: if(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]+1] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]+1] = "*" system_bullet_data[x][0] += 1 system_bullet_data[x][1] += 1 elif(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]+1] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]+1] = " " elif(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]+1] == "#"): system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]+1] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " if(system_bullet_data[x][2] == "<+"): try: if(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]-1] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]-1] = "*" system_bullet_data[x][0] -= 1 system_bullet_data[x][1] -= 1 elif(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]-1] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]-1] = " " elif(system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]-1] == "#"): system_pythonfights_space[system_bullet_data[x][1]-1][system_bullet_data[x][0]-1] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " if(system_bullet_data[x][2] == "<-"): try: if(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]-1] == " "): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]-1] = "*" system_bullet_data[x][0] -= 1 system_bullet_data[x][1] += 1 elif(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]-1] == "*"): system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]-1] = " " elif(system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]-1] == "#"): system_pythonfights_space[system_bullet_data[x][1]+1][system_bullet_data[x][0]-1] = " " except: system_pythonfights_space[system_bullet_data[x][1]][system_bullet_data[x][0]] = " " for x in range(0, len(system_gonna_be_popped)): system_bullet_data.pop(system_gonna_be_popped[x]) del system_gonna_be_popped if("s" in system_player1_output and system_player1_is_alive): system_player1_output = system_player1_output.replace("s", "") try: if(system_player1_bullet_delay == 0): system_player1_bullet_delay = system_player_bullet_delay if(system_player1_output == ">"): if(system_pythonfights_space[system_player1_position[1]][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]+1] = "*" system_bullet_data.append([system_player1_position[0]+1, system_player1_position[1], system_player1_output]) if(system_player1_output == "<"): if(system_pythonfights_space[system_player1_position[1]][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]][system_player1_position[0]-1] = "*" system_bullet_data.append([system_player1_position[0]-1, system_player1_position[1], system_player1_output]) if(system_player1_output == "+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]] == " "): system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]] = "*" system_bullet_data.append([system_player1_position[0], system_player1_position[1]-1, system_player1_output]) if(system_player1_output == "-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]] == " "): system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]] = "*" system_bullet_data.append([system_player1_position[0], system_player1_position[1]+1, system_player1_output]) if(system_player1_output == ">+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]+1] = "*" system_bullet_data.append([system_player1_position[0]+1, system_player1_position[1]-1, system_player1_output]) if(system_player1_output == ">-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]+1] == " "): system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]+1] = "*" system_bullet_data.append([system_player1_position[0]+1, system_player1_position[1]+1, system_player1_output]) if(system_player1_output == "<+"): if(system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]-1][system_player1_position[0]-1] = "*" system_bullet_data.append([system_player1_position[0]-1, system_player1_position[1]-1, system_player1_output]) if(system_player1_output == "<-"): if(system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]-1] == " "): system_pythonfights_space[system_player1_position[1]+1][system_player1_position[0]-1] = "*" system_bullet_data.append([system_player1_position[0]-1, system_player1_position[1]+1, system_player1_output]) except: pass if("s" in system_player2_output and system_player2_is_alive): system_player2_output = system_player2_output.replace("s", "") try: if(system_player2_bullet_delay == 0): system_player2_bullet_delay = system_player_bullet_delay if(system_player2_output == ">"): if(system_pythonfights_space[system_player2_position[1]][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]+1] = "*" system_bullet_data.append([system_player2_position[0]+1, system_player2_position[1], system_player2_output]) if(system_player2_output == "<"): if(system_pythonfights_space[system_player2_position[1]][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]][system_player2_position[0]-1] = "*" system_bullet_data.append([system_player2_position[0]-1, system_player2_position[1], system_player2_output]) if(system_player2_output == "+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]] == " "): system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]] = "*" system_bullet_data.append([system_player2_position[0], system_player2_position[1]-1, system_player2_output]) if(system_player2_output == "-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]] == " "): system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]] = "*" system_bullet_data.append([system_player2_position[0], system_player2_position[1]+1, system_player2_output]) if(system_player2_output == ">+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]+1] = "*" system_bullet_data.append([system_player2_position[0]+1, system_player2_position[1]-1, system_player2_output]) if(system_player2_output == ">-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]+1] == " "): system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]+1] = "*" system_bullet_data.append([system_player2_position[0]+1, system_player2_position[1]+1, system_player2_output]) if(system_player2_output == "<+"): if(system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]-1][system_player2_position[0]-1] = "*" system_bullet_data.append([system_player2_position[0]-1, system_player2_position[1]-1, system_player2_output]) if(system_player2_output == "<-"): if(system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]-1] == " "): system_pythonfights_space[system_player2_position[1]+1][system_player2_position[0]-1] = "*" system_bullet_data.append([system_player2_position[0]-1, system_player2_position[1]+1, system_player2_output]) except: pass if("s" in system_player3_output and system_player3_is_alive): system_player3_output = system_player3_output.replace("s", "") try: if(system_player3_bullet_delay == 0): system_player3_bullet_delay = system_player_bullet_delay if(system_player3_output == ">"): if(system_pythonfights_space[system_player3_position[1]][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]+1] = "*" system_bullet_data.append([system_player3_position[0]+1, system_player3_position[1], system_player3_output]) if(system_player3_output == "<"): if(system_pythonfights_space[system_player3_position[1]][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]][system_player3_position[0]-1] = "*" system_bullet_data.append([system_player3_position[0]-1, system_player3_position[1], system_player3_output]) if(system_player3_output == "+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]] == " "): system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]] = "*" system_bullet_data.append([system_player3_position[0], system_player3_position[1]-1, system_player3_output]) if(system_player3_output == "-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]] == " "): system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]] = "*" system_bullet_data.append([system_player3_position[0], system_player3_position[1]+1, system_player3_output]) if(system_player3_output == ">+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]+1] = "*" system_bullet_data.append([system_player3_position[0]+1, system_player3_position[1]-1, system_player3_output]) if(system_player3_output == ">-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]+1] == " "): system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]+1] = "*" system_bullet_data.append([system_player3_position[0]+1, system_player3_position[1]+1, system_player3_output]) if(system_player3_output == "<+"): if(system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]-1][system_player3_position[0]-1] = "*" system_bullet_data.append([system_player3_position[0]-1, system_player3_position[1]-1, system_player3_output]) if(system_player3_output == "<-"): if(system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]-1] == " "): system_pythonfights_space[system_player3_position[1]+1][system_player3_position[0]-1] = "*" system_bullet_data.append([system_player3_position[0]-1, system_player3_position[1]+1, system_player3_output]) except: pass if("s" in system_player4_output and system_player4_is_alive): system_player4_output = system_player4_output.replace("s", "") try: if(system_player4_bullet_delay == 0): system_player4_bullet_delay = system_player_bullet_delay if(system_player4_output == ">"): if(system_pythonfights_space[system_player4_position[1]][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]+1] = "*" system_bullet_data.append([system_player4_position[0]+1, system_player4_position[1], system_player4_output]) if(system_player4_output == "<"): if(system_pythonfights_space[system_player4_position[1]][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]][system_player4_position[0]-1] = "*" system_bullet_data.append([system_player4_position[0]-1, system_player4_position[1], system_player4_output]) if(system_player4_output == "+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]] == " "): system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]] = "*" system_bullet_data.append([system_player4_position[0], system_player4_position[1]-1, system_player4_output]) if(system_player4_output == "-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]] == " "): system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]] = "*" system_bullet_data.append([system_player4_position[0], system_player4_position[1]+1, system_player4_output]) if(system_player4_output == ">+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]+1] = "*" system_bullet_data.append([system_player4_position[0]+1, system_player4_position[1]-1, system_player4_output]) if(system_player4_output == ">-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]+1] == " "): system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]+1] = "*" system_bullet_data.append([system_player4_position[0]+1, system_player4_position[1]+1, system_player4_output]) if(system_player4_output == "<+"): if(system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]-1][system_player4_position[0]-1] = "*" system_bullet_data.append([system_player4_position[0]-1, system_player4_position[1]-1, system_player4_output]) if(system_player4_output == "<-"): if(system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]-1] == " "): system_pythonfights_space[system_player4_position[1]+1][system_player4_position[0]-1] = "*" system_bullet_data.append([system_player4_position[0]-1, system_player4_position[1]+1, system_player4_output]) except: pass # Process Current Frame # Reduce Delay if(system_player1_bullet_delay != 0): system_player1_bullet_delay -= 1 if(system_player2_bullet_delay != 0): system_player2_bullet_delay -= 1 if(system_player3_bullet_delay != 0): system_player3_bullet_delay -= 1 if(system_player4_bullet_delay != 0): system_player4_bullet_delay -= 1 if(system_player1_build_delay != 0): system_player1_build_delay -= 1 if(system_player2_build_delay != 0): system_player2_build_delay -= 1 if(system_player3_build_delay != 0): system_player3_build_delay -= 1 if(system_player4_build_delay != 0): system_player4_build_delay -= 1 # Reduce Delay # Output Current Frame system_tmp_str = "" for x in range(0, len(system_pythonfights_space)): for xx in range(0, len(system_pythonfights_space[x])): system_tmp_str += system_pythonfights_space[x][xx] system_tmp_str += "\n" system_tmp_str += "-" system_game_write_file = open("game.pyf", "a") system_game_write_file.write(system_tmp_str+"\n") system_game_write_file.close() del system_tmp_str # Output Current Frame if(system_frame == system_frame_limit): break system_frame += 1 # Create Game_____________________________________________________________________ print("Game created successfully") while True: pass

63.688378

173

0.737427

6,591

49,868

5.067971

0.0132

0.111068

0.228602

0.265665

0.954256

0.940993

0.916265

0.906685

0.885429

0.87561

0

0.048996

0.123326

49,868

782

174

63.769821

0.71506

0.012052

0

0.65722

0

0.012731

0

1

0

false

0.017544

0.004049

0

0.004049

0.002699

0

null

0

1

0

null

0

8

e4e5f25902ffe341bcf77bf4c9374d1b2a591a1a

631

py

Python

24/00/real_quick_ratio.py

pylangstudy/201708

126b1af96a1d1f57522d5a1d435b58597bea2e57

[ "CC0-1.0" ]

null

24/00/real_quick_ratio.py

pylangstudy/201708

126b1af96a1d1f57522d5a1d435b58597bea2e57

[ "CC0-1.0" ]

39

2017-07-31T22:54:01.000Z

2017-08-31T00:19:03.000Z

24/00/real_quick_ratio.py

pylangstudy/201708

126b1af96a1d1f57522d5a1d435b58597bea2e57

[ "CC0-1.0" ]

null

#!python3.6 import difflib sm = difflib.SequenceMatcher(); print(sm); sm = difflib.SequenceMatcher(a='abc', b='abc') print('ratio:', sm.ratio()); print('quick_ratio:', sm.quick_ratio()); print('real_quick_ratio:', sm.real_quick_ratio()); sm = difflib.SequenceMatcher(a='abc', b='a b c') print('ratio:', sm.ratio()); print('quick_ratio:', sm.quick_ratio()); print('real_quick_ratio:', sm.real_quick_ratio()); sm = difflib.SequenceMatcher(isjunk=lambda x: x in " \t", a='abc', b='a b c'); print(sm, sm.ratio()); print('ratio:', sm.ratio()); print('quick_ratio:', sm.quick_ratio()); print('real_quick_ratio:', sm.real_quick_ratio());

39.4375

101

0.687797

98

631

4.244898

0.193878

0.288462

0.230769

0.192308

0.805288

0.735577

0.685096

0

0.003436

0.077655

631

15

102

42.066667

0.71134

0.015848

0

0.785714

0

0.209677

0

1

0

false

0

0.071429

0

0.071429

0.785714

0

null

1

0

1

0

1

0

null

0

1

0

9

e4e9bedd5877d94b4f6b7ac3529d84bb774d7e63

13,406

py

Python

tests/test_user.py

bachya/pyflunearyou

12fe7ef6082c2010fe427dae6281ecd9a758d77f

[ "MIT" ]

null

tests/test_user.py

bachya/pyflunearyou

12fe7ef6082c2010fe427dae6281ecd9a758d77f

[ "MIT" ]

54

2018-11-01T21:30:06.000Z

2022-03-01T18:40:47.000Z

tests/test_user.py

bachya/pyflunearyou

12fe7ef6082c2010fe427dae6281ecd9a758d77f

[ "MIT" ]

null

"""Define tests for the user report endpoints.""" from aiocache import SimpleMemoryCache import aiohttp import pytest from pyflunearyou import Client from pyflunearyou.helpers.report import CACHE_KEY_LOCAL_DATA, CACHE_KEY_STATE_DATA from .common import ( TEST_LATITUDE, TEST_LATITUDE_UNCONTAINED, TEST_LONGITUDE, TEST_LONGITUDE_UNCONTAINED, TEST_ZIP, load_fixture, ) @pytest.mark.asyncio async def test_no_explicit_client_session(aresponses): """Test not providing an explicit aiohttp ClientSession.""" cache = SimpleMemoryCache() await cache.delete(CACHE_KEY_LOCAL_DATA) await cache.delete(CACHE_KEY_STATE_DATA) aresponses.add( "api.v2.flunearyou.org", "/map/markers", "get", aresponses.Response( text=load_fixture("user_report_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) aresponses.add( "api.v2.flunearyou.org", "/states", "get", aresponses.Response( text=load_fixture("states_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) client = Client() info = await client.user_reports.status_by_coordinates( TEST_LATITUDE, TEST_LONGITUDE ) assert info == { "local": { "id": 2, "city": "Los Angeles(90046)", "place_id": "23818", "zip": "90046", "contained_by": "204", "latitude": "34.114731", "longitude": "-118.363724", "none": 2, "symptoms": 0, "flu": 0, "lepto": 0, "dengue": 0, "chick": 0, "icon": "1", }, "state": { "name": "California", "place_id": "204", "lat": "37.250198", "lon": "-119.750298", "data": { "symptoms_percentage": 12.32, "none_percentage": 87.68, "ili_percentage": 2.69, "lepto_percentage": 0, "dengue_percentage": 2.17, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2119, "symptoms": 261, "no_symptoms": 1858, "ili": 57, "lepto": 0, "dengue": 46, "chick": 0, }, "last_week_data": { "symptoms_percentage": 14.29, "none_percentage": 85.71, "ili_percentage": 2.91, "lepto_percentage": 0.05, "dengue_percentage": 2.21, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2128, "symptoms": 304, "no_symptoms": 1824, "ili": 62, "lepto": 1, "dengue": 47, "chick": 0, }, }, } @pytest.mark.asyncio async def test_status_by_coordinates_success_id(aresponses): """Test getting user reports by latitude/longitude (contained ID).""" cache = SimpleMemoryCache() await cache.delete(CACHE_KEY_LOCAL_DATA) await cache.delete(CACHE_KEY_STATE_DATA) aresponses.add( "api.v2.flunearyou.org", "/map/markers", "get", aresponses.Response( text=load_fixture("user_report_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) aresponses.add( "api.v2.flunearyou.org", "/states", "get", aresponses.Response( text=load_fixture("states_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) async with aiohttp.ClientSession() as session: client = Client(session=session) info = await client.user_reports.status_by_coordinates( TEST_LATITUDE, TEST_LONGITUDE ) assert info == { "local": { "id": 2, "city": "Los Angeles(90046)", "place_id": "23818", "zip": "90046", "contained_by": "204", "latitude": "34.114731", "longitude": "-118.363724", "none": 2, "symptoms": 0, "flu": 0, "lepto": 0, "dengue": 0, "chick": 0, "icon": "1", }, "state": { "name": "California", "place_id": "204", "lat": "37.250198", "lon": "-119.750298", "data": { "symptoms_percentage": 12.32, "none_percentage": 87.68, "ili_percentage": 2.69, "lepto_percentage": 0, "dengue_percentage": 2.17, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2119, "symptoms": 261, "no_symptoms": 1858, "ili": 57, "lepto": 0, "dengue": 46, "chick": 0, }, "last_week_data": { "symptoms_percentage": 14.29, "none_percentage": 85.71, "ili_percentage": 2.91, "lepto_percentage": 0.05, "dengue_percentage": 2.21, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2128, "symptoms": 304, "no_symptoms": 1824, "ili": 62, "lepto": 1, "dengue": 47, "chick": 0, }, }, } @pytest.mark.asyncio async def test_status_by_coordinates_success_measure(aresponses): """Test getting user reports by latitude/longitude (measurement).""" cache = SimpleMemoryCache() await cache.delete(CACHE_KEY_LOCAL_DATA) await cache.delete(CACHE_KEY_STATE_DATA) aresponses.add( "api.v2.flunearyou.org", "/map/markers", "get", aresponses.Response( text=load_fixture("user_report_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) aresponses.add( "api.v2.flunearyou.org", "/states", "get", aresponses.Response( text=load_fixture("states_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) async with aiohttp.ClientSession() as session: client = Client(session=session) info = await client.user_reports.status_by_coordinates( TEST_LATITUDE_UNCONTAINED, TEST_LONGITUDE_UNCONTAINED ) assert info == { "local": { "id": 3, "city": "Corvallis(97330)", "place_id": "21462", "zip": "97330", "contained_by": "239", "latitude": "44.638504", "longitude": "-123.292938", "none": 3, "symptoms": 0, "flu": 0, "lepto": 0, "dengue": 0, "chick": 0, "icon": "1", }, "state": { "name": "California", "place_id": "204", "lat": "37.250198", "lon": "-119.750298", "data": { "symptoms_percentage": 12.32, "none_percentage": 87.68, "ili_percentage": 2.69, "lepto_percentage": 0, "dengue_percentage": 2.17, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2119, "symptoms": 261, "no_symptoms": 1858, "ili": 57, "lepto": 0, "dengue": 46, "chick": 0, }, "last_week_data": { "symptoms_percentage": 14.29, "none_percentage": 85.71, "ili_percentage": 2.91, "lepto_percentage": 0.05, "dengue_percentage": 2.21, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2128, "symptoms": 304, "no_symptoms": 1824, "ili": 62, "lepto": 1, "dengue": 47, "chick": 0, }, }, } @pytest.mark.asyncio async def test_status_by_zip_success(aresponses): """Test getting user reports by ZIP code.""" cache = SimpleMemoryCache() await cache.delete(CACHE_KEY_LOCAL_DATA) await cache.delete(CACHE_KEY_STATE_DATA) aresponses.add( "api.v2.flunearyou.org", "/map/markers", "get", aresponses.Response( text=load_fixture("user_report_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) aresponses.add( "api.v2.flunearyou.org", "/states", "get", aresponses.Response( text=load_fixture("states_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) async with aiohttp.ClientSession() as session: client = Client(session=session) info = await client.user_reports.status_by_zip(TEST_ZIP) assert info == { "local": { "id": 2, "city": "Los Angeles(90046)", "place_id": "23818", "zip": "90046", "contained_by": "204", "latitude": "34.114731", "longitude": "-118.363724", "none": 2, "symptoms": 0, "flu": 0, "lepto": 0, "dengue": 0, "chick": 0, "icon": "1", }, "state": { "name": "California", "place_id": "204", "lat": "37.250198", "lon": "-119.750298", "data": { "symptoms_percentage": 12.32, "none_percentage": 87.68, "ili_percentage": 2.69, "lepto_percentage": 0, "dengue_percentage": 2.17, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2119, "symptoms": 261, "no_symptoms": 1858, "ili": 57, "lepto": 0, "dengue": 46, "chick": 0, }, "last_week_data": { "symptoms_percentage": 14.29, "none_percentage": 85.71, "ili_percentage": 2.91, "lepto_percentage": 0.05, "dengue_percentage": 2.21, "chick_percentage": 0, "level": 3, "overlay_color": "#00B7B6", "total_surveys": 2128, "symptoms": 304, "no_symptoms": 1824, "ili": 62, "lepto": 1, "dengue": 47, "chick": 0, }, }, } @pytest.mark.asyncio async def test_status_by_zip_failure(aresponses): """Test getting user reports by ZIP code.""" cache = SimpleMemoryCache() await cache.delete(CACHE_KEY_LOCAL_DATA) await cache.delete(CACHE_KEY_STATE_DATA) aresponses.add( "api.v2.flunearyou.org", "/map/markers", "get", aresponses.Response( text=load_fixture("user_report_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) aresponses.add( "api.v2.flunearyou.org", "/states", "get", aresponses.Response( text=load_fixture("states_response.json"), status=200, headers={"Content-Type": "application/json; charset=utf-8"}, ), ) async with aiohttp.ClientSession() as session: client = Client(session=session) info = await client.user_reports.status_by_zip("00000") assert info == {}

31.919048

82

0.446964

1,154

13,406

5.012998

0.130849

0.030424

0.027658

0.036301

0.906482

0.896111

0.891098

0.873466

0

0.080484

0.426302

13,406

419

83

31.995227

0.671694

0.003208

0

0.836317

0

0.246692

0.025625

0

0.012788

1

0

false

0

0.015345

0

0.015345

0

null

0

1

0

1

0

null

0

7

e4ef6780ca2a6cc411906e18d8b89785e1f3be3e

18,276

py

Python

src/model/models.py

parrondo/tutorial-LSTM

e9ef8297fabf2a479496036a9a6ed5210224a5e3

[ "MIT" ]

null

src/model/models.py

parrondo/tutorial-LSTM

e9ef8297fabf2a479496036a9a6ed5210224a5e3

[ "MIT" ]

null

src/model/models.py

parrondo/tutorial-LSTM

e9ef8297fabf2a479496036a9a6ed5210224a5e3

[ "MIT" ]

1

2019-11-04T14:34:05.000Z

import keras.backend as K from keras.models import Sequential from keras.layers.core import Flatten, Dense, Dropout from keras.layers.convolutional import Convolution2D from keras.layers.convolutional import MaxPooling2D from keras.layers.convolutional import ZeroPadding2D from keras.layers.convolutional import AveragePooling2D import theano.tensor.nnet.abstract_conv as absconv import h5py def CNN(nb_classes, img_dim, pretr_weights_file=None, model_name=None): """ Build Convolution Neural Network args : nb_classes (int) number of classes img_dim (tuple of int) num_chan, height, width returns : model (keras NN) the Neural Net model """ model = Sequential() model.add(Convolution2D(32, 3, 3, name="convolution2d_1", input_shape=(3, 224, 224), border_mode="same", activation='relu')) model.add(Convolution2D(32, 3, 3, name="convolution2d_2", border_mode="same", activation='relu')) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_1")) model.add(Convolution2D(64, 3, 3, name="convolution2d_3", border_mode="same", activation='relu')) model.add(Convolution2D(64, 3, 3, name="convolution2d_4", border_mode="same", activation='relu')) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_2")) model.add(Convolution2D(128, 3, 3, name="convolution2d_5", border_mode="same", activation='relu')) model.add(Convolution2D(128, 3, 3, name="convolution2d_6", border_mode="same", activation='relu')) model.add(Convolution2D(128, 3, 3, name="convolution2d_7", border_mode="same", activation='relu')) model.add(MaxPooling2D((2,2), strides=(2, 2), name="maxpooling2d_3")) # model.add(Convolution2D(256, 3, 3, name="convolution2d_8", border_mode="same", activation='relu')) # model.add(Convolution2D(256, 3, 3, name="convolution2d_9", border_mode="same", activation='relu')) # model.add(Convolution2D(256, 3, 3, name="convolution2d_10", border_mode="same", activation='relu')) # model.add(MaxPooling2D((2,2), strides=(2, 2), name="maxpooling2d_4")) # model.add(Convolution2D(512, 3, 3, name="convolution2d_11", border_mode="same", activation='relu')) # model.add(Convolution2D(512, 3, 3, name="convolution2d_12", border_mode="same", activation='relu')) # model.add(Convolution2D(512, 3, 3, name="convolution2d_13", border_mode="same", activation='relu')) # model.add(MaxPooling2D((2,2), strides=(2, 2), name="maxpooling2d_5")) model.add(Flatten(name="flatten_1")) model.add(Dense(1024, activation='relu', name="dense_1")) model.add(Dropout(0.5, name="dropout_1")) model.add(Dense(1024, activation='relu', name="dense_2")) model.add(Dropout(0.5, name="dropout_2")) model.add(Dense(nb_classes, activation='softmax', name="dense_3")) if model_name: model.name = model_name else: model.name = "CNN" if pretr_weights_file: model.load_weights(pretr_weights_file) model.layers.pop() model.outputs = [model.layers[-1].output] model.layers[-1].outbound_nodes = [] model.add(Dense(nb_classes, activation='softmax', name="dense_4")) return model def VGG(nb_classes, img_dim, pretr_weights_file=None, model_name=None): """ Build Convolution Neural Network args : nb_classes (int) number of classes img_dim (tuple of int) num_chan, height, width pretr_weights_file (str) file holding pre trained weights returns : model (keras NN) the Neural Net model """ model = Sequential() model.add(ZeroPadding2D((1, 1), input_shape=img_dim, name="zeropadding2d_1")) model.add(Convolution2D(64, 3, 3, activation='relu', name="convolution2d_1")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_2")) model.add(Convolution2D(64, 3, 3, activation='relu', name="convolution2d_2")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_1")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_3")) model.add(Convolution2D(128, 3, 3, activation='relu', name="convolution2d_3")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_4")) model.add(Convolution2D(128, 3, 3, activation='relu', name="convolution2d_4")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_2")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_5")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_5")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_6")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_6")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_7")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_7")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_3")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_8")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_8")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_9")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_9")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_10")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_10")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_4")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_11")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_11")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_12")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_12")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_13")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_13")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_5")) model.add(Flatten(name="flatten_1")) model.add(Dense(4096, activation='relu', name="dense_1")) model.add(Dropout(0.5, name="dropout_1")) model.add(Dense(4096, activation='relu', name="dense_2")) model.add(Dropout(0.5, name="dropout_2")) model.add(Dense(1000, activation='softmax', name="dense_3")) if model_name: model.name = model_name else: model.name = "VGG" if pretr_weights_file: model.load_weights(pretr_weights_file) model.layers.pop() model.outputs = [model.layers[-1].output] model.layers[-1].outbound_nodes = [] model.add(Dense(nb_classes, activation='softmax', name="dense_4")) # Freeze layers until specified number # for k in range(freeze_until): # model.layers[k].trainable = True return model def VGG19(nb_classes, img_dim, pretr_weights_file=None, model_name=None): """ Build Convolution Neural Network args : nb_classes (int) number of classes img_dim (tuple of int) num_chan, height, width returns : model (keras NN) the Neural Net model """ model = Sequential() model.add(ZeroPadding2D((1, 1), input_shape=img_dim, name="zeropadding2d_1")) model.add(Convolution2D(64, 3, 3, activation='relu', name="convolution2d_1")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_2")) model.add(Convolution2D(64, 3, 3, activation='relu', name="convolution2d_2")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_1")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_3")) model.add(Convolution2D(128, 3, 3, activation='relu', name="convolution2d_3")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_4")) model.add(Convolution2D(128, 3, 3, activation='relu', name="convolution2d_4")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_2")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_5")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_5")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_6")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_6")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_7")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_7")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_8")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_8")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_3")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_9")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_9")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_10")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_10")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_11")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_11")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_12")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_12")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_4")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_13")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_13")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_14")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_14")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_15")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_15")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_16")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_16")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_5")) model.add(Flatten(name="flatten_1")) model.add(Dense(4096, activation='relu', name="dense_1")) model.add(Dropout(0.5, name="dropout_1")) model.add(Dense(4096, activation='relu', name="dense_2")) model.add(Dropout(0.5, name="dropout_2")) model.add(Dense(1000, activation='softmax', name="dense_3")) if model_name: model.name = model_name else: model.name = "VGG19" if pretr_weights_file: model.load_weights(pretr_weights_file) model.layers.pop() model.outputs = [model.layers[-1].output] model.layers[-1].outbound_nodes = [] model.add(Dense(nb_classes, activation='softmax', name="dense_4")) # Freeze layers until specified number # for k in range(freeze_until): # model.layers[k].trainable = True return model def VGG_celeba(nb_classes, img_dim, pretr_weights_file=None, model_name=None): """ Build Convolution Neural Network args : nb_classes (int) number of classes img_dim (tuple of int) num_chan, height, width pretr_weights_file (str) file holding pre trained weights returns : model (keras NN) the Neural Net model """ model = Sequential() model.add(Convolution2D(32, 3, 3, name="convolution2d_1", input_shape=(3, 224, 224), border_mode="same", activation='relu')) model.add(Convolution2D(32, 3, 3, name="convolution2d_2", border_mode="same", activation='relu')) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_1")) model.add(Convolution2D(64, 3, 3, name="convolution2d_3", border_mode="same", activation='relu')) model.add(Convolution2D(64, 3, 3, name="convolution2d_4", border_mode="same", activation='relu')) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_2")) model.add(Convolution2D(128, 3, 3, name="convolution2d_5", border_mode="same", activation='relu')) model.add(Convolution2D(128, 3, 3, name="convolution2d_6", border_mode="same", activation='relu')) model.add(Convolution2D(128, 3, 3, name="convolution2d_7", border_mode="same", activation='relu')) model.add(MaxPooling2D((2,2), strides=(2, 2), name="maxpooling2d_3")) model.add(Convolution2D(256, 3, 3, name="convolution2d_8", border_mode="same", activation='relu')) model.add(Convolution2D(256, 3, 3, name="convolution2d_9", border_mode="same", activation='relu')) model.add(Convolution2D(256, 3, 3, name="convolution2d_10", border_mode="same", activation='relu')) model.add(MaxPooling2D((2,2), strides=(2, 2), name="maxpooling2d_4")) model.add(Convolution2D(512, 3, 3, name="convolution2d_11", border_mode="same", activation='relu')) model.add(Convolution2D(512, 3, 3, name="convolution2d_12", border_mode="same", activation='relu')) model.add(Convolution2D(512, 3, 3, name="convolution2d_13", border_mode="same", activation='relu')) model.add(MaxPooling2D((2,2), strides=(2, 2), name="maxpooling2d_5")) model.add(Flatten(name="flatten_1")) model.add(Dense(4096, activation='relu', name="dense_1")) model.add(Dropout(0.5, name="dropout_1")) model.add(Dense(4096, activation='relu', name="dense_2")) model.add(Dropout(0.5, name="dropout_2")) model.add(Dense(2, activation='softmax', name="dense_3")) if model_name: model.name = model_name else: model.name = "VGG_celeba" if pretr_weights_file: model.load_weights(pretr_weights_file) model.layers.pop() model.outputs = [model.layers[-1].output] model.layers[-1].outbound_nodes = [] model.add(Dense(nb_classes, activation='softmax', name="dense_4")) # Freeze layers until specified number # for k in range(freeze_until): # model.layers[k].trainable = True return model def VGGCAM(nb_classes, img_dim, pretr_weights_file=None, model_name=None): """ Build VGGCAM network args : nb_classes (int) number of classes img_dim (tuple of int) num_chan, height, width pretr_weights_file (str) file holding pre trained weights returns : model (keras NN) the Neural Net model """ model = Sequential() model.add(ZeroPadding2D((1, 1), input_shape=img_dim, name="zeropadding2d_1")) model.add(Convolution2D(64, 3, 3, activation='relu', name="convolution2d_1")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_2")) model.add(Convolution2D(64, 3, 3, activation='relu', name="convolution2d_2")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_1")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_3")) model.add(Convolution2D(128, 3, 3, activation='relu', name="convolution2d_3")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_4")) model.add(Convolution2D(128, 3, 3, activation='relu', name="convolution2d_4")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_2")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_5")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_5")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_6")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_6")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_7")) model.add(Convolution2D(256, 3, 3, activation='relu', name="convolution2d_7")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_3")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_8")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_8")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_9")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_9")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_10")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_10")) model.add(MaxPooling2D((2, 2), strides=(2, 2), name="maxpooling2d_4")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_11")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_11")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_12")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_12")) model.add(ZeroPadding2D((1, 1), name="zeropadding2d_13")) model.add(Convolution2D(512, 3, 3, activation='relu', name="convolution2d_13")) # Add another conv layer with ReLU + GAP model.add(Convolution2D(1024, 3, 3, activation='relu', border_mode="same", name="convolution2d_14")) model.add(AveragePooling2D((14, 14), name="average_pooling2d_1")) model.add(Flatten(name="flatten_1")) # Add the W layer model.add(Dense(10, activation='softmax', name="dense_1")) if model_name: model.name = model_name else: model.name = "VGGCAM" if pretr_weights_file: with h5py.File(pretr_weights_file) as hw: for k in range(hw.attrs['nb_layers']): g = hw['layer_{}'.format(k)] weights = [g['param_{}'.format(p)] for p in range(g.attrs['nb_params'])] model.layers[k].set_weights(weights) if model.layers[k].name == "convolution2d_13": break return model def get_classmap(model, X, nb_classes, batch_size, num_input_channels, ratio): inc = model.layers[0].input conv6 = model.layers[-4].output conv6_resized = absconv.bilinear_upsampling(conv6, ratio, batch_size=batch_size, num_input_channels=num_input_channels) WT = model.layers[-1].W.T conv6_resized = K.reshape(conv6_resized, (-1, num_input_channels, 224 * 224)) classmap = K.dot(WT, conv6_resized).reshape((-1, nb_classes, 224, 224)) get_cmap = K.function([inc], classmap) return get_cmap([X]) def load(model_name, nb_classes, img_dim, pretr_weights_file=None): if model_name == "VGG": model = VGG(nb_classes, img_dim, pretr_weights_file=pretr_weights_file, model_name=None) elif model_name == "VGG19": model = VGG19(nb_classes, img_dim, pretr_weights_file=pretr_weights_file, model_name=None) elif model_name == "VGGCAM": model = VGGCAM(nb_classes, img_dim, pretr_weights_file=pretr_weights_file, model_name=None) elif model_name == "CNN": model = CNN(nb_classes, img_dim, pretr_weights_file=pretr_weights_file, model_name=None) elif model_name == "VGG_celeba": model = VGG_celeba(nb_classes, img_dim, pretr_weights_file=pretr_weights_file, model_name=None) return model

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Python

src/ai/utils/.ipynb_checkpoints/predictor-checkpoint.py

carlov93/predictive_maintenance

eb00b82bde02668387d0308571296a82f78abef6

[ "MIT" ]

1

2020-02-11T07:50:33.000Z

src/ai/utils/.ipynb_checkpoints/predictor-checkpoint.py

carlov93/predictive_maintenance

eb00b82bde02668387d0308571296a82f78abef6

[ "MIT" ]

12

2020-03-24T18:16:51.000Z

2022-03-12T00:15:55.000Z

src/ai/utils/.ipynb_checkpoints/predictor-checkpoint.py

carlov93/predictive_maintenance

eb00b82bde02668387d0308571296a82f78abef6

[ "MIT" ]

null

import torch import torch.nn as nn import torch.optim as optim import pandas as pd import numpy as np import builtins class PredictorMse(): def __init__(self, model, criterion, path_data, columns_to_ignore): self.model = model self.criterion = criterion self.path_data = path_data self.column_names_data = self.get_column_names_data() self.columns_to_ignore = columns_to_ignore def get_column_names_data(self): with open(self.path_data, 'r') as f: header = f.readline().replace('\n','') return header.split(",") def create_column_names_result(self): column_names_target = [column_name+" target" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_predicted = [column_name+" predicted" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_loss_per_sensor = [column_name+" share of loss " for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_residuals= ["residual "+column_name for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] return ["ID"] + column_names_target + column_names_predicted + ["loss"] + column_names_loss_per_sensor + column_names_residuals def predict(self, data_loader): results = pd.DataFrame(columns=self.create_column_names_result()) self.model.eval() with torch.no_grad(): print("Start predicting.") for batch_number, data in enumerate(data_loader): input_data, target_data = data # Store ID of target sample id_target = target_data[:,0] #ID must be on first position! # De-select ID feature in both input_data and target data for inference input_data = torch.from_numpy(input_data.numpy()[:,:,1:]) # ID must be on first position! target_data = torch.from_numpy(target_data.numpy()[:,1:]) # ID must be on first position! # Initilize Hidden and Cell State hidden = self.model.init_hidden() # Forward propagation output = self.model(input_data, hidden) # Calculate loss loss = self.criterion(output, target_data) loss_share_per_sensor = self.criterion.share_per_sensor(output, target_data) for batch in range(self.model.batch_size): # Reshape and Calculate prediction metrics predicted_data = output[batch,:].data.numpy().tolist() ground_truth = target_data[batch,:].data.numpy().tolist() loss_share_per_sensor_np = loss_share_per_sensor[batch,:].data.numpy().tolist() residuals = [target_i - prediction_i for target_i, prediction_i in zip(ground_truth, predicted_data)] # Add values to dataframe data = [id_target[batch].item()] + ground_truth + predicted_data + [loss[batch].item()] + loss_share_per_sensor_np + residuals results = results.append(pd.Series(data, index=results.columns), ignore_index=True) # Print status if (batch_number*self.model.batch_size)%5000 == 0: print("Current status: " + str(batch_number*self.model.batch_size) + " samples are predicted.") print("Finished predicting.") return results class PredictorMle(): def __init__(self, model, criterion, path_data, columns_to_ignore): self.model = model self.criterion = criterion self.path_data = path_data self.column_names_data = self.get_column_names_data() self.columns_to_ignore = columns_to_ignore def get_column_names_data(self): with open(self.path_data, 'r') as f: header = f.readline().replace('\n','') return header.split(",") def create_column_names_result_mse(self): column_names_target = [column_name+" target" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_predicted = [column_name+" predicted" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_loss_per_sensor = [column_name+" share of loss " for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_residuals= ["normalised residual "+column_name for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] return ["ID"] + column_names_target + column_names_predicted + ["loss"] + column_names_loss_per_sensor + column_names_residuals def predict(self, data_loader): results = pd.DataFrame(columns=self.create_column_names_result()) self.model.eval() with torch.no_grad(): print("Start predicting") for batch_number, data in enumerate(data_loader): input_data, target_data = data # Store ID of target sample id_target = int(target_data[:,0].item()) #ID must be on first position! # De-select ID feature in both input_data and target data for inference input_data = torch.from_numpy(input_data.numpy()[:,:,1:]) # ID must be on first position! target_data = torch.from_numpy(target_data.numpy()[:,1:]) # ID must be on first position! # Initilize Hidden and Cell State hidden = self.model.init_hidden() # Forward propagation y_hat, tau = self.model(input_data, hidden) # Because of the transformation of sigma inside the LossModuleMle (σ_t = exp(τ_t)) # we have to revert this transformation with exp(tau_i). # ToDo: sigma = torch.exp(tau) ???????? # Calculate loss loss = self.criterion(y_hat, target_data) loss_share_per_sensor = self.criterion.share_per_sensor(y_hat, target_data) # Reshape and Calculate prediction metrics y_hat = torch.squeeze(y_hat) predicted_data = y_hat.data.numpy().tolist() sigma = torch.squeeze(sigma) sigma = sigma.data.numpy().tolist() target_data = torch.squeeze(target_data) target_data = target_data.data.numpy().tolist() loss_share_per_sensor = torch.squeeze(loss_share_per_sensor) loss_share_per_sensor = loss_share_per_sensor.data.numpy().tolist() normalised_residuals = [(target_i - prediction_i)/sigma_i for target_i, prediction_i, sigma_i in zip(target_data, predicted_data, sigma)] # Add values to dataframe data = [id_target] + target_data + predicted_data + [loss.item()] + loss_share_per_sensor + normalised_residuals results = results.append(pd.Series(data, index=results.columns), ignore_index=True) # Print status if id_target%5000 == 0: print("Current status: " + str(id_target) + " samples are predicted.") print("Finished predicting") return results class PredictorMultiTaskLearning(): def __init__(self, model, criterion, path_data, columns_to_ignore, threshold_anomaly): self.model = model self.criterion = criterion self.path_data = path_data self.column_names_data = self.get_column_names_data() self.columns_to_ignore = columns_to_ignore self.threshold_anomaly = threshold_anomaly def get_column_names_data(self): with open(self.path_data, 'r') as f: header = f.readline().replace('\n','') return header.split(",") def create_column_names_result(self): column_names_target = [column_name+" target" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_predicted = [column_name+" predicted" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_loss_per_sensor = [column_name+" share of loss " for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_residuals= ["residual "+column_name for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_latent_space= ["latent_space_"+str(i) for i in range(self.model.n_hidden_fc_ls_analysis)] column_names = ["ID"] + column_names_target + column_names_predicted + ["loss"] + \ column_names_loss_per_sensor + column_names_residuals + column_names_latent_space return column_names def predict(self, data_loader): results = pd.DataFrame(columns=self.create_column_names_result()) self.model.eval() with torch.no_grad(): print("Start predicting.") for batch_number, data in enumerate(data_loader): input_data, target_data = data # Store ID of target sample id_target = target_data[:,0] #ID must be on first position! # De-select ID feature in both input_data and target data for inference input_data = torch.from_numpy(input_data.numpy()[:,:,1:]) # ID must be on first position! target_data = torch.from_numpy(target_data.numpy()[:,1:]) # ID must be on first position! # Initilize Hidden and Cell State hidden = self.model.init_hidden() # Forward propagation prediction, _ = self.model(input_data, hidden) latent_space = self.model.current_latent_space # Calculate loss (subnetwork for latent space analysis not longer considered) loss_prediction_network = self.criterion(prediction, target_data) loss_share_per_sensor = self.criterion.share_per_sensor(prediction, target_data) for batch in range(self.model.batch_size): # Reshape and Calculate prediction metrics predicted_data = prediction[batch,:].data.numpy().tolist() ground_truth = target_data[batch,:].data.numpy().tolist() residuals = [target_i - prediction_i for target_i, prediction_i in zip(ground_truth, predicted_data)] latent_space_np = latent_space[batch,:].data.numpy().tolist() loss = loss_prediction_network[batch].item() loss_share_per_sensor_np = loss_share_per_sensor[batch,:].data.numpy().tolist() # Add values to dataframe data = [id_target[batch].item()] + ground_truth + predicted_data + [loss] + loss_share_per_sensor_np + residuals + latent_space_np results = results.append(pd.Series(data, index=results.columns), ignore_index=True) # Print status if (batch_number*self.model.batch_size)%5000 == 0: print("Current status: " + str(batch_number*self.model.batch_size) + " samples are predicted.") return results def detect_anomaly(self, results_prediction, smooth_rate): # smooth loss to smoothed_loss = [] for i,value in enumerate(results_prediction.loc[:,"loss"]): if i==0: smoothed_loss.append(value) else: x = smooth_rate * value + (1 - smooth_rate) * smoothed_loss[-1] smoothed_loss.append(x) results_prediction["smoothed_loss"]=smoothed_loss # tag sample as an anomaly (1) if loss is higher than given threshold, otherwhise 0 results_prediction["anomaly"] = np.where(results_prediction["smoothed_loss"]>=self.threshold_anomaly, 1, 0) return results_prediction class PredictorMultiTaskLearningCopy(): def __init__(self, model, criterion, path_data, columns_to_ignore, threshold_anomaly): self.model = model self.criterion = criterion self.path_data = path_data self.column_names_data = self.get_column_names_data() self.columns_to_ignore = columns_to_ignore self.threshold_anomaly = threshold_anomaly def get_column_names_data(self): with open(self.path_data, 'r') as f: header = f.readline().replace('\n','') return header.split(",") def create_column_names_result(self): column_names_target = [column_name+" target" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_predicted = [column_name+" predicted" for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_loss_per_sensor = [column_name+" share of loss " for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_residuals= ["residual "+column_name for column_name in self.column_names_data if column_name not in self.columns_to_ignore+["ID"]] column_names_latent_space= ["latent_space_"+str(i) for i in range(self.model.n_hidden_fc_ls_analysis)] column_names = ["ID"] + column_names_target + column_names_predicted + ["loss"] + \ column_names_loss_per_sensor + column_names_residuals + column_names_latent_space return column_names def predict(self, data): results = pd.DataFrame(columns=self.create_column_names_result()) self.model.eval() with torch.no_grad(): input_data, target_data = data # Store ID of target sample id_target = target_data[:,0] #ID must be on first position! # De-select ID feature in both input_data and target data for inference input_data = torch.from_numpy(input_data.numpy()[:,:,1:]) # ID must be on first position! target_data = torch.from_numpy(target_data.numpy()[:,1:]) # ID must be on first position! # Initilize Hidden and Cell State hidden = self.model.init_hidden() # Forward propagation prediction, _ = self.model(input_data, hidden) latent_space = self.model.current_latent_space # Calculate loss (subnetwork for latent space analysis not longer considered) loss_prediction_network = self.criterion(prediction, target_data) loss_share_per_sensor = self.criterion.share_per_sensor(prediction, target_data) batch_results= [] for batch in range(self.model.batch_size): # Reshape and Calculate prediction metrics predicted_data = prediction[batch,:].data.numpy().tolist() ground_truth = target_data[batch,:].data.numpy().tolist() residuals = [target_i - prediction_i for target_i, prediction_i in zip(ground_truth, predicted_data)] latent_space_np = latent_space[batch,:].data.numpy().tolist() loss = loss_prediction_network[batch].item() loss_share_per_sensor_np = loss_share_per_sensor[batch,:].data.numpy().tolist() # Add values to dataframe data = str(id_target[batch].item())+str(";")+str(ground_truth)+str(";")+str(predicted_data)+str(";")+str(loss) +str(";")+str(loss_share_per_sensor_np)+str(";")+str(residuals)+str(";")+str(latent_space_np)+str("\n") batch_results.append(data) return batch_results def detect_anomaly(self, results_prediction, smooth_rate): # smooth loss to smoothed_loss = [] for i,value in enumerate(results_prediction.loc[:,"loss"]): if i==0: smoothed_loss.append(value) else: x = smooth_rate * value + (1 - smooth_rate) * smoothed_loss[-1] smoothed_loss.append(x) results_prediction["smoothed_loss"]=smoothed_loss # tag sample as an anomaly (1) if loss is higher than given threshold, otherwhise 0 results_prediction["anomaly"] = np.where(results_prediction["smoothed_loss"]>=self.threshold_anomaly, 1, 0) return results_prediction

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1

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null

0

7

900d11aedc3aa70ad91e5ffd4183fa0f21043a15

14,868

py

Python

draw_num_ue.py

T610/MEC

351b83362e0c8a7128bd95d20de2a720a87b5c48

[ "MIT" ]

null

draw_num_ue.py

T610/MEC

351b83362e0c8a7128bd95d20de2a720a87b5c48

[ "MIT" ]

null

draw_num_ue.py

T610/MEC

351b83362e0c8a7128bd95d20de2a720a87b5c48

[ "MIT" ]

null

import numpy as np from wolf_agent import WoLFAgent from matrix_game_local_only import MatrixGame_local from matrix_game_mec_only import MatrixGame_mec from matrix_game import MatrixGame from queue_relay import QueueRelay import matplotlib.pyplot as plt from gpd import GPD ## TLIU from dataToExcel import DTE ## TLIU import xlrd ## TLIU import xlsxwriter ## TLIU class draw_picture(): def __init__(self): self.bandwidth = [] self.usersnumber = [] def run_for_all_mode(self,bw,un): nb_episode = 700 actions = np.arange(8) user_num = un lambda_n = np.zeros(user_num) for i in range(user_num): # 每比特需要周期量 70~800 cycles/bits if i % 5 == 0: lambda_n[i] = 0.001 if i % 5 == 1: lambda_n[i] = 0.01 if i % 5 == 2: lambda_n[i] = 0.1 if i % 5 == 3: lambda_n[i] = 0.001 if i % 5 == 4: lambda_n[i] = 0.01 actions_set = [[0, 5 * pow(10, 6), 0.4], [0, 5 * pow(10, 6), 0.4], [0, 5 * pow(10, 6), 0.4], [0, 5 * pow(10, 6), 0.4], [1, 0, 0.4], [1, 0, 0.4], [1, 0, 0.4], [1, 0, 0.4]] GPD1_array = [4 * pow(10, 6) for _ in range(user_num)] GPD2_array = [0.3 for _ in range(user_num)] # init wolf agent wolf_agent_array = [] for i in range(user_num): wolf_agent_array.append(WoLFAgent(alpha=0.1, actions=actions, high_delta=0.004, low_delta=0.002)) queue_relay_array = [] for i in range(user_num): queue_relay_array.append(QueueRelay(lambda_n[i], GPD1_array[i], GPD2_array[i])) # set reward functio # reward = Reward() reward_history = [] # init_Queue_relay Q_array_histroy = [[10] for i in range(user_num)] ## TLIU for episode in range(nb_episode): Q_array = [] Qx_array = [] Qy_array = [] Qz_array = [] M1_array = [] M2_array = [] for i in range(user_num): Q_array.append(queue_relay_array[i].Q) Qx_array.append(queue_relay_array[i].Qx) Qy_array.append(queue_relay_array[i].Qy) Qz_array.append(queue_relay_array[i].Qz) M1_array.append(queue_relay_array[i].M1) M2_array.append(queue_relay_array[i].M2) for i in range(user_num): Q_array_histroy[i].append(Q_array[i]) if episode % 50 == 0 and episode != 0: for i in range(user_num): aa = GPD() data = Q_array_histroy[i] # data = [10000000000000 for i in range(200) ] # res = aa.gpd( data , 3.96*pow(10,5) ) res = aa.gpd(data, 3.96 * pow(10, 6)) if res: queue_relay_array[i].GPD1 = res[0][0] queue_relay_array[i].GPD2 = res[0][1] queue_relay_array[i].updateM1() queue_relay_array[i].updateM2() iteration_actions = [] for i in range(user_num): iteration_actions.append(wolf_agent_array[i].act()) game = MatrixGame(actions=iteration_actions, Q=Q_array, Qx=Qx_array, Qy=Qy_array, Qz=Qz_array, M1=M1_array, M2=M2_array , BW= bw) reward, bn, lumbda, rff = game.step(actions=iteration_actions) print("episode",episode,"reward",sum(reward)) for i in range(user_num): # wolf agent act # update_Queue_relay queue_relay_array[i].lumbda = lumbda[i] queue_relay_array[i].updateQ(bn[i], actions_set[iteration_actions[i]][0], rff[i]) queue_relay_array[i].updateQx() queue_relay_array[i].updateQy() queue_relay_array[i].updateQz() # reward step reward_history.append(sum(reward)) for i in range(user_num): wolf_agent_array[i].observe(reward=reward[i]) # for i in range(user_num): # print(wolf_agent_array[i].pi_average) # plt.plot(np.arange(len(reward_history)), reward_history, label="") # plt.show() return reward_history[-1] def run_for_only_mec(self,bw1,un1): nb_episode = 700 actions_set = [ [1, 0, 0.1], [1, 0, 0.5], [1, 0, 1], [1, 0, 2]] actions = np.arange(len(actions_set)) user_num = un1 lambda_n = np.zeros(user_num) for i in range(user_num): # 每比特需要周期量 70~800 cycles/bits if i % 5 == 0: lambda_n[i] = 0.001 if i % 5 == 1: lambda_n[i] = 0.01 if i % 5 == 2: lambda_n[i] = 0.1 if i % 5 == 3: lambda_n[i] = 0.001 if i % 5 == 4: lambda_n[i] = 0.01 GPD1_array = [4 * pow(10, 6) for _ in range(user_num)] GPD2_array = [0.3 for _ in range(user_num)] # init wolf agent wolf_agent_array = [] for i in range(user_num): wolf_agent_array.append(WoLFAgent(alpha=0.1, actions=actions, high_delta=0.004, low_delta=0.002)) queue_relay_array = [] for i in range(user_num): queue_relay_array.append(QueueRelay(lambda_n[i], GPD1_array[i], GPD2_array[i])) # set reward functio # reward = Reward() reward_history = [] # init_Queue_relay Q_array_histroy = [[10] for i in range(user_num)] ## TLIU for episode in range(nb_episode): Q_array = [] Qx_array = [] Qy_array = [] Qz_array = [] M1_array = [] M2_array = [] for i in range(user_num): Q_array.append(queue_relay_array[i].Q) Qx_array.append(queue_relay_array[i].Qx) Qy_array.append(queue_relay_array[i].Qy) Qz_array.append(queue_relay_array[i].Qz) M1_array.append(queue_relay_array[i].M1) M2_array.append(queue_relay_array[i].M2) for i in range(user_num): Q_array_histroy[i].append(Q_array[i]) if episode % 50 == 0 and episode != 0: for i in range(user_num): aa = GPD() data = Q_array_histroy[i] # data = [10000000000000 for i in range(200) ] # res = aa.gpd( data , 3.96*pow(10,5) ) res = aa.gpd(data, 3.96 * pow(10, 6)) if res: queue_relay_array[i].GPD1 = res[0][0] queue_relay_array[i].GPD2 = res[0][1] queue_relay_array[i].updateM1() queue_relay_array[i].updateM2() iteration_actions = [] for i in range(user_num): iteration_actions.append(wolf_agent_array[i].act()) game = MatrixGame_mec(actions=iteration_actions, Q=Q_array, Qx=Qx_array, Qy=Qy_array, Qz=Qz_array, M1=M1_array, M2=M2_array, BW=bw1) #print('Q value :' + str(Q_array) + str(Qx_array) + str(Qy_array) + str(Qz_array)) reward, bn, lumbda, rff = game.step(actions=iteration_actions) for i in range(user_num): # wolf agent act # update_Queue_relay queue_relay_array[i].lumbda = lumbda[i] queue_relay_array[i].updateQ(bn[i], actions_set[iteration_actions[i]][0], rff[i]) queue_relay_array[i].updateQx() queue_relay_array[i].updateQy() queue_relay_array[i].updateQz() # reward step reward_history.append(sum(reward)) for i in range(user_num): wolf_agent_array[i].observe(reward=reward[i]) # for i in range(user_num): # print(wolf_agent_array[i].pi_average) # plt.plot(np.arange(len(reward_history)), reward_history, label="") # plt.show() return reward_history[-1] def run_for_only_local(self,bw2,un2): nb_episode = 700 actions_set = [ [0, 5 * pow(10, 6), 0], [0, 10 * pow(10, 6), 0], [0, 20 * pow(10, 6), 0], [0, 30 * pow(10, 6), 0]] actions = np.arange(len(actions_set)) user_num = un2 lambda_n = np.zeros(user_num) for i in range(user_num): # 每比特需要周期量 70~800 cycles/bits if i % 5 == 0: lambda_n[i] = 0.001 if i % 5 == 1: lambda_n[i] = 0.01 if i % 5 == 2: lambda_n[i] = 0.1 if i % 5 == 3: lambda_n[i] = 0.001 if i % 5 == 4: lambda_n[i] = 0.01 GPD1_array = [4 * pow(10, 6) for _ in range(user_num)] GPD2_array = [0.3 for _ in range(user_num)] # init wolf agent wolf_agent_array = [] for i in range(user_num): wolf_agent_array.append(WoLFAgent(alpha=0.1, actions=actions, high_delta=0.004, low_delta=0.002)) queue_relay_array = [] for i in range(user_num): queue_relay_array.append(QueueRelay(lambda_n[i], GPD1_array[i], GPD2_array[i])) # set reward functio # reward = Reward() reward_history = [] # init_Queue_relay Q_array_histroy = [[10] for i in range(user_num)] ## TLIU for episode in range(nb_episode): Q_array = [] Qx_array = [] Qy_array = [] Qz_array = [] M1_array = [] M2_array = [] for i in range(user_num): Q_array.append(queue_relay_array[i].Q) Qx_array.append(queue_relay_array[i].Qx) Qy_array.append(queue_relay_array[i].Qy) Qz_array.append(queue_relay_array[i].Qz) M1_array.append(queue_relay_array[i].M1) M2_array.append(queue_relay_array[i].M2) for i in range(user_num): Q_array_histroy[i].append(Q_array[i]) if episode % 50 == 0 and episode != 0: for i in range(user_num): aa = GPD() data = Q_array_histroy[i] # data = [10000000000000 for i in range(200) ] # res = aa.gpd( data , 3.96*pow(10,5) ) res = aa.gpd(data, 3.96 * pow(10, 6)) if res: queue_relay_array[i].GPD1 = res[0][0] queue_relay_array[i].GPD2 = res[0][1] queue_relay_array[i].updateM1() queue_relay_array[i].updateM2() iteration_actions = [] for i in range(user_num): iteration_actions.append(wolf_agent_array[i].act()) game = MatrixGame_local(actions=iteration_actions, Q=Q_array, Qx=Qx_array, Qy=Qy_array, Qz=Qz_array, M1=M1_array, M2=M2_array, BW=bw2) reward, bn, lumbda, rff = game.step(actions=iteration_actions) for i in range(user_num): # wolf agent act # update_Queue_relay queue_relay_array[i].lumbda = lumbda[i] queue_relay_array[i].updateQ(bn[i], actions_set[iteration_actions[i]][0], rff[i]) queue_relay_array[i].updateQx() queue_relay_array[i].updateQy() queue_relay_array[i].updateQz() # reward step reward_history.append(sum(reward)) for i in range(user_num): wolf_agent_array[i].observe(reward=reward[i]) # for i in range(user_num): # print(wolf_agent_array[i].pi_average) # plt.plot(np.arange(len(reward_history)), reward_history, label="") # plt.show() return reward_history[-1] if __name__ == '__main__': #bandwidth = np.array([2*pow(10,6),4*pow(10,6),6*pow(10,6),8*pow(10,6),10*pow(10,6),12*pow(10,6),14*pow(10,6),16*pow(10,6)]) usernumber = np.array([10,15,20,25,30,35,40,45]) draw = draw_picture() cost_of_all = [] cost_of_mec = [] cost_of_local = [] cost_of_all_6mhz = [] cost_of_all_8mhz = [] cost_of_all_12mhz = [] for i in range(8): cost_of_all.append(draw.run_for_all_mode(bw=10*pow(10,6), un=usernumber[i])) cost_of_mec.append(draw.run_for_only_mec(bw1=10*pow(10,6), un1=usernumber[i])) cost_of_local.append(draw.run_for_only_local(bw2=10*pow(10,6), un2=usernumber[i])) cost_of_all_6mhz.append(draw.run_for_all_mode(bw=6 * pow(10, 6), un=usernumber[i])) cost_of_all_8mhz.append(draw.run_for_all_mode(bw=8 * pow(10, 6), un=usernumber[i])) cost_of_all_12mhz.append(draw.run_for_all_mode(bw=12 * pow(10, 6), un=usernumber[i])) plt.plot(usernumber, cost_of_all, '^-', linewidth=0.4, label='all selection') plt.plot(usernumber, cost_of_local, '<-', linewidth=0.4, label='only local selection') plt.plot(usernumber, cost_of_mec, '>-', linewidth=0.4, label='only MEC selection') plt.plot(usernumber, cost_of_all_6mhz, '<-', linewidth=0.2, label='all selection of 6mhz') plt.plot(usernumber, cost_of_all_8mhz, '<-', linewidth=0.2, label='all selection of 8mhz') plt.plot(usernumber, cost_of_all_12mhz, '<-', linewidth=0.2, label='all selection of 12mhz') plt.grid(True) #显示网格 plt.xlabel('The number of UE') plt.ylabel('Sum Cost') plt.legend(loc='upper left') #图例右上角 plt.show() data = DTE("./picture/pic2/all") ## TLIU print(cost_of_all) data.write(cost_of_all) data = DTE("./picture/pic2/mec") ## TLIU print(cost_of_mec) data.write(cost_of_mec) data = DTE("./picture/pic2/local") ## TLIU print(cost_of_local) data.write(cost_of_local) data = DTE("./picture/pic2/all_6MHZ") ## TLIU print(cost_of_all_6mhz) data.write(cost_of_all_6mhz) data = DTE("./picture/pic2/all_8MHZ") ## TLIU print(cost_of_all_8mhz) data.write(cost_of_all_8mhz) data = DTE("./picture/pic2/all_12MHZ") ## TLIU print(cost_of_all_12mhz) data.write(cost_of_all_12mhz)

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null

0

1

0

1

0

null

0

7

90123dc13141a8929af9b8cdcf1a759bb7563372

167

py

Python

maskrcnn_benchmark/modeling/rpn/__init__.py

p517332051/face_benchmark

c76c2b2142ecf65b7bace4b007a33fa4e795d2d0

[ "MIT" ]

2

2020-04-02T14:53:29.000Z

2021-07-13T04:31:47.000Z

maskrcnn_benchmark/modeling/rpn/__init__.py

p517332051/face_benchmark

c76c2b2142ecf65b7bace4b007a33fa4e795d2d0

[ "MIT" ]

null

maskrcnn_benchmark/modeling/rpn/__init__.py

p517332051/face_benchmark

c76c2b2142ecf65b7bace4b007a33fa4e795d2d0

[ "MIT" ]

1

2020-07-13T06:02:42.000Z

33.4

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Python

boto3_type_annotations_with_docs/boto3_type_annotations/appmesh/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

119

2018-12-01T18:20:57.000Z

2022-02-02T10:31:29.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/appmesh/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

15

2018-11-16T00:16:44.000Z

2021-11-13T03:44:18.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/appmesh/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

11

2019-05-06T05:26:51.000Z

2021-09-28T15:27:59.000Z

from typing import Optional from botocore.client import BaseClient from typing import Dict from botocore.paginate import Paginator from botocore.waiter import Waiter from typing import Union from typing import List class Client(BaseClient): def can_paginate(self, operation_name: str = None): """ Check if an operation can be paginated. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :return: ``True`` if the operation can be paginated, ``False`` otherwise. """ pass def create_mesh(self, meshName: str, clientToken: str = None, spec: Dict = None, tags: List = None) -> Dict: """ Creates a service mesh. A service mesh is a logical boundary for network traffic between the services that reside within it. After you create your service mesh, you can create virtual services, virtual nodes, virtual routers, and routes to distribute traffic between the applications in your mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/CreateMesh>`_ **Request Syntax** :: response = client.create_mesh( clientToken='string', meshName='string', spec={ 'egressFilter': { 'type': 'ALLOW_ALL'|'DROP_ALL' } }, tags=[ { 'key': 'string', 'value': 'string' }, ] ) **Response Syntax** :: { 'mesh': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'egressFilter': { 'type': 'ALLOW_ALL'|'DROP_ALL' } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' } } } **Response Structure** - *(dict) --* - **mesh** *(dict) --* The full description of your service mesh following the create call. - **meshName** *(string) --* The name of the service mesh. - **metadata** *(dict) --* The associated metadata for the service mesh. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The associated specification for the service mesh. - **egressFilter** *(dict) --* The egress filter rules for the service mesh. - **type** *(string) --* The egress filter type. By default, the type is ``DROP_ALL`` , which allows egress only from virtual nodes to other defined resources in the service mesh (and any traffic to ``*.amazonaws.com`` for AWS API calls). You can set the egress filter type to ``ALLOW_ALL`` to allow egress to any endpoint inside or outside of the service mesh. - **status** *(dict) --* The status of the service mesh. - **status** *(string) --* The current mesh status. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name to use for the service mesh. :type spec: dict :param spec: The service mesh specification to apply. - **egressFilter** *(dict) --* The egress filter rules for the service mesh. - **type** *(string) --* **[REQUIRED]** The egress filter type. By default, the type is ``DROP_ALL`` , which allows egress only from virtual nodes to other defined resources in the service mesh (and any traffic to ``*.amazonaws.com`` for AWS API calls). You can set the egress filter type to ``ALLOW_ALL`` to allow egress to any endpoint inside or outside of the service mesh. :type tags: list :param tags: Optional metadata that you can apply to the service mesh to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - *(dict) --* Optional metadata that you apply to a resource to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - **key** *(string) --* **[REQUIRED]** One part of a key-value pair that make up a tag. A ``key`` is a general label that acts like a category for more specific tag values. - **value** *(string) --* The optional part of a key-value pair that make up a tag. A ``value`` acts as a descriptor within a tag category (key). :rtype: dict :returns: """ pass def create_route(self, meshName: str, routeName: str, spec: Dict, virtualRouterName: str, clientToken: str = None, tags: List = None) -> Dict: """ Creates a route that is associated with a virtual router. You can use the ``prefix`` parameter in your route specification for path-based routing of requests. For example, if your virtual service name is ``my-service.local`` and you want the route to match requests to ``my-service.local/metrics`` , your prefix should be ``/metrics`` . If your route matches a request, you can distribute traffic to one or more target virtual nodes with relative weighting. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/CreateRoute>`_ **Request Syntax** :: response = client.create_route( clientToken='string', meshName='string', routeName='string', spec={ 'httpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] }, 'match': { 'prefix': 'string' } }, 'tcpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] } } }, tags=[ { 'key': 'string', 'value': 'string' }, ], virtualRouterName='string' ) **Response Syntax** :: { 'route': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'routeName': 'string', 'spec': { 'httpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] }, 'match': { 'prefix': 'string' } }, 'tcpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **route** *(dict) --* The full description of your mesh following the create call. - **meshName** *(string) --* The name of the service mesh that the route resides in. - **metadata** *(dict) --* The associated metadata for the route. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **routeName** *(string) --* The name of the route. - **spec** *(dict) --* The specifications of the route. - **httpRoute** *(dict) --* The HTTP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **match** *(dict) --* The criteria for determining an HTTP request match. - **prefix** *(string) --* Specifies the path to match requests with. This parameter must always start with ``/`` , which by itself matches all requests to the virtual service name. You can also match for path-based routing of requests. For example, if your virtual service name is ``my-service.local`` and you want the route to match requests to ``my-service.local/metrics`` , your prefix should be ``/metrics`` . - **tcpRoute** *(dict) --* The TCP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **status** *(dict) --* The status of the route. - **status** *(string) --* The current status for the route. - **virtualRouterName** *(string) --* The virtual router that the route is associated with. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to create the route in. :type routeName: string :param routeName: **[REQUIRED]** The name to use for the route. :type spec: dict :param spec: **[REQUIRED]** The route specification to apply. - **httpRoute** *(dict) --* The HTTP routing information for the route. - **action** *(dict) --* **[REQUIRED]** The action to take if a match is determined. - **weightedTargets** *(list) --* **[REQUIRED]** The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* **[REQUIRED]** The virtual node to associate with the weighted target. - **weight** *(integer) --* **[REQUIRED]** The relative weight of the weighted target. - **match** *(dict) --* **[REQUIRED]** The criteria for determining an HTTP request match. - **prefix** *(string) --* **[REQUIRED]** Specifies the path to match requests with. This parameter must always start with ``/`` , which by itself matches all requests to the virtual service name. You can also match for path-based routing of requests. For example, if your virtual service name is ``my-service.local`` and you want the route to match requests to ``my-service.local/metrics`` , your prefix should be ``/metrics`` . - **tcpRoute** *(dict) --* The TCP routing information for the route. - **action** *(dict) --* **[REQUIRED]** The action to take if a match is determined. - **weightedTargets** *(list) --* **[REQUIRED]** The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* **[REQUIRED]** The virtual node to associate with the weighted target. - **weight** *(integer) --* **[REQUIRED]** The relative weight of the weighted target. :type tags: list :param tags: Optional metadata that you can apply to the route to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - *(dict) --* Optional metadata that you apply to a resource to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - **key** *(string) --* **[REQUIRED]** One part of a key-value pair that make up a tag. A ``key`` is a general label that acts like a category for more specific tag values. - **value** *(string) --* The optional part of a key-value pair that make up a tag. A ``value`` acts as a descriptor within a tag category (key). :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router in which to create the route. :rtype: dict :returns: """ pass def create_virtual_node(self, meshName: str, spec: Dict, virtualNodeName: str, clientToken: str = None, tags: List = None) -> Dict: """ Creates a virtual node within a service mesh. A virtual node acts as a logical pointer to a particular task group, such as an Amazon ECS service or a Kubernetes deployment. When you create a virtual node, you must specify the DNS service discovery hostname for your task group. Any inbound traffic that your virtual node expects should be specified as a ``listener`` . Any outbound traffic that your virtual node expects to reach should be specified as a ``backend`` . The response metadata for your new virtual node contains the ``arn`` that is associated with the virtual node. Set this value (either the full ARN or the truncated resource name: for example, ``mesh/default/virtualNode/simpleapp`` ) as the ``APPMESH_VIRTUAL_NODE_NAME`` environment variable for your task group's Envoy proxy container in your task definition or pod spec. This is then mapped to the ``node.id`` and ``node.cluster`` Envoy parameters. .. note:: If you require your Envoy stats or tracing to use a different name, you can override the ``node.cluster`` value that is set by ``APPMESH_VIRTUAL_NODE_NAME`` with the ``APPMESH_VIRTUAL_NODE_CLUSTER`` environment variable. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/CreateVirtualNode>`_ **Request Syntax** :: response = client.create_virtual_node( clientToken='string', meshName='string', spec={ 'backends': [ { 'virtualService': { 'virtualServiceName': 'string' } }, ], 'listeners': [ { 'healthCheck': { 'healthyThreshold': 123, 'intervalMillis': 123, 'path': 'string', 'port': 123, 'protocol': 'http'|'tcp', 'timeoutMillis': 123, 'unhealthyThreshold': 123 }, 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ], 'logging': { 'accessLog': { 'file': { 'path': 'string' } } }, 'serviceDiscovery': { 'dns': { 'hostname': 'string' } } }, tags=[ { 'key': 'string', 'value': 'string' }, ], virtualNodeName='string' ) **Response Syntax** :: { 'virtualNode': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'backends': [ { 'virtualService': { 'virtualServiceName': 'string' } }, ], 'listeners': [ { 'healthCheck': { 'healthyThreshold': 123, 'intervalMillis': 123, 'path': 'string', 'port': 123, 'protocol': 'http'|'tcp', 'timeoutMillis': 123, 'unhealthyThreshold': 123 }, 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ], 'logging': { 'accessLog': { 'file': { 'path': 'string' } } }, 'serviceDiscovery': { 'dns': { 'hostname': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualNodeName': 'string' } } **Response Structure** - *(dict) --* - **virtualNode** *(dict) --* The full description of your virtual node following the create call. - **meshName** *(string) --* The name of the service mesh that the virtual node resides in. - **metadata** *(dict) --* The associated metadata for the virtual node. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual node. - **backends** *(list) --* The backends that the virtual node is expected to send outbound traffic to. - *(dict) --* An object representing the backends that a virtual node is expected to send outbound traffic to. - **virtualService** *(dict) --* Specifies a virtual service to use as a backend for a virtual node. - **virtualServiceName** *(string) --* The name of the virtual service that is acting as a virtual node backend. - **listeners** *(list) --* The listeners that the virtual node is expected to receive inbound traffic from. Currently only one listener is supported per virtual node. - *(dict) --* An object representing a listener for a virtual node. - **healthCheck** *(dict) --* The health check information for the listener. - **healthyThreshold** *(integer) --* The number of consecutive successful health checks that must occur before declaring listener healthy. - **intervalMillis** *(integer) --* The time period in milliseconds between each health check execution. - **path** *(string) --* The destination path for the health check request. This is required only if the specified protocol is HTTP. If the protocol is TCP, this parameter is ignored. - **port** *(integer) --* The destination port for the health check request. This port must match the port defined in the PortMapping for the listener. - **protocol** *(string) --* The protocol for the health check request. - **timeoutMillis** *(integer) --* The amount of time to wait when receiving a response from the health check, in milliseconds. - **unhealthyThreshold** *(integer) --* The number of consecutive failed health checks that must occur before declaring a virtual node unhealthy. - **portMapping** *(dict) --* The port mapping information for the listener. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **logging** *(dict) --* The inbound and outbound access logging information for the virtual node. - **accessLog** *(dict) --* The access log configuration for a virtual node. - **file** *(dict) --* The file object to send virtual node access logs to. - **path** *(string) --* The file path to write access logs to. You can use ``/dev/stdout`` to send access logs to standard out and configure your Envoy container to use a log driver, such as ``awslogs`` , to export the access logs to a log storage service such as Amazon CloudWatch Logs. You can also specify a path in the Envoy container's file system to write the files to disk. .. note:: The Envoy process must have write permissions to the path that you specify here. Otherwise, Envoy fails to bootstrap properly. - **serviceDiscovery** *(dict) --* The service discovery information for the virtual node. If your virtual node does not expect ingress traffic, you can omit this parameter. - **dns** *(dict) --* Specifies the DNS information for the virtual node. - **hostname** *(string) --* Specifies the DNS service discovery hostname for the virtual node. - **status** *(dict) --* The current status for the virtual node. - **status** *(string) --* The current status of the virtual node. - **virtualNodeName** *(string) --* The name of the virtual node. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to create the virtual node in. :type spec: dict :param spec: **[REQUIRED]** The virtual node specification to apply. - **backends** *(list) --* The backends that the virtual node is expected to send outbound traffic to. - *(dict) --* An object representing the backends that a virtual node is expected to send outbound traffic to. - **virtualService** *(dict) --* Specifies a virtual service to use as a backend for a virtual node. - **virtualServiceName** *(string) --* **[REQUIRED]** The name of the virtual service that is acting as a virtual node backend. - **listeners** *(list) --* The listeners that the virtual node is expected to receive inbound traffic from. Currently only one listener is supported per virtual node. - *(dict) --* An object representing a listener for a virtual node. - **healthCheck** *(dict) --* The health check information for the listener. - **healthyThreshold** *(integer) --* **[REQUIRED]** The number of consecutive successful health checks that must occur before declaring listener healthy. - **intervalMillis** *(integer) --* **[REQUIRED]** The time period in milliseconds between each health check execution. - **path** *(string) --* The destination path for the health check request. This is required only if the specified protocol is HTTP. If the protocol is TCP, this parameter is ignored. - **port** *(integer) --* The destination port for the health check request. This port must match the port defined in the PortMapping for the listener. - **protocol** *(string) --* **[REQUIRED]** The protocol for the health check request. - **timeoutMillis** *(integer) --* **[REQUIRED]** The amount of time to wait when receiving a response from the health check, in milliseconds. - **unhealthyThreshold** *(integer) --* **[REQUIRED]** The number of consecutive failed health checks that must occur before declaring a virtual node unhealthy. - **portMapping** *(dict) --* **[REQUIRED]** The port mapping information for the listener. - **port** *(integer) --* **[REQUIRED]** The port used for the port mapping. - **protocol** *(string) --* **[REQUIRED]** The protocol used for the port mapping. - **logging** *(dict) --* The inbound and outbound access logging information for the virtual node. - **accessLog** *(dict) --* The access log configuration for a virtual node. - **file** *(dict) --* The file object to send virtual node access logs to. - **path** *(string) --* **[REQUIRED]** The file path to write access logs to. You can use ``/dev/stdout`` to send access logs to standard out and configure your Envoy container to use a log driver, such as ``awslogs`` , to export the access logs to a log storage service such as Amazon CloudWatch Logs. You can also specify a path in the Envoy container\'s file system to write the files to disk. .. note:: The Envoy process must have write permissions to the path that you specify here. Otherwise, Envoy fails to bootstrap properly. - **serviceDiscovery** *(dict) --* The service discovery information for the virtual node. If your virtual node does not expect ingress traffic, you can omit this parameter. - **dns** *(dict) --* Specifies the DNS information for the virtual node. - **hostname** *(string) --* **[REQUIRED]** Specifies the DNS service discovery hostname for the virtual node. :type tags: list :param tags: Optional metadata that you can apply to the virtual node to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - *(dict) --* Optional metadata that you apply to a resource to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - **key** *(string) --* **[REQUIRED]** One part of a key-value pair that make up a tag. A ``key`` is a general label that acts like a category for more specific tag values. - **value** *(string) --* The optional part of a key-value pair that make up a tag. A ``value`` acts as a descriptor within a tag category (key). :type virtualNodeName: string :param virtualNodeName: **[REQUIRED]** The name to use for the virtual node. :rtype: dict :returns: """ pass def create_virtual_router(self, meshName: str, spec: Dict, virtualRouterName: str, clientToken: str = None, tags: List = None) -> Dict: """ Creates a virtual router within a service mesh. Any inbound traffic that your virtual router expects should be specified as a ``listener`` . Virtual routers handle traffic for one or more virtual services within your mesh. After you create your virtual router, create and associate routes for your virtual router that direct incoming requests to different virtual nodes. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/CreateVirtualRouter>`_ **Request Syntax** :: response = client.create_virtual_router( clientToken='string', meshName='string', spec={ 'listeners': [ { 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ] }, tags=[ { 'key': 'string', 'value': 'string' }, ], virtualRouterName='string' ) **Response Syntax** :: { 'virtualRouter': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'listeners': [ { 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ] }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **virtualRouter** *(dict) --* The full description of your virtual router following the create call. - **meshName** *(string) --* The name of the service mesh that the virtual router resides in. - **metadata** *(dict) --* The associated metadata for the virtual router. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual router. - **listeners** *(list) --* The listeners that the virtual router is expected to receive inbound traffic from. Currently only one listener is supported per virtual router. - *(dict) --* An object representing a virtual router listener. - **portMapping** *(dict) --* An object representing a virtual node or virtual router listener port mapping. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **status** *(dict) --* The current status of the virtual router. - **status** *(string) --* The current status of the virtual router. - **virtualRouterName** *(string) --* The name of the virtual router. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to create the virtual router in. :type spec: dict :param spec: **[REQUIRED]** The virtual router specification to apply. - **listeners** *(list) --* **[REQUIRED]** The listeners that the virtual router is expected to receive inbound traffic from. Currently only one listener is supported per virtual router. - *(dict) --* An object representing a virtual router listener. - **portMapping** *(dict) --* **[REQUIRED]** An object representing a virtual node or virtual router listener port mapping. - **port** *(integer) --* **[REQUIRED]** The port used for the port mapping. - **protocol** *(string) --* **[REQUIRED]** The protocol used for the port mapping. :type tags: list :param tags: Optional metadata that you can apply to the virtual router to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - *(dict) --* Optional metadata that you apply to a resource to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - **key** *(string) --* **[REQUIRED]** One part of a key-value pair that make up a tag. A ``key`` is a general label that acts like a category for more specific tag values. - **value** *(string) --* The optional part of a key-value pair that make up a tag. A ``value`` acts as a descriptor within a tag category (key). :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name to use for the virtual router. :rtype: dict :returns: """ pass def create_virtual_service(self, meshName: str, spec: Dict, virtualServiceName: str, clientToken: str = None, tags: List = None) -> Dict: """ Creates a virtual service within a service mesh. A virtual service is an abstraction of a real service that is provided by a virtual node directly or indirectly by means of a virtual router. Dependent services call your virtual service by its ``virtualServiceName`` , and those requests are routed to the virtual node or virtual router that is specified as the provider for the virtual service. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/CreateVirtualService>`_ **Request Syntax** :: response = client.create_virtual_service( clientToken='string', meshName='string', spec={ 'provider': { 'virtualNode': { 'virtualNodeName': 'string' }, 'virtualRouter': { 'virtualRouterName': 'string' } } }, tags=[ { 'key': 'string', 'value': 'string' }, ], virtualServiceName='string' ) **Response Syntax** :: { 'virtualService': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'provider': { 'virtualNode': { 'virtualNodeName': 'string' }, 'virtualRouter': { 'virtualRouterName': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualServiceName': 'string' } } **Response Structure** - *(dict) --* - **virtualService** *(dict) --* The full description of your virtual service following the create call. - **meshName** *(string) --* The name of the service mesh that the virtual service resides in. - **metadata** *(dict) --* An object representing metadata for a resource. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual service. - **provider** *(dict) --* The App Mesh object that is acting as the provider for a virtual service. You can specify a single virtual node or virtual router. - **virtualNode** *(dict) --* The virtual node associated with a virtual service. - **virtualNodeName** *(string) --* The name of the virtual node that is acting as a service provider. - **virtualRouter** *(dict) --* The virtual router associated with a virtual service. - **virtualRouterName** *(string) --* The name of the virtual router that is acting as a service provider. - **status** *(dict) --* The current status of the virtual service. - **status** *(string) --* The current status of the virtual service. - **virtualServiceName** *(string) --* The name of the virtual service. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to create the virtual service in. :type spec: dict :param spec: **[REQUIRED]** The virtual service specification to apply. - **provider** *(dict) --* The App Mesh object that is acting as the provider for a virtual service. You can specify a single virtual node or virtual router. - **virtualNode** *(dict) --* The virtual node associated with a virtual service. - **virtualNodeName** *(string) --* **[REQUIRED]** The name of the virtual node that is acting as a service provider. - **virtualRouter** *(dict) --* The virtual router associated with a virtual service. - **virtualRouterName** *(string) --* **[REQUIRED]** The name of the virtual router that is acting as a service provider. :type tags: list :param tags: Optional metadata that you can apply to the virtual service to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - *(dict) --* Optional metadata that you apply to a resource to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - **key** *(string) --* **[REQUIRED]** One part of a key-value pair that make up a tag. A ``key`` is a general label that acts like a category for more specific tag values. - **value** *(string) --* The optional part of a key-value pair that make up a tag. A ``value`` acts as a descriptor within a tag category (key). :type virtualServiceName: string :param virtualServiceName: **[REQUIRED]** The name to use for the virtual service. :rtype: dict :returns: """ pass def delete_mesh(self, meshName: str) -> Dict: """ Deletes an existing service mesh. You must delete all resources (virtual services, routes, virtual routers, and virtual nodes) in the service mesh before you can delete the mesh itself. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DeleteMesh>`_ **Request Syntax** :: response = client.delete_mesh( meshName='string' ) **Response Syntax** :: { 'mesh': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'egressFilter': { 'type': 'ALLOW_ALL'|'DROP_ALL' } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' } } } **Response Structure** - *(dict) --* - **mesh** *(dict) --* The service mesh that was deleted. - **meshName** *(string) --* The name of the service mesh. - **metadata** *(dict) --* The associated metadata for the service mesh. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The associated specification for the service mesh. - **egressFilter** *(dict) --* The egress filter rules for the service mesh. - **type** *(string) --* The egress filter type. By default, the type is ``DROP_ALL`` , which allows egress only from virtual nodes to other defined resources in the service mesh (and any traffic to ``*.amazonaws.com`` for AWS API calls). You can set the egress filter type to ``ALLOW_ALL`` to allow egress to any endpoint inside or outside of the service mesh. - **status** *(dict) --* The status of the service mesh. - **status** *(string) --* The current mesh status. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to delete. :rtype: dict :returns: """ pass def delete_route(self, meshName: str, routeName: str, virtualRouterName: str) -> Dict: """ Deletes an existing route. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DeleteRoute>`_ **Request Syntax** :: response = client.delete_route( meshName='string', routeName='string', virtualRouterName='string' ) **Response Syntax** :: { 'route': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'routeName': 'string', 'spec': { 'httpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] }, 'match': { 'prefix': 'string' } }, 'tcpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **route** *(dict) --* The route that was deleted. - **meshName** *(string) --* The name of the service mesh that the route resides in. - **metadata** *(dict) --* The associated metadata for the route. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **routeName** *(string) --* The name of the route. - **spec** *(dict) --* The specifications of the route. - **httpRoute** *(dict) --* The HTTP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **match** *(dict) --* The criteria for determining an HTTP request match. - **prefix** *(string) --* Specifies the path to match requests with. This parameter must always start with ``/`` , which by itself matches all requests to the virtual service name. You can also match for path-based routing of requests. For example, if your virtual service name is ``my-service.local`` and you want the route to match requests to ``my-service.local/metrics`` , your prefix should be ``/metrics`` . - **tcpRoute** *(dict) --* The TCP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **status** *(dict) --* The status of the route. - **status** *(string) --* The current status for the route. - **virtualRouterName** *(string) --* The virtual router that the route is associated with. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to delete the route in. :type routeName: string :param routeName: **[REQUIRED]** The name of the route to delete. :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router to delete the route in. :rtype: dict :returns: """ pass def delete_virtual_node(self, meshName: str, virtualNodeName: str) -> Dict: """ Deletes an existing virtual node. You must delete any virtual services that list a virtual node as a service provider before you can delete the virtual node itself. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DeleteVirtualNode>`_ **Request Syntax** :: response = client.delete_virtual_node( meshName='string', virtualNodeName='string' ) **Response Syntax** :: { 'virtualNode': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'backends': [ { 'virtualService': { 'virtualServiceName': 'string' } }, ], 'listeners': [ { 'healthCheck': { 'healthyThreshold': 123, 'intervalMillis': 123, 'path': 'string', 'port': 123, 'protocol': 'http'|'tcp', 'timeoutMillis': 123, 'unhealthyThreshold': 123 }, 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ], 'logging': { 'accessLog': { 'file': { 'path': 'string' } } }, 'serviceDiscovery': { 'dns': { 'hostname': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualNodeName': 'string' } } **Response Structure** - *(dict) --* - **virtualNode** *(dict) --* The virtual node that was deleted. - **meshName** *(string) --* The name of the service mesh that the virtual node resides in. - **metadata** *(dict) --* The associated metadata for the virtual node. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual node. - **backends** *(list) --* The backends that the virtual node is expected to send outbound traffic to. - *(dict) --* An object representing the backends that a virtual node is expected to send outbound traffic to. - **virtualService** *(dict) --* Specifies a virtual service to use as a backend for a virtual node. - **virtualServiceName** *(string) --* The name of the virtual service that is acting as a virtual node backend. - **listeners** *(list) --* The listeners that the virtual node is expected to receive inbound traffic from. Currently only one listener is supported per virtual node. - *(dict) --* An object representing a listener for a virtual node. - **healthCheck** *(dict) --* The health check information for the listener. - **healthyThreshold** *(integer) --* The number of consecutive successful health checks that must occur before declaring listener healthy. - **intervalMillis** *(integer) --* The time period in milliseconds between each health check execution. - **path** *(string) --* The destination path for the health check request. This is required only if the specified protocol is HTTP. If the protocol is TCP, this parameter is ignored. - **port** *(integer) --* The destination port for the health check request. This port must match the port defined in the PortMapping for the listener. - **protocol** *(string) --* The protocol for the health check request. - **timeoutMillis** *(integer) --* The amount of time to wait when receiving a response from the health check, in milliseconds. - **unhealthyThreshold** *(integer) --* The number of consecutive failed health checks that must occur before declaring a virtual node unhealthy. - **portMapping** *(dict) --* The port mapping information for the listener. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **logging** *(dict) --* The inbound and outbound access logging information for the virtual node. - **accessLog** *(dict) --* The access log configuration for a virtual node. - **file** *(dict) --* The file object to send virtual node access logs to. - **path** *(string) --* The file path to write access logs to. You can use ``/dev/stdout`` to send access logs to standard out and configure your Envoy container to use a log driver, such as ``awslogs`` , to export the access logs to a log storage service such as Amazon CloudWatch Logs. You can also specify a path in the Envoy container's file system to write the files to disk. .. note:: The Envoy process must have write permissions to the path that you specify here. Otherwise, Envoy fails to bootstrap properly. - **serviceDiscovery** *(dict) --* The service discovery information for the virtual node. If your virtual node does not expect ingress traffic, you can omit this parameter. - **dns** *(dict) --* Specifies the DNS information for the virtual node. - **hostname** *(string) --* Specifies the DNS service discovery hostname for the virtual node. - **status** *(dict) --* The current status for the virtual node. - **status** *(string) --* The current status of the virtual node. - **virtualNodeName** *(string) --* The name of the virtual node. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to delete the virtual node in. :type virtualNodeName: string :param virtualNodeName: **[REQUIRED]** The name of the virtual node to delete. :rtype: dict :returns: """ pass def delete_virtual_router(self, meshName: str, virtualRouterName: str) -> Dict: """ Deletes an existing virtual router. You must delete any routes associated with the virtual router before you can delete the router itself. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DeleteVirtualRouter>`_ **Request Syntax** :: response = client.delete_virtual_router( meshName='string', virtualRouterName='string' ) **Response Syntax** :: { 'virtualRouter': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'listeners': [ { 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ] }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **virtualRouter** *(dict) --* The virtual router that was deleted. - **meshName** *(string) --* The name of the service mesh that the virtual router resides in. - **metadata** *(dict) --* The associated metadata for the virtual router. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual router. - **listeners** *(list) --* The listeners that the virtual router is expected to receive inbound traffic from. Currently only one listener is supported per virtual router. - *(dict) --* An object representing a virtual router listener. - **portMapping** *(dict) --* An object representing a virtual node or virtual router listener port mapping. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **status** *(dict) --* The current status of the virtual router. - **status** *(string) --* The current status of the virtual router. - **virtualRouterName** *(string) --* The name of the virtual router. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to delete the virtual router in. :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router to delete. :rtype: dict :returns: """ pass def delete_virtual_service(self, meshName: str, virtualServiceName: str) -> Dict: """ Deletes an existing virtual service. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DeleteVirtualService>`_ **Request Syntax** :: response = client.delete_virtual_service( meshName='string', virtualServiceName='string' ) **Response Syntax** :: { 'virtualService': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'provider': { 'virtualNode': { 'virtualNodeName': 'string' }, 'virtualRouter': { 'virtualRouterName': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualServiceName': 'string' } } **Response Structure** - *(dict) --* - **virtualService** *(dict) --* The virtual service that was deleted. - **meshName** *(string) --* The name of the service mesh that the virtual service resides in. - **metadata** *(dict) --* An object representing metadata for a resource. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual service. - **provider** *(dict) --* The App Mesh object that is acting as the provider for a virtual service. You can specify a single virtual node or virtual router. - **virtualNode** *(dict) --* The virtual node associated with a virtual service. - **virtualNodeName** *(string) --* The name of the virtual node that is acting as a service provider. - **virtualRouter** *(dict) --* The virtual router associated with a virtual service. - **virtualRouterName** *(string) --* The name of the virtual router that is acting as a service provider. - **status** *(dict) --* The current status of the virtual service. - **status** *(string) --* The current status of the virtual service. - **virtualServiceName** *(string) --* The name of the virtual service. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to delete the virtual service in. :type virtualServiceName: string :param virtualServiceName: **[REQUIRED]** The name of the virtual service to delete. :rtype: dict :returns: """ pass def describe_mesh(self, meshName: str) -> Dict: """ Describes an existing service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DescribeMesh>`_ **Request Syntax** :: response = client.describe_mesh( meshName='string' ) **Response Syntax** :: { 'mesh': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'egressFilter': { 'type': 'ALLOW_ALL'|'DROP_ALL' } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' } } } **Response Structure** - *(dict) --* - **mesh** *(dict) --* The full description of your service mesh. - **meshName** *(string) --* The name of the service mesh. - **metadata** *(dict) --* The associated metadata for the service mesh. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The associated specification for the service mesh. - **egressFilter** *(dict) --* The egress filter rules for the service mesh. - **type** *(string) --* The egress filter type. By default, the type is ``DROP_ALL`` , which allows egress only from virtual nodes to other defined resources in the service mesh (and any traffic to ``*.amazonaws.com`` for AWS API calls). You can set the egress filter type to ``ALLOW_ALL`` to allow egress to any endpoint inside or outside of the service mesh. - **status** *(dict) --* The status of the service mesh. - **status** *(string) --* The current mesh status. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to describe. :rtype: dict :returns: """ pass def describe_route(self, meshName: str, routeName: str, virtualRouterName: str) -> Dict: """ Describes an existing route. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DescribeRoute>`_ **Request Syntax** :: response = client.describe_route( meshName='string', routeName='string', virtualRouterName='string' ) **Response Syntax** :: { 'route': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'routeName': 'string', 'spec': { 'httpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] }, 'match': { 'prefix': 'string' } }, 'tcpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **route** *(dict) --* The full description of your route. - **meshName** *(string) --* The name of the service mesh that the route resides in. - **metadata** *(dict) --* The associated metadata for the route. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **routeName** *(string) --* The name of the route. - **spec** *(dict) --* The specifications of the route. - **httpRoute** *(dict) --* The HTTP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **match** *(dict) --* The criteria for determining an HTTP request match. - **prefix** *(string) --* Specifies the path to match requests with. This parameter must always start with ``/`` , which by itself matches all requests to the virtual service name. You can also match for path-based routing of requests. For example, if your virtual service name is ``my-service.local`` and you want the route to match requests to ``my-service.local/metrics`` , your prefix should be ``/metrics`` . - **tcpRoute** *(dict) --* The TCP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **status** *(dict) --* The status of the route. - **status** *(string) --* The current status for the route. - **virtualRouterName** *(string) --* The virtual router that the route is associated with. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the route resides in. :type routeName: string :param routeName: **[REQUIRED]** The name of the route to describe. :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router that the route is associated with. :rtype: dict :returns: """ pass def describe_virtual_node(self, meshName: str, virtualNodeName: str) -> Dict: """ Describes an existing virtual node. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DescribeVirtualNode>`_ **Request Syntax** :: response = client.describe_virtual_node( meshName='string', virtualNodeName='string' ) **Response Syntax** :: { 'virtualNode': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'backends': [ { 'virtualService': { 'virtualServiceName': 'string' } }, ], 'listeners': [ { 'healthCheck': { 'healthyThreshold': 123, 'intervalMillis': 123, 'path': 'string', 'port': 123, 'protocol': 'http'|'tcp', 'timeoutMillis': 123, 'unhealthyThreshold': 123 }, 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ], 'logging': { 'accessLog': { 'file': { 'path': 'string' } } }, 'serviceDiscovery': { 'dns': { 'hostname': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualNodeName': 'string' } } **Response Structure** - *(dict) --* - **virtualNode** *(dict) --* The full description of your virtual node. - **meshName** *(string) --* The name of the service mesh that the virtual node resides in. - **metadata** *(dict) --* The associated metadata for the virtual node. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual node. - **backends** *(list) --* The backends that the virtual node is expected to send outbound traffic to. - *(dict) --* An object representing the backends that a virtual node is expected to send outbound traffic to. - **virtualService** *(dict) --* Specifies a virtual service to use as a backend for a virtual node. - **virtualServiceName** *(string) --* The name of the virtual service that is acting as a virtual node backend. - **listeners** *(list) --* The listeners that the virtual node is expected to receive inbound traffic from. Currently only one listener is supported per virtual node. - *(dict) --* An object representing a listener for a virtual node. - **healthCheck** *(dict) --* The health check information for the listener. - **healthyThreshold** *(integer) --* The number of consecutive successful health checks that must occur before declaring listener healthy. - **intervalMillis** *(integer) --* The time period in milliseconds between each health check execution. - **path** *(string) --* The destination path for the health check request. This is required only if the specified protocol is HTTP. If the protocol is TCP, this parameter is ignored. - **port** *(integer) --* The destination port for the health check request. This port must match the port defined in the PortMapping for the listener. - **protocol** *(string) --* The protocol for the health check request. - **timeoutMillis** *(integer) --* The amount of time to wait when receiving a response from the health check, in milliseconds. - **unhealthyThreshold** *(integer) --* The number of consecutive failed health checks that must occur before declaring a virtual node unhealthy. - **portMapping** *(dict) --* The port mapping information for the listener. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **logging** *(dict) --* The inbound and outbound access logging information for the virtual node. - **accessLog** *(dict) --* The access log configuration for a virtual node. - **file** *(dict) --* The file object to send virtual node access logs to. - **path** *(string) --* The file path to write access logs to. You can use ``/dev/stdout`` to send access logs to standard out and configure your Envoy container to use a log driver, such as ``awslogs`` , to export the access logs to a log storage service such as Amazon CloudWatch Logs. You can also specify a path in the Envoy container's file system to write the files to disk. .. note:: The Envoy process must have write permissions to the path that you specify here. Otherwise, Envoy fails to bootstrap properly. - **serviceDiscovery** *(dict) --* The service discovery information for the virtual node. If your virtual node does not expect ingress traffic, you can omit this parameter. - **dns** *(dict) --* Specifies the DNS information for the virtual node. - **hostname** *(string) --* Specifies the DNS service discovery hostname for the virtual node. - **status** *(dict) --* The current status for the virtual node. - **status** *(string) --* The current status of the virtual node. - **virtualNodeName** *(string) --* The name of the virtual node. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the virtual node resides in. :type virtualNodeName: string :param virtualNodeName: **[REQUIRED]** The name of the virtual node to describe. :rtype: dict :returns: """ pass def describe_virtual_router(self, meshName: str, virtualRouterName: str) -> Dict: """ Describes an existing virtual router. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DescribeVirtualRouter>`_ **Request Syntax** :: response = client.describe_virtual_router( meshName='string', virtualRouterName='string' ) **Response Syntax** :: { 'virtualRouter': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'listeners': [ { 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ] }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **virtualRouter** *(dict) --* The full description of your virtual router. - **meshName** *(string) --* The name of the service mesh that the virtual router resides in. - **metadata** *(dict) --* The associated metadata for the virtual router. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual router. - **listeners** *(list) --* The listeners that the virtual router is expected to receive inbound traffic from. Currently only one listener is supported per virtual router. - *(dict) --* An object representing a virtual router listener. - **portMapping** *(dict) --* An object representing a virtual node or virtual router listener port mapping. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **status** *(dict) --* The current status of the virtual router. - **status** *(string) --* The current status of the virtual router. - **virtualRouterName** *(string) --* The name of the virtual router. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the virtual router resides in. :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router to describe. :rtype: dict :returns: """ pass def describe_virtual_service(self, meshName: str, virtualServiceName: str) -> Dict: """ Describes an existing virtual service. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/DescribeVirtualService>`_ **Request Syntax** :: response = client.describe_virtual_service( meshName='string', virtualServiceName='string' ) **Response Syntax** :: { 'virtualService': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'provider': { 'virtualNode': { 'virtualNodeName': 'string' }, 'virtualRouter': { 'virtualRouterName': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualServiceName': 'string' } } **Response Structure** - *(dict) --* - **virtualService** *(dict) --* The full description of your virtual service. - **meshName** *(string) --* The name of the service mesh that the virtual service resides in. - **metadata** *(dict) --* An object representing metadata for a resource. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual service. - **provider** *(dict) --* The App Mesh object that is acting as the provider for a virtual service. You can specify a single virtual node or virtual router. - **virtualNode** *(dict) --* The virtual node associated with a virtual service. - **virtualNodeName** *(string) --* The name of the virtual node that is acting as a service provider. - **virtualRouter** *(dict) --* The virtual router associated with a virtual service. - **virtualRouterName** *(string) --* The name of the virtual router that is acting as a service provider. - **status** *(dict) --* The current status of the virtual service. - **status** *(string) --* The current status of the virtual service. - **virtualServiceName** *(string) --* The name of the virtual service. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the virtual service resides in. :type virtualServiceName: string :param virtualServiceName: **[REQUIRED]** The name of the virtual service to describe. :rtype: dict :returns: """ pass def generate_presigned_url(self, ClientMethod: str = None, Params: Dict = None, ExpiresIn: int = None, HttpMethod: str = None): """ Generate a presigned url given a client, its method, and arguments :type ClientMethod: string :param ClientMethod: The client method to presign for :type Params: dict :param Params: The parameters normally passed to ``ClientMethod``. :type ExpiresIn: int :param ExpiresIn: The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds) :type HttpMethod: string :param HttpMethod: The http method to use on the generated url. By default, the http method is whatever is used in the method\'s model. :returns: The presigned url """ pass def get_paginator(self, operation_name: str = None) -> Paginator: """ Create a paginator for an operation. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :raise OperationNotPageableError: Raised if the operation is not pageable. You can use the ``client.can_paginate`` method to check if an operation is pageable. :rtype: L{botocore.paginate.Paginator} :return: A paginator object. """ pass def get_waiter(self, waiter_name: str = None) -> Waiter: """ Returns an object that can wait for some condition. :type waiter_name: str :param waiter_name: The name of the waiter to get. See the waiters section of the service docs for a list of available waiters. :returns: The specified waiter object. :rtype: botocore.waiter.Waiter """ pass def list_meshes(self, limit: int = None, nextToken: str = None) -> Dict: """ Returns a list of existing service meshes. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/ListMeshes>`_ **Request Syntax** :: response = client.list_meshes( limit=123, nextToken='string' ) **Response Syntax** :: { 'meshes': [ { 'arn': 'string', 'meshName': 'string' }, ], 'nextToken': 'string' } **Response Structure** - *(dict) --* - **meshes** *(list) --* The list of existing service meshes. - *(dict) --* An object representing a service mesh returned by a list operation. - **arn** *(string) --* The full Amazon Resource Name (ARN) of the service mesh. - **meshName** *(string) --* The name of the service mesh. - **nextToken** *(string) --* The ``nextToken`` value to include in a future ``ListMeshes`` request. When the results of a ``ListMeshes`` request exceed ``limit`` , you can use this value to retrieve the next page of results. This value is ``null`` when there are no more results to return. :type limit: integer :param limit: The maximum number of results returned by ``ListMeshes`` in paginated output. When you use this parameter, ``ListMeshes`` returns only ``limit`` results in a single page along with a ``nextToken`` response element. You can see the remaining results of the initial request by sending another ``ListMeshes`` request with the returned ``nextToken`` value. This value can be between 1 and 100. If you don\'t use this parameter, ``ListMeshes`` returns up to 100 results and a ``nextToken`` value if applicable. :type nextToken: string :param nextToken: The ``nextToken`` value returned from a previous paginated ``ListMeshes`` request where ``limit`` was used and the results exceeded the value of that parameter. Pagination continues from the end of the previous results that returned the ``nextToken`` value. .. note:: This token should be treated as an opaque identifier that is used only to retrieve the next items in a list and not for other programmatic purposes. :rtype: dict :returns: """ pass def list_routes(self, meshName: str, virtualRouterName: str, limit: int = None, nextToken: str = None) -> Dict: """ Returns a list of existing routes in a service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/ListRoutes>`_ **Request Syntax** :: response = client.list_routes( limit=123, meshName='string', nextToken='string', virtualRouterName='string' ) **Response Syntax** :: { 'nextToken': 'string', 'routes': [ { 'arn': 'string', 'meshName': 'string', 'routeName': 'string', 'virtualRouterName': 'string' }, ] } **Response Structure** - *(dict) --* - **nextToken** *(string) --* The ``nextToken`` value to include in a future ``ListRoutes`` request. When the results of a ``ListRoutes`` request exceed ``limit`` , you can use this value to retrieve the next page of results. This value is ``null`` when there are no more results to return. - **routes** *(list) --* The list of existing routes for the specified service mesh and virtual router. - *(dict) --* An object representing a route returned by a list operation. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the route. - **meshName** *(string) --* The name of the service mesh that the route resides in. - **routeName** *(string) --* The name of the route. - **virtualRouterName** *(string) --* The virtual router that the route is associated with. :type limit: integer :param limit: The maximum number of results returned by ``ListRoutes`` in paginated output. When you use this parameter, ``ListRoutes`` returns only ``limit`` results in a single page along with a ``nextToken`` response element. You can see the remaining results of the initial request by sending another ``ListRoutes`` request with the returned ``nextToken`` value. This value can be between 1 and 100. If you don\'t use this parameter, ``ListRoutes`` returns up to 100 results and a ``nextToken`` value if applicable. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to list routes in. :type nextToken: string :param nextToken: The ``nextToken`` value returned from a previous paginated ``ListRoutes`` request where ``limit`` was used and the results exceeded the value of that parameter. Pagination continues from the end of the previous results that returned the ``nextToken`` value. :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router to list routes in. :rtype: dict :returns: """ pass def list_tags_for_resource(self, resourceArn: str, limit: int = None, nextToken: str = None) -> Dict: """ List the tags for an App Mesh resource. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/ListTagsForResource>`_ **Request Syntax** :: response = client.list_tags_for_resource( limit=123, nextToken='string', resourceArn='string' ) **Response Syntax** :: { 'nextToken': 'string', 'tags': [ { 'key': 'string', 'value': 'string' }, ] } **Response Structure** - *(dict) --* - **nextToken** *(string) --* The ``nextToken`` value to include in a future ``ListTagsForResource`` request. When the results of a ``ListTagsForResource`` request exceed ``limit`` , you can use this value to retrieve the next page of results. This value is ``null`` when there are no more results to return. - **tags** *(list) --* The tags for the resource. - *(dict) --* Optional metadata that you apply to a resource to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - **key** *(string) --* One part of a key-value pair that make up a tag. A ``key`` is a general label that acts like a category for more specific tag values. - **value** *(string) --* The optional part of a key-value pair that make up a tag. A ``value`` acts as a descriptor within a tag category (key). :type limit: integer :param limit: The maximum number of tag results returned by ``ListTagsForResource`` in paginated output. When this parameter is used, ``ListTagsForResource`` returns only ``limit`` results in a single page along with a ``nextToken`` response element. You can see the remaining results of the initial request by sending another ``ListTagsForResource`` request with the returned ``nextToken`` value. This value can be between 1 and 100. If you don\'t use this parameter, ``ListTagsForResource`` returns up to 100 results and a ``nextToken`` value if applicable. :type nextToken: string :param nextToken: The ``nextToken`` value returned from a previous paginated ``ListTagsForResource`` request where ``limit`` was used and the results exceeded the value of that parameter. Pagination continues from the end of the previous results that returned the ``nextToken`` value. :type resourceArn: string :param resourceArn: **[REQUIRED]** The Amazon Resource Name (ARN) that identifies the resource to list the tags for. :rtype: dict :returns: """ pass def list_virtual_nodes(self, meshName: str, limit: int = None, nextToken: str = None) -> Dict: """ Returns a list of existing virtual nodes. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/ListVirtualNodes>`_ **Request Syntax** :: response = client.list_virtual_nodes( limit=123, meshName='string', nextToken='string' ) **Response Syntax** :: { 'nextToken': 'string', 'virtualNodes': [ { 'arn': 'string', 'meshName': 'string', 'virtualNodeName': 'string' }, ] } **Response Structure** - *(dict) --* - **nextToken** *(string) --* The ``nextToken`` value to include in a future ``ListVirtualNodes`` request. When the results of a ``ListVirtualNodes`` request exceed ``limit`` , you can use this value to retrieve the next page of results. This value is ``null`` when there are no more results to return. - **virtualNodes** *(list) --* The list of existing virtual nodes for the specified service mesh. - *(dict) --* An object representing a virtual node returned by a list operation. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the virtual node. - **meshName** *(string) --* The name of the service mesh that the virtual node resides in. - **virtualNodeName** *(string) --* The name of the virtual node. :type limit: integer :param limit: The maximum number of results returned by ``ListVirtualNodes`` in paginated output. When you use this parameter, ``ListVirtualNodes`` returns only ``limit`` results in a single page along with a ``nextToken`` response element. You can see the remaining results of the initial request by sending another ``ListVirtualNodes`` request with the returned ``nextToken`` value. This value can be between 1 and 100. If you don\'t use this parameter, ``ListVirtualNodes`` returns up to 100 results and a ``nextToken`` value if applicable. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to list virtual nodes in. :type nextToken: string :param nextToken: The ``nextToken`` value returned from a previous paginated ``ListVirtualNodes`` request where ``limit`` was used and the results exceeded the value of that parameter. Pagination continues from the end of the previous results that returned the ``nextToken`` value. :rtype: dict :returns: """ pass def list_virtual_routers(self, meshName: str, limit: int = None, nextToken: str = None) -> Dict: """ Returns a list of existing virtual routers in a service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/ListVirtualRouters>`_ **Request Syntax** :: response = client.list_virtual_routers( limit=123, meshName='string', nextToken='string' ) **Response Syntax** :: { 'nextToken': 'string', 'virtualRouters': [ { 'arn': 'string', 'meshName': 'string', 'virtualRouterName': 'string' }, ] } **Response Structure** - *(dict) --* - **nextToken** *(string) --* The ``nextToken`` value to include in a future ``ListVirtualRouters`` request. When the results of a ``ListVirtualRouters`` request exceed ``limit`` , you can use this value to retrieve the next page of results. This value is ``null`` when there are no more results to return. - **virtualRouters** *(list) --* The list of existing virtual routers for the specified service mesh. - *(dict) --* An object representing a virtual router returned by a list operation. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the virtual router. - **meshName** *(string) --* The name of the service mesh that the virtual router resides in. - **virtualRouterName** *(string) --* The name of the virtual router. :type limit: integer :param limit: The maximum number of results returned by ``ListVirtualRouters`` in paginated output. When you use this parameter, ``ListVirtualRouters`` returns only ``limit`` results in a single page along with a ``nextToken`` response element. You can see the remaining results of the initial request by sending another ``ListVirtualRouters`` request with the returned ``nextToken`` value. This value can be between 1 and 100. If you don\'t use this parameter, ``ListVirtualRouters`` returns up to 100 results and a ``nextToken`` value if applicable. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to list virtual routers in. :type nextToken: string :param nextToken: The ``nextToken`` value returned from a previous paginated ``ListVirtualRouters`` request where ``limit`` was used and the results exceeded the value of that parameter. Pagination continues from the end of the previous results that returned the ``nextToken`` value. :rtype: dict :returns: """ pass def list_virtual_services(self, meshName: str, limit: int = None, nextToken: str = None) -> Dict: """ Returns a list of existing virtual services in a service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/ListVirtualServices>`_ **Request Syntax** :: response = client.list_virtual_services( limit=123, meshName='string', nextToken='string' ) **Response Syntax** :: { 'nextToken': 'string', 'virtualServices': [ { 'arn': 'string', 'meshName': 'string', 'virtualServiceName': 'string' }, ] } **Response Structure** - *(dict) --* - **nextToken** *(string) --* The ``nextToken`` value to include in a future ``ListVirtualServices`` request. When the results of a ``ListVirtualServices`` request exceed ``limit`` , you can use this value to retrieve the next page of results. This value is ``null`` when there are no more results to return. - **virtualServices** *(list) --* The list of existing virtual services for the specified service mesh. - *(dict) --* An object representing a virtual service returned by a list operation. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the virtual service. - **meshName** *(string) --* The name of the service mesh that the virtual service resides in. - **virtualServiceName** *(string) --* The name of the virtual service. :type limit: integer :param limit: The maximum number of results returned by ``ListVirtualServices`` in paginated output. When you use this parameter, ``ListVirtualServices`` returns only ``limit`` results in a single page along with a ``nextToken`` response element. You can see the remaining results of the initial request by sending another ``ListVirtualServices`` request with the returned ``nextToken`` value. This value can be between 1 and 100. If you don\'t use this parameter, ``ListVirtualServices`` returns up to 100 results and a ``nextToken`` value if applicable. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to list virtual services in. :type nextToken: string :param nextToken: The ``nextToken`` value returned from a previous paginated ``ListVirtualServices`` request where ``limit`` was used and the results exceeded the value of that parameter. Pagination continues from the end of the previous results that returned the ``nextToken`` value. :rtype: dict :returns: """ pass def tag_resource(self, resourceArn: str, tags: List) -> Dict: """ Associates the specified tags to a resource with the specified ``resourceArn`` . If existing tags on a resource aren't specified in the request parameters, they aren't changed. When a resource is deleted, the tags associated with that resource are also deleted. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/TagResource>`_ **Request Syntax** :: response = client.tag_resource( resourceArn='string', tags=[ { 'key': 'string', 'value': 'string' }, ] ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type resourceArn: string :param resourceArn: **[REQUIRED]** The Amazon Resource Name (ARN) of the resource to add tags to. :type tags: list :param tags: **[REQUIRED]** The tags to add to the resource. A tag is an array of key-value pairs. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - *(dict) --* Optional metadata that you apply to a resource to assist with categorization and organization. Each tag consists of a key and an optional value, both of which you define. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters. - **key** *(string) --* **[REQUIRED]** One part of a key-value pair that make up a tag. A ``key`` is a general label that acts like a category for more specific tag values. - **value** *(string) --* The optional part of a key-value pair that make up a tag. A ``value`` acts as a descriptor within a tag category (key). :rtype: dict :returns: """ pass def untag_resource(self, resourceArn: str, tagKeys: List) -> Dict: """ Deletes specified tags from a resource. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/UntagResource>`_ **Request Syntax** :: response = client.untag_resource( resourceArn='string', tagKeys=[ 'string', ] ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type resourceArn: string :param resourceArn: **[REQUIRED]** The Amazon Resource Name (ARN) of the resource to delete tags from. :type tagKeys: list :param tagKeys: **[REQUIRED]** The keys of the tags to be removed. - *(string) --* :rtype: dict :returns: """ pass def update_mesh(self, meshName: str, clientToken: str = None, spec: Dict = None) -> Dict: """ Updates an existing service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/UpdateMesh>`_ **Request Syntax** :: response = client.update_mesh( clientToken='string', meshName='string', spec={ 'egressFilter': { 'type': 'ALLOW_ALL'|'DROP_ALL' } } ) **Response Syntax** :: { 'mesh': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'egressFilter': { 'type': 'ALLOW_ALL'|'DROP_ALL' } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' } } } **Response Structure** - *(dict) --* - **mesh** *(dict) --* An object representing a service mesh returned by a describe operation. - **meshName** *(string) --* The name of the service mesh. - **metadata** *(dict) --* The associated metadata for the service mesh. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The associated specification for the service mesh. - **egressFilter** *(dict) --* The egress filter rules for the service mesh. - **type** *(string) --* The egress filter type. By default, the type is ``DROP_ALL`` , which allows egress only from virtual nodes to other defined resources in the service mesh (and any traffic to ``*.amazonaws.com`` for AWS API calls). You can set the egress filter type to ``ALLOW_ALL`` to allow egress to any endpoint inside or outside of the service mesh. - **status** *(dict) --* The status of the service mesh. - **status** *(string) --* The current mesh status. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh to update. :type spec: dict :param spec: The service mesh specification to apply. - **egressFilter** *(dict) --* The egress filter rules for the service mesh. - **type** *(string) --* **[REQUIRED]** The egress filter type. By default, the type is ``DROP_ALL`` , which allows egress only from virtual nodes to other defined resources in the service mesh (and any traffic to ``*.amazonaws.com`` for AWS API calls). You can set the egress filter type to ``ALLOW_ALL`` to allow egress to any endpoint inside or outside of the service mesh. :rtype: dict :returns: """ pass def update_route(self, meshName: str, routeName: str, spec: Dict, virtualRouterName: str, clientToken: str = None) -> Dict: """ Updates an existing route for a specified service mesh and virtual router. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/UpdateRoute>`_ **Request Syntax** :: response = client.update_route( clientToken='string', meshName='string', routeName='string', spec={ 'httpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] }, 'match': { 'prefix': 'string' } }, 'tcpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] } } }, virtualRouterName='string' ) **Response Syntax** :: { 'route': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'routeName': 'string', 'spec': { 'httpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] }, 'match': { 'prefix': 'string' } }, 'tcpRoute': { 'action': { 'weightedTargets': [ { 'virtualNode': 'string', 'weight': 123 }, ] } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **route** *(dict) --* A full description of the route that was updated. - **meshName** *(string) --* The name of the service mesh that the route resides in. - **metadata** *(dict) --* The associated metadata for the route. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **routeName** *(string) --* The name of the route. - **spec** *(dict) --* The specifications of the route. - **httpRoute** *(dict) --* The HTTP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **match** *(dict) --* The criteria for determining an HTTP request match. - **prefix** *(string) --* Specifies the path to match requests with. This parameter must always start with ``/`` , which by itself matches all requests to the virtual service name. You can also match for path-based routing of requests. For example, if your virtual service name is ``my-service.local`` and you want the route to match requests to ``my-service.local/metrics`` , your prefix should be ``/metrics`` . - **tcpRoute** *(dict) --* The TCP routing information for the route. - **action** *(dict) --* The action to take if a match is determined. - **weightedTargets** *(list) --* The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* The virtual node to associate with the weighted target. - **weight** *(integer) --* The relative weight of the weighted target. - **status** *(dict) --* The status of the route. - **status** *(string) --* The current status for the route. - **virtualRouterName** *(string) --* The virtual router that the route is associated with. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the route resides in. :type routeName: string :param routeName: **[REQUIRED]** The name of the route to update. :type spec: dict :param spec: **[REQUIRED]** The new route specification to apply. This overwrites the existing data. - **httpRoute** *(dict) --* The HTTP routing information for the route. - **action** *(dict) --* **[REQUIRED]** The action to take if a match is determined. - **weightedTargets** *(list) --* **[REQUIRED]** The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* **[REQUIRED]** The virtual node to associate with the weighted target. - **weight** *(integer) --* **[REQUIRED]** The relative weight of the weighted target. - **match** *(dict) --* **[REQUIRED]** The criteria for determining an HTTP request match. - **prefix** *(string) --* **[REQUIRED]** Specifies the path to match requests with. This parameter must always start with ``/`` , which by itself matches all requests to the virtual service name. You can also match for path-based routing of requests. For example, if your virtual service name is ``my-service.local`` and you want the route to match requests to ``my-service.local/metrics`` , your prefix should be ``/metrics`` . - **tcpRoute** *(dict) --* The TCP routing information for the route. - **action** *(dict) --* **[REQUIRED]** The action to take if a match is determined. - **weightedTargets** *(list) --* **[REQUIRED]** The targets that traffic is routed to when a request matches the route. You can specify one or more targets and their relative weights to distribute traffic with. - *(dict) --* An object representing a target and its relative weight. Traffic is distributed across targets according to their relative weight. For example, a weighted target with a relative weight of 50 receives five times as much traffic as one with a relative weight of 10. - **virtualNode** *(string) --* **[REQUIRED]** The virtual node to associate with the weighted target. - **weight** *(integer) --* **[REQUIRED]** The relative weight of the weighted target. :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router that the route is associated with. :rtype: dict :returns: """ pass def update_virtual_node(self, meshName: str, spec: Dict, virtualNodeName: str, clientToken: str = None) -> Dict: """ Updates an existing virtual node in a specified service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/UpdateVirtualNode>`_ **Request Syntax** :: response = client.update_virtual_node( clientToken='string', meshName='string', spec={ 'backends': [ { 'virtualService': { 'virtualServiceName': 'string' } }, ], 'listeners': [ { 'healthCheck': { 'healthyThreshold': 123, 'intervalMillis': 123, 'path': 'string', 'port': 123, 'protocol': 'http'|'tcp', 'timeoutMillis': 123, 'unhealthyThreshold': 123 }, 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ], 'logging': { 'accessLog': { 'file': { 'path': 'string' } } }, 'serviceDiscovery': { 'dns': { 'hostname': 'string' } } }, virtualNodeName='string' ) **Response Syntax** :: { 'virtualNode': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'backends': [ { 'virtualService': { 'virtualServiceName': 'string' } }, ], 'listeners': [ { 'healthCheck': { 'healthyThreshold': 123, 'intervalMillis': 123, 'path': 'string', 'port': 123, 'protocol': 'http'|'tcp', 'timeoutMillis': 123, 'unhealthyThreshold': 123 }, 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ], 'logging': { 'accessLog': { 'file': { 'path': 'string' } } }, 'serviceDiscovery': { 'dns': { 'hostname': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualNodeName': 'string' } } **Response Structure** - *(dict) --* - **virtualNode** *(dict) --* A full description of the virtual node that was updated. - **meshName** *(string) --* The name of the service mesh that the virtual node resides in. - **metadata** *(dict) --* The associated metadata for the virtual node. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual node. - **backends** *(list) --* The backends that the virtual node is expected to send outbound traffic to. - *(dict) --* An object representing the backends that a virtual node is expected to send outbound traffic to. - **virtualService** *(dict) --* Specifies a virtual service to use as a backend for a virtual node. - **virtualServiceName** *(string) --* The name of the virtual service that is acting as a virtual node backend. - **listeners** *(list) --* The listeners that the virtual node is expected to receive inbound traffic from. Currently only one listener is supported per virtual node. - *(dict) --* An object representing a listener for a virtual node. - **healthCheck** *(dict) --* The health check information for the listener. - **healthyThreshold** *(integer) --* The number of consecutive successful health checks that must occur before declaring listener healthy. - **intervalMillis** *(integer) --* The time period in milliseconds between each health check execution. - **path** *(string) --* The destination path for the health check request. This is required only if the specified protocol is HTTP. If the protocol is TCP, this parameter is ignored. - **port** *(integer) --* The destination port for the health check request. This port must match the port defined in the PortMapping for the listener. - **protocol** *(string) --* The protocol for the health check request. - **timeoutMillis** *(integer) --* The amount of time to wait when receiving a response from the health check, in milliseconds. - **unhealthyThreshold** *(integer) --* The number of consecutive failed health checks that must occur before declaring a virtual node unhealthy. - **portMapping** *(dict) --* The port mapping information for the listener. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **logging** *(dict) --* The inbound and outbound access logging information for the virtual node. - **accessLog** *(dict) --* The access log configuration for a virtual node. - **file** *(dict) --* The file object to send virtual node access logs to. - **path** *(string) --* The file path to write access logs to. You can use ``/dev/stdout`` to send access logs to standard out and configure your Envoy container to use a log driver, such as ``awslogs`` , to export the access logs to a log storage service such as Amazon CloudWatch Logs. You can also specify a path in the Envoy container's file system to write the files to disk. .. note:: The Envoy process must have write permissions to the path that you specify here. Otherwise, Envoy fails to bootstrap properly. - **serviceDiscovery** *(dict) --* The service discovery information for the virtual node. If your virtual node does not expect ingress traffic, you can omit this parameter. - **dns** *(dict) --* Specifies the DNS information for the virtual node. - **hostname** *(string) --* Specifies the DNS service discovery hostname for the virtual node. - **status** *(dict) --* The current status for the virtual node. - **status** *(string) --* The current status of the virtual node. - **virtualNodeName** *(string) --* The name of the virtual node. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the virtual node resides in. :type spec: dict :param spec: **[REQUIRED]** The new virtual node specification to apply. This overwrites the existing data. - **backends** *(list) --* The backends that the virtual node is expected to send outbound traffic to. - *(dict) --* An object representing the backends that a virtual node is expected to send outbound traffic to. - **virtualService** *(dict) --* Specifies a virtual service to use as a backend for a virtual node. - **virtualServiceName** *(string) --* **[REQUIRED]** The name of the virtual service that is acting as a virtual node backend. - **listeners** *(list) --* The listeners that the virtual node is expected to receive inbound traffic from. Currently only one listener is supported per virtual node. - *(dict) --* An object representing a listener for a virtual node. - **healthCheck** *(dict) --* The health check information for the listener. - **healthyThreshold** *(integer) --* **[REQUIRED]** The number of consecutive successful health checks that must occur before declaring listener healthy. - **intervalMillis** *(integer) --* **[REQUIRED]** The time period in milliseconds between each health check execution. - **path** *(string) --* The destination path for the health check request. This is required only if the specified protocol is HTTP. If the protocol is TCP, this parameter is ignored. - **port** *(integer) --* The destination port for the health check request. This port must match the port defined in the PortMapping for the listener. - **protocol** *(string) --* **[REQUIRED]** The protocol for the health check request. - **timeoutMillis** *(integer) --* **[REQUIRED]** The amount of time to wait when receiving a response from the health check, in milliseconds. - **unhealthyThreshold** *(integer) --* **[REQUIRED]** The number of consecutive failed health checks that must occur before declaring a virtual node unhealthy. - **portMapping** *(dict) --* **[REQUIRED]** The port mapping information for the listener. - **port** *(integer) --* **[REQUIRED]** The port used for the port mapping. - **protocol** *(string) --* **[REQUIRED]** The protocol used for the port mapping. - **logging** *(dict) --* The inbound and outbound access logging information for the virtual node. - **accessLog** *(dict) --* The access log configuration for a virtual node. - **file** *(dict) --* The file object to send virtual node access logs to. - **path** *(string) --* **[REQUIRED]** The file path to write access logs to. You can use ``/dev/stdout`` to send access logs to standard out and configure your Envoy container to use a log driver, such as ``awslogs`` , to export the access logs to a log storage service such as Amazon CloudWatch Logs. You can also specify a path in the Envoy container\'s file system to write the files to disk. .. note:: The Envoy process must have write permissions to the path that you specify here. Otherwise, Envoy fails to bootstrap properly. - **serviceDiscovery** *(dict) --* The service discovery information for the virtual node. If your virtual node does not expect ingress traffic, you can omit this parameter. - **dns** *(dict) --* Specifies the DNS information for the virtual node. - **hostname** *(string) --* **[REQUIRED]** Specifies the DNS service discovery hostname for the virtual node. :type virtualNodeName: string :param virtualNodeName: **[REQUIRED]** The name of the virtual node to update. :rtype: dict :returns: """ pass def update_virtual_router(self, meshName: str, spec: Dict, virtualRouterName: str, clientToken: str = None) -> Dict: """ Updates an existing virtual router in a specified service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/UpdateVirtualRouter>`_ **Request Syntax** :: response = client.update_virtual_router( clientToken='string', meshName='string', spec={ 'listeners': [ { 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ] }, virtualRouterName='string' ) **Response Syntax** :: { 'virtualRouter': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'listeners': [ { 'portMapping': { 'port': 123, 'protocol': 'http'|'tcp' } }, ] }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualRouterName': 'string' } } **Response Structure** - *(dict) --* - **virtualRouter** *(dict) --* A full description of the virtual router that was updated. - **meshName** *(string) --* The name of the service mesh that the virtual router resides in. - **metadata** *(dict) --* The associated metadata for the virtual router. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual router. - **listeners** *(list) --* The listeners that the virtual router is expected to receive inbound traffic from. Currently only one listener is supported per virtual router. - *(dict) --* An object representing a virtual router listener. - **portMapping** *(dict) --* An object representing a virtual node or virtual router listener port mapping. - **port** *(integer) --* The port used for the port mapping. - **protocol** *(string) --* The protocol used for the port mapping. - **status** *(dict) --* The current status of the virtual router. - **status** *(string) --* The current status of the virtual router. - **virtualRouterName** *(string) --* The name of the virtual router. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the virtual router resides in. :type spec: dict :param spec: **[REQUIRED]** The new virtual router specification to apply. This overwrites the existing data. - **listeners** *(list) --* **[REQUIRED]** The listeners that the virtual router is expected to receive inbound traffic from. Currently only one listener is supported per virtual router. - *(dict) --* An object representing a virtual router listener. - **portMapping** *(dict) --* **[REQUIRED]** An object representing a virtual node or virtual router listener port mapping. - **port** *(integer) --* **[REQUIRED]** The port used for the port mapping. - **protocol** *(string) --* **[REQUIRED]** The protocol used for the port mapping. :type virtualRouterName: string :param virtualRouterName: **[REQUIRED]** The name of the virtual router to update. :rtype: dict :returns: """ pass def update_virtual_service(self, meshName: str, spec: Dict, virtualServiceName: str, clientToken: str = None) -> Dict: """ Updates an existing virtual service in a specified service mesh. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/appmesh-2019-01-25/UpdateVirtualService>`_ **Request Syntax** :: response = client.update_virtual_service( clientToken='string', meshName='string', spec={ 'provider': { 'virtualNode': { 'virtualNodeName': 'string' }, 'virtualRouter': { 'virtualRouterName': 'string' } } }, virtualServiceName='string' ) **Response Syntax** :: { 'virtualService': { 'meshName': 'string', 'metadata': { 'arn': 'string', 'createdAt': datetime(2015, 1, 1), 'lastUpdatedAt': datetime(2015, 1, 1), 'uid': 'string', 'version': 123 }, 'spec': { 'provider': { 'virtualNode': { 'virtualNodeName': 'string' }, 'virtualRouter': { 'virtualRouterName': 'string' } } }, 'status': { 'status': 'ACTIVE'|'DELETED'|'INACTIVE' }, 'virtualServiceName': 'string' } } **Response Structure** - *(dict) --* - **virtualService** *(dict) --* A full description of the virtual service that was updated. - **meshName** *(string) --* The name of the service mesh that the virtual service resides in. - **metadata** *(dict) --* An object representing metadata for a resource. - **arn** *(string) --* The full Amazon Resource Name (ARN) for the resource. - **createdAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was created. - **lastUpdatedAt** *(datetime) --* The Unix epoch timestamp in seconds for when the resource was last updated. - **uid** *(string) --* The unique identifier for the resource. - **version** *(integer) --* The version of the resource. Resources are created at version 1, and this version is incremented each time that they're updated. - **spec** *(dict) --* The specifications of the virtual service. - **provider** *(dict) --* The App Mesh object that is acting as the provider for a virtual service. You can specify a single virtual node or virtual router. - **virtualNode** *(dict) --* The virtual node associated with a virtual service. - **virtualNodeName** *(string) --* The name of the virtual node that is acting as a service provider. - **virtualRouter** *(dict) --* The virtual router associated with a virtual service. - **virtualRouterName** *(string) --* The name of the virtual router that is acting as a service provider. - **status** *(dict) --* The current status of the virtual service. - **status** *(string) --* The current status of the virtual service. - **virtualServiceName** *(string) --* The name of the virtual service. :type clientToken: string :param clientToken: Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 36 letters, numbers, hyphens, and underscores are allowed. This field is autopopulated if not provided. :type meshName: string :param meshName: **[REQUIRED]** The name of the service mesh that the virtual service resides in. :type spec: dict :param spec: **[REQUIRED]** The new virtual service specification to apply. This overwrites the existing data. - **provider** *(dict) --* The App Mesh object that is acting as the provider for a virtual service. You can specify a single virtual node or virtual router. - **virtualNode** *(dict) --* The virtual node associated with a virtual service. - **virtualNodeName** *(string) --* **[REQUIRED]** The name of the virtual node that is acting as a service provider. - **virtualRouter** *(dict) --* The virtual router associated with a virtual service. - **virtualRouterName** *(string) --* **[REQUIRED]** The name of the virtual router that is acting as a service provider. :type virtualServiceName: string :param virtualServiceName: **[REQUIRED]** The name of the virtual service to update. :rtype: dict :returns: """ pass

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1

0

1

0

10

5fb9a70d1227d97cfee21a0859c864326ebd39cf

1,164

py

Python

ChkUsrInputX.py

Epikarsios/MFC_Master

663a80446649eeee3dc29386b2a96cfef812d188

[ "MIT" ]

null

ChkUsrInputX.py

Epikarsios/MFC_Master

663a80446649eeee3dc29386b2a96cfef812d188

[ "MIT" ]

null

ChkUsrInputX.py

Epikarsios/MFC_Master

663a80446649eeee3dc29386b2a96cfef812d188

[ "MIT" ]

null

def chkUsrNumSetPoint(str_Cmd): allowed_Chars = set('0123456789.') if set(str_Cmd).issubset(allowed_Chars) and str_Cmd: numDecPoint = str_Cmd.count('.') if numDecPoint > 1: print('Too many decimal points.') return False else: if float(str_Cmd)> 0.0009 and float(str_Cmd)< 10 or float(str_Cmd)==0: print( 'Valid number') return True else: print( 'Out Of Range') else: print( 'Not a valid number') return False def chkUsrNumMole(str_Cmd): allowed_Chars = set('0123456789.') if set(str_Cmd).issubset(allowed_Chars) and str_Cmd: numDecPoint = str_Cmd.count('.') if numDecPoint > 1: print('Too many decimal points.') return False else: if float(str_Cmd)> 0.001 and float(str_Cmd)< 1000 or float(str_Cmd)==0: print( 'Valid number') return True else: print( 'Out Of Range') else: print( 'Not a valid number') return False

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395de470c994af57ab51c35a0e2ad5e25892ed5b

115

py

Python

soane/items/__init__.py

spheten/soane

b5517275b8b3fd3b2b5a19b031c98cfd45d42292

[ "BSD-3-Clause" ]

1

2021-10-03T07:13:55.000Z

soane/items/__init__.py

spheten/soane

b5517275b8b3fd3b2b5a19b031c98cfd45d42292

[ "BSD-3-Clause" ]

14

2021-10-03T07:10:10.000Z

2021-10-06T09:07:41.000Z

soane/items/__init__.py

spheten/soane

b5517275b8b3fd3b2b5a19b031c98cfd45d42292

[ "BSD-3-Clause" ]

null

''' Package definition for 'soane.items'. ''' from soane.items.book import Book from soane.items.note import Note

16.428571

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null

0

1

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1

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1

0

7

396eda635a05fced7862c22c71a8d525ab8c9b84

9,450

py

Python

pm/models/coach_mobility_standing.py

aosojnik/pipeline-manager-features-models

e5232f1c1b2073253a1c505dc9fff0d3d839dd6c

[ "MIT" ]

null

pm/models/coach_mobility_standing.py

aosojnik/pipeline-manager-features-models

e5232f1c1b2073253a1c505dc9fff0d3d839dd6c

[ "MIT" ]

null

pm/models/coach_mobility_standing.py

aosojnik/pipeline-manager-features-models

e5232f1c1b2073253a1c505dc9fff0d3d839dd6c

[ "MIT" ]

null

################################################################################## ##########--this is an autogenerated python model definition for proDEX--######### ##--original file: coach_mobility_standing_v04_forprodex.dxi --## ################################################################################## from .lib.proDEX import * coach_mobility_standing = Node() Relative_change = Node() situ_mobility_standing = Atrib() situ_mobility_standing_predicted = Atrib() coach_mobility_standing.setName('coach_mobility_standing') Relative_change.setName('Relative_change') situ_mobility_standing.setName('situ_mobility_standing') situ_mobility_standing_predicted.setName('situ_mobility_standing_predicted') coach_mobility_standing.setValues(['negative_message_to_PU_or_SU', 'positive_message_to_PU_or_SU', 'no_action']) Relative_change.setValues(['big_drop', 'medium_drop', 'small_drop', 'no_change', 'small_improvement', 'medium_improvement', 'big_improvement']) situ_mobility_standing.setValues(['very_low', 'low', 'medium', 'high', 'very_high']) situ_mobility_standing_predicted.setValues(['very_low', 'low', 'medium', 'high', 'very_high']) coach_mobility_standing.addChild(situ_mobility_standing) situ_mobility_standing.setParent(coach_mobility_standing) coach_mobility_standing.addChild(Relative_change) Relative_change.setParent(coach_mobility_standing) Relative_change.addChild(situ_mobility_standing) situ_mobility_standing.setParent(Relative_change) Relative_change.addChild(situ_mobility_standing_predicted) situ_mobility_standing_predicted.setParent(Relative_change) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_low', Relative_change:'big_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_low', Relative_change:'medium_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_low', Relative_change:'small_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_low', Relative_change:'no_change'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_low', Relative_change:'small_improvement'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_low', Relative_change:'medium_improvement'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_low', Relative_change:'big_improvement'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'low', Relative_change:'big_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'low', Relative_change:'medium_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'low', Relative_change:'small_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'low', Relative_change:'no_change'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'low', Relative_change:'small_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'low', Relative_change:'medium_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'low', Relative_change:'big_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'medium', Relative_change:'big_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'medium', Relative_change:'medium_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'medium', Relative_change:'small_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'medium', Relative_change:'no_change'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'medium', Relative_change:'small_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'medium', Relative_change:'medium_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'medium', Relative_change:'big_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'high', Relative_change:'big_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'high', Relative_change:'medium_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'high', Relative_change:'small_drop'}, 'negative_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'high', Relative_change:'no_change'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'high', Relative_change:'small_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'high', Relative_change:'medium_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'high', Relative_change:'big_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_high', Relative_change:'big_drop'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_high', Relative_change:'medium_drop'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_high', Relative_change:'small_drop'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_high', Relative_change:'no_change'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_high', Relative_change:'small_improvement'}, 'no_action']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_high', Relative_change:'medium_improvement'}, 'positive_message_to_PU_or_SU']) coach_mobility_standing.addFunctionRow([{situ_mobility_standing:'very_high', Relative_change:'big_improvement'}, 'positive_message_to_PU_or_SU']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_low', situ_mobility_standing_predicted:'very_low'}, 'no_change']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_low', situ_mobility_standing_predicted:'low'}, 'small_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_low', situ_mobility_standing_predicted:'medium'}, 'big_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_low', situ_mobility_standing_predicted:'high'}, 'big_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_low', situ_mobility_standing_predicted:'very_high'}, 'big_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'low', situ_mobility_standing_predicted:'very_low'}, 'small_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'low', situ_mobility_standing_predicted:'low'}, 'no_change']) Relative_change.addFunctionRow([{situ_mobility_standing:'low', situ_mobility_standing_predicted:'medium'}, 'small_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'low', situ_mobility_standing_predicted:'high'}, 'big_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'low', situ_mobility_standing_predicted:'very_high'}, 'big_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'medium', situ_mobility_standing_predicted:'very_low'}, 'big_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'medium', situ_mobility_standing_predicted:'low'}, 'small_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'medium', situ_mobility_standing_predicted:'medium'}, 'no_change']) Relative_change.addFunctionRow([{situ_mobility_standing:'medium', situ_mobility_standing_predicted:'high'}, 'small_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'medium', situ_mobility_standing_predicted:'very_high'}, 'big_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'high', situ_mobility_standing_predicted:'very_low'}, 'big_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'high', situ_mobility_standing_predicted:'low'}, 'big_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'high', situ_mobility_standing_predicted:'medium'}, 'small_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'high', situ_mobility_standing_predicted:'high'}, 'no_change']) Relative_change.addFunctionRow([{situ_mobility_standing:'high', situ_mobility_standing_predicted:'very_high'}, 'small_drop']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_high', situ_mobility_standing_predicted:'very_low'}, 'big_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_high', situ_mobility_standing_predicted:'low'}, 'big_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_high', situ_mobility_standing_predicted:'medium'}, 'small_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_high', situ_mobility_standing_predicted:'high'}, 'small_improvement']) Relative_change.addFunctionRow([{situ_mobility_standing:'very_high', situ_mobility_standing_predicted:'very_high'}, 'no_change'])

100.531915

148

0.83037

1,141

9,450

6.323401

0.042068

0.317117

0.274428

0.282744

0.903812

0.895218

0.86833

0.867775

0.838808

0.828274

0

0.000217

0.026561

9,450

93

149

101.612903

0.784107

0.013122

0

1

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0.251696

0.08503

0

1

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false

0

0.012346

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0.012346

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null

1

0

1

0

1

0

null

0

11

39ec6604cd7e9f6141d01e4dae04e56601492418

2,052

py

Python

visualization_tools/test_wrap2pi.py

rafaelbarretorb/trajectory_tracking_control

6203577568e5c7b128b36604ccc5e279069ad5e2

[ "MIT" ]

11

2020-05-22T04:44:16.000Z

2022-03-29T10:49:07.000Z

visualization_tools/test_wrap2pi.py

rafaelbarretorb/trajectory_tracking_control

6203577568e5c7b128b36604ccc5e279069ad5e2

[ "MIT" ]

15

2021-11-26T23:37:56.000Z

2021-11-28T20:48:07.000Z

visualization_tools/test_wrap2pi.py

rafaelbarretorb/trajectory_tracking_control

6203577568e5c7b128b36604ccc5e279069ad5e2

[ "MIT" ]

2

2021-08-16T01:16:36.000Z

2021-09-22T08:13:06.000Z

import unittest import numpy as np from linear_controller import wrapToPi, wrapToPi2 PI = np.pi class TestWrap2Pi(unittest.TestCase): def test1(self): self.assertAlmostEqual(wrapToPi( np.radians(360)), np.radians(0.0), places=2) # x axis positive self.assertAlmostEqual(wrapToPi( np.radians(-270)), np.radians(90.0), places=2) # y axis positive self.assertAlmostEqual(wrapToPi( np.radians(-540)), np.radians(-180.0), places=2) # x axis negative self.assertAlmostEqual(wrapToPi( np.radians(270)), np.radians(-90.0), places=2) # y axis negative self.assertAlmostEqual(wrapToPi( np.radians(-270-45)), np.radians(45), places=2) # 1st quadrant. self.assertAlmostEqual(wrapToPi( np.radians(-180-45)), np.radians(90+45), places=2) # 2nd quadrant. self.assertAlmostEqual(wrapToPi( np.radians(180+45)), np.radians(-180+45), places=2) # 3rd quadrant. self.assertAlmostEqual(wrapToPi( np.radians(270+45)), np.radians(-90+45), places=2) # 4th quadrant. def test2(self): self.assertAlmostEqual(wrapToPi2( np.radians(270)), np.radians(-90.0), places=2) self.assertAlmostEqual(wrapToPi2( np.radians(360)), np.radians(0.0), places=2) # x axis positive self.assertAlmostEqual(wrapToPi2( np.radians(-270)), np.radians(90.0), places=2) # y axis positive self.assertAlmostEqual(wrapToPi2( np.radians(-540)), np.radians(-180.0), places=2) # x axis negative self.assertAlmostEqual(wrapToPi2( np.radians(270)), np.radians(-90.0), places=2) # y axis negative self.assertAlmostEqual(wrapToPi2( np.radians(-270-45)), np.radians(45), places=2) # 1st quadrant. self.assertAlmostEqual(wrapToPi2( np.radians(-180-45)), np.radians(90+45), places=2) # 2nd quadrant. self.assertAlmostEqual(wrapToPi2( np.radians(180+45)), np.radians(-180+45), places=2) # 3rd quadrant. self.assertAlmostEqual(wrapToPi2( np.radians(270+45)), np.radians(-90+45), places=2) # 4th quadrant. if __name__ == '__main__': unittest.main()

58.628571

110

0.68616

280

2,052

4.996429

0.15

0.218728

0.051465

0.205861

0.888492

0.846319

0.834167

0.809864

0

0.093588

0.156433

2,052

34

111

60.352941

0.714616

0.116472

0

0.076923

0

0.004459

0

0.653846

1

0.076923

false

0

0.115385

0

0.230769

0

null

1

0

1

0

null

0

1

0

9

844e3ba99659d75528532b6e17bc37aa61216569

238

py

Python

python/__init__.py

dhohn/vbfcprw

6378b1ae9d968ec4049361b17f192daebb2a7577

[ "MIT" ]

null

python/__init__.py

dhohn/vbfcprw

6378b1ae9d968ec4049361b17f192daebb2a7577

[ "MIT" ]

null

python/__init__.py

dhohn/vbfcprw

6378b1ae9d968ec4049361b17f192daebb2a7577

[ "MIT" ]

null

# make class and functions available in this namespace #class from ROOT import OptObsEventStore #functions from ROOT.HLeptonsCPRW import getOptObs from ROOT.HLeptonsCPRW import getReweight from ROOT.HLeptonsCPRW import getWeightsDtilde

23.8

54

0.852941

29

238

7

0.551724

0.157635

0.295567

0.384236

0

0.121849

238

9

55

26.444444

0.971292

0.277311

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

7

ffd11cc41504c9d074e99f4f76f1758bbedaf92f

314

py

Python

word_embedding_loader/__init__.py

Emekaborisama/word_embedding_loader

5b0fd435360d335341dc111bbc52869bb2731422

[ "MIT" ]

4

2017-11-17T22:03:37.000Z

2018-06-26T08:50:27.000Z

word_embedding_loader/__init__.py

Emekaborisama/word_embedding_loader

5b0fd435360d335341dc111bbc52869bb2731422

[ "MIT" ]

7

2017-08-09T12:51:00.000Z

2018-06-29T19:12:11.000Z

word_embedding_loader/__init__.py

Emekaborisama/word_embedding_loader

5b0fd435360d335341dc111bbc52869bb2731422

[ "MIT" ]

2

2018-06-26T09:06:31.000Z

2020-06-13T16:05:05.000Z

# -*- coding: utf-8 -*- from __future__ import absolute_import, division, print_function, \ unicode_literals from word_embedding_loader._version import __version__ from word_embedding_loader.exceptions import ParseError, ParseWarning, parse_warn from word_embedding_loader.word_embedding import WordEmbedding

39.25

81

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38

314

6.421053

0.578947

0.213115

0.209016

0.282787

0

0.003546

0.101911

314

7

82

44.857143

0.861702

0.066879

0

1

0

true

0

0.8

0

0.8

0.2

0

null

1

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1

0

null

0

1

0

1

0

1

0

7

081a17d8af79628412cfb1bdc63d657e169bd27f

8,865

py

Python

Dockerized_Apps/taxii-client/src/taxii/easy_taxii_print.py

CanadianInstituteForCybersecurity/cic-exchange-model

1bb4f3ed51252cf152c2279cbeae75ca607b6fca

[ "MIT" ]

null

Dockerized_Apps/taxii-client/src/taxii/easy_taxii_print.py

CanadianInstituteForCybersecurity/cic-exchange-model

1bb4f3ed51252cf152c2279cbeae75ca607b6fca

[ "MIT" ]

null

Dockerized_Apps/taxii-client/src/taxii/easy_taxii_print.py

CanadianInstituteForCybersecurity/cic-exchange-model

1bb4f3ed51252cf152c2279cbeae75ca607b6fca

[ "MIT" ]

null

import pprint from taxii2client.v21 import Server, ApiRoot, Collection, as_pages def print_api_roots(path, username=None, user_password=None): """Prints all api roots in the server username and password requirements are dependent on the server""" if not username and user_password: server1 = Server(url=path) else: server1 = Server(url=path, user=username, password=user_password) print("Server Title: {}".format(server1.title)) print("Server Description: {}".format(server1.description)) print("Server Contact: {}".format(server1.contact)) print("Server Default API: {}\n".format(server1.default.url)) for api_root in server1.api_roots: print("API Title: " + api_root.title) print("API Description: {}".format(api_root.description)) print("API Versions: {}".format(api_root.versions)) print("API required length: {}".format(api_root.max_content_length)) print("API URL: {} \n".format(api_root.url)) def print_single_api_root(api_path, username=None, user_password=None): """Prints an api root in the server username and password requirements are dependent on the server""" if not username and user_password: api_root = ApiRoot(url=api_path) else: api_root = ApiRoot(url=api_path, user=username, password=user_password) print("API Title: " + api_root.title) print("API Description: {}".format(api_root.description)) print("API Versions: {}".format(api_root.versions)) print("API required length: {}".format(api_root.max_content_length)) print("API URL: {} \n".format(api_root.url)) def print_collections_per_api_root(path, username=None, user_password=None): """Prints all collections within all api roots in the server username and password requirements are dependent on the server""" if not username and user_password: server1 = Server(url=path) else: server1 = Server(url=path, user=username, password=user_password) for api_root in server1.api_roots: print("API Root: {}".format(api_root.title)) for collection in api_root.collections: print("\tTitle: " + collection.title) print("\tID: " + collection.id) print("\tDescription: {}".format(collection.description)) print("\tReadable: {}".format(collection.can_read)) print("\tWriteable: {}".format(collection.can_write)) print("\tMedia Types: {}".format(collection.media_types)) print("\tURL: {}".format(collection.url)) for key, values in collection.custom_properties.items(): print("\t{}: {}".format(key,values)) print("\n") def print_single_collection(collection_path, username=None, user_password=None): """Prints a collection within an api root in the server username and password requirements are dependent on the server""" if not username and user_password: collection = Collection(url=collection_path) else: collection = Collection(url=collection_path, user=username, password=user_password) print("\tTitle: " + collection.title) print("\tID: " + collection.id) print("\tDescription: {}".format(collection.description)) print("\tReadable: {}".format(collection.can_read)) print("\tWriteable: {}".format(collection.can_write)) print("\tMedia Types: {}".format(collection.media_types)) print("\tURL: {}\n".format(collection.url)) def print_bundles_per_collections_per_api_root(path, username=None, user_password=None): """Prints all bundles within each collection within each api roots in the server""" if not username and user_password: server1 = Server(url=path) else: server1 = Server(url=path, user=username, password=user_password) for api_root in server1.api_roots: print("API Root: {}".format(api_root.title)) for collection in api_root.collections: print("\tTitle: " + collection.title) print("\tID: " + collection.id) if collection.can_read: bundle = collection.get_objects() pprint.pprint(bundle) else: print("\tCannot access") def print_bundles_per_single_collection(collection_path, username=None, user_password=None): """Prints all bundles within a collection in the server username and password requirements are dependent on the server""" if not username and user_password: collection = Collection(url=collection_path) else: collection = Collection(url=collection_path, user=username, password=user_password) print("\tTitle: " + collection.title) print("\tID: " + collection.id) print("\tDescription: {}".format(collection.description)) print("\tReadable: {}".format(collection.can_read)) print("\tWriteable: {}".format(collection.can_write)) print("\tMedia Types: {}".format(collection.media_types)) print("\tURL: {}\n".format(collection.url)) if collection.can_read: bundle = collection.get_objects() pprint.pprint(bundle) else: print("\tCannot access") def print_single_object(collection_path, object_id, username=None, user_password=None): """Prints a single object in a collections username and password requirements are dependent on the server""" if not username and user_password: collection = Collection(url=collection_path) else: collection = Collection(url=collection_path, user=username, password=user_password) bundle = collection.get_object(object_id) print("\tTitle: " + collection.title) print("\tID: " + collection.id) print("\t===============Object=============") pprint.pprint(bundle) object_list = bundle["objects"] for obj in object_list: print(obj) def print_manifest_per_collections_per_api_root(path, username=None, user_password=None): """Prints all manifests within each collection within each api root in the server username and password requirements are dependent on the server""" if not username and user_password: server1 = Server(url=path) else: server1 = Server(url=path, user=username, password=user_password) for api_root in server1.api_roots: print("API Root: {}".format(api_root.title)) for collection in api_root.collections: print("\tTitle: " + collection.title) print("\tID: " + collection.id) if collection.can_read: try: manifest_resource = collection.get_manifest() pprint.pprint(manifest_resource) except: pass else: print("\tCannot access") def print_manifest_per_single_collection(collection_path, username=None, user_password=None): """Prints all manifests within a collection username and password requirements are dependent on the server""" if not username and user_password: collection = Collection(url=collection_path) else: collection = Collection(url=collection_path, user=username, password=user_password) print("\tTitle: " + collection.title) print("\tID: " + collection.id) print("\tDescription: {}".format(collection.description)) print("\tReadable: {}".format(collection.can_read)) print("\tWriteable: {}".format(collection.can_write)) print("\tMedia Types: {}".format(collection.media_types)) print("\tURL: {}\n".format(collection.url)) if collection.can_read: bundle = collection.get_manifest() pprint.pprint(bundle) else: print("\tCannot access") def copy_object_to_collection(from_collection_path, to_collection_path, object_id, from_username=None, from_user_password=None, to_username=None, to_user_password=None): """copies bundle from one collection to another collection username and password requirements are dependent on the server""" if not from_username and from_user_password: from_collection = Collection(url=from_collection_path) else: from_collection = Collection(url=from_collection_path, user=from_username, password=from_user_password) if not to_username and to_username: to_collection = Collection(url=to_collection_path) else: to_collection = Collection(url=to_collection_path, user=to_username, password=to_user_password) bundle = from_collection.get_object(object_id) to_collection.add_objects(bundle) print("========Successful===========") to_collection.get_object(bundle) # try: # bundle = from_collection.get_object(object_id) # to_collection.add_objects(bundle) # print("========Successful===========") # to_collection.get_object(bundle) # except: # print("Addition Failed")

43.033981

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0.819709

0.798286

0.7491

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0.721851

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0.002683

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8,865

206

170

43.033981

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0.110204

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0.066667

false

0.213333

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0

null

0

1

0

1

0

9

08289650a721b2511b611234286658166242db65

206

py

Python

xsd2tkform/core/list.py

Dolgalad/xsd2tkform

27f0d5bd1d9b6816982c18c45323ff7d1191efca

[ "MIT" ]

null

xsd2tkform/core/list.py

Dolgalad/xsd2tkform

27f0d5bd1d9b6816982c18c45323ff7d1191efca

[ "MIT" ]

null

xsd2tkform/core/list.py

Dolgalad/xsd2tkform

27f0d5bd1d9b6816982c18c45323ff7d1191efca

[ "MIT" ]

null

"""Simple type value list definition """ class List: def __init__(self, item_type=None): self.item_type = None def __str__(self): return "List(item_type={})".format(self.item_type)

22.888889

58

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null

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7

f27a763c0e260694798be75fea4d592cfd53d55c

38,379

py

Python

nova/tests/unit/api/openstack/compute/test_multiple_create.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

null

nova/tests/unit/api/openstack/compute/test_multiple_create.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

null

nova/tests/unit/api/openstack/compute/test_multiple_create.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

2

2017-07-20T17:31:34.000Z

2020-07-24T02:42:19.000Z

begin_unit comment|'# Copyright 2013 IBM Corp.' nl|'\n' comment|'# All Rights Reserved.' nl|'\n' comment|'#' nl|'\n' comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may' nl|'\n' comment|'# not use this file except in compliance with the License. You may obtain' nl|'\n' comment|'# a copy of the License at' nl|'\n' comment|'#' nl|'\n' comment|'# http://www.apache.org/licenses/LICENSE-2.0' nl|'\n' comment|'#' nl|'\n' comment|'# Unless required by applicable law or agreed to in writing, software' nl|'\n' comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT' nl|'\n' comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the' nl|'\n' comment|'# License for the specific language governing permissions and limitations' nl|'\n' comment|'# under the License.' nl|'\n' nl|'\n' name|'import' name|'datetime' newline|'\n' nl|'\n' name|'import' name|'webob' newline|'\n' nl|'\n' name|'from' name|'nova' op|'.' name|'api' op|'.' name|'openstack' op|'.' name|'compute' name|'import' name|'block_device_mapping' name|'as' name|'block_device_mapping_v21' newline|'\n' name|'from' name|'nova' op|'.' name|'api' op|'.' name|'openstack' op|'.' name|'compute' name|'import' name|'extension_info' newline|'\n' name|'from' name|'nova' op|'.' name|'api' op|'.' name|'openstack' op|'.' name|'compute' name|'import' name|'multiple_create' name|'as' name|'multiple_create_v21' newline|'\n' name|'from' name|'nova' op|'.' name|'api' op|'.' name|'openstack' op|'.' name|'compute' name|'import' name|'servers' name|'as' name|'servers_v21' newline|'\n' name|'from' name|'nova' op|'.' name|'compute' name|'import' name|'api' name|'as' name|'compute_api' newline|'\n' name|'from' name|'nova' op|'.' name|'compute' name|'import' name|'flavors' newline|'\n' name|'import' name|'nova' op|'.' name|'conf' newline|'\n' name|'from' name|'nova' name|'import' name|'exception' newline|'\n' name|'from' name|'nova' op|'.' name|'network' name|'import' name|'manager' newline|'\n' name|'from' name|'nova' name|'import' name|'test' newline|'\n' name|'from' name|'nova' op|'.' name|'tests' op|'.' name|'unit' op|'.' name|'api' op|'.' name|'openstack' name|'import' name|'fakes' newline|'\n' name|'from' name|'nova' op|'.' name|'tests' op|'.' name|'unit' name|'import' name|'fake_instance' newline|'\n' name|'from' name|'nova' op|'.' name|'tests' op|'.' name|'unit' op|'.' name|'image' name|'import' name|'fake' newline|'\n' nl|'\n' DECL|variable|CONF name|'CONF' op|'=' name|'nova' op|'.' name|'conf' op|'.' name|'CONF' newline|'\n' nl|'\n' nl|'\n' DECL|function|return_security_group name|'def' name|'return_security_group' op|'(' name|'context' op|',' name|'instance_id' op|',' name|'security_group_id' op|')' op|':' newline|'\n' indent|' ' name|'pass' newline|'\n' nl|'\n' nl|'\n' DECL|class|MultiCreateExtensionTestV21 dedent|'' name|'class' name|'MultiCreateExtensionTestV21' op|'(' name|'test' op|'.' name|'TestCase' op|')' op|':' newline|'\n' DECL|variable|validation_error indent|' ' name|'validation_error' op|'=' name|'exception' op|'.' name|'ValidationError' newline|'\n' nl|'\n' DECL|member|setUp name|'def' name|'setUp' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' string|'"""Shared implementation for tests below that create instance."""' newline|'\n' name|'super' op|'(' name|'MultiCreateExtensionTestV21' op|',' name|'self' op|')' op|'.' name|'setUp' op|'(' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'flags' op|'(' name|'verbose' op|'=' name|'True' op|',' nl|'\n' name|'enable_instance_password' op|'=' name|'True' op|')' newline|'\n' name|'self' op|'.' name|'instance_cache_num' op|'=' number|'0' newline|'\n' name|'self' op|'.' name|'instance_cache_by_id' op|'=' op|'{' op|'}' newline|'\n' name|'self' op|'.' name|'instance_cache_by_uuid' op|'=' op|'{' op|'}' newline|'\n' nl|'\n' name|'ext_info' op|'=' name|'extension_info' op|'.' name|'LoadedExtensionInfo' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'controller' op|'=' name|'servers_v21' op|'.' name|'ServersController' op|'(' nl|'\n' name|'extension_info' op|'=' name|'ext_info' op|')' newline|'\n' name|'CONF' op|'.' name|'set_override' op|'(' string|"'extensions_blacklist'" op|',' string|"'os-multiple-create'" op|',' nl|'\n' string|"'osapi_v21'" op|')' newline|'\n' name|'self' op|'.' name|'no_mult_create_controller' op|'=' name|'servers_v21' op|'.' name|'ServersController' op|'(' nl|'\n' name|'extension_info' op|'=' name|'ext_info' op|')' newline|'\n' nl|'\n' DECL|function|instance_create name|'def' name|'instance_create' op|'(' name|'context' op|',' name|'inst' op|')' op|':' newline|'\n' indent|' ' name|'inst_type' op|'=' name|'flavors' op|'.' name|'get_flavor_by_flavor_id' op|'(' number|'3' op|')' newline|'\n' name|'image_uuid' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'def_image_ref' op|'=' string|"'http://localhost/images/%s'" op|'%' name|'image_uuid' newline|'\n' name|'self' op|'.' name|'instance_cache_num' op|'+=' number|'1' newline|'\n' name|'instance' op|'=' name|'fake_instance' op|'.' name|'fake_db_instance' op|'(' op|'**' op|'{' nl|'\n' string|"'id'" op|':' name|'self' op|'.' name|'instance_cache_num' op|',' nl|'\n' string|"'display_name'" op|':' name|'inst' op|'[' string|"'display_name'" op|']' name|'or' string|"'test'" op|',' nl|'\n' string|"'uuid'" op|':' name|'inst' op|'[' string|"'uuid'" op|']' op|',' nl|'\n' string|"'instance_type'" op|':' name|'inst_type' op|',' nl|'\n' string|"'access_ip_v4'" op|':' string|"'1.2.3.4'" op|',' nl|'\n' string|"'access_ip_v6'" op|':' string|"'fead::1234'" op|',' nl|'\n' string|"'image_ref'" op|':' name|'inst' op|'.' name|'get' op|'(' string|"'image_ref'" op|',' name|'def_image_ref' op|')' op|',' nl|'\n' string|"'user_id'" op|':' string|"'fake'" op|',' nl|'\n' string|"'project_id'" op|':' string|"'fake'" op|',' nl|'\n' string|"'reservation_id'" op|':' name|'inst' op|'[' string|"'reservation_id'" op|']' op|',' nl|'\n' string|'"created_at"' op|':' name|'datetime' op|'.' name|'datetime' op|'(' number|'2010' op|',' number|'10' op|',' number|'10' op|',' number|'12' op|',' number|'0' op|',' number|'0' op|')' op|',' nl|'\n' string|'"updated_at"' op|':' name|'datetime' op|'.' name|'datetime' op|'(' number|'2010' op|',' number|'11' op|',' number|'11' op|',' number|'11' op|',' number|'0' op|',' number|'0' op|')' op|',' nl|'\n' string|'"progress"' op|':' number|'0' op|',' nl|'\n' string|'"fixed_ips"' op|':' op|'[' op|']' op|',' nl|'\n' string|'"task_state"' op|':' string|'""' op|',' nl|'\n' string|'"vm_state"' op|':' string|'""' op|',' nl|'\n' string|'"security_groups"' op|':' name|'inst' op|'[' string|"'security_groups'" op|']' op|',' nl|'\n' op|'}' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'instance_cache_by_id' op|'[' name|'instance' op|'[' string|"'id'" op|']' op|']' op|'=' name|'instance' newline|'\n' name|'self' op|'.' name|'instance_cache_by_uuid' op|'[' name|'instance' op|'[' string|"'uuid'" op|']' op|']' op|'=' name|'instance' newline|'\n' name|'return' name|'instance' newline|'\n' nl|'\n' DECL|function|instance_get dedent|'' name|'def' name|'instance_get' op|'(' name|'context' op|',' name|'instance_id' op|')' op|':' newline|'\n' indent|' ' string|'"""Stub for compute/api create() pulling in instance after\n scheduling\n """' newline|'\n' name|'return' name|'self' op|'.' name|'instance_cache_by_id' op|'[' name|'instance_id' op|']' newline|'\n' nl|'\n' DECL|function|instance_update dedent|'' name|'def' name|'instance_update' op|'(' name|'context' op|',' name|'uuid' op|',' name|'values' op|')' op|':' newline|'\n' indent|' ' name|'instance' op|'=' name|'self' op|'.' name|'instance_cache_by_uuid' op|'[' name|'uuid' op|']' newline|'\n' name|'instance' op|'.' name|'update' op|'(' name|'values' op|')' newline|'\n' name|'return' name|'instance' newline|'\n' nl|'\n' DECL|function|server_update dedent|'' name|'def' name|'server_update' op|'(' name|'context' op|',' name|'instance_uuid' op|',' name|'params' op|',' nl|'\n' name|'columns_to_join' op|'=' name|'None' op|')' op|':' newline|'\n' indent|' ' name|'inst' op|'=' name|'self' op|'.' name|'instance_cache_by_uuid' op|'[' name|'instance_uuid' op|']' newline|'\n' name|'inst' op|'.' name|'update' op|'(' name|'params' op|')' newline|'\n' name|'return' op|'(' name|'inst' op|',' name|'inst' op|')' newline|'\n' nl|'\n' DECL|function|fake_method dedent|'' name|'def' name|'fake_method' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' op|':' newline|'\n' indent|' ' name|'pass' newline|'\n' nl|'\n' DECL|function|project_get_networks dedent|'' name|'def' name|'project_get_networks' op|'(' name|'context' op|',' name|'user_id' op|')' op|':' newline|'\n' indent|' ' name|'return' name|'dict' op|'(' name|'id' op|'=' string|"'1'" op|',' name|'host' op|'=' string|"'localhost'" op|')' newline|'\n' nl|'\n' dedent|'' name|'fakes' op|'.' name|'stub_out_rate_limiting' op|'(' name|'self' op|'.' name|'stubs' op|')' newline|'\n' name|'fakes' op|'.' name|'stub_out_key_pair_funcs' op|'(' name|'self' op|'.' name|'stubs' op|')' newline|'\n' name|'fake' op|'.' name|'stub_out_image_service' op|'(' name|'self' op|')' newline|'\n' name|'fakes' op|'.' name|'stub_out_nw_api' op|'(' name|'self' op|')' newline|'\n' name|'self' op|'.' name|'stub_out' op|'(' string|"'nova.db.instance_add_security_group'" op|',' nl|'\n' name|'return_security_group' op|')' newline|'\n' name|'self' op|'.' name|'stub_out' op|'(' string|"'nova.db.project_get_networks'" op|',' name|'project_get_networks' op|')' newline|'\n' name|'self' op|'.' name|'stub_out' op|'(' string|"'nova.db.instance_create'" op|',' name|'instance_create' op|')' newline|'\n' name|'self' op|'.' name|'stub_out' op|'(' string|"'nova.db.instance_system_metadata_update'" op|',' name|'fake_method' op|')' newline|'\n' name|'self' op|'.' name|'stub_out' op|'(' string|"'nova.db.instance_get'" op|',' name|'instance_get' op|')' newline|'\n' name|'self' op|'.' name|'stub_out' op|'(' string|"'nova.db.instance_update'" op|',' name|'instance_update' op|')' newline|'\n' name|'self' op|'.' name|'stub_out' op|'(' string|"'nova.db.instance_update_and_get_original'" op|',' nl|'\n' name|'server_update' op|')' newline|'\n' name|'self' op|'.' name|'stubs' op|'.' name|'Set' op|'(' name|'manager' op|'.' name|'VlanManager' op|',' string|"'allocate_fixed_ip'" op|',' nl|'\n' name|'fake_method' op|')' newline|'\n' name|'self' op|'.' name|'req' op|'=' name|'fakes' op|'.' name|'HTTPRequest' op|'.' name|'blank' op|'(' string|"''" op|')' newline|'\n' nl|'\n' DECL|member|_test_create_extra dedent|'' name|'def' name|'_test_create_extra' op|'(' name|'self' op|',' name|'params' op|',' name|'no_image' op|'=' name|'False' op|',' nl|'\n' name|'override_controller' op|'=' name|'None' op|')' op|':' newline|'\n' indent|' ' name|'image_uuid' op|'=' string|"'c905cedb-7281-47e4-8a62-f26bc5fc4c77'" newline|'\n' name|'server' op|'=' name|'dict' op|'(' name|'name' op|'=' string|"'server_test'" op|',' name|'imageRef' op|'=' name|'image_uuid' op|',' name|'flavorRef' op|'=' number|'2' op|')' newline|'\n' name|'if' name|'no_image' op|':' newline|'\n' indent|' ' name|'server' op|'.' name|'pop' op|'(' string|"'imageRef'" op|',' name|'None' op|')' newline|'\n' dedent|'' name|'server' op|'.' name|'update' op|'(' name|'params' op|')' newline|'\n' name|'body' op|'=' name|'dict' op|'(' name|'server' op|'=' name|'server' op|')' newline|'\n' name|'if' name|'override_controller' op|':' newline|'\n' indent|' ' name|'server' op|'=' name|'override_controller' op|'.' name|'create' op|'(' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' op|'.' name|'obj' op|'[' string|"'server'" op|']' newline|'\n' dedent|'' name|'else' op|':' newline|'\n' indent|' ' name|'server' op|'=' name|'self' op|'.' name|'controller' op|'.' name|'create' op|'(' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' op|'.' name|'obj' op|'[' string|"'server'" op|']' newline|'\n' nl|'\n' DECL|member|_check_multiple_create_extension_disabled dedent|'' dedent|'' name|'def' name|'_check_multiple_create_extension_disabled' op|'(' name|'self' op|',' op|'**' name|'kwargs' op|')' op|':' newline|'\n' comment|'# NOTE: on v2.1 API, "create a server" API doesn\'t add the following' nl|'\n' comment|'# attributes into kwargs when non-loading multiple_create extension.' nl|'\n' comment|'# However, v2.0 API adds them as values "1" instead. So we need to' nl|'\n' comment|'# define checking methods for each API here.' nl|'\n' indent|' ' name|'self' op|'.' name|'assertNotIn' op|'(' string|"'min_count'" op|',' name|'kwargs' op|')' newline|'\n' name|'self' op|'.' name|'assertNotIn' op|'(' string|"'max_count'" op|',' name|'kwargs' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_with_multiple_create_disabled dedent|'' name|'def' name|'test_create_instance_with_multiple_create_disabled' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'min_count' op|'=' number|'2' newline|'\n' name|'max_count' op|'=' number|'3' newline|'\n' name|'params' op|'=' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' name|'min_count' op|',' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' name|'max_count' op|',' nl|'\n' op|'}' newline|'\n' name|'old_create' op|'=' name|'compute_api' op|'.' name|'API' op|'.' name|'create' newline|'\n' nl|'\n' DECL|function|create name|'def' name|'create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'_check_multiple_create_extension_disabled' op|'(' op|'**' name|'kwargs' op|')' newline|'\n' name|'return' name|'old_create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' newline|'\n' nl|'\n' dedent|'' name|'self' op|'.' name|'stubs' op|'.' name|'Set' op|'(' name|'compute_api' op|'.' name|'API' op|',' string|"'create'" op|',' name|'create' op|')' newline|'\n' name|'self' op|'.' name|'_test_create_extra' op|'(' nl|'\n' name|'params' op|',' nl|'\n' name|'override_controller' op|'=' name|'self' op|'.' name|'no_mult_create_controller' op|')' newline|'\n' nl|'\n' DECL|member|test_multiple_create_with_string_type_min_and_max dedent|'' name|'def' name|'test_multiple_create_with_string_type_min_and_max' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'min_count' op|'=' string|"'2'" newline|'\n' name|'max_count' op|'=' string|"'3'" newline|'\n' name|'params' op|'=' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' name|'min_count' op|',' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' name|'max_count' op|',' nl|'\n' op|'}' newline|'\n' name|'old_create' op|'=' name|'compute_api' op|'.' name|'API' op|'.' name|'create' newline|'\n' nl|'\n' DECL|function|create name|'def' name|'create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'assertIsInstance' op|'(' name|'kwargs' op|'[' string|"'min_count'" op|']' op|',' name|'int' op|')' newline|'\n' name|'self' op|'.' name|'assertIsInstance' op|'(' name|'kwargs' op|'[' string|"'max_count'" op|']' op|',' name|'int' op|')' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' name|'kwargs' op|'[' string|"'min_count'" op|']' op|',' number|'2' op|')' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' name|'kwargs' op|'[' string|"'max_count'" op|']' op|',' number|'3' op|')' newline|'\n' name|'return' name|'old_create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' newline|'\n' nl|'\n' dedent|'' name|'self' op|'.' name|'stubs' op|'.' name|'Set' op|'(' name|'compute_api' op|'.' name|'API' op|',' string|"'create'" op|',' name|'create' op|')' newline|'\n' name|'self' op|'.' name|'_test_create_extra' op|'(' name|'params' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_with_multiple_create_enabled dedent|'' name|'def' name|'test_create_instance_with_multiple_create_enabled' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'min_count' op|'=' number|'2' newline|'\n' name|'max_count' op|'=' number|'3' newline|'\n' name|'params' op|'=' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' name|'min_count' op|',' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' name|'max_count' op|',' nl|'\n' op|'}' newline|'\n' name|'old_create' op|'=' name|'compute_api' op|'.' name|'API' op|'.' name|'create' newline|'\n' nl|'\n' DECL|function|create name|'def' name|'create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'assertEqual' op|'(' name|'kwargs' op|'[' string|"'min_count'" op|']' op|',' number|'2' op|')' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' name|'kwargs' op|'[' string|"'max_count'" op|']' op|',' number|'3' op|')' newline|'\n' name|'return' name|'old_create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' newline|'\n' nl|'\n' dedent|'' name|'self' op|'.' name|'stubs' op|'.' name|'Set' op|'(' name|'compute_api' op|'.' name|'API' op|',' string|"'create'" op|',' name|'create' op|')' newline|'\n' name|'self' op|'.' name|'_test_create_extra' op|'(' name|'params' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_invalid_negative_min dedent|'' name|'def' name|'test_create_instance_invalid_negative_min' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' nl|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' op|'-' number|'1' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' nl|'\n' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_invalid_negative_max dedent|'' name|'def' name|'test_create_instance_invalid_negative_max' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' nl|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' op|'-' number|'1' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' nl|'\n' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_with_blank_min dedent|'' name|'def' name|'test_create_instance_with_blank_min' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' nl|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' string|"''" op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'image_ref'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavor_ref'" op|':' name|'flavor_ref' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' nl|'\n' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_with_blank_max dedent|'' name|'def' name|'test_create_instance_with_blank_max' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' nl|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' string|"''" op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'image_ref'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavor_ref'" op|':' name|'flavor_ref' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' nl|'\n' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_invalid_min_greater_than_max dedent|'' name|'def' name|'test_create_instance_invalid_min_greater_than_max' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' nl|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' number|'4' op|',' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' number|'2' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'webob' op|'.' name|'exc' op|'.' name|'HTTPBadRequest' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' nl|'\n' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_invalid_alpha_min dedent|'' name|'def' name|'test_create_instance_invalid_alpha_min' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' nl|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' string|"'abcd'" op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' nl|'\n' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_instance_invalid_alpha_max dedent|'' name|'def' name|'test_create_instance_invalid_alpha_max' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' nl|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' string|"'abcd'" op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' nl|'\n' name|'self' op|'.' name|'req' op|',' nl|'\n' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instances dedent|'' name|'def' name|'test_create_multiple_instances' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' string|'"""Test creating multiple instances but not asking for\n reservation_id\n """' newline|'\n' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' number|'2' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' string|"'metadata'" op|':' op|'{' string|"'hello'" op|':' string|"'world'" op|',' nl|'\n' string|"'open'" op|':' string|"'stack'" op|'}' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' nl|'\n' name|'res' op|'=' name|'self' op|'.' name|'controller' op|'.' name|'create' op|'(' name|'self' op|'.' name|'req' op|',' name|'body' op|'=' name|'body' op|')' op|'.' name|'obj' newline|'\n' nl|'\n' name|'instance_uuids' op|'=' name|'self' op|'.' name|'instance_cache_by_uuid' op|'.' name|'keys' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'assertIn' op|'(' name|'res' op|'[' string|'"server"' op|']' op|'[' string|'"id"' op|']' op|',' name|'instance_uuids' op|')' newline|'\n' name|'self' op|'.' name|'_check_admin_password_len' op|'(' name|'res' op|'[' string|'"server"' op|']' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instances_pass_disabled dedent|'' name|'def' name|'test_create_multiple_instances_pass_disabled' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' string|'"""Test creating multiple instances but not asking for\n reservation_id\n """' newline|'\n' name|'self' op|'.' name|'flags' op|'(' name|'enable_instance_password' op|'=' name|'False' op|')' newline|'\n' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' number|'2' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' string|"'metadata'" op|':' op|'{' string|"'hello'" op|':' string|"'world'" op|',' nl|'\n' string|"'open'" op|':' string|"'stack'" op|'}' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' nl|'\n' name|'res' op|'=' name|'self' op|'.' name|'controller' op|'.' name|'create' op|'(' name|'self' op|'.' name|'req' op|',' name|'body' op|'=' name|'body' op|')' op|'.' name|'obj' newline|'\n' nl|'\n' name|'instance_uuids' op|'=' name|'self' op|'.' name|'instance_cache_by_uuid' op|'.' name|'keys' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'assertIn' op|'(' name|'res' op|'[' string|'"server"' op|']' op|'[' string|'"id"' op|']' op|',' name|'instance_uuids' op|')' newline|'\n' name|'self' op|'.' name|'_check_admin_password_missing' op|'(' name|'res' op|'[' string|'"server"' op|']' op|')' newline|'\n' nl|'\n' DECL|member|_check_admin_password_len dedent|'' name|'def' name|'_check_admin_password_len' op|'(' name|'self' op|',' name|'server_dict' op|')' op|':' newline|'\n' indent|' ' string|'"""utility function - check server_dict for admin_password length."""' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' name|'CONF' op|'.' name|'password_length' op|',' nl|'\n' name|'len' op|'(' name|'server_dict' op|'[' string|'"adminPass"' op|']' op|')' op|')' newline|'\n' nl|'\n' DECL|member|_check_admin_password_missing dedent|'' name|'def' name|'_check_admin_password_missing' op|'(' name|'self' op|',' name|'server_dict' op|')' op|':' newline|'\n' indent|' ' string|'"""utility function - check server_dict for admin_password absence."""' newline|'\n' name|'self' op|'.' name|'assertNotIn' op|'(' string|'"admin_password"' op|',' name|'server_dict' op|')' newline|'\n' nl|'\n' DECL|member|_create_multiple_instances_resv_id_return dedent|'' name|'def' name|'_create_multiple_instances_resv_id_return' op|'(' name|'self' op|',' name|'resv_id_return' op|')' op|':' newline|'\n' indent|' ' string|'"""Test creating multiple instances with asking for\n reservation_id\n """' newline|'\n' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' number|'2' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' string|"'metadata'" op|':' op|'{' string|"'hello'" op|':' string|"'world'" op|',' nl|'\n' string|"'open'" op|':' string|"'stack'" op|'}' op|',' nl|'\n' name|'multiple_create_v21' op|'.' name|'RRID_ATTRIBUTE_NAME' op|':' name|'resv_id_return' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' nl|'\n' name|'res' op|'=' name|'self' op|'.' name|'controller' op|'.' name|'create' op|'(' name|'self' op|'.' name|'req' op|',' name|'body' op|'=' name|'body' op|')' newline|'\n' name|'reservation_id' op|'=' name|'res' op|'.' name|'obj' op|'[' string|"'reservation_id'" op|']' newline|'\n' name|'self' op|'.' name|'assertNotEqual' op|'(' name|'reservation_id' op|',' string|'""' op|')' newline|'\n' name|'self' op|'.' name|'assertIsNotNone' op|'(' name|'reservation_id' op|')' newline|'\n' name|'self' op|'.' name|'assertTrue' op|'(' name|'len' op|'(' name|'reservation_id' op|')' op|'>' number|'1' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instances_with_resv_id_return dedent|'' name|'def' name|'test_create_multiple_instances_with_resv_id_return' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'_create_multiple_instances_resv_id_return' op|'(' name|'True' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instances_with_string_resv_id_return dedent|'' name|'def' name|'test_create_multiple_instances_with_string_resv_id_return' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'_create_multiple_instances_resv_id_return' op|'(' string|'"True"' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instances_with_multiple_volume_bdm dedent|'' name|'def' name|'test_create_multiple_instances_with_multiple_volume_bdm' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' string|'"""Test that a BadRequest is raised if multiple instances\n are requested with a list of block device mappings for volumes.\n """' newline|'\n' name|'min_count' op|'=' number|'2' newline|'\n' name|'bdm' op|'=' op|'[' op|'{' string|"'source_type'" op|':' string|"'volume'" op|',' string|"'uuid'" op|':' string|"'vol-xxxx'" op|'}' op|',' nl|'\n' op|'{' string|"'source_type'" op|':' string|"'volume'" op|',' string|"'uuid'" op|':' string|"'vol-yyyy'" op|'}' nl|'\n' op|']' newline|'\n' name|'params' op|'=' op|'{' nl|'\n' name|'block_device_mapping_v21' op|'.' name|'ATTRIBUTE_NAME' op|':' name|'bdm' op|',' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' name|'min_count' nl|'\n' op|'}' newline|'\n' name|'old_create' op|'=' name|'compute_api' op|'.' name|'API' op|'.' name|'create' newline|'\n' nl|'\n' DECL|function|create name|'def' name|'create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'assertEqual' op|'(' name|'kwargs' op|'[' string|"'min_count'" op|']' op|',' number|'2' op|')' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' name|'len' op|'(' name|'kwargs' op|'[' string|"'block_device_mapping'" op|']' op|')' op|',' number|'2' op|')' newline|'\n' name|'return' name|'old_create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' newline|'\n' nl|'\n' dedent|'' name|'self' op|'.' name|'stubs' op|'.' name|'Set' op|'(' name|'compute_api' op|'.' name|'API' op|',' string|"'create'" op|',' name|'create' op|')' newline|'\n' name|'exc' op|'=' name|'self' op|'.' name|'assertRaises' op|'(' name|'webob' op|'.' name|'exc' op|'.' name|'HTTPBadRequest' op|',' nl|'\n' name|'self' op|'.' name|'_test_create_extra' op|',' name|'params' op|',' name|'no_image' op|'=' name|'True' op|')' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' string|'"Cannot attach one or more volumes to multiple "' nl|'\n' string|'"instances"' op|',' name|'exc' op|'.' name|'explanation' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instances_with_single_volume_bdm dedent|'' name|'def' name|'test_create_multiple_instances_with_single_volume_bdm' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' string|'"""Test that a BadRequest is raised if multiple instances\n are requested to boot from a single volume.\n """' newline|'\n' name|'min_count' op|'=' number|'2' newline|'\n' name|'bdm' op|'=' op|'[' op|'{' string|"'source_type'" op|':' string|"'volume'" op|',' string|"'uuid'" op|':' string|"'vol-xxxx'" op|'}' op|']' newline|'\n' name|'params' op|'=' op|'{' nl|'\n' name|'block_device_mapping_v21' op|'.' name|'ATTRIBUTE_NAME' op|':' name|'bdm' op|',' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' name|'min_count' nl|'\n' op|'}' newline|'\n' name|'old_create' op|'=' name|'compute_api' op|'.' name|'API' op|'.' name|'create' newline|'\n' nl|'\n' DECL|function|create name|'def' name|'create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'assertEqual' op|'(' name|'kwargs' op|'[' string|"'min_count'" op|']' op|',' number|'2' op|')' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' name|'kwargs' op|'[' string|"'block_device_mapping'" op|']' op|'[' number|'0' op|']' op|'[' string|"'volume_id'" op|']' op|',' nl|'\n' string|"'vol-xxxx'" op|')' newline|'\n' name|'return' name|'old_create' op|'(' op|'*' name|'args' op|',' op|'**' name|'kwargs' op|')' newline|'\n' nl|'\n' dedent|'' name|'self' op|'.' name|'stubs' op|'.' name|'Set' op|'(' name|'compute_api' op|'.' name|'API' op|',' string|"'create'" op|',' name|'create' op|')' newline|'\n' name|'exc' op|'=' name|'self' op|'.' name|'assertRaises' op|'(' name|'webob' op|'.' name|'exc' op|'.' name|'HTTPBadRequest' op|',' nl|'\n' name|'self' op|'.' name|'_test_create_extra' op|',' name|'params' op|',' name|'no_image' op|'=' name|'True' op|')' newline|'\n' name|'self' op|'.' name|'assertEqual' op|'(' string|'"Cannot attach one or more volumes to multiple "' nl|'\n' string|'"instances"' op|',' name|'exc' op|'.' name|'explanation' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instance_with_non_integer_max_count dedent|'' name|'def' name|'test_create_multiple_instance_with_non_integer_max_count' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MAX_ATTRIBUTE_NAME' op|':' number|'2.5' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' string|"'metadata'" op|':' op|'{' string|"'hello'" op|':' string|"'world'" op|',' nl|'\n' string|"'open'" op|':' string|"'stack'" op|'}' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' nl|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' name|'self' op|'.' name|'req' op|',' name|'body' op|'=' name|'body' op|')' newline|'\n' nl|'\n' DECL|member|test_create_multiple_instance_with_non_integer_min_count dedent|'' name|'def' name|'test_create_multiple_instance_with_non_integer_min_count' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'image_href' op|'=' string|"'76fa36fc-c930-4bf3-8c8a-ea2a2420deb6'" newline|'\n' name|'flavor_ref' op|'=' string|"'http://localhost/123/flavors/3'" newline|'\n' name|'body' op|'=' op|'{' nl|'\n' string|"'server'" op|':' op|'{' nl|'\n' name|'multiple_create_v21' op|'.' name|'MIN_ATTRIBUTE_NAME' op|':' number|'2.5' op|',' nl|'\n' string|"'name'" op|':' string|"'server_test'" op|',' nl|'\n' string|"'imageRef'" op|':' name|'image_href' op|',' nl|'\n' string|"'flavorRef'" op|':' name|'flavor_ref' op|',' nl|'\n' string|"'metadata'" op|':' op|'{' string|"'hello'" op|':' string|"'world'" op|',' nl|'\n' string|"'open'" op|':' string|"'stack'" op|'}' op|',' nl|'\n' op|'}' nl|'\n' op|'}' newline|'\n' nl|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'self' op|'.' name|'validation_error' op|',' nl|'\n' name|'self' op|'.' name|'controller' op|'.' name|'create' op|',' name|'self' op|'.' name|'req' op|',' name|'body' op|'=' name|'body' op|')' newline|'\n' dedent|'' dedent|'' endmarker|'' end_unit

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null

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0

8

f28c4e9784618dee268d5f8588a3f4d202c01e57

1,344

py

Python

ocradmin/documents/models.py

mikesname/ocropodium

a3e379cca38dc1999349bf4e9b5608e81dc54b10

[ "Apache-2.0" ]

1

2018-04-18T20:39:02.000Z

ocradmin/documents/models.py

mikesname/ocropodium

a3e379cca38dc1999349bf4e9b5608e81dc54b10

[ "Apache-2.0" ]

null

ocradmin/documents/models.py

mikesname/ocropodium

a3e379cca38dc1999349bf4e9b5608e81dc54b10

[ "Apache-2.0" ]

null

from django.db import models from ocradmin.projects.models import Project from ocradmin import storage from django.conf import settings #class DocumentBase(object): # """Document model abstract class. Each storage # backend implements its own version of this.""" # def __init__(self, label): # """Initialise the Document with an image path/handle.""" # self._label = label # # @property # def label(self): # raise NotImplementedError # # def __unicode__(self): # """Unicode representation.""" # return self.label # # def save(self): # """Save objects, settings dates if necessary # and writing all cached datastreams to storage.""" # raise NotImplementedError # # def set_image_content(self, content): # """Set image content.""" # raise NotImplementedError # # def set_image_mimetype(self, mimetype): # """Set image mimetype.""" # raise NotImplementedError # # def set_image_label(self, label): # """Set image label.""" # raise NotImplementedError # # def set_label(self, label): # """Set document label.""" # raise NotImplementedError # # def set_metadata(self, attr, value): # """Set arbitrary document metadata.""" # raise NotImplementedError

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0

1

0

1

0

7

f2ab73ebd7c9f579f7e3cee6ff1e83814bff2cf1

101

py

Python

DSA/bit_magic/divisibility.py

RohanMiraje/DSAwithPython

ea4884afcac9d6cc2817a93e918c829dd10cef5d

[ "MIT" ]

2

2020-02-12T03:00:03.000Z

2020-07-06T17:27:03.000Z

DSA/bit_magic/divisibility.py

RohanMiraje/DSAwithPython

ea4884afcac9d6cc2817a93e918c829dd10cef5d

[ "MIT" ]

null

DSA/bit_magic/divisibility.py

RohanMiraje/DSAwithPython

ea4884afcac9d6cc2817a93e918c829dd10cef5d

[ "MIT" ]

null

def check_if_no_is_div_by_9(n): pass if __name__ == '__main__': check_if_no_is_div_by_9(9)

14.428571

31

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21

101

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0.264151

0.339623

0.415094

0.641509

0

0.036145

0.178218

101

6

32

16.833333

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0

0.079208

0

1

0.25

false

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0.25

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1

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1

0

null

0

1

0

1

0

7

4b80c16aa52029cb5daf60aaf5c85d5e67b38206

11,964

py

Python

tests/test_apis_APIBuilder.py

josiah-wolf-oberholtzer/uqbar

96f86eb6264b0677a9e2931a527769640e5658b6

[ "MIT" ]

7

2018-12-02T05:59:54.000Z

2021-12-28T22:40:18.000Z

tests/test_apis_APIBuilder.py

josiah-wolf-oberholtzer/uqbar

96f86eb6264b0677a9e2931a527769640e5658b6

[ "MIT" ]

16

2017-12-28T22:08:09.000Z

2022-02-26T14:47:23.000Z

tests/test_apis_APIBuilder.py

josiah-wolf-oberholtzer/uqbar

96f86eb6264b0677a9e2931a527769640e5658b6

[ "MIT" ]

5

2020-03-28T14:57:47.000Z

2022-02-01T10:02:18.000Z

import pathlib import shutil import sys import pytest import uqbar.apis from uqbar.strings import normalize @pytest.fixture def test_path(): test_path = pathlib.Path(__file__).parent docs_path = test_path / "docs" if str(test_path) not in sys.path: sys.path.insert(0, str(test_path)) if docs_path.exists(): shutil.rmtree(str(docs_path)) yield test_path if docs_path.exists(): shutil.rmtree(str(docs_path)) def test_collection_01(test_path): builder = uqbar.apis.APIBuilder([test_path / "fake_package"], test_path / "docs") source_paths = uqbar.apis.collect_source_paths(builder._initial_source_paths) node_tree = builder.build_node_tree(source_paths) assert normalize(str(node_tree)) == normalize( """ None/ fake_package/ fake_package.empty_module fake_package.empty_package/ fake_package.empty_package.empty fake_package.enums fake_package.module fake_package.multi/ fake_package.multi.one fake_package.multi.two """ ) documenters = list(builder.collect_module_documenters(node_tree)) assert isinstance(documenters[0], uqbar.apis.RootDocumenter) assert [documenter.package_path for documenter in documenters[1:]] == [ "fake_package", "fake_package.empty_module", "fake_package.empty_package", "fake_package.empty_package.empty", "fake_package.enums", "fake_package.module", "fake_package.multi", "fake_package.multi.one", "fake_package.multi.two", ] def test_collection_02(test_path): builder = uqbar.apis.APIBuilder( [test_path / "fake_package"], test_path / "docs", document_private_modules=True ) source_paths = uqbar.apis.collect_source_paths(builder._initial_source_paths) node_tree = builder.build_node_tree(source_paths) assert normalize(str(node_tree)) == normalize( """ None/ fake_package/ fake_package._private/ fake_package._private.nested fake_package.empty_module fake_package.empty_package/ fake_package.empty_package.empty fake_package.enums fake_package.module fake_package.multi/ fake_package.multi.one fake_package.multi.two """ ) documenters = list(builder.collect_module_documenters(node_tree)) assert isinstance(documenters[0], uqbar.apis.RootDocumenter) assert [documenter.package_path for documenter in documenters[1:]] == [ "fake_package", "fake_package._private", "fake_package._private.nested", "fake_package.empty_module", "fake_package.empty_package", "fake_package.empty_package.empty", "fake_package.enums", "fake_package.module", "fake_package.multi", "fake_package.multi.one", "fake_package.multi.two", ] def test_collection_03(test_path): builder = uqbar.apis.APIBuilder( [test_path / "fake_package" / "multi"], test_path / "docs" ) source_paths = uqbar.apis.collect_source_paths(builder._initial_source_paths) node_tree = builder.build_node_tree(source_paths) documenters = list(builder.collect_module_documenters(node_tree)) assert isinstance(documenters[0], uqbar.apis.RootDocumenter) assert [documenter.package_path for documenter in documenters[1:]] == [ "fake_package", "fake_package.multi", "fake_package.multi.one", "fake_package.multi.two", ] def test_collection_04(test_path): builder = uqbar.apis.APIBuilder( [test_path / "fake_package"], test_path / "docs", document_empty_modules=False ) source_paths = uqbar.apis.collect_source_paths(builder._initial_source_paths) node_tree = builder.build_node_tree(source_paths) assert normalize(str(node_tree)) == normalize( """ None/ fake_package/ fake_package.enums fake_package.module fake_package.multi/ fake_package.multi.one fake_package.multi.two """ ) documenters = list(builder.collect_module_documenters(node_tree)) assert isinstance(documenters[0], uqbar.apis.RootDocumenter) assert [documenter.package_path for documenter in documenters[1:]] == [ "fake_package", "fake_package.enums", "fake_package.module", "fake_package.multi", "fake_package.multi.one", "fake_package.multi.two", ] def test_output_01(test_path): builder = uqbar.apis.APIBuilder([test_path / "fake_package"], test_path / "docs") builder() paths = sorted((test_path / "docs").rglob("*")) paths = [str(path.relative_to(test_path)) for path in paths] assert paths == [ "docs/fake_package", "docs/fake_package/empty_module.rst", "docs/fake_package/empty_package", "docs/fake_package/empty_package/empty.rst", "docs/fake_package/empty_package/index.rst", "docs/fake_package/enums.rst", "docs/fake_package/index.rst", "docs/fake_package/module.rst", "docs/fake_package/multi", "docs/fake_package/multi/index.rst", "docs/fake_package/multi/one.rst", "docs/fake_package/multi/two.rst", "docs/index.rst", ] base_path = test_path / "docs" / "fake_package" with (base_path / ".." / "index.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ API === .. toctree:: fake_package/index """ ) with (base_path / "index.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ .. _fake-package: fake_package ============ .. automodule:: fake_package .. currentmodule:: fake_package .. toctree:: empty_module empty_package/index enums module multi/index """ ) with (base_path / "module.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ .. _fake-package--module: module ====== .. automodule:: fake_package.module .. currentmodule:: fake_package.module .. autoclass:: ChildClass :members: :undoc-members: .. autoclass:: PublicClass :members: :undoc-members: .. autofunction:: public_function """ ) def test_output_02(test_path): builder = uqbar.apis.APIBuilder( [test_path / "fake_package"], test_path / "docs", document_private_modules=True ) builder() paths = sorted((test_path / "docs").rglob("*")) paths = [str(path.relative_to(test_path)) for path in paths] assert paths == [ "docs/fake_package", "docs/fake_package/_private", "docs/fake_package/_private/index.rst", "docs/fake_package/_private/nested.rst", "docs/fake_package/empty_module.rst", "docs/fake_package/empty_package", "docs/fake_package/empty_package/empty.rst", "docs/fake_package/empty_package/index.rst", "docs/fake_package/enums.rst", "docs/fake_package/index.rst", "docs/fake_package/module.rst", "docs/fake_package/multi", "docs/fake_package/multi/index.rst", "docs/fake_package/multi/one.rst", "docs/fake_package/multi/two.rst", "docs/index.rst", ] base_path = test_path / "docs" / "fake_package" with (base_path / ".." / "index.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ API === .. toctree:: fake_package/index """ ) with (base_path / "index.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ .. _fake-package: fake_package ============ .. automodule:: fake_package .. currentmodule:: fake_package .. toctree:: _private/index empty_module empty_package/index enums module multi/index """ ) with (base_path / "module.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ .. _fake-package--module: module ====== .. automodule:: fake_package.module .. currentmodule:: fake_package.module .. autoclass:: ChildClass :members: :undoc-members: .. autoclass:: PublicClass :members: :undoc-members: .. autofunction:: public_function """ ) def test_output_03(test_path): builder = uqbar.apis.APIBuilder( [test_path / "fake_package"], test_path / "docs", document_private_members=True, document_private_modules=True, ) builder() paths = sorted((test_path / "docs").rglob("*")) paths = [str(path.relative_to(test_path)) for path in paths] assert paths == [ "docs/fake_package", "docs/fake_package/_private", "docs/fake_package/_private/index.rst", "docs/fake_package/_private/nested.rst", "docs/fake_package/empty_module.rst", "docs/fake_package/empty_package", "docs/fake_package/empty_package/empty.rst", "docs/fake_package/empty_package/index.rst", "docs/fake_package/enums.rst", "docs/fake_package/index.rst", "docs/fake_package/module.rst", "docs/fake_package/multi", "docs/fake_package/multi/index.rst", "docs/fake_package/multi/one.rst", "docs/fake_package/multi/two.rst", "docs/index.rst", ] base_path = test_path / "docs" / "fake_package" with (base_path / ".." / "index.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ API === .. toctree:: fake_package/index """ ) with (base_path / "index.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ .. _fake-package: fake_package ============ .. automodule:: fake_package .. currentmodule:: fake_package .. toctree:: _private/index empty_module empty_package/index enums module multi/index """ ) with (base_path / "module.rst").open() as file_pointer: assert normalize(file_pointer.read()) == normalize( """ .. _fake-package--module: module ====== .. automodule:: fake_package.module .. currentmodule:: fake_package.module .. autoclass:: ChildClass :members: :undoc-members: .. autoclass:: PublicClass :members: :undoc-members: .. autoclass:: _PrivateClass :members: :undoc-members: .. autofunction:: _private_function .. autofunction:: public_function """ )

30.365482

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0.56996

1,208

11,964

5.362583

0.073676

0.224143

0.104199

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11,964

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1

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1

0

1

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null

0

8

4ba874689ddef0d70402f40b7202be1dafa315d9

4,836

py

Python

imagemodel/experimental/reference_tracking/dataset_providers/rt_transformer.py

tenkeyless/imagemodel

360c672117b5ccb1bfb3d6771b0720fa1a1f513c

[ "MIT" ]

null

imagemodel/experimental/reference_tracking/dataset_providers/rt_transformer.py

tenkeyless/imagemodel

360c672117b5ccb1bfb3d6771b0720fa1a1f513c

[ "MIT" ]

null

imagemodel/experimental/reference_tracking/dataset_providers/rt_transformer.py

tenkeyless/imagemodel

360c672117b5ccb1bfb3d6771b0720fa1a1f513c

[ "MIT" ]

null

from abc import ABCMeta, abstractmethod from typing import Tuple import tensorflow as tf from imagemodel.common.dataset_providers.transformer import TransformerP, TransformerT class RTTransformerT(TransformerT, metaclass=ABCMeta): @property @abstractmethod def bin_size(self) -> int: pass def __augment( self, main_img: tf.Tensor, ref_img: tf.Tensor, main_label: tf.Tensor, ref_label: tf.Tensor, main_bw_label: tf.Tensor, ref_bw_label: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: pass def __resize( self, main_img: tf.Tensor, ref_img: tf.Tensor, main_label: tf.Tensor, ref_label: tf.Tensor, main_bw_label: tf.Tensor, ref_bw_label: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: pass def __color_extract( self, main_img: tf.Tensor, ref_img: tf.Tensor, main_label: tf.Tensor, ref_label: tf.Tensor, main_bw_label: tf.Tensor, ref_bw_label: tf.Tensor) -> \ Tuple[tf.Tensor, tf.Tensor, tf.Tensor, Tuple[tf.Tensor, tf.Tensor], tf.Tensor, tf.Tensor, tf.Tensor]: pass def __color_to_bin( self, main_img: tf.Tensor, ref_img: tf.Tensor, main_label: tf.Tensor, ref_label_color_map: tf.Tensor, ref_label: tf.Tensor, main_bw_label: tf.Tensor, ref_bw_label: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: pass def __apply_filter( self, main_img: tf.Tensor, ref_img: tf.Tensor, bin_main_label: tf.Tensor, bin_ref_label: tf.Tensor, main_bw_label: tf.Tensor, ref_bw_label: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: pass def __norm_data( self, main_img: tf.Tensor, ref_img: tf.Tensor, bin_main_label: tf.Tensor, bin_ref_label: tf.Tensor, main_bw_label: tf.Tensor, ref_bw_label: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: pass def __zip_dataset( self, main_img: tf.Tensor, ref_img: tf.Tensor, bin_main_label: tf.Tensor, bin_ref_label: tf.Tensor, main_bw_label: tf.Tensor, ref_bw_label: tf.Tensor) -> \ Tuple[Tuple[tf.Tensor, tf.Tensor, tf.Tensor], Tuple[tf.Tensor, tf.Tensor, tf.Tensor]]: pass class RTTransformerP(TransformerP, metaclass=ABCMeta): @property @abstractmethod def bin_size(self) -> int: pass def __resize(self, filename: tf.Tensor, main_img: tf.Tensor, ref_img: tf.Tensor, ref_label: tf.Tensor) -> \ Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor]: pass def __color_extract(self, filename: tf.Tensor, main_img: tf.Tensor, ref_img: tf.Tensor, ref_label: tf.Tensor) -> \ Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, Tuple[tf.Tensor, tf.Tensor]]: pass def __color_to_bin( self, filename: tf.Tensor, main_img: tf.Tensor, ref_img: tf.Tensor, ref_label: tf.Tensor, ref_label_color_map: Tuple[tf.Tensor, tf.Tensor]) -> \ Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, Tuple[tf.Tensor, tf.Tensor]]: pass def __apply_filter( self, filename: tf.Tensor, main_img: tf.Tensor, ref_img: tf.Tensor, bin_ref_label: tf.Tensor, ref_label_color_map: Tuple[tf.Tensor, tf.Tensor]) -> \ Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, Tuple[tf.Tensor, tf.Tensor]]: pass def __norm_data( self, filename: tf.Tensor, main_img: tf.Tensor, ref_img: tf.Tensor, bin_ref_label: tf.Tensor, ref_label_color_map: Tuple[tf.Tensor, tf.Tensor]) -> \ Tuple[tf.Tensor, tf.Tensor, tf.Tensor, tf.Tensor, Tuple[tf.Tensor, tf.Tensor]]: pass def __zip_dataset( self, filename: tf.Tensor, main_img: tf.Tensor, ref_img: tf.Tensor, bin_ref_label: tf.Tensor, ref_label_color_map: Tuple[tf.Tensor, tf.Tensor]) -> \ Tuple[Tuple[tf.Tensor, tf.Tensor, tf.Tensor], Tuple[tf.Tensor, Tuple[tf.Tensor, tf.Tensor]]]: pass

34.056338

118

0.56493

614

4,836

4.223127

0.074919

0.47204

0.235249

0.376398

0.910143

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0.895874

0.873506

0

0.327543

4,836

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119

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1

0

1

0

null

0

1

0

11

4bc2106f1b1852ec4a2e3e054f318f2eec8fce24

3,732

py

Python

20180806_HTML.py

DahyeLee0403/HTML_-

adab04b24181c1e4fbeb14bbeca4dd960c49e3a9

[ "MIT" ]

null

20180806_HTML.py

DahyeLee0403/HTML_-

adab04b24181c1e4fbeb14bbeca4dd960c49e3a9

[ "MIT" ]

null

20180806_HTML.py

DahyeLee0403/HTML_-

adab04b24181c1e4fbeb14bbeca4dd960c49e3a9

[ "MIT" ]

null

#20180806_코딩야학_4일차 #부모 자식과 목차 <ul>: unordered list/ 다른 목록 들과 구분할 경계 <ol>: ordered list (1. 2. 3. 이렇게 숫자 부여) <li>: list ----------------------------------------------- <ol> <li>1. HTML</li> <li>2. CSS</li> <li>3. JavaScript</li> </ol> <h1>HTML</h1> <p>Hypertext Markup Language (HTML) is the standard markup language for <strong>creating <u>web</u> pages</strong> and web applications.Web browsers receive HTML documents from a web server or from local storage and render them into multimedia web pages. HTML describes the structure of a web page semantically and originally included cues for the appearance of the document. </p><p style="margin-top:45px;">HTML elements are the building blocks of HTML pages. With HTML constructs, images and other objects, such as interactive forms, may be embedded into the rendered page. It provides a means to create structured documents by denoting structural semantics for text such as headings, paragraphs, lists, links, quotes and other items. HTML elements are delineated by tags, written using angle brackets. </p> VIEW RESO ----------------------------------------------- #문서의 구조 제목 지정 <title> : 검색엔진이 웹페이지를 검색 시, 가장 중요 영어가 아닌 문자 가 깨지는 이유 웹페이지가 저장된 문자 '표현 방식'이 일치 X 웹브라우저가 웹페이지를 '해석하는 방식'이 일치 X <meta charset="utf-8">:'utf-8'으로 <!doctype html> :페이지가 html 로 만들어졌다. ----------------------------------------------- <head> <html> <title>WEB1 - html</title> <meta charset="utf-8"> </head> <body> <ol> <li>HTML</li> <li>CSS</li> <li>JavaScript</li> </ol> <h1>HTML</h1> <p>Hypertext Markup Language (HTML) is the standard markup language for <strong>creating <u>web</u> pages</strong> and web applications.Web browsers receive HTML documents from a web server or from local storage and render them into multimedia web pages. HTML describes the structure of a web page semantically and originally included cues for the appearance of the document. </p><p style="margin-top:45px;">HTML elements are the building blocks of HTML pages. With HTML constructs, images and other objects, such as interactive forms, may be embedded into the rendered page. It provides a means to create structured documents by denoting structural semantics for text such as headings, paragraphs, lists, links, quotes and other items. HTML elements are delineated by tags, written using angle brackets. </p> ----------------------------------------------- #HTML 태그의 제왕 <href> : hyper text reference <a> : anchor target="_blank" : 링크 클릭했을 때 새창에서 페이지 열리게 title : 링크가 어떤 내용을 담고 있는지 툴팁으로 보여주는 기능 ----------------------------------------------- <!doctype html> <html> <head> <title>WEB1 - html</title> <meta charset="utf-8"> </head> <body> <ol> <li>HTML</li> <li>CSS</li> <li>JavaScript</li> </ol> <h1>HTML</h1> <p><a href="https://www.w3.org/TR/html5/" target="_blank" title="html5 specification">Hypertext Markup Language (HTML)</a> is the standard markup language for <strong>creating <u>web</u> pages</strong> and web applications.Web browsers receive HTML documents from a web server or from local storage and render them into multimedia web pages. HTML describes the structure of a web page semantically and originally included cues for the appearance of the document. <img src="coding.jpg" width="100%"> </p><p style="margin-top:45px;">HTML elements are the building blocks of HTML pages. With HTML constructs, images and other objects, such as interactive forms, may be embedded into the rendered page. It provides a means to create structured documents by denoting structural semantics for text such as headings, paragraphs, lists, links, quotes and other items. HTML elements are delineated by tags, written using angle brackets. </p> </body> </html>

47.846154

464

0.693462

575

3,732

4.493913

0.32

0.009288

0.03483

0.018576

0.816176

0

0.012318

0.151661

3,732

77

465

48.467532

0.803853

0.011522

0

0.634921

0

0.04152

0

null

0

null

0

null

0

1

0

null

0

1

0

7

29a99923af94efeab6ab8092d6f592745aea08cb

106

py

Python

app/models.py

OrigamiCranes/PrintingPortal

e25f9f683dca3a0dcf4c90ae50515d7693447cb8

[ "MIT", "Unlicense" ]

null

app/models.py

OrigamiCranes/PrintingPortal

e25f9f683dca3a0dcf4c90ae50515d7693447cb8

[ "MIT", "Unlicense" ]

null

app/models.py

OrigamiCranes/PrintingPortal

e25f9f683dca3a0dcf4c90ae50515d7693447cb8

[ "MIT", "Unlicense" ]

null

from app import db from app.blueprints.printing.models import * from app.blueprints.auth.models import *

21.2

44

0.801887

16

106

5.3125

0.5

0.247059

0.4

0

0.122642

106

4

45

26.5

0.913978

0

1

0

true

0

1

0

1

0.666667

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

29e2f48e5a36d3aaac84e02312e8a2ca8448c94b

35,089

py

Python

0_joan_stark/lamp.py

wang0618/ascii-art

7ce6f152541716034bf0a22d341a898b17e2865f

[ "MIT" ]

1

2021-08-29T09:52:06.000Z

0_joan_stark/lamp.py

wang0618/ascii-art

7ce6f152541716034bf0a22d341a898b17e2865f

[ "MIT" ]

null

0_joan_stark/lamp.py

wang0618/ascii-art

7ce6f152541716034bf0a22d341a898b17e2865f

[ "MIT" ]

null

# Genie in a Lamp # https://web.archive.org/web/20000229125939/http://www.geocities.com/SoHo/Gallery/6446/mlamp.htm duration = 200 name = "Aladdin" frames = [ " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " ()\n" + " <^^>\n" + " .-\"\"-. \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " ()\n" + " <^^>\n" + " .-\"\"-. \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " ()\n" + " <^^> * \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " ()\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " `\\' \\'\\`'----'\n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " `-._ `~` `-,./_<\n" + " `\\' \\'\\`'----'\n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " \n" + " \\ \\_.-./=\\.-._ __\n" + " `-._ `~` `-,./_<\n" + " `\\' \\'\\`'----'\n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " \n" + " / / \\ c /O\n" + " \\ \\_.-./=\\.-._ __\n" + " `-._ `~` `-,./_<\n" + " `\\' \\'\\`'----'\n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " \n" + " / _<( ^.^ )\n" + " / / \\ c /O\n" + " \\ \\_.-./=\\.-._ __\n" + " `-._ `~` `-,./_<\n" + " `\\' \\'\\`'----'\n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " \n" + " ___\\__/__/\n" + " / _<( ^.^ )\n" + " / / \\ c /O\n" + " \\ \\_.-./=\\.-._ __\n" + " `-._ `~` `-,./_<\n" + " `\\' \\'\\`'----'\n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. ( \n" + " .\"-....-\".\n" + " jgs .':. `. \n" + " \"-..______..-\" ", " \n" + " \n" + " / ! )\\\n" + " ___\\__/__/\n" + " / _<( ^.^ )\n" + " / / \\ c /O\n" + " \\ \\_.-./=\\.-._ __\n" + " `-._ `~` `-,./_<\n" + " `\\' \\'\\`'----'\n" + " * \\ . \\ *\n" + " `-~~~\\ .\n" + " . `-._`-._ *\n" + " * `~~~-, \n" + " () ) *\n" + " <^^> * ( \n" + " .-\"\"-. )* \n" + " .---. .\"-....-\"-._ _...---''`/\n" + " ( (`\\ \\ .' ``-'' _.-\"'`\n" + " \\ \\ \\ : :. .-'\n" + " `\\`.\\: `:. _.'\n" + " ( .'`.` _.'\n" + " `` `-..______.-'\n" + " ):. 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d9b2055b16e6617b69be689c0ed46fc395f5b9c6

52,317

py

Python

test/unit/samplot_test.py

mchowdh200/samplot

780094b6d694e0c1194c17d4ed33e06f7ce56975

[ "MIT" ]

1

2021-01-16T05:58:57.000Z

test/unit/samplot_test.py

mchowdh200/samplot

780094b6d694e0c1194c17d4ed33e06f7ce56975

[ "MIT" ]

null

test/unit/samplot_test.py

mchowdh200/samplot

780094b6d694e0c1194c17d4ed33e06f7ce56975

[ "MIT" ]

null

import unittest import sys sys.path.append('../../src/') import samplot bam_1 = '../data/NA12878_restricted.bam' bam_2 = '../data/NA12889_restricted.bam' bam_3 = '../data/NA12890_restricted.bam' bams=[bam_1, bam_2, bam_3] sv_chrm = 'chr4' sv_start = 115928730 sv_end = 115931875 sv_type = 'DEL' #{{{ class Test_set_plot_dimensions(unittest.TestCase): class Test_set_plot_dimensions(unittest.TestCase): #{{{ def test_set_plot_dimensions(self): def test_set_plot_dimensions(self): ''' def set_plot_dimensions(sv, sv_type, arg_plot_height, arg_plot_width, bams, annotation_files, transcript_file, arg_window, zoom): ''' plot_height = None plot_width = None annotation_files = None transcript_file = None zoom = None window = None sv = [samplot.genome_interval(sv_chrm,sv_start,sv_end)] # Test basic function where window is set to be proportional to SV size r_plot_height, r_plot_width, r_window, r_ranges = \ samplot.set_plot_dimensions(sv, sv_type, plot_height, plot_width, bams, annotation_files, transcript_file, window, zoom) self.assertEqual(r_plot_height, 5) self.assertEqual(r_plot_width, 8) this_window = int((sv_end - sv_start)/2) self.assertEqual( r_window, this_window) self.assertEqual( r_ranges[0], samplot.genome_interval(sv_chrm, sv_start - this_window, sv_end + this_window)) # Test to see if zoom is ignored when it is larger than window zoom = 10000 r_plot_height, r_plot_width, r_window, r_ranges = \ samplot.set_plot_dimensions(sv, sv_type, plot_height, plot_width, bams, annotation_files, transcript_file, window, zoom) self.assertEqual( r_ranges[0], samplot.genome_interval(sv_chrm, sv_start - this_window, sv_end + this_window)) # Test to see if zoom creates two ranges zoom = 100 r_plot_height, r_plot_width, r_window, r_ranges = \ samplot.set_plot_dimensions(sv, sv_type, plot_height, plot_width, bams, annotation_files, transcript_file, window, zoom) self.assertEqual( r_window, zoom) self.assertEqual( len(r_ranges), 2) self.assertEqual( r_ranges[0], samplot.genome_interval(sv_chrm, sv_start - zoom, sv_start + zoom,)) self.assertEqual( r_ranges[1], samplot.genome_interval(sv_chrm, sv_end - zoom, sv_end + zoom) ) # Test to multiple sv regions window = None zoom = None sv = [samplot.genome_interval(sv_chrm,sv_start,sv_start), samplot.genome_interval(sv_chrm,sv_end,sv_end)] r_plot_height, r_plot_width, r_window, r_ranges = \ samplot.set_plot_dimensions(sv, sv_type, plot_height, plot_width, bams, annotation_files, transcript_file, window, zoom) self.assertEqual( len(r_ranges), 2) self.assertEqual( r_ranges[0], samplot.genome_interval(sv_chrm, sv_start-1000, sv_start+1000) ) self.assertEqual( r_ranges[1], samplot.genome_interval(sv_chrm, sv_end-1000, sv_end+1000) ) #}}} #{{{def test_get_read_data(self): def test_get_read_data(self): ''' read_data,max_coverage = get_read_data(ranges, options.bams, options.reference, options.min_mqual, options.coverage_only, options.long_read, options.same_yaxis_scales, options.max_depth, options.z) ''' plot_height = None plot_width = None annotation_files = None transcript_file = None zoom = None window = None sv = [samplot.genome_interval(sv_chrm,sv_start,sv_end)] # Test basic function where window is set to be proportional to SV size r_plot_height, r_plot_width, r_window, r_ranges = \ samplot.set_plot_dimensions(sv, sv_type, plot_height, plot_width, bams, annotation_files, transcript_file, window, zoom) reference = None min_mqual = None coverage_only = None long_read = 1000 long_even_size = 100 same_yaxis_scales = None max_depth = 100 z = 4 read_data,max_coverage = samplot.get_read_data(r_ranges, bams, reference, min_mqual, coverage_only, long_read, long_even_size, same_yaxis_scales, max_depth, z) #}}} #}}} #{{{ class Test_genome_interval(unittest.TestCase): class Test_genome_interval(unittest.TestCase): #{{{ def test_init(self): def test_init(self): gi = samplot.genome_interval('chr1', 1, 1000) self.assertEqual(gi.chrm, 'chr1') self.assertEqual(gi.start, 1) self.assertEqual(gi.end, 1000) #}}} #{{{ def test_init(self): def test_intersect(self): gi = samplot.genome_interval('chr8', 500, 1000) self.assertEqual(-1, gi.intersect(samplot.genome_interval('chr7', 500, 1000))) self.assertEqual(1, gi.intersect(samplot.genome_interval('chr9', 500, 1000))) self.assertEqual(-1, gi.intersect(samplot.genome_interval('chr8', 100, 499))) self.assertEqual(1, gi.intersect(samplot.genome_interval('chr8', 1001, 2000))) self.assertEqual(0, gi.intersect(samplot.genome_interval('chr8', 1, 500))) self.assertEqual(0, gi.intersect(samplot.genome_interval('chr8', 500, 501))) self.assertEqual(0, gi.intersect(samplot.genome_interval('chr8', 1000, 2000))) #}}} #{{{ def test_get_range_hit(self): def test_get_range_hit(self): gi_0 = samplot.genome_interval('chr8', 500, 1000) ranges = [gi_0] self.assertEqual(0, samplot.get_range_hit(ranges, 'chr8', 500)) gi_1 = samplot.genome_interval('chr8', 2000, 3000) ranges = [gi_0, gi_1] self.assertEqual(0, samplot.get_range_hit(ranges, 'chr8', 500)) self.assertEqual(1, samplot.get_range_hit(ranges, 'chr8', 2500)) self.assertEqual(None, samplot.get_range_hit(ranges, 'chr7', 2500)) self.assertEqual(None, samplot.get_range_hit(ranges, 'chr8', 100)) self.assertEqual(None, samplot.get_range_hit(ranges, 'chr8', 10000)) #}}} #{{{ def test_map_genome_point_to_range_points(self): def test_map_genome_point_to_range_points(self): gi_0 = samplot.genome_interval('chr8', 100, 200) ranges = [gi_0] self.assertEqual(None, samplot.map_genome_point_to_range_points(ranges, 'chr8', 10)) self.assertEqual(0.0, samplot.map_genome_point_to_range_points(ranges, 'chr8', 100)) self.assertEqual(0.25, samplot.map_genome_point_to_range_points(ranges, 'chr8', 125)) self.assertEqual(0.5, samplot.map_genome_point_to_range_points(ranges, 'chr8', 150)) self.assertEqual(0.75, samplot.map_genome_point_to_range_points(ranges, 'chr8', 175)) self.assertEqual(1.0, samplot.map_genome_point_to_range_points(ranges, 'chr8', 200)) self.assertEqual(None, samplot.map_genome_point_to_range_points(ranges, 'chr8', 201)) gi_1 = samplot.genome_interval('chr8', 300, 400) ranges = [gi_0, gi_1] self.assertEqual(None, samplot.map_genome_point_to_range_points(ranges, 'chr8', 10)) self.assertEqual(0.0, samplot.map_genome_point_to_range_points(ranges, 'chr8', 100)) self.assertEqual(0.25/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 125)) self.assertEqual(0.5/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 150)) self.assertEqual(0.75/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 175)) self.assertEqual(1.0/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 200)) self.assertEqual(None, samplot.map_genome_point_to_range_points(ranges, 'chr8', 201)) self.assertEqual(0.5, samplot.map_genome_point_to_range_points(ranges, 'chr8', 300)) self.assertEqual(0.5+0.25/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 325)) self.assertEqual(0.5+0.5/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 350)) self.assertEqual(0.5+0.75/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 375)) self.assertEqual(1.0, samplot.map_genome_point_to_range_points(ranges, 'chr8', 400)) gi_0 = samplot.genome_interval('chr8', 100, 200) gi_1 = samplot.genome_interval('chr9', 300, 400) ranges = [gi_0, gi_1] self.assertEqual(None, samplot.map_genome_point_to_range_points(ranges, 'chr8', 10)) self.assertEqual(0.0, samplot.map_genome_point_to_range_points(ranges, 'chr8', 100)) self.assertEqual(0.25/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 125)) self.assertEqual(0.5/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 150)) self.assertEqual(0.75/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 175)) self.assertEqual(1.0/2, samplot.map_genome_point_to_range_points(ranges, 'chr8', 200)) self.assertEqual(None, samplot.map_genome_point_to_range_points(ranges, 'chr8', 201)) self.assertEqual(0.5, samplot.map_genome_point_to_range_points(ranges, 'chr9', 300)) self.assertEqual(0.5+0.25/2, samplot.map_genome_point_to_range_points(ranges, 'chr9', 325)) self.assertEqual(0.5+0.5/2, samplot.map_genome_point_to_range_points(ranges, 'chr9', 350)) self.assertEqual(0.5+0.75/2, samplot.map_genome_point_to_range_points(ranges, 'chr9', 375)) self.assertEqual(1.0, samplot.map_genome_point_to_range_points(ranges, 'chr9', 400)) #}}} #}}} #{{{ class Test_long_read_plan(unittest.TestCase): class Test_long_read_plan(unittest.TestCase): #{{{ def test_init(self): def test_add_align_step(self): alignment = samplot.Alignment('chr8', 100, 500, True, 0) # both are in the same range gi_0 = samplot.genome_interval('chr8', 100, 1000) ranges = [gi_0] steps = [] samplot.add_align_step(alignment, steps, ranges) self.assertEqual(1, len(steps)) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(500, steps[0].end_pos.start) self.assertEqual(500, steps[0].end_pos.end) self.assertEqual('Align', steps[0].info['TYPE']) # in different ranges gi_0 = samplot.genome_interval('chr8', 100, 200) gi_1 = samplot.genome_interval('chr8', 300, 1000) ranges = [gi_0, gi_1] steps = [] samplot.add_align_step(alignment, steps, ranges) self.assertEqual(2, len(steps)) #start self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) #end self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(200, steps[0].end_pos.start) self.assertEqual(200, steps[0].end_pos.end) #event self.assertEqual('Align', steps[0].info['TYPE']) #start self.assertEqual('chr8', steps[1].start_pos.chrm) self.assertEqual(300, steps[1].start_pos.start) self.assertEqual(300, steps[1].start_pos.end) #end self.assertEqual('chr8', steps[1].end_pos.chrm) self.assertEqual(500, steps[1].end_pos.start) self.assertEqual(500, steps[1].end_pos.end) #event self.assertEqual('Align', steps[1].info['TYPE']) # start is not in range, use end hit gi_0 = samplot.genome_interval('chr8', 10, 20) gi_1 = samplot.genome_interval('chr8', 300, 1000) ranges = [gi_0, gi_1] steps = [] samplot.add_align_step(alignment, steps, ranges) self.assertEqual(1, len(steps)) #start self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(300, steps[0].start_pos.start) self.assertEqual(300, steps[0].start_pos.end) #end self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(500, steps[0].end_pos.start) self.assertEqual(500, steps[0].end_pos.end) #event self.assertEqual('Align', steps[0].info['TYPE']) # end is not in range, use start hit gi_0 = samplot.genome_interval('chr8', 100, 200) gi_1 = samplot.genome_interval('chr8', 3000, 4000) ranges = [gi_0, gi_1] steps = [] samplot.add_align_step(alignment, steps, ranges) #start self.assertEqual(1, len(steps)) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) #end self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(200, steps[0].end_pos.end) self.assertEqual(200, steps[0].end_pos.start) #event self.assertEqual('Align', steps[0].info['TYPE']) # neither end is in range, add nothing gi_0 = samplot.genome_interval('chr8', 10, 20) gi_1 = samplot.genome_interval('chr8', 3000, 4000) ranges = [gi_0, gi_1] steps = [] samplot.add_align_step(alignment, steps, ranges) self.assertEqual(0, len(steps)) #}}} #{{{def test_get_alignments_from_cigar(self): def test_get_alignments_from_cigar(self): ''' alignments = get_alignments_from_cigar( bam_file.get_reference_name(read.reference_id), read.pos, not read.is_reverse, read.cigartuples) ''' CIGAR_MAP = { 'M' : 0, 'I' : 1, 'D' : 2, 'N' : 3, 'S' : 4, 'H' : 5, 'P' : 6, '=' : 7, 'X' : 8, 'B' : 9 } cigar = [(CIGAR_MAP['M'], 100), (CIGAR_MAP['D'], 100), (CIGAR_MAP['M'], 100)] alignments = samplot.get_alignments_from_cigar('chr8', 100, True, cigar) self.assertEqual(2,len(alignments)) self.assertEqual('chr8', alignments[0].pos.chrm) self.assertEqual(100, alignments[0].pos.start) self.assertEqual(200, alignments[0].pos.end) self.assertEqual(True, alignments[0].strand) self.assertEqual(0, alignments[0].query_position) self.assertEqual('chr8', alignments[1].pos.chrm) self.assertEqual(300, alignments[1].pos.start) self.assertEqual(400, alignments[1].pos.end) self.assertEqual(True, alignments[1].strand) self.assertEqual(100, alignments[1].query_position) #}}} #{{{def test_get_long_read_plan(self): def test_get_long_read_plan(self): gi_0 = samplot.genome_interval('chr8', 100, 250) gi_1 = samplot.genome_interval('chr8', 300, 400) ranges = [gi_0, gi_1] long_reads = {} read_name = 'Test' alignments = [samplot.Alignment('chr8', 100, 200, True, 0)] long_reads[read_name] = [ samplot.LongRead(alignments) ] max_gap, steps = samplot.get_long_read_plan(read_name, long_reads, ranges) self.assertEqual(0, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(200, steps[0].end_pos.start) self.assertEqual(200, steps[0].end_pos.end) self.assertEqual('LONGREAD', steps[0].event) self.assertEqual('Align', steps[0].info['TYPE']) alignments = [samplot.Alignment('chr8', 100, 299, True, 0)] long_reads[read_name] = [ samplot.LongRead(alignments) ] max_gap, steps = samplot.get_long_read_plan(read_name, long_reads, ranges) self.assertEqual(0, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(250, steps[0].end_pos.start) self.assertEqual(250, steps[0].end_pos.end) self.assertEqual('Align', steps[0].info['TYPE']) alignments = [samplot.Alignment('chr8', 100, 350, True, 0)] long_reads[read_name] = [ samplot.LongRead(alignments) ] max_gap, steps = samplot.get_long_read_plan(read_name, long_reads, ranges) self.assertEqual(0, max_gap) self.assertEqual(2, len(steps)) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(250, steps[0].end_pos.start) self.assertEqual(250, steps[0].end_pos.end) self.assertEqual('Align', steps[0].info['TYPE']) self.assertEqual('chr8', steps[1].start_pos.chrm) self.assertEqual(300, steps[1].start_pos.start) self.assertEqual(300, steps[1].start_pos.end) self.assertEqual('chr8', steps[1].end_pos.chrm) self.assertEqual(350, steps[1].end_pos.start) self.assertEqual(350, steps[1].end_pos.end) self.assertEqual('Align', steps[1].info['TYPE']) alignments = [samplot.Alignment('chr8', 100, 250, True, 0), samplot.Alignment('chr8', 300, 350, True, 150)] long_reads[read_name] = [ samplot.LongRead(alignments) ] max_gap, steps = samplot.get_long_read_plan(read_name, long_reads, ranges) self.assertEqual(50, max_gap) self.assertEqual(3, len(steps)) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(250, steps[0].end_pos.start) self.assertEqual(250, steps[0].end_pos.end) self.assertEqual('Align', steps[0].info['TYPE']) self.assertEqual('chr8', steps[1].start_pos.chrm) self.assertEqual(250, steps[1].start_pos.start) self.assertEqual(250, steps[1].start_pos.end) self.assertEqual('chr8', steps[1].end_pos.chrm) self.assertEqual(300, steps[1].end_pos.start) self.assertEqual(300, steps[1].end_pos.end) self.assertEqual('Deletion', steps[1].info['TYPE']) self.assertEqual('chr8', steps[2].start_pos.chrm) self.assertEqual(300, steps[2].start_pos.start) self.assertEqual(300, steps[2].start_pos.end) self.assertEqual('chr8', steps[2].end_pos.chrm) self.assertEqual(350, steps[2].end_pos.start) self.assertEqual(350, steps[2].end_pos.end) self.assertEqual('Align', steps[2].info['TYPE']) gi_0 = samplot.genome_interval('chr8', 100, 250) gi_1 = samplot.genome_interval('chr9', 300, 400) ranges = [gi_0, gi_1] alignments = [samplot.Alignment('chr8', 100, 250, True, 0), samplot.Alignment('chr9', 300, 350, True, 150)] long_reads[read_name] = [ samplot.LongRead(alignments) ] max_gap, steps = samplot.get_long_read_plan(read_name, long_reads, ranges) self.assertEqual(5000, max_gap) self.assertEqual(3, len(steps)) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(250, steps[0].end_pos.start) self.assertEqual(250, steps[0].end_pos.end) self.assertEqual('Align', steps[0].info['TYPE']) self.assertEqual('chr8', steps[1].start_pos.chrm) self.assertEqual(250, steps[1].start_pos.start) self.assertEqual(250, steps[1].start_pos.end) self.assertEqual('chr9', steps[1].end_pos.chrm) self.assertEqual(300, steps[1].end_pos.start) self.assertEqual(300, steps[1].end_pos.end) self.assertEqual('InterChrm', steps[1].info['TYPE']) self.assertEqual('chr9', steps[2].start_pos.chrm) self.assertEqual(300, steps[2].start_pos.start) self.assertEqual(300, steps[2].start_pos.end) self.assertEqual('chr9', steps[2].end_pos.chrm) self.assertEqual(350, steps[2].end_pos.start) self.assertEqual(350, steps[2].end_pos.end) self.assertEqual('Align', steps[2].info['TYPE']) #}}} #}}} #{{{class Test_annotation_plan(unittest.TestCase): class Test_annotation_plan(unittest.TestCase): #{{{def test_get_alignments_from_cigar(self): def test_get_alignments_from_cigar(self): gi_1 = samplot.genome_interval('chr8', 100, 200) gi_2 = samplot.genome_interval('chr8', 300, 400) ranges = [gi_1, gi_2] i = samplot.genome_interval('chr8', 110, 120) s, e = samplot.get_interval_range_plan_start_end(ranges, i) self.assertEqual('chr8',s.chrm) self.assertEqual(110,s.start) self.assertEqual(110,s.end) self.assertEqual('chr8',e.chrm) self.assertEqual(120,e.start) self.assertEqual(120,e.end) i = samplot.genome_interval('chr8', 110, 220) s, e = samplot.get_interval_range_plan_start_end(ranges, i) self.assertEqual('chr8',s.chrm) self.assertEqual(110,s.start) self.assertEqual(110,s.end) self.assertEqual('chr8',e.chrm) self.assertEqual(200,e.start) self.assertEqual(200,e.end) i = samplot.genome_interval('chr8', 220, 320) s, e = samplot.get_interval_range_plan_start_end(ranges, i) self.assertEqual('chr8',s.chrm) self.assertEqual(300,s.start) self.assertEqual(300,s.end) self.assertEqual('chr8',e.chrm) self.assertEqual(320,e.start) self.assertEqual(320,e.end) i = samplot.genome_interval('chr8', 120, 320) s, e = samplot.get_interval_range_plan_start_end(ranges, i) self.assertEqual('chr8',s.chrm) self.assertEqual(120,s.start) self.assertEqual(120,s.end) self.assertEqual('chr8',e.chrm) self.assertEqual(320,e.start) self.assertEqual(320,e.end) i = samplot.genome_interval('chr8', 320, 520) s, e = samplot.get_interval_range_plan_start_end(ranges, i) self.assertEqual('chr8',s.chrm) self.assertEqual(320,s.start) self.assertEqual(320,s.end) self.assertEqual('chr8',e.chrm) self.assertEqual(400,e.start) self.assertEqual(400,e.end) i = samplot.genome_interval('chr8', 30, 50) s, e = samplot.get_interval_range_plan_start_end(ranges, i) self.assertEqual(None, s) self.assertEqual(None, e) i = samplot.genome_interval('chr8', 3000, 5000) s, e = samplot.get_interval_range_plan_start_end(ranges, i) self.assertEqual(None, s) self.assertEqual(None, e) #}}} #}}} #{{{class Test_splits(unittest.TestCase): class Test_splits(unittest.TestCase): #{{{def test_get_split_plan(self): def test_get_split_plan(self): splits = {} hp = 0 splits[hp] = {} read_name_1 = 'Test1' ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr8', 600, 800) ] #both in same ragne #Deletion splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 170, 180, True, 50, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) max_gap, steps = plan self.assertEqual(20, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('SPLITREAD', steps[0].event) self.assertEqual('Deletion', steps[0].info['TYPE']) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(150, steps[0].start_pos.start) self.assertEqual(150, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(170, steps[0].end_pos.start) self.assertEqual(170, steps[0].end_pos.end) #Duplication splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 130, 180, True, 50, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) max_gap, steps = plan self.assertEqual(20, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('SPLITREAD', steps[0].event) self.assertEqual('Duplication', steps[0].info['TYPE']) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(150, steps[0].start_pos.start) self.assertEqual(150, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(130, steps[0].end_pos.start) self.assertEqual(130, steps[0].end_pos.end) #Inversion splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 151, 180, False, 50, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) max_gap, steps = plan self.assertEqual(30, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('SPLITREAD', steps[0].event) self.assertEqual('Inversion', steps[0].info['TYPE']) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(150, steps[0].start_pos.start) self.assertEqual(150, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(151, steps[0].end_pos.start) self.assertEqual(151, steps[0].end_pos.end) #both in same ragne splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) self.assertEqual(None, plan) #both in same ragne splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 550, 650, True, 0, False, False), samplot.SplitRead('chr8', 700, 750, True, 50, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) max_gap, steps = plan self.assertEqual(50, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('SPLITREAD', steps[0].event) self.assertEqual('Deletion', steps[0].info['TYPE']) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(650, steps[0].start_pos.start) self.assertEqual(650, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(700, steps[0].end_pos.start) self.assertEqual(700, steps[0].end_pos.end) #both in same ragne splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 150, 175, True, 0, False, False), samplot.SplitRead('chr8', 650, 675, True, 50, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) max_gap, steps = plan self.assertEqual(475, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('SPLITREAD', steps[0].event) self.assertEqual('Deletion', steps[0].info['TYPE']) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(175, steps[0].start_pos.start) self.assertEqual(175, steps[0].start_pos.end) self.assertEqual('chr8', steps[0].end_pos.chrm) self.assertEqual(650, steps[0].end_pos.start) self.assertEqual(650, steps[0].end_pos.end) #inter chrom ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr9', 600, 800) ] splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 150, 175, True, 0, False, False), samplot.SplitRead('chr9', 650, 675, True, 50, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) max_gap, steps = plan self.assertEqual(samplot.INTERCHROM_YAXIS, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('SPLITREAD', steps[0].event) self.assertEqual('InterChrm', steps[0].info['TYPE']) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(175, steps[0].start_pos.start) self.assertEqual(175, steps[0].start_pos.end) self.assertEqual('chr9', steps[0].end_pos.chrm) self.assertEqual(650, steps[0].end_pos.start) self.assertEqual(650, steps[0].end_pos.end) splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 150, 175, True, 0, False, False), samplot.SplitRead('chr9', 650, 675, False, 50, False, False)] plan = samplot.get_split_plan(ranges, splits[hp][read_name_1]) max_gap, steps = plan self.assertEqual(samplot.INTERCHROM_YAXIS, max_gap) self.assertEqual(1, len(steps)) self.assertEqual('SPLITREAD', steps[0].event) self.assertEqual('InterChrmInversion', steps[0].info['TYPE']) self.assertEqual('chr8', steps[0].start_pos.chrm) self.assertEqual(175, steps[0].start_pos.start) self.assertEqual(175, steps[0].start_pos.end) self.assertEqual('chr9', steps[0].end_pos.chrm) self.assertEqual(650, steps[0].end_pos.start) self.assertEqual(650, steps[0].end_pos.end) #}}} #{{{def test_get_splits_plan(self): def test_get_splits_plan(self): splits = {} hp = 0 splits[hp] = {} ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr9', 600, 800) ] #Deletion splits[hp]['del'] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 170, 180, True, 50, False, False)] #Duplication splits[hp]['dup'] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 130, 180, True, 50, False, False)] #Inversion splits[hp]['inv'] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 151, 180, False, 50, False, False)] #Bad split splits[hp]['bad'] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False)] #Interchm splits[hp]['interchm'] = [\ samplot.SplitRead('chr8', 150, 175, True, 0, False, False), samplot.SplitRead('chr9', 650, 675, True, 50, False, False)] #InterchmInv splits[hp]['interchminv'] = [\ samplot.SplitRead('chr8', 150, 175, True, 0, False, False), samplot.SplitRead('chr9', 650, 675, False, 50, False, False)] plan = samplot.get_splits_plan(ranges, splits[hp]) max_gap, steps = plan self.assertEqual(samplot.INTERCHROM_YAXIS, max_gap) self.assertEqual(5, len(steps)) #}}} #{{{def test_get_split_insert_size(self): def test_get_split_insert_size(self): splits = {} hp = 0 splits[hp] = {} read_name_1 = 'Test1' #both in same ragne splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 170, 180, True, 50, False, False)] read_name_2 = 'Test2' splits[hp][read_name_2] = [\ samplot.SplitRead('chr8', 100, 150, True, 0, False, False), samplot.SplitRead('chr8', 170, 180, True, 50, False, False)] ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr8', 600, 800) ] split_insert_sizes = samplot.get_splits_insert_sizes(ranges, splits) self.assertEqual(2, len(split_insert_sizes)) self.assertEqual(20, split_insert_sizes[0]) self.assertEqual(20, split_insert_sizes[1]) #one starting in range ends out of range splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 100, 350, True, 0, False, False), samplot.SplitRead('chr8', 650, 700, True, 250, False, False)] split_insert_sizes = samplot.get_splits_insert_sizes(ranges, splits) self.assertEqual(2, len(split_insert_sizes)) self.assertEqual(300, split_insert_sizes[0]) self.assertEqual(20, split_insert_sizes[1]) #one out of range splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 10, 35, True, 0, False, False), samplot.SplitRead('chr8', 650, 700, True, 25, False, False)] split_insert_sizes = samplot.get_splits_insert_sizes(ranges, splits) self.assertEqual(1, len(split_insert_sizes)) self.assertEqual(20, split_insert_sizes[0]) #DUP splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 125, 150, True, 0, False, False), samplot.SplitRead('chr8', 130, 155, True, 25, False, False)] split_insert_sizes = samplot.get_splits_insert_sizes(ranges, splits) self.assertEqual(2, len(split_insert_sizes)) self.assertEqual(20, split_insert_sizes[0]) self.assertEqual(20, split_insert_sizes[1]) #INV splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 125, 150, True, 0, False, False), samplot.SplitRead('chr8', 151, 175, False, 25, False, False)] split_insert_sizes = samplot.get_splits_insert_sizes(ranges, splits) self.assertEqual(2, len(split_insert_sizes)) self.assertEqual(25, split_insert_sizes[0]) self.assertEqual(20, split_insert_sizes[1]) #interchrm ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr9', 600, 800) ] splits[hp][read_name_1] = [\ samplot.SplitRead('chr8', 125, 150, True, 0, False, False), samplot.SplitRead('chr9', 650, 675, True, 25, False, False)] split_insert_sizes = samplot.get_splits_insert_sizes(ranges, splits) self.assertEqual(2, len(split_insert_sizes)) self.assertEqual(samplot.INTERCHROM_YAXIS, split_insert_sizes[0]) self.assertEqual(20, split_insert_sizes[1]) #}}} #}}} #{{{ class Test_pairs(unittest.TestCase): class Test_pairs(unittest.TestCase): #{{{ def test_get_pair_insert_size(self): def test_get_pair_insert_size(self): ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr8', 600, 800) ] pairs = {} hp = 0 pairs[hp] = {} read_name_1 = 'Test1' #both in same ragne pairs[hp][read_name_1] = [\ samplot.PairedEnd('chr8', 100, 150, True, False, False), samplot.PairedEnd('chr8', 170, 180, False, False, False)] read_name_2 = 'Test2' pairs[hp][read_name_2] = [\ samplot.PairedEnd('chr8', 100, 150, True, False, False), samplot.PairedEnd('chr8', 170, 180, False, False, False)] pair_insert_sizes = samplot.get_pairs_insert_sizes(ranges, pairs) self.assertEqual(2, len(pair_insert_sizes)) self.assertEqual(80, pair_insert_sizes[0]) self.assertEqual(80, pair_insert_sizes[1]) #one starting in range ends out of range pairs[hp][read_name_1] = [\ samplot.PairedEnd('chr8', 100, 150, True, False, False), samplot.PairedEnd('chr8', 190, 240, False, False, False)] pair_insert_sizes = samplot.get_pairs_insert_sizes(ranges, pairs) self.assertEqual(2, len(pair_insert_sizes)) self.assertEqual(140, pair_insert_sizes[0]) self.assertEqual(80, pair_insert_sizes[1]) #one out of range pairs[hp][read_name_1] = [\ samplot.PairedEnd('chr9', 100, 150, True, False, False), samplot.PairedEnd('chr8', 190, 240, False, False, False)] pair_insert_sizes = samplot.get_pairs_insert_sizes(ranges, pairs) self.assertEqual(1, len(pair_insert_sizes)) self.assertEqual(80, pair_insert_sizes[0]) #DUP pairs[hp][read_name_1] = [\ samplot.PairedEnd('chr8', 125, 150, True, False, False), samplot.PairedEnd('chr8', 175, 200, False, False, False)] pair_insert_sizes = samplot.get_pairs_insert_sizes(ranges, pairs) self.assertEqual(2, len(pair_insert_sizes)) self.assertEqual(75, pair_insert_sizes[0]) self.assertEqual(80, pair_insert_sizes[1]) #INV pairs[hp][read_name_1] = [\ samplot.PairedEnd('chr8', 125, 150, True, False, False), samplot.PairedEnd('chr8', 175, 200, True, False, False)] pair_insert_sizes = samplot.get_pairs_insert_sizes(ranges, pairs) self.assertEqual(2, len(pair_insert_sizes)) self.assertEqual(75, pair_insert_sizes[0]) self.assertEqual(80, pair_insert_sizes[1]) #interchrm ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr9', 600, 800) ] pairs[hp][read_name_1] = [\ samplot.PairedEnd('chr8', 125, 150, True, False, False), samplot.PairedEnd('chr9', 675, 700, True, False, False)] pair_insert_sizes = samplot.get_pairs_insert_sizes(ranges, pairs) self.assertEqual(2, len(pair_insert_sizes)) self.assertEqual(samplot.INTERCHROM_YAXIS, pair_insert_sizes[0]) self.assertEqual(80, pair_insert_sizes[1]) #}}} #{{{ def test_get_pair_plan(self): def test_get_pair_plan(self): ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr8', 600, 800) ] pairs = {} hp = 0 pairs[hp] = {} read_name_1 = 'Test1' #both in same ragne pairs[hp][read_name_1] = [\ samplot.PairedEnd('chr8', 100, 150, False, False, False), samplot.PairedEnd('chr8', 170, 180, True, False, False)] read_name_2 = 'Test2' pairs[hp][read_name_2] = [\ samplot.PairedEnd('chr8', 100, 150, False, False, False), samplot.PairedEnd('chr8', 170, 180, True, False, False)] max_event, steps = samplot.get_pairs_plan(ranges, pairs[hp]) self.assertEqual(80, max_event) self.assertEqual(2, len(steps)) #}}} #}}} #{{{ class Test_linked(unittest.TestCase): class Test_linked(unittest.TestCase): #{{{def test_get_split_insert_size(self): def test_get_linked_plan(self): ranges = [samplot.genome_interval('chr8', 100, 200), samplot.genome_interval('chr8', 600, 800) ] pairs = {} hp = 0 pairs[hp] = {} pairs[hp]['PE_1'] = [\ samplot.PairedEnd('chr8', 100, 150, False, False, False), samplot.PairedEnd('chr8', 170, 180, True, False, False)] pairs[hp]['PE_2'] = [\ samplot.PairedEnd('chr8', 110, 160, False, False, False), samplot.PairedEnd('chr8', 680, 690, True, False, False)] splits = {} splits[hp] = {} splits[hp]['SR_1'] = [\ samplot.SplitRead('chr8', 155, 160, True, 0, False, False), samplot.SplitRead('chr8', 670, 675, True, 50, False, False)] linked_reads = {} linked_reads[hp] = {} MI = 5 linked_reads[hp][MI] = [[],[]] linked_reads[hp][MI][0].append('PE_1') linked_reads[hp][MI][0].append('PE_2') linked_reads[hp][MI][1].append('SR_1') max_event, steps = samplot.get_linked_plan(ranges, pairs[hp], splits[hp], linked_reads[hp], MI) self.assertEqual(580, max_event) self.assertEqual(2, len(steps)) self.assertEqual(2, len(steps[0].info['PAIR_STEPS'])) self.assertEqual(1, len(steps[0].info['SPLIT_STEPS'])) self.assertEqual(100, steps[0].start_pos.start) self.assertEqual(100, steps[0].start_pos.end) self.assertEqual(ranges[0].end, steps[0].end_pos.start) self.assertEqual(ranges[0].end, steps[0].end_pos.end) self.assertEqual(ranges[1].start, steps[1].start_pos.start) self.assertEqual(ranges[1].start, steps[1].start_pos.end) self.assertEqual(690, steps[1].end_pos.start) self.assertEqual(690, steps[1].end_pos.end) self.assertEqual(100,steps[0].info['PAIR_STEPS'][0].start_pos.start) self.assertEqual(100,steps[0].info['PAIR_STEPS'][0].start_pos.end) self.assertEqual(180,steps[0].info['PAIR_STEPS'][0].end_pos.start) self.assertEqual(180,steps[0].info['PAIR_STEPS'][0].end_pos.end) self.assertEqual(110,steps[0].info['PAIR_STEPS'][1].start_pos.start) self.assertEqual(110,steps[0].info['PAIR_STEPS'][1].start_pos.end) self.assertEqual(690,steps[0].info['PAIR_STEPS'][1].end_pos.start) self.assertEqual(690,steps[0].info['PAIR_STEPS'][1].end_pos.end) self.assertEqual(160,steps[0].info['SPLIT_STEPS'][0].start_pos.start) self.assertEqual(160,steps[0].info['SPLIT_STEPS'][0].start_pos.end) self.assertEqual(670,steps[0].info['SPLIT_STEPS'][0].end_pos.start) self.assertEqual(670,steps[0].info['SPLIT_STEPS'][0].end_pos.end) #}}} #}}} if __name__ == '__main__': unittest.main()

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d9cf739f7ae8c5fa72f25c4c260720eef62183a2

6,691

py

Python

tf_quant_finance/experimental/instruments/overnight_index_linked_futures_test.py

slowy07/tf-quant-finance

0976f720fb58a2d7bfd863640c12a2425cd2f94f

[ "Apache-2.0" ]

3,138

2019-07-24T21:43:17.000Z

2022-03-30T12:11:09.000Z

tf_quant_finance/experimental/instruments/overnight_index_linked_futures_test.py

Aarif1430/tf-quant-finance

9372eb1ddf2b48cb1a3d4283bc67a10647ddc7a6

[ "Apache-2.0" ]

63

2019-09-07T19:16:03.000Z

2022-03-29T19:29:40.000Z

tf_quant_finance/experimental/instruments/overnight_index_linked_futures_test.py

Aarif1430/tf-quant-finance

9372eb1ddf2b48cb1a3d4283bc67a10647ddc7a6

[ "Apache-2.0" ]

423

2019-07-26T21:28:05.000Z

2022-03-26T13:07:44.000Z

# Lint as: python3 # Copyright 2020 Google LLC # # 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 # # https://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. """Tests for overnight_index_linked_futures.py.""" from absl.testing import parameterized import numpy as np import tensorflow.compat.v2 as tf import tf_quant_finance as tff from tensorflow.python.framework import test_util # pylint: disable=g-direct-tensorflow-import dates = tff.datetime instruments = tff.experimental.instruments @test_util.run_all_in_graph_and_eager_modes class OvernightIndexLinkedFuturesTest(tf.test.TestCase, parameterized.TestCase): @parameterized.named_parameters( ('DoublePrecision', np.float64), ) def test_fut_compounded(self, dtype): cal = dates.create_holiday_calendar(weekend_mask=dates.WeekendMask.NONE) start_date = dates.convert_to_date_tensor([(2020, 5, 1)]) end_date = dates.convert_to_date_tensor([(2020, 5, 31)]) valuation_date = dates.convert_to_date_tensor([(2020, 2, 8)]) indexfuture = instruments.OvernightIndexLinkedFutures( start_date, end_date, holiday_calendar=cal, averaging_type=instruments.AverageType.COMPOUNDING, dtype=dtype) curve_dates = valuation_date + dates.months([1, 2, 6]) reference_curve = instruments.RateCurve( curve_dates, np.array([0.02, 0.025, 0.015], dtype=dtype), valuation_date=valuation_date, dtype=dtype) market = tff.experimental.instruments.InterestRateMarket( reference_curve=reference_curve, discount_curve=None) price = self.evaluate(indexfuture.price(valuation_date, market)) np.testing.assert_allclose(price, 98.64101997, atol=1e-6) @parameterized.named_parameters( ('DoublePrecision', np.float64), ) def test_fut_averaged(self, dtype): cal = dates.create_holiday_calendar(weekend_mask=dates.WeekendMask.NONE) start_date = dates.convert_to_date_tensor([(2020, 5, 1)]) end_date = dates.convert_to_date_tensor([(2020, 5, 31)]) valuation_date = dates.convert_to_date_tensor([(2020, 2, 8)]) indexfuture = instruments.OvernightIndexLinkedFutures( start_date, end_date, averaging_type=instruments.AverageType.ARITHMETIC_AVERAGE, holiday_calendar=cal, dtype=dtype) curve_dates = valuation_date + dates.months([1, 2, 6]) reference_curve = instruments.RateCurve( curve_dates, np.array([0.02, 0.025, 0.015], dtype=dtype), valuation_date=valuation_date, dtype=dtype) market = tff.experimental.instruments.InterestRateMarket( reference_curve=reference_curve, discount_curve=None) price = self.evaluate(indexfuture.price(valuation_date, market)) np.testing.assert_allclose(price, 98.6417886, atol=1e-6) @parameterized.named_parameters( ('DoublePrecision', np.float64), ) def test_fut_compounded_calendar(self, dtype): cal = dates.create_holiday_calendar( weekend_mask=dates.WeekendMask.SATURDAY_SUNDAY) start_date = dates.convert_to_date_tensor([(2020, 5, 1)]) end_date = dates.convert_to_date_tensor([(2020, 5, 31)]) valuation_date = dates.convert_to_date_tensor([(2020, 2, 8)]) indexfuture = instruments.OvernightIndexLinkedFutures( start_date, end_date, holiday_calendar=cal, averaging_type=instruments.AverageType.COMPOUNDING, dtype=dtype) curve_dates = valuation_date + dates.months([1, 2, 6]) reference_curve = instruments.RateCurve( curve_dates, np.array([0.02, 0.025, 0.015], dtype=dtype), valuation_date=valuation_date, dtype=dtype) market = tff.experimental.instruments.InterestRateMarket( reference_curve=reference_curve, discount_curve=None) price = self.evaluate(indexfuture.price(valuation_date, market)) np.testing.assert_allclose(price, 98.6332129, atol=1e-6) @parameterized.named_parameters( ('DoublePrecision', np.float64), ) def test_fut_averaged_calendar(self, dtype): cal = dates.create_holiday_calendar( weekend_mask=dates.WeekendMask.SATURDAY_SUNDAY) start_date = dates.convert_to_date_tensor([(2020, 5, 1)]) end_date = dates.convert_to_date_tensor([(2020, 5, 31)]) valuation_date = dates.convert_to_date_tensor([(2020, 2, 8)]) indexfuture = instruments.OvernightIndexLinkedFutures( start_date, end_date, averaging_type=instruments.AverageType.ARITHMETIC_AVERAGE, holiday_calendar=cal, dtype=dtype) curve_dates = valuation_date + dates.months([1, 2, 6]) reference_curve = instruments.RateCurve( curve_dates, np.array([0.02, 0.025, 0.015], dtype=dtype), valuation_date=valuation_date, dtype=dtype) market = tff.experimental.instruments.InterestRateMarket( reference_curve=reference_curve, discount_curve=None) price = self.evaluate(indexfuture.price(valuation_date, market)) np.testing.assert_allclose(price, 98.63396465, atol=1e-6) @parameterized.named_parameters( ('DoublePrecision', np.float64), ) def test_fut_many(self, dtype): cal = dates.create_holiday_calendar(weekend_mask=dates.WeekendMask.NONE) start_date = dates.convert_to_date_tensor([(2020, 5, 1), (2020, 5, 1)]) end_date = dates.convert_to_date_tensor([(2020, 5, 31), (2020, 5, 31)]) valuation_date = dates.convert_to_date_tensor([(2020, 2, 8)]) indexfuture = instruments.OvernightIndexLinkedFutures( start_date, end_date, holiday_calendar=cal, averaging_type=instruments.AverageType.COMPOUNDING, dtype=dtype) curve_dates = valuation_date + dates.months([1, 2, 6]) reference_curve = instruments.RateCurve( curve_dates, np.array([0.02, 0.025, 0.015], dtype=dtype), valuation_date=valuation_date, dtype=dtype) market = tff.experimental.instruments.InterestRateMarket( reference_curve=reference_curve, discount_curve=None) price = self.evaluate(indexfuture.price(valuation_date, market)) np.testing.assert_allclose(price, [98.64101997, 98.64101997], atol=1e-6) if __name__ == '__main__': tf.test.main()

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8a4282b7092d1b82fab471cd450754e6ce4cac3b

12,119

py

Python

opendr/__init__.py

foamliu/opendr

d75b1a95806bc0e8c6cc400b016fb31d2ca3c7b7

[ "MIT" ]

363

2015-02-08T20:51:30.000Z

2022-03-27T08:56:40.000Z

opendr/__init__.py

MF1523017/opendr

bc16a6a51771d6e062d088ba5cede66649b7c7ec

[ "MIT" ]

41

2015-06-26T14:59:15.000Z

2021-12-28T03:24:18.000Z

opendr/__init__.py

MF1523017/opendr

bc16a6a51771d6e062d088ba5cede66649b7c7ec

[ "MIT" ]

118

2015-01-15T21:53:08.000Z

2021-10-04T13:49:44.000Z

from .version import version as __version__ def test(): from os.path import split import unittest test_loader = unittest.TestLoader() test_loader = test_loader.discover(split(__file__)[0]) test_runner = unittest.TextTestRunner() test_runner.run( test_loader ) demos = {} demos['texture'] = """ # Create renderer import chumpy as ch from opendr.renderer import TexturedRenderer rn = TexturedRenderer() # Assign attributes to renderer from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,4]), rotation=ch.zeros(3)) w, h = (320, 240) from opendr.camera import ProjectPoints rn.camera = ProjectPoints(v=m.v, rt=ch.zeros(3), t=ch.zeros(3), f=ch.array([w,w])/2., c=ch.array([w,h])/2., k=ch.zeros(5)) rn.frustum = {'near': 1., 'far': 10., 'width': w, 'height': h} rn.set(v=m.v, f=m.f, vc=m.vc, texture_image=m.texture_image, ft=m.ft, vt=m.vt) # Show it import matplotlib.pyplot as plt plt.ion() plt.imshow(rn.r) plt.show() dr = rn.dr_wrt(rn.v) # or rn.vc, or rn.camera.rt, rn.camera.t, rn.camera.f, rn.camera.c, etc """ demos['moments'] = """ from opendr.util_tests import get_earthmesh from opendr.simple import * import numpy as np w, h = 320, 240 m = get_earthmesh(trans=ch.array([0,0,4]), rotation=ch.zeros(3)) # Create V, A, U, f: geometry, brightness, camera, renderer V = ch.array(m.v) A = SphericalHarmonics(vn=VertNormals(v=V, f=m.f), components=[3.,1.,0.,0.,0.,0.,0.,0.,0.], light_color=ch.ones(3)) U = ProjectPoints(v=V, f=[300,300.], c=[w/2.,h/2.], k=ch.zeros(5), t=ch.zeros(3), rt=ch.zeros(3)) rn = TexturedRenderer(vc=A, camera=U, f=m.f, bgcolor=[0.,0.,0.], texture_image=m.texture_image, vt=m.vt, ft=m.ft, frustum={'width':w, 'height':h, 'near':1,'far':20}) i, j = ch.array([2.]), ch.array([1.]) xs, ys = ch.meshgrid(range(rn.shape[1]), range(rn.shape[0])) ysp = ys ** j xsp = xs ** i rn_bw = ch.sum(rn, axis=2) moment = ch.sum((rn_bw * ysp * xsp).ravel()) # Print our numerical result print moment # Note that opencv produces the same result for 'm21', # and that other moments can be created by changing "i" and "j" above import cv2 print cv2.moments(rn_bw.r)['m21'] # Derivatives wrt vertices and lighting print moment.dr_wrt(V) print moment.dr_wrt(A.components) """ demos['per_face_normals'] = """ # Create renderer import chumpy as ch import numpy as np from opendr.renderer import ColoredRenderer from opendr.lighting import LambertianPointLight rn = ColoredRenderer() # Assign attributes to renderer from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,4]), rotation=ch.zeros(3)) w, h = (320, 240) # THESE ARE THE 3 CRITICAL LINES m.v = m.v[m.f.ravel()] m.vc = m.vc[m.f.ravel()] m.f = np.arange(m.f.size).reshape((-1,3)) from opendr.camera import ProjectPoints rn.camera = ProjectPoints(v=m.v, rt=ch.zeros(3), t=ch.zeros(3), f=ch.array([w,w])/2., c=ch.array([w,h])/2., k=ch.zeros(5)) rn.frustum = {'near': 1., 'far': 10., 'width': w, 'height': h} rn.set(v=m.v, f=m.f, bgcolor=ch.zeros(3)) # Construct point light source rn.vc = LambertianPointLight( f=m.f, v=rn.v, num_verts=len(m.v), light_pos=ch.array([-1000,-1000,-1000]), vc=m.vc, light_color=ch.array([1., 1., 1.])) # Show it import matplotlib.pyplot as plt plt.ion() plt.imshow(rn.r) plt.show() dr = rn.dr_wrt(rn.v) # or rn.vc, or rn.camera.rt, rn.camera.t, rn.camera.f, rn.camera.c, etc """ demos['silhouette'] = """ # Create renderer import chumpy as ch from opendr.renderer import ColoredRenderer rn = ColoredRenderer() # Assign attributes to renderer from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,4]), rotation=ch.zeros(3)) w, h = (320, 240) from opendr.camera import ProjectPoints rn.camera = ProjectPoints(v=m.v, rt=ch.zeros(3), t=ch.zeros(3), f=ch.array([w,w])/2., c=ch.array([w,h])/2., k=ch.zeros(5)) rn.frustum = {'near': 1., 'far': 10., 'width': w, 'height': h} rn.set(v=m.v, f=m.f, vc=m.vc*0+1, bgcolor=ch.zeros(3)) # Show it import matplotlib.pyplot as plt plt.ion() plt.imshow(rn.r) plt.show() dr = rn.dr_wrt(rn.v) # or rn.vc, or rn.camera.rt, rn.camera.t, rn.camera.f, rn.camera.c, etc """ demos['boundary'] = """ # Create renderer import chumpy as ch from opendr.renderer import BoundaryRenderer rn = BoundaryRenderer() # Assign attributes to renderer from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,4]), rotation=ch.zeros(3)) w, h = (320, 240) from opendr.camera import ProjectPoints rn.camera = ProjectPoints(v=m.v, rt=ch.zeros(3), t=ch.zeros(3), f=ch.array([w,w])/2., c=ch.array([w,h])/2., k=ch.zeros(5)) rn.frustum = {'near': 1., 'far': 10., 'width': w, 'height': h} rn.set(v=m.v, f=m.f, vc=m.vc*0+1, bgcolor=ch.zeros(3), num_channels=3) # Show it import matplotlib.pyplot as plt plt.ion() plt.imshow(rn.r) plt.show() dr = rn.dr_wrt(rn.v) # or rn.vc, or rn.camera.rt, rn.camera.t, rn.camera.f, rn.camera.c, etc """ demos['point_light'] = """ # Create renderer import chumpy as ch from opendr.renderer import ColoredRenderer from opendr.lighting import LambertianPointLight rn = ColoredRenderer() # Assign attributes to renderer from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,4]), rotation=ch.zeros(3)) w, h = (320, 240) from opendr.camera import ProjectPoints rn.camera = ProjectPoints(v=m.v, rt=ch.zeros(3), t=ch.zeros(3), f=ch.array([w,w])/2., c=ch.array([w,h])/2., k=ch.zeros(5)) rn.frustum = {'near': 1., 'far': 10., 'width': w, 'height': h} rn.set(v=m.v, f=m.f, bgcolor=ch.zeros(3)) # Construct point light source rn.vc = LambertianPointLight( f=m.f, v=rn.v, num_verts=len(m.v), light_pos=ch.array([-1000,-1000,-1000]), vc=m.vc, light_color=ch.array([1., 1., 1.])) # Show it import matplotlib.pyplot as plt plt.ion() plt.imshow(rn.r) plt.show() dr = rn.dr_wrt(rn.v) # or rn.vc, or rn.camera.rt, rn.camera.t, rn.camera.f, rn.camera.c, etc """ demos['spherical_harmonics'] = """ # Create renderer import chumpy as ch from opendr.renderer import ColoredRenderer from opendr.lighting import SphericalHarmonics from opendr.geometry import VertNormals rn = ColoredRenderer() # Assign attributes to renderer from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,4]), rotation=ch.zeros(3)) w, h = (320, 240) from opendr.camera import ProjectPoints rn.camera = ProjectPoints(v=m.v, rt=ch.zeros(3), t=ch.zeros(3), f=ch.array([w,w])/2., c=ch.array([w,h])/2., k=ch.zeros(5)) rn.frustum = {'near': 1., 'far': 10., 'width': w, 'height': h} rn.set(v=m.v, f=m.f, bgcolor=ch.zeros(3)) vn = VertNormals(v=rn.v, f=rn.f) sh_red = SphericalHarmonics(vn=vn, light_color=ch.array([1,0,0]), components=ch.random.randn(9)) sh_green = SphericalHarmonics(vn=vn, light_color=ch.array([0,1,0]), components=ch.random.randn(9)) sh_blue = SphericalHarmonics(vn=vn, light_color=ch.array([0,0,1]), components=ch.random.randn(9)) rn.vc = sh_red + sh_green + sh_blue # Show it import matplotlib.pyplot as plt plt.ion() plt.imshow(rn.r) plt.show() dr = rn.dr_wrt(rn.v) # or rn.vc, or rn.camera.rt, rn.camera.t, rn.camera.f, rn.camera.c, etc """ demos['optimization'] = """ from opendr.simple import * import numpy as np import matplotlib.pyplot as plt w, h = 320, 240 try: m = load_mesh('earth.obj') except: from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,0]), rotation=ch.zeros(3)) # Create V, A, U, f: geometry, brightness, camera, renderer V = ch.array(m.v) A = SphericalHarmonics(vn=VertNormals(v=V, f=m.f), components=[3.,2.,0.,0.,0.,0.,0.,0.,0.], light_color=ch.ones(3)) U = ProjectPoints(v=V, f=[w,w], c=[w/2.,h/2.], k=ch.zeros(5), t=ch.zeros(3), rt=ch.zeros(3)) f = TexturedRenderer(vc=A, camera=U, f=m.f, bgcolor=[0.,0.,0.], texture_image=m.texture_image, vt=m.vt, ft=m.ft, frustum={'width':w, 'height':h, 'near':1,'far':20}) # Parameterize the vertices translation, rotation = ch.array([0,0,8]), ch.zeros(3) f.v = translation + V.dot(Rodrigues(rotation)) observed = f.r np.random.seed(1) translation[:] = translation.r + np.random.rand(3) rotation[:] = rotation.r + np.random.rand(3) *.2 A.components[1:] = 0 # Create the energy E_raw = f - observed E_pyr = gaussian_pyramid(E_raw, n_levels=6, normalization='size') def cb(_): import cv2 global E_raw cv2.imshow('Absolute difference', np.abs(E_raw.r)) cv2.waitKey(1) print 'OPTIMIZING TRANSLATION, ROTATION, AND LIGHT PARMS' free_variables=[translation, rotation, A.components] ch.minimize({'pyr': E_pyr}, x0=free_variables, callback=cb) ch.minimize({'raw': E_raw}, x0=free_variables, callback=cb) """ demos['optimization_cpl'] = """ from opendr.simple import * import numpy as np import matplotlib.pyplot as plt w, h = 320, 240 try: m = load_mesh('earth.obj') except: from opendr.util_tests import get_earthmesh m = get_earthmesh(trans=ch.array([0,0,0]), rotation=ch.zeros(3)) # Create V, A, U, f: geometry, brightness, camera, renderer V = ch.array(m.v) A = SphericalHarmonics(vn=VertNormals(v=V, f=m.f), components=[3.,2.,0.,0.,0.,0.,0.,0.,0.], light_color=ch.ones(3)) U = ProjectPoints(v=V, f=[w,w], c=[w/2.,h/2.], k=ch.zeros(5), t=ch.zeros(3), rt=ch.zeros(3)) f = TexturedRenderer(vc=A, camera=U, f=m.f, bgcolor=[0.,0.,0.], texture_image=m.texture_image, vt=m.vt, ft=m.ft, frustum={'width':w, 'height':h, 'near':1,'far':20}) # Parameterize the vertices translation, rotation = ch.array([0,0,8]), ch.zeros(3) model_v = translation + ch.array(V.r).dot(Rodrigues(rotation)) # Simulate an observed image V[:] = model_v.r observed = f.r np.random.seed(1) translation[:] = translation.r + np.random.rand(3) rotation[:] = rotation.r + np.random.rand(3) *.2 V[:] = model_v.r A.components[1:] = 0 # Create the energy E_raw = f - observed E_pyr = gaussian_pyramid(E_raw, n_levels=6, normalization='size') def cb(_): import cv2 global E_raw cv2.imshow('Absolute difference', np.abs(E_raw.r)) cv2.waitKey(1) print 'OPTIMIZING TRANSLATION, ROTATION, AND LIGHT PARMS' free_variables=[translation, rotation, A.components, V] ch.minimize({'pyr': E_pyr, 'cpl': (V - model_v)*1e-4}, x0=free_variables, callback=cb) ch.minimize({'raw': E_raw, 'cpl': V - model_v}, x0=free_variables, callback=cb) """ def demo(which=None): import re if which not in demos: print('Please indicate which demo you want, as follows:') for key in demos: print("\tdemo('%s')" % (key,)) return print('- - - - - - - - - - - <CODE> - - - - - - - - - - - -') print(re.sub('global.*\n','',demos[which])) print('- - - - - - - - - - - </CODE> - - - - - - - - - - - -\n') exec('global np\n' + demos[which], globals(), locals())

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0.813809

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0.772213

0.755659

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Python

dizzy/tests/test_interaction.py

0xc0decafe/dizzy

6cf6abf7a9b990fe77618e42651f3c3d286cc15b

[ "BSD-3-Clause" ]

1

2020-11-19T10:11:43.000Z

dizzy/tests/test_interaction.py

0xc0decafe/dizzy

6cf6abf7a9b990fe77618e42651f3c3d286cc15b

[ "BSD-3-Clause" ]

null

dizzy/tests/test_interaction.py

0xc0decafe/dizzy

6cf6abf7a9b990fe77618e42651f3c3d286cc15b

[ "BSD-3-Clause" ]

1

2020-11-19T10:12:18.000Z

# test_interations.py # # Copyright 2017 Daniel Mende <mail@c0decafe.de> # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following disclaimer # in the documentation and/or other materials provided with the # distribution. # * Neither the name of the nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. from unittest import TestCase, main from dizzy.interaction import Interaction from dizzy.objects.field import Field from dizzy.functions.length import length from dizzy.dizz import Dizz from dizzy.functions.checksum import checksum from dizzy.functions import BOTH from dizzy.value import Value class TestInteraction(TestCase): def __init__(self, arg): self.maxDiff = None TestCase.__init__(self, arg) def test_init(self): objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 17), fuzz="std")] d0 = Dizz("test0", objects, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std")] d1 = Dizz("test1", objects, fuzz="std") act = Interaction("Test", [d0, d1]) self.assertEqual(act.name, "Test") self.assertEqual(act.objects, [d0, d1]) def test_iter(self): expected = [Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x00\x00w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x00\x02w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x00\x04w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x00\x06w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x00\x08w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x01\xff\xf6w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x01\xff\xf8w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x01\xff\xfaw3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x01\xff\xfcw3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x01\xff\xfew3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\xff\xf8w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\xff\xfaw3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\xff\xfcw3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\xff\xfew3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x02\x00w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x04\x00w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x06\x00w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00\x08\x00w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""33\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""33\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""73\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""73\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00"";3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00"#\xf73\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00"#\xfb3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00"#\xfb3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00"#\xff3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00"#\xff3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""\xfb3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""\xfb3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""\xff3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""\xff3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, 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Value(b'\x00""w3\x00!', 49), Value(b'\x02\xa4\xaa\x00\x01\xd0\xfb', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xa8\xaa\x00\x01\xdbh', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xac\xaa\x00\x01D\xd1', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xb0\xaa\x00\x01\x91\xe4', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xb4\xaa\x00\x01\x1a\x90', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xb8\xaa\x00\x01\x81\x12', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xbc\xaa\x00\x01\n\x94', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xc0\xaa\x00\x01\xe0\xea', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xc4\xaa\x00\x01,C', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xc8\xaa\x00\x01\xd5t', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xcc\xaa\x00\x01\xb6\x12', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xd0\xaa\x00\x01-\x0c', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xd4\xaa\x00\x01C\xe5', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xd8\xaa\x00\x01\x0e\xe8', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xdc\xaa\x00\x01U2', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xe0\xaa\x00\x010\xba', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xe4\xaa\x00\x01\xf2>', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xe8\xaa\x00\x01\xfc6', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xec\xaa\x00\x01\x1b.', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xf0\xaa\x00\x01S,', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xf4\xaa\x00\x01\x82\xce', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xf8\xaa\x00\x01\x1ea', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x02\xfc\xaa\x00\x01\xe6;', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x00\xaa\x00\x01"\x86', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x04\xaa\x00\x01\x97L', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x08\xaa\x00\x01G\xa9', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x0c\xaa\x00\x01\x9e\x1a', 50), None, Value(b'\x00""w3\x00!', 49), Value(b"\x03\x10\xaa\x00\x01\xb4'", 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x14\xaa\x00\x01\x16\xbc', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x18\xaa\x00\x01Y\xf5', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x1c\xaa\x00\x01^\xdf', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03 \xaa\x00\x01fl', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03$\xaa\x00\x01YA', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03(\xaa\x00\x01\xd5\xf4', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03,\xaa\x00\x01\x83(', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x030\xaa\x00\x01\x84\xc6', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x034\xaa\x00\x01y\xa0', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x038\xaa\x00\x01\x06\x93', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03<\xaa\x00\x01\x99:', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03@\xaa\x00\x01\xabT', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03D\xaa\x00\x01\xd9\xf0', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03H\xaa\x00\x01d\xdd', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03L\xaa\x00\x01\xfd~', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03P\xaa\x00\x01\x10\x7f', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03T\xaa\x00\x01qd', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03X\xaa\x00\x01\xf9\xed', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\\\xaa\x00\x01\x9a\x13', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03`\xaa\x00\x01p}', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03d\xaa\x00\x01`+', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03h\xaa\x00\x01.Q', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03l\xaa\x00\x01\x9f\xab', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03p\xaa\x00\x01.\\', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03t\xaa\x00\x01\x8d\xaf', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03x\xaa\x00\x01\xaf\xcd', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03|\xaa\x00\x01\xcby', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x80\xaa\x00\x01\x19H', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x84\xaa\x00\x01V\x86', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x88\xaa\x00\x01J\xce', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x8c\xaa\x00\x01\xd6\x82', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x90\xaa\x00\x01\x89@', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x94\xaa\x00\x01\x9f#', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x98\xaa\x00\x01\xc7+', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\x9c\xaa\x00\x01Zr', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xa0\xaa\x00\x01\xdb\xf1', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xa4\xaa\x00\x01\x1b\x1b', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xa8\xaa\x00\x0103', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xac\xaa\x00\x01\xc6\x92', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xb0\xaa\x00\x01\xa3\x96', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xb4\xaa\x00\x01\xd4\xd6', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xb8\xaa\x00\x01\x1c\x1a', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xbc\xaa\x00\x01l<', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xc0\xaa\x00\x01;\x19', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xc4\xaa\x00\x01V\xf4', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xc8\xaa\x00\x01L\xd9', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xcc\xaa\x00\x01\x07 ', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xd0\xaa\x00\x01\xb6$', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xd4\xaa\x00\x01%~', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xd8\xaa\x00\x01\xd9\xc7', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xdc\xaa\x00\x01?\xe2', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xe0\xaa\x00\x01\xdf\x12', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xe4\xaa\x00\x01\xb1\xa8', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xe8\xaa\x00\x01P\x10', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xec\xaa\x00\x01\x19\x8b', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xf0\xaa\x00\x01\r\xc8', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xf4\xaa\x00\x01.2', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xf8\xaa\x00\x01V\xab', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\xaa\x00\x018}', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\x00\x00\x01i{', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\x01\x00\x01\xc8\x98', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\x02\x00\x01\xe8,', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\x03\x00\x01\xf1\xf2', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\x04\x00\x01\xd2\xaa', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xff\xfb\x00\x01a\x93', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xff\xfc\x00\x01]\xf3', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xff\xfd\x00\x01\x9bE', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xff\xfe\x00\x01\xd9\x1b', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xff\xff\x00\x01\xe8R', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfd\xfc\x00\x01\xa1E', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfd\xfd\x00\x014\x1b', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfd\xfe\x00\x01\xac\xcd', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfd\xff\x00\x01.\xe0', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfd\x00\x00\x01\xb4d', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfe\x00\x00\x01)\x1d', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xff\x00\x00\x01\xbd\x08', 50), None, Value(b'\x00""w3\x00!', 49), Value(b'\x03\xfc\x00\x00\x01i{', 50)] objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 17), fuzz="std"), Field("length", b"\x00\x00", fuzz="std")] functions = [length("length", "test0", "test2")] d0 = Dizz("test0", objects, functions, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std"), Field("test2", b"\x00\x00"), Field("checksum", b"\x00\x00")] functions = [checksum("checksum", "test0", "test2", "sha1")] d1 = Dizz("test1", objects, functions, fuzz="std") def inc(interaction_iterator, dizzy_iterator, response): i = int.from_bytes(dizzy_iterator["test2"].byte, "big") + 1 dizzy_iterator["test2"] = i.to_bytes(2, "big") act = Interaction("Test", [d0, d1], {1: [inc]}) self.assertEqual([i for i in act], expected) def test_length_std(self): objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 17), fuzz="std"), Field("length", b"\x00\x00", fuzz="std")] functions = [length("length", "test0", "test2")] d0 = Dizz("test0", objects, functions, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std"), Field("test2", b"\x00\x00"), Field("checksum", b"\x00\x00")] functions = [checksum("checksum", "test0", "test2", "sha1")] d1 = Dizz("test1", objects, functions, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std"), Field("test2", b"\x00\x00"), Field("checksum", b"\x00\x00")] functions = [checksum("checksum", "test0", "test2", "sha1")] d2 = Dizz("test2", objects, functions, fuzz="std") def inc(interaction_iterator, dizzy_iterator, response): i = int.from_bytes(dizzy_iterator["test2"].byte, "big") + 1 dizzy_iterator["test2"] = Value(i.to_bytes(2, "big")) act = Interaction("Test", [d0, d1, d2], {1: [inc]}, fuzz="std") self.assertEqual(len([i for i in act]), act.length()) def test_iterations_std(self): objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 17), fuzz="std"), Field("length", b"\x00\x00", fuzz="std")] functions = [length("length", "test0", "test2")] d0 = Dizz("test0", objects, functions, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std"), Field("test2", b"\x00\x00"), Field("checksum", b"\x00\x00")] functions = [checksum("checksum", "test0", "test2", "sha1")] d1 = Dizz("test1", objects, functions, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std"), Field("test2", b"\x00\x00"), Field("checksum", b"\x00\x00")] functions = [checksum("checksum", "test0", "test2", "sha1")] d2 = Dizz("test2", objects, functions, fuzz="std") def inc(_, dizzy_iterator, __): i = int.from_bytes(dizzy_iterator["test2"].byte, "big") + 1 dizzy_iterator["test2"] = Value(i.to_bytes(2, "big")) act = Interaction("Test", [d0, d1, d2], {1: [inc]}, fuzz="std") iterations_1 = 1 iterations_2 = 0 for obj in act: if obj is None: iterations_1 += 1 else: iterations_2 += 1 self.assertEqual(iterations_1, act.iterations()) self.assertEqual(iterations_2 // len(act.objects), act.iterations()) def test_length_full(self): objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 17), fuzz="std"), Field("length", b"\x00\x00", fuzz="std")] functions = [length("length", "test0", "test2")] d0 = Dizz("test0", objects, functions, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std"), Field("test2", b"\x00\x00"), Field("checksum", b"\x00\x00")] functions = [checksum("checksum", "test0", "test2", "sha1")] d1 = Dizz("test1", objects, functions, fuzz="std") def inc(interaction_iterator, dizzy_iterator, response): i = int.from_bytes(dizzy_iterator["test2"].byte, "big") + 1 dizzy_iterator["test2"] = Value(i.to_bytes(2, "big")) act = Interaction("Test", [d0, d1], {1: [inc]}, fuzz="full") self.assertEqual(len([i for i in act]), act.length()) def test_iterations_full(self): objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 17), fuzz="std"), Field("length", b"\x00\x00", fuzz="std")] functions = [length("length", "test0", "test2")] d0 = Dizz("test0", objects, functions, fuzz="std") objects = [Field("test0", b"\xff", fuzz="full"), Field("test1", b"\xaa", 10, fuzz="std"), Field("test2", b"\x00\x00"), Field("checksum", b"\x00\x00")] functions = [checksum("checksum", "test0", "test2", "sha1")] d1 = Dizz("test1", objects, functions, fuzz="std") def inc(_, dizzy_iterator, __): i = int.from_bytes(dizzy_iterator["test2"].byte, "big") + 1 dizzy_iterator["test2"] = Value(i.to_bytes(2, "big")) act = Interaction("Test", [d0, d1], {1: [inc]}, fuzz="full") iterations_1 = 1 iterations_2 = 0 for obj in act: if obj is None: iterations_1 += 1 else: iterations_2 += 1 self.assertEqual(iterations_1, act.iterations()) self.assertEqual(iterations_2 // len(act.objects), act.iterations()) def test_start_at_std(self): objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 11), fuzz="std"), Field("length", b"\x00\x00")] functions = [length("length", "test0", "test2")] d0 = Dizz("test0", objects, functions, fuzz="std") objects = [Field("test0", b"\xff"), Field("test1", b"\xaa", 9, fuzz="std"), Field("test2", b"\x00\x00")] functions = list() d1 = Dizz("test1", objects, functions, fuzz="std") dizz_objects = [d0, d1] act = Interaction("Test", dizz_objects, {}, fuzz="std") excepted = list(act) for i in range(act.iterations()): got = list(Interaction("Test", dizz_objects, {}, fuzz="std", start_at=i)) self.assertListEqual(excepted[(i * (len(dizz_objects) + 1)):], got) def test_start_at_full(self): objects = [Field("test0", b"\x11\x11", fuzz="std"), Field("test1", b"\x22", fuzz="std"), Field("test2", b"\x33\x33", slice(9, 11), fuzz="std"), Field("length", b"\x00\x00")] functions = [length("length", "test0", "test2")] d0 = Dizz("test0", objects, functions, fuzz="std") objects = [Field("test0", b"\xff"), Field("test1", b"\xaa", 9, fuzz="std"), Field("test2", b"\x00\x00")] functions = list() d1 = Dizz("test1", objects, functions, fuzz="std") dizz_objects = [d0, d1] act = Interaction("Test", dizz_objects, {}, fuzz="full") excepted = list(act) for i in range(act.iterations()): got = list(Interaction("Test", [d0, d1], {}, fuzz="full", start_at=i)) self.assertListEqual(excepted[(i * (len(dizz_objects) + 1)):], got) if __name__ == '__main__': main()

81.981022

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0.054097

0.198281

0.18137

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0.829235

0.828495

0

0.206456

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10

8a6219b36f724f9522aacf6afc0fff48900928ed

13,260

py

Python

lib/model/rpn/proposal_layer.py

miyamotost/faster-rcnn.pytorch

374396d87c85ffe2373d2ae13dc002ea6bb08734

[ "MIT" ]

null

lib/model/rpn/proposal_layer.py

miyamotost/faster-rcnn.pytorch

374396d87c85ffe2373d2ae13dc002ea6bb08734

[ "MIT" ]

null

lib/model/rpn/proposal_layer.py

miyamotost/faster-rcnn.pytorch

374396d87c85ffe2373d2ae13dc002ea6bb08734

[ "MIT" ]

null

from __future__ import absolute_import # -------------------------------------------------------- # Faster R-CNN # Copyright (c) 2015 Microsoft # Licensed under The MIT License [see LICENSE for details] # Written by Ross Girshick and Sean Bell # -------------------------------------------------------- # -------------------------------------------------------- # Reorganized and modified by Jianwei Yang and Jiasen Lu # -------------------------------------------------------- import torch import torch.nn as nn import numpy as np import math import yaml from model.utils.config import cfg from .generate_anchors import generate_anchors from .bbox_transform import bbox_transform_inv, clip_boxes, clip_boxes_batch from model.nms.nms_wrapper import nms import pdb DEBUG = False class _ProposalLayer(nn.Module): """ Outputs object detection proposals by applying estimated bounding-box transformations to a set of regular boxes (called "anchors"). """ def __init__(self, feat_stride, scales, ratios): super(_ProposalLayer, self).__init__() self._feat_stride = feat_stride self._anchors = torch.from_numpy(generate_anchors(scales=np.array(scales), ratios=np.array(ratios))).float() self._num_anchors = self._anchors.size(0) # rois blob: holds R regions of interest, each is a 5-tuple # (n, x1, y1, x2, y2) specifying an image batch index n and a # rectangle (x1, y1, x2, y2) # top[0].reshape(1, 5) # # # scores blob: holds scores for R regions of interest # if len(top) > 1: # top[1].reshape(1, 1, 1, 1) def forward(self, input): # Algorithm: # # for each (H, W) location i # generate A anchor boxes centered on cell i # apply predicted bbox deltas at cell i to each of the A anchors # clip predicted boxes to image # remove predicted boxes with either height or width < threshold # sort all (proposal, score) pairs by score from highest to lowest # take top pre_nms_topN proposals before NMS # apply NMS with threshold 0.7 to remaining proposals # take after_nms_topN proposals after NMS # return the top proposals (-> RoIs top, scores top) # the first set of _num_anchors channels are bg probs # the second set are the fg probs scores = input[0][:, self._num_anchors:, :, :] bbox_deltas = input[1] im_info = input[2] cfg_key = input[3] pre_nms_topN = cfg[cfg_key].RPN_PRE_NMS_TOP_N post_nms_topN = cfg[cfg_key].RPN_POST_NMS_TOP_N nms_thresh = cfg[cfg_key].RPN_NMS_THRESH min_size = cfg[cfg_key].RPN_MIN_SIZE batch_size = bbox_deltas.size(0) feat_height, feat_width = scores.size(2), scores.size(3) shift_x = np.arange(0, feat_width) * self._feat_stride shift_y = np.arange(0, feat_height) * self._feat_stride shift_x, shift_y = np.meshgrid(shift_x, shift_y) shifts = torch.from_numpy(np.vstack((shift_x.ravel(), shift_y.ravel(), shift_x.ravel(), shift_y.ravel())).transpose()) shifts = shifts.contiguous().type_as(scores).float() A = self._num_anchors K = shifts.size(0) self._anchors = self._anchors.type_as(scores) # anchors = self._anchors.view(1, A, 4) + shifts.view(1, K, 4).permute(1, 0, 2).contiguous() anchors = self._anchors.view(1, A, 4) + shifts.view(K, 1, 4) anchors = anchors.view(1, K * A, 4).expand(batch_size, K * A, 4) # Transpose and reshape predicted bbox transformations to get them # into the same order as the anchors: bbox_deltas = bbox_deltas.permute(0, 2, 3, 1).contiguous() bbox_deltas = bbox_deltas.view(batch_size, -1, 4) # Same story for the scores: scores = scores.permute(0, 2, 3, 1).contiguous() scores = scores.view(batch_size, -1) # Convert anchors into proposals via bbox transformations proposals = bbox_transform_inv(anchors, bbox_deltas, batch_size) # 2. clip predicted boxes to image proposals = clip_boxes(proposals, im_info, batch_size) # proposals = clip_boxes_batch(proposals, im_info, batch_size) # assign the score to 0 if it's non keep. # keep = self._filter_boxes(proposals, min_size * im_info[:, 2]) # trim keep index to make it euqal over batch # keep_idx = torch.cat(tuple(keep_idx), 0) # scores_keep = scores.view(-1)[keep_idx].view(batch_size, trim_size) # proposals_keep = proposals.view(-1, 4)[keep_idx, :].contiguous().view(batch_size, trim_size, 4) # _, order = torch.sort(scores_keep, 1, True) scores_keep = scores proposals_keep = proposals _, order = torch.sort(scores_keep, 1, True) output = scores.new(batch_size, post_nms_topN, 5).zero_() for i in range(batch_size): # # 3. remove predicted boxes with either height or width < threshold # # (NOTE: convert min_size to input image scale stored in im_info[2]) proposals_single = proposals_keep[i] scores_single = scores_keep[i] # # 4. sort all (proposal, score) pairs by score from highest to lowest # # 5. take top pre_nms_topN (e.g. 6000) order_single = order[i] if pre_nms_topN > 0 and pre_nms_topN < scores_keep.numel(): order_single = order_single[:pre_nms_topN] proposals_single = proposals_single[order_single, :] scores_single = scores_single[order_single].view(-1,1) # 6. apply nms (e.g. threshold = 0.7) # 7. take after_nms_topN (e.g. 300) # 8. return the top proposals (-> RoIs top) keep_idx_i = nms(torch.cat((proposals_single, scores_single), 1), nms_thresh, force_cpu=not cfg.USE_GPU_NMS) keep_idx_i = keep_idx_i.long().view(-1) if post_nms_topN > 0: keep_idx_i = keep_idx_i[:post_nms_topN] proposals_single = proposals_single[keep_idx_i, :] scores_single = scores_single[keep_idx_i, :] # padding 0 at the end. num_proposal = proposals_single.size(0) output[i,:,0] = i output[i,:num_proposal,1:] = proposals_single return output def backward(self, top, propagate_down, bottom): """This layer does not propagate gradients.""" pass def reshape(self, bottom, top): """Reshaping happens during the call to forward.""" pass def _filter_boxes(self, boxes, min_size): """Remove all boxes with any side smaller than min_size.""" ws = boxes[:, :, 2] - boxes[:, :, 0] + 1 hs = boxes[:, :, 3] - boxes[:, :, 1] + 1 keep = ((ws >= min_size.view(-1,1).expand_as(ws)) & (hs >= min_size.view(-1,1).expand_as(hs))) return keep class _ProposalLayer2(nn.Module): """ Outputs object detection proposals by applying estimated bounding-box transformations to a set of regular boxes (called "anchors"). """ def __init__(self, feat_stride, scales, ratios): super(_ProposalLayer2, self).__init__() self._feat_stride = feat_stride self._anchors = torch.from_numpy(generate_anchors(scales=np.array(scales), ratios=np.array(ratios))).float() self._num_anchors = self._anchors.size(0) # rois blob: holds R regions of interest, each is a 5-tuple # (n, x1, y1, x2, y2) specifying an image batch index n and a # rectangle (x1, y1, x2, y2) # top[0].reshape(1, 5) # # # scores blob: holds scores for R regions of interest # if len(top) > 1: # top[1].reshape(1, 1, 1, 1) def forward(self, input0, input1, input2): # Algorithm: # # for each (H, W) location i # generate A anchor boxes centered on cell i # apply predicted bbox deltas at cell i to each of the A anchors # clip predicted boxes to image # remove predicted boxes with either height or width < threshold # sort all (proposal, score) pairs by score from highest to lowest # take top pre_nms_topN proposals before NMS # apply NMS with threshold 0.7 to remaining proposals # take after_nms_topN proposals after NMS # return the top proposals (-> RoIs top, scores top) # the first set of _num_anchors channels are bg probs # the second set are the fg probs scores = input0[:, self._num_anchors:, :, :] bbox_deltas = input1 im_info = input2 cfg_key = "TEST" pre_nms_topN = cfg[cfg_key].RPN_PRE_NMS_TOP_N post_nms_topN = cfg[cfg_key].RPN_POST_NMS_TOP_N nms_thresh = cfg[cfg_key].RPN_NMS_THRESH min_size = cfg[cfg_key].RPN_MIN_SIZE batch_size = bbox_deltas.size(0) feat_height, feat_width = scores.size(2), scores.size(3) shift_x = np.arange(0, feat_width) * self._feat_stride shift_y = np.arange(0, feat_height) * self._feat_stride shift_x, shift_y = np.meshgrid(shift_x, shift_y) shifts = torch.from_numpy(np.vstack((shift_x.ravel(), shift_y.ravel(), shift_x.ravel(), shift_y.ravel())).transpose()) shifts = shifts.contiguous().type_as(scores).float() A = self._num_anchors K = shifts.size(0) self._anchors = self._anchors.type_as(scores) # anchors = self._anchors.view(1, A, 4) + shifts.view(1, K, 4).permute(1, 0, 2).contiguous() anchors = self._anchors.view(1, A, 4) + shifts.view(K, 1, 4) anchors = anchors.view(1, K * A, 4).expand(batch_size, K * A, 4) # Transpose and reshape predicted bbox transformations to get them # into the same order as the anchors: bbox_deltas = bbox_deltas.permute(0, 2, 3, 1).contiguous() bbox_deltas = bbox_deltas.view(batch_size, -1, 4) # Same story for the scores: scores = scores.permute(0, 2, 3, 1).contiguous() scores = scores.view(batch_size, -1) # Convert anchors into proposals via bbox transformations proposals = bbox_transform_inv(anchors, bbox_deltas, batch_size) # 2. clip predicted boxes to image proposals = clip_boxes(proposals, im_info, batch_size) # proposals = clip_boxes_batch(proposals, im_info, batch_size) # assign the score to 0 if it's non keep. # keep = self._filter_boxes(proposals, min_size * im_info[:, 2]) # trim keep index to make it euqal over batch # keep_idx = torch.cat(tuple(keep_idx), 0) # scores_keep = scores.view(-1)[keep_idx].view(batch_size, trim_size) # proposals_keep = proposals.view(-1, 4)[keep_idx, :].contiguous().view(batch_size, trim_size, 4) # _, order = torch.sort(scores_keep, 1, True) scores_keep = scores proposals_keep = proposals _, order = torch.sort(scores_keep, 1, True) output = scores.new(batch_size, post_nms_topN, 5).zero_() for i in range(batch_size): # # 3. remove predicted boxes with either height or width < threshold # # (NOTE: convert min_size to input image scale stored in im_info[2]) proposals_single = proposals_keep[i] scores_single = scores_keep[i] # # 4. sort all (proposal, score) pairs by score from highest to lowest # # 5. take top pre_nms_topN (e.g. 6000) order_single = order[i] if pre_nms_topN > 0 and pre_nms_topN < scores_keep.numel(): order_single = order_single[:pre_nms_topN] proposals_single = proposals_single[order_single, :] scores_single = scores_single[order_single].view(-1,1) # 6. apply nms (e.g. threshold = 0.7) # 7. take after_nms_topN (e.g. 300) # 8. return the top proposals (-> RoIs top) keep_idx_i = nms(torch.cat((proposals_single, scores_single), 1), nms_thresh, force_cpu=not cfg.USE_GPU_NMS) keep_idx_i = keep_idx_i.long().view(-1) if post_nms_topN > 0: keep_idx_i = keep_idx_i[:post_nms_topN] proposals_single = proposals_single[keep_idx_i, :] scores_single = scores_single[keep_idx_i, :] # padding 0 at the end. num_proposal = proposals_single.size(0) output[i,:,0] = i output[i,:num_proposal,1:] = proposals_single return output def backward(self, top, propagate_down, bottom): """This layer does not propagate gradients.""" pass def reshape(self, bottom, top): """Reshaping happens during the call to forward.""" pass def _filter_boxes(self, boxes, min_size): """Remove all boxes with any side smaller than min_size.""" ws = boxes[:, :, 2] - boxes[:, :, 0] + 1 hs = boxes[:, :, 3] - boxes[:, :, 1] + 1 keep = ((ws >= min_size.view(-1,1).expand_as(ws)) & (hs >= min_size.view(-1,1).expand_as(hs))) return keep

40.303951

120

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4.20426

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0.021824

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0.917381

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0.270739

13,260

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null

0

7

8a7c242242e10ebbc9a164675a985b97d08a5c4d

140,469

py

Python

lookerapi/apis/project_api.py

jcarah/python_sdk

3bff34d04a828c940c3f93055e10b6a0095c2327

[ "MIT" ]

null

lookerapi/apis/project_api.py

jcarah/python_sdk

3bff34d04a828c940c3f93055e10b6a0095c2327

[ "MIT" ]

null

lookerapi/apis/project_api.py

jcarah/python_sdk

3bff34d04a828c940c3f93055e10b6a0095c2327

[ "MIT" ]

null

# coding: utf-8 """ Looker API 3.1 Reference ### Authorization The Looker API uses Looker **API3** credentials for authorization and access control. Looker admins can create API3 credentials on Looker's **Admin/Users** page. Pass API3 credentials to the **/login** endpoint to obtain a temporary access_token. Include that access_token in the Authorization header of Looker API requests. For details, see [Looker API Authorization](https://looker.com/docs/r/api/authorization) ### Client SDKs The Looker API is a RESTful system that should be usable by any programming language capable of making HTTPS requests. Client SDKs for a variety of programming languages can be generated from the Looker API's Swagger JSON metadata to streamline use of the Looker API in your applications. A client SDK for Ruby is available as an example. For more information, see [Looker API Client SDKs](https://looker.com/docs/r/api/client_sdks) ### Try It Out! The 'api-docs' page served by the Looker instance includes 'Try It Out!' buttons for each API method. After logging in with API3 credentials, you can use the \"Try It Out!\" buttons to call the API directly from the documentation page to interactively explore API features and responses. Note! With great power comes great responsibility: The \"Try It Out!\" button makes API calls to your live Looker instance. Be especially careful with destructive API operations such as `delete_user` or similar. There is no \"undo\" for API operations. ### Versioning Future releases of Looker will expand this API release-by-release to securely expose more and more of the core power of Looker to API client applications. API endpoints marked as \"beta\" may receive breaking changes without warning (but we will try to avoid doing that). Stable (non-beta) API endpoints should not receive breaking changes in future releases. For more information, see [Looker API Versioning](https://looker.com/docs/r/api/versioning) This **API 3.1** is in active development. This is where support for new Looker features will appear as non-breaking additions - new functions, new optional parameters on existing functions, or new optional properties in existing types. Additive changes should not impact your existing application code that calls the Looker API. Your existing application code will not be aware of any new Looker API functionality until you choose to upgrade your app to use a newer Looker API client SDK release. The following are a few examples of noteworthy items that have changed between API 3.0 and API 3.1. For more comprehensive coverage of API changes, please see the release notes for your Looker release. ### Examples of new things added in API 3.1: * Dashboard construction APIs * Themes and custom color collections APIs * Create and run SQL_runner queries * Create and run merged results queries * Create and modify dashboard filters * Create and modify password requirements ### Deprecated in API 3.0 The following functions and properties have been deprecated in API 3.0. They continue to exist and work in API 3.0 for the next several Looker releases but they have not been carried forward to API 3.1: * Dashboard Prefetch functions * User access_filter functions * User API 1.0 credentials functions * Space.is_root and Space.is_user_root properties. Use Space.is_shared_root and Space.is_users_root instead. ### Semantic changes in API 3.1: * `all_looks` no longer includes soft-deleted looks, matching `all_dashboards` behavior. You can find soft-deleted looks using `search_looks` with the `deleted` param set to True. * `all_spaces` no longer includes duplicate items * `search_users` no longer accepts Y,y,1,0,N,n for Boolean params, only \"true\" and \"false\". * For greater client and network compatibility, `render_task_results` now returns HTTP status ***202 Accepted*** instead of HTTP status ***102 Processing*** * `all_running_queries` and `kill_query` functions have moved into the `Query` function group. If you have application code which relies on the old behavior of the APIs above, you may continue using the API 3.0 functions in this Looker release. We strongly suggest you update your code to use API 3.1 analogs as soon as possible. OpenAPI spec version: 3.1.0 Contact: support@looker.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import sys import os import re # python 2 and python 3 compatibility library from six import iteritems from ..configuration import Configuration from ..api_client import ApiClient class ProjectApi(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient() self.api_client = config.api_client def all_git_branches(self, project_id, **kwargs): """ Get All Git Branches ### Get All Git Branches Returns a list of git branches in the project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_git_branches(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: list[GitBranch] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.all_git_branches_with_http_info(project_id, **kwargs) else: (data) = self.all_git_branches_with_http_info(project_id, **kwargs) return data def all_git_branches_with_http_info(self, project_id, **kwargs): """ Get All Git Branches ### Get All Git Branches Returns a list of git branches in the project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_git_branches_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: list[GitBranch] If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method all_git_branches" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `all_git_branches`") collection_formats = {} resource_path = '/projects/{project_id}/git_branches'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[GitBranch]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def all_git_connection_tests(self, project_id, **kwargs): """ Get All Git Connection Tests ### Get All Git Connection Tests Returns a list of tests which can be run against a project's (or the dependency project for the provided remote_url) git connection. Call [Run Git Connection Test](#!/Project/run_git_connection_test) to execute each test in sequence. Tests are ordered by increasing specificity. Tests should be run in the order returned because later tests require functionality tested by tests earlier in the test list. For example, a late-stage test for write access is meaningless if connecting to the git server (an early test) is failing. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_git_connection_tests(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str remote_url: (Optional: leave blank for root project) The remote url for remote dependency to test. :return: list[GitConnectionTest] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.all_git_connection_tests_with_http_info(project_id, **kwargs) else: (data) = self.all_git_connection_tests_with_http_info(project_id, **kwargs) return data def all_git_connection_tests_with_http_info(self, project_id, **kwargs): """ Get All Git Connection Tests ### Get All Git Connection Tests Returns a list of tests which can be run against a project's (or the dependency project for the provided remote_url) git connection. Call [Run Git Connection Test](#!/Project/run_git_connection_test) to execute each test in sequence. Tests are ordered by increasing specificity. Tests should be run in the order returned because later tests require functionality tested by tests earlier in the test list. For example, a late-stage test for write access is meaningless if connecting to the git server (an early test) is failing. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_git_connection_tests_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str remote_url: (Optional: leave blank for root project) The remote url for remote dependency to test. :return: list[GitConnectionTest] If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'remote_url'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method all_git_connection_tests" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `all_git_connection_tests`") collection_formats = {} resource_path = '/projects/{project_id}/git_connection_tests'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'remote_url' in params: query_params['remote_url'] = params['remote_url'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[GitConnectionTest]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def all_project_files(self, project_id, **kwargs): """ Get All Project Files ### Get All Project Files Returns a list of the files in the project This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_project_files(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: list[ProjectFile] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.all_project_files_with_http_info(project_id, **kwargs) else: (data) = self.all_project_files_with_http_info(project_id, **kwargs) return data def all_project_files_with_http_info(self, project_id, **kwargs): """ Get All Project Files ### Get All Project Files Returns a list of the files in the project This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_project_files_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: list[ProjectFile] If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method all_project_files" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `all_project_files`") collection_formats = {} resource_path = '/projects/{project_id}/files'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[ProjectFile]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def all_projects(self, **kwargs): """ Get All Projects ### Get All Projects Returns all projects visible to the current user This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_projects(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str fields: Requested fields :return: list[Project] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.all_projects_with_http_info(**kwargs) else: (data) = self.all_projects_with_http_info(**kwargs) return data def all_projects_with_http_info(self, **kwargs): """ Get All Projects ### Get All Projects Returns all projects visible to the current user This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.all_projects_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str fields: Requested fields :return: list[Project] If the method is called asynchronously, returns the request thread. """ all_params = ['fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method all_projects" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/projects'.replace('{format}', 'json') path_params = {} query_params = {} if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Project]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def create_git_branch(self, project_id, **kwargs): """ Checkout New Git Branch ### Create and Checkout a Git Branch Creates and checks out a new branch in the given project repository Only allowed in development mode - Call `update_session` to select the 'dev' workspace. Optionally specify a branch name, tag name or commit SHA as the start point in the ref field. If no ref is specified, HEAD of the current branch will be used as the start point for the new branch. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.create_git_branch(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param GitBranch body: Git Branch :return: GitBranch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.create_git_branch_with_http_info(project_id, **kwargs) else: (data) = self.create_git_branch_with_http_info(project_id, **kwargs) return data def create_git_branch_with_http_info(self, project_id, **kwargs): """ Checkout New Git Branch ### Create and Checkout a Git Branch Creates and checks out a new branch in the given project repository Only allowed in development mode - Call `update_session` to select the 'dev' workspace. Optionally specify a branch name, tag name or commit SHA as the start point in the ref field. If no ref is specified, HEAD of the current branch will be used as the start point for the new branch. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.create_git_branch_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param GitBranch body: Git Branch :return: GitBranch If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'body'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_git_branch" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `create_git_branch`") collection_formats = {} resource_path = '/projects/{project_id}/git_branch'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='GitBranch', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def create_git_deploy_key(self, project_id, **kwargs): """ Create Deploy Key ### Create Git Deploy Key Create a public/private key pair for authenticating ssh git requests from Looker to a remote git repository for a particular Looker project. Returns the public key of the generated ssh key pair. Copy this public key to your remote git repository's ssh keys configuration so that the remote git service can validate and accept git requests from the Looker server. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.create_git_deploy_key(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.create_git_deploy_key_with_http_info(project_id, **kwargs) else: (data) = self.create_git_deploy_key_with_http_info(project_id, **kwargs) return data def create_git_deploy_key_with_http_info(self, project_id, **kwargs): """ Create Deploy Key ### Create Git Deploy Key Create a public/private key pair for authenticating ssh git requests from Looker to a remote git repository for a particular Looker project. Returns the public key of the generated ssh key pair. Copy this public key to your remote git repository's ssh keys configuration so that the remote git service can validate and accept git requests from the Looker server. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.create_git_deploy_key_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_git_deploy_key" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `create_git_deploy_key`") collection_formats = {} resource_path = '/projects/{project_id}/git/deploy_key'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['text/plain']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def create_project(self, **kwargs): """ Create Project ### Create A Project dev mode required. - Call `update_session` to select the 'dev' workspace. `name` is required. `git_remote_url` is not allowed. To configure Git for the newly created project, follow the instructions in `update_project`. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.create_project(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param Project body: Project :return: Project If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.create_project_with_http_info(**kwargs) else: (data) = self.create_project_with_http_info(**kwargs) return data def create_project_with_http_info(self, **kwargs): """ Create Project ### Create A Project dev mode required. - Call `update_session` to select the 'dev' workspace. `name` is required. `git_remote_url` is not allowed. To configure Git for the newly created project, follow the instructions in `update_project`. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.create_project_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param Project body: Project :return: Project If the method is called asynchronously, returns the request thread. """ all_params = ['body'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_project" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/projects'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Project', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_git_branch(self, project_id, branch_name, **kwargs): """ Delete a Git Branch ### Delete the specified Git Branch Delete git branch specified in branch_name path param from local and remote of specified project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.delete_git_branch(project_id, branch_name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str branch_name: Branch Name (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.delete_git_branch_with_http_info(project_id, branch_name, **kwargs) else: (data) = self.delete_git_branch_with_http_info(project_id, branch_name, **kwargs) return data def delete_git_branch_with_http_info(self, project_id, branch_name, **kwargs): """ Delete a Git Branch ### Delete the specified Git Branch Delete git branch specified in branch_name path param from local and remote of specified project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.delete_git_branch_with_http_info(project_id, branch_name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str branch_name: Branch Name (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'branch_name'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_git_branch" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `delete_git_branch`") # verify the required parameter 'branch_name' is set if ('branch_name' not in params) or (params['branch_name'] is None): raise ValueError("Missing the required parameter `branch_name` when calling `delete_git_branch`") collection_formats = {} resource_path = '/projects/{project_id}/git_branch/{branch_name}'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] if 'branch_name' in params: path_params['branch_name'] = params['branch_name'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_repository_credential(self, root_project_id, credential_id, **kwargs): """ Delete Repository Credential ### Repository Credential for a remote dependency Admin required. `root_project_id` is required. `credential_id` is required. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.delete_repository_credential(root_project_id, credential_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str root_project_id: Root Project Id (required) :param str credential_id: Credential Id (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.delete_repository_credential_with_http_info(root_project_id, credential_id, **kwargs) else: (data) = self.delete_repository_credential_with_http_info(root_project_id, credential_id, **kwargs) return data def delete_repository_credential_with_http_info(self, root_project_id, credential_id, **kwargs): """ Delete Repository Credential ### Repository Credential for a remote dependency Admin required. `root_project_id` is required. `credential_id` is required. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.delete_repository_credential_with_http_info(root_project_id, credential_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str root_project_id: Root Project Id (required) :param str credential_id: Credential Id (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['root_project_id', 'credential_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_repository_credential" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'root_project_id' is set if ('root_project_id' not in params) or (params['root_project_id'] is None): raise ValueError("Missing the required parameter `root_project_id` when calling `delete_repository_credential`") # verify the required parameter 'credential_id' is set if ('credential_id' not in params) or (params['credential_id'] is None): raise ValueError("Missing the required parameter `credential_id` when calling `delete_repository_credential`") collection_formats = {} resource_path = '/projects/{root_project_id}/credential/{credential_id}'.replace('{format}', 'json') path_params = {} if 'root_project_id' in params: path_params['root_project_id'] = params['root_project_id'] if 'credential_id' in params: path_params['credential_id'] = params['credential_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def deploy_to_production(self, project_id, **kwargs): """ Deploy To Production ### Deploy LookML from this Development Mode Project to Production Git must have been configured, must be in dev mode and deploy permission required Deploy is a two / three step process 1. Push commits in current branch of dev mode project to the production branch (origin/master). Note a. This step is skipped in read-only projects. Note b. If this step is unsuccessful for any reason (e.g. rejected non-fastforward because production branch has commits not in current branch), subsequent steps will be skipped. 2. If this is the first deploy of this project, create the production project with git repository. 3. Pull the production branch into the production project. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.deploy_to_production(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Id of project (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.deploy_to_production_with_http_info(project_id, **kwargs) else: (data) = self.deploy_to_production_with_http_info(project_id, **kwargs) return data def deploy_to_production_with_http_info(self, project_id, **kwargs): """ Deploy To Production ### Deploy LookML from this Development Mode Project to Production Git must have been configured, must be in dev mode and deploy permission required Deploy is a two / three step process 1. Push commits in current branch of dev mode project to the production branch (origin/master). Note a. This step is skipped in read-only projects. Note b. If this step is unsuccessful for any reason (e.g. rejected non-fastforward because production branch has commits not in current branch), subsequent steps will be skipped. 2. If this is the first deploy of this project, create the production project with git repository. 3. Pull the production branch into the production project. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.deploy_to_production_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Id of project (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method deploy_to_production" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `deploy_to_production`") collection_formats = {} resource_path = '/projects/{project_id}/deploy_to_production'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def find_git_branch(self, project_id, branch_name, **kwargs): """ Find a Git Branch ### Get the specified Git Branch Returns the git branch specified in branch_name path param if it exists in the given project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.find_git_branch(project_id, branch_name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str branch_name: Branch Name (required) :return: GitBranch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.find_git_branch_with_http_info(project_id, branch_name, **kwargs) else: (data) = self.find_git_branch_with_http_info(project_id, branch_name, **kwargs) return data def find_git_branch_with_http_info(self, project_id, branch_name, **kwargs): """ Find a Git Branch ### Get the specified Git Branch Returns the git branch specified in branch_name path param if it exists in the given project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.find_git_branch_with_http_info(project_id, branch_name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str branch_name: Branch Name (required) :return: GitBranch If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'branch_name'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method find_git_branch" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `find_git_branch`") # verify the required parameter 'branch_name' is set if ('branch_name' not in params) or (params['branch_name'] is None): raise ValueError("Missing the required parameter `branch_name` when calling `find_git_branch`") collection_formats = {} resource_path = '/projects/{project_id}/git_branch/{branch_name}'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] if 'branch_name' in params: path_params['branch_name'] = params['branch_name'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='GitBranch', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_all_repository_credentials(self, root_project_id, **kwargs): """ Get All Repository Credentials ### Get all Repository Credentials for a project `root_project_id` is required. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_repository_credentials(root_project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str root_project_id: Root Project Id (required) :return: list[RepositoryCredential] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_all_repository_credentials_with_http_info(root_project_id, **kwargs) else: (data) = self.get_all_repository_credentials_with_http_info(root_project_id, **kwargs) return data def get_all_repository_credentials_with_http_info(self, root_project_id, **kwargs): """ Get All Repository Credentials ### Get all Repository Credentials for a project `root_project_id` is required. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_all_repository_credentials_with_http_info(root_project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str root_project_id: Root Project Id (required) :return: list[RepositoryCredential] If the method is called asynchronously, returns the request thread. """ all_params = ['root_project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_all_repository_credentials" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'root_project_id' is set if ('root_project_id' not in params) or (params['root_project_id'] is None): raise ValueError("Missing the required parameter `root_project_id` when calling `get_all_repository_credentials`") collection_formats = {} resource_path = '/projects/{root_project_id}/credentials'.replace('{format}', 'json') path_params = {} if 'root_project_id' in params: path_params['root_project_id'] = params['root_project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[RepositoryCredential]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def git_branch(self, project_id, **kwargs): """ Get Active Git Branch ### Get the Current Git Branch Returns the git branch currently checked out in the given project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.git_branch(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: GitBranch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.git_branch_with_http_info(project_id, **kwargs) else: (data) = self.git_branch_with_http_info(project_id, **kwargs) return data def git_branch_with_http_info(self, project_id, **kwargs): """ Get Active Git Branch ### Get the Current Git Branch Returns the git branch currently checked out in the given project repository This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.git_branch_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: GitBranch If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method git_branch" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `git_branch`") collection_formats = {} resource_path = '/projects/{project_id}/git_branch'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='GitBranch', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def git_deploy_key(self, project_id, **kwargs): """ Git Deploy Key ### Git Deploy Key Returns the ssh public key previously created for a project's git repository. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.git_deploy_key(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.git_deploy_key_with_http_info(project_id, **kwargs) else: (data) = self.git_deploy_key_with_http_info(project_id, **kwargs) return data def git_deploy_key_with_http_info(self, project_id, **kwargs): """ Git Deploy Key ### Git Deploy Key Returns the ssh public key previously created for a project's git repository. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.git_deploy_key_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method git_deploy_key" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `git_deploy_key`") collection_formats = {} resource_path = '/projects/{project_id}/git/deploy_key'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['text/plain']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def manifest(self, project_id, **kwargs): """ Get Manifest ### Get A Projects Manifest object Returns the project with the given project id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.manifest(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: Manifest If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.manifest_with_http_info(project_id, **kwargs) else: (data) = self.manifest_with_http_info(project_id, **kwargs) return data def manifest_with_http_info(self, project_id, **kwargs): """ Get Manifest ### Get A Projects Manifest object Returns the project with the given project id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.manifest_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :return: Manifest If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method manifest" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `manifest`") collection_formats = {} resource_path = '/projects/{project_id}/manifest'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Manifest', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def project(self, project_id, **kwargs): """ Get Project ### Get A Project Returns the project with the given project id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: Project If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.project_with_http_info(project_id, **kwargs) else: (data) = self.project_with_http_info(project_id, **kwargs) return data def project_with_http_info(self, project_id, **kwargs): """ Get Project ### Get A Project Returns the project with the given project id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: Project If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method project" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `project`") collection_formats = {} resource_path = '/projects/{project_id}'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Project', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def project_file(self, project_id, file_id, **kwargs): """ Get Project File ### Get Project File Info Returns information about a file in the project This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project_file(project_id, file_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str file_id: File Id (required) :param str fields: Requested fields :return: ProjectFile If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.project_file_with_http_info(project_id, file_id, **kwargs) else: (data) = self.project_file_with_http_info(project_id, file_id, **kwargs) return data def project_file_with_http_info(self, project_id, file_id, **kwargs): """ Get Project File ### Get Project File Info Returns information about a file in the project This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project_file_with_http_info(project_id, file_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str file_id: File Id (required) :param str fields: Requested fields :return: ProjectFile If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'file_id', 'fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method project_file" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `project_file`") # verify the required parameter 'file_id' is set if ('file_id' not in params) or (params['file_id'] is None): raise ValueError("Missing the required parameter `file_id` when calling `project_file`") collection_formats = {} resource_path = '/projects/{project_id}/files/file'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'file_id' in params: query_params['file_id'] = params['file_id'] if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ProjectFile', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def project_validation_results(self, project_id, **kwargs): """ Cached Project Validation Results ### Get Cached Project Validation Results Returns the cached results of a previous project validation calculation, if any. Returns http status 204 No Content if no validation results exist. Validating the content of all the files in a project can be computationally intensive for large projects. Use this API to simply fetch the results of the most recent project validation rather than revalidating the entire project from scratch. A value of `\"stale\": true` in the response indicates that the project has changed since the cached validation results were computed. The cached validation results may no longer reflect the current state of the project. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project_validation_results(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: ProjectValidationCache If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.project_validation_results_with_http_info(project_id, **kwargs) else: (data) = self.project_validation_results_with_http_info(project_id, **kwargs) return data def project_validation_results_with_http_info(self, project_id, **kwargs): """ Cached Project Validation Results ### Get Cached Project Validation Results Returns the cached results of a previous project validation calculation, if any. Returns http status 204 No Content if no validation results exist. Validating the content of all the files in a project can be computationally intensive for large projects. Use this API to simply fetch the results of the most recent project validation rather than revalidating the entire project from scratch. A value of `\"stale\": true` in the response indicates that the project has changed since the cached validation results were computed. The cached validation results may no longer reflect the current state of the project. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project_validation_results_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: ProjectValidationCache If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method project_validation_results" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `project_validation_results`") collection_formats = {} resource_path = '/projects/{project_id}/validate'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ProjectValidationCache', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def project_workspace(self, project_id, **kwargs): """ Get Project Workspace ### Get Project Workspace Returns information about the state of the project files in the currently selected workspace This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project_workspace(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: ProjectWorkspace If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.project_workspace_with_http_info(project_id, **kwargs) else: (data) = self.project_workspace_with_http_info(project_id, **kwargs) return data def project_workspace_with_http_info(self, project_id, **kwargs): """ Get Project Workspace ### Get Project Workspace Returns information about the state of the project files in the currently selected workspace This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.project_workspace_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: ProjectWorkspace If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method project_workspace" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `project_workspace`") collection_formats = {} resource_path = '/projects/{project_id}/current_workspace'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ProjectWorkspace', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def reset_project_to_production(self, project_id, **kwargs): """ Reset To Production ### Reset a project to the revision of the project that is in production. **DANGER** this will delete any changes that have not been pushed to a remote repository. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.reset_project_to_production(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Id of project (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.reset_project_to_production_with_http_info(project_id, **kwargs) else: (data) = self.reset_project_to_production_with_http_info(project_id, **kwargs) return data def reset_project_to_production_with_http_info(self, project_id, **kwargs): """ Reset To Production ### Reset a project to the revision of the project that is in production. **DANGER** this will delete any changes that have not been pushed to a remote repository. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.reset_project_to_production_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Id of project (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method reset_project_to_production" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `reset_project_to_production`") collection_formats = {} resource_path = '/projects/{project_id}/reset_to_production'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def reset_project_to_remote(self, project_id, **kwargs): """ Reset To Remote ### Reset a project development branch to the revision of the project that is on the remote. **DANGER** this will delete any changes that have not been pushed to a remote repository. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.reset_project_to_remote(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Id of project (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.reset_project_to_remote_with_http_info(project_id, **kwargs) else: (data) = self.reset_project_to_remote_with_http_info(project_id, **kwargs) return data def reset_project_to_remote_with_http_info(self, project_id, **kwargs): """ Reset To Remote ### Reset a project development branch to the revision of the project that is on the remote. **DANGER** this will delete any changes that have not been pushed to a remote repository. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.reset_project_to_remote_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Id of project (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['project_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method reset_project_to_remote" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `reset_project_to_remote`") collection_formats = {} resource_path = '/projects/{project_id}/reset_to_remote'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def run_git_connection_test(self, project_id, test_id, **kwargs): """ Run Git Connection Test ### Run a git connection test Run the named test on the git service used by this project (or the dependency project for the provided remote_url) and return the result. This is intended to help debug git connections when things do not work properly, to give more helpful information about why a git url is not working with Looker. Tests should be run in the order they are returned by [Get All Git Connection Tests](#!/Project/all_git_connection_tests). This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.run_git_connection_test(project_id, test_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str test_id: Test Id (required) :param str remote_url: (Optional: leave blank for root project) The remote url for remote dependency to test. :return: GitConnectionTestResult If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.run_git_connection_test_with_http_info(project_id, test_id, **kwargs) else: (data) = self.run_git_connection_test_with_http_info(project_id, test_id, **kwargs) return data def run_git_connection_test_with_http_info(self, project_id, test_id, **kwargs): """ Run Git Connection Test ### Run a git connection test Run the named test on the git service used by this project (or the dependency project for the provided remote_url) and return the result. This is intended to help debug git connections when things do not work properly, to give more helpful information about why a git url is not working with Looker. Tests should be run in the order they are returned by [Get All Git Connection Tests](#!/Project/all_git_connection_tests). This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.run_git_connection_test_with_http_info(project_id, test_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str test_id: Test Id (required) :param str remote_url: (Optional: leave blank for root project) The remote url for remote dependency to test. :return: GitConnectionTestResult If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'test_id', 'remote_url'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method run_git_connection_test" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `run_git_connection_test`") # verify the required parameter 'test_id' is set if ('test_id' not in params) or (params['test_id'] is None): raise ValueError("Missing the required parameter `test_id` when calling `run_git_connection_test`") collection_formats = {} resource_path = '/projects/{project_id}/git_connection_tests/{test_id}'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] if 'test_id' in params: path_params['test_id'] = params['test_id'] query_params = {} if 'remote_url' in params: query_params['remote_url'] = params['remote_url'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='GitConnectionTestResult', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_git_branch(self, project_id, body, **kwargs): """ Update Project Git Branch ### Checkout and/or reset --hard an existing Git Branch Only allowed in development mode - Call `update_session` to select the 'dev' workspace. Checkout an existing branch if name field is different from the name of the currently checked out branch. Optionally specify a branch name, tag name or commit SHA to which the branch should be reset. **DANGER** hard reset will be force pushed to the remote. Unsaved changes and commits may be permanently lost. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_git_branch(project_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param GitBranch body: Git Branch (required) :return: GitBranch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.update_git_branch_with_http_info(project_id, body, **kwargs) else: (data) = self.update_git_branch_with_http_info(project_id, body, **kwargs) return data def update_git_branch_with_http_info(self, project_id, body, **kwargs): """ Update Project Git Branch ### Checkout and/or reset --hard an existing Git Branch Only allowed in development mode - Call `update_session` to select the 'dev' workspace. Checkout an existing branch if name field is different from the name of the currently checked out branch. Optionally specify a branch name, tag name or commit SHA to which the branch should be reset. **DANGER** hard reset will be force pushed to the remote. Unsaved changes and commits may be permanently lost. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_git_branch_with_http_info(project_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param GitBranch body: Git Branch (required) :return: GitBranch If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'body'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_git_branch" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `update_git_branch`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `update_git_branch`") collection_formats = {} resource_path = '/projects/{project_id}/git_branch'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='GitBranch', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_project(self, project_id, body, **kwargs): """ Update Project ### Update Project Configuration Apply changes to a project's configuration. #### Configuring Git for a Project To set up a Looker project with a remote git repository, follow these steps: 1. Call `update_session` to select the 'dev' workspace. 1. Call `create_git_deploy_key` to create a new deploy key for the project 1. Copy the deploy key text into the remote git repository's ssh key configuration 1. Call `update_project` to set project's `git_remote_url` ()and `git_service_name`, if necessary). When you modify a project's `git_remote_url`, Looker connects to the remote repository to fetch metadata. The remote git repository MUST be configured with the Looker-generated deploy key for this project prior to setting the project's `git_remote_url`. To set up a Looker project with a git repository residing on the Looker server (a 'bare' git repo): 1. Call `update_session` to select the 'dev' workspace. 1. Call `update_project` setting `git_remote_url` to nil and `git_service_name` to \"bare\". This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_project(project_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param Project body: Project (required) :param str fields: Requested fields :return: Project If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.update_project_with_http_info(project_id, body, **kwargs) else: (data) = self.update_project_with_http_info(project_id, body, **kwargs) return data def update_project_with_http_info(self, project_id, body, **kwargs): """ Update Project ### Update Project Configuration Apply changes to a project's configuration. #### Configuring Git for a Project To set up a Looker project with a remote git repository, follow these steps: 1. Call `update_session` to select the 'dev' workspace. 1. Call `create_git_deploy_key` to create a new deploy key for the project 1. Copy the deploy key text into the remote git repository's ssh key configuration 1. Call `update_project` to set project's `git_remote_url` ()and `git_service_name`, if necessary). When you modify a project's `git_remote_url`, Looker connects to the remote repository to fetch metadata. The remote git repository MUST be configured with the Looker-generated deploy key for this project prior to setting the project's `git_remote_url`. To set up a Looker project with a git repository residing on the Looker server (a 'bare' git repo): 1. Call `update_session` to select the 'dev' workspace. 1. Call `update_project` setting `git_remote_url` to nil and `git_service_name` to \"bare\". This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_project_with_http_info(project_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param Project body: Project (required) :param str fields: Requested fields :return: Project If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'body', 'fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_project" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `update_project`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `update_project`") collection_formats = {} resource_path = '/projects/{project_id}'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Project', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_repository_credential(self, root_project_id, credential_id, body, **kwargs): """ Create Repository Credential ### Configure Repository Credential for a remote dependency Admin required. `root_project_id` is required. `credential_id` is required. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_repository_credential(root_project_id, credential_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str root_project_id: Root Project Id (required) :param str credential_id: Credential Id (required) :param RepositoryCredential body: Remote Project Information (required) :return: RepositoryCredential If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.update_repository_credential_with_http_info(root_project_id, credential_id, body, **kwargs) else: (data) = self.update_repository_credential_with_http_info(root_project_id, credential_id, body, **kwargs) return data def update_repository_credential_with_http_info(self, root_project_id, credential_id, body, **kwargs): """ Create Repository Credential ### Configure Repository Credential for a remote dependency Admin required. `root_project_id` is required. `credential_id` is required. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.update_repository_credential_with_http_info(root_project_id, credential_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str root_project_id: Root Project Id (required) :param str credential_id: Credential Id (required) :param RepositoryCredential body: Remote Project Information (required) :return: RepositoryCredential If the method is called asynchronously, returns the request thread. """ all_params = ['root_project_id', 'credential_id', 'body'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_repository_credential" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'root_project_id' is set if ('root_project_id' not in params) or (params['root_project_id'] is None): raise ValueError("Missing the required parameter `root_project_id` when calling `update_repository_credential`") # verify the required parameter 'credential_id' is set if ('credential_id' not in params) or (params['credential_id'] is None): raise ValueError("Missing the required parameter `credential_id` when calling `update_repository_credential`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `update_repository_credential`") collection_formats = {} resource_path = '/projects/{root_project_id}/credential/{credential_id}'.replace('{format}', 'json') path_params = {} if 'root_project_id' in params: path_params['root_project_id'] = params['root_project_id'] if 'credential_id' in params: path_params['credential_id'] = params['credential_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RepositoryCredential', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def validate_project(self, project_id, **kwargs): """ Validate Project ### Validate Project Performs lint validation of all lookml files in the project. Returns a list of errors found, if any. Validating the content of all the files in a project can be computationally intensive for large projects. For best performance, call `validate_project(project_id)` only when you really want to recompute project validation. To quickly display the results of the most recent project validation (without recomputing), use `project_validation_results(project_id)` This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.validate_project(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: ProjectValidation If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.validate_project_with_http_info(project_id, **kwargs) else: (data) = self.validate_project_with_http_info(project_id, **kwargs) return data def validate_project_with_http_info(self, project_id, **kwargs): """ Validate Project ### Validate Project Performs lint validation of all lookml files in the project. Returns a list of errors found, if any. Validating the content of all the files in a project can be computationally intensive for large projects. For best performance, call `validate_project(project_id)` only when you really want to recompute project validation. To quickly display the results of the most recent project validation (without recomputing), use `project_validation_results(project_id)` This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.validate_project_with_http_info(project_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str project_id: Project Id (required) :param str fields: Requested fields :return: ProjectValidation If the method is called asynchronously, returns the request thread. """ all_params = ['project_id', 'fields'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method validate_project" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'project_id' is set if ('project_id' not in params) or (params['project_id'] is None): raise ValueError("Missing the required parameter `project_id` when calling `validate_project`") collection_formats = {} resource_path = '/projects/{project_id}/validate'.replace('{format}', 'json') path_params = {} if 'project_id' in params: path_params['project_id'] = params['project_id'] query_params = {} if 'fields' in params: query_params['fields'] = params['fields'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ProjectValidation', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

48.089353

4,190

0.595882

15,277

140,469

5.258166

0.036984

0.051986

0.018125

0.023304

0.946856

0.941777

0.937507

0.93081

0.926714

0.920153

0

0.00072

0.327353

140,469

2,920

4,191

48.105822

0.849449

0.390791

0

0.83195

0

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1

0.036653

false

0

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0

1

0

1

0

1

0

null

0

8

8a9682a5a98d86f6db38ea59da25b965efb309df

1,073

py

Python

processor/tests/conftest.py

soote1/bettingtool

96472d05476088f44b3469c7d89722efe0f62d35

[ "MIT" ]

1

2020-07-18T19:07:28.000Z

processor/tests/conftest.py

soote1/bettingtool

96472d05476088f44b3469c7d89722efe0f62d35

[ "MIT" ]

4

2020-06-20T02:15:00.000Z

2021-12-13T20:47:42.000Z

processor/tests/conftest.py

soote1/bettingtool

96472d05476088f44b3469c7d89722efe0f62d35

[ "MIT" ]

1

2020-07-20T13:23:11.000Z

import pytest def processor_input_sample(): return '{"game_id": "https://sports.caliente.mx/es_MX/La-Liga/20200626/Sevilla-vs-Valladolid", "game_type": "correct_score", "odds": [[" 1-0 ", "4/1", "5.00", "+400"], [" 0-0 ", "8/1", "9.00", "+800"], [" 0-1 ", "16/1", "17.00", "+1600"], [" 2-0 ", "4/1", "5.00", "+400"], [" 1-1 ", "8/1", "9.00", "+800"], [" 0-2 ", "55/1", "56.00", "+5500"], [" 2-1 ", "8/1", "9.00", "+800"], [" 2-2 ", "30/1", "31.00", "+3000"], [" 1-2 ", "30/1", "31.00", "+3000"], [" 3-0 ", "7/1", "8.00", "+700"], [" 3-3 ", "125/1", "126.00", "+12500"], [" 1-3 ", "125/1", "126.00", "+12500"], [" 3-1 ", "12/1", "13.00", "+1200"], [" 2-3 ", "125/1", "126.00", "+12500"], [" 3-2 ", "45/1", "46.00", "+4500"], [" 4-0 ", "14/1", "15.00", "+1400"], [" 4-1 ", "25/1", "26.00", "+2500"], [" 4-2 ", "75/1", "76.00", "+7500"], [" 5-0 ", "28/1", "29.00", "+2800"], [" 5-1 ", "45/1", "46.00", "+4500"], [" 5-2 ", "100/1", "101.00", "+10000"], [" 6-0 ", "66/1", "67.00", "+6600"], [" 6-1 ", "90/1", "91.00", "+9000"]], "crawled_at": "2020-06-26 19:05:24.788499"}'

268.25

1,028

0.426841

196

1,073

2.30102

0.433673

0.013304

0.019956

0.033259

0.308204

0.259424

0.070953

0

0.349673

0.144455

1,073

4

1,028

268.25

0.141612

0

0.333333

0.945065

0

1

0.333333

true

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1

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null

0

1

0

1

0

1

0

null

0

1

0

1

0

12

8aa2ebb28dc10e9ed6891b9c45315c8db5575b45

44

py

Python

sol/sol_count_hi.py

igamberdievhasan/codingbat-notebooks

b0a41f22b9064efc7f7f7da55e8c99fc21ce364d

[ "Apache-2.0" ]

null

sol/sol_count_hi.py

igamberdievhasan/codingbat-notebooks

b0a41f22b9064efc7f7f7da55e8c99fc21ce364d

[ "Apache-2.0" ]

6

2020-03-02T20:59:43.000Z

2020-03-18T01:20:30.000Z

sol/sol_count_hi.py

igamberdievhasan/codingbat-notebooks

b0a41f22b9064efc7f7f7da55e8c99fc21ce364d

[ "Apache-2.0" ]

1

2020-03-13T02:48:04.000Z

def count_hi(str): return str.count("hi")

14.666667

24

0.681818

8

44

3.625

0.625

0.482759

0

0.136364

44

2

25

22

0.763158

0

0.045455

0

1

0.5

false

0

0.5

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

8aac7e02f9e0aba7ba46166890294f64442e5953

35,594

py

Python

looker_client_31/api/look_api.py

ContrastingSounds/looker_sdk_31

f973434049fff1b605b10086ab8b84f2f62e3489

[ "MIT" ]

null

looker_client_31/api/look_api.py

ContrastingSounds/looker_sdk_31

f973434049fff1b605b10086ab8b84f2f62e3489

[ "MIT" ]

null

looker_client_31/api/look_api.py

ContrastingSounds/looker_sdk_31

f973434049fff1b605b10086ab8b84f2f62e3489

[ "MIT" ]

null

# coding: utf-8 """ Experimental Looker API 3.1 Preview This API 3.1 is in active development. Breaking changes are likely to occur to some API functions in future Looker releases until API 3.1 is officially launched and upgraded to beta status. If you have time and interest to experiment with new or modified services exposed in this embryonic API 3.1, we welcome your participation and feedback! For large development efforts or critical line-of-business projects, we strongly recommend you stick with the API 3.0 while API 3.1 is under construction. # noqa: E501 OpenAPI spec version: 3.1.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from looker_client_31.api_client import ApiClient class LookApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def all_looks(self, **kwargs): # noqa: E501 """Get All Looks # noqa: E501 ### Get all the looks. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.all_looks(async=True) >>> result = thread.get() :param async bool :param str fields: Requested fields. :return: list[Look] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.all_looks_with_http_info(**kwargs) # noqa: E501 else: (data) = self.all_looks_with_http_info(**kwargs) # noqa: E501 return data def all_looks_with_http_info(self, **kwargs): # noqa: E501 """Get All Looks # noqa: E501 ### Get all the looks. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.all_looks_with_http_info(async=True) >>> result = thread.get() :param async bool :param str fields: Requested fields. :return: list[Look] If the method is called asynchronously, returns the request thread. """ all_params = ['fields'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method all_looks" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'fields' in params: query_params.append(('fields', params['fields'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/looks', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Look]', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def create_look(self, **kwargs): # noqa: E501 """Create Look # noqa: E501 ### Create a Look with specified information. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.create_look(async=True) >>> result = thread.get() :param async bool :param LookWithQuery body: Look :param str fields: Requested fields. :return: LookWithQuery If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.create_look_with_http_info(**kwargs) # noqa: E501 else: (data) = self.create_look_with_http_info(**kwargs) # noqa: E501 return data def create_look_with_http_info(self, **kwargs): # noqa: E501 """Create Look # noqa: E501 ### Create a Look with specified information. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.create_look_with_http_info(async=True) >>> result = thread.get() :param async bool :param LookWithQuery body: Look :param str fields: Requested fields. :return: LookWithQuery If the method is called asynchronously, returns the request thread. """ all_params = ['body', 'fields'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_look" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'fields' in params: query_params.append(('fields', params['fields'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/looks', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='LookWithQuery', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_look(self, look_id, **kwargs): # noqa: E501 """Delete Look # noqa: E501 ### Delete the look with a specific id. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.delete_look(look_id, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.delete_look_with_http_info(look_id, **kwargs) # noqa: E501 else: (data) = self.delete_look_with_http_info(look_id, **kwargs) # noqa: E501 return data def delete_look_with_http_info(self, look_id, **kwargs): # noqa: E501 """Delete Look # noqa: E501 ### Delete the look with a specific id. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.delete_look_with_http_info(look_id, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['look_id'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_look" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'look_id' is set if ('look_id' not in params or params['look_id'] is None): raise ValueError("Missing the required parameter `look_id` when calling `delete_look`") # noqa: E501 collection_formats = {} path_params = {} if 'look_id' in params: path_params['look_id'] = params['look_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/looks/{look_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def look(self, look_id, **kwargs): # noqa: E501 """Get Look # noqa: E501 ### Get a Look. Return detailed information about the Look and its associated Query. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.look(look_id, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :param str fields: Requested fields. :return: LookWithQuery If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.look_with_http_info(look_id, **kwargs) # noqa: E501 else: (data) = self.look_with_http_info(look_id, **kwargs) # noqa: E501 return data def look_with_http_info(self, look_id, **kwargs): # noqa: E501 """Get Look # noqa: E501 ### Get a Look. Return detailed information about the Look and its associated Query. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.look_with_http_info(look_id, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :param str fields: Requested fields. :return: LookWithQuery If the method is called asynchronously, returns the request thread. """ all_params = ['look_id', 'fields'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method look" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'look_id' is set if ('look_id' not in params or params['look_id'] is None): raise ValueError("Missing the required parameter `look_id` when calling `look`") # noqa: E501 collection_formats = {} path_params = {} if 'look_id' in params: path_params['look_id'] = params['look_id'] # noqa: E501 query_params = [] if 'fields' in params: query_params.append(('fields', params['fields'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/looks/{look_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='LookWithQuery', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def run_look(self, look_id, result_format, **kwargs): # noqa: E501 """Run Look # noqa: E501 ### Run a Look. Runs a given look's query and returns the results in the requested format. Suported formats: | result_format | Description | :-----------: | :--- | | json | Plain json | json_detail | Row data plus metadata describing the fields, pivots, table calcs, and other aspects of the query | csv | Comma separated values with a header | txt | Tab separated values with a header | html | Simple html | md | Simple markdown | xlsx | MS Excel spreadsheet | sql | Returns the generated SQL rather than running the query | png | A PNG image of the visualization of the query | jpg | A JPG image of the visualization of the query # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.run_look(look_id, result_format, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :param str result_format: Format of result (required) :param int limit: Row limit (may override the limit in the saved query). :param bool apply_formatting: Apply model-specified formatting to each result. :param bool apply_vis: Apply visualization options to results. :param bool cache: Get results from cache if available. :param int image_width: Render width for image formats. :param int image_height: Render height for image formats. :param bool generate_drill_links: Generate drill links (only applicable to 'json_detail' format. :param bool force_production: Force use of production models even if the user is in development mode. :param bool cache_only: Retrieve any results from cache even if the results have expired. :param str path_prefix: Prefix to use for drill links (url encoded). :param bool rebuild_pdts: Rebuild PDTS used in query. :param bool server_table_calcs: Perform table calculations on query results :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.run_look_with_http_info(look_id, result_format, **kwargs) # noqa: E501 else: (data) = self.run_look_with_http_info(look_id, result_format, **kwargs) # noqa: E501 return data def run_look_with_http_info(self, look_id, result_format, **kwargs): # noqa: E501 """Run Look # noqa: E501 ### Run a Look. Runs a given look's query and returns the results in the requested format. Suported formats: | result_format | Description | :-----------: | :--- | | json | Plain json | json_detail | Row data plus metadata describing the fields, pivots, table calcs, and other aspects of the query | csv | Comma separated values with a header | txt | Tab separated values with a header | html | Simple html | md | Simple markdown | xlsx | MS Excel spreadsheet | sql | Returns the generated SQL rather than running the query | png | A PNG image of the visualization of the query | jpg | A JPG image of the visualization of the query # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.run_look_with_http_info(look_id, result_format, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :param str result_format: Format of result (required) :param int limit: Row limit (may override the limit in the saved query). :param bool apply_formatting: Apply model-specified formatting to each result. :param bool apply_vis: Apply visualization options to results. :param bool cache: Get results from cache if available. :param int image_width: Render width for image formats. :param int image_height: Render height for image formats. :param bool generate_drill_links: Generate drill links (only applicable to 'json_detail' format. :param bool force_production: Force use of production models even if the user is in development mode. :param bool cache_only: Retrieve any results from cache even if the results have expired. :param str path_prefix: Prefix to use for drill links (url encoded). :param bool rebuild_pdts: Rebuild PDTS used in query. :param bool server_table_calcs: Perform table calculations on query results :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['look_id', 'result_format', 'limit', 'apply_formatting', 'apply_vis', 'cache', 'image_width', 'image_height', 'generate_drill_links', 'force_production', 'cache_only', 'path_prefix', 'rebuild_pdts', 'server_table_calcs'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method run_look" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'look_id' is set if ('look_id' not in params or params['look_id'] is None): raise ValueError("Missing the required parameter `look_id` when calling `run_look`") # noqa: E501 # verify the required parameter 'result_format' is set if ('result_format' not in params or params['result_format'] is None): raise ValueError("Missing the required parameter `result_format` when calling `run_look`") # noqa: E501 collection_formats = {} path_params = {} if 'look_id' in params: path_params['look_id'] = params['look_id'] # noqa: E501 if 'result_format' in params: path_params['result_format'] = params['result_format'] # noqa: E501 query_params = [] if 'limit' in params: query_params.append(('limit', params['limit'])) # noqa: E501 if 'apply_formatting' in params: query_params.append(('apply_formatting', params['apply_formatting'])) # noqa: E501 if 'apply_vis' in params: query_params.append(('apply_vis', params['apply_vis'])) # noqa: E501 if 'cache' in params: query_params.append(('cache', params['cache'])) # noqa: E501 if 'image_width' in params: query_params.append(('image_width', params['image_width'])) # noqa: E501 if 'image_height' in params: query_params.append(('image_height', params['image_height'])) # noqa: E501 if 'generate_drill_links' in params: query_params.append(('generate_drill_links', params['generate_drill_links'])) # noqa: E501 if 'force_production' in params: query_params.append(('force_production', params['force_production'])) # noqa: E501 if 'cache_only' in params: query_params.append(('cache_only', params['cache_only'])) # noqa: E501 if 'path_prefix' in params: query_params.append(('path_prefix', params['path_prefix'])) # noqa: E501 if 'rebuild_pdts' in params: query_params.append(('rebuild_pdts', params['rebuild_pdts'])) # noqa: E501 if 'server_table_calcs' in params: query_params.append(('server_table_calcs', params['server_table_calcs'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['text', 'application/json', 'image/png', 'image/jpg']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/looks/{look_id}/run/{result_format}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def search_looks(self, **kwargs): # noqa: E501 """Search Looks # noqa: E501 Search looks. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.search_looks(async=True) >>> result = thread.get() :param async bool :param str fields: Requested fields. :param int page: Requested page. :param int per_page: Results per page. :param int limit: Number of results to return. (used with offset and takes priority over page and per_page) :param int offset: Number of results to skip before returning any. (used with limit and takes priority over page and per_page) :param str sorts: Fields to sort by. :param str title: Match Look title. :param str description: Match Look description. :param int content_favorite_id: Match content favorite id :param str space_id: Filter on a particular space. :param str user_id: Filter on dashboards created by a particular user. :param str view_count: Filter on a particular value of view_count :return: list[Look] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.search_looks_with_http_info(**kwargs) # noqa: E501 else: (data) = self.search_looks_with_http_info(**kwargs) # noqa: E501 return data def search_looks_with_http_info(self, **kwargs): # noqa: E501 """Search Looks # noqa: E501 Search looks. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.search_looks_with_http_info(async=True) >>> result = thread.get() :param async bool :param str fields: Requested fields. :param int page: Requested page. :param int per_page: Results per page. :param int limit: Number of results to return. (used with offset and takes priority over page and per_page) :param int offset: Number of results to skip before returning any. (used with limit and takes priority over page and per_page) :param str sorts: Fields to sort by. :param str title: Match Look title. :param str description: Match Look description. :param int content_favorite_id: Match content favorite id :param str space_id: Filter on a particular space. :param str user_id: Filter on dashboards created by a particular user. :param str view_count: Filter on a particular value of view_count :return: list[Look] If the method is called asynchronously, returns the request thread. """ all_params = ['fields', 'page', 'per_page', 'limit', 'offset', 'sorts', 'title', 'description', 'content_favorite_id', 'space_id', 'user_id', 'view_count'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method search_looks" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'fields' in params: query_params.append(('fields', params['fields'])) # noqa: E501 if 'page' in params: query_params.append(('page', params['page'])) # noqa: E501 if 'per_page' in params: query_params.append(('per_page', params['per_page'])) # noqa: E501 if 'limit' in params: query_params.append(('limit', params['limit'])) # noqa: E501 if 'offset' in params: query_params.append(('offset', params['offset'])) # noqa: E501 if 'sorts' in params: query_params.append(('sorts', params['sorts'])) # noqa: E501 if 'title' in params: query_params.append(('title', params['title'])) # noqa: E501 if 'description' in params: query_params.append(('description', params['description'])) # noqa: E501 if 'content_favorite_id' in params: query_params.append(('content_favorite_id', params['content_favorite_id'])) # noqa: E501 if 'space_id' in params: query_params.append(('space_id', params['space_id'])) # noqa: E501 if 'user_id' in params: query_params.append(('user_id', params['user_id'])) # noqa: E501 if 'view_count' in params: query_params.append(('view_count', params['view_count'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/looks/search', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Look]', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_look(self, look_id, body, **kwargs): # noqa: E501 """Update Look # noqa: E501 ### Update the Look with a specific id. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.update_look(look_id, body, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :param LookWithQuery body: Look (required) :param str fields: Requested fields. :return: LookWithQuery If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.update_look_with_http_info(look_id, body, **kwargs) # noqa: E501 else: (data) = self.update_look_with_http_info(look_id, body, **kwargs) # noqa: E501 return data def update_look_with_http_info(self, look_id, body, **kwargs): # noqa: E501 """Update Look # noqa: E501 ### Update the Look with a specific id. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.update_look_with_http_info(look_id, body, async=True) >>> result = thread.get() :param async bool :param int look_id: Id of look (required) :param LookWithQuery body: Look (required) :param str fields: Requested fields. :return: LookWithQuery If the method is called asynchronously, returns the request thread. """ all_params = ['look_id', 'body', 'fields'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_look" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'look_id' is set if ('look_id' not in params or params['look_id'] is None): raise ValueError("Missing the required parameter `look_id` when calling `update_look`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `update_look`") # noqa: E501 collection_formats = {} path_params = {} if 'look_id' in params: path_params['look_id'] = params['look_id'] # noqa: E501 query_params = [] if 'fields' in params: query_params.append(('fields', params['fields'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/looks/{look_id}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='LookWithQuery', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

42.576555

659

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35,594

4.886289

0.072064

0.052863

0.030933

0.024133

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null

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null

0

1

0

1

0

null

0

1

0

8

8ad642b18a67ece3f54822b8edb719c4022cde82

472

py

Python

lifelines/__init__.py

fmfn/lifelines

fec81897674ebeb3223efba48b99e7b1302cdf9e

[ "MIT" ]

2

2020-02-06T09:24:09.000Z

2021-03-20T08:10:26.000Z

lifelines/__init__.py

fmfn/lifelines

fec81897674ebeb3223efba48b99e7b1302cdf9e

[ "MIT" ]

null

lifelines/__init__.py

fmfn/lifelines

fec81897674ebeb3223efba48b99e7b1302cdf9e

[ "MIT" ]

1

2018-05-08T08:10:12.000Z

# -*- coding: utf-8 -*- from .estimation import KaplanMeierFitter, NelsonAalenFitter, \ AalenAdditiveFitter, BreslowFlemingHarringtonFitter, CoxPHFitter, \ WeibullFitter, ExponentialFitter, SBGSurvival import lifelines.datasets from .version import __version__ __all__ = ['KaplanMeierFitter', 'NelsonAalenFitter', 'AalenAdditiveFitter', 'BreslowFlemingHarringtonFitter', 'CoxPHFitter', 'WeibullFitter', 'ExponentialFitter', 'SBGSurvival']

36.307692

76

0.758475

30

472

11.666667

0.6

0.194286

0.302857

0.474286

0.771429

0

0.002469

0.141949

472

12

77

39.333333

0.861728

0.044492

0

0.300668

0.066815

0

1

0

false

0

0.375

0

0.375

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1

null

0

1

0

1

0

null

0

1

0

7

76d04d7055ca8b102379be6a2ddf47f7f79a7a9d

102,686

py

Python

eeauditor/auditors/aws/AWS_IAM_Auditor.py

kbhagi/ElectricEye

31960e1e1cfb75c5d354844ea9e07d5295442823

[ "Apache-2.0" ]

442

2020-03-15T20:56:36.000Z

2022-03-31T22:13:07.000Z

eeauditor/auditors/aws/AWS_IAM_Auditor.py

kbhagi/ElectricEye

31960e1e1cfb75c5d354844ea9e07d5295442823

[ "Apache-2.0" ]

57

2020-03-15T22:09:56.000Z

2022-03-31T13:17:06.000Z

eeauditor/auditors/aws/AWS_IAM_Auditor.py

kbhagi/ElectricEye

31960e1e1cfb75c5d354844ea9e07d5295442823

[ "Apache-2.0" ]

59

2020-03-15T21:19:10.000Z

2022-03-31T15:01:31.000Z

#This file is part of ElectricEye. #SPDX-License-Identifier: Apache-2.0 #Licensed to the Apache Software Foundation (ASF) under one #or more contributor license agreements. See the NOTICE file #distributed with this work for additional information #regarding copyright ownership. The ASF licenses this file #to you 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 boto3 import datetime from check_register import CheckRegister import json registry = CheckRegister() # import boto3 clients iam = boto3.client("iam") # loop through IAM users def list_users(cache): response = cache.get("list_users") if response: return response cache["list_users"] = iam.list_users(MaxItems=1000) return cache["list_users"] @registry.register_check("iam") def iam_access_key_age_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.1] IAM Access Keys should be rotated every 90 days""" user = list_users(cache=cache) for users in user["Users"]: userName = str(users["UserName"]) userArn = str(users["Arn"]) try: response = iam.list_access_keys(UserName=userName) for keys in response["AccessKeyMetadata"]: keyUserName = str(keys["UserName"]) keyId = str(keys["AccessKeyId"]) keyStatus = str(keys["Status"]) # ISO Time iso8601Time = ( datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() ) if keyStatus == "Active": keyCreateDate = keys["CreateDate"] todaysDatetime = datetime.datetime.now(datetime.timezone.utc) keyAgeFinder = todaysDatetime - keyCreateDate if keyAgeFinder <= datetime.timedelta(days=90): # this is a passing check finding = { "SchemaVersion": "2018-10-08", "Id": keyUserName + keyId + "/iam-access-key-age-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn + keyId, "AwsAccountId": awsAccountId, "Types": [ "Software and Configuration Checks/AWS Security Best Practices" ], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.1] IAM Access Keys should be rotated every 90 days", "Description": "IAM access key " + keyId + " for user " + keyUserName + " is not over 90 days old.", "Remediation": { "Recommendation": { "Text": "For information on IAM access key rotation refer to the Rotating Access Keys section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html#Using_RotateAccessKey", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamAccessKey", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": { "AwsIamAccessKey": { "PrincipalId": keyId, "PrincipalName": keyUserName, "Status": keyStatus, } }, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding else: finding = { "SchemaVersion": "2018-10-08", "Id": keyUserName + keyId + "/iam-access-key-age-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn + keyId, "AwsAccountId": awsAccountId, "Types": [ "Software and Configuration Checks/AWS Security Best Practices" ], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "MEDIUM"}, "Confidence": 99, "Title": "[IAM.1] IAM Access Keys should be rotated every 90 days", "Description": "IAM access key " + keyId + " for user " + keyUserName + " is over 90 days old. As a security best practice, AWS recommends that you regularly rotate (change) IAM user access keys. If your administrator granted you the necessary permissions, you can rotate your own access keys. Refer to the remediation section to remediate this behavior.", "Remediation": { "Recommendation": { "Text": "For information on IAM access key rotation refer to the Rotating Access Keys section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html#Using_RotateAccessKey", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamAccessKey", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": { "AwsIamAccessKey": { "PrincipalId": keyId, "PrincipalName": keyUserName, "Status": keyStatus, } }, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding else: pass except Exception as e: print(e) @registry.register_check("iam") def user_permission_boundary_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """aaa""" user = list_users(cache=cache) for users in user["Users"]: userName = str(users["UserName"]) userArn = str(users["Arn"]) # ISO Time iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() try: permBoundaryArn = str(users["PermissionsBoundary"]["PermissionsBoundaryArn"]) # this is a passing check finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-permissions-boundary-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.2] IAM users should have permissions boundaries attached", "Description": "IAM user " + userName + " has a permissions boundary attached.", "Remediation": { "Recommendation": { "Text": "For information on permissions boundaries refer to the Permissions Boundaries for IAM Entities section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_boundaries.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": { "Other": { "PrincipalName": userName, "permissionsBoundaryArn": permBoundaryArn, } }, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-4", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 AC-3", "NIST SP 800-53 AC-5", "NIST SP 800-53 AC-6", "NIST SP 800-53 AC-14", "NIST SP 800-53 AC-16", "NIST SP 800-53 AC-24", "AICPA TSC CC6.3", "ISO 27001:2013 A.6.1.2", "ISO 27001:2013 A.9.1.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.4.1", "ISO 27001:2013 A.9.4.4", "ISO 27001:2013 A.9.4.5", ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding except Exception as e: if str(e) == "'PermissionsBoundary'": finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-permissions-boundary-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "MEDIUM"}, "Confidence": 99, "Title": "[IAM.2] IAM users should have permissions boundaries attached", "Description": "IAM user " + userName + " does not have a permissions boundary attached. A permissions boundary is an advanced feature for using a managed policy to set the maximum permissions that an identity-based policy can grant to an IAM entity. A permissions boundary allows it to perform only the actions that are allowed by both its identity-based policies and its permissions boundaries. Refer to the remediation section to remediate this behavior.", "Remediation": { "Recommendation": { "Text": "For information on permissions boundaries refer to the Permissions Boundaries for IAM Entities section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_boundaries.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PrincipalName": userName}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-4", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 AC-3", "NIST SP 800-53 AC-5", "NIST SP 800-53 AC-6", "NIST SP 800-53 AC-14", "NIST SP 800-53 AC-16", "NIST SP 800-53 AC-24", "AICPA TSC CC6.3", "ISO 27001:2013 A.6.1.2", "ISO 27001:2013 A.9.1.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.4.1", "ISO 27001:2013 A.9.4.4", "ISO 27001:2013 A.9.4.5", ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding else: print(e) @registry.register_check("iam") def user_mfa_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.3] IAM users should have Multi-Factor Authentication (MFA) enabled""" user = list_users(cache=cache) for users in user["Users"]: userName = str(users["UserName"]) userArn = str(users["Arn"]) # ISO Time iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() try: response = iam.list_mfa_devices(UserName=userName) if str(response["MFADevices"]) == "[]": finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-mfa-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "MEDIUM"}, "Confidence": 99, "Title": "[IAM.3] IAM users should have Multi-Factor Authentication (MFA) enabled", "Description": "IAM user " + userName + " does not have MFA enabled. For increased security, AWS recommends that you configure multi-factor authentication (MFA) to help protect your AWS resources. Refer to the remediation section to remediate this behavior.", "Remediation": { "Recommendation": { "Text": "For information on MFA refer to the Using Multi-Factor Authentication (MFA) in AWS section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_mfa.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PrincipalName": userName}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding else: finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-mfa-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.3] IAM users should have Multi-Factor Authentication (MFA) enabled", "Description": "IAM user " + userName + " has MFA enabled.", "Remediation": { "Recommendation": { "Text": "For information on MFA refer to the Using Multi-Factor Authentication (MFA) in AWS section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_mfa.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PrincipalName": userName}}, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding except Exception as e: print(e) @registry.register_check("iam") def user_inline_policy_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.4] IAM users should not have attached in-line policies""" user = list_users(cache=cache) allUsers = user["Users"] for users in allUsers: userName = str(users["UserName"]) userArn = str(users["Arn"]) # ISO Time iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() try: response = iam.list_user_policies(UserName=userName) if str(response["PolicyNames"]) != "[]": finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-attach-inline-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "LOW"}, "Confidence": 99, "Title": "[IAM.4] IAM users should not have attached in-line policies", "Description": "IAM user " + userName + " has an in-line policy attached. It is recommended that IAM policies be applied directly to groups and roles but not users. Refer to the remediation section to remediate this behavior.", "Remediation": { "Recommendation": { "Text": "For information on user attached policies refer to the Managed Policies and Inline Policies section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PrincipalName": userName}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding else: finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-attach-inline-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.4] IAM users should not have attached in-line policies", "Description": "IAM user " + userName + " does not have an in-line policy attached.", "Remediation": { "Recommendation": { "Text": "For information on user attached policies refer to the Managed Policies and Inline Policies section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PrincipalName": userName}}, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding except Exception as e: print(e) @registry.register_check("iam") def user_direct_attached_policy_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.5] IAM users should not have attached managed policies""" user = list_users(cache=cache) allUsers = user["Users"] for users in allUsers: userName = str(users["UserName"]) userArn = str(users["Arn"]) # ISO Time iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() try: response = iam.list_attached_user_policies(UserName=userName) if str(response["AttachedPolicies"]) != "[]": finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-attach-managed-policy-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "LOW"}, "Confidence": 99, "Title": "[IAM.5] IAM users should not have attached managed policies", "Description": "IAM user " + userName + " has a managed policy attached. It is recommended that IAM policies be applied directly to groups and roles but not users. Refer to the remediation section to remediate this behavior.", "Remediation": { "Recommendation": { "Text": "For information on user attached policies refer to the Managed Policies and Inline Policies section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PrincipalName": userName}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding else: finding = { "SchemaVersion": "2018-10-08", "Id": userArn + "/iam-user-attach-managed-policy-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": userArn, "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.5] IAM users should not have attached managed policies", "Description": "IAM user " + userName + " does not have a managed policy attached.", "Remediation": { "Recommendation": { "Text": "For information on user attached policies refer to the Managed Policies and Inline Policies section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": userArn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PrincipalName": userName}}, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding except Exception as e: print(e) @registry.register_check("iam") def cis_aws_foundation_benchmark_pw_policy_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.6] The IAM password policy should meet or exceed the AWS CIS Foundations Benchmark standard""" try: # TODO: if no policy is found, this will throw an exception in # which case we need to create an ACTIVE finding response = iam.get_account_password_policy() pwPolicy = response["PasswordPolicy"] minPwLength = int(pwPolicy["MinimumPasswordLength"]) symbolReq = str(pwPolicy["RequireSymbols"]) numberReq = str(pwPolicy["RequireNumbers"]) uppercaseReq = str(pwPolicy["RequireUppercaseCharacters"]) lowercaseReq = str(pwPolicy["RequireLowercaseCharacters"]) maxPwAge = int(pwPolicy["MaxPasswordAge"]) pwReuse = int(pwPolicy["PasswordReusePrevention"]) # ISO Time iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() if ( minPwLength >= 14 and maxPwAge <= 90 and pwReuse >= 24 and symbolReq == "True" and numberReq == "True" and uppercaseReq == "True" and lowercaseReq == "True" ): finding = { "SchemaVersion": "2018-10-08", "Id": awsAccountId + "/cis-aws-foundations-benchmark-pw-policy-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": awsAccountId + "iam-password-policy", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.6] The IAM password policy should meet or exceed the AWS CIS Foundations Benchmark standard", "Description": "The IAM password policy for account " + awsAccountId + " meets or exceeds the AWS CIS Foundations Benchmark standard.", "Remediation": { "Recommendation": { "Text": "For information on the CIS AWS Foundations Benchmark standard for the password policy refer to the linked Standard", "Url": "https://d1.awsstatic.com/whitepapers/compliance/AWS_CIS_Foundations_Benchmark.pdf", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsAccount", "Id": f"{awsPartition.upper()}::::Account:{awsAccountId}", "Partition": awsPartition, "Region": awsRegion, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding else: finding = { "SchemaVersion": "2018-10-08", "Id": awsAccountId + "/cis-aws-foundations-benchmark-pw-policy-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": awsAccountId + "iam-password-policy", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "MEDIUM"}, "Confidence": 99, "Title": "[IAM.6] The IAM password policy should meet or exceed the AWS CIS Foundations Benchmark standard", "Description": "The IAM password policy for account " + awsAccountId + " does not meet the AWS CIS Foundations Benchmark standard. Refer to the remediation instructions if this configuration is not intended.", "Remediation": { "Recommendation": { "Text": "For information on the CIS AWS Foundations Benchmark standard for the password policy refer to the linked Standard", "Url": "https://d1.awsstatic.com/whitepapers/compliance/AWS_CIS_Foundations_Benchmark.pdf", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsAccount", "Id": f"{awsPartition.upper()}::::Account:{awsAccountId}", "Partition": awsPartition, "Region": awsRegion, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding except Exception as e: print(e) @registry.register_check("iam") def server_certs_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.7] There should not be any server certificates stored in AWS IAM""" try: response = iam.list_server_certificates() # ISO Time iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() if str(response["ServerCertificateMetadataList"]) != "[]": finding = { "SchemaVersion": "2018-10-08", "Id": awsAccountId + "/server-x509-certs-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": awsAccountId + "server-cert", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "MEDIUM"}, "Confidence": 99, "Title": "[IAM.7] There should not be any server certificates stored in AWS IAM", "Description": "There are server certificates stored in AWS IAM for the account " + awsAccountId + ". ACM is the preferred tool to provision, manage, and deploy your server certificates. With ACM you can request a certificate or deploy an existing ACM or external certificate to AWS resources. Certificates provided by ACM are free and automatically renew. Refer to the remediation instructions if this configuration is not intended.", "Remediation": { "Recommendation": { "Text": "For information on server certificates refer to the Working with Server Certificates section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_server-certs.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsAccount", "Id": f"{awsPartition.upper()}::::Account:{awsAccountId}", "Partition": awsPartition, "Region": awsRegion, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding else: finding = { "SchemaVersion": "2018-10-08", "Id": awsAccountId + "/server-x509-certs-check", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": awsAccountId + "server-cert", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.7] There should not be any server certificates stored in AWS IAM", "Description": "There are not server certificates stored in AWS IAM for the account " + awsAccountId + ".", "Remediation": { "Recommendation": { "Text": "For information on server certificates refer to the Working with Server Certificates section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_server-certs.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsAccount", "Id": f"{awsPartition.upper()}::::Account:{awsAccountId}", "Partition": awsPartition, "Region": awsRegion, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-1", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-2", "NIST SP 800-53 IA-1", "NIST SP 800-53 IA-2", "NIST SP 800-53 IA-3", "NIST SP 800-53 IA-4", "NIST SP 800-53 IA-5", "NIST SP 800-53 IA-6", "NIST SP 800-53 IA-7", "NIST SP 800-53 IA-8", "NIST SP 800-53 IA-9", "NIST SP 800-53 IA-10", "NIST SP 800-53 IA-11", "AICPA TSC CC6.1", "AICPA TSC CC6.2", "ISO 27001:2013 A.9.2.1", "ISO 27001:2013 A.9.2.2", "ISO 27001:2013 A.9.2.3", "ISO 27001:2013 A.9.2.4", "ISO 27001:2013 A.9.2.6", "ISO 27001:2013 A.9.3.1", "ISO 27001:2013 A.9.4.2", "ISO 27001:2013 A.9.4.3", ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding except Exception as e: print(e) @registry.register_check("iam") def iam_mngd_policy_least_priv_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.8] Managed policies should follow least privilege principles""" try: policies = iam.list_policies(Scope='Local') for mngd_policy in policies['Policies']: policy_arn = mngd_policy['Arn'] version_id = mngd_policy['DefaultVersionId'] policy_doc = iam.get_policy_version( PolicyArn=policy_arn, VersionId=version_id )['PolicyVersion']['Document'] #handle policies docs returned as strings if type(policy_doc) == str: policy_doc = json.loads(policy_doc) least_priv_rating = 'passing' for statement in policy_doc['Statement']: if statement["Effect"] == 'Allow': if statement.get('Condition') == None: # action structure could be a string or a list if type(statement['Action']) == list: if len(['True' for x in statement['Action'] if ":*" in x or '*' == x]) > 0: if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' # Single action in a statement elif type(statement['Action']) == str: if ":*" in statement['Action'] or statement['Action'] == '*': if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() if least_priv_rating == 'passing': finding = { "SchemaVersion": "2018-10-08", "Id": policy_arn + "/mngd_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": policy_arn + "mngd_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.8] Managed policies should follow least privilege principles", "Description": f"The customer managed policy {policy_arn} is following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the Controlling access section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_controlling.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamPolicy", "Id": policy_arn, "Partition": awsPartition, "Region": awsRegion } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding elif least_priv_rating == 'failed_low': finding = { "SchemaVersion": "2018-10-08", "Id": policy_arn + "/mngd_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": policy_arn + "mngd_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "LOW"}, "Confidence": 99, "Title": "[IAM.8] Managed policies should follow least privilege principles", "Description": f"The customer managed policy {policy_arn} is not following least privilege principles and has been rated: {least_priv_rating}.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the Controlling access section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_controlling.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamPolicy", "Id": policy_arn, "Partition": awsPartition, "Region": awsRegion } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding elif least_priv_rating == 'failed_high': finding = { "SchemaVersion": "2018-10-08", "Id": policy_arn + "/mngd_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": policy_arn + "mngd_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "HIGH"}, "Confidence": 99, "Title": "[IAM.8] Managed policies should follow least privilege principles", "Description": f"The customer managed policy {policy_arn} is not following least privilege principles and has been rated: {least_priv_rating}.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the Controlling access section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_controlling.html", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamPolicy", "Id": policy_arn, "Partition": awsPartition, "Region": awsRegion } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding except: pass @registry.register_check("iam") def iam_user_policy_least_priv_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.9] User inline policies should follow least privilege principles""" try: Users = iam.list_users() for user in Users['Users']: user_arn = user['Arn'] UserName = user['UserName'] policy_names = iam.list_user_policies( UserName=UserName )['PolicyNames'] for policy_name in policy_names: policy_doc = iam.get_user_policy( UserName=UserName, PolicyName=policy_name )['PolicyDocument'] #handle policies docs returned as strings if type(policy_doc) == str: policy_doc = json.loads(policy_doc) least_priv_rating = 'passing' for statement in policy_doc['Statement']: if statement["Effect"] == 'Allow': if statement.get('Condition') == None: # action structure could be a string or a list if type(statement['Action']) == list: if len(['True' for x in statement['Action'] if ":*" in x or '*' == x]) > 0: if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' # Single action in a statement elif type(statement['Action']) == str: if ":*" in statement['Action'] or statement['Action'] == '*': if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() if least_priv_rating == 'passing': finding = { "SchemaVersion": "2018-10-08", "Id": user_arn + "/user_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": user_arn + "user_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.9] User inline policies should follow least privilege principles", "Description": f"The user {user_arn} inline policy {policy_name} is following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": user_arn, "Partition": awsPartition, "Region": awsRegion, "Details": { "Other": { "PrincipalName": UserName } }, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding elif least_priv_rating == 'failed_low': finding = { "SchemaVersion": "2018-10-08", "Id": user_arn + "/user_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": user_arn + "user_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "LOW"}, "Confidence": 99, "Title": "[IAM.9] User inline policies should follow least privilege principles", "Description": f"The user {user_arn} inline policy {policy_name} is not following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": user_arn, "Partition": awsPartition, "Region": awsRegion, "Details": { "Other": { "PrincipalName": UserName } }, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding elif least_priv_rating == 'failed_high': finding = { "SchemaVersion": "2018-10-08", "Id": user_arn + "/user_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": user_arn + "user_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "HIGH"}, "Confidence": 99, "Title": "[IAM.9] User inline policies should follow least privilege principles", "Description": f"The user {user_arn} inline policy {policy_name} is not following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamUser", "Id": user_arn, "Partition": awsPartition, "Region": awsRegion, "Details": { "Other": { "PrincipalName": UserName } } } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding except: pass @registry.register_check("iam") def iam_group_policy_least_priv_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.10] Group inline policies should follow least privilege principles""" try: Groups = iam.list_groups() for group in Groups['Groups']: group_arn = group['Arn'] GroupName = group['GroupName'] policy_names = iam.list_group_policies( GroupName=GroupName )['PolicyNames'] for policy_name in policy_names: policy_doc = iam.get_group_policy( GroupName=GroupName, PolicyName=policy_name )['PolicyDocument'] #handle policies docs returned as strings if type(policy_doc) == str: policy_doc = json.loads(policy_doc) least_priv_rating = 'passing' for statement in policy_doc['Statement']: if statement["Effect"] == 'Allow': if statement.get('Condition') == None: # action structure could be a string or a list if type(statement['Action']) == list: if len(['True' for x in statement['Action'] if ":*" in x or '*' == x]) > 0: if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' # Single action in a statement elif type(statement['Action']) == str: if ":*" in statement['Action'] or statement['Action'] == '*': if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() if least_priv_rating == 'passing': finding = { "SchemaVersion": "2018-10-08", "Id": group_arn + "/group_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": group_arn + "group_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.10] Group inline policies should follow least privilege principles", "Description": f"The group {group_arn} inline policy {policy_name} is following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamGroup", "Id": group_arn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PolicyName": policy_name}}, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding elif least_priv_rating == 'failed_low': finding = { "SchemaVersion": "2018-10-08", "Id": group_arn + "/group_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": group_arn + "group_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "LOW"}, "Confidence": 99, "Title": "[IAM.10] Group inline policies should follow least privilege principles", "Description": f"The group {group_arn} inline policy {policy_name} is not following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamGroup", "Id": group_arn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PolicyName": policy_name}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding elif least_priv_rating == 'failed_high': finding = { "SchemaVersion": "2018-10-08", "Id": group_arn + "/group_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": group_arn + "group_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "HIGH"}, "Confidence": 99, "Title": "[IAM.10] Group inline policies should follow least privilege principles", "Description": f"The group {group_arn} inline policy {policy_name} is not following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamGroup", "Id": group_arn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": {"PolicyName": policy_name}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding except: pass @registry.register_check("iam") def iam_role_policy_least_priv_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict: """[IAM.11] Role inline policies should follow least privilege principles""" try: Roles = iam.list_roles() for role in Roles['Roles']: role_arn = role['Arn'] RoleName = role['RoleName'] policy_names = iam.list_role_policies( RoleName=RoleName )['PolicyNames'] for policy_name in policy_names: policy_doc = iam.get_role_policy( RoleName=RoleName, PolicyName=policy_name )['PolicyDocument'] #handle policies docs returned as strings if type(policy_doc) == str: policy_doc = json.loads(policy_doc) least_priv_rating = 'passing' for statement in policy_doc['Statement']: if statement["Effect"] == 'Allow': if statement.get('Condition') == None: # action structure could be a string or a list if type(statement['Action']) == list: if len(['True' for x in statement['Action'] if ":*" in x or '*' == x]) > 0: if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' # Single action in a statement elif type(statement['Action']) == str: if ":*" in statement['Action'] or statement['Action'] == '*': if type(statement['Resource']) == str and statement['Resource'] == '*': least_priv_rating = 'failed_high' # Means that an initial failure will not be overwritten by a lower finding later next elif type(statement['Resource']) == list: least_priv_rating = 'failed_low' iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat() if least_priv_rating == 'passing': finding = { "SchemaVersion": "2018-10-08", "Id": role_arn + "/role_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": role_arn + "role_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "INFORMATIONAL"}, "Confidence": 99, "Title": "[IAM.11] Role inline policies should follow least privilege principles", "Description": f"The role {role_arn} inline policy {policy_name} is following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamRole", "Id": role_arn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": { "PolicyName": policy_name}}, } ], "Compliance": { "Status": "PASSED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "RESOLVED"}, "RecordState": "ARCHIVED", } yield finding elif least_priv_rating == 'failed_low': finding = { "SchemaVersion": "2018-10-08", "Id": role_arn + "/role_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": role_arn + "role_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "LOW"}, "Confidence": 99, "Title": "[IAM.11] Role inline policies should follow least privilege principles", "Description": f"The role {role_arn} inline policy {policy_name} is not following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamRole", "Id": role_arn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": { "PolicyName": policy_name}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding elif least_priv_rating == 'failed_high': finding = { "SchemaVersion": "2018-10-08", "Id": role_arn + "/role_policy_least_priv", "ProductArn": f"arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default", "GeneratorId": role_arn + "role_policy_least_priv", "AwsAccountId": awsAccountId, "Types": ["Software and Configuration Checks/AWS Security Best Practices"], "FirstObservedAt": iso8601Time, "CreatedAt": iso8601Time, "UpdatedAt": iso8601Time, "Severity": {"Label": "HIGH"}, "Confidence": 99, "Title": "[IAM.11] Role inline policies should follow least privilege principles", "Description": f"The role {role_arn} inline policy {policy_name} is not following least privilege principles.", "Remediation": { "Recommendation": { "Text": "For information on IAM least privilege refer to the inline policy section of the AWS IAM User Guide", "Url": "https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_managed-vs-inline.html#inline-policies", } }, "ProductFields": {"Product Name": "ElectricEye"}, "Resources": [ { "Type": "AwsIamRole", "Id": role_arn, "Partition": awsPartition, "Region": awsRegion, "Details": {"Other": { "PolicyName": policy_name}}, } ], "Compliance": { "Status": "FAILED", "RelatedRequirements": [ "NIST CSF PR.AC-3", "NIST SP 800-53 AC-1", "NIST SP 800-53 AC-17", "NIST SP 800-53 AC-19", "NIST SP 800-53 AC-20", "NIST SP 800-53 SC-15", "AICPA TSC CC6.6", "ISO 27001:2013 A.6.2.1", "ISO 27001:2013 A.6.2.2", "ISO 27001:2013 A.11.2.6", "ISO 27001:2013 A.13.1.1", "ISO 27001:2013 A.13.2.1" ], }, "Workflow": {"Status": "NEW"}, "RecordState": "ACTIVE", } yield finding except: pass

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py

Python

tests/unit/gapic/aiplatform_v1/test_job_service.py

conankun/python-aiplatform

d6c1bce7e00186aa5ee3cd0e7b8712b21bd06f2a

[ "Apache-2.0" ]

180

2020-09-23T17:21:15.000Z

2022-03-30T17:25:47.000Z

tests/unit/gapic/aiplatform_v1/test_job_service.py

conankun/python-aiplatform

d6c1bce7e00186aa5ee3cd0e7b8712b21bd06f2a

[ "Apache-2.0" ]

601

2020-09-23T16:23:44.000Z

2022-03-31T19:08:23.000Z

tests/unit/gapic/aiplatform_v1/test_job_service.py

conankun/python-aiplatform

d6c1bce7e00186aa5ee3cd0e7b8712b21bd06f2a

[ "Apache-2.0" ]

109

2020-09-23T16:22:04.000Z

2022-03-28T21:18:29.000Z

# -*- coding: utf-8 -*- # Copyright 2020 Google LLC # # 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 os import mock import grpc from grpc.experimental import aio import math import pytest from proto.marshal.rules.dates import DurationRule, TimestampRule from google.api_core import client_options from google.api_core import exceptions as core_exceptions from google.api_core import future from google.api_core import gapic_v1 from google.api_core import grpc_helpers from google.api_core import grpc_helpers_async from google.api_core import operation_async # type: ignore from google.api_core import operations_v1 from google.api_core import path_template from google.auth import credentials as ga_credentials from google.auth.exceptions import MutualTLSChannelError from google.cloud.aiplatform_v1.services.job_service import JobServiceAsyncClient from google.cloud.aiplatform_v1.services.job_service import JobServiceClient from google.cloud.aiplatform_v1.services.job_service import pagers from google.cloud.aiplatform_v1.services.job_service import transports from google.cloud.aiplatform_v1.types import accelerator_type from google.cloud.aiplatform_v1.types import batch_prediction_job from google.cloud.aiplatform_v1.types import ( batch_prediction_job as gca_batch_prediction_job, ) from google.cloud.aiplatform_v1.types import completion_stats from google.cloud.aiplatform_v1.types import custom_job from google.cloud.aiplatform_v1.types import custom_job as gca_custom_job from google.cloud.aiplatform_v1.types import data_labeling_job from google.cloud.aiplatform_v1.types import data_labeling_job as gca_data_labeling_job from google.cloud.aiplatform_v1.types import encryption_spec from google.cloud.aiplatform_v1.types import env_var from google.cloud.aiplatform_v1.types import explanation from google.cloud.aiplatform_v1.types import explanation_metadata from google.cloud.aiplatform_v1.types import hyperparameter_tuning_job from google.cloud.aiplatform_v1.types import ( hyperparameter_tuning_job as gca_hyperparameter_tuning_job, ) from google.cloud.aiplatform_v1.types import io from google.cloud.aiplatform_v1.types import job_service from google.cloud.aiplatform_v1.types import job_state from google.cloud.aiplatform_v1.types import machine_resources from google.cloud.aiplatform_v1.types import manual_batch_tuning_parameters from google.cloud.aiplatform_v1.types import model from google.cloud.aiplatform_v1.types import model_deployment_monitoring_job from google.cloud.aiplatform_v1.types import ( model_deployment_monitoring_job as gca_model_deployment_monitoring_job, ) from google.cloud.aiplatform_v1.types import model_monitoring from google.cloud.aiplatform_v1.types import operation as gca_operation from google.cloud.aiplatform_v1.types import study from google.cloud.aiplatform_v1.types import unmanaged_container_model from google.longrunning import operations_pb2 from google.oauth2 import service_account from google.protobuf import any_pb2 # type: ignore from google.protobuf import duration_pb2 # type: ignore from google.protobuf import field_mask_pb2 # type: ignore from google.protobuf import struct_pb2 # type: ignore from google.protobuf import timestamp_pb2 # type: ignore from google.rpc import status_pb2 # type: ignore from google.type import money_pb2 # type: ignore import google.auth def client_cert_source_callback(): return b"cert bytes", b"key bytes" # If default endpoint is localhost, then default mtls endpoint will be the same. # This method modifies the default endpoint so the client can produce a different # mtls endpoint for endpoint testing purposes. def modify_default_endpoint(client): return ( "foo.googleapis.com" if ("localhost" in client.DEFAULT_ENDPOINT) else client.DEFAULT_ENDPOINT ) def test__get_default_mtls_endpoint(): api_endpoint = "example.googleapis.com" api_mtls_endpoint = "example.mtls.googleapis.com" sandbox_endpoint = "example.sandbox.googleapis.com" sandbox_mtls_endpoint = "example.mtls.sandbox.googleapis.com" non_googleapi = "api.example.com" assert JobServiceClient._get_default_mtls_endpoint(None) is None assert ( JobServiceClient._get_default_mtls_endpoint(api_endpoint) == api_mtls_endpoint ) assert ( JobServiceClient._get_default_mtls_endpoint(api_mtls_endpoint) == api_mtls_endpoint ) assert ( JobServiceClient._get_default_mtls_endpoint(sandbox_endpoint) == sandbox_mtls_endpoint ) assert ( JobServiceClient._get_default_mtls_endpoint(sandbox_mtls_endpoint) == sandbox_mtls_endpoint ) assert JobServiceClient._get_default_mtls_endpoint(non_googleapi) == non_googleapi @pytest.mark.parametrize("client_class", [JobServiceClient, JobServiceAsyncClient,]) def test_job_service_client_from_service_account_info(client_class): creds = ga_credentials.AnonymousCredentials() with mock.patch.object( service_account.Credentials, "from_service_account_info" ) as factory: factory.return_value = creds info = {"valid": True} client = client_class.from_service_account_info(info) assert client.transport._credentials == creds assert isinstance(client, client_class) assert client.transport._host == "aiplatform.googleapis.com:443" @pytest.mark.parametrize( "transport_class,transport_name", [ (transports.JobServiceGrpcTransport, "grpc"), (transports.JobServiceGrpcAsyncIOTransport, "grpc_asyncio"), ], ) def test_job_service_client_service_account_always_use_jwt( transport_class, transport_name ): with mock.patch.object( service_account.Credentials, "with_always_use_jwt_access", create=True ) as use_jwt: creds = service_account.Credentials(None, None, None) transport = transport_class(credentials=creds, always_use_jwt_access=True) use_jwt.assert_called_once_with(True) with mock.patch.object( service_account.Credentials, "with_always_use_jwt_access", create=True ) as use_jwt: creds = service_account.Credentials(None, None, None) transport = transport_class(credentials=creds, always_use_jwt_access=False) use_jwt.assert_not_called() @pytest.mark.parametrize("client_class", [JobServiceClient, JobServiceAsyncClient,]) def test_job_service_client_from_service_account_file(client_class): creds = ga_credentials.AnonymousCredentials() with mock.patch.object( service_account.Credentials, "from_service_account_file" ) as factory: factory.return_value = creds client = client_class.from_service_account_file("dummy/file/path.json") assert client.transport._credentials == creds assert isinstance(client, client_class) client = client_class.from_service_account_json("dummy/file/path.json") assert client.transport._credentials == creds assert isinstance(client, client_class) assert client.transport._host == "aiplatform.googleapis.com:443" def test_job_service_client_get_transport_class(): transport = JobServiceClient.get_transport_class() available_transports = [ transports.JobServiceGrpcTransport, ] assert transport in available_transports transport = JobServiceClient.get_transport_class("grpc") assert transport == transports.JobServiceGrpcTransport @pytest.mark.parametrize( "client_class,transport_class,transport_name", [ (JobServiceClient, transports.JobServiceGrpcTransport, "grpc"), ( JobServiceAsyncClient, transports.JobServiceGrpcAsyncIOTransport, "grpc_asyncio", ), ], ) @mock.patch.object( JobServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(JobServiceClient) ) @mock.patch.object( JobServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(JobServiceAsyncClient), ) def test_job_service_client_client_options( client_class, transport_class, transport_name ): # Check that if channel is provided we won't create a new one. with mock.patch.object(JobServiceClient, "get_transport_class") as gtc: transport = transport_class(credentials=ga_credentials.AnonymousCredentials()) client = client_class(transport=transport) gtc.assert_not_called() # Check that if channel is provided via str we will create a new one. with mock.patch.object(JobServiceClient, "get_transport_class") as gtc: client = client_class(transport=transport_name) gtc.assert_called() # Check the case api_endpoint is provided. options = client_options.ClientOptions(api_endpoint="squid.clam.whelk") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(transport=transport_name, client_options=options) patched.assert_called_once_with( credentials=None, credentials_file=None, host="squid.clam.whelk", scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is # "never". with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}): with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is # "always". with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}): with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_MTLS_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT has # unsupported value. with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): with pytest.raises(MutualTLSChannelError): client = client_class() # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"} ): with pytest.raises(ValueError): client = client_class() # Check the case quota_project_id is provided options = client_options.ClientOptions(quota_project_id="octopus") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(transport=transport_name, client_options=options) patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id="octopus", client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) @pytest.mark.parametrize( "client_class,transport_class,transport_name,use_client_cert_env", [ (JobServiceClient, transports.JobServiceGrpcTransport, "grpc", "true"), ( JobServiceAsyncClient, transports.JobServiceGrpcAsyncIOTransport, "grpc_asyncio", "true", ), (JobServiceClient, transports.JobServiceGrpcTransport, "grpc", "false"), ( JobServiceAsyncClient, transports.JobServiceGrpcAsyncIOTransport, "grpc_asyncio", "false", ), ], ) @mock.patch.object( JobServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(JobServiceClient) ) @mock.patch.object( JobServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(JobServiceAsyncClient), ) @mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "auto"}) def test_job_service_client_mtls_env_auto( client_class, transport_class, transport_name, use_client_cert_env ): # This tests the endpoint autoswitch behavior. Endpoint is autoswitched to the default # mtls endpoint, if GOOGLE_API_USE_CLIENT_CERTIFICATE is "true" and client cert exists. # Check the case client_cert_source is provided. Whether client cert is used depends on # GOOGLE_API_USE_CLIENT_CERTIFICATE value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env} ): options = client_options.ClientOptions( client_cert_source=client_cert_source_callback ) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(transport=transport_name, client_options=options) if use_client_cert_env == "false": expected_client_cert_source = None expected_host = client.DEFAULT_ENDPOINT else: expected_client_cert_source = client_cert_source_callback expected_host = client.DEFAULT_MTLS_ENDPOINT patched.assert_called_once_with( credentials=None, credentials_file=None, host=expected_host, scopes=None, client_cert_source_for_mtls=expected_client_cert_source, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case ADC client cert is provided. Whether client cert is used depends on # GOOGLE_API_USE_CLIENT_CERTIFICATE value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env} ): with mock.patch.object(transport_class, "__init__") as patched: with mock.patch( "google.auth.transport.mtls.has_default_client_cert_source", return_value=True, ): with mock.patch( "google.auth.transport.mtls.default_client_cert_source", return_value=client_cert_source_callback, ): if use_client_cert_env == "false": expected_host = client.DEFAULT_ENDPOINT expected_client_cert_source = None else: expected_host = client.DEFAULT_MTLS_ENDPOINT expected_client_cert_source = client_cert_source_callback patched.return_value = None client = client_class(transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, host=expected_host, scopes=None, client_cert_source_for_mtls=expected_client_cert_source, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case client_cert_source and ADC client cert are not provided. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env} ): with mock.patch.object(transport_class, "__init__") as patched: with mock.patch( "google.auth.transport.mtls.has_default_client_cert_source", return_value=False, ): patched.return_value = None client = client_class(transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) @pytest.mark.parametrize( "client_class,transport_class,transport_name", [ (JobServiceClient, transports.JobServiceGrpcTransport, "grpc"), ( JobServiceAsyncClient, transports.JobServiceGrpcAsyncIOTransport, "grpc_asyncio", ), ], ) def test_job_service_client_client_options_scopes( client_class, transport_class, transport_name ): # Check the case scopes are provided. options = client_options.ClientOptions(scopes=["1", "2"],) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(transport=transport_name, client_options=options) patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=["1", "2"], client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) @pytest.mark.parametrize( "client_class,transport_class,transport_name", [ (JobServiceClient, transports.JobServiceGrpcTransport, "grpc"), ( JobServiceAsyncClient, transports.JobServiceGrpcAsyncIOTransport, "grpc_asyncio", ), ], ) def test_job_service_client_client_options_credentials_file( client_class, transport_class, transport_name ): # Check the case credentials file is provided. options = client_options.ClientOptions(credentials_file="credentials.json") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(transport=transport_name, client_options=options) patched.assert_called_once_with( credentials=None, credentials_file="credentials.json", host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) def test_job_service_client_client_options_from_dict(): with mock.patch( "google.cloud.aiplatform_v1.services.job_service.transports.JobServiceGrpcTransport.__init__" ) as grpc_transport: grpc_transport.return_value = None client = JobServiceClient(client_options={"api_endpoint": "squid.clam.whelk"}) grpc_transport.assert_called_once_with( credentials=None, credentials_file=None, host="squid.clam.whelk", scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) def test_create_custom_job( transport: str = "grpc", request_type=job_service.CreateCustomJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_custom_job.CustomJob( name="name_value", display_name="display_name_value", state=job_state.JobState.JOB_STATE_QUEUED, ) response = client.create_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateCustomJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_custom_job.CustomJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED def test_create_custom_job_from_dict(): test_create_custom_job(request_type=dict) def test_create_custom_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_custom_job), "__call__" ) as call: client.create_custom_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateCustomJobRequest() @pytest.mark.asyncio async def test_create_custom_job_async( transport: str = "grpc_asyncio", request_type=job_service.CreateCustomJobRequest ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_custom_job.CustomJob( name="name_value", display_name="display_name_value", state=job_state.JobState.JOB_STATE_QUEUED, ) ) response = await client.create_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateCustomJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_custom_job.CustomJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED @pytest.mark.asyncio async def test_create_custom_job_async_from_dict(): await test_create_custom_job_async(request_type=dict) def test_create_custom_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateCustomJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_custom_job), "__call__" ) as call: call.return_value = gca_custom_job.CustomJob() client.create_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_create_custom_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateCustomJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_custom_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_custom_job.CustomJob() ) await client.create_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_create_custom_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_custom_job.CustomJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.create_custom_job( parent="parent_value", custom_job=gca_custom_job.CustomJob(name="name_value"), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].custom_job mock_val = gca_custom_job.CustomJob(name="name_value") assert arg == mock_val def test_create_custom_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.create_custom_job( job_service.CreateCustomJobRequest(), parent="parent_value", custom_job=gca_custom_job.CustomJob(name="name_value"), ) @pytest.mark.asyncio async def test_create_custom_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_custom_job.CustomJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_custom_job.CustomJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.create_custom_job( parent="parent_value", custom_job=gca_custom_job.CustomJob(name="name_value"), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].custom_job mock_val = gca_custom_job.CustomJob(name="name_value") assert arg == mock_val @pytest.mark.asyncio async def test_create_custom_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.create_custom_job( job_service.CreateCustomJobRequest(), parent="parent_value", custom_job=gca_custom_job.CustomJob(name="name_value"), ) def test_get_custom_job( transport: str = "grpc", request_type=job_service.GetCustomJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_custom_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = custom_job.CustomJob( name="name_value", display_name="display_name_value", state=job_state.JobState.JOB_STATE_QUEUED, ) response = client.get_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetCustomJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, custom_job.CustomJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED def test_get_custom_job_from_dict(): test_get_custom_job(request_type=dict) def test_get_custom_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_custom_job), "__call__") as call: client.get_custom_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetCustomJobRequest() @pytest.mark.asyncio async def test_get_custom_job_async( transport: str = "grpc_asyncio", request_type=job_service.GetCustomJobRequest ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_custom_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( custom_job.CustomJob( name="name_value", display_name="display_name_value", state=job_state.JobState.JOB_STATE_QUEUED, ) ) response = await client.get_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetCustomJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, custom_job.CustomJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED @pytest.mark.asyncio async def test_get_custom_job_async_from_dict(): await test_get_custom_job_async(request_type=dict) def test_get_custom_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetCustomJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_custom_job), "__call__") as call: call.return_value = custom_job.CustomJob() client.get_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_get_custom_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetCustomJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_custom_job), "__call__") as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( custom_job.CustomJob() ) await client.get_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_get_custom_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_custom_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = custom_job.CustomJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.get_custom_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_get_custom_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.get_custom_job( job_service.GetCustomJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_get_custom_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_custom_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = custom_job.CustomJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( custom_job.CustomJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.get_custom_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_get_custom_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.get_custom_job( job_service.GetCustomJobRequest(), name="name_value", ) def test_list_custom_jobs( transport: str = "grpc", request_type=job_service.ListCustomJobsRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListCustomJobsResponse( next_page_token="next_page_token_value", ) response = client.list_custom_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListCustomJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListCustomJobsPager) assert response.next_page_token == "next_page_token_value" def test_list_custom_jobs_from_dict(): test_list_custom_jobs(request_type=dict) def test_list_custom_jobs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: client.list_custom_jobs() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListCustomJobsRequest() @pytest.mark.asyncio async def test_list_custom_jobs_async( transport: str = "grpc_asyncio", request_type=job_service.ListCustomJobsRequest ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListCustomJobsResponse(next_page_token="next_page_token_value",) ) response = await client.list_custom_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListCustomJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListCustomJobsAsyncPager) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_list_custom_jobs_async_from_dict(): await test_list_custom_jobs_async(request_type=dict) def test_list_custom_jobs_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListCustomJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: call.return_value = job_service.ListCustomJobsResponse() client.list_custom_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_list_custom_jobs_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListCustomJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListCustomJobsResponse() ) await client.list_custom_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_list_custom_jobs_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListCustomJobsResponse() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.list_custom_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val def test_list_custom_jobs_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.list_custom_jobs( job_service.ListCustomJobsRequest(), parent="parent_value", ) @pytest.mark.asyncio async def test_list_custom_jobs_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListCustomJobsResponse() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListCustomJobsResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.list_custom_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val @pytest.mark.asyncio async def test_list_custom_jobs_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.list_custom_jobs( job_service.ListCustomJobsRequest(), parent="parent_value", ) def test_list_custom_jobs_pager(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListCustomJobsResponse( custom_jobs=[ custom_job.CustomJob(), custom_job.CustomJob(), custom_job.CustomJob(), ], next_page_token="abc", ), job_service.ListCustomJobsResponse(custom_jobs=[], next_page_token="def",), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(),], next_page_token="ghi", ), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(), custom_job.CustomJob(),], ), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)), ) pager = client.list_custom_jobs(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all(isinstance(i, custom_job.CustomJob) for i in results) def test_list_custom_jobs_pages(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_custom_jobs), "__call__") as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListCustomJobsResponse( custom_jobs=[ custom_job.CustomJob(), custom_job.CustomJob(), custom_job.CustomJob(), ], next_page_token="abc", ), job_service.ListCustomJobsResponse(custom_jobs=[], next_page_token="def",), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(),], next_page_token="ghi", ), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(), custom_job.CustomJob(),], ), RuntimeError, ) pages = list(client.list_custom_jobs(request={}).pages) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_list_custom_jobs_async_pager(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_custom_jobs), "__call__", new_callable=mock.AsyncMock ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListCustomJobsResponse( custom_jobs=[ custom_job.CustomJob(), custom_job.CustomJob(), custom_job.CustomJob(), ], next_page_token="abc", ), job_service.ListCustomJobsResponse(custom_jobs=[], next_page_token="def",), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(),], next_page_token="ghi", ), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(), custom_job.CustomJob(),], ), RuntimeError, ) async_pager = await client.list_custom_jobs(request={},) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all(isinstance(i, custom_job.CustomJob) for i in responses) @pytest.mark.asyncio async def test_list_custom_jobs_async_pages(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_custom_jobs), "__call__", new_callable=mock.AsyncMock ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListCustomJobsResponse( custom_jobs=[ custom_job.CustomJob(), custom_job.CustomJob(), custom_job.CustomJob(), ], next_page_token="abc", ), job_service.ListCustomJobsResponse(custom_jobs=[], next_page_token="def",), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(),], next_page_token="ghi", ), job_service.ListCustomJobsResponse( custom_jobs=[custom_job.CustomJob(), custom_job.CustomJob(),], ), RuntimeError, ) pages = [] async for page_ in (await client.list_custom_jobs(request={})).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_delete_custom_job( transport: str = "grpc", request_type=job_service.DeleteCustomJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/spam") response = client.delete_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteCustomJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) def test_delete_custom_job_from_dict(): test_delete_custom_job(request_type=dict) def test_delete_custom_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_custom_job), "__call__" ) as call: client.delete_custom_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteCustomJobRequest() @pytest.mark.asyncio async def test_delete_custom_job_async( transport: str = "grpc_asyncio", request_type=job_service.DeleteCustomJobRequest ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) response = await client.delete_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteCustomJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) @pytest.mark.asyncio async def test_delete_custom_job_async_from_dict(): await test_delete_custom_job_async(request_type=dict) def test_delete_custom_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteCustomJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_custom_job), "__call__" ) as call: call.return_value = operations_pb2.Operation(name="operations/op") client.delete_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_delete_custom_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteCustomJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_custom_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/op") ) await client.delete_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_delete_custom_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.delete_custom_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_delete_custom_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.delete_custom_job( job_service.DeleteCustomJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_delete_custom_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.delete_custom_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_delete_custom_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.delete_custom_job( job_service.DeleteCustomJobRequest(), name="name_value", ) def test_cancel_custom_job( transport: str = "grpc", request_type=job_service.CancelCustomJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None response = client.cancel_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelCustomJobRequest() # Establish that the response is the type that we expect. assert response is None def test_cancel_custom_job_from_dict(): test_cancel_custom_job(request_type=dict) def test_cancel_custom_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_custom_job), "__call__" ) as call: client.cancel_custom_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelCustomJobRequest() @pytest.mark.asyncio async def test_cancel_custom_job_async( transport: str = "grpc_asyncio", request_type=job_service.CancelCustomJobRequest ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.cancel_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelCustomJobRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_cancel_custom_job_async_from_dict(): await test_cancel_custom_job_async(request_type=dict) def test_cancel_custom_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelCustomJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_custom_job), "__call__" ) as call: call.return_value = None client.cancel_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_cancel_custom_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelCustomJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_custom_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.cancel_custom_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_cancel_custom_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.cancel_custom_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_cancel_custom_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.cancel_custom_job( job_service.CancelCustomJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_cancel_custom_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_custom_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.cancel_custom_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_cancel_custom_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.cancel_custom_job( job_service.CancelCustomJobRequest(), name="name_value", ) def test_create_data_labeling_job( transport: str = "grpc", request_type=job_service.CreateDataLabelingJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_data_labeling_job.DataLabelingJob( name="name_value", display_name="display_name_value", datasets=["datasets_value"], labeler_count=1375, instruction_uri="instruction_uri_value", inputs_schema_uri="inputs_schema_uri_value", state=job_state.JobState.JOB_STATE_QUEUED, labeling_progress=1810, specialist_pools=["specialist_pools_value"], ) response = client.create_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateDataLabelingJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_data_labeling_job.DataLabelingJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.datasets == ["datasets_value"] assert response.labeler_count == 1375 assert response.instruction_uri == "instruction_uri_value" assert response.inputs_schema_uri == "inputs_schema_uri_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert response.labeling_progress == 1810 assert response.specialist_pools == ["specialist_pools_value"] def test_create_data_labeling_job_from_dict(): test_create_data_labeling_job(request_type=dict) def test_create_data_labeling_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_data_labeling_job), "__call__" ) as call: client.create_data_labeling_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateDataLabelingJobRequest() @pytest.mark.asyncio async def test_create_data_labeling_job_async( transport: str = "grpc_asyncio", request_type=job_service.CreateDataLabelingJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_data_labeling_job.DataLabelingJob( name="name_value", display_name="display_name_value", datasets=["datasets_value"], labeler_count=1375, instruction_uri="instruction_uri_value", inputs_schema_uri="inputs_schema_uri_value", state=job_state.JobState.JOB_STATE_QUEUED, labeling_progress=1810, specialist_pools=["specialist_pools_value"], ) ) response = await client.create_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateDataLabelingJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_data_labeling_job.DataLabelingJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.datasets == ["datasets_value"] assert response.labeler_count == 1375 assert response.instruction_uri == "instruction_uri_value" assert response.inputs_schema_uri == "inputs_schema_uri_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert response.labeling_progress == 1810 assert response.specialist_pools == ["specialist_pools_value"] @pytest.mark.asyncio async def test_create_data_labeling_job_async_from_dict(): await test_create_data_labeling_job_async(request_type=dict) def test_create_data_labeling_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateDataLabelingJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_data_labeling_job), "__call__" ) as call: call.return_value = gca_data_labeling_job.DataLabelingJob() client.create_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_create_data_labeling_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateDataLabelingJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_data_labeling_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_data_labeling_job.DataLabelingJob() ) await client.create_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_create_data_labeling_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_data_labeling_job.DataLabelingJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.create_data_labeling_job( parent="parent_value", data_labeling_job=gca_data_labeling_job.DataLabelingJob(name="name_value"), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].data_labeling_job mock_val = gca_data_labeling_job.DataLabelingJob(name="name_value") assert arg == mock_val def test_create_data_labeling_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.create_data_labeling_job( job_service.CreateDataLabelingJobRequest(), parent="parent_value", data_labeling_job=gca_data_labeling_job.DataLabelingJob(name="name_value"), ) @pytest.mark.asyncio async def test_create_data_labeling_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_data_labeling_job.DataLabelingJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_data_labeling_job.DataLabelingJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.create_data_labeling_job( parent="parent_value", data_labeling_job=gca_data_labeling_job.DataLabelingJob(name="name_value"), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].data_labeling_job mock_val = gca_data_labeling_job.DataLabelingJob(name="name_value") assert arg == mock_val @pytest.mark.asyncio async def test_create_data_labeling_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.create_data_labeling_job( job_service.CreateDataLabelingJobRequest(), parent="parent_value", data_labeling_job=gca_data_labeling_job.DataLabelingJob(name="name_value"), ) def test_get_data_labeling_job( transport: str = "grpc", request_type=job_service.GetDataLabelingJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = data_labeling_job.DataLabelingJob( name="name_value", display_name="display_name_value", datasets=["datasets_value"], labeler_count=1375, instruction_uri="instruction_uri_value", inputs_schema_uri="inputs_schema_uri_value", state=job_state.JobState.JOB_STATE_QUEUED, labeling_progress=1810, specialist_pools=["specialist_pools_value"], ) response = client.get_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetDataLabelingJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, data_labeling_job.DataLabelingJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.datasets == ["datasets_value"] assert response.labeler_count == 1375 assert response.instruction_uri == "instruction_uri_value" assert response.inputs_schema_uri == "inputs_schema_uri_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert response.labeling_progress == 1810 assert response.specialist_pools == ["specialist_pools_value"] def test_get_data_labeling_job_from_dict(): test_get_data_labeling_job(request_type=dict) def test_get_data_labeling_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_data_labeling_job), "__call__" ) as call: client.get_data_labeling_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetDataLabelingJobRequest() @pytest.mark.asyncio async def test_get_data_labeling_job_async( transport: str = "grpc_asyncio", request_type=job_service.GetDataLabelingJobRequest ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( data_labeling_job.DataLabelingJob( name="name_value", display_name="display_name_value", datasets=["datasets_value"], labeler_count=1375, instruction_uri="instruction_uri_value", inputs_schema_uri="inputs_schema_uri_value", state=job_state.JobState.JOB_STATE_QUEUED, labeling_progress=1810, specialist_pools=["specialist_pools_value"], ) ) response = await client.get_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetDataLabelingJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, data_labeling_job.DataLabelingJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.datasets == ["datasets_value"] assert response.labeler_count == 1375 assert response.instruction_uri == "instruction_uri_value" assert response.inputs_schema_uri == "inputs_schema_uri_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert response.labeling_progress == 1810 assert response.specialist_pools == ["specialist_pools_value"] @pytest.mark.asyncio async def test_get_data_labeling_job_async_from_dict(): await test_get_data_labeling_job_async(request_type=dict) def test_get_data_labeling_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetDataLabelingJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_data_labeling_job), "__call__" ) as call: call.return_value = data_labeling_job.DataLabelingJob() client.get_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_get_data_labeling_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetDataLabelingJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_data_labeling_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( data_labeling_job.DataLabelingJob() ) await client.get_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_get_data_labeling_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = data_labeling_job.DataLabelingJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.get_data_labeling_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_get_data_labeling_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.get_data_labeling_job( job_service.GetDataLabelingJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_get_data_labeling_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = data_labeling_job.DataLabelingJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( data_labeling_job.DataLabelingJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.get_data_labeling_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_get_data_labeling_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.get_data_labeling_job( job_service.GetDataLabelingJobRequest(), name="name_value", ) def test_list_data_labeling_jobs( transport: str = "grpc", request_type=job_service.ListDataLabelingJobsRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListDataLabelingJobsResponse( next_page_token="next_page_token_value", ) response = client.list_data_labeling_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListDataLabelingJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListDataLabelingJobsPager) assert response.next_page_token == "next_page_token_value" def test_list_data_labeling_jobs_from_dict(): test_list_data_labeling_jobs(request_type=dict) def test_list_data_labeling_jobs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: client.list_data_labeling_jobs() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListDataLabelingJobsRequest() @pytest.mark.asyncio async def test_list_data_labeling_jobs_async( transport: str = "grpc_asyncio", request_type=job_service.ListDataLabelingJobsRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListDataLabelingJobsResponse( next_page_token="next_page_token_value", ) ) response = await client.list_data_labeling_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListDataLabelingJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListDataLabelingJobsAsyncPager) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_list_data_labeling_jobs_async_from_dict(): await test_list_data_labeling_jobs_async(request_type=dict) def test_list_data_labeling_jobs_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListDataLabelingJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: call.return_value = job_service.ListDataLabelingJobsResponse() client.list_data_labeling_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_list_data_labeling_jobs_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListDataLabelingJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListDataLabelingJobsResponse() ) await client.list_data_labeling_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_list_data_labeling_jobs_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListDataLabelingJobsResponse() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.list_data_labeling_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val def test_list_data_labeling_jobs_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.list_data_labeling_jobs( job_service.ListDataLabelingJobsRequest(), parent="parent_value", ) @pytest.mark.asyncio async def test_list_data_labeling_jobs_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListDataLabelingJobsResponse() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListDataLabelingJobsResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.list_data_labeling_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val @pytest.mark.asyncio async def test_list_data_labeling_jobs_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.list_data_labeling_jobs( job_service.ListDataLabelingJobsRequest(), parent="parent_value", ) def test_list_data_labeling_jobs_pager(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], next_page_token="abc", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[], next_page_token="def", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[data_labeling_job.DataLabelingJob(),], next_page_token="ghi", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], ), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)), ) pager = client.list_data_labeling_jobs(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all(isinstance(i, data_labeling_job.DataLabelingJob) for i in results) def test_list_data_labeling_jobs_pages(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], next_page_token="abc", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[], next_page_token="def", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[data_labeling_job.DataLabelingJob(),], next_page_token="ghi", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], ), RuntimeError, ) pages = list(client.list_data_labeling_jobs(request={}).pages) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_list_data_labeling_jobs_async_pager(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], next_page_token="abc", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[], next_page_token="def", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[data_labeling_job.DataLabelingJob(),], next_page_token="ghi", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], ), RuntimeError, ) async_pager = await client.list_data_labeling_jobs(request={},) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all(isinstance(i, data_labeling_job.DataLabelingJob) for i in responses) @pytest.mark.asyncio async def test_list_data_labeling_jobs_async_pages(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_data_labeling_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], next_page_token="abc", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[], next_page_token="def", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[data_labeling_job.DataLabelingJob(),], next_page_token="ghi", ), job_service.ListDataLabelingJobsResponse( data_labeling_jobs=[ data_labeling_job.DataLabelingJob(), data_labeling_job.DataLabelingJob(), ], ), RuntimeError, ) pages = [] async for page_ in (await client.list_data_labeling_jobs(request={})).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_delete_data_labeling_job( transport: str = "grpc", request_type=job_service.DeleteDataLabelingJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/spam") response = client.delete_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteDataLabelingJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) def test_delete_data_labeling_job_from_dict(): test_delete_data_labeling_job(request_type=dict) def test_delete_data_labeling_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_data_labeling_job), "__call__" ) as call: client.delete_data_labeling_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteDataLabelingJobRequest() @pytest.mark.asyncio async def test_delete_data_labeling_job_async( transport: str = "grpc_asyncio", request_type=job_service.DeleteDataLabelingJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) response = await client.delete_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteDataLabelingJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) @pytest.mark.asyncio async def test_delete_data_labeling_job_async_from_dict(): await test_delete_data_labeling_job_async(request_type=dict) def test_delete_data_labeling_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteDataLabelingJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_data_labeling_job), "__call__" ) as call: call.return_value = operations_pb2.Operation(name="operations/op") client.delete_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_delete_data_labeling_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteDataLabelingJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_data_labeling_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/op") ) await client.delete_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_delete_data_labeling_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.delete_data_labeling_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_delete_data_labeling_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.delete_data_labeling_job( job_service.DeleteDataLabelingJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_delete_data_labeling_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.delete_data_labeling_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_delete_data_labeling_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.delete_data_labeling_job( job_service.DeleteDataLabelingJobRequest(), name="name_value", ) def test_cancel_data_labeling_job( transport: str = "grpc", request_type=job_service.CancelDataLabelingJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None response = client.cancel_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelDataLabelingJobRequest() # Establish that the response is the type that we expect. assert response is None def test_cancel_data_labeling_job_from_dict(): test_cancel_data_labeling_job(request_type=dict) def test_cancel_data_labeling_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_data_labeling_job), "__call__" ) as call: client.cancel_data_labeling_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelDataLabelingJobRequest() @pytest.mark.asyncio async def test_cancel_data_labeling_job_async( transport: str = "grpc_asyncio", request_type=job_service.CancelDataLabelingJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.cancel_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelDataLabelingJobRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_cancel_data_labeling_job_async_from_dict(): await test_cancel_data_labeling_job_async(request_type=dict) def test_cancel_data_labeling_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelDataLabelingJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_data_labeling_job), "__call__" ) as call: call.return_value = None client.cancel_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_cancel_data_labeling_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelDataLabelingJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_data_labeling_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.cancel_data_labeling_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_cancel_data_labeling_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.cancel_data_labeling_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_cancel_data_labeling_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.cancel_data_labeling_job( job_service.CancelDataLabelingJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_cancel_data_labeling_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_data_labeling_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.cancel_data_labeling_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_cancel_data_labeling_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.cancel_data_labeling_job( job_service.CancelDataLabelingJobRequest(), name="name_value", ) def test_create_hyperparameter_tuning_job( transport: str = "grpc", request_type=job_service.CreateHyperparameterTuningJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value", display_name="display_name_value", max_trial_count=1609, parallel_trial_count=2128, max_failed_trial_count=2317, state=job_state.JobState.JOB_STATE_QUEUED, ) response = client.create_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_hyperparameter_tuning_job.HyperparameterTuningJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.max_trial_count == 1609 assert response.parallel_trial_count == 2128 assert response.max_failed_trial_count == 2317 assert response.state == job_state.JobState.JOB_STATE_QUEUED def test_create_hyperparameter_tuning_job_from_dict(): test_create_hyperparameter_tuning_job(request_type=dict) def test_create_hyperparameter_tuning_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_hyperparameter_tuning_job), "__call__" ) as call: client.create_hyperparameter_tuning_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateHyperparameterTuningJobRequest() @pytest.mark.asyncio async def test_create_hyperparameter_tuning_job_async( transport: str = "grpc_asyncio", request_type=job_service.CreateHyperparameterTuningJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value", display_name="display_name_value", max_trial_count=1609, parallel_trial_count=2128, max_failed_trial_count=2317, state=job_state.JobState.JOB_STATE_QUEUED, ) ) response = await client.create_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_hyperparameter_tuning_job.HyperparameterTuningJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.max_trial_count == 1609 assert response.parallel_trial_count == 2128 assert response.max_failed_trial_count == 2317 assert response.state == job_state.JobState.JOB_STATE_QUEUED @pytest.mark.asyncio async def test_create_hyperparameter_tuning_job_async_from_dict(): await test_create_hyperparameter_tuning_job_async(request_type=dict) def test_create_hyperparameter_tuning_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateHyperparameterTuningJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = gca_hyperparameter_tuning_job.HyperparameterTuningJob() client.create_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_create_hyperparameter_tuning_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateHyperparameterTuningJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_hyperparameter_tuning_job.HyperparameterTuningJob() ) await client.create_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_create_hyperparameter_tuning_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_hyperparameter_tuning_job.HyperparameterTuningJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.create_hyperparameter_tuning_job( parent="parent_value", hyperparameter_tuning_job=gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value" ), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].hyperparameter_tuning_job mock_val = gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value" ) assert arg == mock_val def test_create_hyperparameter_tuning_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.create_hyperparameter_tuning_job( job_service.CreateHyperparameterTuningJobRequest(), parent="parent_value", hyperparameter_tuning_job=gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value" ), ) @pytest.mark.asyncio async def test_create_hyperparameter_tuning_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_hyperparameter_tuning_job.HyperparameterTuningJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_hyperparameter_tuning_job.HyperparameterTuningJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.create_hyperparameter_tuning_job( parent="parent_value", hyperparameter_tuning_job=gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value" ), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].hyperparameter_tuning_job mock_val = gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value" ) assert arg == mock_val @pytest.mark.asyncio async def test_create_hyperparameter_tuning_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.create_hyperparameter_tuning_job( job_service.CreateHyperparameterTuningJobRequest(), parent="parent_value", hyperparameter_tuning_job=gca_hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value" ), ) def test_get_hyperparameter_tuning_job( transport: str = "grpc", request_type=job_service.GetHyperparameterTuningJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value", display_name="display_name_value", max_trial_count=1609, parallel_trial_count=2128, max_failed_trial_count=2317, state=job_state.JobState.JOB_STATE_QUEUED, ) response = client.get_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, hyperparameter_tuning_job.HyperparameterTuningJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.max_trial_count == 1609 assert response.parallel_trial_count == 2128 assert response.max_failed_trial_count == 2317 assert response.state == job_state.JobState.JOB_STATE_QUEUED def test_get_hyperparameter_tuning_job_from_dict(): test_get_hyperparameter_tuning_job(request_type=dict) def test_get_hyperparameter_tuning_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_hyperparameter_tuning_job), "__call__" ) as call: client.get_hyperparameter_tuning_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetHyperparameterTuningJobRequest() @pytest.mark.asyncio async def test_get_hyperparameter_tuning_job_async( transport: str = "grpc_asyncio", request_type=job_service.GetHyperparameterTuningJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( hyperparameter_tuning_job.HyperparameterTuningJob( name="name_value", display_name="display_name_value", max_trial_count=1609, parallel_trial_count=2128, max_failed_trial_count=2317, state=job_state.JobState.JOB_STATE_QUEUED, ) ) response = await client.get_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, hyperparameter_tuning_job.HyperparameterTuningJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.max_trial_count == 1609 assert response.parallel_trial_count == 2128 assert response.max_failed_trial_count == 2317 assert response.state == job_state.JobState.JOB_STATE_QUEUED @pytest.mark.asyncio async def test_get_hyperparameter_tuning_job_async_from_dict(): await test_get_hyperparameter_tuning_job_async(request_type=dict) def test_get_hyperparameter_tuning_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetHyperparameterTuningJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = hyperparameter_tuning_job.HyperparameterTuningJob() client.get_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_get_hyperparameter_tuning_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetHyperparameterTuningJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( hyperparameter_tuning_job.HyperparameterTuningJob() ) await client.get_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_get_hyperparameter_tuning_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = hyperparameter_tuning_job.HyperparameterTuningJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.get_hyperparameter_tuning_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_get_hyperparameter_tuning_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.get_hyperparameter_tuning_job( job_service.GetHyperparameterTuningJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_get_hyperparameter_tuning_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = hyperparameter_tuning_job.HyperparameterTuningJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( hyperparameter_tuning_job.HyperparameterTuningJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.get_hyperparameter_tuning_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_get_hyperparameter_tuning_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.get_hyperparameter_tuning_job( job_service.GetHyperparameterTuningJobRequest(), name="name_value", ) def test_list_hyperparameter_tuning_jobs( transport: str = "grpc", request_type=job_service.ListHyperparameterTuningJobsRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListHyperparameterTuningJobsResponse( next_page_token="next_page_token_value", ) response = client.list_hyperparameter_tuning_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListHyperparameterTuningJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListHyperparameterTuningJobsPager) assert response.next_page_token == "next_page_token_value" def test_list_hyperparameter_tuning_jobs_from_dict(): test_list_hyperparameter_tuning_jobs(request_type=dict) def test_list_hyperparameter_tuning_jobs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: client.list_hyperparameter_tuning_jobs() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListHyperparameterTuningJobsRequest() @pytest.mark.asyncio async def test_list_hyperparameter_tuning_jobs_async( transport: str = "grpc_asyncio", request_type=job_service.ListHyperparameterTuningJobsRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListHyperparameterTuningJobsResponse( next_page_token="next_page_token_value", ) ) response = await client.list_hyperparameter_tuning_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListHyperparameterTuningJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListHyperparameterTuningJobsAsyncPager) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_list_hyperparameter_tuning_jobs_async_from_dict(): await test_list_hyperparameter_tuning_jobs_async(request_type=dict) def test_list_hyperparameter_tuning_jobs_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListHyperparameterTuningJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: call.return_value = job_service.ListHyperparameterTuningJobsResponse() client.list_hyperparameter_tuning_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_list_hyperparameter_tuning_jobs_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListHyperparameterTuningJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListHyperparameterTuningJobsResponse() ) await client.list_hyperparameter_tuning_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_list_hyperparameter_tuning_jobs_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListHyperparameterTuningJobsResponse() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.list_hyperparameter_tuning_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val def test_list_hyperparameter_tuning_jobs_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.list_hyperparameter_tuning_jobs( job_service.ListHyperparameterTuningJobsRequest(), parent="parent_value", ) @pytest.mark.asyncio async def test_list_hyperparameter_tuning_jobs_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListHyperparameterTuningJobsResponse() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListHyperparameterTuningJobsResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.list_hyperparameter_tuning_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val @pytest.mark.asyncio async def test_list_hyperparameter_tuning_jobs_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.list_hyperparameter_tuning_jobs( job_service.ListHyperparameterTuningJobsRequest(), parent="parent_value", ) def test_list_hyperparameter_tuning_jobs_pager(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="abc", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[], next_page_token="def", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="ghi", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], ), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)), ) pager = client.list_hyperparameter_tuning_jobs(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all( isinstance(i, hyperparameter_tuning_job.HyperparameterTuningJob) for i in results ) def test_list_hyperparameter_tuning_jobs_pages(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="abc", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[], next_page_token="def", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="ghi", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], ), RuntimeError, ) pages = list(client.list_hyperparameter_tuning_jobs(request={}).pages) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_list_hyperparameter_tuning_jobs_async_pager(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="abc", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[], next_page_token="def", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="ghi", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], ), RuntimeError, ) async_pager = await client.list_hyperparameter_tuning_jobs(request={},) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all( isinstance(i, hyperparameter_tuning_job.HyperparameterTuningJob) for i in responses ) @pytest.mark.asyncio async def test_list_hyperparameter_tuning_jobs_async_pages(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_hyperparameter_tuning_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="abc", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[], next_page_token="def", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), ], next_page_token="ghi", ), job_service.ListHyperparameterTuningJobsResponse( hyperparameter_tuning_jobs=[ hyperparameter_tuning_job.HyperparameterTuningJob(), hyperparameter_tuning_job.HyperparameterTuningJob(), ], ), RuntimeError, ) pages = [] async for page_ in ( await client.list_hyperparameter_tuning_jobs(request={}) ).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_delete_hyperparameter_tuning_job( transport: str = "grpc", request_type=job_service.DeleteHyperparameterTuningJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/spam") response = client.delete_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) def test_delete_hyperparameter_tuning_job_from_dict(): test_delete_hyperparameter_tuning_job(request_type=dict) def test_delete_hyperparameter_tuning_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_hyperparameter_tuning_job), "__call__" ) as call: client.delete_hyperparameter_tuning_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteHyperparameterTuningJobRequest() @pytest.mark.asyncio async def test_delete_hyperparameter_tuning_job_async( transport: str = "grpc_asyncio", request_type=job_service.DeleteHyperparameterTuningJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) response = await client.delete_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) @pytest.mark.asyncio async def test_delete_hyperparameter_tuning_job_async_from_dict(): await test_delete_hyperparameter_tuning_job_async(request_type=dict) def test_delete_hyperparameter_tuning_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteHyperparameterTuningJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = operations_pb2.Operation(name="operations/op") client.delete_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_delete_hyperparameter_tuning_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteHyperparameterTuningJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/op") ) await client.delete_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_delete_hyperparameter_tuning_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.delete_hyperparameter_tuning_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_delete_hyperparameter_tuning_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.delete_hyperparameter_tuning_job( job_service.DeleteHyperparameterTuningJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_delete_hyperparameter_tuning_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.delete_hyperparameter_tuning_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_delete_hyperparameter_tuning_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.delete_hyperparameter_tuning_job( job_service.DeleteHyperparameterTuningJobRequest(), name="name_value", ) def test_cancel_hyperparameter_tuning_job( transport: str = "grpc", request_type=job_service.CancelHyperparameterTuningJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None response = client.cancel_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert response is None def test_cancel_hyperparameter_tuning_job_from_dict(): test_cancel_hyperparameter_tuning_job(request_type=dict) def test_cancel_hyperparameter_tuning_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_hyperparameter_tuning_job), "__call__" ) as call: client.cancel_hyperparameter_tuning_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelHyperparameterTuningJobRequest() @pytest.mark.asyncio async def test_cancel_hyperparameter_tuning_job_async( transport: str = "grpc_asyncio", request_type=job_service.CancelHyperparameterTuningJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.cancel_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelHyperparameterTuningJobRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_cancel_hyperparameter_tuning_job_async_from_dict(): await test_cancel_hyperparameter_tuning_job_async(request_type=dict) def test_cancel_hyperparameter_tuning_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelHyperparameterTuningJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = None client.cancel_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_cancel_hyperparameter_tuning_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelHyperparameterTuningJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_hyperparameter_tuning_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.cancel_hyperparameter_tuning_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_cancel_hyperparameter_tuning_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.cancel_hyperparameter_tuning_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_cancel_hyperparameter_tuning_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.cancel_hyperparameter_tuning_job( job_service.CancelHyperparameterTuningJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_cancel_hyperparameter_tuning_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_hyperparameter_tuning_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.cancel_hyperparameter_tuning_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_cancel_hyperparameter_tuning_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.cancel_hyperparameter_tuning_job( job_service.CancelHyperparameterTuningJobRequest(), name="name_value", ) def test_create_batch_prediction_job( transport: str = "grpc", request_type=job_service.CreateBatchPredictionJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_batch_prediction_job.BatchPredictionJob( name="name_value", display_name="display_name_value", model="model_value", generate_explanation=True, state=job_state.JobState.JOB_STATE_QUEUED, ) response = client.create_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_batch_prediction_job.BatchPredictionJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.model == "model_value" assert response.generate_explanation is True assert response.state == job_state.JobState.JOB_STATE_QUEUED def test_create_batch_prediction_job_from_dict(): test_create_batch_prediction_job(request_type=dict) def test_create_batch_prediction_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_batch_prediction_job), "__call__" ) as call: client.create_batch_prediction_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateBatchPredictionJobRequest() @pytest.mark.asyncio async def test_create_batch_prediction_job_async( transport: str = "grpc_asyncio", request_type=job_service.CreateBatchPredictionJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_batch_prediction_job.BatchPredictionJob( name="name_value", display_name="display_name_value", model="model_value", generate_explanation=True, state=job_state.JobState.JOB_STATE_QUEUED, ) ) response = await client.create_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, gca_batch_prediction_job.BatchPredictionJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.model == "model_value" assert response.generate_explanation is True assert response.state == job_state.JobState.JOB_STATE_QUEUED @pytest.mark.asyncio async def test_create_batch_prediction_job_async_from_dict(): await test_create_batch_prediction_job_async(request_type=dict) def test_create_batch_prediction_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateBatchPredictionJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_batch_prediction_job), "__call__" ) as call: call.return_value = gca_batch_prediction_job.BatchPredictionJob() client.create_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_create_batch_prediction_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateBatchPredictionJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_batch_prediction_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_batch_prediction_job.BatchPredictionJob() ) await client.create_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_create_batch_prediction_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_batch_prediction_job.BatchPredictionJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.create_batch_prediction_job( parent="parent_value", batch_prediction_job=gca_batch_prediction_job.BatchPredictionJob( name="name_value" ), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].batch_prediction_job mock_val = gca_batch_prediction_job.BatchPredictionJob(name="name_value") assert arg == mock_val def test_create_batch_prediction_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.create_batch_prediction_job( job_service.CreateBatchPredictionJobRequest(), parent="parent_value", batch_prediction_job=gca_batch_prediction_job.BatchPredictionJob( name="name_value" ), ) @pytest.mark.asyncio async def test_create_batch_prediction_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_batch_prediction_job.BatchPredictionJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_batch_prediction_job.BatchPredictionJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.create_batch_prediction_job( parent="parent_value", batch_prediction_job=gca_batch_prediction_job.BatchPredictionJob( name="name_value" ), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].batch_prediction_job mock_val = gca_batch_prediction_job.BatchPredictionJob(name="name_value") assert arg == mock_val @pytest.mark.asyncio async def test_create_batch_prediction_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.create_batch_prediction_job( job_service.CreateBatchPredictionJobRequest(), parent="parent_value", batch_prediction_job=gca_batch_prediction_job.BatchPredictionJob( name="name_value" ), ) def test_get_batch_prediction_job( transport: str = "grpc", request_type=job_service.GetBatchPredictionJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = batch_prediction_job.BatchPredictionJob( name="name_value", display_name="display_name_value", model="model_value", generate_explanation=True, state=job_state.JobState.JOB_STATE_QUEUED, ) response = client.get_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, batch_prediction_job.BatchPredictionJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.model == "model_value" assert response.generate_explanation is True assert response.state == job_state.JobState.JOB_STATE_QUEUED def test_get_batch_prediction_job_from_dict(): test_get_batch_prediction_job(request_type=dict) def test_get_batch_prediction_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_batch_prediction_job), "__call__" ) as call: client.get_batch_prediction_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetBatchPredictionJobRequest() @pytest.mark.asyncio async def test_get_batch_prediction_job_async( transport: str = "grpc_asyncio", request_type=job_service.GetBatchPredictionJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( batch_prediction_job.BatchPredictionJob( name="name_value", display_name="display_name_value", model="model_value", generate_explanation=True, state=job_state.JobState.JOB_STATE_QUEUED, ) ) response = await client.get_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, batch_prediction_job.BatchPredictionJob) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.model == "model_value" assert response.generate_explanation is True assert response.state == job_state.JobState.JOB_STATE_QUEUED @pytest.mark.asyncio async def test_get_batch_prediction_job_async_from_dict(): await test_get_batch_prediction_job_async(request_type=dict) def test_get_batch_prediction_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetBatchPredictionJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_batch_prediction_job), "__call__" ) as call: call.return_value = batch_prediction_job.BatchPredictionJob() client.get_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_get_batch_prediction_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetBatchPredictionJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_batch_prediction_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( batch_prediction_job.BatchPredictionJob() ) await client.get_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_get_batch_prediction_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = batch_prediction_job.BatchPredictionJob() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.get_batch_prediction_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_get_batch_prediction_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.get_batch_prediction_job( job_service.GetBatchPredictionJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_get_batch_prediction_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = batch_prediction_job.BatchPredictionJob() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( batch_prediction_job.BatchPredictionJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.get_batch_prediction_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_get_batch_prediction_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.get_batch_prediction_job( job_service.GetBatchPredictionJobRequest(), name="name_value", ) def test_list_batch_prediction_jobs( transport: str = "grpc", request_type=job_service.ListBatchPredictionJobsRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListBatchPredictionJobsResponse( next_page_token="next_page_token_value", ) response = client.list_batch_prediction_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListBatchPredictionJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListBatchPredictionJobsPager) assert response.next_page_token == "next_page_token_value" def test_list_batch_prediction_jobs_from_dict(): test_list_batch_prediction_jobs(request_type=dict) def test_list_batch_prediction_jobs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: client.list_batch_prediction_jobs() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListBatchPredictionJobsRequest() @pytest.mark.asyncio async def test_list_batch_prediction_jobs_async( transport: str = "grpc_asyncio", request_type=job_service.ListBatchPredictionJobsRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListBatchPredictionJobsResponse( next_page_token="next_page_token_value", ) ) response = await client.list_batch_prediction_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListBatchPredictionJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListBatchPredictionJobsAsyncPager) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_list_batch_prediction_jobs_async_from_dict(): await test_list_batch_prediction_jobs_async(request_type=dict) def test_list_batch_prediction_jobs_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListBatchPredictionJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: call.return_value = job_service.ListBatchPredictionJobsResponse() client.list_batch_prediction_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_list_batch_prediction_jobs_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListBatchPredictionJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListBatchPredictionJobsResponse() ) await client.list_batch_prediction_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_list_batch_prediction_jobs_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListBatchPredictionJobsResponse() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.list_batch_prediction_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val def test_list_batch_prediction_jobs_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.list_batch_prediction_jobs( job_service.ListBatchPredictionJobsRequest(), parent="parent_value", ) @pytest.mark.asyncio async def test_list_batch_prediction_jobs_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListBatchPredictionJobsResponse() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListBatchPredictionJobsResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.list_batch_prediction_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val @pytest.mark.asyncio async def test_list_batch_prediction_jobs_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.list_batch_prediction_jobs( job_service.ListBatchPredictionJobsRequest(), parent="parent_value", ) def test_list_batch_prediction_jobs_pager(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], next_page_token="abc", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[], next_page_token="def", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[batch_prediction_job.BatchPredictionJob(),], next_page_token="ghi", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], ), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)), ) pager = client.list_batch_prediction_jobs(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all( isinstance(i, batch_prediction_job.BatchPredictionJob) for i in results ) def test_list_batch_prediction_jobs_pages(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], next_page_token="abc", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[], next_page_token="def", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[batch_prediction_job.BatchPredictionJob(),], next_page_token="ghi", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], ), RuntimeError, ) pages = list(client.list_batch_prediction_jobs(request={}).pages) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_list_batch_prediction_jobs_async_pager(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], next_page_token="abc", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[], next_page_token="def", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[batch_prediction_job.BatchPredictionJob(),], next_page_token="ghi", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], ), RuntimeError, ) async_pager = await client.list_batch_prediction_jobs(request={},) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all( isinstance(i, batch_prediction_job.BatchPredictionJob) for i in responses ) @pytest.mark.asyncio async def test_list_batch_prediction_jobs_async_pages(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_batch_prediction_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], next_page_token="abc", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[], next_page_token="def", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[batch_prediction_job.BatchPredictionJob(),], next_page_token="ghi", ), job_service.ListBatchPredictionJobsResponse( batch_prediction_jobs=[ batch_prediction_job.BatchPredictionJob(), batch_prediction_job.BatchPredictionJob(), ], ), RuntimeError, ) pages = [] async for page_ in (await client.list_batch_prediction_jobs(request={})).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_delete_batch_prediction_job( transport: str = "grpc", request_type=job_service.DeleteBatchPredictionJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/spam") response = client.delete_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) def test_delete_batch_prediction_job_from_dict(): test_delete_batch_prediction_job(request_type=dict) def test_delete_batch_prediction_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_batch_prediction_job), "__call__" ) as call: client.delete_batch_prediction_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteBatchPredictionJobRequest() @pytest.mark.asyncio async def test_delete_batch_prediction_job_async( transport: str = "grpc_asyncio", request_type=job_service.DeleteBatchPredictionJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) response = await client.delete_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) @pytest.mark.asyncio async def test_delete_batch_prediction_job_async_from_dict(): await test_delete_batch_prediction_job_async(request_type=dict) def test_delete_batch_prediction_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteBatchPredictionJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_batch_prediction_job), "__call__" ) as call: call.return_value = operations_pb2.Operation(name="operations/op") client.delete_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_delete_batch_prediction_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteBatchPredictionJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_batch_prediction_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/op") ) await client.delete_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_delete_batch_prediction_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.delete_batch_prediction_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_delete_batch_prediction_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.delete_batch_prediction_job( job_service.DeleteBatchPredictionJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_delete_batch_prediction_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.delete_batch_prediction_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_delete_batch_prediction_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.delete_batch_prediction_job( job_service.DeleteBatchPredictionJobRequest(), name="name_value", ) def test_cancel_batch_prediction_job( transport: str = "grpc", request_type=job_service.CancelBatchPredictionJobRequest ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None response = client.cancel_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert response is None def test_cancel_batch_prediction_job_from_dict(): test_cancel_batch_prediction_job(request_type=dict) def test_cancel_batch_prediction_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_batch_prediction_job), "__call__" ) as call: client.cancel_batch_prediction_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelBatchPredictionJobRequest() @pytest.mark.asyncio async def test_cancel_batch_prediction_job_async( transport: str = "grpc_asyncio", request_type=job_service.CancelBatchPredictionJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.cancel_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CancelBatchPredictionJobRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_cancel_batch_prediction_job_async_from_dict(): await test_cancel_batch_prediction_job_async(request_type=dict) def test_cancel_batch_prediction_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelBatchPredictionJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_batch_prediction_job), "__call__" ) as call: call.return_value = None client.cancel_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_cancel_batch_prediction_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CancelBatchPredictionJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_batch_prediction_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.cancel_batch_prediction_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_cancel_batch_prediction_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.cancel_batch_prediction_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_cancel_batch_prediction_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.cancel_batch_prediction_job( job_service.CancelBatchPredictionJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_cancel_batch_prediction_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.cancel_batch_prediction_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.cancel_batch_prediction_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_cancel_batch_prediction_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.cancel_batch_prediction_job( job_service.CancelBatchPredictionJobRequest(), name="name_value", ) def test_create_model_deployment_monitoring_job( transport: str = "grpc", request_type=job_service.CreateModelDeploymentMonitoringJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value", display_name="display_name_value", endpoint="endpoint_value", state=job_state.JobState.JOB_STATE_QUEUED, schedule_state=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING, predict_instance_schema_uri="predict_instance_schema_uri_value", analysis_instance_schema_uri="analysis_instance_schema_uri_value", enable_monitoring_pipeline_logs=True, ) response = client.create_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance( response, gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob ) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.endpoint == "endpoint_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert ( response.schedule_state == gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING ) assert response.predict_instance_schema_uri == "predict_instance_schema_uri_value" assert response.analysis_instance_schema_uri == "analysis_instance_schema_uri_value" assert response.enable_monitoring_pipeline_logs is True def test_create_model_deployment_monitoring_job_from_dict(): test_create_model_deployment_monitoring_job(request_type=dict) def test_create_model_deployment_monitoring_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_model_deployment_monitoring_job), "__call__" ) as call: client.create_model_deployment_monitoring_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateModelDeploymentMonitoringJobRequest() @pytest.mark.asyncio async def test_create_model_deployment_monitoring_job_async( transport: str = "grpc_asyncio", request_type=job_service.CreateModelDeploymentMonitoringJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value", display_name="display_name_value", endpoint="endpoint_value", state=job_state.JobState.JOB_STATE_QUEUED, schedule_state=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING, predict_instance_schema_uri="predict_instance_schema_uri_value", analysis_instance_schema_uri="analysis_instance_schema_uri_value", enable_monitoring_pipeline_logs=True, ) ) response = await client.create_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.CreateModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance( response, gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob ) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.endpoint == "endpoint_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert ( response.schedule_state == gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING ) assert response.predict_instance_schema_uri == "predict_instance_schema_uri_value" assert response.analysis_instance_schema_uri == "analysis_instance_schema_uri_value" assert response.enable_monitoring_pipeline_logs is True @pytest.mark.asyncio async def test_create_model_deployment_monitoring_job_async_from_dict(): await test_create_model_deployment_monitoring_job_async(request_type=dict) def test_create_model_deployment_monitoring_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateModelDeploymentMonitoringJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = ( gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) client.create_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_create_model_deployment_monitoring_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.CreateModelDeploymentMonitoringJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) await client.create_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_create_model_deployment_monitoring_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = ( gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.create_model_deployment_monitoring_job( parent="parent_value", model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].model_deployment_monitoring_job mock_val = gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ) assert arg == mock_val def test_create_model_deployment_monitoring_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.create_model_deployment_monitoring_job( job_service.CreateModelDeploymentMonitoringJobRequest(), parent="parent_value", model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), ) @pytest.mark.asyncio async def test_create_model_deployment_monitoring_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = ( gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.create_model_deployment_monitoring_job( parent="parent_value", model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val arg = args[0].model_deployment_monitoring_job mock_val = gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ) assert arg == mock_val @pytest.mark.asyncio async def test_create_model_deployment_monitoring_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.create_model_deployment_monitoring_job( job_service.CreateModelDeploymentMonitoringJobRequest(), parent="parent_value", model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), ) def test_search_model_deployment_monitoring_stats_anomalies( transport: str = "grpc", request_type=job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( next_page_token="next_page_token_value", ) response = client.search_model_deployment_monitoring_stats_anomalies(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert ( args[0] == job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest() ) # Establish that the response is the type that we expect. assert isinstance( response, pagers.SearchModelDeploymentMonitoringStatsAnomaliesPager ) assert response.next_page_token == "next_page_token_value" def test_search_model_deployment_monitoring_stats_anomalies_from_dict(): test_search_model_deployment_monitoring_stats_anomalies(request_type=dict) def test_search_model_deployment_monitoring_stats_anomalies_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: client.search_model_deployment_monitoring_stats_anomalies() call.assert_called() _, args, _ = call.mock_calls[0] assert ( args[0] == job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest() ) @pytest.mark.asyncio async def test_search_model_deployment_monitoring_stats_anomalies_async( transport: str = "grpc_asyncio", request_type=job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( next_page_token="next_page_token_value", ) ) response = await client.search_model_deployment_monitoring_stats_anomalies( request ) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert ( args[0] == job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest() ) # Establish that the response is the type that we expect. assert isinstance( response, pagers.SearchModelDeploymentMonitoringStatsAnomaliesAsyncPager ) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_search_model_deployment_monitoring_stats_anomalies_async_from_dict(): await test_search_model_deployment_monitoring_stats_anomalies_async( request_type=dict ) def test_search_model_deployment_monitoring_stats_anomalies_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest() request.model_deployment_monitoring_job = "model_deployment_monitoring_job/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: call.return_value = ( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse() ) client.search_model_deployment_monitoring_stats_anomalies(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ( "x-goog-request-params", "model_deployment_monitoring_job=model_deployment_monitoring_job/value", ) in kw["metadata"] @pytest.mark.asyncio async def test_search_model_deployment_monitoring_stats_anomalies_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest() request.model_deployment_monitoring_job = "model_deployment_monitoring_job/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse() ) await client.search_model_deployment_monitoring_stats_anomalies(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ( "x-goog-request-params", "model_deployment_monitoring_job=model_deployment_monitoring_job/value", ) in kw["metadata"] def test_search_model_deployment_monitoring_stats_anomalies_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: # Designate an appropriate return value for the call. call.return_value = ( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.search_model_deployment_monitoring_stats_anomalies( model_deployment_monitoring_job="model_deployment_monitoring_job_value", deployed_model_id="deployed_model_id_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].model_deployment_monitoring_job mock_val = "model_deployment_monitoring_job_value" assert arg == mock_val arg = args[0].deployed_model_id mock_val = "deployed_model_id_value" assert arg == mock_val def test_search_model_deployment_monitoring_stats_anomalies_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.search_model_deployment_monitoring_stats_anomalies( job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest(), model_deployment_monitoring_job="model_deployment_monitoring_job_value", deployed_model_id="deployed_model_id_value", ) @pytest.mark.asyncio async def test_search_model_deployment_monitoring_stats_anomalies_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: # Designate an appropriate return value for the call. call.return_value = ( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse() ) call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.search_model_deployment_monitoring_stats_anomalies( model_deployment_monitoring_job="model_deployment_monitoring_job_value", deployed_model_id="deployed_model_id_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].model_deployment_monitoring_job mock_val = "model_deployment_monitoring_job_value" assert arg == mock_val arg = args[0].deployed_model_id mock_val = "deployed_model_id_value" assert arg == mock_val @pytest.mark.asyncio async def test_search_model_deployment_monitoring_stats_anomalies_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.search_model_deployment_monitoring_stats_anomalies( job_service.SearchModelDeploymentMonitoringStatsAnomaliesRequest(), model_deployment_monitoring_job="model_deployment_monitoring_job_value", deployed_model_id="deployed_model_id_value", ) def test_search_model_deployment_monitoring_stats_anomalies_pager(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="abc", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[], next_page_token="def", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="ghi", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], ), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata( (("model_deployment_monitoring_job", ""),) ), ) pager = client.search_model_deployment_monitoring_stats_anomalies(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all( isinstance( i, gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies ) for i in results ) def test_search_model_deployment_monitoring_stats_anomalies_pages(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="abc", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[], next_page_token="def", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="ghi", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], ), RuntimeError, ) pages = list( client.search_model_deployment_monitoring_stats_anomalies(request={}).pages ) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_search_model_deployment_monitoring_stats_anomalies_async_pager(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="abc", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[], next_page_token="def", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="ghi", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], ), RuntimeError, ) async_pager = await client.search_model_deployment_monitoring_stats_anomalies( request={}, ) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all( isinstance( i, gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies ) for i in responses ) @pytest.mark.asyncio async def test_search_model_deployment_monitoring_stats_anomalies_async_pages(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.search_model_deployment_monitoring_stats_anomalies), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="abc", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[], next_page_token="def", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], next_page_token="ghi", ), job_service.SearchModelDeploymentMonitoringStatsAnomaliesResponse( monitoring_stats=[ gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), gca_model_deployment_monitoring_job.ModelMonitoringStatsAnomalies(), ], ), RuntimeError, ) pages = [] async for page_ in ( await client.search_model_deployment_monitoring_stats_anomalies(request={}) ).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_get_model_deployment_monitoring_job( transport: str = "grpc", request_type=job_service.GetModelDeploymentMonitoringJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value", display_name="display_name_value", endpoint="endpoint_value", state=job_state.JobState.JOB_STATE_QUEUED, schedule_state=model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING, predict_instance_schema_uri="predict_instance_schema_uri_value", analysis_instance_schema_uri="analysis_instance_schema_uri_value", enable_monitoring_pipeline_logs=True, ) response = client.get_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance( response, model_deployment_monitoring_job.ModelDeploymentMonitoringJob ) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.endpoint == "endpoint_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert ( response.schedule_state == model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING ) assert response.predict_instance_schema_uri == "predict_instance_schema_uri_value" assert response.analysis_instance_schema_uri == "analysis_instance_schema_uri_value" assert response.enable_monitoring_pipeline_logs is True def test_get_model_deployment_monitoring_job_from_dict(): test_get_model_deployment_monitoring_job(request_type=dict) def test_get_model_deployment_monitoring_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_model_deployment_monitoring_job), "__call__" ) as call: client.get_model_deployment_monitoring_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetModelDeploymentMonitoringJobRequest() @pytest.mark.asyncio async def test_get_model_deployment_monitoring_job_async( transport: str = "grpc_asyncio", request_type=job_service.GetModelDeploymentMonitoringJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value", display_name="display_name_value", endpoint="endpoint_value", state=job_state.JobState.JOB_STATE_QUEUED, schedule_state=model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING, predict_instance_schema_uri="predict_instance_schema_uri_value", analysis_instance_schema_uri="analysis_instance_schema_uri_value", enable_monitoring_pipeline_logs=True, ) ) response = await client.get_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.GetModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance( response, model_deployment_monitoring_job.ModelDeploymentMonitoringJob ) assert response.name == "name_value" assert response.display_name == "display_name_value" assert response.endpoint == "endpoint_value" assert response.state == job_state.JobState.JOB_STATE_QUEUED assert ( response.schedule_state == model_deployment_monitoring_job.ModelDeploymentMonitoringJob.MonitoringScheduleState.PENDING ) assert response.predict_instance_schema_uri == "predict_instance_schema_uri_value" assert response.analysis_instance_schema_uri == "analysis_instance_schema_uri_value" assert response.enable_monitoring_pipeline_logs is True @pytest.mark.asyncio async def test_get_model_deployment_monitoring_job_async_from_dict(): await test_get_model_deployment_monitoring_job_async(request_type=dict) def test_get_model_deployment_monitoring_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = ( model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) client.get_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_get_model_deployment_monitoring_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.GetModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) await client.get_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_get_model_deployment_monitoring_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = ( model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.get_model_deployment_monitoring_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_get_model_deployment_monitoring_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.get_model_deployment_monitoring_job( job_service.GetModelDeploymentMonitoringJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_get_model_deployment_monitoring_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.get_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = ( model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( model_deployment_monitoring_job.ModelDeploymentMonitoringJob() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.get_model_deployment_monitoring_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_get_model_deployment_monitoring_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.get_model_deployment_monitoring_job( job_service.GetModelDeploymentMonitoringJobRequest(), name="name_value", ) def test_list_model_deployment_monitoring_jobs( transport: str = "grpc", request_type=job_service.ListModelDeploymentMonitoringJobsRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListModelDeploymentMonitoringJobsResponse( next_page_token="next_page_token_value", ) response = client.list_model_deployment_monitoring_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListModelDeploymentMonitoringJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListModelDeploymentMonitoringJobsPager) assert response.next_page_token == "next_page_token_value" def test_list_model_deployment_monitoring_jobs_from_dict(): test_list_model_deployment_monitoring_jobs(request_type=dict) def test_list_model_deployment_monitoring_jobs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: client.list_model_deployment_monitoring_jobs() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListModelDeploymentMonitoringJobsRequest() @pytest.mark.asyncio async def test_list_model_deployment_monitoring_jobs_async( transport: str = "grpc_asyncio", request_type=job_service.ListModelDeploymentMonitoringJobsRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListModelDeploymentMonitoringJobsResponse( next_page_token="next_page_token_value", ) ) response = await client.list_model_deployment_monitoring_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.ListModelDeploymentMonitoringJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListModelDeploymentMonitoringJobsAsyncPager) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_list_model_deployment_monitoring_jobs_async_from_dict(): await test_list_model_deployment_monitoring_jobs_async(request_type=dict) def test_list_model_deployment_monitoring_jobs_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListModelDeploymentMonitoringJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: call.return_value = job_service.ListModelDeploymentMonitoringJobsResponse() client.list_model_deployment_monitoring_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_list_model_deployment_monitoring_jobs_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ListModelDeploymentMonitoringJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListModelDeploymentMonitoringJobsResponse() ) await client.list_model_deployment_monitoring_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_list_model_deployment_monitoring_jobs_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListModelDeploymentMonitoringJobsResponse() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.list_model_deployment_monitoring_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val def test_list_model_deployment_monitoring_jobs_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.list_model_deployment_monitoring_jobs( job_service.ListModelDeploymentMonitoringJobsRequest(), parent="parent_value", ) @pytest.mark.asyncio async def test_list_model_deployment_monitoring_jobs_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = job_service.ListModelDeploymentMonitoringJobsResponse() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( job_service.ListModelDeploymentMonitoringJobsResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.list_model_deployment_monitoring_jobs( parent="parent_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].parent mock_val = "parent_value" assert arg == mock_val @pytest.mark.asyncio async def test_list_model_deployment_monitoring_jobs_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.list_model_deployment_monitoring_jobs( job_service.ListModelDeploymentMonitoringJobsRequest(), parent="parent_value", ) def test_list_model_deployment_monitoring_jobs_pager(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="abc", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[], next_page_token="def", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="ghi", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], ), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)), ) pager = client.list_model_deployment_monitoring_jobs(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all( isinstance(i, model_deployment_monitoring_job.ModelDeploymentMonitoringJob) for i in results ) def test_list_model_deployment_monitoring_jobs_pages(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="abc", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[], next_page_token="def", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="ghi", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], ), RuntimeError, ) pages = list(client.list_model_deployment_monitoring_jobs(request={}).pages) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_list_model_deployment_monitoring_jobs_async_pager(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="abc", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[], next_page_token="def", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="ghi", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], ), RuntimeError, ) async_pager = await client.list_model_deployment_monitoring_jobs(request={},) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all( isinstance(i, model_deployment_monitoring_job.ModelDeploymentMonitoringJob) for i in responses ) @pytest.mark.asyncio async def test_list_model_deployment_monitoring_jobs_async_pages(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_model_deployment_monitoring_jobs), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="abc", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[], next_page_token="def", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], next_page_token="ghi", ), job_service.ListModelDeploymentMonitoringJobsResponse( model_deployment_monitoring_jobs=[ model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), model_deployment_monitoring_job.ModelDeploymentMonitoringJob(), ], ), RuntimeError, ) pages = [] async for page_ in ( await client.list_model_deployment_monitoring_jobs(request={}) ).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_update_model_deployment_monitoring_job( transport: str = "grpc", request_type=job_service.UpdateModelDeploymentMonitoringJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.update_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/spam") response = client.update_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.UpdateModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) def test_update_model_deployment_monitoring_job_from_dict(): test_update_model_deployment_monitoring_job(request_type=dict) def test_update_model_deployment_monitoring_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.update_model_deployment_monitoring_job), "__call__" ) as call: client.update_model_deployment_monitoring_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.UpdateModelDeploymentMonitoringJobRequest() @pytest.mark.asyncio async def test_update_model_deployment_monitoring_job_async( transport: str = "grpc_asyncio", request_type=job_service.UpdateModelDeploymentMonitoringJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.update_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) response = await client.update_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.UpdateModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) @pytest.mark.asyncio async def test_update_model_deployment_monitoring_job_async_from_dict(): await test_update_model_deployment_monitoring_job_async(request_type=dict) def test_update_model_deployment_monitoring_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.UpdateModelDeploymentMonitoringJobRequest() request.model_deployment_monitoring_job.name = ( "model_deployment_monitoring_job.name/value" ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.update_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = operations_pb2.Operation(name="operations/op") client.update_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ( "x-goog-request-params", "model_deployment_monitoring_job.name=model_deployment_monitoring_job.name/value", ) in kw["metadata"] @pytest.mark.asyncio async def test_update_model_deployment_monitoring_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.UpdateModelDeploymentMonitoringJobRequest() request.model_deployment_monitoring_job.name = ( "model_deployment_monitoring_job.name/value" ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.update_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/op") ) await client.update_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ( "x-goog-request-params", "model_deployment_monitoring_job.name=model_deployment_monitoring_job.name/value", ) in kw["metadata"] def test_update_model_deployment_monitoring_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.update_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.update_model_deployment_monitoring_job( model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), update_mask=field_mask_pb2.FieldMask(paths=["paths_value"]), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].model_deployment_monitoring_job mock_val = gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ) assert arg == mock_val arg = args[0].update_mask mock_val = field_mask_pb2.FieldMask(paths=["paths_value"]) assert arg == mock_val def test_update_model_deployment_monitoring_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.update_model_deployment_monitoring_job( job_service.UpdateModelDeploymentMonitoringJobRequest(), model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), update_mask=field_mask_pb2.FieldMask(paths=["paths_value"]), ) @pytest.mark.asyncio async def test_update_model_deployment_monitoring_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.update_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.update_model_deployment_monitoring_job( model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), update_mask=field_mask_pb2.FieldMask(paths=["paths_value"]), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].model_deployment_monitoring_job mock_val = gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ) assert arg == mock_val arg = args[0].update_mask mock_val = field_mask_pb2.FieldMask(paths=["paths_value"]) assert arg == mock_val @pytest.mark.asyncio async def test_update_model_deployment_monitoring_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.update_model_deployment_monitoring_job( job_service.UpdateModelDeploymentMonitoringJobRequest(), model_deployment_monitoring_job=gca_model_deployment_monitoring_job.ModelDeploymentMonitoringJob( name="name_value" ), update_mask=field_mask_pb2.FieldMask(paths=["paths_value"]), ) def test_delete_model_deployment_monitoring_job( transport: str = "grpc", request_type=job_service.DeleteModelDeploymentMonitoringJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/spam") response = client.delete_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) def test_delete_model_deployment_monitoring_job_from_dict(): test_delete_model_deployment_monitoring_job(request_type=dict) def test_delete_model_deployment_monitoring_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_model_deployment_monitoring_job), "__call__" ) as call: client.delete_model_deployment_monitoring_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteModelDeploymentMonitoringJobRequest() @pytest.mark.asyncio async def test_delete_model_deployment_monitoring_job_async( transport: str = "grpc_asyncio", request_type=job_service.DeleteModelDeploymentMonitoringJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) response = await client.delete_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.DeleteModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, future.Future) @pytest.mark.asyncio async def test_delete_model_deployment_monitoring_job_async_from_dict(): await test_delete_model_deployment_monitoring_job_async(request_type=dict) def test_delete_model_deployment_monitoring_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = operations_pb2.Operation(name="operations/op") client.delete_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_delete_model_deployment_monitoring_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.DeleteModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/op") ) await client.delete_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_delete_model_deployment_monitoring_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.delete_model_deployment_monitoring_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_delete_model_deployment_monitoring_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.delete_model_deployment_monitoring_job( job_service.DeleteModelDeploymentMonitoringJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_delete_model_deployment_monitoring_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = operations_pb2.Operation(name="operations/op") call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( operations_pb2.Operation(name="operations/spam") ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.delete_model_deployment_monitoring_job( name="name_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_delete_model_deployment_monitoring_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.delete_model_deployment_monitoring_job( job_service.DeleteModelDeploymentMonitoringJobRequest(), name="name_value", ) def test_pause_model_deployment_monitoring_job( transport: str = "grpc", request_type=job_service.PauseModelDeploymentMonitoringJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.pause_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None response = client.pause_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.PauseModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert response is None def test_pause_model_deployment_monitoring_job_from_dict(): test_pause_model_deployment_monitoring_job(request_type=dict) def test_pause_model_deployment_monitoring_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.pause_model_deployment_monitoring_job), "__call__" ) as call: client.pause_model_deployment_monitoring_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.PauseModelDeploymentMonitoringJobRequest() @pytest.mark.asyncio async def test_pause_model_deployment_monitoring_job_async( transport: str = "grpc_asyncio", request_type=job_service.PauseModelDeploymentMonitoringJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.pause_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.pause_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.PauseModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_pause_model_deployment_monitoring_job_async_from_dict(): await test_pause_model_deployment_monitoring_job_async(request_type=dict) def test_pause_model_deployment_monitoring_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.PauseModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.pause_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = None client.pause_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_pause_model_deployment_monitoring_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.PauseModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.pause_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.pause_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_pause_model_deployment_monitoring_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.pause_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.pause_model_deployment_monitoring_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_pause_model_deployment_monitoring_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.pause_model_deployment_monitoring_job( job_service.PauseModelDeploymentMonitoringJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_pause_model_deployment_monitoring_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.pause_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.pause_model_deployment_monitoring_job( name="name_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_pause_model_deployment_monitoring_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.pause_model_deployment_monitoring_job( job_service.PauseModelDeploymentMonitoringJobRequest(), name="name_value", ) def test_resume_model_deployment_monitoring_job( transport: str = "grpc", request_type=job_service.ResumeModelDeploymentMonitoringJobRequest, ): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.resume_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None response = client.resume_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == job_service.ResumeModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert response is None def test_resume_model_deployment_monitoring_job_from_dict(): test_resume_model_deployment_monitoring_job(request_type=dict) def test_resume_model_deployment_monitoring_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.resume_model_deployment_monitoring_job), "__call__" ) as call: client.resume_model_deployment_monitoring_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == job_service.ResumeModelDeploymentMonitoringJobRequest() @pytest.mark.asyncio async def test_resume_model_deployment_monitoring_job_async( transport: str = "grpc_asyncio", request_type=job_service.ResumeModelDeploymentMonitoringJobRequest, ): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.resume_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.resume_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == job_service.ResumeModelDeploymentMonitoringJobRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_resume_model_deployment_monitoring_job_async_from_dict(): await test_resume_model_deployment_monitoring_job_async(request_type=dict) def test_resume_model_deployment_monitoring_job_field_headers(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ResumeModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.resume_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = None client.resume_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_resume_model_deployment_monitoring_job_field_headers_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = job_service.ResumeModelDeploymentMonitoringJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.resume_model_deployment_monitoring_job), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.resume_model_deployment_monitoring_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_resume_model_deployment_monitoring_job_flattened(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.resume_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.resume_model_deployment_monitoring_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val def test_resume_model_deployment_monitoring_job_flattened_error(): client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.resume_model_deployment_monitoring_job( job_service.ResumeModelDeploymentMonitoringJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_resume_model_deployment_monitoring_job_flattened_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.resume_model_deployment_monitoring_job), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.resume_model_deployment_monitoring_job( name="name_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] arg = args[0].name mock_val = "name_value" assert arg == mock_val @pytest.mark.asyncio async def test_resume_model_deployment_monitoring_job_flattened_error_async(): client = JobServiceAsyncClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.resume_model_deployment_monitoring_job( job_service.ResumeModelDeploymentMonitoringJobRequest(), name="name_value", ) def test_credentials_transport_error(): # It is an error to provide credentials and a transport instance. transport = transports.JobServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) with pytest.raises(ValueError): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # It is an error to provide a credentials file and a transport instance. transport = transports.JobServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) with pytest.raises(ValueError): client = JobServiceClient( client_options={"credentials_file": "credentials.json"}, transport=transport, ) # It is an error to provide scopes and a transport instance. transport = transports.JobServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) with pytest.raises(ValueError): client = JobServiceClient( client_options={"scopes": ["1", "2"]}, transport=transport, ) def test_transport_instance(): # A client may be instantiated with a custom transport instance. transport = transports.JobServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) client = JobServiceClient(transport=transport) assert client.transport is transport def test_transport_get_channel(): # A client may be instantiated with a custom transport instance. transport = transports.JobServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) channel = transport.grpc_channel assert channel transport = transports.JobServiceGrpcAsyncIOTransport( credentials=ga_credentials.AnonymousCredentials(), ) channel = transport.grpc_channel assert channel @pytest.mark.parametrize( "transport_class", [transports.JobServiceGrpcTransport, transports.JobServiceGrpcAsyncIOTransport,], ) def test_transport_adc(transport_class): # Test default credentials are used if not provided. with mock.patch.object(google.auth, "default") as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) transport_class() adc.assert_called_once() def test_transport_grpc_default(): # A client should use the gRPC transport by default. client = JobServiceClient(credentials=ga_credentials.AnonymousCredentials(),) assert isinstance(client.transport, transports.JobServiceGrpcTransport,) def test_job_service_base_transport_error(): # Passing both a credentials object and credentials_file should raise an error with pytest.raises(core_exceptions.DuplicateCredentialArgs): transport = transports.JobServiceTransport( credentials=ga_credentials.AnonymousCredentials(), credentials_file="credentials.json", ) def test_job_service_base_transport(): # Instantiate the base transport. with mock.patch( "google.cloud.aiplatform_v1.services.job_service.transports.JobServiceTransport.__init__" ) as Transport: Transport.return_value = None transport = transports.JobServiceTransport( credentials=ga_credentials.AnonymousCredentials(), ) # Every method on the transport should just blindly # raise NotImplementedError. methods = ( "create_custom_job", "get_custom_job", "list_custom_jobs", "delete_custom_job", "cancel_custom_job", "create_data_labeling_job", "get_data_labeling_job", "list_data_labeling_jobs", "delete_data_labeling_job", "cancel_data_labeling_job", "create_hyperparameter_tuning_job", "get_hyperparameter_tuning_job", "list_hyperparameter_tuning_jobs", "delete_hyperparameter_tuning_job", "cancel_hyperparameter_tuning_job", "create_batch_prediction_job", "get_batch_prediction_job", "list_batch_prediction_jobs", "delete_batch_prediction_job", "cancel_batch_prediction_job", "create_model_deployment_monitoring_job", "search_model_deployment_monitoring_stats_anomalies", "get_model_deployment_monitoring_job", "list_model_deployment_monitoring_jobs", "update_model_deployment_monitoring_job", "delete_model_deployment_monitoring_job", "pause_model_deployment_monitoring_job", "resume_model_deployment_monitoring_job", ) for method in methods: with pytest.raises(NotImplementedError): getattr(transport, method)(request=object()) with pytest.raises(NotImplementedError): transport.close() # Additionally, the LRO client (a property) should # also raise NotImplementedError with pytest.raises(NotImplementedError): transport.operations_client def test_job_service_base_transport_with_credentials_file(): # Instantiate the base transport with a credentials file with mock.patch.object( google.auth, "load_credentials_from_file", autospec=True ) as load_creds, mock.patch( "google.cloud.aiplatform_v1.services.job_service.transports.JobServiceTransport._prep_wrapped_messages" ) as Transport: Transport.return_value = None load_creds.return_value = (ga_credentials.AnonymousCredentials(), None) transport = transports.JobServiceTransport( credentials_file="credentials.json", quota_project_id="octopus", ) load_creds.assert_called_once_with( "credentials.json", scopes=None, default_scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id="octopus", ) def test_job_service_base_transport_with_adc(): # Test the default credentials are used if credentials and credentials_file are None. with mock.patch.object(google.auth, "default", autospec=True) as adc, mock.patch( "google.cloud.aiplatform_v1.services.job_service.transports.JobServiceTransport._prep_wrapped_messages" ) as Transport: Transport.return_value = None adc.return_value = (ga_credentials.AnonymousCredentials(), None) transport = transports.JobServiceTransport() adc.assert_called_once() def test_job_service_auth_adc(): # If no credentials are provided, we should use ADC credentials. with mock.patch.object(google.auth, "default", autospec=True) as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) JobServiceClient() adc.assert_called_once_with( scopes=None, default_scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id=None, ) @pytest.mark.parametrize( "transport_class", [transports.JobServiceGrpcTransport, transports.JobServiceGrpcAsyncIOTransport,], ) def test_job_service_transport_auth_adc(transport_class): # If credentials and host are not provided, the transport class should use # ADC credentials. with mock.patch.object(google.auth, "default", autospec=True) as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) transport_class(quota_project_id="octopus", scopes=["1", "2"]) adc.assert_called_once_with( scopes=["1", "2"], default_scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id="octopus", ) @pytest.mark.parametrize( "transport_class,grpc_helpers", [ (transports.JobServiceGrpcTransport, grpc_helpers), (transports.JobServiceGrpcAsyncIOTransport, grpc_helpers_async), ], ) def test_job_service_transport_create_channel(transport_class, grpc_helpers): # If credentials and host are not provided, the transport class should use # ADC credentials. with mock.patch.object( google.auth, "default", autospec=True ) as adc, mock.patch.object( grpc_helpers, "create_channel", autospec=True ) as create_channel: creds = ga_credentials.AnonymousCredentials() adc.return_value = (creds, None) transport_class(quota_project_id="octopus", scopes=["1", "2"]) create_channel.assert_called_with( "aiplatform.googleapis.com:443", credentials=creds, credentials_file=None, quota_project_id="octopus", default_scopes=("https://www.googleapis.com/auth/cloud-platform",), scopes=["1", "2"], default_host="aiplatform.googleapis.com", ssl_credentials=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) @pytest.mark.parametrize( "transport_class", [transports.JobServiceGrpcTransport, transports.JobServiceGrpcAsyncIOTransport], ) def test_job_service_grpc_transport_client_cert_source_for_mtls(transport_class): cred = ga_credentials.AnonymousCredentials() # Check ssl_channel_credentials is used if provided. with mock.patch.object(transport_class, "create_channel") as mock_create_channel: mock_ssl_channel_creds = mock.Mock() transport_class( host="squid.clam.whelk", credentials=cred, ssl_channel_credentials=mock_ssl_channel_creds, ) mock_create_channel.assert_called_once_with( "squid.clam.whelk:443", credentials=cred, credentials_file=None, scopes=None, ssl_credentials=mock_ssl_channel_creds, quota_project_id=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) # Check if ssl_channel_credentials is not provided, then client_cert_source_for_mtls # is used. with mock.patch.object(transport_class, "create_channel", return_value=mock.Mock()): with mock.patch("grpc.ssl_channel_credentials") as mock_ssl_cred: transport_class( credentials=cred, client_cert_source_for_mtls=client_cert_source_callback, ) expected_cert, expected_key = client_cert_source_callback() mock_ssl_cred.assert_called_once_with( certificate_chain=expected_cert, private_key=expected_key ) def test_job_service_host_no_port(): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), client_options=client_options.ClientOptions( api_endpoint="aiplatform.googleapis.com" ), ) assert client.transport._host == "aiplatform.googleapis.com:443" def test_job_service_host_with_port(): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), client_options=client_options.ClientOptions( api_endpoint="aiplatform.googleapis.com:8000" ), ) assert client.transport._host == "aiplatform.googleapis.com:8000" def test_job_service_grpc_transport_channel(): channel = grpc.secure_channel("http://localhost/", grpc.local_channel_credentials()) # Check that channel is used if provided. transport = transports.JobServiceGrpcTransport( host="squid.clam.whelk", channel=channel, ) assert transport.grpc_channel == channel assert transport._host == "squid.clam.whelk:443" assert transport._ssl_channel_credentials == None def test_job_service_grpc_asyncio_transport_channel(): channel = aio.secure_channel("http://localhost/", grpc.local_channel_credentials()) # Check that channel is used if provided. transport = transports.JobServiceGrpcAsyncIOTransport( host="squid.clam.whelk", channel=channel, ) assert transport.grpc_channel == channel assert transport._host == "squid.clam.whelk:443" assert transport._ssl_channel_credentials == None # Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are # removed from grpc/grpc_asyncio transport constructor. @pytest.mark.parametrize( "transport_class", [transports.JobServiceGrpcTransport, transports.JobServiceGrpcAsyncIOTransport], ) def test_job_service_transport_channel_mtls_with_client_cert_source(transport_class): with mock.patch( "grpc.ssl_channel_credentials", autospec=True ) as grpc_ssl_channel_cred: with mock.patch.object( transport_class, "create_channel" ) as grpc_create_channel: mock_ssl_cred = mock.Mock() grpc_ssl_channel_cred.return_value = mock_ssl_cred mock_grpc_channel = mock.Mock() grpc_create_channel.return_value = mock_grpc_channel cred = ga_credentials.AnonymousCredentials() with pytest.warns(DeprecationWarning): with mock.patch.object(google.auth, "default") as adc: adc.return_value = (cred, None) transport = transport_class( host="squid.clam.whelk", api_mtls_endpoint="mtls.squid.clam.whelk", client_cert_source=client_cert_source_callback, ) adc.assert_called_once() grpc_ssl_channel_cred.assert_called_once_with( certificate_chain=b"cert bytes", private_key=b"key bytes" ) grpc_create_channel.assert_called_once_with( "mtls.squid.clam.whelk:443", credentials=cred, credentials_file=None, scopes=None, ssl_credentials=mock_ssl_cred, quota_project_id=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) assert transport.grpc_channel == mock_grpc_channel assert transport._ssl_channel_credentials == mock_ssl_cred # Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are # removed from grpc/grpc_asyncio transport constructor. @pytest.mark.parametrize( "transport_class", [transports.JobServiceGrpcTransport, transports.JobServiceGrpcAsyncIOTransport], ) def test_job_service_transport_channel_mtls_with_adc(transport_class): mock_ssl_cred = mock.Mock() with mock.patch.multiple( "google.auth.transport.grpc.SslCredentials", __init__=mock.Mock(return_value=None), ssl_credentials=mock.PropertyMock(return_value=mock_ssl_cred), ): with mock.patch.object( transport_class, "create_channel" ) as grpc_create_channel: mock_grpc_channel = mock.Mock() grpc_create_channel.return_value = mock_grpc_channel mock_cred = mock.Mock() with pytest.warns(DeprecationWarning): transport = transport_class( host="squid.clam.whelk", credentials=mock_cred, api_mtls_endpoint="mtls.squid.clam.whelk", client_cert_source=None, ) grpc_create_channel.assert_called_once_with( "mtls.squid.clam.whelk:443", credentials=mock_cred, credentials_file=None, scopes=None, ssl_credentials=mock_ssl_cred, quota_project_id=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) assert transport.grpc_channel == mock_grpc_channel def test_job_service_grpc_lro_client(): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) transport = client.transport # Ensure that we have a api-core operations client. assert isinstance(transport.operations_client, operations_v1.OperationsClient,) # Ensure that subsequent calls to the property send the exact same object. assert transport.operations_client is transport.operations_client def test_job_service_grpc_lro_async_client(): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc_asyncio", ) transport = client.transport # Ensure that we have a api-core operations client. assert isinstance(transport.operations_client, operations_v1.OperationsAsyncClient,) # Ensure that subsequent calls to the property send the exact same object. assert transport.operations_client is transport.operations_client def test_batch_prediction_job_path(): project = "squid" location = "clam" batch_prediction_job = "whelk" expected = "projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}".format( project=project, location=location, batch_prediction_job=batch_prediction_job, ) actual = JobServiceClient.batch_prediction_job_path( project, location, batch_prediction_job ) assert expected == actual def test_parse_batch_prediction_job_path(): expected = { "project": "octopus", "location": "oyster", "batch_prediction_job": "nudibranch", } path = JobServiceClient.batch_prediction_job_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_batch_prediction_job_path(path) assert expected == actual def test_custom_job_path(): project = "cuttlefish" location = "mussel" custom_job = "winkle" expected = "projects/{project}/locations/{location}/customJobs/{custom_job}".format( project=project, location=location, custom_job=custom_job, ) actual = JobServiceClient.custom_job_path(project, location, custom_job) assert expected == actual def test_parse_custom_job_path(): expected = { "project": "nautilus", "location": "scallop", "custom_job": "abalone", } path = JobServiceClient.custom_job_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_custom_job_path(path) assert expected == actual def test_data_labeling_job_path(): project = "squid" location = "clam" data_labeling_job = "whelk" expected = "projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}".format( project=project, location=location, data_labeling_job=data_labeling_job, ) actual = JobServiceClient.data_labeling_job_path( project, location, data_labeling_job ) assert expected == actual def test_parse_data_labeling_job_path(): expected = { "project": "octopus", "location": "oyster", "data_labeling_job": "nudibranch", } path = JobServiceClient.data_labeling_job_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_data_labeling_job_path(path) assert expected == actual def test_dataset_path(): project = "cuttlefish" location = "mussel" dataset = "winkle" expected = "projects/{project}/locations/{location}/datasets/{dataset}".format( project=project, location=location, dataset=dataset, ) actual = JobServiceClient.dataset_path(project, location, dataset) assert expected == actual def test_parse_dataset_path(): expected = { "project": "nautilus", "location": "scallop", "dataset": "abalone", } path = JobServiceClient.dataset_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_dataset_path(path) assert expected == actual def test_endpoint_path(): project = "squid" location = "clam" endpoint = "whelk" expected = "projects/{project}/locations/{location}/endpoints/{endpoint}".format( project=project, location=location, endpoint=endpoint, ) actual = JobServiceClient.endpoint_path(project, location, endpoint) assert expected == actual def test_parse_endpoint_path(): expected = { "project": "octopus", "location": "oyster", "endpoint": "nudibranch", } path = JobServiceClient.endpoint_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_endpoint_path(path) assert expected == actual def test_hyperparameter_tuning_job_path(): project = "cuttlefish" location = "mussel" hyperparameter_tuning_job = "winkle" expected = "projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}".format( project=project, location=location, hyperparameter_tuning_job=hyperparameter_tuning_job, ) actual = JobServiceClient.hyperparameter_tuning_job_path( project, location, hyperparameter_tuning_job ) assert expected == actual def test_parse_hyperparameter_tuning_job_path(): expected = { "project": "nautilus", "location": "scallop", "hyperparameter_tuning_job": "abalone", } path = JobServiceClient.hyperparameter_tuning_job_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_hyperparameter_tuning_job_path(path) assert expected == actual def test_model_path(): project = "squid" location = "clam" model = "whelk" expected = "projects/{project}/locations/{location}/models/{model}".format( project=project, location=location, model=model, ) actual = JobServiceClient.model_path(project, location, model) assert expected == actual def test_parse_model_path(): expected = { "project": "octopus", "location": "oyster", "model": "nudibranch", } path = JobServiceClient.model_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_model_path(path) assert expected == actual def test_model_deployment_monitoring_job_path(): project = "cuttlefish" location = "mussel" model_deployment_monitoring_job = "winkle" expected = "projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}".format( project=project, location=location, model_deployment_monitoring_job=model_deployment_monitoring_job, ) actual = JobServiceClient.model_deployment_monitoring_job_path( project, location, model_deployment_monitoring_job ) assert expected == actual def test_parse_model_deployment_monitoring_job_path(): expected = { "project": "nautilus", "location": "scallop", "model_deployment_monitoring_job": "abalone", } path = JobServiceClient.model_deployment_monitoring_job_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_model_deployment_monitoring_job_path(path) assert expected == actual def test_network_path(): project = "squid" network = "clam" expected = "projects/{project}/global/networks/{network}".format( project=project, network=network, ) actual = JobServiceClient.network_path(project, network) assert expected == actual def test_parse_network_path(): expected = { "project": "whelk", "network": "octopus", } path = JobServiceClient.network_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_network_path(path) assert expected == actual def test_tensorboard_path(): project = "oyster" location = "nudibranch" tensorboard = "cuttlefish" expected = "projects/{project}/locations/{location}/tensorboards/{tensorboard}".format( project=project, location=location, tensorboard=tensorboard, ) actual = JobServiceClient.tensorboard_path(project, location, tensorboard) assert expected == actual def test_parse_tensorboard_path(): expected = { "project": "mussel", "location": "winkle", "tensorboard": "nautilus", } path = JobServiceClient.tensorboard_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_tensorboard_path(path) assert expected == actual def test_trial_path(): project = "scallop" location = "abalone" study = "squid" trial = "clam" expected = "projects/{project}/locations/{location}/studies/{study}/trials/{trial}".format( project=project, location=location, study=study, trial=trial, ) actual = JobServiceClient.trial_path(project, location, study, trial) assert expected == actual def test_parse_trial_path(): expected = { "project": "whelk", "location": "octopus", "study": "oyster", "trial": "nudibranch", } path = JobServiceClient.trial_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_trial_path(path) assert expected == actual def test_common_billing_account_path(): billing_account = "cuttlefish" expected = "billingAccounts/{billing_account}".format( billing_account=billing_account, ) actual = JobServiceClient.common_billing_account_path(billing_account) assert expected == actual def test_parse_common_billing_account_path(): expected = { "billing_account": "mussel", } path = JobServiceClient.common_billing_account_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_common_billing_account_path(path) assert expected == actual def test_common_folder_path(): folder = "winkle" expected = "folders/{folder}".format(folder=folder,) actual = JobServiceClient.common_folder_path(folder) assert expected == actual def test_parse_common_folder_path(): expected = { "folder": "nautilus", } path = JobServiceClient.common_folder_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_common_folder_path(path) assert expected == actual def test_common_organization_path(): organization = "scallop" expected = "organizations/{organization}".format(organization=organization,) actual = JobServiceClient.common_organization_path(organization) assert expected == actual def test_parse_common_organization_path(): expected = { "organization": "abalone", } path = JobServiceClient.common_organization_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_common_organization_path(path) assert expected == actual def test_common_project_path(): project = "squid" expected = "projects/{project}".format(project=project,) actual = JobServiceClient.common_project_path(project) assert expected == actual def test_parse_common_project_path(): expected = { "project": "clam", } path = JobServiceClient.common_project_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_common_project_path(path) assert expected == actual def test_common_location_path(): project = "whelk" location = "octopus" expected = "projects/{project}/locations/{location}".format( project=project, location=location, ) actual = JobServiceClient.common_location_path(project, location) assert expected == actual def test_parse_common_location_path(): expected = { "project": "oyster", "location": "nudibranch", } path = JobServiceClient.common_location_path(**expected) # Check that the path construction is reversible. actual = JobServiceClient.parse_common_location_path(path) assert expected == actual def test_client_withDEFAULT_CLIENT_INFO(): client_info = gapic_v1.client_info.ClientInfo() with mock.patch.object( transports.JobServiceTransport, "_prep_wrapped_messages" ) as prep: client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), client_info=client_info, ) prep.assert_called_once_with(client_info) with mock.patch.object( transports.JobServiceTransport, "_prep_wrapped_messages" ) as prep: transport_class = JobServiceClient.get_transport_class() transport = transport_class( credentials=ga_credentials.AnonymousCredentials(), client_info=client_info, ) prep.assert_called_once_with(client_info) @pytest.mark.asyncio async def test_transport_close_async(): client = JobServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc_asyncio", ) with mock.patch.object( type(getattr(client.transport, "grpc_channel")), "close" ) as close: async with client: close.assert_not_called() close.assert_called_once() def test_transport_close(): transports = { "grpc": "_grpc_channel", } for transport, close_name in transports.items(): client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport ) with mock.patch.object( type(getattr(client.transport, close_name)), "close" ) as close: with client: close.assert_not_called() close.assert_called_once() def test_client_ctx(): transports = [ "grpc", ] for transport in transports: client = JobServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport ) # Test client calls underlying transport. with mock.patch.object(type(client.transport), "close") as close: close.assert_not_called() with client: pass close.assert_called()

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Python

sdk/translation/azure-ai-translation-document/azure/ai/translation/document/_generated/operations/_document_translation_operations.py

ankitarorabit/azure-sdk-for-python

dd90281cbad9400f8080754a5ef2f56791a5a88f

[ "MIT" ]

null

sdk/translation/azure-ai-translation-document/azure/ai/translation/document/_generated/operations/_document_translation_operations.py

ankitarorabit/azure-sdk-for-python

dd90281cbad9400f8080754a5ef2f56791a5a88f

[ "MIT" ]

null

sdk/translation/azure-ai-translation-document/azure/ai/translation/document/_generated/operations/_document_translation_operations.py

ankitarorabit/azure-sdk-for-python

dd90281cbad9400f8080754a5ef2f56791a5a88f

[ "MIT" ]

null

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- import datetime from typing import TYPE_CHECKING import warnings from ..._polling import DocumentTranslationLROPollingMethod, DocumentTranslationPoller from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.paging import ItemPaged from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpRequest, HttpResponse from azure.core.polling import NoPolling, PollingMethod from .. import models as _models if TYPE_CHECKING: # pylint: disable=unused-import,ungrouped-imports from typing import Any, Callable, Dict, Generic, Iterable, List, Optional, TypeVar, Union T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] class DocumentTranslationOperations(object): """DocumentTranslationOperations operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~azure.ai.translation.document.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = _models def __init__(self, client, config, serializer, deserializer): self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config def _start_translation_initial( self, inputs, # type: List["_models.BatchRequest"] **kwargs # type: Any ): # type: (...) -> None cls = kwargs.pop('cls', None) # type: ClsType[None] error_map = { 404: ResourceNotFoundError, 409: ResourceExistsError, 400: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 401: lambda response: ClientAuthenticationError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) _body = _models.StartTranslationDetails(inputs=inputs) content_type = kwargs.pop("content_type", "application/json") accept = "application/json" # Construct URL url = self._start_translation_initial.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') body_content_kwargs = {} # type: Dict[str, Any] body_content = self._serialize.body(_body, 'StartTranslationDetails') body_content_kwargs['content'] = body_content request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [202]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) if cls: return cls(pipeline_response, None, response_headers) _start_translation_initial.metadata = {'url': '/batches'} # type: ignore def begin_start_translation( self, inputs, # type: List["_models.BatchRequest"] **kwargs # type: Any ): # type: (...) -> DocumentTranslationPoller[None] """Submit a document translation request to the Document Translation service. Use this API to submit a bulk (batch) translation request to the Document Translation service. Each request can contain multiple documents and must contain a source and destination container for each document. The prefix and suffix filter (if supplied) are used to filter folders. The prefix is applied to the subpath after the container name. Glossaries / Translation memory can be included in the request and are applied by the service when the document is translated. If the glossary is invalid or unreachable during translation, an error is indicated in the document status. If a file with the same name already exists at the destination, it will be overwritten. The targetUrl for each target language must be unique. :param inputs: The input list of documents or folders containing documents. :type inputs: list[~azure.ai.translation.document.models.BatchRequest] :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: By default, your polling method will be DocumentTranslationLROPollingMethod. Pass in False for this operation to not poll, or pass in your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of DocumentTranslationPoller that returns either None or the result of cls(response) :rtype: ~..._polling.DocumentTranslationPoller[None] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType[None] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._start_translation_initial( inputs=inputs, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): if cls: return cls(pipeline_response, None, {}) path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } if polling is True: polling_method = DocumentTranslationLROPollingMethod(lro_delay, lro_options={'final-state-via': 'location'}, path_format_arguments=path_format_arguments, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return DocumentTranslationPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return DocumentTranslationPoller(self._client, raw_result, get_long_running_output, polling_method) begin_start_translation.metadata = {'url': '/batches'} # type: ignore def get_translations_status( self, top=None, # type: Optional[int] skip=0, # type: Optional[int] maxpagesize=50, # type: Optional[int] ids=None, # type: Optional[List[str]] statuses=None, # type: Optional[List[str]] created_date_time_utc_start=None, # type: Optional[datetime.datetime] created_date_time_utc_end=None, # type: Optional[datetime.datetime] order_by=None, # type: Optional[List[str]] **kwargs # type: Any ): # type: (...) -> Iterable["_models.TranslationsStatus"] """Returns a list of batch requests submitted and the status for each request. Returns a list of batch requests submitted and the status for each request. This list only contains batch requests submitted by the user (based on the resource). If the number of requests exceeds our paging limit, server-side paging is used. Paginated responses indicate a partial result and include a continuation token in the response. The absence of a continuation token means that no additional pages are available. $top, $skip and $maxpagesize query parameters can be used to specify a number of results to return and an offset for the collection. $top indicates the total number of records the user wants to be returned across all pages. $skip indicates the number of records to skip from the list of batches based on the sorting method specified. By default, we sort by descending start time. $maxpagesize is the maximum items returned in a page. If more items are requested via $top (or $top is not specified and there are more items to be returned), @nextLink will contain the link to the next page. $orderBy query parameter can be used to sort the returned list (ex "$orderBy=createdDateTimeUtc asc" or "$orderBy=createdDateTimeUtc desc"). The default sorting is descending by createdDateTimeUtc. Some query parameters can be used to filter the returned list (ex: "status=Succeeded,Cancelled") will only return succeeded and cancelled operations. createdDateTimeUtcStart and createdDateTimeUtcEnd can be used combined or separately to specify a range of datetime to filter the returned list by. The supported filtering query parameters are (status, ids, createdDateTimeUtcStart, createdDateTimeUtcEnd). The server honors the values specified by the client. However, clients must be prepared to handle responses that contain a different page size or contain a continuation token. When both $top and $skip are included, the server should first apply $skip and then $top on the collection. Note: If the server can't honor $top and/or $skip, the server must return an error to the client informing about it instead of just ignoring the query options. This reduces the risk of the client making assumptions about the data returned. :param top: $top indicates the total number of records the user wants to be returned across all pages. Clients MAY use $top and $skip query parameters to specify a number of results to return and an offset into the collection. When both $top and $skip are given by a client, the server SHOULD first apply $skip and then $top on the collection. Note: If the server can't honor $top and/or $skip, the server MUST return an error to the client informing about it instead of just ignoring the query options. :type top: int :param skip: $skip indicates the number of records to skip from the list of records held by the server based on the sorting method specified. By default, we sort by descending start time. Clients MAY use $top and $skip query parameters to specify a number of results to return and an offset into the collection. When both $top and $skip are given by a client, the server SHOULD first apply $skip and then $top on the collection. Note: If the server can't honor $top and/or $skip, the server MUST return an error to the client informing about it instead of just ignoring the query options. :type skip: int :param maxpagesize: $maxpagesize is the maximum items returned in a page. If more items are requested via $top (or $top is not specified and there are more items to be returned), @nextLink will contain the link to the next page. Clients MAY request server-driven paging with a specific page size by specifying a $maxpagesize preference. The server SHOULD honor this preference if the specified page size is smaller than the server's default page size. :type maxpagesize: int :param ids: Ids to use in filtering. :type ids: list[str] :param statuses: Statuses to use in filtering. :type statuses: list[str] :param created_date_time_utc_start: the start datetime to get items after. :type created_date_time_utc_start: ~datetime.datetime :param created_date_time_utc_end: the end datetime to get items before. :type created_date_time_utc_end: ~datetime.datetime :param order_by: the sorting query for the collection (ex: 'CreatedDateTimeUtc asc', 'CreatedDateTimeUtc desc'). :type order_by: list[str] :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either TranslationsStatus or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.ai.translation.document.models.TranslationsStatus] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.TranslationsStatus"] error_map = { 404: ResourceNotFoundError, 409: ResourceExistsError, 400: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 401: lambda response: ClientAuthenticationError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.get_translations_status.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] if top is not None: query_parameters['$top'] = self._serialize.query("top", top, 'int', maximum=2147483647, minimum=0) if skip is not None: query_parameters['$skip'] = self._serialize.query("skip", skip, 'int', maximum=2147483647, minimum=0) if maxpagesize is not None: query_parameters['$maxpagesize'] = self._serialize.query("maxpagesize", maxpagesize, 'int', maximum=100, minimum=1) if ids is not None: query_parameters['ids'] = self._serialize.query("ids", ids, '[str]', div=',') if statuses is not None: query_parameters['statuses'] = self._serialize.query("statuses", statuses, '[str]', div=',') if created_date_time_utc_start is not None: query_parameters['createdDateTimeUtcStart'] = self._serialize.query("created_date_time_utc_start", created_date_time_utc_start, 'iso-8601') if created_date_time_utc_end is not None: query_parameters['createdDateTimeUtcEnd'] = self._serialize.query("created_date_time_utc_end", created_date_time_utc_end, 'iso-8601') if order_by is not None: query_parameters['$orderBy'] = self._serialize.query("order_by", order_by, '[str]', div=',') request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } url = self._client.format_url(url, **path_format_arguments) request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('TranslationsStatus', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) return pipeline_response return ItemPaged( get_next, extract_data ) get_translations_status.metadata = {'url': '/batches'} # type: ignore def get_document_status( self, id, # type: str document_id, # type: str **kwargs # type: Any ): # type: (...) -> "_models.DocumentStatus" """Returns the status for a specific document. Returns the translation status for a specific document based on the request Id and document Id. :param id: Format - uuid. The batch id. :type id: str :param document_id: Format - uuid. The document id. :type document_id: str :keyword callable cls: A custom type or function that will be passed the direct response :return: DocumentStatus, or the result of cls(response) :rtype: ~azure.ai.translation.document.models.DocumentStatus :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.DocumentStatus"] error_map = { 409: ResourceExistsError, 401: lambda response: ClientAuthenticationError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 404: lambda response: ResourceNotFoundError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" # Construct URL url = self.get_document_status.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), 'id': self._serialize.url("id", id, 'str'), 'documentId': self._serialize.url("document_id", document_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After')) response_headers['ETag']=self._deserialize('str', response.headers.get('ETag')) deserialized = self._deserialize('DocumentStatus', pipeline_response) if cls: return cls(pipeline_response, deserialized, response_headers) return deserialized get_document_status.metadata = {'url': '/batches/{id}/documents/{documentId}'} # type: ignore def get_translation_status( self, id, # type: str **kwargs # type: Any ): # type: (...) -> "_models.TranslationStatus" """Returns the status for a document translation request. Returns the status for a document translation request. The status includes the overall request status, as well as the status for documents that are being translated as part of that request. :param id: Format - uuid. The operation id. :type id: str :keyword callable cls: A custom type or function that will be passed the direct response :return: TranslationStatus, or the result of cls(response) :rtype: ~azure.ai.translation.document.models.TranslationStatus :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.TranslationStatus"] error_map = { 409: ResourceExistsError, 401: lambda response: ClientAuthenticationError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 404: lambda response: ResourceNotFoundError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" # Construct URL url = self.get_translation_status.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), 'id': self._serialize.url("id", id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After')) response_headers['ETag']=self._deserialize('str', response.headers.get('ETag')) deserialized = self._deserialize('TranslationStatus', pipeline_response) if cls: return cls(pipeline_response, deserialized, response_headers) return deserialized get_translation_status.metadata = {'url': '/batches/{id}'} # type: ignore def cancel_translation( self, id, # type: str **kwargs # type: Any ): # type: (...) -> "_models.TranslationStatus" """Cancel a currently processing or queued translation. Cancel a currently processing or queued translation. Cancel a currently processing or queued translation. A translation will not be cancelled if it is already completed or failed or cancelling. A bad request will be returned. All documents that have completed translation will not be cancelled and will be charged. All pending documents will be cancelled if possible. :param id: Format - uuid. The operation-id. :type id: str :keyword callable cls: A custom type or function that will be passed the direct response :return: TranslationStatus, or the result of cls(response) :rtype: ~azure.ai.translation.document.models.TranslationStatus :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.TranslationStatus"] error_map = { 409: ResourceExistsError, 401: lambda response: ClientAuthenticationError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 404: lambda response: ResourceNotFoundError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" # Construct URL url = self.cancel_translation.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), 'id': self._serialize.url("id", id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.delete(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) deserialized = self._deserialize('TranslationStatus', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized cancel_translation.metadata = {'url': '/batches/{id}'} # type: ignore def get_documents_status( self, id, # type: str top=None, # type: Optional[int] skip=0, # type: Optional[int] maxpagesize=50, # type: Optional[int] ids=None, # type: Optional[List[str]] statuses=None, # type: Optional[List[str]] created_date_time_utc_start=None, # type: Optional[datetime.datetime] created_date_time_utc_end=None, # type: Optional[datetime.datetime] order_by=None, # type: Optional[List[str]] **kwargs # type: Any ): # type: (...) -> Iterable["_models.DocumentsStatus"] """Returns the status for all documents in a batch document translation request. Returns the status for all documents in a batch document translation request. If the number of documents in the response exceeds our paging limit, server-side paging is used. Paginated responses indicate a partial result and include a continuation token in the response. The absence of a continuation token means that no additional pages are available. $top, $skip and $maxpagesize query parameters can be used to specify a number of results to return and an offset for the collection. $top indicates the total number of records the user wants to be returned across all pages. $skip indicates the number of records to skip from the list of document status held by the server based on the sorting method specified. By default, we sort by descending start time. $maxpagesize is the maximum items returned in a page. If more items are requested via $top (or $top is not specified and there are more items to be returned), @nextLink will contain the link to the next page. $orderBy query parameter can be used to sort the returned list (ex "$orderBy=createdDateTimeUtc asc" or "$orderBy=createdDateTimeUtc desc"). The default sorting is descending by createdDateTimeUtc. Some query parameters can be used to filter the returned list (ex: "status=Succeeded,Cancelled") will only return succeeded and cancelled documents. createdDateTimeUtcStart and createdDateTimeUtcEnd can be used combined or separately to specify a range of datetime to filter the returned list by. The supported filtering query parameters are (status, ids, createdDateTimeUtcStart, createdDateTimeUtcEnd). When both $top and $skip are included, the server should first apply $skip and then $top on the collection. Note: If the server can't honor $top and/or $skip, the server must return an error to the client informing about it instead of just ignoring the query options. This reduces the risk of the client making assumptions about the data returned. :param id: Format - uuid. The operation id. :type id: str :param top: $top indicates the total number of records the user wants to be returned across all pages. Clients MAY use $top and $skip query parameters to specify a number of results to return and an offset into the collection. When both $top and $skip are given by a client, the server SHOULD first apply $skip and then $top on the collection. Note: If the server can't honor $top and/or $skip, the server MUST return an error to the client informing about it instead of just ignoring the query options. :type top: int :param skip: $skip indicates the number of records to skip from the list of records held by the server based on the sorting method specified. By default, we sort by descending start time. Clients MAY use $top and $skip query parameters to specify a number of results to return and an offset into the collection. When both $top and $skip are given by a client, the server SHOULD first apply $skip and then $top on the collection. Note: If the server can't honor $top and/or $skip, the server MUST return an error to the client informing about it instead of just ignoring the query options. :type skip: int :param maxpagesize: $maxpagesize is the maximum items returned in a page. If more items are requested via $top (or $top is not specified and there are more items to be returned), @nextLink will contain the link to the next page. Clients MAY request server-driven paging with a specific page size by specifying a $maxpagesize preference. The server SHOULD honor this preference if the specified page size is smaller than the server's default page size. :type maxpagesize: int :param ids: Ids to use in filtering. :type ids: list[str] :param statuses: Statuses to use in filtering. :type statuses: list[str] :param created_date_time_utc_start: the start datetime to get items after. :type created_date_time_utc_start: ~datetime.datetime :param created_date_time_utc_end: the end datetime to get items before. :type created_date_time_utc_end: ~datetime.datetime :param order_by: the sorting query for the collection (ex: 'CreatedDateTimeUtc asc', 'CreatedDateTimeUtc desc'). :type order_by: list[str] :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either DocumentsStatus or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.ai.translation.document.models.DocumentsStatus] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.DocumentsStatus"] error_map = { 409: ResourceExistsError, 400: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 401: lambda response: ClientAuthenticationError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 404: lambda response: ResourceNotFoundError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.get_documents_status.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), 'id': self._serialize.url("id", id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] if top is not None: query_parameters['$top'] = self._serialize.query("top", top, 'int', maximum=2147483647, minimum=0) if skip is not None: query_parameters['$skip'] = self._serialize.query("skip", skip, 'int', maximum=2147483647, minimum=0) if maxpagesize is not None: query_parameters['$maxpagesize'] = self._serialize.query("maxpagesize", maxpagesize, 'int', maximum=100, minimum=1) if ids is not None: query_parameters['ids'] = self._serialize.query("ids", ids, '[str]', div=',') if statuses is not None: query_parameters['statuses'] = self._serialize.query("statuses", statuses, '[str]', div=',') if created_date_time_utc_start is not None: query_parameters['createdDateTimeUtcStart'] = self._serialize.query("created_date_time_utc_start", created_date_time_utc_start, 'iso-8601') if created_date_time_utc_end is not None: query_parameters['createdDateTimeUtcEnd'] = self._serialize.query("created_date_time_utc_end", created_date_time_utc_end, 'iso-8601') if order_by is not None: query_parameters['$orderBy'] = self._serialize.query("order_by", order_by, '[str]', div=',') request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), 'id': self._serialize.url("id", id, 'str'), } url = self._client.format_url(url, **path_format_arguments) request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('DocumentsStatus', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) return pipeline_response return ItemPaged( get_next, extract_data ) get_documents_status.metadata = {'url': '/batches/{id}/documents'} # type: ignore def get_supported_document_formats( self, **kwargs # type: Any ): # type: (...) -> "_models.SupportedFileFormats" """Returns a list of supported document formats. The list of supported document formats supported by the Document Translation service. The list includes the common file extension, as well as the content-type if using the upload API. :keyword callable cls: A custom type or function that will be passed the direct response :return: SupportedFileFormats, or the result of cls(response) :rtype: ~azure.ai.translation.document.models.SupportedFileFormats :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.SupportedFileFormats"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError, 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" # Construct URL url = self.get_supported_document_formats.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After')) deserialized = self._deserialize('SupportedFileFormats', pipeline_response) if cls: return cls(pipeline_response, deserialized, response_headers) return deserialized get_supported_document_formats.metadata = {'url': '/documents/formats'} # type: ignore def get_supported_glossary_formats( self, **kwargs # type: Any ): # type: (...) -> "_models.SupportedFileFormats" """Returns the list of supported glossary formats. The list of supported glossary formats supported by the Document Translation service. The list includes the common file extension used. :keyword callable cls: A custom type or function that will be passed the direct response :return: SupportedFileFormats, or the result of cls(response) :rtype: ~azure.ai.translation.document.models.SupportedFileFormats :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.SupportedFileFormats"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError, 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" # Construct URL url = self.get_supported_glossary_formats.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After')) deserialized = self._deserialize('SupportedFileFormats', pipeline_response) if cls: return cls(pipeline_response, deserialized, response_headers) return deserialized get_supported_glossary_formats.metadata = {'url': '/glossaries/formats'} # type: ignore def get_supported_storage_sources( self, **kwargs # type: Any ): # type: (...) -> "_models.SupportedStorageSources" """Returns a list of supported storage sources. Returns a list of storage sources/options supported by the Document Translation service. :keyword callable cls: A custom type or function that will be passed the direct response :return: SupportedStorageSources, or the result of cls(response) :rtype: ~azure.ai.translation.document.models.SupportedStorageSources :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.SupportedStorageSources"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError, 429: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 500: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), 503: lambda response: HttpResponseError(response=response, model=self._deserialize(_models.TranslationErrorResponse, response)), } error_map.update(kwargs.pop('error_map', {})) accept = "application/json" # Construct URL url = self.get_supported_storage_sources.metadata['url'] # type: ignore path_format_arguments = { 'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After')) deserialized = self._deserialize('SupportedStorageSources', pipeline_response) if cls: return cls(pipeline_response, deserialized, response_headers) return deserialized get_supported_storage_sources.metadata = {'url': '/storagesources'} # type: ignore

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0a2163f73e1e9add2305cdadd97357c958a8e4d3

35,214

py

Python

release-assistant/test/test_check/test_check_cli.py

openeuler-mirror/release-tools

655d08d6555f9a9211f982da6470be6b17eeafae

[ "MulanPSL-1.0" ]

1

2021-09-23T09:06:30.000Z

release-assistant/test/test_check/test_check_cli.py

openeuler-mirror/release-tools

655d08d6555f9a9211f982da6470be6b17eeafae

[ "MulanPSL-1.0" ]

null

release-assistant/test/test_check/test_check_cli.py

openeuler-mirror/release-tools

655d08d6555f9a9211f982da6470be6b17eeafae

[ "MulanPSL-1.0" ]

null

#!/usr/bin/python3 # ****************************************************************************** # Copyright (c) Huawei Technologies Co., Ltd. 2020-2020. All rights reserved. # licensed under the Mulan PSL v2. # You can use this software according to the terms and conditions of the Mulan PSL v2. # You may obtain a copy of Mulan PSL v2 at: # http://license.coscl.org.cn/MulanPSL2 # THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR # PURPOSE. # See the Mulan PSL v2 for more details. # ******************************************************************************/ # -*- coding:utf-8 -*- """ TestCheck """ import os from requests import RequestException from test.base.basetest import TestMixin from javcra.cli.commands.checkpart import CheckCommand MOCK_DATA_FILE = os.path.join(os.path.abspath(os.path.dirname(__file__)), "mock_data") EXPECT_DATA_FILE = os.path.join(os.path.abspath(os.path.dirname(__file__)), "expected_data") class TestCheck(TestMixin): """ class for test TestCheck """ cmd_class = CheckCommand def test_check_status_success(self): """ test check status success """ self.expect_str = """ [INFO] successfully update status in check part. [INFO] All issues are completed, the next step is sending repo to test platform. [INFO] successfully to send repo info. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_bugfix_r = self.make_need_content('mock_bugfix_issue.txt', MOCK_DATA_FILE) mock_install_r = self.make_need_content('mock_install_issue.txt', MOCK_DATA_FILE) mock_check_r = self.make_need_content('check_status_success.txt', MOCK_DATA_FILE) mock_post_data = self.make_need_content('mock_post_data.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) self.mock_requests_post(return_value=mock_post_data) self.mock_request( side_effect=[resp, resp, resp, resp, resp, mock_install_r, resp, resp, resp, mock_bugfix_r, mock_check_r, resp, resp, mock_install_r, mock_bugfix_r, resp, resp, resp, resp, mock_repo_list_data, resp]) self.assert_result() def test_check_status_failed(self): """ test check status failed """ self.expect_str = """ during the operation status, a failure occurred, and the cause of the error was failed to update status in check part. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_request( side_effect=[resp, resp, RequestException]) self.assert_result() def test_count_issue_status_failed(self): """ test count issue status failed """ self.expect_str = """ [INFO] successfully update status in check part. during the operation status, a failure occurred, and the cause of the error was the status of the issue is not all completed, please complete first """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') mock_bugfix_r = self.make_need_content('mock_bugfix_issue.txt', MOCK_DATA_FILE) mock_install_r = self.make_need_content('mock_install_issue.txt', MOCK_DATA_FILE) mock_abnormal_r = self.make_need_content('mock_abnormal_issue.txt', MOCK_DATA_FILE) mock_check_r = self.make_need_content('check_status_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, mock_install_r, resp, resp, resp, mock_bugfix_r, mock_check_r, resp, resp, RequestException, mock_abnormal_r]) self.assert_result() def test_send_repo_info_requests_post_failed(self): """ test send repo info requests post failed """ self.expect_str = """ [INFO] successfully update status in check part. [INFO] All issues are completed, the next step is sending repo to test platform. [ERROR] failed to send repo info. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_bugfix_r = self.make_need_content('mock_bugfix_issue.txt', MOCK_DATA_FILE) mock_install_r = self.make_need_content('mock_install_issue.txt', MOCK_DATA_FILE) mock_check_r = self.make_need_content('check_status_success.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) self.mock_requests_post(return_value=None) self.mock_request( side_effect=[resp, resp, resp, resp, resp, mock_install_r, resp, resp, resp, mock_bugfix_r, mock_check_r, resp, resp, mock_install_r, mock_bugfix_r, resp, resp, resp, resp, mock_repo_list_data, resp]) self.assert_result() def test_send_repo_info_request_exception(self): """ test send repo info test send repo info request exception """ self.expect_str = """ [INFO] successfully update status in check part. [INFO] All issues are completed, the next step is sending repo to test platform. [ERROR] failed to send repo info. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_bugfix_r = self.make_need_content('mock_bugfix_issue.txt', MOCK_DATA_FILE) mock_install_r = self.make_need_content('mock_install_issue.txt', MOCK_DATA_FILE) mock_check_r = self.make_need_content('check_status_success.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) self.mock_requests_post(side_effect=[RequestException]) self.mock_request( side_effect=[resp, resp, resp, resp, resp, mock_install_r, resp, resp, resp, mock_bugfix_r, mock_check_r, resp, resp, mock_install_r, mock_bugfix_r, resp, resp, resp, resp, mock_repo_list_data, resp]) self.assert_result() def test_send_repo_info_error_code_400(self): """ test send repo info error code 400 """ self.expect_str = """ [INFO] successfully update status in check part. [INFO] All issues are completed, the next step is sending repo to test platform. [ERROR] failed to send repo info. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_bugfix_r = self.make_need_content('mock_bugfix_issue.txt', MOCK_DATA_FILE) mock_install_r = self.make_need_content('mock_install_issue.txt', MOCK_DATA_FILE) mock_check_r = self.make_need_content('check_status_success.txt', MOCK_DATA_FILE) mock_post_data = self.make_need_content('mock_error_post_data.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) self.mock_requests_post(return_value=mock_post_data) self.mock_request( side_effect=[resp, resp, resp, resp, resp, mock_install_r, resp, resp, resp, mock_bugfix_r, mock_check_r, resp, resp, mock_install_r, mock_bugfix_r, resp, resp, resp, resp, mock_repo_list_data, resp]) self.assert_result() def test_send_repo_info_request_repo_url_failed(self): """ test send repo info requests post failed """ self.expect_str = """ [INFO] successfully update status in check part. [INFO] All issues are completed, the next step is sending repo to test platform. [ERROR] failed to send repo info. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_bugfix_r = self.make_need_content('mock_bugfix_issue.txt', MOCK_DATA_FILE) mock_install_r = self.make_need_content('mock_install_issue.txt', MOCK_DATA_FILE) mock_check_r = self.make_need_content('check_status_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, mock_install_r, resp, resp, resp, mock_bugfix_r, mock_check_r, resp, resp, mock_install_r, mock_bugfix_r, resp, resp, resp, resp, RequestException, resp]) self.assert_result() def test_send_repo_info_get_update_list_failed(self): """ test send repo info requests post failed """ self.expect_str = """ [INFO] successfully update status in check part. [INFO] All issues are completed, the next step is sending repo to test platform. [ERROR] failed to send repo info. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_bugfix_r = self.make_need_content('mock_bugfix_issue.txt', MOCK_DATA_FILE) mock_install_r = self.make_need_content('mock_install_issue.txt', MOCK_DATA_FILE) mock_check_r = self.make_need_content('check_status_success.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, mock_install_r, resp, resp, resp, mock_bugfix_r, mock_check_r, resp, resp, mock_install_r, mock_bugfix_r, resp, resp, resp, resp, mock_repo_list_data, RequestException]) self.assert_result() def test_block_has_no_related_issues(self): """ test block has no related issues """ self.expect_str = """ [INFO] successfully update status in check part. [INFO] All issues are completed, the next step is sending repo to test platform. [ERROR] failed to send repo info. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_no_related_issues_r = self.make_need_content('mock_no_related_issues.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, mock_no_related_issues_r, mock_no_related_issues_r, mock_no_related_issues_r, RequestException]) self.assert_result() def test_people_review_success(self): """ test people review success """ self.expect_str = """ [INFO] successfully operate test in check part. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=test", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') mock_comment_r = self.make_need_content('mock_issue_comment.txt', MOCK_DATA_FILE) self.mock_request(side_effect=[resp, resp, resp, mock_comment_r]) self.assert_result() def test_create_issue_comment_failed(self): """ test create issue comment failed """ self.expect_str = """ [ERROR] failed to operate test in check part. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=test", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.mock_request(side_effect=[resp, resp, resp, RequestException]) self.assert_result() def test_empty_related_personnel_information(self): """ test empty related personnel information """ self.expect_str = """ [ERROR] failed to operate test in check part. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=test", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') mock_empty_related_personnel_r = self.make_need_content('mock_empty_related_personnel.txt', MOCK_DATA_FILE) self.mock_request(side_effect=[resp, resp, mock_empty_related_personnel_r]) self.assert_result() def test_parameter_validation_failed(self): """ test parameter validation failed """ self.expect_str = """ Parameter validation failed """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", ""] self.assert_result() def test_no_personnel_authority(self): """test_no_personnel_authority""" self.expect_str = """ [ERROR] Failed to get the list of personnel permissions """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=status", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'mock_incorrect_issue.txt') self.mock_request(side_effect=[resp]) self.assert_result() def test_check_requires_success(self): """ test check requires success """ self.expect_str = self.read_file_content("requires_success.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] self.prepare_jenkins_data() self.prepare_obs_data() resp = self.make_expect_data(200, 'checkpart.txt') self.mock_subprocess_check_output( side_effect=[b"published-everything-src", b"published-everything-src", b"published-everything-src", b"published-everything-src", None, b"published-Epol-src", b"published-everything-src", b"published-everything-src", b"published-everything-src", b"published-everything-src", None, b"published-Epol-src", b"published-everything-src", b"published-everything-src", b"published-everything-src", b"published-everything-src", None, b"published-Epol-src"]) mock_add_repo_r = self.make_need_content('mock_add_repo_success.txt', MOCK_DATA_FILE) mock_exist_issues = self.make_need_content('exist_issues.txt', MOCK_DATA_FILE) mock_create_jenkins_comment = self.make_need_content('create_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) mock_create_install_jenkins_comment = self.make_need_content('create_install_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_build_jenkins_comment = self.make_need_content('create_build_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_build_issue = self.make_need_content('create_build_issue_success.txt', MOCK_DATA_FILE) mock_create_install_issue = self.make_need_content('create_install_issue_success.txt', MOCK_DATA_FILE) mock_checkpart_add_build = self.make_need_content('checkpart_add_build_success.txt', MOCK_DATA_FILE) mock_checkpart_add_install = self.make_need_content('checkpart_add_install_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, resp, resp, resp, resp, resp, mock_repo_list_data, mock_repo_list_data, mock_create_jenkins_comment, mock_create_jenkins_comment, resp, resp, resp, resp, mock_add_repo_r, mock_create_build_jenkins_comment, mock_create_install_jenkins_comment, mock_create_install_jenkins_comment, resp, resp, mock_exist_issues, mock_create_build_issue, resp, resp, mock_create_build_issue, mock_checkpart_add_build, resp, resp, mock_exist_issues, mock_create_install_issue, resp, resp, resp, mock_create_install_issue, mock_checkpart_add_install]) self.assert_result() def test_get_require_delete_file_failed(self): """ test get require and delete file failed """ self.expect_str = self.read_file_content("get_require_delete_file_failed.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] self.prepare_jenkins_data() self.prepare_obs_data(delete_status_code=400) resp = self.make_expect_data(200, 'checkpart.txt') self.mock_request(side_effect=[resp, resp, resp, resp, resp, resp]) self.assert_result() def test_get_repo_in_table_failed(self): """ test add repo in table failed """ self.expect_str = self.read_file_content("add_repo_in_table_failed.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] self.prepare_jenkins_data() self.prepare_obs_data() mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) self.mock_subprocess_check_output(return_value=b"published-everything-src") mock_create_jenkins_comment = self.make_need_content('create_jenkins_comments_success.txt', MOCK_DATA_FILE) resp = self.make_expect_data(200, 'checkpart.txt') self.mock_request( side_effect=[resp, resp, resp, resp, resp, resp, resp, resp, resp, resp, mock_repo_list_data, mock_create_jenkins_comment, resp, resp, resp, resp, RequestException]) self.assert_result() def test_create_jenkins_comment_and_build_comment_and_install_comment_failed(self): """ test create jenkins comment and build comment and install comment failed """ self.expect_str = self.read_file_content("create_comment_failed.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] self.prepare_jenkins_data() self.prepare_obs_data() resp = self.make_expect_data(200, 'checkpart.txt') mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) mock_exist_issues = self.make_need_content('exist_issues.txt', MOCK_DATA_FILE) mock_add_repo_r = self.make_need_content('mock_add_repo_success.txt', MOCK_DATA_FILE) mock_create_build_issue = self.make_need_content('create_build_issue_success.txt', MOCK_DATA_FILE) mock_create_install_issue = self.make_need_content('create_install_issue_success.txt', MOCK_DATA_FILE) mock_checkpart_add_build = self.make_need_content('checkpart_add_build_success.txt', MOCK_DATA_FILE) mock_checkpart_add_install = self.make_need_content('checkpart_add_install_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, resp, resp, resp, resp, resp, mock_repo_list_data, RequestException, resp, resp, resp, resp, mock_add_repo_r, RequestException, RequestException, resp, resp, mock_exist_issues, mock_create_build_issue, resp, resp, mock_create_build_issue, mock_checkpart_add_build, resp, resp, mock_exist_issues, mock_create_install_issue, resp, resp, mock_create_install_issue, mock_checkpart_add_install]) self.assert_result() def test_check_requires_epol_list_failed(self): """ test check requires epol list failed """ self.expect_str = self.read_file_content("check_requires_epol_list_failed.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] self.prepare_jenkins_data() self.prepare_obs_data() resp = self.make_expect_data(200, 'check_epol_list.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) self.mock_subprocess_check_output(return_value=b'published-Epol-src') mock_create_jenkins_comment = self.make_need_content('create_jenkins_comments_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, resp, resp, resp, resp, resp, mock_repo_list_data, mock_create_jenkins_comment, resp, resp, resp, resp, RequestException]) self.assert_result() def test_get_update_issue_branch_and_get_update_list_failed(self): """ test get update issue branch and get update list failed """ self.expect_str = """ during the operation requires, a failure occurred, and the cause of the error was failed to get branch name. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') branch_abnormal_r = self.make_need_content('check_branch_abnormal.txt', MOCK_DATA_FILE) self.mock_request(side_effect=[resp, resp, branch_abnormal_r, branch_abnormal_r, RequestException]) self.assert_result() def test_branch_name_is_none_and_get_update_list_failed(self): """ test branch name is none and get update list failed """ self.expect_str = """ during the operation requires, a failure occurred, and the cause of the error was failed to get branch name. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') branch_abnormal_r = self.make_need_content('branch_name_is_none.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, branch_abnormal_r, branch_abnormal_r, RequestException]) self.assert_result() def test_create_jenkins_comment_failed(self): """ failed to create jenkins comment """ self.expect_str = """ [ERROR] failed to get requires. already exists the repo url, then update the pkglist in repo. during the operation requires, a failure occurred, and the cause of the error was transfer standard rpm jenkins res: No comment information. The content is: []. """ self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.prepare_jenkins_data() self.prepare_obs_data() self.mock_jenkins_build_job(return_value=0) self.mock_request(return_value=resp) self.assert_result() def test_download_pkg_log_write_back_create_install_build_issue_failed(self): """ test download pkg log write back create install build issue failed """ self.expect_str = self.read_file_content("download_pkg_log_failed.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] self.prepare_jenkins_data() self.prepare_obs_data(get_objects_status_code=400) resp = self.make_expect_data(200, 'checkpart.txt') mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) mock_add_repo_r = self.make_need_content('mock_add_repo_success.txt', MOCK_DATA_FILE) mock_exist_issues = self.make_need_content('single_exist_issues.txt', MOCK_DATA_FILE) mock_create_jenkins_comment = self.make_need_content('create_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_install_jenkins_comment = self.make_need_content('create_install_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_build_jenkins_comment = self.make_need_content('create_build_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_issue_comment = self.make_need_content('mock_issue_comment.txt', MOCK_DATA_FILE) mock_create_build_issue = self.make_need_content('create_build_issue_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, resp, resp, resp, resp, resp, mock_repo_list_data, mock_create_jenkins_comment, resp, resp, resp, resp, mock_add_repo_r, mock_create_build_jenkins_comment, mock_create_install_jenkins_comment, resp, resp, mock_exist_issues, mock_issue_comment, mock_create_build_issue, RequestException, RequestException]) self.assert_result() def test_write_back_create_install_build_issue_failed(self): """ write_back_create_install_build_issue_failed """ self.expect_str = self.read_file_content("write_back_create_install_build_issue_failed.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] self.prepare_jenkins_data() self.prepare_obs_data() resp = self.make_expect_data(200, 'checkpart.txt') mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) mock_add_repo_r = self.make_need_content('mock_add_repo_success.txt', MOCK_DATA_FILE) mock_exist_issues = self.make_need_content('exist_issues.txt', MOCK_DATA_FILE) mock_create_jenkins_comment = self.make_need_content('create_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_install_jenkins_comment = self.make_need_content('create_install_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_build_jenkins_comment = self.make_need_content('create_build_jenkins_comments_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, resp, resp, resp, resp, resp, mock_repo_list_data, mock_create_jenkins_comment, resp, resp, resp, resp, mock_add_repo_r, mock_create_build_jenkins_comment, mock_create_install_jenkins_comment, resp, resp, mock_exist_issues, RequestException, RequestException]) self.assert_result() def test_write_back_operate_release_issue_failed(self): """ write_back_operate_release_issue_failed """ self.expect_str = self.read_file_content("write_back_operate_release_issue_failed.txt", folder=EXPECT_DATA_FILE, is_json=False) self.command_params = ["--giteeid=Mary", "--token=example", "--type=requires", "--jenkinsuser=mary", "--jenkinskey=marykey", "--ak=forexample", "--sk=forexample", "I40769"] resp = self.make_expect_data(200, 'checkpart.txt') self.prepare_jenkins_data() self.prepare_obs_data() mock_add_repo_r = self.make_need_content('mock_add_repo_success.txt', MOCK_DATA_FILE) mock_exist_issues = self.make_need_content('exist_issues.txt', MOCK_DATA_FILE) mock_repo_list_data = self.make_need_content('repo_list_data.txt', MOCK_DATA_FILE) mock_create_jenkins_comment = self.make_need_content('create_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_install_jenkins_comment = self.make_need_content('create_install_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_build_jenkins_comment = self.make_need_content('create_build_jenkins_comments_success.txt', MOCK_DATA_FILE) mock_create_build_issue = self.make_need_content('create_build_issue_success.txt', MOCK_DATA_FILE) mock_create_install_issue = self.make_need_content('create_install_issue_success.txt', MOCK_DATA_FILE) self.mock_request( side_effect=[resp, resp, resp, resp, resp, resp, resp, resp, resp, resp, mock_repo_list_data, mock_create_jenkins_comment, resp, resp, resp, resp, mock_add_repo_r, mock_create_build_jenkins_comment, mock_create_install_jenkins_comment, resp, resp, mock_exist_issues, mock_create_build_issue, resp, resp, mock_create_build_issue, RequestException, resp, resp, mock_exist_issues, mock_create_install_issue, resp, mock_create_install_issue, RequestException]) self.assert_result() def prepare_jenkins_data(self): """ prepare jenkins mock data """ self.mock_jenkins_build_job(return_value=2) self.mock_jenkins_get_queue_item( return_value=self.read_file_content("get_queue_item.json", folder=MOCK_DATA_FILE)) self.mock_jenkins_get_job_info( return_value=self.read_file_content("get_job_info.json", folder=MOCK_DATA_FILE)) self.mock_jenkins_get_build_info( return_value=self.read_file_content("get_build_info.json", folder=MOCK_DATA_FILE)) self.mock_jenkins_build_job_url( return_value=self.read_file_content("build_job_url.txt", folder=MOCK_DATA_FILE, is_json=False)) self.mock_jenkins_create_folder(return_value=True) self.mock_jenkins_job_exists(return_value=True) self.mock_jenkins_delete_job(return_value=True) self.mock_subprocess_check_output(return_value=b"published-everything-src") trigger_config = self.read_file_content('test_template_config_trigger.xml', folder=MOCK_DATA_FILE, is_json=False) aarch64_config = self.read_file_content('test_template_config_aarch64.xml', folder=MOCK_DATA_FILE, is_json=False) x86_64_config = self.read_file_content('test_template_config_x86.xml', folder=MOCK_DATA_FILE, is_json=False) self.mock_jenkins_get_job_config( side_effect=[trigger_config, aarch64_config, aarch64_config, aarch64_config, aarch64_config, aarch64_config, x86_64_config, x86_64_config, x86_64_config, x86_64_config, x86_64_config]) self.mock_jenkins_create_job(return_value=True) self.mock_jenkins_get_build_console_output( return_value=self.read_file_content('get_build_console_output.txt', folder=MOCK_DATA_FILE, is_json=False)) def prepare_obs_data(self, file_name='mock_obs_data.json', list_status_code=200, delete_status_code=200, get_objects_status_code=200): """ prepare obs mock data """ mock_obs_list_objects_r = self.make_need_obs_cloud_data(file_name, MOCK_DATA_FILE, list_status_code) mock_obs_delete_objects_r = self.make_need_obs_cloud_data(file_name, MOCK_DATA_FILE, delete_status_code) mock_getobjects_r = self.make_object_data(get_objects_status_code) self.mock_obs_cloud_get_objects(return_value=mock_getobjects_r) self.mock_obs_cloud_list_objects(return_value=mock_obs_list_objects_r) self.mock_obs_cloud_delete_object(return_value=mock_obs_delete_objects_r)

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0a3796e6b47cbd2e5ffba2e7cfa74b8c49642853

255,839

py

Python

openstack_controller/tests/test_end_to_end.py

someword/integrations-core

8861147fadf07500948a72fe2e1ef952ddcd9e2d

[ "BSD-3-Clause" ]

null

openstack_controller/tests/test_end_to_end.py

someword/integrations-core

8861147fadf07500948a72fe2e1ef952ddcd9e2d

[ "BSD-3-Clause" ]

null

openstack_controller/tests/test_end_to_end.py

someword/integrations-core

8861147fadf07500948a72fe2e1ef952ddcd9e2d

[ "BSD-3-Clause" ]

null

# (C) Datadog, Inc. 2018 # All rights reserved # Licensed under Simplified BSD License (see LICENSE) import mock import os import json from . import common from datadog_checks.openstack_controller import OpenStackControllerCheck def make_request_responses(url, header, params=None, timeout=None): if url == "http://10.0.2.15:5000/v3/projects": mock_path = "v3_projects.json" elif url == "http://10.0.2.15:9696": return elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1": return elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/limits": mock_path = "v2.1_4bfc1_limits" if params.get("tenant_id") == u'***************************d91a1': mock_path = "{}_d91a1.json".format(mock_path) elif params.get("tenant_id") == u'***************************4bfc1': mock_path = "{}_4bfc1.json".format(mock_path) elif params.get("tenant_id") == u'***************************73dbe': mock_path = "{}_73dbe.json".format(mock_path) elif params.get("tenant_id") == u'***************************3fb11': mock_path = "{}_3fb11.json".format(mock_path) elif params.get("tenant_id") == u'***************************44736': mock_path = "{}_44736.json".format(mock_path) elif params.get("tenant_id") == u'***************************147d1': mock_path = "{}_147d1.json".format(mock_path) elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/detail": mock_path = "v2.1_4bfc1_os-hypervisors_detail.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/1/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/2/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/8/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/9/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/10/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/11/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/12/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/13/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/14/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-hypervisors/15/uptime": mock_path = "v2.1_4bfc1_os-hypervisors_uptime.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/os-aggregates": mock_path = "v2.1_4bfc1_os-aggregates.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/detail": mock_path = "v2.1_4bfc1_servers_detail.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/flavors/detail": mock_path = "v2.1_4bfc1_flavors_detail.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/ff2f581c-5d03-4a27-a0ba-f102603fe38f/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_ff2f581c-5d03-4a27-a0ba-f102603fe38f_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/acb4197c-f54e-488e-a40a-1b7f59cc9117/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_acb4197c-f54e-488e-a40a-1b7f59cc9117_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/b3c8eee3-7e22-4a7c-9745-759073673cbe/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_b3c8eee3-7e22-4a7c-9745-759073673cbe_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/412c79b2-25f2-44d6-8e3b-be4baee11a7f/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_412c79b2-25f2-44d6-8e3b-be4baee11a7f_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/7e622c28-4b12-4a58-8ac2-4a2e854f84eb/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_7e622c28-4b12-4a58-8ac2-4a2e854f84eb_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/4ceb4c69-a332-4b9d-907b-e99635aae644/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_4ceb4c69-a332-4b9d-907b-e99635aae644_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/1cc21586-8d43-40ea-bdc9-6f54a79957b4/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_1cc21586-8d43-40ea-bdc9-6f54a79957b4_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/836f724f-0028-4dc0-b9bd-e0843d767ca2/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_836f724f-0028-4dc0-b9bd-e0843d767ca2_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/7eaa751c-1e37-4963-a836-0a28bc283a9a/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_7eaa751c-1e37-4963-a836-0a28bc283a9a_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/5357e70e-f12c-4bb7-85a2-b40d642a7e92/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_5357e70e-f12c-4bb7-85a2-b40d642a7e92_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/f2dd3f90-e738-4135-84d4-1a2d30d04929/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_f2dd3f90-e738-4135-84d4-1a2d30d04929_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/30888944-fb39-4590-9073-ef977ac1f039/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_30888944-fb39-4590-9073-ef977ac1f039_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/4d7cb923-788f-4b61-9061-abfc576ecc1a/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_4d7cb923-788f-4b61-9061-abfc576ecc1a_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/2e1ce152-b19d-4c4a-9cc7-0d150fa97a18/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_2e1ce152-b19d-4c4a-9cc7-0d150fa97a18_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/52561f29-e479-43d7-85de-944d29ef178d/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_52561f29-e479-43d7-85de-944d29ef178d_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/1b7a987f-c4fb-4b6b-aad9-3b461df2019d/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_1b7a987f-c4fb-4b6b-aad9-3b461df2019d_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/7324440d-915b-4e12-8b85-ec8c9a524d6c/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_7324440d-915b-4e12-8b85-ec8c9a524d6c_diagnostics.json" elif url == "http://10.0.2.15:8774/v2.1/***************************4bfc1/servers/57030997-f1b5-4f79-9429-8cb285318633/diagnostics": # noqa E501 mock_path = "v2.1_4bfc1_servers_57030997-f1b5-4f79-9429-8cb285318633_diagnostics.json" elif url == "http://10.0.2.15:9696/v2.0/networks": mock_path = "v2.0_networks.json" else: raise RuntimeError() mock_path = os.path.join(common.FIXTURES_DIR, mock_path) with open(mock_path, 'r') as f: return json.loads(f.read()) class MockHTTPResponse(object): def __init__(self, response_dict, headers): self.response_dict = response_dict self.headers = headers def json(self): return self.response_dict @mock.patch('datadog_checks.openstack_controller.api.AbstractApi._make_request', side_effect=make_request_responses) def test_scenario(make_request, aggregator): instance = common.MOCK_CONFIG["instances"][0] init_config = common.MOCK_CONFIG['init_config'] check = OpenStackControllerCheck('openstack_controller', init_config, {}, instances=[instance]) auth_tokens_response_path = os.path.join(common.FIXTURES_DIR, "auth_tokens_response.json") with open(auth_tokens_response_path, 'r') as f: auth_tokens_response = json.loads(f.read()) auth_tokens_response = MockHTTPResponse(response_dict=auth_tokens_response, headers={'X-Subject-Token': 'fake_token'}) auth_projects_response_path = os.path.join(common.FIXTURES_DIR, "auth_projects_response.json") with open(auth_projects_response_path, 'r') as f: auth_projects_response = json.loads(f.read()) with mock.patch('datadog_checks.openstack_controller.scopes.KeystoneApi.post_auth_token', return_value=auth_tokens_response): with mock.patch('datadog_checks.openstack_controller.scopes.KeystoneApi.get_auth_projects', return_value=auth_projects_response): check.check(common.MOCK_CONFIG['instances'][0]) aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.rx', value=17286.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.limits.max_image_meta', value=128.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_image_meta', value=128.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_image_meta', value=128.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_image_meta', value=128.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_image_meta', value=128.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_image_meta', value=128.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.tx', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.limits.max_personality', value=5.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality', value=10.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality', value=5.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality', value=5.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality', value=5.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality', value=5.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb', value=7982.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.tx_packets', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.tx', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.rx', value=16542.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.limits.total_security_groups_used', value=0.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_security_groups_used', value=1.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_security_groups_used', value=0.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_security_groups_used', value=1.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_security_groups_used', value=0.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_security_groups_used', value=0.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_cores', value=20.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_cores', value=40.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_cores', value=40.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_cores', value=40.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_cores', value=40.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_cores', value=40.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.rx', value=15564.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.limits.total_floating_ips_used', value=0.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_floating_ips_used', value=0.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_floating_ips_used', value=0.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_floating_ips_used', value=0.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_floating_ips_used', value=0.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_floating_ips_used', value=0.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_packets', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.rx_packets', value=170.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.rx', value=6306.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.current_workload', value=0.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_floating_ips', value=10.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_floating_ips', value=10.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_floating_ips', value=10.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_floating_ips', value=10.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_floating_ips', value=10.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_floating_ips', value=10.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.tx', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.limits.total_ram_used', value=0.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_ram_used', value=17408.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_ram_used', value=0.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_ram_used', value=1024.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_ram_used', value=0.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_ram_used', value=0.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.rx', value=15408.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.rx', value=5946.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.free_ram_mb', value=3886.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=2862.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=5934.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=2862.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=3886.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=5934.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=2862.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=3886.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=5934.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_ram_mb', value=2862.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.rx_packets', value=207.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.rx_packets', value=67.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=2422550000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=648410000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=6915020290000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=830250000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=3008600000000.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=741940000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=2406870000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=3193240000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=2616630000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=3608370000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=2124150000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=556800000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=4697690000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=3320700000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=1876660000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=2512910000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=567940000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.cpu0_time', value=2242410000000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.limits.max_personality_size', value=10240.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality_size', value=10240.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality_size', value=10240.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality_size', value=10240.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality_size', value=10240.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_personality_size', value=10240.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.rx_packets', value=67.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.rx_packets', value=193.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.limits.max_server_meta', value=128.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_server_meta', value=128.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_server_meta', value=128.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_server_meta', value=128.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_server_meta', value=128.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_server_meta', value=128.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.vcpus_used', value=4.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=6.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=0.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=6.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=4.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=0.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=6.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=4.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=0.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus_used', value=6.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.limits.max_total_keypairs', value=100.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_keypairs', value=100.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_keypairs', value=100.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_keypairs', value=100.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_keypairs', value=100.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_keypairs', value=100.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_groups', value=10.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_groups', value=10.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_groups', value=10.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_groups', value=10.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_groups', value=10.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_groups', value=10.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=2.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=3.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=0.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=3.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=2.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=0.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=3.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=2.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=0.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.running_vms', value=3.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.vcpus', value=8.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.limits.total_instances_used', value=0.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_instances_used', value=17.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_instances_used', value=0.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_instances_used', value=1.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_instances_used', value=0.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_instances_used', value=0.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.rx_packets', value=71.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.rx', value=15306.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.free_disk_gb', value=26.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=16.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=46.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=16.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=26.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=46.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=16.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=26.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=46.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.free_disk_gb', value=16.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=22.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=32.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=2.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=32.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=22.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=2.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=32.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=22.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=2.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb_used', value=32.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.memory', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.rx_packets', value=195.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.tx_packets', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.rx_packets', value=199.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.rx_packets', value=71.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.rx', value=5946.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.rx_packets', value=198.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.rx_packets', value=172.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.limits.total_cores_used', value=0.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_cores_used', value=34.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_cores_used', value=0.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_cores_used', value=2.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_cores_used', value=0.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.total_cores_used', value=0.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.rx', value=17826.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.vda_write', value=296960.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.vda_write', value=356352.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.vda_write', value=146432.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.vda_write', value=369664.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.vda_write', value=307200.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.vda_write', value=359424.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.vda_write', value=297984.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.vda_write', value=305152.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.vda_write', value=351232.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.vda_write', value=373760.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.vda_write', value=299008.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.vda_write', value=368640.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.vda_write', value=316416.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.vda_write', value=297984.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.vda_write', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.vda_write', value=105472.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.vda_write', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.vda_write', value=295936.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.rx', value=17466.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.rx', value=15228.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova', 'interface:tapab9b23ee-c1'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.rx_packets', value=66.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.rx', value=18522.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.rx_packets', value=197.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=878.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=1154.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=825.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=1161.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=878.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=1171.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=877.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=878.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=1156.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=1157.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=878.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=1128.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=875.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=878.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=424.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=574.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=424.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.vda_read_req', value=878.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.vda_read', value=20160512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.vda_read', value=20432896.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.vda_read', value=15403008.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.vda_read', value=20445184.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.vda_read', value=20160512.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.vda_read', value=20473856.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.vda_read', value=20164608.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.vda_read', value=20160512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.vda_read', value=20458496.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.vda_read', value=20431872.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.vda_read', value=20160512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.vda_read', value=20446208.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.vda_read', value=20153344.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.vda_read', value=20160512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.vda_read', value=13560832.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.vda_read', value=15155200.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.vda_read', value=13560832.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.vda_read', value=20160512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.memory_actual', value=1048576.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.vda_errors', value=-1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.local_gb', value=48.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.tx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.rx', value=6306.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.limits.max_total_instances', value=10.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_instances', value=20.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_instances', value=20.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_instances', value=20.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_instances', value=20.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_instances', value=20.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.rx', value=5844.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.rx_packets', value=154.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.disk_available_least', value=14.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=-2.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=38.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=2.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=14.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=37.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=3.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=13.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=3.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.disk_available_least', value=3.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.tx', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova', 'interface:tapf3e5d7a2-94'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.limits.max_total_ram_size', value=51200.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_ram_size', value=51200.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_ram_size', value=51200.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_ram_size', value=51200.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_ram_size', value=51200.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_total_ram_size', value=51200.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=84.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=105.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=32.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=106.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=82.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=105.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=85.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=84.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=108.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=107.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=82.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=105.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=89.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=84.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=28.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.vda_write_req', value=83.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.memory_rss', value=145116.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.memory_rss', value=160832.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.memory_rss', value=147684.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.memory_rss', value=148000.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.memory_rss', value=141980.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.memory_rss', value=161108.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.memory_rss', value=144728.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.memory_rss', value=142012.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.memory_rss', value=146064.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.memory_rss', value=145892.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.memory_rss', value=140812.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.memory_rss', value=149456.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.memory_rss', value=146460.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.memory_rss', value=142300.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.memory_rss', value=146188.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.memory_rss', value=144460.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.memory_rss', value=148752.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.memory_rss', value=143992.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.rx_packets', value=185.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.tx_packets', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova', 'interface:tapad123605-18'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.rx', value=13788.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.rx_packets', value=199.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.memory_mb_used', value=4096.0, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=5120.0, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=2048.0, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=5120.0, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=4096.0, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=2048.0, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=5120.0, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=4096.0, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=2048.0, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.memory_mb_used', value=5120.0, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova', 'interface:tape690927f-80'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.rx', value=17748.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.limits.max_security_group_rules', value=20.0, tags=['tenant_id:***************************4bfc1', 'project_name:service'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_group_rules', value=20.0, tags=['tenant_id:***************************3fb11', 'project_name:admin'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_group_rules', value=20.0, tags=['tenant_id:***************************d91a1', 'project_name:testProj2'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_group_rules', value=20.0, tags=['tenant_id:***************************73dbe', 'project_name:testProj1'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_group_rules', value=20.0, tags=['tenant_id:***************************147d1', 'project_name:12345'], hostname='') aggregator.assert_metric('openstack.nova.limits.max_security_group_rules', value=20.0, tags=['tenant_id:***************************44736', 'project_name:abcde'], hostname='') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova', 'interface:tap66a9ffb5-8f'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova', 'interface:tap9ac4ed56-d2'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.rx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova', 'interface:tapf86369c0-84'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova', 'interface:tap9bff9e73-2f'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova', 'interface:tap39a71720-01'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.rx', value=17826.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova', 'interface:tapc929a75b-94'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova', 'interface:tapcb21dae0-46'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.rx_packets', value=174.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova', 'interface:tap8880f875-12'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova', 'interface:tap73364860-8e'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.tx', value=1464.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova', 'interface:tap3fd8281c-97'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.rx', value=17646.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.rx_errors', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova', 'interface:tap702092ed-a5'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.tx_drop', value=0.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova', 'interface:tap69a50430-3b'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.rx_packets', value=171.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova', 'interface:tap56f02c54-da'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.tx_packets', value=9.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova', 'interface:tapb488fc1e-3e'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.flavor.disk', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.flavor.ram', value=512.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.flavor.vcpus', value=1.0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.flavor.ephemeral', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-1', 'availability_zone:nova'], hostname=u'7eaa751c-1e37-4963-a836-0a28bc283a9a') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-2', 'availability_zone:nova'], hostname=u'52561f29-e479-43d7-85de-944d29ef178d') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:ReadyServerOne', 'availability_zone:nova'], hostname=u'412c79b2-25f2-44d6-8e3b-be4baee11a7f') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-6', 'availability_zone:nova'], hostname=u'acb4197c-f54e-488e-a40a-1b7f59cc9117') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-4', 'availability_zone:nova'], hostname=u'7e622c28-4b12-4a58-8ac2-4a2e854f84eb') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute8.openstack.local', 'server_name:finalDestination-7', 'availability_zone:nova'], hostname=u'1cc21586-8d43-40ea-bdc9-6f54a79957b4') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:jenga', 'availability_zone:nova'], hostname=u'f2dd3f90-e738-4135-84d4-1a2d30d04929') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:moarserver-13', 'availability_zone:nova'], hostname=u'4ceb4c69-a332-4b9d-907b-e99635aae644') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:finalDestination-8', 'availability_zone:nova'], hostname=u'836f724f-0028-4dc0-b9bd-e0843d767ca2') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:HoneyIShrunkTheServer', 'availability_zone:nova'], hostname=u'1b7a987f-c4fb-4b6b-aad9-3b461df2019d') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute4.openstack.local', 'server_name:server_take_zero-2', 'availability_zone:nova'], hostname=u'ff2f581c-5d03-4a27-a0ba-f102603fe38f') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:finalDestination-1', 'availability_zone:nova'], hostname=u'4d7cb923-788f-4b61-9061-abfc576ecc1a') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute5.openstack.local', 'server_name:finalDestination-5', 'availability_zone:nova'], hostname=u'5357e70e-f12c-4bb7-85a2-b40d642a7e92') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute7.openstack.local', 'server_name:blacklist', 'availability_zone:nova'], hostname=u'7324440d-915b-4e12-8b85-ec8c9a524d6c') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute10.openstack.local', 'server_name:anotherServer', 'availability_zone:nova'], hostname=u'30888944-fb39-4590-9073-ef977ac1f039') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:testProj1', 'hypervisor:compute4.openstack.local', 'server_name:blacklistServer', 'availability_zone:nova'], hostname=u'57030997-f1b5-4f79-9429-8cb285318633') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute1.openstack.local', 'server_name:Rocky', 'availability_zone:nova'], hostname=u'2e1ce152-b19d-4c4a-9cc7-0d150fa97a18') aggregator.assert_metric('openstack.nova.server.flavor.swap', value=0, tags=['nova_managed_server', 'project_name:admin', 'hypervisor:compute2.openstack.local', 'server_name:jnrgjoner', 'availability_zone:nova'], hostname=u'b3c8eee3-7e22-4a7c-9745-759073673cbe') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.15', value=0.14, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.5', value=0.12, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute1.openstack.local', 'hypervisor_id:1', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute2.openstack.local', 'hypervisor_id:2', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute3.openstack.local', 'hypervisor_id:8', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute4.openstack.local', 'hypervisor_id:9', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute5.openstack.local', 'hypervisor_id:10', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute6.openstack.local', 'hypervisor_id:11', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute7.openstack.local', 'hypervisor_id:12', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute8.openstack.local', 'hypervisor_id:13', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute9.openstack.local', 'hypervisor_id:14', 'virt_type:QEMU', 'status:enabled'], hostname='') aggregator.assert_metric('openstack.nova.hypervisor_load.1', value=0.2, tags=['hypervisor:compute10.openstack.local', 'hypervisor_id:15', 'virt_type:QEMU', 'status:enabled'], hostname='') # Assert coverage for this check on this instance aggregator.assert_all_metrics_covered()

87.977648

148

0.497684

21,255

255,839

5.79713

0.022865

0.082196

0.112841

0.159003

0.98488

0.983006

0.981634

0.981147

0.980823

0.972131

0

0.093877

0.38328

255,839

2,907

149

88.007912

0.687066

0.001259

0

0.918459

0

0.011103

0.425861

0.323346

0

0.219639

1

0.001388

false

0

0.001735

0.000347

0.004858

0

null

0

1

0

1

0

null

0

7

0a481be93b5a7d5486f90957b6918dd93e559248

128

py

Python

python/testData/completion/heavyStarPropagation/lib/_pkg1/_pkg1_0/_pkg1_0_1/_pkg1_0_1_1/_pkg1_0_1_1_0/_mod1_0_1_1_0_1.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/completion/heavyStarPropagation/lib/_pkg1/_pkg1_0/_pkg1_0_1/_pkg1_0_1_1/_pkg1_0_1_1_0/_mod1_0_1_1_0_1.py

Cyril-lamirand/intellij-community

60ab6c61b82fc761dd68363eca7d9d69663cfa39

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/completion/heavyStarPropagation/lib/_pkg1/_pkg1_0/_pkg1_0_1/_pkg1_0_1_1/_pkg1_0_1_1_0/_mod1_0_1_1_0_1.py

Cyril-lamirand/intellij-community

60ab6c61b82fc761dd68363eca7d9d69663cfa39

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

name1_0_1_1_0_1_0 = None name1_0_1_1_0_1_1 = None name1_0_1_1_0_1_2 = None name1_0_1_1_0_1_3 = None name1_0_1_1_0_1_4 = None

14.222222

24

0.820313

40

128

1.875

0.175

0.266667

0.24

0.533333

0.88

0.746667

0

0.318182

0.140625

128

9

25

14.222222

0.363636

0

1

0

false

0

1

null

1

0

1

0

1

0

1

0

null

0

10

6a6f87e359ff6590124f9683585aedd0def68b75

183

py

Python

ummon/metrics/base.py

matherm/ummon3

08476d21ce17cc95180525d48202a1690dfc8a08

[ "BSD-3-Clause" ]

1

2022-02-10T06:47:13.000Z

ummon/metrics/base.py

matherm/ummon3

08476d21ce17cc95180525d48202a1690dfc8a08

[ "BSD-3-Clause" ]

null

ummon/metrics/base.py

matherm/ummon3

08476d21ce17cc95180525d48202a1690dfc8a08

[ "BSD-3-Clause" ]

null

class OfflineMetric(): def __repr__(self): return str(self.__class__.__name__) class OnlineMetric(): def __repr__(self): return str(self.__class__.__name__)

20.333333

43

0.68306

20

183

5.05

0.45

0.138614

0.217822

0.336634

0.653465

0

0.20765

183

9

44

20.333333

0.696552

0

0.666667

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

7

6ae1f5e203040ce419050c671b8c4912128cc2e9

5,802

py

Python

tools.py

tjards/reynolds_escort

5565ece406dcf6ed91f96efed21436c7e5edf444

[ "MIT" ]

null

tools.py

tjards/reynolds_escort

5565ece406dcf6ed91f96efed21436c7e5edf444

[ "MIT" ]

null

tools.py

tjards/reynolds_escort

5565ece406dcf6ed91f96efed21436c7e5edf444

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Dec 28 20:29:59 2020 This file defines some useful planar constraints @author: tjards """ import numpy as np def centroid(points): length = points.shape[0] sum_x = np.sum(points[:, 0]) sum_y = np.sum(points[:, 1]) sum_z = np.sum(points[:, 2]) centroid = np.array((sum_x/length, sum_y/length, sum_z/length), ndmin = 2) return centroid.transpose() def buildWall(wType, pos): if wType == 'horizontal': # define 3 points on the plane (this one is horizontal) wallp1 = np.array([0, 0, pos]) wallp2 = np.array([5, 10, pos]) wallp3 = np.array([20, 30, pos+0.05]) # define two vectors on the plane v1 = wallp3 - wallp1 v2 = wallp2 - wallp1 # compute vector normal to the plane wallcp = np.cross(v1, v2) walla, wallb, wallc = wallcp walld = np.dot(wallcp, wallp3) walls = np.zeros((6,1)) walls[0:3,0] = np.array(wallcp, ndmin=2)#.transpose() walls[3:6,0] = np.array(wallp1, ndmin=2)#.transpose() walls_plots = np.zeros((4,1)) walls_plots[:,0] = np.array([walla, wallb, wallc, walld]) if wType == 'vertical1': # define 3 points on the plane (this one is vertical wallp1 = np.array([0, pos, 0]) wallp2 = np.array([5, pos, 10]) wallp3 = np.array([20,pos+0.05, 30]) # define two vectors on the plane v1 = wallp3 - wallp1 v2 = wallp2 - wallp1 # compute vector normal to the plane wallcp = np.cross(v1, v2) walla, wallb, wallc = wallcp walld = np.dot(wallcp, wallp3) walls = np.zeros((6,1)) walls[0:3,0] = np.array(wallcp, ndmin=2)#.transpose() walls[3:6,0] = np.array(wallp1, ndmin=2)#.transpose() walls_plots = np.zeros((4,1)) walls_plots[:,0] = np.array([walla, wallb, wallc, walld]) if wType == 'vertical2': # define 3 points on the plane (this one is vertical wallp1 = np.array([pos, 0, 0]) wallp2 = np.array([pos, 5, 10]) wallp3 = np.array([pos+0.05, 20, 30]) # define two vectors on the plane v1 = wallp3 - wallp1 v2 = wallp2 - wallp1 # compute vector normal to the plane wallcp = np.cross(v1, v2) walla, wallb, wallc = wallcp walld = np.dot(wallcp, wallp3) walls = np.zeros((6,1)) walls[0:3,0] = np.array(wallcp, ndmin=2)#.transpose() walls[3:6,0] = np.array(wallp1, ndmin=2)#.transpose() walls_plots = np.zeros((4,1)) walls_plots[:,0] = np.array([walla, wallb, wallc, walld]) if wType == 'diagonal1a': # define 3 points on the plane (this one is vertical wallp1 = np.array([0, pos, 0]) wallp2 = np.array([0, pos+5, 5]) wallp3 = np.array([-5,pos+5, 5]) # define two vectors on the plane v1 = wallp3 - wallp1 v2 = wallp2 - wallp1 # compute vector normal to the plane wallcp = np.cross(v1, v2) walla, wallb, wallc = wallcp walld = np.dot(wallcp, wallp3) walls = np.zeros((6,1)) walls[0:3,0] = np.array(wallcp, ndmin=2)#.transpose() walls[3:6,0] = np.array(wallp1, ndmin=2)#.transpose() walls_plots = np.zeros((4,1)) walls_plots[:,0] = np.array([walla, wallb, wallc, walld]) if wType == 'diagonal1b': # define 3 points on the plane (this one is vertical wallp1 = np.array([0, pos, 0]) wallp2 = np.array([0, pos-5, 5]) wallp3 = np.array([-5,pos-5, 5]) # define two vectors on the plane v1 = wallp3 - wallp1 v2 = wallp2 - wallp1 # compute vector normal to the plane wallcp = np.cross(v1, v2) walla, wallb, wallc = wallcp walld = np.dot(wallcp, wallp3) walls = np.zeros((6,1)) walls[0:3,0] = np.array(wallcp, ndmin=2)#.transpose() walls[3:6,0] = np.array(wallp1, ndmin=2)#.transpose() walls_plots = np.zeros((4,1)) walls_plots[:,0] = np.array([walla, wallb, wallc, walld]) if wType == 'diagonal2a': # define 3 points on the plane (this one is vertical wallp1 = np.array([pos, 0, 0]) wallp2 = np.array([pos-5, 0, 5]) wallp3 = np.array([pos-5, -5, 5]) # define two vectors on the plane v1 = wallp3 - wallp1 v2 = wallp2 - wallp1 # compute vector normal to the plane wallcp = np.cross(v1, v2) walla, wallb, wallc = wallcp walld = np.dot(wallcp, wallp3) walls = np.zeros((6,1)) walls[0:3,0] = np.array(wallcp, ndmin=2)#.transpose() walls[3:6,0] = np.array(wallp1, ndmin=2)#.transpose() walls_plots = np.zeros((4,1)) walls_plots[:,0] = np.array([walla, wallb, wallc, walld]) if wType == 'diagonal2b': # define 3 points on the plane (this one is vertical wallp1 = np.array([pos, 0, 0]) wallp2 = np.array([pos+5, 0, 5]) wallp3 = np.array([pos+5, -5, 5]) # define two vectors on the plane v1 = wallp3 - wallp1 v2 = wallp2 - wallp1 # compute vector normal to the plane wallcp = np.cross(v1, v2) walla, wallb, wallc = wallcp walld = np.dot(wallcp, wallp3) walls = np.zeros((6,1)) walls[0:3,0] = np.array(wallcp, ndmin=2)#.transpose() walls[3:6,0] = np.array(wallp1, ndmin=2)#.transpose() walls_plots = np.zeros((4,1)) walls_plots[:,0] = np.array([walla, wallb, wallc, walld]) return walls, walls_plots

36.955414

78

0.542227

814

5,802

3.839066

0.110565

0.09632

0.05376

0.0896

0.8352

0.82496

0

0.070926

0.314719

5,802

157

79

36.955414

0.71504

0.197001

0

0.703704

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1

0.018519

false

0

0.009259

0

0.046296

0

null

0

1

0

1

0

null

0

7

6ae5444598de0cd0bf77a515197cd9ecf63b9e9d

177

py

Python

test_example2.py

greatfirsty/hellopython

f12aacf36b8f208d6c5622ffd6b4c1927f37b45a

[ "Apache-2.0" ]

1

2019-05-04T01:25:43.000Z

test_example2.py

greatfirsty/hellopython

f12aacf36b8f208d6c5622ffd6b4c1927f37b45a

[ "Apache-2.0" ]

null

test_example2.py

greatfirsty/hellopython

f12aacf36b8f208d6c5622ffd6b4c1927f37b45a

[ "Apache-2.0" ]

null

class Count: def __init__(self,a,b): self.a = a self.b = b def add(self): return self.a+self.b def sub(self): return self.a+self.b

16.090909

28

0.514124

29

177

3

0.344828

0.229885

0.206897

0.344828

0.45977

0

0.361582

177

10

29

17.7

0.769912

0

0.25

0

1

0.375

false

0

0.25

0.75

0

1

0

null

1

0

null

0

1

0

1

0

7

0a838c56ac7908fcc24d218501cb9bc672529b9e

180,129

py

Python

hl7apy/v2_5/groups.py

ryoung29/hl7apy

e83029ca68f31581b95f85f280c7b4cc81c0f6b2

[ "MIT" ]

163

2015-01-26T22:52:59.000Z

2022-03-27T18:24:22.000Z

hl7apy/v2_5/groups.py

ryoung29/hl7apy

e83029ca68f31581b95f85f280c7b4cc81c0f6b2

[ "MIT" ]

87

2015-01-12T14:49:15.000Z

2022-02-04T22:35:41.000Z

hl7apy/v2_5/groups.py

ryoung29/hl7apy

e83029ca68f31581b95f85f280c7b4cc81c0f6b2

[ "MIT" ]

88

2015-03-20T18:56:03.000Z

2022-03-16T17:49:00.000Z

from hl7apy.utils import iteritems from .segments import SEGMENTS GROUPS = { 'ADR_A19_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADR_A19_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADR_A19_QUERY_RESPONSE': ('sequence', (['EVN', SEGMENTS['EVN'], (0, 1), 'SEG'], ['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'], ['NK1', SEGMENTS['NK1'], (0, -1), 'SEG'], ['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'], ['DB1', SEGMENTS['DB1'], (0, -1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['DRG', SEGMENTS['DRG'], (0, 1), 'SEG'], ['ADR_A19_PROCEDURE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['ADR_A19_INSURANCE', None, (0, -1), 'GRP'], ['ACC', SEGMENTS['ACC'], (0, 1), 'SEG'], ['UB1', SEGMENTS['UB1'], (0, 1), 'SEG'], ['UB2', SEGMENTS['UB2'], (0, 1), 'SEG'],)), 'ADT_A01_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A01_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A03_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A03_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A05_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A05_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A06_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A06_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A16_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A16_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'ADT_A39_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['MRG', SEGMENTS['MRG'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'],)), 'ADT_A43_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['MRG', SEGMENTS['MRG'], (1, 1), 'SEG'],)), 'ADT_A45_MERGE_INFO': ('sequence', (['MRG', SEGMENTS['MRG'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'],)), 'BAR_P01_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'BAR_P01_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'BAR_P01_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'], ['DB1', SEGMENTS['DB1'], (0, -1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['DRG', SEGMENTS['DRG'], (0, 1), 'SEG'], ['BAR_P01_PROCEDURE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['NK1', SEGMENTS['NK1'], (0, -1), 'SEG'], ['BAR_P01_INSURANCE', None, (0, -1), 'GRP'], ['ACC', SEGMENTS['ACC'], (0, 1), 'SEG'], ['UB1', SEGMENTS['UB1'], (0, 1), 'SEG'], ['UB2', SEGMENTS['UB2'], (0, 1), 'SEG'],)), 'BAR_P02_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['DB1', SEGMENTS['DB1'], (0, -1), 'SEG'],)), 'BAR_P05_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'BAR_P05_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'BAR_P05_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'], ['DB1', SEGMENTS['DB1'], (0, -1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['DRG', SEGMENTS['DRG'], (0, 1), 'SEG'], ['BAR_P05_PROCEDURE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['NK1', SEGMENTS['NK1'], (0, -1), 'SEG'], ['BAR_P05_INSURANCE', None, (0, -1), 'GRP'], ['ACC', SEGMENTS['ACC'], (0, 1), 'SEG'], ['UB1', SEGMENTS['UB1'], (0, 1), 'SEG'], ['UB2', SEGMENTS['UB2'], (0, 1), 'SEG'], ['ABS', SEGMENTS['ABS'], (0, 1), 'SEG'], ['BLC', SEGMENTS['BLC'], (0, -1), 'SEG'], ['RMI', SEGMENTS['RMI'], (0, 1), 'SEG'],)), 'BAR_P06_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'],)), 'BAR_P10_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['GP2', SEGMENTS['GP2'], (0, 1), 'SEG'],)), 'BAR_P12_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'BPS_O29_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['BPS_O29_TIMING', None, (0, -1), 'GRP'], ['BPO', SEGMENTS['BPO'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['BPS_O29_PRODUCT', None, (0, -1), 'GRP'],)), 'BPS_O29_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['BPS_O29_PATIENT_VISIT', None, (0, 1), 'GRP'],)), 'BPS_O29_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'BPS_O29_PRODUCT': ('sequence', (['BPX', SEGMENTS['BPX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'BPS_O29_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'BRP_O30_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['BRP_O30_TIMING', None, (0, -1), 'GRP'], ['BPO', SEGMENTS['BPO'], (0, 1), 'SEG'], ['BPX', SEGMENTS['BPX'], (0, -1), 'SEG'],)), 'BRP_O30_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['BRP_O30_ORDER', None, (0, -1), 'GRP'],)), 'BRP_O30_RESPONSE': ('sequence', (['BRP_O30_PATIENT', None, (0, 1), 'GRP'],)), 'BRP_O30_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'BRT_O32_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['BRT_O32_TIMING', None, (0, -1), 'GRP'], ['BPO', SEGMENTS['BPO'], (0, 1), 'SEG'], ['BTX', SEGMENTS['BTX'], (0, -1), 'SEG'],)), 'BRT_O32_RESPONSE': ('sequence', (['PID', SEGMENTS['PID'], (0, 1), 'SEG'], ['BRT_O32_ORDER', None, (0, -1), 'GRP'],)), 'BRT_O32_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'BTS_O31_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['BTS_O31_TIMING', None, (0, -1), 'GRP'], ['BPO', SEGMENTS['BPO'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['BTS_O31_PRODUCT_STATUS', None, (0, -1), 'GRP'],)), 'BTS_O31_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['BTS_O31_PATIENT_VISIT', None, (0, 1), 'GRP'],)), 'BTS_O31_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'BTS_O31_PRODUCT_STATUS': ('sequence', (['BTX', SEGMENTS['BTX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'BTS_O31_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'CRM_C01_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['CSR', SEGMENTS['CSR'], (1, 1), 'SEG'], ['CSP', SEGMENTS['CSP'], (0, -1), 'SEG'],)), 'CSU_C09_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CSU_C09_VISIT', None, (0, 1), 'GRP'], ['CSR', SEGMENTS['CSR'], (1, 1), 'SEG'], ['CSU_C09_STUDY_PHASE', None, (1, -1), 'GRP'],)), 'CSU_C09_RX_ADMIN': ('sequence', (['RXA', SEGMENTS['RXA'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, 1), 'SEG'],)), 'CSU_C09_STUDY_OBSERVATION': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['CSU_C09_TIMING_QTY', None, (0, -1), 'GRP'], ['OBX', SEGMENTS['OBX'], (1, -1), 'SEG'],)), 'CSU_C09_STUDY_PHARM': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['CSU_C09_RX_ADMIN', None, (1, -1), 'GRP'],)), 'CSU_C09_STUDY_PHASE': ('sequence', (['CSP', SEGMENTS['CSP'], (0, 1), 'SEG'], ['CSU_C09_STUDY_SCHEDULE', None, (1, -1), 'GRP'],)), 'CSU_C09_STUDY_SCHEDULE': ('sequence', (['CSS', SEGMENTS['CSS'], (0, 1), 'SEG'], ['CSU_C09_STUDY_OBSERVATION', None, (1, -1), 'GRP'], ['CSU_C09_STUDY_PHARM', None, (1, -1), 'GRP'],)), 'CSU_C09_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'CSU_C09_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'DFT_P03_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['DFT_P03_TIMING_QUANTITY', None, (0, -1), 'GRP'], ['DFT_P03_ORDER', None, (0, 1), 'GRP'], ['DFT_P03_OBSERVATION', None, (0, -1), 'GRP'],)), 'DFT_P03_FINANCIAL': ('sequence', (['FT1', SEGMENTS['FT1'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, 1), 'SEG'], ['DFT_P03_FINANCIAL_PROCEDURE', None, (0, -1), 'GRP'], ['DFT_P03_FINANCIAL_COMMON_ORDER', None, (0, -1), 'GRP'],)), 'DFT_P03_FINANCIAL_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['DFT_P03_FINANCIAL_TIMING_QUANTITY', None, (0, -1), 'GRP'], ['DFT_P03_FINANCIAL_ORDER', None, (0, 1), 'GRP'], ['DFT_P03_FINANCIAL_OBSERVATION', None, (0, -1), 'GRP'],)), 'DFT_P03_FINANCIAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P03_FINANCIAL_ORDER': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P03_FINANCIAL_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'DFT_P03_FINANCIAL_TIMING_QUANTITY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'DFT_P03_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'DFT_P03_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P03_ORDER': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P03_TIMING_QUANTITY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'DFT_P11_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['DFT_P11_TIMING_QUANTITY', None, (0, -1), 'GRP'], ['DFT_P11_ORDER', None, (0, 1), 'GRP'], ['DFT_P11_OBSERVATION', None, (0, -1), 'GRP'],)), 'DFT_P11_FINANCIAL': ('sequence', (['FT1', SEGMENTS['FT1'], (1, 1), 'SEG'], ['DFT_P11_FINANCIAL_PROCEDURE', None, (0, -1), 'GRP'], ['DFT_P11_FINANCIAL_COMMON_ORDER', None, (0, -1), 'GRP'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['DRG', SEGMENTS['DRG'], (0, 1), 'SEG'], ['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['DFT_P11_FINANCIAL_INSURANCE', None, (0, -1), 'GRP'],)), 'DFT_P11_FINANCIAL_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['DFT_P11_FINANCIAL_TIMING_QUANTITY', None, (0, -1), 'GRP'], ['DFT_P11_FINANCIAL_ORDER', None, (0, 1), 'GRP'], ['DFT_P11_FINANCIAL_OBSERVATION', None, (0, -1), 'GRP'],)), 'DFT_P11_FINANCIAL_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'DFT_P11_FINANCIAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P11_FINANCIAL_ORDER': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P11_FINANCIAL_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'DFT_P11_FINANCIAL_TIMING_QUANTITY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'DFT_P11_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, -1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'DFT_P11_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P11_ORDER': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'DFT_P11_TIMING_QUANTITY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'DOC_T12_RESULT': ('sequence', (['EVN', SEGMENTS['EVN'], (0, 1), 'SEG'], ['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['TXA', SEGMENTS['TXA'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'],)), 'EAC_U07_COMMAND': ('sequence', (['ECD', SEGMENTS['ECD'], (1, 1), 'SEG'], ['TQ1', SEGMENTS['TQ1'], (0, 1), 'SEG'], ['EAC_U07_SPECIMEN_CONTAINER', None, (0, 1), 'GRP'], ['CNS', SEGMENTS['CNS'], (0, 1), 'SEG'],)), 'EAC_U07_SPECIMEN_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['SPM', SEGMENTS['SPM'], (0, -1), 'SEG'],)), 'EAN_U09_NOTIFICATION': ('sequence', (['NDS', SEGMENTS['NDS'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, 1), 'SEG'],)), 'EAR_U08_COMMAND_RESPONSE': ('sequence', (['ECD', SEGMENTS['ECD'], (1, 1), 'SEG'], ['EAR_U08_SPECIMEN_CONTAINER', None, (0, 1), 'GRP'], ['ECR', SEGMENTS['ECR'], (1, 1), 'SEG'],)), 'EAR_U08_SPECIMEN_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['SPM', SEGMENTS['SPM'], (0, -1), 'SEG'],)), 'MDM_T01_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['MDM_T01_TIMING', None, (0, -1), 'GRP'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'MDM_T01_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'MDM_T02_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['MDM_T02_TIMING', None, (0, -1), 'GRP'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'MDM_T02_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'MDM_T02_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'MFN_M01_MF': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (0, 1), 'SEG'],)), 'MFN_M02_MF_STAFF': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['STF', SEGMENTS['STF'], (1, 1), 'SEG'], ['PRA', SEGMENTS['PRA'], (0, -1), 'SEG'], ['ORG', SEGMENTS['ORG'], (0, -1), 'SEG'], ['AFF', SEGMENTS['AFF'], (0, -1), 'SEG'], ['LAN', SEGMENTS['LAN'], (0, -1), 'SEG'], ['EDU', SEGMENTS['EDU'], (0, -1), 'SEG'], ['CER', SEGMENTS['CER'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'MFN_M03_MF_TEST': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['OM1', SEGMENTS['OM1'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'MFN_M04_MF_CDM': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['CDM', SEGMENTS['CDM'], (1, 1), 'SEG'], ['PRC', SEGMENTS['PRC'], (0, -1), 'SEG'],)), 'MFN_M05_MF_LOCATION': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['LOC', SEGMENTS['LOC'], (1, 1), 'SEG'], ['LCH', SEGMENTS['LCH'], (0, -1), 'SEG'], ['LRL', SEGMENTS['LRL'], (0, -1), 'SEG'], ['MFN_M05_MF_LOC_DEPT', None, (1, -1), 'GRP'],)), 'MFN_M05_MF_LOC_DEPT': ('sequence', (['LDP', SEGMENTS['LDP'], (1, 1), 'SEG'], ['LCH', SEGMENTS['LCH'], (0, -1), 'SEG'], ['LCC', SEGMENTS['LCC'], (0, -1), 'SEG'],)), 'MFN_M06_MF_CLIN_STUDY': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['CM0', SEGMENTS['CM0'], (1, 1), 'SEG'], ['MFN_M06_MF_PHASE_SCHED_DETAIL', None, (0, -1), 'GRP'],)), 'MFN_M06_MF_PHASE_SCHED_DETAIL': ('sequence', (['CM1', SEGMENTS['CM1'], (1, 1), 'SEG'], ['CM2', SEGMENTS['CM2'], (0, -1), 'SEG'],)), 'MFN_M07_MF_CLIN_STUDY_SCHED': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['CM0', SEGMENTS['CM0'], (1, 1), 'SEG'], ['CM2', SEGMENTS['CM2'], (0, -1), 'SEG'],)), 'MFN_M08_MF_TEST_NUMERIC': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['OM1', SEGMENTS['OM1'], (1, 1), 'SEG'], ['OM2', SEGMENTS['OM2'], (0, 1), 'SEG'], ['OM3', SEGMENTS['OM3'], (0, 1), 'SEG'], ['OM4', SEGMENTS['OM4'], (0, 1), 'SEG'],)), 'MFN_M09_MF_TEST_CATEGORICAL': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['OM1', SEGMENTS['OM1'], (1, 1), 'SEG'], ['MFN_M09_MF_TEST_CAT_DETAIL', None, (0, 1), 'GRP'],)), 'MFN_M09_MF_TEST_CAT_DETAIL': ('sequence', (['OM3', SEGMENTS['OM3'], (1, 1), 'SEG'], ['OM4', SEGMENTS['OM4'], (0, -1), 'SEG'],)), 'MFN_M10_MF_TEST_BATTERIES': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['OM1', SEGMENTS['OM1'], (1, 1), 'SEG'], ['MFN_M10_MF_TEST_BATT_DETAIL', None, (0, 1), 'GRP'],)), 'MFN_M10_MF_TEST_BATT_DETAIL': ('sequence', (['OM5', SEGMENTS['OM5'], (1, 1), 'SEG'], ['OM4', SEGMENTS['OM4'], (0, -1), 'SEG'],)), 'MFN_M11_MF_TEST_CALCULATED': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['OM1', SEGMENTS['OM1'], (1, 1), 'SEG'], ['MFN_M11_MF_TEST_CALC_DETAIL', None, (0, 1), 'GRP'],)), 'MFN_M11_MF_TEST_CALC_DETAIL': ('sequence', (['OM6', SEGMENTS['OM6'], (1, 1), 'SEG'], ['OM2', SEGMENTS['OM2'], (1, 1), 'SEG'],)), 'MFN_M12_MF_OBS_ATTRIBUTES': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['OM1', SEGMENTS['OM1'], (1, 1), 'SEG'], ['OM7', SEGMENTS['OM7'], (0, 1), 'SEG'],)), 'MFN_M15_MF_INV_ITEM': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['IIM', SEGMENTS['IIM'], (1, 1), 'SEG'],)), 'MFN_ZNN': ('sequence', (['MSH', SEGMENTS['MSH'], (1, 1), 'SEG'], ['SFT', SEGMENTS['SFT'], (0, -1), 'SEG'], ['MFI', SEGMENTS['MFI'], (1, 1), 'SEG'], ['MFN_ZNN_MF_SITE_DEFINED', None, (1, -1), 'GRP'],)), 'MFN_ZNN_MF_SITE_DEFINED': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'MFR_M01_MF_QUERY': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (0, 1), 'SEG'],)), 'MFR_M04_MF_QUERY': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['CDM', SEGMENTS['CDM'], (1, 1), 'SEG'], ['LCH', SEGMENTS['LCH'], (0, -1), 'SEG'], ['PRC', SEGMENTS['PRC'], (0, -1), 'SEG'],)), 'MFR_M05_MF_QUERY': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['LOC', SEGMENTS['LOC'], (1, 1), 'SEG'], ['LCH', SEGMENTS['LCH'], (0, -1), 'SEG'], ['LRL', SEGMENTS['LRL'], (0, -1), 'SEG'], ['LDP', SEGMENTS['LDP'], (1, -1), 'SEG'], ['LCH', SEGMENTS['LCH'], (0, -1), 'SEG'], ['LCC', SEGMENTS['LCC'], (0, -1), 'SEG'],)), 'MFR_M06_MF_QUERY': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['CM0', SEGMENTS['CM0'], (1, 1), 'SEG'], ['CM1', SEGMENTS['CM1'], (0, -1), 'SEG'], ['CM2', SEGMENTS['CM2'], (0, -1), 'SEG'],)), 'MFR_M07_MF_QUERY': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['CM0', SEGMENTS['CM0'], (1, 1), 'SEG'], ['CM2', SEGMENTS['CM2'], (0, -1), 'SEG'],)), 'NMD_N02_APP_STATS': ('sequence', (['NST', SEGMENTS['NST'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'NMD_N02_APP_STATUS': ('sequence', (['NSC', SEGMENTS['NSC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'NMD_N02_CLOCK': ('sequence', (['NCK', SEGMENTS['NCK'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'NMD_N02_CLOCK_AND_STATS_WITH_NOTES': ('sequence', (['NMD_N02_CLOCK', None, (0, 1), 'GRP'], ['NMD_N02_APP_STATS', None, (0, 1), 'GRP'], ['NMD_N02_APP_STATUS', None, (0, 1), 'GRP'],)), 'NMQ_N01_CLOCK_AND_STATISTICS': ('sequence', (['NCK', SEGMENTS['NCK'], (0, 1), 'SEG'], ['NST', SEGMENTS['NST'], (0, 1), 'SEG'], ['NSC', SEGMENTS['NSC'], (0, 1), 'SEG'],)), 'NMQ_N01_QRY_WITH_DETAIL': ('sequence', (['QRD', SEGMENTS['QRD'], (1, 1), 'SEG'], ['QRF', SEGMENTS['QRF'], (0, 1), 'SEG'],)), 'NMR_N01_CLOCK_AND_STATS_WITH_NOTES_ALT': ('sequence', (['NCK', SEGMENTS['NCK'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['NST', SEGMENTS['NST'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['NSC', SEGMENTS['NSC'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OMB_O27_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'OMB_O27_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OMB_O27_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['OMB_O27_TIMING', None, (0, -1), 'GRP'], ['BPO', SEGMENTS['BPO'], (1, 1), 'SEG'], ['SPM', SEGMENTS['SPM'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['OMB_O27_OBSERVATION', None, (0, -1), 'GRP'], ['FT1', SEGMENTS['FT1'], (0, -1), 'SEG'], ['BLG', SEGMENTS['BLG'], (0, 1), 'SEG'],)), 'OMB_O27_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OMB_O27_PATIENT_VISIT', None, (0, 1), 'GRP'], ['OMB_O27_INSURANCE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, 1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'],)), 'OMB_O27_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OMB_O27_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OMD_O03_DIET': ('sequence', (['ODS', SEGMENTS['ODS'], (1, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OMD_O03_OBSERVATION', None, (0, -1), 'GRP'],)), 'OMD_O03_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'OMD_O03_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OMD_O03_ORDER_DIET': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['OMD_O03_TIMING_DIET', None, (0, -1), 'GRP'], ['OMD_O03_DIET', None, (0, 1), 'GRP'],)), 'OMD_O03_ORDER_TRAY': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['OMD_O03_TIMING_TRAY', None, (0, -1), 'GRP'], ['ODT', SEGMENTS['ODT'], (1, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OMD_O03_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OMD_O03_PATIENT_VISIT', None, (0, 1), 'GRP'], ['OMD_O03_INSURANCE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, 1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'],)), 'OMD_O03_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OMD_O03_TIMING_DIET': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OMD_O03_TIMING_TRAY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OMG_O19_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'],)), 'OMG_O19_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'OMG_O19_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OMG_O19_OBSERVATION_PRIOR': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OMG_O19_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['OMG_O19_TIMING', None, (0, -1), 'GRP'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['OMG_O19_OBSERVATION', None, (0, -1), 'GRP'], ['OMG_O19_SPECIMEN', None, (0, -1), 'GRP'], ['OMG_O19_PRIOR_RESULT', None, (0, -1), 'GRP'], ['FT1', SEGMENTS['FT1'], (0, -1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'], ['BLG', SEGMENTS['BLG'], (0, 1), 'SEG'],)), 'OMG_O19_ORDER_PRIOR': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['OMG_O19_TIMING_PRIOR', None, (0, -1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'], ['OMG_O19_OBSERVATION_PRIOR', None, 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1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OML_O33_OBSERVATION_REQUEST': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['TCD', SEGMENTS['TCD'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['OML_O33_OBSERVATION', None, (0, -1), 'GRP'], ['OML_O33_PRIOR_RESULT', None, (0, -1), 'GRP'],)), 'OML_O33_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['OML_O33_TIMING', None, (0, -1), 'GRP'], ['OML_O33_OBSERVATION_REQUEST', None, (0, 1), 'GRP'], ['FT1', SEGMENTS['FT1'], (0, -1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'], ['BLG', SEGMENTS['BLG'], (0, 1), 'SEG'],)), 'OML_O33_ORDER_PRIOR': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OML_O33_TIMING_PRIOR', None, (0, -1), 'GRP'], ['OML_O33_OBSERVATION_PRIOR', None, (1, -1), 'GRP'],)), 'OML_O33_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], 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SEGMENTS['OBX'], (0, -1), 'SEG'], ['SAC', SEGMENTS['SAC'], (0, -1), 'SEG'], ['OML_O33_ORDER', None, (1, -1), 'GRP'],)), 'OML_O33_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OML_O33_TIMING_PRIOR': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OML_O35_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'OML_O35_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['TCD', SEGMENTS['TCD'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OML_O35_OBSERVATION_PRIOR': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OML_O35_OBSERVATION_REQUEST': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['TCD', SEGMENTS['TCD'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['DG1', 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SEGMENTS['GT1'], (0, 1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'],)), 'OML_O35_PATIENT_PRIOR': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'],)), 'OML_O35_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OML_O35_PATIENT_VISIT_PRIOR': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OML_O35_PRIOR_RESULT': ('sequence', (['OML_O35_PATIENT_PRIOR', None, (0, 1), 'GRP'], ['OML_O35_PATIENT_VISIT_PRIOR', None, (0, 1), 'GRP'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['OML_O35_ORDER_PRIOR', None, (1, -1), 'GRP'],)), 'OML_O35_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['OML_O35_SPECIMEN_CONTAINER', None, (1, -1), 'GRP'],)), 'OML_O35_SPECIMEN_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['OML_O35_ORDER', None, (1, -1), 'GRP'],)), 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'OMS_O05_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OMS_O05_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['OMS_O05_TIMING', None, (0, -1), 'GRP'], ['RQD', SEGMENTS['RQD'], (1, 1), 'SEG'], ['RQ1', SEGMENTS['RQ1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OMS_O05_OBSERVATION', None, (0, -1), 'GRP'], ['BLG', SEGMENTS['BLG'], (0, 1), 'SEG'],)), 'OMS_O05_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OMS_O05_PATIENT_VISIT', None, (0, 1), 'GRP'], ['OMS_O05_INSURANCE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, 1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'],)), 'OMS_O05_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OMS_O05_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORB_O28_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORB_O28_TIMING', None, (0, -1), 'GRP'], ['BPO', SEGMENTS['BPO'], (0, 1), 'SEG'],)), 'ORB_O28_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['ORB_O28_ORDER', None, (0, -1), 'GRP'],)), 'ORB_O28_RESPONSE': ('sequence', (['ORB_O28_PATIENT', None, (0, 1), 'GRP'],)), 'ORB_O28_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORD_O04_ORDER_DIET': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORD_O04_TIMING_DIET', None, (0, -1), 'GRP'], ['ODS', SEGMENTS['ODS'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORD_O04_ORDER_TRAY': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORD_O04_TIMING_TRAY', None, (0, -1), 'GRP'], ['ODT', SEGMENTS['ODT'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORD_O04_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORD_O04_RESPONSE': ('sequence', (['ORD_O04_PATIENT', None, (0, 1), 'GRP'], ['ORD_O04_ORDER_DIET', None, (1, -1), 'GRP'], ['ORD_O04_ORDER_TRAY', None, (0, -1), 'GRP'],)), 'ORD_O04_TIMING_DIET': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORD_O04_TIMING_TRAY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORF_R04_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORF_R04_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['ORF_R04_TIMING_QTY', None, (0, -1), 'GRP'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'], ['ORF_R04_OBSERVATION', None, (1, -1), 'GRP'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'ORF_R04_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORF_R04_QUERY_RESPONSE': ('sequence', (['ORF_R04_PATIENT', None, (0, 1), 'GRP'], ['ORF_R04_ORDER', None, (1, -1), 'GRP'],)), 'ORF_R04_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORG_O20_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORG_O20_TIMING', None, (0, -1), 'GRP'], ['OBR', SEGMENTS['OBR'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'], ['ORG_O20_SPECIMEN', None, (0, -1), 'GRP'],)), 'ORG_O20_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORG_O20_RESPONSE': ('sequence', (['ORG_O20_PATIENT', None, (0, 1), 'GRP'], ['ORG_O20_ORDER', None, (1, -1), 'GRP'],)), 'ORG_O20_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['SAC', SEGMENTS['SAC'], (0, -1), 'SEG'],)), 'ORG_O20_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORI_O24_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORI_O24_TIMING', None, (0, -1), 'GRP'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['IPC', SEGMENTS['IPC'], (1, -1), 'SEG'],)), 'ORI_O24_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORI_O24_RESPONSE': ('sequence', (['ORI_O24_PATIENT', None, (0, 1), 'GRP'], ['ORI_O24_ORDER', None, (1, -1), 'GRP'],)), 'ORI_O24_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORL_O22_OBSERVATION_REQUEST': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ORL_O22_SPECIMEN', None, (0, -1), 'GRP'],)), 'ORL_O22_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORL_O22_TIMING', None, (0, -1), 'GRP'], ['ORL_O22_OBSERVATION_REQUEST', None, (0, 1), 'GRP'],)), 'ORL_O22_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['ORL_O22_ORDER', None, (0, -1), 'GRP'],)), 'ORL_O22_RESPONSE': ('sequence', (['ORL_O22_PATIENT', None, (0, 1), 'GRP'],)), 'ORL_O22_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['SAC', SEGMENTS['SAC'], (0, -1), 'SEG'],)), 'ORL_O22_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORL_O34_OBSERVATION_REQUEST': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ORL_O34_SPMSAC_SUPPGRP2', None, (0, -1), 'GRP'],)), 'ORL_O34_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORL_O34_TIMING', None, (0, -1), 'GRP'], ['ORL_O34_OBSERVATION_REQUEST', None, (0, 1), 'GRP'],)), 'ORL_O34_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['ORL_O34_SPECIMEN', None, (1, -1), 'GRP'],)), 'ORL_O34_RESPONSE': ('sequence', (['ORL_O34_PATIENT', None, (0, 1), 'GRP'],)), 'ORL_O34_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['SAC', SEGMENTS['SAC'], (0, -1), 'SEG'], ['ORL_O34_ORDER', None, (0, -1), 'GRP'],)), 'ORL_O34_SPMSAC_SUPPGRP2': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['SAC', SEGMENTS['SAC'], (0, -1), 'SEG'],)), 'ORL_O34_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORL_O36_OBSERVATION_REQUEST': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'],)), 'ORL_O36_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORL_O36_TIMING', None, (0, -1), 'GRP'], ['ORL_O36_OBSERVATION_REQUEST', None, (0, 1), 'GRP'],)), 'ORL_O36_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['ORL_O36_SPECIMEN', None, (1, -1), 'GRP'],)), 'ORL_O36_RESPONSE': ('sequence', (['ORL_O36_PATIENT', None, (0, 1), 'GRP'],)), 'ORL_O36_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['ORL_O36_SPECIMEN_CONTAINER', None, (1, -1), 'GRP'],)), 'ORL_O36_SPECIMEN_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['ORL_O36_ORDER', None, (0, -1), 'GRP'],)), 'ORL_O36_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORM_O01_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'ORM_O01_OBRRQDRQ1RXOODSODT_SUPPGRP': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['RQD', SEGMENTS['RQD'], (1, 1), 'SEG'], ['RQ1', SEGMENTS['RQ1'], (1, 1), 'SEG'], ['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['ODS', SEGMENTS['ODS'], (1, 1), 'SEG'], ['ODT', SEGMENTS['ODT'], (1, 1), 'SEG'],)), 'ORM_O01_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORM_O01_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORM_O01_ORDER_DETAIL', None, (0, 1), 'GRP'], ['FT1', SEGMENTS['FT1'], (0, -1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'], ['BLG', SEGMENTS['BLG'], (0, 1), 'SEG'],)), 'ORM_O01_ORDER_DETAIL': ('sequence', (['ORM_O01_OBRRQDRQ1RXOODSODT_SUPPGRP', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'], ['ORM_O01_OBSERVATION', None, (0, -1), 'GRP'],)), 'ORM_O01_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['ORM_O01_PATIENT_VISIT', None, (0, 1), 'GRP'], ['ORM_O01_INSURANCE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, 1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'],)), 'ORM_O01_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'ORN_O08_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORN_O08_TIMING', None, (0, -1), 'GRP'], ['RQD', SEGMENTS['RQD'], (1, 1), 'SEG'], ['RQ1', SEGMENTS['RQ1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORN_O08_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORN_O08_RESPONSE': ('sequence', (['ORN_O08_PATIENT', None, (0, 1), 'GRP'], ['ORN_O08_ORDER', None, (1, -1), 'GRP'],)), 'ORN_O08_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORP_O10_COMPONENT': ('sequence', (['RXC', SEGMENTS['RXC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORP_O10_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORP_O10_TIMING', None, (0, -1), 'GRP'], ['ORP_O10_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'ORP_O10_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['ORP_O10_COMPONENT', None, (0, -1), 'GRP'],)), 'ORP_O10_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORP_O10_RESPONSE': ('sequence', (['ORP_O10_PATIENT', None, (0, 1), 'GRP'], ['ORP_O10_ORDER', None, (1, -1), 'GRP'],)), 'ORP_O10_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORR_O02_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['RQD', SEGMENTS['RQD'], (1, 1), 'SEG'], ['RQ1', SEGMENTS['RQ1'], (1, 1), 'SEG'], ['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['ODS', SEGMENTS['ODS'], (1, 1), 'SEG'], ['ODT', SEGMENTS['ODT'], (1, 1), 'SEG'],)), 'ORR_O02_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORR_O02_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'ORR_O02_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORR_O02_RESPONSE': ('sequence', (['ORR_O02_PATIENT', None, (0, 1), 'GRP'], ['ORR_O02_ORDER', None, (1, -1), 'GRP'],)), 'ORS_O06_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['ORS_O06_TIMING', None, (0, -1), 'GRP'], ['RQD', SEGMENTS['RQD'], (1, 1), 'SEG'], ['RQ1', SEGMENTS['RQ1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORS_O06_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORS_O06_RESPONSE': ('sequence', (['ORS_O06_PATIENT', None, (0, 1), 'GRP'], ['ORS_O06_ORDER', None, (1, -1), 'GRP'],)), 'ORS_O06_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORU_R01_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORU_R01_ORDER_OBSERVATION': ('sequence', (['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['ORU_R01_TIMING_QTY', None, (0, -1), 'GRP'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'], ['ORU_R01_OBSERVATION', None, (0, -1), 'GRP'], ['FT1', SEGMENTS['FT1'], (0, -1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'], ['ORU_R01_SPECIMEN', None, (0, -1), 'GRP'],)), 'ORU_R01_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['NK1', SEGMENTS['NK1'], (0, -1), 'SEG'], ['ORU_R01_VISIT', None, (0, 1), 'GRP'],)), 'ORU_R01_PATIENT_RESULT': ('sequence', (['ORU_R01_PATIENT', None, (0, 1), 'GRP'], ['ORU_R01_ORDER_OBSERVATION', None, (1, -1), 'GRP'],)), 'ORU_R01_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'],)), 'ORU_R01_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORU_R01_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'ORU_R30_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'ORU_R30_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ORU_R30_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OSR_Q06_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['RQD', SEGMENTS['RQD'], (1, 1), 'SEG'], ['RQ1', SEGMENTS['RQ1'], (1, 1), 'SEG'], ['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['ODS', SEGMENTS['ODS'], (1, 1), 'SEG'], ['ODT', SEGMENTS['ODT'], (1, 1), 'SEG'],)), 'OSR_Q06_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['OSR_Q06_TIMING', None, (0, -1), 'GRP'], ['OSR_Q06_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'OSR_Q06_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OSR_Q06_RESPONSE': ('sequence', (['OSR_Q06_PATIENT', None, (0, 1), 'GRP'], ['OSR_Q06_ORDER', None, (1, -1), 'GRP'],)), 'OSR_Q06_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OUL_R21_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['SID', SEGMENTS['SID'], (0, 1), 'SEG'],)), 'OUL_R21_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['TCD', SEGMENTS['TCD'], (0, 1), 'SEG'], ['SID', SEGMENTS['SID'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R21_ORDER_OBSERVATION': ('sequence', (['OUL_R21_CONTAINER', None, (0, 1), 'GRP'], ['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OUL_R21_TIMING_QTY', None, (0, -1), 'GRP'], ['OUL_R21_OBSERVATION', None, (1, -1), 'GRP'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'OUL_R21_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R21_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OUL_R21_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OUL_R22_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['INV', SEGMENTS['INV'], (0, 1), 'SEG'],)), 'OUL_R22_ORDER': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OUL_R22_TIMING_QTY', None, (0, -1), 'GRP'], ['OUL_R22_RESULT', None, (0, -1), 'GRP'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'OUL_R22_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R22_RESULT': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['TCD', SEGMENTS['TCD'], (0, 1), 'SEG'], ['SID', SEGMENTS['SID'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R22_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['OUL_R22_CONTAINER', None, (0, -1), 'GRP'], ['OUL_R22_ORDER', None, (1, -1), 'GRP'],)), 'OUL_R22_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OUL_R22_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OUL_R23_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['INV', SEGMENTS['INV'], (0, 1), 'SEG'], ['OUL_R23_ORDER', None, (1, -1), 'GRP'],)), 'OUL_R23_ORDER': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OUL_R23_TIMING_QTY', None, (0, -1), 'GRP'], ['OUL_R23_RESULT', None, (0, -1), 'GRP'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'OUL_R23_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R23_RESULT': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['TCD', SEGMENTS['TCD'], (0, 1), 'SEG'], ['SID', SEGMENTS['SID'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R23_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['OUL_R23_CONTAINER', None, (1, -1), 'GRP'],)), 'OUL_R23_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OUL_R23_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'OUL_R24_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['INV', SEGMENTS['INV'], (0, 1), 'SEG'],)), 'OUL_R24_ORDER': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ORC', SEGMENTS['ORC'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['OUL_R24_TIMING_QTY', None, (0, -1), 'GRP'], ['OUL_R24_SPECIMEN', None, (0, -1), 'GRP'], ['OUL_R24_RESULT', None, (0, -1), 'GRP'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'OUL_R24_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R24_RESULT': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['TCD', SEGMENTS['TCD'], (0, 1), 'SEG'], ['SID', SEGMENTS['SID'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'OUL_R24_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['OUL_R24_CONTAINER', None, (0, -1), 'GRP'],)), 'OUL_R24_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'OUL_R24_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PEX_P07_ASSOCIATED_PERSON': ('sequence', (['NK1', SEGMENTS['NK1'], (1, 1), 'SEG'], ['PEX_P07_ASSOCIATED_RX_ORDER', None, (0, 1), 'GRP'], ['PEX_P07_ASSOCIATED_RX_ADMIN', None, (0, -1), 'GRP'], ['PRB', SEGMENTS['PRB'], (0, -1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'],)), 'PEX_P07_ASSOCIATED_RX_ADMIN': ('sequence', (['RXA', SEGMENTS['RXA'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (0, 1), 'SEG'],)), 'PEX_P07_ASSOCIATED_RX_ORDER': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['PEX_P07_NK1_TIMING_QTY', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (0, -1), 'SEG'],)), 'PEX_P07_EXPERIENCE': ('sequence', (['PES', SEGMENTS['PES'], (1, 1), 'SEG'], ['PEX_P07_PEX_OBSERVATION', None, (1, -1), 'GRP'],)), 'PEX_P07_NK1_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'PEX_P07_PEX_CAUSE': ('sequence', (['PCR', SEGMENTS['PCR'], (1, 1), 'SEG'], ['PEX_P07_RX_ORDER', None, (0, 1), 'GRP'], ['PEX_P07_RX_ADMINISTRATION', None, (0, -1), 'GRP'], ['PRB', SEGMENTS['PRB'], (0, -1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['PEX_P07_ASSOCIATED_PERSON', None, (0, 1), 'GRP'], ['PEX_P07_STUDY', None, (0, -1), 'GRP'],)), 'PEX_P07_PEX_OBSERVATION': ('sequence', (['PEO', SEGMENTS['PEO'], (1, 1), 'SEG'], ['PEX_P07_PEX_CAUSE', None, (1, -1), 'GRP'],)), 'PEX_P07_RX_ADMINISTRATION': ('sequence', (['RXA', SEGMENTS['RXA'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (0, 1), 'SEG'],)), 'PEX_P07_RX_ORDER': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['PEX_P07_TIMING_QTY', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (0, -1), 'SEG'],)), 'PEX_P07_STUDY': ('sequence', (['CSR', SEGMENTS['CSR'], (1, 1), 'SEG'], ['CSP', SEGMENTS['CSP'], (0, -1), 'SEG'],)), 'PEX_P07_TIMING_QTY': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'PEX_P07_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PGL_PC6_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PGL_PC6_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PGL_PC6_GOAL_ROLE', None, (0, -1), 'GRP'], ['PGL_PC6_PATHWAY', None, (0, -1), 'GRP'], ['PGL_PC6_OBSERVATION', None, (0, -1), 'GRP'], ['PGL_PC6_PROBLEM', None, (0, -1), 'GRP'], ['PGL_PC6_ORDER', None, (0, -1), 'GRP'],)), 'PGL_PC6_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PGL_PC6_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PGL_PC6_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PGL_PC6_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PGL_PC6_ORDER_DETAIL': ('sequence', (['PGL_PC6_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PGL_PC6_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PGL_PC6_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PGL_PC6_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PGL_PC6_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PGL_PC6_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PGL_PC6_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PGL_PC6_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'],)), 'PGL_PC6_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PGL_PC6_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PMU_B07_CERTIFICATE': ('sequence', (['CER', SEGMENTS['CER'], (1, 1), 'SEG'], ['ROL', SEGMENTS['ROL'], (0, -1), 'SEG'],)), 'PPG_PCG_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PPG_PCG_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPG_PCG_GOAL_ROLE', None, (0, -1), 'GRP'], ['PPG_PCG_GOAL_OBSERVATION', None, (0, -1), 'GRP'], ['PPG_PCG_PROBLEM', None, (0, -1), 'GRP'], ['PPG_PCG_ORDER', None, (0, -1), 'GRP'],)), 'PPG_PCG_GOAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPG_PCG_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPG_PCG_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PPG_PCG_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PPG_PCG_ORDER_DETAIL': ('sequence', (['PPG_PCG_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPG_PCG_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPG_PCG_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPG_PCG_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPG_PCG_PATHWAY_ROLE', None, (0, -1), 'GRP'], ['PPG_PCG_GOAL', None, (0, -1), 'GRP'],)), 'PPG_PCG_PATHWAY_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPG_PCG_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PPG_PCG_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPG_PCG_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PPG_PCG_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPG_PCG_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPG_PCG_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPP_PCB_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PPP_PCB_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPP_PCB_GOAL_ROLE', None, (0, -1), 'GRP'], ['PPP_PCB_GOAL_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPP_PCB_GOAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPP_PCB_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPP_PCB_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PPP_PCB_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PPP_PCB_ORDER_DETAIL': ('sequence', (['PPP_PCB_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPP_PCB_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPP_PCB_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPP_PCB_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPP_PCB_PATHWAY_ROLE', None, (0, -1), 'GRP'], ['PPP_PCB_PROBLEM', None, (0, -1), 'GRP'],)), 'PPP_PCB_PATHWAY_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPP_PCB_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PPP_PCB_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPP_PCB_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PPP_PCB_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'], ['PPP_PCB_GOAL', None, (0, -1), 'GRP'], ['PPP_PCB_ORDER', None, (0, -1), 'GRP'],)), 'PPP_PCB_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPP_PCB_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPR_PC1_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PPR_PC1_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPR_PC1_GOAL_ROLE', None, (0, -1), 'GRP'], ['PPR_PC1_GOAL_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPR_PC1_GOAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPR_PC1_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPR_PC1_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PPR_PC1_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PPR_PC1_ORDER_DETAIL': ('sequence', (['PPR_PC1_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPR_PC1_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPR_PC1_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPR_PC1_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPR_PC1_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PPR_PC1_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPR_PC1_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PPR_PC1_PATHWAY', None, (0, -1), 'GRP'], ['PPR_PC1_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'], ['PPR_PC1_GOAL', None, (0, -1), 'GRP'], ['PPR_PC1_ORDER', None, (0, -1), 'GRP'],)), 'PPR_PC1_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPR_PC1_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPT_PCL_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PPT_PCL_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPT_PCL_GOAL_ROLE', None, (0, -1), 'GRP'], ['PPT_PCL_GOAL_OBSERVATION', None, (0, -1), 'GRP'], ['PPT_PCL_PROBLEM', None, (0, -1), 'GRP'], ['PPT_PCL_ORDER', None, (0, -1), 'GRP'],)), 'PPT_PCL_GOAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPT_PCL_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPT_PCL_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PPT_PCL_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PPT_PCL_ORDER_DETAIL': ('sequence', (['PPT_PCL_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPT_PCL_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPT_PCL_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPT_PCL_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPT_PCL_PATHWAY_ROLE', None, (0, -1), 'GRP'], ['PPT_PCL_GOAL', None, (0, -1), 'GRP'],)), 'PPT_PCL_PATHWAY_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPT_PCL_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PPT_PCL_PATIENT_VISIT', None, (0, 1), 'GRP'], ['PPT_PCL_PATHWAY', None, (1, -1), 'GRP'],)), 'PPT_PCL_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PPT_PCL_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPT_PCL_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PPT_PCL_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPT_PCL_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPT_PCL_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPV_PCA_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPV_PCA_GOAL_ROLE', None, (0, -1), 'GRP'], ['PPV_PCA_GOAL_PATHWAY', None, (0, -1), 'GRP'], ['PPV_PCA_GOAL_OBSERVATION', None, (0, -1), 'GRP'], ['PPV_PCA_PROBLEM', None, (0, -1), 'GRP'], ['PPV_PCA_ORDER', None, (0, -1), 'GRP'],)), 'PPV_PCA_GOAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPV_PCA_GOAL_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPV_PCA_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPV_PCA_OBRANYHL7SEGMENT_SUPPGRP': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PPV_PCA_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PPV_PCA_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PPV_PCA_ORDER_DETAIL': ('sequence', (['PPV_PCA_OBRANYHL7SEGMENT_SUPPGRP', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPV_PCA_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPV_PCA_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PPV_PCA_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PPV_PCA_PATIENT_VISIT', None, (0, 1), 'GRP'], ['PPV_PCA_GOAL', None, (1, -1), 'GRP'],)), 'PPV_PCA_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PPV_PCA_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PPV_PCA_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PPV_PCA_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'],)), 'PPV_PCA_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PPV_PCA_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PRR_PC5_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PRR_PC5_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PRR_PC5_GOAL_ROLE', None, (0, -1), 'GRP'], ['PRR_PC5_GOAL_OBSERVATION', None, (0, -1), 'GRP'],)), 'PRR_PC5_GOAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PRR_PC5_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PRR_PC5_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PRR_PC5_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PRR_PC5_ORDER_DETAIL': ('sequence', (['PRR_PC5_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PRR_PC5_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PRR_PC5_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PRR_PC5_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PRR_PC5_PATIENT_VISIT', None, (0, 1), 'GRP'], ['PRR_PC5_PROBLEM', None, (1, -1), 'GRP'],)), 'PRR_PC5_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PRR_PC5_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PRR_PC5_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PRR_PC5_PROBLEM_PATHWAY', None, (0, -1), 'GRP'], ['PRR_PC5_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'], ['PRR_PC5_GOAL', None, (0, -1), 'GRP'], ['PRR_PC5_ORDER', None, (0, -1), 'GRP'],)), 'PRR_PC5_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PRR_PC5_PROBLEM_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PRR_PC5_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PTR_PCF_CHOICE': ('choice', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'],)), 'PTR_PCF_GOAL': ('sequence', (['GOL', SEGMENTS['GOL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PTR_PCF_GOAL_ROLE', None, (0, -1), 'GRP'], ['PTR_PCF_GOAL_OBSERVATION', None, (0, -1), 'GRP'],)), 'PTR_PCF_GOAL_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PTR_PCF_GOAL_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PTR_PCF_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['PTR_PCF_ORDER_DETAIL', None, (0, 1), 'GRP'],)), 'PTR_PCF_ORDER_DETAIL': ('sequence', (['PTR_PCF_CHOICE', None, (1, 1), 'GRP'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PTR_PCF_ORDER_OBSERVATION', None, (0, -1), 'GRP'],)), 'PTR_PCF_ORDER_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PTR_PCF_PATHWAY': ('sequence', (['PTH', SEGMENTS['PTH'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PTR_PCF_PATHWAY_ROLE', None, (0, -1), 'GRP'], ['PTR_PCF_PROBLEM', None, (0, -1), 'GRP'],)), 'PTR_PCF_PATHWAY_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'PTR_PCF_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PTR_PCF_PATIENT_VISIT', None, (0, 1), 'GRP'], ['PTR_PCF_PATHWAY', None, (1, -1), 'GRP'],)), 'PTR_PCF_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'PTR_PCF_PROBLEM': ('sequence', (['PRB', SEGMENTS['PRB'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'], ['PTR_PCF_PROBLEM_ROLE', None, (0, -1), 'GRP'], ['PTR_PCF_PROBLEM_OBSERVATION', None, (0, -1), 'GRP'], ['PTR_PCF_GOAL', None, (0, -1), 'GRP'], ['PTR_PCF_ORDER', None, (0, -1), 'GRP'],)), 'PTR_PCF_PROBLEM_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'PTR_PCF_PROBLEM_ROLE': ('sequence', (['ROL', SEGMENTS['ROL'], (1, 1), 'SEG'], ['VAR', SEGMENTS['VAR'], (0, -1), 'SEG'],)), 'QBP_K13_ROW_DEFINITION': ('sequence', (['RDF', SEGMENTS['RDF'], (1, 1), 'SEG'], ['RDT', SEGMENTS['RDT'], (0, -1), 'SEG'],)), 'QBP_QNN': ('sequence', (['MSH', SEGMENTS['MSH'], (1, 1), 'SEG'], ['SFT', SEGMENTS['SFT'], (0, -1), 'SEG'], ['QPD', SEGMENTS['QPD'], (1, 1), 'SEG'], ['RDF', SEGMENTS['RDF'], (0, 1), 'SEG'], ['RCP', SEGMENTS['RCP'], (1, 1), 'SEG'], ['DSC', SEGMENTS['DSC'], (0, 1), 'SEG'],)), 'QVR_Q17_QBP': ('sequence', (['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (0, 1), 'SEG'],)), 'RAR_RAR_DEFINITION': ('sequence', (['QRD', SEGMENTS['QRD'], (1, 1), 'SEG'], ['QRF', SEGMENTS['QRF'], (0, 1), 'SEG'], ['RAR_RAR_PATIENT', None, (0, 1), 'GRP'], ['RAR_RAR_ORDER', None, (1, -1), 'GRP'],)), 'RAR_RAR_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RAR_RAR_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RAR_RAR_ENCODING', None, (0, 1), 'GRP'], ['RXA', SEGMENTS['RXA'], (1, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, 1), 'SEG'],)), 'RAR_RAR_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RAS_O17_ADMINISTRATION': ('sequence', (['RXA', SEGMENTS['RXA'], (1, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, 1), 'SEG'], ['RAS_O17_OBSERVATION', None, (0, -1), 'GRP'],)), 'RAS_O17_COMPONENTS': ('sequence', (['RXC', SEGMENTS['RXC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RAS_O17_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RAS_O17_TIMING_ENCODED', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RAS_O17_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RAS_O17_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RAS_O17_TIMING', None, (0, -1), 'GRP'], ['RAS_O17_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RAS_O17_ENCODING', None, (0, 1), 'GRP'], ['RAS_O17_ADMINISTRATION', None, (1, -1), 'GRP'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'RAS_O17_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['RAS_O17_ORDER_DETAIL_SUPPLEMENT', None, (0, 1), 'GRP'],)), 'RAS_O17_ORDER_DETAIL_SUPPLEMENT': ('sequence', (['NTE', SEGMENTS['NTE'], (1, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RAS_O17_COMPONENTS', None, (0, -1), 'GRP'],)), 'RAS_O17_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['RAS_O17_PATIENT_VISIT', None, (0, 1), 'GRP'],)), 'RAS_O17_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RAS_O17_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RAS_O17_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RCI_I05_OBSERVATION': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RCI_I05_RESULTS', None, (0, -1), 'GRP'],)), 'RCI_I05_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RCI_I05_RESULTS': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RCL_I06_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RDE_O11_COMPONENT': ('sequence', (['RXC', SEGMENTS['RXC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RDE_O11_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'RDE_O11_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RDE_O11_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RDE_O11_TIMING', None, (0, -1), 'GRP'], ['RDE_O11_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RDE_O11_TIMING_ENCODED', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'], ['RDE_O11_OBSERVATION', None, (0, -1), 'GRP'], ['FT1', SEGMENTS['FT1'], (0, -1), 'SEG'], ['BLG', SEGMENTS['BLG'], (0, 1), 'SEG'], ['CTI', SEGMENTS['CTI'], (0, -1), 'SEG'],)), 'RDE_O11_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RDE_O11_COMPONENT', None, (0, -1), 'GRP'],)), 'RDE_O11_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RDE_O11_PATIENT_VISIT', None, (0, 1), 'GRP'], ['RDE_O11_INSURANCE', None, (0, -1), 'GRP'], ['GT1', SEGMENTS['GT1'], (0, 1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'],)), 'RDE_O11_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RDE_O11_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RDE_O11_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RDR_RDR_DEFINITION': ('sequence', (['QRD', SEGMENTS['QRD'], (1, 1), 'SEG'], ['QRF', SEGMENTS['QRF'], (0, 1), 'SEG'], ['RDR_RDR_PATIENT', None, (0, 1), 'GRP'], ['RDR_RDR_ORDER', None, (1, -1), 'GRP'],)), 'RDR_RDR_DISPENSE': ('sequence', (['RXD', SEGMENTS['RXD'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RDR_RDR_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RDR_RDR_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RDR_RDR_ENCODING', None, (0, 1), 'GRP'], ['RDR_RDR_DISPENSE', None, (1, -1), 'GRP'],)), 'RDR_RDR_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RDS_O13_COMPONENT': ('sequence', (['RXC', SEGMENTS['RXC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RDS_O13_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RDS_O13_TIMING_ENCODED', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RDS_O13_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RDS_O13_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RDS_O13_TIMING', None, (0, -1), 'GRP'], ['RDS_O13_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RDS_O13_ENCODING', None, (0, 1), 'GRP'], ['RXD', SEGMENTS['RXD'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'], ['RDS_O13_OBSERVATION', None, (0, -1), 'GRP'], ['FT1', SEGMENTS['FT1'], (0, -1), 'SEG'],)), 'RDS_O13_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['RDS_O13_ORDER_DETAIL_SUPPLEMENT', None, (0, 1), 'GRP'],)), 'RDS_O13_ORDER_DETAIL_SUPPLEMENT': ('sequence', (['NTE', SEGMENTS['NTE'], (1, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RDS_O13_COMPONENT', None, (0, -1), 'GRP'],)), 'RDS_O13_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['RDS_O13_PATIENT_VISIT', None, (0, 1), 'GRP'],)), 'RDS_O13_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RDS_O13_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RDS_O13_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'REF_I12_AUTCTD_SUPPGRP2': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'REF_I12_AUTHORIZATION_CONTACT': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'REF_I12_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'REF_I12_OBSERVATION': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['REF_I12_RESULTS_NOTES', None, (0, -1), 'GRP'],)), 'REF_I12_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'REF_I12_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['REF_I12_AUTCTD_SUPPGRP2', None, (0, 1), 'GRP'],)), 'REF_I12_PROVIDER_CONTACT': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'REF_I12_RESULTS_NOTES': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RER_RER_DEFINITION': ('sequence', (['QRD', SEGMENTS['QRD'], (1, 1), 'SEG'], ['QRF', SEGMENTS['QRF'], (0, 1), 'SEG'], ['RER_RER_PATIENT', None, (0, 1), 'GRP'], ['RER_RER_ORDER', None, (1, -1), 'GRP'],)), 'RER_RER_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RER_RER_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RGR_RGR_DEFINITION': ('sequence', (['QRD', SEGMENTS['QRD'], (1, 1), 'SEG'], ['QRF', SEGMENTS['QRF'], (0, 1), 'SEG'], ['RGR_RGR_PATIENT', None, (0, 1), 'GRP'], ['RGR_RGR_ORDER', None, (1, -1), 'GRP'],)), 'RGR_RGR_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RGR_RGR_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RGR_RGR_ENCODING', None, (0, 1), 'GRP'], ['RXG', SEGMENTS['RXG'], (1, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RGR_RGR_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RGV_O15_COMPONENTS': ('sequence', (['RXC', SEGMENTS['RXC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RGV_O15_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RGV_O15_TIMING_ENCODED', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RGV_O15_GIVE': ('sequence', (['RXG', SEGMENTS['RXG'], (1, 1), 'SEG'], ['RGV_O15_TIMING_GIVE', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'], ['RGV_O15_OBSERVATION', None, (1, -1), 'GRP'],)), 'RGV_O15_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RGV_O15_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RGV_O15_TIMING', None, (0, -1), 'GRP'], ['RGV_O15_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RGV_O15_ENCODING', None, (0, 1), 'GRP'], ['RGV_O15_GIVE', None, (1, -1), 'GRP'],)), 'RGV_O15_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['RGV_O15_ORDER_DETAIL_SUPPLEMENT', None, (0, 1), 'GRP'],)), 'RGV_O15_ORDER_DETAIL_SUPPLEMENT': ('sequence', (['NTE', SEGMENTS['NTE'], (1, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RGV_O15_COMPONENTS', None, (0, -1), 'GRP'],)), 'RGV_O15_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['RGV_O15_PATIENT_VISIT', None, (0, 1), 'GRP'],)), 'RGV_O15_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RGV_O15_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RGV_O15_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RGV_O15_TIMING_GIVE': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'ROR_ROR_DEFINITION': ('sequence', (['QRD', SEGMENTS['QRD'], (1, 1), 'SEG'], ['QRF', SEGMENTS['QRF'], (0, 1), 'SEG'], ['ROR_ROR_PATIENT', None, (0, 1), 'GRP'], ['ROR_ROR_ORDER', None, (1, -1), 'GRP'],)), 'ROR_ROR_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'ROR_ROR_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RPA_I08_AUTHORIZATION_1': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'RPA_I08_AUTHORIZATION_2': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'RPA_I08_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'RPA_I08_OBSERVATION': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RPA_I08_RESULTS', None, (0, -1), 'GRP'],)), 'RPA_I08_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['RPA_I08_AUTHORIZATION_2', None, (0, 1), 'GRP'],)), 'RPA_I08_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RPA_I08_RESULTS': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RPA_I08_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RPI_I01_GUARANTOR_INSURANCE': ('sequence', (['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['RPI_I01_INSURANCE', None, (1, -1), 'GRP'],)), 'RPI_I01_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'RPI_I01_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RPI_I04_GUARANTOR_INSURANCE': ('sequence', (['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['RPI_I04_INSURANCE', None, (1, -1), 'GRP'],)), 'RPI_I04_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'RPI_I04_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RPL_I02_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RPR_I03_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RQA_I08_AUTCTD_SUPPGRP2': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'RQA_I08_AUTHORIZATION': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'RQA_I08_GUARANTOR_INSURANCE': ('sequence', (['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['RQA_I08_INSURANCE', None, (1, -1), 'GRP'],)), 'RQA_I08_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'RQA_I08_OBSERVATION': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RQA_I08_RESULTS', None, (0, -1), 'GRP'],)), 'RQA_I08_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['RQA_I08_AUTCTD_SUPPGRP2', None, (0, 1), 'GRP'],)), 'RQA_I08_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RQA_I08_RESULTS': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RQA_I08_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RQC_I05_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RQI_I01_GUARANTOR_INSURANCE': ('sequence', (['GT1', SEGMENTS['GT1'], (0, -1), 'SEG'], ['RQI_I01_INSURANCE', None, (1, -1), 'GRP'],)), 'RQI_I01_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'RQI_I01_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RQP_I04_PROVIDER': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RRA_O18_ADMINISTRATION': ('sequence', (['RXA', SEGMENTS['RXA'], (1, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, 1), 'SEG'],)), 'RRA_O18_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RRA_O18_TIMING', None, (0, -1), 'GRP'], ['RRA_O18_ADMINISTRATION', None, (0, 1), 'GRP'],)), 'RRA_O18_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RRA_O18_RESPONSE': ('sequence', (['RRA_O18_PATIENT', None, (0, 1), 'GRP'], ['RRA_O18_ORDER', None, (1, -1), 'GRP'],)), 'RRA_O18_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RRD_O14_DISPENSE': ('sequence', (['RXD', SEGMENTS['RXD'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RRD_O14_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RRD_O14_TIMING', None, (0, -1), 'GRP'], ['RRD_O14_DISPENSE', None, (0, 1), 'GRP'],)), 'RRD_O14_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RRD_O14_RESPONSE': ('sequence', (['RRD_O14_PATIENT', None, (0, 1), 'GRP'], ['RRD_O14_ORDER', None, (1, -1), 'GRP'],)), 'RRD_O14_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RRE_O12_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RRE_O12_TIMING_ENCODED', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RRE_O12_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RRE_O12_TIMING', None, (0, -1), 'GRP'], ['RRE_O12_ENCODING', None, (0, 1), 'GRP'],)), 'RRE_O12_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RRE_O12_RESPONSE': ('sequence', (['RRE_O12_PATIENT', None, (0, 1), 'GRP'], ['RRE_O12_ORDER', None, (1, -1), 'GRP'],)), 'RRE_O12_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RRE_O12_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RRG_O16_GIVE': ('sequence', (['RXG', SEGMENTS['RXG'], (1, 1), 'SEG'], ['RRG_O16_TIMING_GIVE', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RRG_O16_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RRG_O16_TIMING', None, (0, -1), 'GRP'], ['RRG_O16_GIVE', None, (0, 1), 'GRP'],)), 'RRG_O16_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RRG_O16_RESPONSE': ('sequence', (['RRG_O16_PATIENT', None, (0, 1), 'GRP'], ['RRG_O16_ORDER', None, (1, -1), 'GRP'],)), 'RRG_O16_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RRG_O16_TIMING_GIVE': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RRI_I12_AUTCTD_SUPPGRP2': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'RRI_I12_AUTHORIZATION_CONTACT': ('sequence', (['AUT', SEGMENTS['AUT'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'],)), 'RRI_I12_OBSERVATION': ('sequence', (['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RRI_I12_RESULTS_NOTES', None, (0, -1), 'GRP'],)), 'RRI_I12_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RRI_I12_PROCEDURE': ('sequence', (['PR1', SEGMENTS['PR1'], (1, 1), 'SEG'], ['RRI_I12_AUTCTD_SUPPGRP2', None, (0, 1), 'GRP'],)), 'RRI_I12_PROVIDER_CONTACT': ('sequence', (['PRD', SEGMENTS['PRD'], (1, 1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, -1), 'SEG'],)), 'RRI_I12_RESULTS_NOTES': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_K11_ROW_DEFINITION': ('sequence', (['RDF', SEGMENTS['RDF'], (1, 1), 'SEG'], ['RDT', SEGMENTS['RDT'], (0, -1), 'SEG'],)), 'RSP_K21_QUERY_RESPONSE': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NK1', SEGMENTS['NK1'], (0, -1), 'SEG'], ['QRI', SEGMENTS['QRI'], (1, 1), 'SEG'],)), 'RSP_K23_QUERY_RESPONSE': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'],)), 'RSP_K25_STAFF': ('sequence', (['STF', SEGMENTS['STF'], (1, 1), 'SEG'], ['PRA', SEGMENTS['PRA'], (0, -1), 'SEG'], ['ORG', SEGMENTS['ORG'], (0, -1), 'SEG'], ['AFF', SEGMENTS['AFF'], (0, -1), 'SEG'], ['LAN', SEGMENTS['LAN'], (0, -1), 'SEG'], ['EDU', SEGMENTS['EDU'], (0, -1), 'SEG'], ['CER', SEGMENTS['CER'], (0, -1), 'SEG'],)), 'RSP_K31_COMPONENTS': ('sequence', (['RXC', SEGMENTS['RXC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_K31_ENCODING': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RSP_K31_TIMING_ENCODED', None, (1, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_K31_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_K31_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RSP_K31_TIMING', None, (0, -1), 'GRP'], ['RSP_K31_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RSP_K31_ENCODING', None, (0, 1), 'GRP'], ['RXD', SEGMENTS['RXD'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'], ['RSP_K31_OBSERVATION', None, (1, -1), 'GRP'],)), 'RSP_K31_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RSP_K31_COMPONENTS', None, (0, -1), 'GRP'],)), 'RSP_K31_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'], ['RSP_K31_PATIENT_VISIT', None, (0, 1), 'GRP'],)), 'RSP_K31_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RSP_K31_RESPONSE': ('sequence', (['RSP_K31_PATIENT', None, (0, 1), 'GRP'], ['RSP_K31_ORDER', None, (1, -1), 'GRP'],)), 'RSP_K31_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_K31_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Q11_MF_LOC_DEPT': ('sequence', (['LDP', SEGMENTS['LDP'], (1, 1), 'SEG'], ['LCH', SEGMENTS['LCH'], (0, -1), 'SEG'], ['LCC', SEGMENTS['LCC'], (0, -1), 'SEG'],)), 'RSP_Q11_QUERY_RESULT_CLUSTER': ('sequence', (['MFE', SEGMENTS['MFE'], (1, 1), 'SEG'], ['LOC', SEGMENTS['LOC'], (1, 1), 'SEG'], ['LCH', SEGMENTS['LCH'], (0, -1), 'SEG'], ['LRL', SEGMENTS['LRL'], (0, -1), 'SEG'], ['RSP_Q11_MF_LOC_DEPT', None, (1, -1), 'GRP'],)), 'RSP_Z82_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RSP_Z82_TIMING', None, (0, -1), 'GRP'], ['RSP_Z82_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RSP_Z82_ENCODED_ORDER', None, (0, 1), 'GRP'], ['RXD', SEGMENTS['RXD'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'], ['RSP_Z82_OBSERVATION', None, (1, -1), 'GRP'],)), 'RSP_Z82_ENCODED_ORDER': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RSP_Z82_TIMING_ENCODED', None, (0, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_Z82_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_Z82_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RSP_Z82_TREATMENT', None, (0, 1), 'GRP'],)), 'RSP_Z82_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RSP_Z82_VISIT', None, (0, 1), 'GRP'],)), 'RSP_Z82_QUERY_RESPONSE': ('sequence', (['RSP_Z82_PATIENT', None, (0, 1), 'GRP'], ['RSP_Z82_COMMON_ORDER', None, (1, -1), 'GRP'],)), 'RSP_Z82_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Z82_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Z82_TREATMENT': ('sequence', (['RXC', SEGMENTS['RXC'], (1, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_Z82_VISIT': ('sequence', (['AL1', SEGMENTS['AL1'], (1, -1), 'SEG'], ['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RSP_Z86_ADMINISTRATION': ('sequence', (['RXA', SEGMENTS['RXA'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_Z86_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RSP_Z86_TIMING', None, (0, -1), 'GRP'], ['RSP_Z86_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RSP_Z86_ENCODED_ORDER', None, (0, 1), 'GRP'], ['RSP_Z86_DISPENSE', None, (0, 1), 'GRP'], ['RSP_Z86_GIVE', None, (0, 1), 'GRP'], ['RSP_Z86_ADMINISTRATION', None, (0, 1), 'GRP'], ['RSP_Z86_OBSERVATION', None, (1, -1), 'GRP'],)), 'RSP_Z86_DISPENSE': ('sequence', (['RXD', SEGMENTS['RXD'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_Z86_ENCODED_ORDER': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RSP_Z86_TIMING_ENCODED', None, (0, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_Z86_GIVE': ('sequence', (['RXG', SEGMENTS['RXG'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_Z86_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_Z86_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_Z86_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['AL1', SEGMENTS['AL1'], (0, -1), 'SEG'],)), 'RSP_Z86_QUERY_RESPONSE': ('sequence', (['RSP_Z86_PATIENT', None, (0, 1), 'GRP'], ['RSP_Z86_COMMON_ORDER', None, (1, -1), 'GRP'],)), 'RSP_Z86_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Z86_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Z88_ALLERGY': ('sequence', (['AL1', SEGMENTS['AL1'], (1, -1), 'SEG'], ['RSP_Z88_VISIT', None, (0, 1), 'GRP'],)), 'RSP_Z88_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RSP_Z88_TIMING', None, (0, -1), 'GRP'], ['RSP_Z88_ORDER_DETAIL', None, (0, 1), 'GRP'], ['RSP_Z88_ORDER_ENCODED', None, (0, 1), 'GRP'], ['RXD', SEGMENTS['RXD'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'], ['RSP_Z88_OBSERVATION', None, (1, -1), 'GRP'],)), 'RSP_Z88_COMPONENT': ('sequence', (['RXC', SEGMENTS['RXC'], (1, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_Z88_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_Z88_ORDER_DETAIL': ('sequence', (['RXO', SEGMENTS['RXO'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RSP_Z88_COMPONENT', None, (0, 1), 'GRP'],)), 'RSP_Z88_ORDER_ENCODED': ('sequence', (['RXE', SEGMENTS['RXE'], (1, 1), 'SEG'], ['RSP_Z88_TIMING_ENCODED', None, (0, -1), 'GRP'], ['RXR', SEGMENTS['RXR'], (1, -1), 'SEG'], ['RXC', SEGMENTS['RXC'], (0, -1), 'SEG'],)), 'RSP_Z88_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RSP_Z88_ALLERGY', None, (0, 1), 'GRP'],)), 'RSP_Z88_QUERY_RESPONSE': ('sequence', (['RSP_Z88_PATIENT', None, (0, 1), 'GRP'], ['RSP_Z88_COMMON_ORDER', None, (1, -1), 'GRP'],)), 'RSP_Z88_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Z88_TIMING_ENCODED': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Z88_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RSP_Z90_COMMON_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['RSP_Z90_TIMING', None, (0, -1), 'GRP'], ['OBR', SEGMENTS['OBR'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['CTD', SEGMENTS['CTD'], (0, 1), 'SEG'], ['RSP_Z90_OBSERVATION', None, (1, -1), 'GRP'],)), 'RSP_Z90_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'RSP_Z90_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['NK1', SEGMENTS['NK1'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['RSP_Z90_VISIT', None, (0, 1), 'GRP'],)), 'RSP_Z90_QUERY_RESPONSE': ('sequence', (['RSP_Z90_PATIENT', None, (0, 1), 'GRP'], ['RSP_Z90_COMMON_ORDER', None, (1, -1), 'GRP'], ['RSP_Z90_SPECIMEN', None, (0, -1), 'GRP'],)), 'RSP_Z90_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'],)), 'RSP_Z90_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'RSP_Z90_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'RTB_K13_ROW_DEFINITION': ('sequence', (['RDF', SEGMENTS['RDF'], (1, 1), 'SEG'], ['RDT', SEGMENTS['RDT'], (0, -1), 'SEG'],)), 'RTB_KNN': ('sequence', (['MSH', SEGMENTS['MSH'], (1, 1), 'SEG'], ['SFT', SEGMENTS['SFT'], (0, -1), 'SEG'], ['MSA', SEGMENTS['MSA'], (1, 1), 'SEG'], ['ERR', SEGMENTS['ERR'], (0, 1), 'SEG'], ['QAK', SEGMENTS['QAK'], (1, 1), 'SEG'], ['QPD', SEGMENTS['QPD'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'], ['ANYHL7SEGMENT', SEGMENTS['ANYHL7SEGMENT'], (1, 1), 'SEG'], ['DSC', SEGMENTS['DSC'], (0, 1), 'SEG'],)), 'RTB_Z74_ROW_DEFINITION': ('sequence', (['RDF', SEGMENTS['RDF'], (1, 1), 'SEG'], ['RDT', SEGMENTS['RDT'], (0, -1), 'SEG'],)), 'SIU_S12_GENERAL_RESOURCE': ('sequence', (['AIG', SEGMENTS['AIG'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SIU_S12_LOCATION_RESOURCE': ('sequence', (['AIL', SEGMENTS['AIL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SIU_S12_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PD1', SEGMENTS['PD1'], (0, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'],)), 'SIU_S12_PERSONNEL_RESOURCE': ('sequence', (['AIP', SEGMENTS['AIP'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SIU_S12_RESOURCES': ('sequence', (['RGS', SEGMENTS['RGS'], (1, 1), 'SEG'], ['SIU_S12_SERVICE', None, (0, -1), 'GRP'], ['SIU_S12_GENERAL_RESOURCE', None, (0, -1), 'GRP'], ['SIU_S12_LOCATION_RESOURCE', None, (0, -1), 'GRP'], ['SIU_S12_PERSONNEL_RESOURCE', None, (0, -1), 'GRP'],)), 'SIU_S12_SERVICE': ('sequence', (['AIS', SEGMENTS['AIS'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SQM_S25_GENERAL_RESOURCE': ('sequence', (['AIG', SEGMENTS['AIG'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'],)), 'SQM_S25_LOCATION_RESOURCE': ('sequence', (['AIL', SEGMENTS['AIL'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'],)), 'SQM_S25_PERSONNEL_RESOURCE': ('sequence', (['AIP', SEGMENTS['AIP'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'],)), 'SQM_S25_REQUEST': ('sequence', (['ARQ', SEGMENTS['ARQ'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'], ['PID', SEGMENTS['PID'], (0, 1), 'SEG'], ['SQM_S25_RESOURCES', None, (1, -1), 'GRP'],)), 'SQM_S25_RESOURCES': ('sequence', (['RGS', SEGMENTS['RGS'], (1, 1), 'SEG'], ['SQM_S25_SERVICE', None, (0, -1), 'GRP'], ['SQM_S25_GENERAL_RESOURCE', None, (0, -1), 'GRP'], ['SQM_S25_PERSONNEL_RESOURCE', None, (0, -1), 'GRP'], ['SQM_S25_LOCATION_RESOURCE', None, (0, -1), 'GRP'],)), 'SQM_S25_SERVICE': ('sequence', (['AIS', SEGMENTS['AIS'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'],)), 'SQR_S25_GENERAL_RESOURCE': ('sequence', (['AIG', SEGMENTS['AIG'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SQR_S25_LOCATION_RESOURCE': ('sequence', (['AIL', SEGMENTS['AIL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SQR_S25_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, 1), 'SEG'],)), 'SQR_S25_PERSONNEL_RESOURCE': ('sequence', (['AIP', SEGMENTS['AIP'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SQR_S25_RESOURCES': ('sequence', (['RGS', SEGMENTS['RGS'], (1, 1), 'SEG'], ['SQR_S25_SERVICE', None, (0, -1), 'GRP'], ['SQR_S25_GENERAL_RESOURCE', None, (0, -1), 'GRP'], ['SQR_S25_PERSONNEL_RESOURCE', None, (0, -1), 'GRP'], ['SQR_S25_LOCATION_RESOURCE', None, (0, -1), 'GRP'],)), 'SQR_S25_SCHEDULE': ('sequence', (['SCH', SEGMENTS['SCH'], (1, 1), 'SEG'], ['TQ1', SEGMENTS['TQ1'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['SQR_S25_PATIENT', None, (0, 1), 'GRP'], ['SQR_S25_RESOURCES', None, (1, -1), 'GRP'],)), 'SQR_S25_SERVICE': ('sequence', (['AIS', SEGMENTS['AIS'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRM_S01_GENERAL_RESOURCE': ('sequence', (['AIG', SEGMENTS['AIG'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRM_S01_LOCATION_RESOURCE': ('sequence', (['AIL', SEGMENTS['AIL'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRM_S01_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'],)), 'SRM_S01_PERSONNEL_RESOURCE': ('sequence', (['AIP', SEGMENTS['AIP'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRM_S01_RESOURCES': ('sequence', (['RGS', SEGMENTS['RGS'], (1, 1), 'SEG'], ['SRM_S01_SERVICE', None, (0, -1), 'GRP'], ['SRM_S01_GENERAL_RESOURCE', None, (0, -1), 'GRP'], ['SRM_S01_LOCATION_RESOURCE', None, (0, -1), 'GRP'], ['SRM_S01_PERSONNEL_RESOURCE', None, (0, -1), 'GRP'],)), 'SRM_S01_SERVICE': ('sequence', (['AIS', SEGMENTS['AIS'], (1, 1), 'SEG'], ['APR', SEGMENTS['APR'], (0, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRR_S01_GENERAL_RESOURCE': ('sequence', (['AIG', SEGMENTS['AIG'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRR_S01_LOCATION_RESOURCE': ('sequence', (['AIL', SEGMENTS['AIL'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRR_S01_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['PV1', SEGMENTS['PV1'], (0, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'], ['DG1', SEGMENTS['DG1'], (0, -1), 'SEG'],)), 'SRR_S01_PERSONNEL_RESOURCE': ('sequence', (['AIP', SEGMENTS['AIP'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SRR_S01_RESOURCES': ('sequence', (['RGS', SEGMENTS['RGS'], (1, 1), 'SEG'], ['SRR_S01_SERVICE', None, (0, -1), 'GRP'], ['SRR_S01_GENERAL_RESOURCE', None, (0, -1), 'GRP'], ['SRR_S01_LOCATION_RESOURCE', None, (0, -1), 'GRP'], ['SRR_S01_PERSONNEL_RESOURCE', None, (0, -1), 'GRP'],)), 'SRR_S01_SCHEDULE': ('sequence', (['SCH', SEGMENTS['SCH'], (1, 1), 'SEG'], ['TQ1', SEGMENTS['TQ1'], (0, -1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'], ['SRR_S01_PATIENT', None, (0, -1), 'GRP'], ['SRR_S01_RESOURCES', None, (1, -1), 'GRP'],)), 'SRR_S01_SERVICE': ('sequence', (['AIS', SEGMENTS['AIS'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'SSR_U04_SPECIMEN_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['SPM', SEGMENTS['SPM'], (0, -1), 'SEG'],)), 'SSU_U03_SPECIMEN': ('sequence', (['SPM', SEGMENTS['SPM'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'],)), 'SSU_U03_SPECIMEN_CONTAINER': ('sequence', (['SAC', SEGMENTS['SAC'], (1, 1), 'SEG'], ['OBX', SEGMENTS['OBX'], (0, -1), 'SEG'], ['SSU_U03_SPECIMEN', None, (0, -1), 'GRP'],)), 'SUR_P09_FACILITY': ('sequence', (['FAC', SEGMENTS['FAC'], (1, 1), 'SEG'], ['SUR_P09_PRODUCT', None, (1, -1), 'GRP'], ['PSH', SEGMENTS['PSH'], (1, 1), 'SEG'], ['SUR_P09_FACILITY_DETAIL', None, (1, -1), 'GRP'], )), 'SUR_P09_FACILITY_DETAIL': ('sequence', (['FAC', SEGMENTS['FAC'], (1, 1), 'SEG'], ['PDC', SEGMENTS['PDC'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (1, 1), 'SEG'],)), 'SUR_P09_PRODUCT': ('sequence', (['PSH', SEGMENTS['PSH'], (1, 1), 'SEG'], ['PDC', SEGMENTS['PDC'], (1, 1), 'SEG'],)), 'TCU_U10_TEST_CONFIGURATION': ('sequence', (['SPM', SEGMENTS['SPM'], (0, 1), 'SEG'], ['TCC', SEGMENTS['TCC'], (1, -1), 'SEG'],)), 'VXR_V03_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'VXR_V03_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'VXR_V03_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['VXR_V03_TIMING', None, (0, -1), 'GRP'], ['RXA', SEGMENTS['RXA'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (0, 1), 'SEG'], ['VXR_V03_OBSERVATION', None, (0, -1), 'GRP'],)), 'VXR_V03_PATIENT_VISIT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'VXR_V03_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'VXU_V04_INSURANCE': ('sequence', (['IN1', SEGMENTS['IN1'], (1, 1), 'SEG'], ['IN2', SEGMENTS['IN2'], (0, 1), 'SEG'], ['IN3', SEGMENTS['IN3'], (0, 1), 'SEG'],)), 'VXU_V04_OBSERVATION': ('sequence', (['OBX', SEGMENTS['OBX'], (1, 1), 'SEG'], ['NTE', SEGMENTS['NTE'], (0, -1), 'SEG'],)), 'VXU_V04_ORDER': ('sequence', (['ORC', SEGMENTS['ORC'], (1, 1), 'SEG'], ['VXU_V04_TIMING', None, (0, -1), 'GRP'], ['RXA', SEGMENTS['RXA'], (1, 1), 'SEG'], ['RXR', SEGMENTS['RXR'], (0, 1), 'SEG'], ['VXU_V04_OBSERVATION', None, (0, -1), 'GRP'],)), 'VXU_V04_PATIENT': ('sequence', (['PV1', SEGMENTS['PV1'], (1, 1), 'SEG'], ['PV2', SEGMENTS['PV2'], (0, 1), 'SEG'],)), 'VXU_V04_TIMING': ('sequence', (['TQ1', SEGMENTS['TQ1'], (1, 1), 'SEG'], ['TQ2', SEGMENTS['TQ2'], (0, -1), 'SEG'],)), 'VXX_V02_PATIENT': ('sequence', (['PID', SEGMENTS['PID'], (1, 1), 'SEG'], ['NK1', SEGMENTS['NK1'], (0, -1), 'SEG'],)), } for k, v in iteritems(GROUPS): for item in v[1]: if item[3] == 'GRP': item[1] = GROUPS[item[0]]

63.247542

105

0.351293

16,703

180,129

3.616356

0.028019

0.111251

0.076154

0.055576

0.952172

0.914012

0.844961

0.784286

0.721144

0.689723

0

0.0689

0.408668

180,129

2,847

106

63.269758

0.498188

0

0.559578

0

0.241749

0.044096

0

1

0

false

0

0.000703

0

0.000703

0

null

0

1

0

1

0

null

0

7

0aae34fc234fb44ad4572cbf8003f971454107a6

487

py

Python

test/pagerank.py

roks/snap-python

e316dfae8f0b7707756e0a6bf4237d448259d2d2

[ "BSD-3-Clause" ]

null

test/pagerank.py

roks/snap-python

e316dfae8f0b7707756e0a6bf4237d448259d2d2

[ "BSD-3-Clause" ]

null

test/pagerank.py

roks/snap-python

e316dfae8f0b7707756e0a6bf4237d448259d2d2

[ "BSD-3-Clause" ]

1

2019-11-11T20:25:19.000Z

import snap Graph = snap.GenRndGnm(snap.PNGraph, 100, 1000) PRankH = snap.TIntFltH() snap.GetPageRank(Graph, PRankH) for item in PRankH: print item, PRankH[item] Graph = snap.GenRndGnm(snap.PUNGraph, 5000000, 50000000) PRankH = snap.TIntFltH() snap.GetPageRank(Graph, PRankH) for item in PRankH: print item, PRankH[item] Graph = snap.GenRndGnm(snap.PNEANet, 100, 1000) PRankH = snap.TIntFltH() snap.GetPageRank(Graph, PRankH) for item in PRankH: print item, PRankH[item]

23.190476

56

0.741273

68

487

5.308824

0.264706

0.074792

0.149584

0.182825

0.808864

0

0.069378

0.141684

487

20

57

24.35

0.794258

0

0.75

0

null

0

0.0625

null

0.1875

0

null

0

1

0

1

0

null

0

1

0

9

0abb308dcf500fd4a5d46c36e27a1428a29ac423

40,877

py

Python

airflow/providers/google/cloud/hooks/cloud_memorystore.py

npodewitz/airflow

511ea702d5f732582d018dad79754b54d5e53f9d

[ "Apache-2.0" ]

8,092

2016-04-27T20:32:29.000Z

2019-01-05T07:39:33.000Z

airflow/providers/google/cloud/hooks/cloud_memorystore.py

npodewitz/airflow

511ea702d5f732582d018dad79754b54d5e53f9d

[ "Apache-2.0" ]

2,961

2016-05-05T07:16:16.000Z

2019-01-05T08:47:59.000Z

airflow/providers/google/cloud/hooks/cloud_memorystore.py

npodewitz/airflow

511ea702d5f732582d018dad79754b54d5e53f9d

[ "Apache-2.0" ]

3,546

2016-05-04T20:33:16.000Z

2019-01-05T05:14:26.000Z

# # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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. """ Hooks for Cloud Memorystore service. .. spelling:: DataProtectionMode FieldMask pb memcache """ from typing import Dict, Optional, Sequence, Tuple, Union from google.api_core import path_template from google.api_core.exceptions import NotFound from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault from google.api_core.retry import Retry from google.cloud.memcache_v1beta2 import CloudMemcacheClient from google.cloud.memcache_v1beta2.types import cloud_memcache from google.cloud.redis_v1 import ( CloudRedisClient, FailoverInstanceRequest, InputConfig, Instance, OutputConfig, ) from google.protobuf.field_mask_pb2 import FieldMask from airflow import version from airflow.exceptions import AirflowException from airflow.providers.google.common.hooks.base_google import PROVIDE_PROJECT_ID, GoogleBaseHook class CloudMemorystoreHook(GoogleBaseHook): """ Hook for Google Cloud Memorystore APIs. All the methods in the hook where project_id is used must be called with keyword arguments rather than positional. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account. """ def __init__( self, gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, ) -> None: super().__init__( gcp_conn_id=gcp_conn_id, delegate_to=delegate_to, impersonation_chain=impersonation_chain, ) self._client: Optional[CloudRedisClient] = None def get_conn(self) -> CloudRedisClient: """Retrieves client library object that allow access to Cloud Memorystore service.""" if not self._client: self._client = CloudRedisClient(credentials=self._get_credentials()) return self._client @staticmethod def _append_label(instance: Instance, key: str, val: str) -> Instance: """ Append labels to provided Instance type Labels must fit the regex ``[a-z]([-a-z0-9]*[a-z0-9])?`` (current airflow version string follows semantic versioning spec: x.y.z). :param instance: The proto to append resource_label airflow version to :param key: The key label :param val: :return: The cluster proto updated with new label """ val = val.replace(".", "-").replace("+", "-") instance.labels.update({key: val}) return instance @GoogleBaseHook.fallback_to_default_project_id def create_instance( self, location: str, instance_id: str, instance: Union[Dict, Instance], project_id: str = PROVIDE_PROJECT_ID, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Creates a Redis instance based on the specified tier and memory size. By default, the instance is accessible from the project's `default network <https://cloud.google.com/compute/docs/networks-and-firewalls#networks>`__. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance_id: Required. The logical name of the Redis instance in the customer project with the following restrictions: - Must contain only lowercase letters, numbers, and hyphens. - Must start with a letter. - Must be between 1-40 characters. - Must end with a number or a letter. - Must be unique within the customer project / location :param instance: Required. A Redis [Instance] resource If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.redis_v1.types.Instance` :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() if isinstance(instance, dict): instance = Instance(**instance) elif not isinstance(instance, Instance): raise AirflowException("instance is not instance of Instance type or python dict") parent = f"projects/{project_id}/locations/{location}" instance_name = f"projects/{project_id}/locations/{location}/instances/{instance_id}" try: self.log.info("Fetching instance: %s", instance_name) instance = client.get_instance( request={'name': instance_name}, retry=retry, timeout=timeout, metadata=metadata or () ) self.log.info("Instance exists. Skipping creation.") return instance except NotFound: self.log.info("Instance not exists.") self._append_label(instance, "airflow-version", "v" + version.version) result = client.create_instance( request={'parent': parent, 'instance_id': instance_id, 'instance': instance}, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance created.") return client.get_instance( request={'name': instance_name}, retry=retry, timeout=timeout, metadata=metadata or () ) @GoogleBaseHook.fallback_to_default_project_id def delete_instance( self, location: str, instance: str, project_id: str = PROVIDE_PROJECT_ID, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Deletes a specific Redis instance. Instance stops serving and data is deleted. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance: The logical name of the Redis instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() name = f"projects/{project_id}/locations/{location}/instances/{instance}" self.log.info("Fetching Instance: %s", name) instance = client.get_instance( request={'name': name}, retry=retry, timeout=timeout, metadata=metadata, ) if not instance: return self.log.info("Deleting Instance: %s", name) result = client.delete_instance( request={'name': name}, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance deleted: %s", name) @GoogleBaseHook.fallback_to_default_project_id def export_instance( self, location: str, instance: str, output_config: Union[Dict, OutputConfig], project_id: str = PROVIDE_PROJECT_ID, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Export Redis instance data into a Redis RDB format file in Cloud Storage. Redis will continue serving during this operation. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance: The logical name of the Redis instance in the customer project. :param output_config: Required. Specify data to be exported. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.redis_v1.types.OutputConfig` :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() name = f"projects/{project_id}/locations/{location}/instances/{instance}" self.log.info("Exporting Instance: %s", name) result = client.export_instance( request={'name': name, 'output_config': output_config}, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance exported: %s", name) @GoogleBaseHook.fallback_to_default_project_id def failover_instance( self, location: str, instance: str, data_protection_mode: FailoverInstanceRequest.DataProtectionMode, project_id: str = PROVIDE_PROJECT_ID, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Initiates a failover of the primary node to current replica node for a specific STANDARD tier Cloud Memorystore for Redis instance. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance: The logical name of the Redis instance in the customer project. :param data_protection_mode: Optional. Available data protection modes that the user can choose. If it's unspecified, data protection mode will be LIMITED_DATA_LOSS by default. .DataProtectionMode :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() name = f"projects/{project_id}/locations/{location}/instances/{instance}" self.log.info("Failovering Instance: %s", name) result = client.failover_instance( request={'name': name, 'data_protection_mode': data_protection_mode}, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance failovered: %s", name) @GoogleBaseHook.fallback_to_default_project_id def get_instance( self, location: str, instance: str, project_id: str = PROVIDE_PROJECT_ID, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Gets the details of a specific Redis instance. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance: The logical name of the Redis instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() name = f"projects/{project_id}/locations/{location}/instances/{instance}" result = client.get_instance( request={'name': name}, retry=retry, timeout=timeout, metadata=metadata, ) self.log.info("Fetched Instance: %s", name) return result @GoogleBaseHook.fallback_to_default_project_id def import_instance( self, location: str, instance: str, input_config: Union[Dict, InputConfig], project_id: str = PROVIDE_PROJECT_ID, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Import a Redis RDB snapshot file from Cloud Storage into a Redis instance. Redis may stop serving during this operation. Instance state will be IMPORTING for entire operation. When complete, the instance will contain only data from the imported file. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance: The logical name of the Redis instance in the customer project. :param input_config: Required. Specify data to be imported. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.redis_v1.types.InputConfig` :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() name = f"projects/{project_id}/locations/{location}/instances/{instance}" self.log.info("Importing Instance: %s", name) result = client.import_instance( request={'name': name, 'input_config': input_config}, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance imported: %s", name) @GoogleBaseHook.fallback_to_default_project_id def list_instances( self, location: str, page_size: int, project_id: str = PROVIDE_PROJECT_ID, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Lists all Redis instances owned by a project in either the specified location (region) or all locations. :param location: The location of the Cloud Memorystore instance (for example europe-west1) If it is specified as ``-`` (wildcard), then all regions available to the project are queried, and the results are aggregated. :param page_size: The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() parent = f"projects/{project_id}/locations/{location}" result = client.list_instances( request={'parent': parent, 'page_size': page_size}, retry=retry, timeout=timeout, metadata=metadata, ) self.log.info("Fetched instances") return result @GoogleBaseHook.fallback_to_default_project_id def update_instance( self, update_mask: Union[Dict, FieldMask], instance: Union[Dict, Instance], project_id: str = PROVIDE_PROJECT_ID, location: Optional[str] = None, instance_id: Optional[str] = None, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Updates the metadata and configuration of a specific Redis instance. :param update_mask: Required. Mask of fields to update. At least one path must be supplied in this field. The elements of the repeated paths field may only include these fields from ``Instance``: - ``displayName`` - ``labels`` - ``memorySizeGb`` - ``redisConfig`` If a dict is provided, it must be of the same form as the protobuf message :class:`~google.protobuf.field_mask_pb2.FieldMask` :param instance: Required. Update description. Only fields specified in ``update_mask`` are updated. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.redis_v1.types.Instance` :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance_id: The logical name of the Redis instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() if isinstance(instance, dict): instance = Instance(**instance) elif not isinstance(instance, Instance): raise AirflowException("instance is not instance of Instance type or python dict") if location and instance_id: name = f"projects/{project_id}/locations/{location}/instances/{instance_id}" instance.name = name self.log.info("Updating instances: %s", instance.name) result = client.update_instance( request={'update_mask': update_mask, 'instance': instance}, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance updated: %s", instance.name) class CloudMemorystoreMemcachedHook(GoogleBaseHook): """ Hook for Google Cloud Memorystore for Memcached service APIs. All the methods in the hook where project_id is used must be called with keyword arguments rather than positional. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account. """ def __init__( self, gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, ) -> None: super().__init__( gcp_conn_id=gcp_conn_id, delegate_to=delegate_to, impersonation_chain=impersonation_chain, ) self._client: Optional[CloudMemcacheClient] = None def get_conn( self, ): """Retrieves client library object that allow access to Cloud Memorystore Memcached service.""" if not self._client: self._client = CloudMemcacheClient(credentials=self._get_credentials()) return self._client @staticmethod def _append_label(instance: cloud_memcache.Instance, key: str, val: str) -> cloud_memcache.Instance: """ Append labels to provided Instance type Labels must fit the regex ``[a-z]([-a-z0-9]*[a-z0-9])?`` (current airflow version string follows semantic versioning spec: x.y.z). :param instance: The proto to append resource_label airflow version to :param key: The key label :param val: :return: The cluster proto updated with new label """ val = val.replace(".", "-").replace("+", "-") instance.labels.update({key: val}) return instance @GoogleBaseHook.fallback_to_default_project_id def apply_parameters( self, node_ids: Sequence[str], apply_all: bool, project_id: str, location: str, instance_id: str, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Will update current set of Parameters to the set of specified nodes of the Memcached Instance. :param node_ids: Nodes to which we should apply the instance-level parameter group. :param apply_all: Whether to apply instance-level parameter group to all nodes. If set to true, will explicitly restrict users from specifying any nodes, and apply parameter group updates to all nodes within the instance. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance_id: The logical name of the Memcached instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() metadata = metadata or () name = CloudMemcacheClient.instance_path(project_id, location, instance_id) self.log.info("Applying update to instance: %s", instance_id) result = client.apply_parameters( name=name, node_ids=node_ids, apply_all=apply_all, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance updated: %s", instance_id) @GoogleBaseHook.fallback_to_default_project_id def create_instance( self, location: str, instance_id: str, instance: Union[Dict, cloud_memcache.Instance], project_id: str, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Creates a Memcached instance based on the specified tier and memory size. By default, the instance is accessible from the project's `default network <https://cloud.google.com/compute/docs/networks-and-firewalls#networks>`__. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance_id: Required. The logical name of the Memcached instance in the customer project with the following restrictions: - Must contain only lowercase letters, numbers, and hyphens. - Must start with a letter. - Must be between 1-40 characters. - Must end with a number or a letter. - Must be unique within the customer project / location :param instance: Required. A Memcached [Instance] resource If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.memcache_v1beta2.types.cloud_memcache.Instance` :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the GCP connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() metadata = metadata or () parent = path_template.expand( "projects/{project}/locations/{location}", project=project_id, location=location ) instance_name = CloudMemcacheClient.instance_path(project_id, location, instance_id) try: instance = client.get_instance( name=instance_name, retry=retry, timeout=timeout, metadata=metadata ) self.log.info("Instance exists. Skipping creation.") return instance except NotFound: self.log.info("Instance not exists.") if isinstance(instance, dict): instance = cloud_memcache.Instance(instance) elif not isinstance(instance, cloud_memcache.Instance): raise AirflowException("instance is not instance of Instance type or python dict") self._append_label(instance, "airflow-version", "v" + version.version) result = client.create_instance( parent=parent, instance_id=instance_id, resource=instance, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance created.") return client.get_instance( name=instance_name, retry=retry, timeout=timeout, metadata=metadata, ) @GoogleBaseHook.fallback_to_default_project_id def delete_instance( self, location: str, instance: str, project_id: str, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Deletes a specific Memcached instance. Instance stops serving and data is deleted. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance: The logical name of the Memcached instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the GCP connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() metadata = metadata or () name = CloudMemcacheClient.instance_path(project_id, location, instance) self.log.info("Fetching Instance: %s", name) instance = client.get_instance( name=name, retry=retry, timeout=timeout, metadata=metadata, ) if not instance: return self.log.info("Deleting Instance: %s", name) result = client.delete_instance( name=name, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Instance deleted: %s", name) @GoogleBaseHook.fallback_to_default_project_id def get_instance( self, location: str, instance: str, project_id: str, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Gets the details of a specific Memcached instance. :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance: The logical name of the Memcached instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the GCP connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() metadata = metadata or () name = CloudMemcacheClient.instance_path(project_id, location, instance) result = client.get_instance(name=name, retry=retry, timeout=timeout, metadata=metadata or ()) self.log.info("Fetched Instance: %s", name) return result @GoogleBaseHook.fallback_to_default_project_id def list_instances( self, location: str, project_id: str, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Lists all Memcached instances owned by a project in either the specified location (region) or all locations. :param location: The location of the Cloud Memorystore instance (for example europe-west1) If it is specified as ``-`` (wildcard), then all regions available to the project are queried, and the results are aggregated. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the GCP connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() metadata = metadata or () parent = path_template.expand( "projects/{project}/locations/{location}", project=project_id, location=location ) result = client.list_instances( parent=parent, retry=retry, timeout=timeout, metadata=metadata, ) self.log.info("Fetched instances") return result @GoogleBaseHook.fallback_to_default_project_id def update_instance( self, update_mask: Union[Dict, FieldMask], instance: Union[Dict, cloud_memcache.Instance], project_id: str, location: Optional[str] = None, instance_id: Optional[str] = None, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Updates the metadata and configuration of a specific Memcached instance. :param update_mask: Required. Mask of fields to update. At least one path must be supplied in this field. The elements of the repeated paths field may only include these fields from ``Instance``: - ``displayName`` If a dict is provided, it must be of the same form as the protobuf message :class:`~google.protobuf.field_mask_pb2.FieldMask`) Union[Dict, google.protobuf.field_mask_pb2.FieldMask] :param instance: Required. Update description. Only fields specified in ``update_mask`` are updated. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.memcache_v1beta2.types.cloud_memcache.Instance` :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance_id: The logical name of the Memcached instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() metadata = metadata or () if isinstance(instance, dict): instance = cloud_memcache.Instance(instance) elif not isinstance(instance, cloud_memcache.Instance): raise AirflowException("instance is not instance of Instance type or python dict") if location and instance_id: name = CloudMemcacheClient.instance_path(project_id, location, instance_id) instance.name = name self.log.info("Updating instances: %s", instance.name) result = client.update_instance( update_mask=update_mask, resource=instance, retry=retry, timeout=timeout, metadata=metadata or () ) result.result() self.log.info("Instance updated: %s", instance.name) @GoogleBaseHook.fallback_to_default_project_id def update_parameters( self, update_mask: Union[Dict, FieldMask], parameters: Union[Dict, cloud_memcache.MemcacheParameters], project_id: str, location: str, instance_id: str, retry: Union[Retry, _MethodDefault] = DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), ): """ Updates the defined Memcached Parameters for an existing Instance. This method only stages the parameters, it must be followed by apply_parameters to apply the parameters to nodes of the Memcached Instance. :param update_mask: Required. Mask of fields to update. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.protobuf.field_mask_pb2.FieldMask` Union[Dict, google.protobuf.field_mask_pb2.FieldMask] :param parameters: The parameters to apply to the instance. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.memcache_v1beta2.types.cloud_memcache.MemcacheParameters` :param location: The location of the Cloud Memorystore instance (for example europe-west1) :param instance_id: The logical name of the Memcached instance in the customer project. :param project_id: Project ID of the project that contains the instance. If set to None or missing, the default project_id from the Google Cloud connection is used. :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be retried. :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. :param metadata: Additional metadata that is provided to the method. """ client = self.get_conn() metadata = metadata or () if isinstance(parameters, dict): parameters = cloud_memcache.MemcacheParameters(parameters) elif not isinstance(parameters, cloud_memcache.MemcacheParameters): raise AirflowException("instance is not instance of MemcacheParameters type or python dict") name = CloudMemcacheClient.instance_path(project_id, location, instance_id) self.log.info("Staging update to instance: %s", instance_id) result = client.update_parameters( name=name, update_mask=update_mask, parameters=parameters, retry=retry, timeout=timeout, metadata=metadata, ) result.result() self.log.info("Update staged for instance: %s", instance_id)

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py

Python

Scripts/RQ2_scripts/3_mapped_by_major_cat_version.py

syful-is/Package-manager-project

a73b5ce715d1c83e15404a502d16cfa748b304fe

[ "MIT" ]

1

2021-03-06T23:19:17.000Z

Scripts/RQ2_scripts/3_mapped_by_major_cat_version.py

syful-is/Package-manager-project

a73b5ce715d1c83e15404a502d16cfa748b304fe

[ "MIT" ]

null

Scripts/RQ2_scripts/3_mapped_by_major_cat_version.py

syful-is/Package-manager-project

a73b5ce715d1c83e15404a502d16cfa748b304fe

[ "MIT" ]

1

2020-08-18T07:05:12.000Z

# -*- coding: utf-8 -*- """ Created on Mon Jun 15 16:50:31 2020 @author: SE """ # -*- coding: utf-8 -*- """ Created on Mon Mar 30 15:59:19 2020 @author: SE """ import re import pandas as pd from matplotlib import pyplot as plt from datetime import datetime from collections import Counter import numpy as np import random import os #Please specify your dataset directory. os.chdir("your dataset directory") df_PM=pd.read_csv("RQ2_LDA_topics_mapped_by_major_detail_27_6_20.csv", low_memory=False) #""" post_category=[] post_language=[] post_Enviroment=[] post_Dependency=[] Document_No=[] Dominant_Topic=[] Topic_Perc_Contrib=[] Keywords=[] Title=[] Id=[] Tags=[] AcceptedAnswerId=[] Major_cat=[] Semi_major=[] for i in range(0, len(df_PM)): if df_PM['Dominant_Topic'][i]==0 or df_PM['Dominant_Topic'][i]==1: Semi_major.append(0) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==6 or df_PM['Dominant_Topic'][i]==8: Semi_major.append(1) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==3 or df_PM['Dominant_Topic'][i]==11 : Semi_major.append(2) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==9 or df_PM['Dominant_Topic'][i]==14 : Semi_major.append(3) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==7 : Semi_major.append(4) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==5: Semi_major.append(5) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==2: Semi_major.append(6) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==10: Semi_major.append(7) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==4 or df_PM['Dominant_Topic'][i]==12: Semi_major.append(8) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) if df_PM['Dominant_Topic'][i]==13: Semi_major.append(9) Major_cat.append(df_PM['Major_cat'][i]) post_category.append(df_PM['post_category'][i]) post_language.append(df_PM['post_language'][i]) post_Enviroment.append(df_PM['post_Enviroment'][i]) post_Dependency.append(df_PM['post_Dependency'][i]) Document_No.append(df_PM['Document_No'][i]) Dominant_Topic.append(df_PM['Dominant_Topic'][i]) Topic_Perc_Contrib.append(df_PM['Topic_Perc_Contrib'][i]) Keywords.append(df_PM['Keywords'][i]) Title.append(df_PM['Title'][i]) Id.append(df_PM['Id'][i]) Tags.append(df_PM['Tags'][i]) AcceptedAnswerId.append(df_PM['AcceptedAnswerId'][i]) dict={'Semi_major':Semi_major, 'Major_cat':Major_cat,'post_Enviroment':post_Enviroment, 'post_Dependency':post_Dependency,'post_category':post_category, 'post_language':post_language,'Document_No':list(df_PM['Document_No']), 'Dominant_Topic':list(df_PM['Dominant_Topic']), 'Topic_Perc_Contrib':list(df_PM['Topic_Perc_Contrib']), 'Keywords':list(df_PM['Keywords']), 'Title':list(df_PM['Title']), 'Id':list(df_PM['Id']), 'Tags':list(df_PM['Tags']), 'AcceptedAnswerId':list(df_PM['AcceptedAnswerId']) } df=pd.DataFrame(dict) df.to_csv("RQ2_LDA_topics_mapped_by_major_minor_detail_27_6_20.csv") #"""

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1

0

null

0

8

0ae8fc58644544dfb45188fd20b684df02983b8b

58,642

py

Python

tests/driver/test_mongodb_driver.py

WGriffing/dagda

b1f669063fcb556df39e0730ce41a72ab9130867

[ "Apache-2.0", "MIT" ]

null

tests/driver/test_mongodb_driver.py

WGriffing/dagda

b1f669063fcb556df39e0730ce41a72ab9130867

[ "Apache-2.0", "MIT" ]

null

tests/driver/test_mongodb_driver.py

WGriffing/dagda

b1f669063fcb556df39e0730ce41a72ab9130867

[ "Apache-2.0", "MIT" ]

null

# # Licensed to Dagda under one or more contributor # license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright # ownership. Dagda licenses this file to you 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 unittest from unittest.mock import Mock import pymongo import datetime from dagda.driver.mongodb_driver import MongoDbDriver import pytest # -- Test suite class MongoDbDriverTestCase(unittest.TestCase): def test_get_vulnerabilities_product_full_happy_path(self): mock_driver = FullGetVulnProdMongoDbDriver() vulnerabilities = mock_driver.get_vulnerabilities('openldap') self.assertEqual(len(vulnerabilities), 6) self.assertDictEqual(vulnerabilities[0],{"CVE-2002-2001":{"cvss_access_vector": "Network", "cveid": "CVE-2002-2002", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": ["AV:N","AC:L","Au:N","C:P","I:P","A:P"], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cweid": "CWE-0" }}) self.assertDictEqual(vulnerabilities[1],{"CVE-2002-2002":{"cvss_access_vector": "Network", "cveid": "CVE-2002-2002", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": ["AV:N","AC:L","Au:N","C:P","I:P","A:P"], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cweid": "CWE-0" }}) self.assertDictEqual(vulnerabilities[2],{"BID-1": { "bugtraq_id": 15128, "class": "Boundary Condition Error", "cve": [ "CVE-2005-2978" ], "local": "no", "remote": "yes", "title": "NetPBM PNMToPNG Buffer Overflow Vulnerability" }}) self.assertDictEqual(vulnerabilities[3],{"BID-2": { "bugtraq_id": 15128, "class": "Boundary Condition Error", "cve": [ "CVE-2005-2978" ], "local": "no", "remote": "yes", "title": "NetPBM PNMToPNG Buffer Overflow Vulnerability" }}) self.assertDictEqual(vulnerabilities[4],{"EXPLOIT_DB_ID-3": {'exploit_db_id': 1, 'description': 'Summary example', 'platform': 'Linux', 'type': 'DoS', 'port': 0 }}) self.assertDictEqual(vulnerabilities[5],{"EXPLOIT_DB_ID-4": {'exploit_db_id': 1, 'description': 'Summary example', 'platform': 'Linux', 'type': 'DoS', 'port': 0 }}) def test_get_vulnerabilities_product_and_version_full_happy_path(self): mock_driver = FullGetVulnProdAndVersionMongoDbDriver() vulnerabilities = mock_driver.get_vulnerabilities('openldap','2.2.20') self.assertEqual(len(vulnerabilities), 6) self.assertDictEqual(vulnerabilities[0],{"CVE-2005-4442":{"cvss_access_vector": "Network", "cveid": "CVE-2005-4442", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": ["AV:N","AC:L","Au:N","C:P","I:P","A:P"], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cweid": "CWE-0" }}) self.assertDictEqual(vulnerabilities[1],{"CVE-2006-2754":{"cvss_access_vector": "Network", "cveid": "CVE-2005-4442", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": ["AV:N","AC:L","Au:N","C:P","I:P","A:P"], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cweid": "CWE-0" }}) self.assertDictEqual(vulnerabilities[2],{"CVE-2007-5707":{"cvss_access_vector": "Network", "cveid": "CVE-2005-4442", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": ["AV:N","AC:L","Au:N","C:P","I:P","A:P"], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cweid": "CWE-0" }}) self.assertDictEqual(vulnerabilities[3],{"CVE-2011-4079":{"cvss_access_vector": "Network", "cveid": "CVE-2005-4442", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": ["AV:N","AC:L","Au:N","C:P","I:P","A:P"], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now().strftime('%d-%m-%Y'), "cweid": "CWE-0" }}) self.assertDictEqual(vulnerabilities[4],{"BID-83610": { "bugtraq_id": 15128, "class": "Boundary Condition Error", "cve": [ "CVE-2005-2978" ], "local": "no", "remote": "yes", "title": "NetPBM PNMToPNG Buffer Overflow Vulnerability" }}) self.assertDictEqual(vulnerabilities[5],{"BID-83843": { "bugtraq_id": 15128, "class": "Boundary Condition Error", "cve": [ "CVE-2005-2978" ], "local": "no", "remote": "yes", "title": "NetPBM PNMToPNG Buffer Overflow Vulnerability" }}) def test_bulk_insert_cves(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_cves(["CVE-2002-2001#Vendor 1#Product 1#1.1.0#2001", "CVE-2002-2002#Vendor 2#Product 2#2.1.1#2002"]) mock_driver.db.cve.insert_many.assert_called_once_with([ {'cve_id': 'CVE-2002-2001', 'vendor': 'Vendor 1', 'product': 'Product 1', 'version': '1.1.0', 'year': 2001}, {'cve_id': 'CVE-2002-2002', 'vendor': 'Vendor 2', 'product': 'Product 2', 'version': '2.1.1', 'year': 2002}]) def test_bulk_insert_bids(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_bids(["1#Product 1#1.1.0", "2#Product 2#2.1.1"]) mock_driver.db.bid.insert_many.assert_called_once_with([ {'bugtraq_id': 1, 'product': 'Product 1', 'version': '1.1.0'}, {'bugtraq_id': 2, 'product': 'Product 2', 'version': '2.1.1'}]) def test_bulk_insert_exploit_db_ids(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_exploit_db_ids(["1#Product 1#1.1.0", "2#Product 2#2.1.1"]) mock_driver.db.exploit_db.insert_many.assert_called_once_with([ {'exploit_db_id': 1, 'product': 'Product 1', 'version': '1.1.0'}, {'exploit_db_id': 2, 'product': 'Product 2', 'version': '2.1.1'}]) def test_bulk_insert_sysdig_falco_events(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_sysdig_falco_events([{"container_id": "ef45au6756jh", "image_name": "alpine", "output": "16:47:44.080226697: Warning Sensitive file opened for reading by non-trusted program (user=root command=cat /etc/shadow file=/etc/shadow)", "priority": "Warning", "rule": "read_sensitive_file_untrusted", "time": "2016-06-06T23:47:44.080226697Z" }]) mock_driver.db.falco_events.insert_many.assert_called_once_with([{"container_id": "ef45au6756jh", "image_name": "alpine", "output": "16:47:44.080226697: Warning Sensitive file opened for reading by non-trusted program (user=root command=cat /etc/shadow file=/etc/shadow)", "priority": "Warning", "rule": "read_sensitive_file_untrusted", "time": 1465256864.080226 }]) def test_bulk_insert_rhsa(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhsa([{"vendor": "redhat", "product": "enterprise_linux", "version": "4", "rhsa_id": "RHSA-2010:0002-01"}]) mock_driver.db.rhsa.insert_many.assert_called_once_with([{"vendor": "redhat", "product": "enterprise_linux", "version": "4", "rhsa_id": "RHSA-2010:0002-01"}]) def test_bulk_insert_rhsa_empty(self): # Test bug #85 mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhsa([]) mock_driver.db.rhsa.insert_many.assert_not_called() def test_bulk_insert_rhba(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhba([{"vendor": "redhat", "product": "enterprise_linux", "version": "4", "rhba_id": "RHBA-2010:0002-01"}]) mock_driver.db.rhba.insert_many.assert_called_once_with([{"vendor": "redhat", "product": "enterprise_linux", "version": "4", "rhba_id": "RHBA-2010:0002-01"}]) def test_bulk_insert_rhba_empty(self): # Test bug #85 mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhba([]) mock_driver.db.rhba.insert_many.assert_not_called() def test_bulk_insert_rhsa_info(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhsa_info([{"cve": ["CVE-20101"], "title": "Test", "description": "Test CVE", "severity": "high", "rhsa_id": "RHSA-2010:0002-01"}]) mock_driver.db.rhsa_info.insert_many.assert_called_once_with([{"cve": ["CVE-20101"], "title": "Test", "description": "Test CVE", "severity": "high", "rhsa_id": "RHSA-2010:0002-01"}]) def test_bulk_insert_rhsa_info_empty(self): # Test bug #85 mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhsa_info([]) mock_driver.db.rhsa_info.insert_many.assert_not_called() def test_bulk_insert_rhba_info(self): mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhba_info([{"cve": ["CVE-20101"], "title": "Test", "description": "Test CVE", "severity": "high", "rhba_id": "RHBA-2010:0002-01"}]) mock_driver.db.rhba_info.insert_many.assert_called_once_with([{"cve": ["CVE-20101"], "title": "Test", "description": "Test CVE", "severity": "high", "rhba_id": "RHBA-2010:0002-01"}]) def test_bulk_insert_rhba_info_empty(self): # Test bug #85 mock_driver = BulkInfoMongoDbDriver() mock_driver.bulk_insert_rhba_info([]) mock_driver.db.rhba_info.insert_many.assert_not_called() def test_is_fp_false(self): mock_driver = IsFPMongoDbDriver() is_fp = mock_driver.is_fp('alpine', 'zlib') self.assertFalse(is_fp) def test_is_fp_true(self): mock_driver = IsFPMongoDbDriver() is_fp = mock_driver.is_fp('alpine', 'musl', '1.1.15') self.assertTrue(is_fp) def test_get_max_bid_inserted_zero(self): mock_driver = MaxBidZeroMongoDbDriver() max_bid = mock_driver.get_max_bid_inserted() self.assertEqual(max_bid, 0) def test_get_max_bid_inserted_not_zero(self): mock_driver = MaxBidNotZeroMongoDbDriver() max_bid = mock_driver.get_max_bid_inserted() self.assertEqual(max_bid, 83843) def test_remove_only_cve_for_update_empty(self): mock_driver = RemoveOnlyCVEForUpdateEmptyCollectionNamesMongoDbDriver() cve_year = mock_driver.remove_only_cve_for_update() self.assertEqual(cve_year, 2002) def test_remove_only_cve_for_update_minor_than_2002(self): mock_driver = RemoveOnlyCVEForUpdateMinorThan2002MongoDbDriver() cve_year = mock_driver.remove_only_cve_for_update() self.assertEqual(cve_year, 2002) def test_remove_only_cve_for_update_equals_2011(self): mock_driver = RemoveOnlyCVEForUpdateEquals2011MongoDbDriver() cve_year = mock_driver.remove_only_cve_for_update() self.assertEqual(cve_year, 2011) def test_get_init_db_process_status_none(self): mock_driver = GetEmptyInitDBStatusMongoDbDriver() status = mock_driver.get_init_db_process_status() self.assertEqual(status, {'status': 'None', 'timestamp': None}) def test_get_init_db_process_status_updated(self): mock_driver = GetInitDBStatusMongoDbDriver() status = mock_driver.get_init_db_process_status() self.assertEqual(status, {'status': 'Updated', 'timestamp': None}) def test_update_fp(self): mock_driver = UpdateFPMongoDbDriver() updated = mock_driver.update_product_vulnerability_as_fp('alpine', 'musl', '1.1.15') self.assertTrue(updated) mock_driver.db.image_history.update.assert_called_once_with({'_id': "5915ed36ff1f081833551af5"}, {"_id": "5915ed36ff1f081833551af5", "timestamp": 1494609523.342605, "status": "Completed", "image_name": "alpine", "static_analysis": {"prog_lang_dependencies": { "dependencies_details": {"java": [], "python": [], "js": [], "ruby": [], "php": [], "nodejs": []}, "vuln_dependencies": 0}, "os_packages": {"vuln_os_packages": 1, "os_packages_details": [ {"version": "1.1.15", "vulnerabilities": [{ "CVE-2016-8859": { "cvss_integrity_impact": "Partial", "cvss_access_vector": "Network", "cweid": "CWE-190", "cvss_access_complexity": "Low", "cvss_confidentiality_impact": "Partial", "mod_date": "07-03-2017", "cvss_exploit": 10, "cvss_vector": [ "AV:N", "AC:L", "Au:N", "C:P", "I:P", "A:P"], "cvss_authentication": "None required", "summary": "Multiple integer overflows in the TRE library and musl libc allow attackers to cause memory corruption via a large number of (1) states or (2) tags, which triggers an out-of-bounds write.", "cveid": "CVE-2016-8859", "cvss_impact": 6.4, "pub_date": "13-02-2017", "cvss_base": 7.5, "cvss_availability_impact": "Partial"}}], "product": "musl", "is_vulnerable": True, "is_false_positive": True}, {"version": "1.25.1", "vulnerabilities": [], "product": "busybox", "is_vulnerable": False, "is_false_positive": False}, {"version": "3.0.4", "vulnerabilities": [], "product": "alpine-baselayout", "is_vulnerable": False, "is_false_positive": False}, {"version": "1.3", "vulnerabilities": [], "product": "alpine-keys", "is_vulnerable": False, "is_false_positive": False}, {"version": "2.4.4", "vulnerabilities": [], "product": "libressl2.4-libcrypto", "is_vulnerable": False, "is_false_positive": False}, {"version": "2.4.4", "vulnerabilities": [], "product": "libressl2.4-libssl", "is_vulnerable": False, "is_false_positive": False}, {"version": "1.2.8", "vulnerabilities": [{ "BID-95131": { "cve": [ "CVE-2016-9840"], "bugtraq_id": 95131, "title": "zlib Multiple Denial of Service Vulnerabilities", "remote": "yes", "local": "no", "class": "Design Error"}}], "product": "zlib", "is_vulnerable": True, "is_false_positive": False}, {"version": "2.6.8", "vulnerabilities": [], "product": "apk-tools", "is_vulnerable": False, "is_false_positive": False}, {"version": "1.1.6", "vulnerabilities": [], "product": "scanelf", "is_vulnerable": False, "is_false_positive": False}, {"version": "1.1.15", "vulnerabilities": [], "product": "musl-utils", "is_vulnerable": False, "is_false_positive": False}, {"version": "0.7", "vulnerabilities": [], "product": "libc-utils", "is_vulnerable": False, "is_false_positive": False}], "total_os_packages": 11, "ok_os_packages": 10}}}) def test_get_docker_image_all_history(self): mock_driver = GetFullHistoryMongoDbDriver() history = mock_driver.get_docker_image_all_history() self.assertEqual(history, [{ "anomalies": 0, "image_name": "jboss/wildfly", "libs_vulns": 1, "os_vulns": 2, "malware_bins": 0, "reportid": "58790707ed253944951ec5ba", "start_date": "2017-05-12 17:18:43.342605", "status": "Completed" },{ "anomalies": 2, "image_name": "jboss/wildfly", "libs_vulns": 0, "os_vulns": 0, "malware_bins": 0, "reportid": "58790707ed253944951ec5ba", "start_date": "2017-05-12 17:18:43.342605", "status": "Completed" }]) def test_get_docker_image_history(self): mock_driver = GetDockerImageHistory() history = mock_driver.get_docker_image_history('jboss/wildfly') self.assertEqual(history, [{ "id": "586f7631ed25396a829baaf4", "image_name": "jboss/wildfly", "timestamp": "2017-05-12 17:18:43.342605", "status": "Completed", "runtime_analysis": { "container_id": "69dbf26ab368", "start_timestamp": "2017-05-12 17:18:43.342605", "stop_timestamp": "2017-05-12 17:18:43.342605", "anomalous_activities_detected": { "anomalous_counts_by_severity": { "Warning": 2 }, "anomalous_activities_details": [{ "output": "10:49:47.492517329: Warning Unexpected setuid call by non-sudo, non-root program (user=<NA> command=ping 8.8.8.8 uid=<NA>) container=thirsty_spence (id=69dbf26ab368)", "priority": "Warning", "rule": "Non sudo setuid", "time": "2017-01-06 10:49:47.492516" }, { "output": "10:49:53.181654702: Warning Unexpected setuid call by non-sudo, non-root program (user=<NA> command=ping 8.8.4.4 uid=<NA>) container=thirsty_spence (id=69dbf26ab368)", "priority": "Warning", "rule": "Non sudo setuid", "time": "2017-01-06 10:49:53.181653" }] } } }]) # -- Mock classes class FullGetVulnProdMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() cursor_cve = self.db.cve.find.return_value cursor_cve.sort.return_value = [{'cve_id': "CVE-2002-2001"}, {'cve_id': "CVE-2002-2002"}] cursor_bid = self.db.bid.find.return_value cursor_bid.sort.return_value = [{'bugtraq_id': 1}, {'bugtraq_id': 2}] cursor_expl = self.db.exploit_db.find.return_value cursor_expl.sort.return_value = [{'exploit_db_id': 3}, {'exploit_db_id': 4}] self.db.cve_info.find_one.return_value = {"cvss_access_vector": "Network", "_id": "58d11025100e75000e789c9a", "cveid": "CVE-2002-2002", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": [ "AV:N", "AC:L", "Au:N", "C:P", "I:P", "A:P" ], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now(), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now(), "cweid": "CWE-0" } self.db.exploit_db_info.find_one.return_value = {'_id': '58d11025100e75000e789c9a', 'exploit_db_id': 1, 'description': 'Summary example', 'platform': 'Linux', 'type': 'DoS', 'port': 0 } self.db.bid_info.find_one.return_value = { "_id": "'58d11025100e75000e789c9a", "bugtraq_id": 15128, "class": "Boundary Condition Error", "cve": [ "CVE-2005-2978" ], "local": "no", "remote": "yes", "title": "NetPBM PNMToPNG Buffer Overflow Vulnerability" } cursor_rhba = self.db.rhba.find.return_value cursor_rhba.sort.return_value = [] cursor_rhsa = self.db.rhsa.find.return_value cursor_rhsa.sort.return_value = [] class FullGetVulnProdAndVersionMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() cursor_cve = self.db.cve.find.return_value cursor_cve.sort.return_value = [{'cve_id': "CVE-2005-4442"}, {'cve_id': "CVE-2006-2754"}, {'cve_id': "CVE-2007-5707"}, {'cve_id': "CVE-2011-4079"}] cursor_bid = self.db.bid.find.return_value cursor_bid.sort.return_value = [{'bugtraq_id': 83610}, {'bugtraq_id': 83843}] cursor_expl = self.db.exploit_db.find.return_value cursor_expl.sort.return_value = [] cursor_rhba = self.db.rhba.find.return_value cursor_rhba.sort.return_value = [] cursor_rhsa = self.db.rhsa.find.return_value cursor_rhsa.sort.return_value = [] self.db.cve_info.find_one.return_value = {"cvss_access_vector": "Network", "_id": "58d11025100e75000e789c9a", "cveid": "CVE-2005-4442", "cvss_base": 7.5, "cvss_integrity_impact": "Partial", "cvss_availability_impact": "Partial", "summary": "Summary example", "cvss_confidentiality_impact": "Partial", "cvss_vector": [ "AV:N", "AC:L", "Au:N", "C:P", "I:P", "A:P" ], "cvss_authentication": "None required", "cvss_access_complexity": "Low", "pub_date": datetime.datetime.now(), "cvss_impact": 6.4, "cvss_exploit": 10.0, "mod_date": datetime.datetime.now(), "cweid": "CWE-0" } self.db.exploit_db_info.find_one.return_value = {'_id': '58d11025100e75000e789c9a', 'exploit_db_id': 1, 'description': 'Summary example', 'platform': 'Linux', 'type': 'DoS', 'port': 0 } self.db.bid_info.find_one.return_value = { "_id": "'58d11025100e75000e789c9a", "bugtraq_id": 15128, "class": "Boundary Condition Error", "cve": [ "CVE-2005-2978" ], "local": "no", "remote": "yes", "title": "NetPBM PNMToPNG Buffer Overflow Vulnerability" } class IsFPMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() cursor_image_history = self.db.image_history.find.return_value cursor_image_history.sort.return_value = [ {"_id": "5915ed36ff1f081833551af5", "timestamp": 1494609523.342605, "status": "Completed", "image_name": "alpine", "static_analysis": {"prog_lang_dependencies": { "dependencies_details": {"java": [], "python": [], "js": [], "ruby": [], "php": [], "nodejs": []}, "vuln_dependencies": 0}, "os_packages": {"vuln_os_packages": 1, "os_packages_details": [ {"version": "1.1.15", "vulnerabilities": [{"CVE-2016-8859": {"cvss_integrity_impact": "Partial", "cvss_access_vector": "Network", "cweid": "CWE-190", "cvss_access_complexity": "Low", "cvss_confidentiality_impact": "Partial", "mod_date": "07-03-2017", "cvss_exploit": 10, "cvss_vector": ["AV:N", "AC:L", "Au:N", "C:P", "I:P", "A:P"], "cvss_authentication": "None required", "summary": "Multiple integer overflows in the TRE library and musl libc allow attackers to cause memory corruption via a large number of (1) states or (2) tags, which triggers an out-of-bounds write.", "cveid": "CVE-2016-8859", "cvss_impact": 6.4, "pub_date": "13-02-2017", "cvss_base": 7.5, "cvss_availability_impact": "Partial"}}], "product": "musl", "is_vulnerable": True, "is_false_positive" : True}, {"version": "1.25.1", "vulnerabilities": [], "product": "busybox", "is_vulnerable": False, "is_false_positive" : False}, {"version": "3.0.4", "vulnerabilities": [], "product": "alpine-baselayout", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.3", "vulnerabilities": [], "product": "alpine-keys", "is_vulnerable": False, "is_false_positive" : False}, {"version": "2.4.4", "vulnerabilities": [], "product": "libressl2.4-libcrypto", "is_vulnerable": False, "is_false_positive" : False}, {"version": "2.4.4", "vulnerabilities": [], "product": "libressl2.4-libssl", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.2.8", "vulnerabilities": [{"BID-95131": {"cve": ["CVE-2016-9840"], "bugtraq_id": 95131, "title": "zlib Multiple Denial of Service Vulnerabilities", "remote": "yes", "local": "no", "class": "Design Error"}}], "product": "zlib", "is_vulnerable": True, "is_false_positive" : False}, {"version": "2.6.8", "vulnerabilities": [], "product": "apk-tools", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.1.6", "vulnerabilities": [], "product": "scanelf", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.1.15", "vulnerabilities": [], "product": "musl-utils", "is_vulnerable": False, "is_false_positive" : False}, {"version": "0.7", "vulnerabilities": [], "product": "libc-utils", "is_vulnerable": False, "is_false_positive" : False}], "total_os_packages": 11, "ok_os_packages": 10}}}] class UpdateFPMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() cursor_image_history = self.db.image_history.find.return_value cursor_image_history.sort.return_value = [ {"_id": "5915ed36ff1f081833551af5", "timestamp": 1494609523.342605, "status": "Completed", "image_name": "alpine", "static_analysis": {"prog_lang_dependencies": { "dependencies_details": {"java": [], "python": [], "js": [], "ruby": [], "php": [], "nodejs": []}, "vuln_dependencies": 0}, "os_packages": {"vuln_os_packages": 2, "os_packages_details": [ {"version": "1.1.15", "vulnerabilities": [{"CVE-2016-8859": {"cvss_integrity_impact": "Partial", "cvss_access_vector": "Network", "cweid": "CWE-190", "cvss_access_complexity": "Low", "cvss_confidentiality_impact": "Partial", "mod_date": "07-03-2017", "cvss_exploit": 10, "cvss_vector": ["AV:N", "AC:L", "Au:N", "C:P", "I:P", "A:P"], "cvss_authentication": "None required", "summary": "Multiple integer overflows in the TRE library and musl libc allow attackers to cause memory corruption via a large number of (1) states or (2) tags, which triggers an out-of-bounds write.", "cveid": "CVE-2016-8859", "cvss_impact": 6.4, "pub_date": "13-02-2017", "cvss_base": 7.5, "cvss_availability_impact": "Partial"}}], "product": "musl", "is_vulnerable": True, "is_false_positive" : False}, {"version": "1.25.1", "vulnerabilities": [], "product": "busybox", "is_vulnerable": False, "is_false_positive" : False}, {"version": "3.0.4", "vulnerabilities": [], "product": "alpine-baselayout", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.3", "vulnerabilities": [], "product": "alpine-keys", "is_vulnerable": False, "is_false_positive" : False}, {"version": "2.4.4", "vulnerabilities": [], "product": "libressl2.4-libcrypto", "is_vulnerable": False, "is_false_positive" : False}, {"version": "2.4.4", "vulnerabilities": [], "product": "libressl2.4-libssl", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.2.8", "vulnerabilities": [{"BID-95131": {"cve": ["CVE-2016-9840"], "bugtraq_id": 95131, "title": "zlib Multiple Denial of Service Vulnerabilities", "remote": "yes", "local": "no", "class": "Design Error"}}], "product": "zlib", "is_vulnerable": True, "is_false_positive" : False}, {"version": "2.6.8", "vulnerabilities": [], "product": "apk-tools", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.1.6", "vulnerabilities": [], "product": "scanelf", "is_vulnerable": False, "is_false_positive" : False}, {"version": "1.1.15", "vulnerabilities": [], "product": "musl-utils", "is_vulnerable": False, "is_false_positive" : False}, {"version": "0.7", "vulnerabilities": [], "product": "libc-utils", "is_vulnerable": False, "is_false_positive" : False}], "total_os_packages": 11, "ok_os_packages": 9}}}] self.db.image_history.update.return_value = True class BulkInfoMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() self.db.cve.create_index.return_value = True self.db.bid.create_index.return_value = True self.db.exploit_db.create_index.return_value = True self.db.falco_events.count.return_value = 0 self.db.falco_events.create_index.return_value = True self.db.collection_names.return_value = [] class MaxBidZeroMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() self.db.collection_names.return_value = [] class MaxBidNotZeroMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() self.db.collection_names.return_value = ['bid'] self.db.bid.count.return_value = 10 cursor_bid = self.db.bid.find.return_value sort_bid = cursor_bid.sort.return_value sort_bid.limit.return_value = [{'bugtraq_id': 83843}] class RemoveOnlyCVEForUpdateEmptyCollectionNamesMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() self.db.collection_names.return_value = [] class RemoveOnlyCVEForUpdateMinorThan2002MongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() self.db.collection_names.return_value = ['cve'] self.db.cve.count.return_value = 10 cursor_cve = self.db.cve.find.return_value sort_cve = cursor_cve.sort.return_value sort_cve.limit.return_value = [{'year': 2002}] self.db.cve.drop.return_value = True self.db.cve_info.drop.return_value = True class RemoveOnlyCVEForUpdateEquals2011MongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() self.db.collection_names.return_value = ['cve'] self.db.cve.count.return_value = 10 cursor_cve = self.db.cve.find.return_value sort_cve = cursor_cve.sort.return_value sort_cve.limit.return_value = [{'year': 2012}] self.db.cve.remove.return_value = True self.db.cve_info.remove.return_value = True class GetEmptyInitDBStatusMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() cursor = self.db.init_db_process_status.find.return_value cursor.sort.return_value = [] class GetInitDBStatusMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() cursor = self.db.init_db_process_status.find.return_value cursor.sort.return_value = [{'status': 'Updated', 'timestamp': None}] class GetFullHistoryMongoDbDriver(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() cursor = self.db.image_history.find.return_value cursor.sort.return_value = [{'_id': '58790707ed253944951ec5ba', 'image_name': 'jboss/wildfly', 'status': 'Completed', 'timestamp':1494609523.342605, 'static_analysis':{'os_packages':{'vuln_os_packages':2}, 'malware_binaries':[], 'prog_lang_dependencies':{'vuln_dependencies':1}}, }, {'_id': '58790707ed253944951ec5ba', 'image_name': 'jboss/wildfly', 'status': 'Completed', 'timestamp': 1494609523.342605, 'runtime_analysis':{"anomalous_activities_detected": {"anomalous_counts_by_severity": {"Warning": 2}}}}] class GetDockerImageHistory(MongoDbDriver): def __init__(self): self.client = Mock(spec=pymongo.MongoClient) self.db = Mock() self.db.image_history.count.return_value = 1 cursor = self.db.image_history.find.return_value cursor.sort.return_value = [{ "_id": "586f7631ed25396a829baaf4", "image_name": "jboss/wildfly", "timestamp": 1494609523.342605, "status": "Completed", "runtime_analysis": { "container_id": "69dbf26ab368", "start_timestamp": 1494609523.342605, "stop_timestamp": 1494609523.342605, "anomalous_activities_detected": { "anomalous_counts_by_severity": { "Warning": 2 }, "anomalous_activities_details": [{ "output": "10:49:47.492517329: Warning Unexpected setuid call by non-sudo, non-root program (user=<NA> command=ping 8.8.8.8 uid=<NA>) container=thirsty_spence (id=69dbf26ab368)", "priority": "Warning", "rule": "Non sudo setuid", "time": "2017-01-06 10:49:47.492516" }, { "output": "10:49:53.181654702: Warning Unexpected setuid call by non-sudo, non-root program (user=<NA> command=ping 8.8.4.4 uid=<NA>) container=thirsty_spence (id=69dbf26ab368)", "priority": "Warning", "rule": "Non sudo setuid", "time": "2017-01-06 10:49:53.181653" }] } } }] self.db.image_history.find_one.return_value = { "_id": "586f7631ed25396a829baaf4", "image_name": "jboss/wildfly", "timestamp": 1494609523.342605, "status": "Completed", "runtime_analysis": { "container_id": "69dbf26ab368", "start_timestamp": 1494609523.342605, "stop_timestamp": 1494609523.342605, "anomalous_activities_detected": { "anomalous_counts_by_severity": { "Warning": 2 }, "anomalous_activities_details": [{ "output": "10:49:47.492517329: Warning Unexpected setuid call by non-sudo, non-root program (user=<NA> command=ping 8.8.8.8 uid=<NA>) container=thirsty_spence (id=69dbf26ab368)", "priority": "Warning", "rule": "Non sudo setuid", "time": "2017-01-06 10:49:47.492516" }, { "output": "10:49:53.181654702: Warning Unexpected setuid call by non-sudo, non-root program (user=<NA> command=ping 8.8.4.4 uid=<NA>) container=thirsty_spence (id=69dbf26ab368)", "priority": "Warning", "rule": "Non sudo setuid", "time": "2017-01-06 10:49:53.181653" }] } } } self.db.falco_events.find.return_value = [] if __name__ == '__main__': unittest.main()

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7c32693024a75f08a6a13c8ce55346cd5ff8064d

894

py

Python

settings/incar/write_incar_yaml.py

hegdevinayi/vasp_input_generator

ee127d034b5d7c57fe8b2026c66366b6f2960c41

[ "MIT" ]

null

settings/incar/write_incar_yaml.py

hegdevinayi/vasp_input_generator

ee127d034b5d7c57fe8b2026c66366b6f2960c41

[ "MIT" ]

null

settings/incar/write_incar_yaml.py

hegdevinayi/vasp_input_generator

ee127d034b5d7c57fe8b2026c66366b6f2960c41

[ "MIT" ]

null

import yaml sett_dict = {} with open('INCAR.relaxation' , 'r') as fr: incar = fr.readlines() for row in incar: if not row.strip(): continue if row.strip()[0] == '#': continue tag, value = row.strip().split('=') tag = tag.strip() value = value.strip() sett_dict[tag] = value with open('incar_relaxation.yml', 'w') as fw: yaml.dump(sett_dict, fw, default_flow_style=False) sett_dict = {} with open('INCAR.static' , 'r') as fr: incar = fr.readlines() for row in incar: if not row.strip(): continue if row.strip()[0] == '#': continue tag, value = row.strip().split('=') tag = tag.strip() value = value.strip() sett_dict[tag] = value with open('incar_static.yml', 'w') as fw: yaml.dump(sett_dict, fw, default_flow_style=False)

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