xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

fce4abd58335a0b28d0cc68f213d513a81cecdba

34

py

Python

test/tokenize/t26.py

timmartin/skulpt

2e3a3fbbaccc12baa29094a717ceec491a8a6750

[ "MIT" ]

2,671

2015-01-03T08:23:25.000Z

2022-03-31T06:15:48.000Z

test/tokenize/t26.py

timmartin/skulpt

2e3a3fbbaccc12baa29094a717ceec491a8a6750

[ "MIT" ]

972

2015-01-05T08:11:00.000Z

2022-03-29T13:47:15.000Z

test/tokenize/t26.py

timmartin/skulpt

2e3a3fbbaccc12baa29094a717ceec491a8a6750

[ "MIT" ]

845

2015-01-03T19:53:36.000Z

2022-03-29T18:34:22.000Z

def d22(a, b, c=2, d=2, *k): pass

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138

py

Python

others/edge/speech_recognition/pytorch/src/deepspeech/decoder/__init__.py

luluseptember/inference

acbc7b0bf288343ed81e62b69dea8afec03d679b

[ "Apache-2.0" ]

49

2018-11-02T15:04:40.000Z

2021-11-16T18:11:39.000Z

others/edge/speech_recognition/pytorch/src/deepspeech/decoder/__init__.py

luluseptember/inference

acbc7b0bf288343ed81e62b69dea8afec03d679b

[ "Apache-2.0" ]

6

2018-12-03T19:29:49.000Z

2020-05-16T15:34:33.000Z

others/edge/speech_recognition/pytorch/src/deepspeech/decoder/__init__.py

luluseptember/inference

acbc7b0bf288343ed81e62b69dea8afec03d679b

[ "Apache-2.0" ]

16

2018-11-08T11:52:54.000Z

2021-11-16T18:11:28.000Z

from deepspeech.decoder.beam import BeamCTCDecoder # noqa: F401 from deepspeech.decoder.greedy import GreedyCTCDecoder # noqa: F401

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py

Python

ebdataset/__init__.py

tihbe/python-ebdataset

4d16822a3a6b45882124a8d7f7e124bd39a75868

[ "MIT" ]

7

2020-07-30T09:31:08.000Z

2022-02-22T10:49:23.000Z

ebdataset/__init__.py

tihbe/python-ebdataset

4d16822a3a6b45882124a8d7f7e124bd39a75868

[ "MIT" ]

3

2021-01-15T07:12:31.000Z

2021-10-07T02:59:32.000Z

ebdataset/__init__.py

tihbe/python-ebdataset

4d16822a3a6b45882124a8d7f7e124bd39a75868

[ "MIT" ]

1

2021-03-01T13:27:06.000Z

import ebdataset.vision as vision import ebdataset.audio as audio import ebdataset.generated as generated import ebdataset.bci as bci from .utils.units import *

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1e44fa78dcee224d8353cd2720c4dcf6fe1b8ccd

188

py

Python

tests/parsing/parser/test_str_to_ipv6.py

LeeeeT/valtypes

0c5df3cbab296bf9ca34544604fbb9496a41e01a

[ "MIT" ]

3

2022-02-22T12:59:59.000Z

2022-03-10T14:12:25.000Z

tests/parsing/parser/test_str_to_ipv6.py

LeeeeT/valtypes

0c5df3cbab296bf9ca34544604fbb9496a41e01a

[ "MIT" ]

3

2022-03-08T13:33:38.000Z

2022-03-25T03:31:56.000Z

tests/parsing/parser/test_str_to_ipv6.py

LeeeeT/valtypes

0c5df3cbab296bf9ca34544604fbb9496a41e01a

[ "MIT" ]

null

from ipaddress import IPv6Address from valtypes import parse def test() -> None: """ It parses str to ipv6 """ assert parse(IPv6Address, "1::2") == IPv6Address("1::2")

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py

Python

aikit/models/random_forest_addins.py

LionelMassoulard/aikit

98b2abaa3bf47ab46f2fd3c270010293de06dba9

[ "BSD-2-Clause" ]

null

aikit/models/random_forest_addins.py

LionelMassoulard/aikit

98b2abaa3bf47ab46f2fd3c270010293de06dba9

[ "BSD-2-Clause" ]

null

aikit/models/random_forest_addins.py

LionelMassoulard/aikit

98b2abaa3bf47ab46f2fd3c270010293de06dba9

[ "BSD-2-Clause" ]

null

# -*- coding: utf-8 -*- """ Created on Wed Aug 1 08:59:01 2018 @author: Lionel Massoulard """ from sklearn.exceptions import NotFittedError from sklearn.base import BaseEstimator, ClassifierMixin, TransformerMixin, RegressorMixin from sklearn.linear_model import LogisticRegression, Ridge from sklearn.decomposition import TruncatedSVD from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor from aikit.transformers.model_wrapper import ModelWrapper import numpy as np # In[] def compute_node_norm_classification_tree(tree): """ takes a DecisionTree Regressor and returns a value corresponding to the norm of each node, as well the coefficient of each node """ value = tree.tree_.value ch_left = tree.tree_.children_left ch_right = tree.tree_.children_right nb_nodes = tree.tree_.node_count parents = -np.ones(nb_nodes, dtype=np.int32) nodes_index = np.arange(nb_nodes) parents[ch_left[ch_left != -1]] = nodes_index[ch_left != -1] parents[ch_right[ch_right != -1]] = nodes_index[ch_right != -1] sum_v = value.sum(axis=2, keepdims=True) proba = value / sum_v ii = parents != -1 ii_root = parents == -1 nodes_value = np.zeros(proba.shape, dtype=np.float32) nodes_value[ii] = proba[ii, :, :] - proba[parents[ii], :, :] nodes_value[ii_root] = proba[ii_root, :, :] delta_norm = (nodes_value ** 2).sum(axis=2).sum(axis=1) nodes_norm = sum_v[:, 0, 0] * delta_norm return nodes_norm, nodes_value def compute_node_norm_regression_tree(tree): """ takes a DecisionTree Classifier and returns a value corresponding to the norm of each node, as well the coefficient of each node """ ch_left = tree.tree_.children_left ch_right = tree.tree_.children_right value = tree.tree_.value n_node_samples = tree.tree_.n_node_samples nb_nodes = tree.tree_.node_count parents = -np.ones(nb_nodes, dtype=np.int32) nodes_index = np.arange(nb_nodes) parents[ch_left[ch_left != -1]] = nodes_index[ch_left != -1] parents[ch_right[ch_right != -1]] = nodes_index[ch_right != -1] ii = parents != -1 ii_root = parents == -1 nodes_value = np.zeros(value.shape, dtype=np.float32) nodes_value[ii] = value[ii, :, :] - value[parents[ii], :, :] nodes_value[ii_root] = value[ii_root, :, :] delta_norm = (nodes_value ** 2).sum(axis=2).sum(axis=1) nodes_norm = n_node_samples * delta_norm return nodes_norm, nodes_value def compute_node_dept_is_leaves(tree): """ takes a Decision Tree and returns information about each nodes : depts and if it a leaf or not """ n_nodes = tree.tree_.node_count children_left = tree.tree_.children_left children_right = tree.tree_.children_right nodes_depth = np.zeros(shape=n_nodes, dtype=np.int32) is_leaves = np.zeros(shape=n_nodes, dtype=bool) stack = [(0, -1)] # seed is the root node id and its parent depth while len(stack) > 0: node_id, parent_depth = stack.pop() nodes_depth[node_id] = parent_depth + 1 # If we have a test node if children_left[node_id] != children_right[node_id]: stack.append((children_left[node_id], parent_depth + 1)) stack.append((children_right[node_id], parent_depth + 1)) else: is_leaves[node_id] = True return nodes_depth, is_leaves def compute_node_norm_regression_forest(forest): all_nodes_norms = [] all_nodes_values = [] for tree in forest.estimators_: node_norm, delta_value = compute_node_norm_regression_tree(tree) all_nodes_norms.append(node_norm) all_nodes_values.append(delta_value) forest_nodes_norm = np.concatenate(all_nodes_norms, axis=0) forest_nodes_value = np.concatenate(all_nodes_values, axis=0) forest_nodes_value /= len(forest.estimators_) return forest_nodes_norm, forest_nodes_value def compute_node_norm_classification_forest(forest): all_nodes_norms = [] all_nodes_values = [] for tree in forest.estimators_: nodes_norm, nodes_value = compute_node_norm_classification_tree(tree) all_nodes_norms.append(nodes_norm) all_nodes_values.append(nodes_value) forest_nodes_norm = np.concatenate(all_nodes_norms, axis=0) forest_nodes_value = np.concatenate(all_nodes_values, axis=0) forest_nodes_value /= len(forest.estimators_) return forest_nodes_norm, forest_nodes_value class WaveRandomForestClassifier(BaseEstimator, ClassifierMixin): """ RandomForest based classifier but with nodes that are removed See Paper: Wavelet decomposition of Random Forests http://www.jmlr.org/papers/volume17/15-203/15-203.pdf """ def __init__( self, n_estimators=100, criterion="gini", max_depth=None, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0.0, max_features="auto", max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, bootstrap=True, oob_score=False, n_jobs=1, random_state=None, verbose=0, warm_start=False, class_weight=None, nodes_to_keep=0.9, ): self.n_estimators = n_estimators self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_weight_fraction_leaf = min_weight_fraction_leaf self.max_features = max_features self.max_leaf_nodes = max_leaf_nodes self.min_impurity_decrease = min_impurity_decrease self.min_impurity_split = min_impurity_split self.bootstrap = bootstrap self.oob_score = oob_score self.n_jobs = n_jobs self.random_state = random_state self.verbose = verbose self.warm_start = warm_start self.class_weight = class_weight self.nodes_to_keep = nodes_to_keep self.forest = None def fit(self, X, y): # 1) create RandomForest self.forest = RandomForestClassifier( n_estimators=self.n_estimators, criterion=self.criterion, max_depth=self.max_depth, min_samples_split=self.min_samples_split, min_samples_leaf=self.min_samples_leaf, min_weight_fraction_leaf=self.min_weight_fraction_leaf, max_features=self.max_features, max_leaf_nodes=self.max_leaf_nodes, min_impurity_decrease=self.min_impurity_decrease, min_impurity_split=self.min_impurity_split, bootstrap=self.bootstrap, oob_score=self.oob_score, n_jobs=self.n_jobs, random_state=self.random_state, verbose=self.verbose, warm_start=self.warm_start, class_weight=self.class_weight, ) # 2) fit it self.forest.fit(X, y) self.n_outputs_ = self.forest.n_outputs_ # 3) retrieve node norms and values self.nodes_norm, self.nodes_value = compute_node_norm_classification_forest(self.forest) # 4) filter nodes self._nodes_order = np.argsort(-self.nodes_norm) if self.nodes_to_keep is not None: if self.nodes_to_keep < 1: nodes_to_keep = int(len(self._nodes_order) * self.nodes_to_keep) else: nodes_to_keep = int(self.nodes_to_keep) self._ind_nodes_to_keep = self._nodes_order[:nodes_to_keep] else: self._ind_nodes_to_keep = None return self def _set_nodes_to_keep(self, nodes_to_keep): """ change the number of waweletts to keep withtout refitting the underlying random forest """ self.nodes_to_keep = nodes_to_keep if self.forest is not None: if self.nodes_to_keep is None: self._ind_nodes_to_keep = None else: if self.nodes_to_keep < 1: nodes_to_keep = int(len(self._nodes_order) * self.nodes_to_keep) else: nodes_to_keep = int(self.nodes_to_keep) self._ind_nodes_to_keep = self._nodes_order[:nodes_to_keep] def predict_proba(self, X): if self.forest is None: raise NotFittedError("You should fit the model first") path, _ = self.forest.decision_path(X) if self._ind_nodes_to_keep is not None: predict_proba_filtered = [ path[:, self._ind_nodes_to_keep].dot(self.nodes_value[self._ind_nodes_to_keep, n, :]) for n in range(self.nodes_value.shape[1]) ] else: predict_proba_filtered = [ path[:, :].dot(self.nodes_value[:, n, :]) for n in range(self.nodes_value.shape[1]) ] for p in predict_proba_filtered: p[p < 0] = 0 p[p > 1] = 1 if len(predict_proba_filtered) == 1: return predict_proba_filtered[0] else: return predict_proba_filtered @property def classes_(self): return self.forest.classes_ def predict(self, X): """Predict class for X. The predicted class of an input sample is a vote by the trees in the forest, weighted by their probability estimates. That is, the predicted class is the one with highest mean probability estimate across the trees. Parameters ---------- X : array-like or sparse matrix of shape = [n_samples, n_features] The input samples. Internally, its dtype will be converted to ``dtype=np.float32``. If a sparse matrix is provided, it will be converted into a sparse ``csr_matrix``. Returns ------- y : array of shape = [n_samples] or [n_samples, n_outputs] The predicted classes. """ # Copied from base forest proba = self.predict_proba(X) if self.n_outputs_ == 1: return self.classes_.take(np.argmax(proba, axis=1), axis=0) else: n_samples = proba[0].shape[0] predictions = np.zeros((n_samples, self.n_outputs_)) for k in range(self.n_outputs_): predictions[:, k] = self.classes_[k].take(np.argmax(proba[k], axis=1), axis=0) return predictions def predict_log_proba(self, X): """Predict class log-probabilities for X. The predicted class log-probabilities of an input sample is computed as the log of the mean predicted class probabilities of the trees in the forest. Parameters ---------- X : array-like or sparse matrix of shape = [n_samples, n_features] The input samples. Internally, its dtype will be converted to ``dtype=np.float32``. If a sparse matrix is provided, it will be converted into a sparse ``csr_matrix``. Returns ------- p : array of shape = [n_samples, n_classes], or a list of n_outputs such arrays if n_outputs > 1. The class probabilities of the input samples. The order of the classes corresponds to that in the attribute `classes_`. """ # Copied from base forest proba = self.predict_proba(X) if self.n_outputs_ == 1: return np.log(proba) else: for k in range(self.n_outputs_): proba[k] = np.log(proba[k]) return proba class WaveRandomForestRegressor(BaseEstimator, RegressorMixin): """ RandomForest based classifier but with nodes that are removed See Paper: Wavelet decomposition of Random Forests http://www.jmlr.org/papers/volume17/15-203/15-203.pdf """ def __init__( self, n_estimators=100, criterion="mse", max_depth=None, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0.0, max_features="auto", max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, bootstrap=True, oob_score=False, n_jobs=1, random_state=None, verbose=0, warm_start=False, nodes_to_keep=0.9, ): self.n_estimators = n_estimators self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_weight_fraction_leaf = min_weight_fraction_leaf self.max_features = max_features self.max_leaf_nodes = max_leaf_nodes self.min_impurity_decrease = min_impurity_decrease self.min_impurity_split = min_impurity_split self.bootstrap = bootstrap self.oob_score = oob_score self.n_jobs = n_jobs self.random_state = random_state self.verbose = verbose self.warm_start = warm_start self.nodes_to_keep = nodes_to_keep self.forest = None def fit(self, X, y): # 1) create RandomForest self.forest = RandomForestRegressor( n_estimators=self.n_estimators, criterion=self.criterion, max_depth=self.max_depth, min_samples_split=self.min_samples_split, min_samples_leaf=self.min_samples_leaf, min_weight_fraction_leaf=self.min_weight_fraction_leaf, max_features=self.max_features, max_leaf_nodes=self.max_leaf_nodes, min_impurity_decrease=self.min_impurity_decrease, min_impurity_split=self.min_impurity_split, bootstrap=self.bootstrap, oob_score=self.oob_score, n_jobs=self.n_jobs, random_state=self.random_state, verbose=self.verbose, warm_start=self.warm_start, ) # 2) fit it self.forest.fit(X, y) self.n_outputs_ = self.forest.n_outputs_ # 3) retrieve node norms and values self.nodes_norm, self.nodes_value = compute_node_norm_regression_forest(self.forest) # 4) filter nodes self._nodes_order = np.argsort(-self.nodes_norm) if self.nodes_to_keep is not None: if self.nodes_to_keep < 1: nodes_to_keep = int(len(self._nodes_order) * self.nodes_to_keep) else: nodes_to_keep = int(self.nodes_to_keep) self._ind_nodes_to_keep = self._nodes_order[:nodes_to_keep] else: self._ind_nodes_to_keep = None return self def _set_nodes_to_keep(self, nodes_to_keep): """ change the number of waweletts to keep withtout refitting the underlying random forest """ self.nodes_to_keep = nodes_to_keep if self.forest is not None: if self.nodes_to_keep is None: self._ind_nodes_to_keep = None else: if self.nodes_to_keep < 1: nodes_to_keep = int(len(self._nodes_order) * self.nodes_to_keep) else: nodes_to_keep = int(self.nodes_to_keep) self._ind_nodes_to_keep = self._nodes_order[:nodes_to_keep] def predict(self, X): if self.forest is None: raise NotFittedError("You should fit the model first") path, _ = self.forest.decision_path(X) if self._ind_nodes_to_keep is not None: predict_proba_filtered = [ path[:, self._ind_nodes_to_keep].dot(self.nodes_value[self._ind_nodes_to_keep, n, :]) for n in range(self.nodes_value.shape[1]) ] else: predict_proba_filtered = [ path[:, :].dot(self.nodes_value[:, n, :]) for n in range(self.nodes_value.shape[1]) ] if len(predict_proba_filtered) == 1: return predict_proba_filtered[0][:, 0] else: return predict_proba_filtered # In[] class _RandomForestLinear(BaseEstimator, ClassifierMixin): """ This model is a mixture of a classical RandomForest with on linear model plug after it The idea is to fit a RandomForest and use the node as features for a linear model. So re-optimizing globally the structure created by the RandomForest Parameters ---------- n_estimators : int, default = 100 number of trees of the RandomForest criterion : string, default = 'gini' or 'mse' the splitting criterion for the RandomForest max_deatures : string or number, default = 'auto', the number of features per split max_depth : int or None, default = None the maximum depth of trees random_state : int or None random seed for RandomForest other_rf_params : dict or None additionnal parameters to be passed to the RandomForest do_svd : boolean, default = False if True will do an SVD before calling the linear algorithm svd_n_components : int, default = 100 number of svd components C : float, default = 1 linear model C parameter """ is_regression = None def __init__( self, n_estimators=100, criterion="gini", max_features="auto", max_depth=None, random_state=None, nodes_to_keep=None, other_rf_params=None, do_svd=False, svd_n_components=100, C=1, ): self.n_estimators = n_estimators self.criterion = criterion self.max_features = max_features self.max_depth = max_depth self.random_state = random_state self.do_svd = do_svd self.svd_n_components = svd_n_components self.nodes_to_keep = nodes_to_keep self.other_rf_params = other_rf_params self.C = C def fit(self, X, y=None): if self.is_regression: rf_klass = RandomForestRegressor lin_klass = Ridge kwargs = {"alpha": self.C} else: rf_klass = RandomForestClassifier lin_klass = LogisticRegression kwargs = {"C": self.C} if self.other_rf_params is None: other_rf_params = {} else: other_rf_params = self.other_rf_params self.forest = rf_klass( n_estimators=self.n_estimators, criterion=self.criterion, max_features=self.max_features, max_depth=self.max_depth, random_state=self.random_state, **other_rf_params ) self.forest.fit(X, y) Xnode_onehot, _ = self.forest.decision_path(X) # Filter of Nodes ? if self.nodes_to_keep is not None: if self.is_regression: nodes_norm, nodes_value = compute_node_norm_regression_forest(self.forest) else: nodes_norm, nodes_value = compute_node_norm_regression_forest(self.forest) nodes_order = np.argsort(-nodes_norm) if self.nodes_to_keep < 1: nodes_to_keep = int(len(nodes_order) * self.nodes_to_keep) else: nodes_to_keep = int(self.nodes_to_keep) self._ind_nodes_to_keep = nodes_order[:nodes_to_keep] Xnode_onehot = Xnode_onehot[:, self._ind_nodes_to_keep] else: self._ind_nodes_to_keep = None if self.do_svd: self.svd = TruncatedSVD(n_components=100) Xsvd = self.svd.fit_transform(Xnode_onehot) else: Xsvd = Xnode_onehot self.linear = lin_klass(**kwargs) self.linear.fit(Xsvd, y) return self def predict(self, X): Xnode_onehot, _ = self.forest.decision_path(X) if self._ind_nodes_to_keep is not None: Xnode_onehot = Xnode_onehot[:, self._ind_nodes_to_keep] if self.do_svd: Xsvd = self.svd.transform(Xnode_onehot) else: Xsvd = Xnode_onehot return self.linear.predict(Xsvd) class RandomForestLogit(_RandomForestLinear): __doc__ = _RandomForestLinear.__doc__ is_regression = False @property def classes_(self): return self.linear.classes_ def predict_proba(self, X): Xnode_onehot, _ = self.forest.decision_path(X) if self._ind_nodes_to_keep is not None: Xnode_onehot = Xnode_onehot[:, self._ind_nodes_to_keep] if self.do_svd: Xsvd = self.svd.transform(Xnode_onehot) else: Xsvd = Xnode_onehot return self.linear.predict_proba(Xsvd) def predict_log_proba(self, X): Xnode_onehot, _ = self.forest.decision_path(X) if self._ind_nodes_to_keep is not None: Xnode_onehot = Xnode_onehot[:, self._ind_nodes_to_keep] if self.do_svd: Xsvd = self.svd.transform(Xnode_onehot) else: Xsvd = Xnode_onehot return self.linear.predict_log_proba(Xsvd) class RandomForestRidge(_RandomForestLinear): __doc__ = _RandomForestLinear.__doc__ is_regression = True def __init__( self, n_estimators=100, criterion="mse", # change default argument max_features="auto", max_depth=None, random_state=None, nodes_to_keep=None, other_rf_params=None, do_svd=False, svd_n_components=100, C=1, ): self.n_estimators = n_estimators self.criterion = criterion self.max_features = max_features self.max_depth = max_depth self.random_state = random_state self.nodes_to_keep = nodes_to_keep self.do_svd = do_svd self.svd_n_components = svd_n_components self.other_rf_params = other_rf_params self.C = C # In[] # In[] class _RandomForestTransformerAbstract(BaseEstimator, TransformerMixin): """ This model is a transforms a classical RandomForest into a transformer by returning not the prediction but the nodes. The process is the following : 1. fit a RandomForest 2. get the node dummy variable (using decision path) 3. (optional) filter some of the nodes 4. (optional) apply an SVD It can be useful to * craft non-linear features that can be given to a linear algorithm * create a 'supervised' clustering algorithm * create a similarity between observations based on their nodes * ... Parameters ---------- n_estimators : int, default = 100 number of trees of the RandomForest criterion : string, default = 'gini' or 'mse' the splitting criterion for the RandomForest max_deatures : string or number, default = 'auto', the number of features per split max_depth : int or None, default = None the maximum depth of trees random_state : int or None random seed for RandomForest nodes_to_keep : int, float or None number of nodes to keep in result (filter by their norm), if None no filter, if float < 1 taken as a percentage of the total number of nodes other_rf_params : dict or None additionnal parameters to be passed to the RandomForest do_svd : boolean, default = False if True will do an SVD before calling the linear algorithm svd_n_components : int, default = 100 number of svd components """ is_regression = None def __init__( self, n_estimators=100, criterion="gini", max_features="auto", max_depth=None, random_state=None, nodes_to_keep=None, other_rf_params=None, do_svd=False, svd_n_components=100, ): self.n_estimators = n_estimators self.criterion = criterion self.max_features = max_features self.max_depth = max_depth self.random_state = random_state self.nodes_to_keep = nodes_to_keep self.do_svd = do_svd self.svd_n_components = svd_n_components self.other_rf_params = other_rf_params def fit(self, X, y): self._fit_transform(X, y, do_fit=True, do_transform=False) return self def transform(self, X): Xres = self._fit_transform(X, y=None, do_fit=False, do_transform=True) return Xres def fit_transform(self, X, y): Xres = self._fit_transform(X, y, do_fit=True, do_transform=True) return Xres def _fit_transform(self, X, y, do_fit, do_transform): if do_fit: if self.other_rf_params is None: other_rf_params = {} else: other_rf_params = self.other_rf_params if self.is_regression: rf_klass = RandomForestRegressor else: rf_klass = RandomForestClassifier ## 1) create RF and fit it self.forest = rf_klass( n_estimators=self.n_estimators, criterion=self.criterion, max_features=self.max_features, max_depth=self.max_depth, random_state=self.random_state, **other_rf_params ) self.forest.fit(X, y) ## 2) retrieve node id Xnode_onehot, _ = self.forest.decision_path(X) ### 3) filter nodes if do_fit: if self.nodes_to_keep is not None: if self.is_regression: nodes_norm, nodes_value = compute_node_norm_regression_forest(self.forest) else: nodes_norm, nodes_value = compute_node_norm_regression_forest(self.forest) nodes_order = np.argsort(-nodes_norm) if self.nodes_to_keep < 1: nodes_to_keep = int(len(nodes_order) * self.nodes_to_keep) else: nodes_to_keep = int(self.nodes_to_keep) self._ind_nodes_to_keep = nodes_order[:nodes_to_keep] else: self._ind_nodes_to_keep = None if self._ind_nodes_to_keep is not None: Xnode_onehot = Xnode_onehot[:, self._ind_nodes_to_keep] if self.do_svd: if do_fit: self.svd = TruncatedSVD(n_components=self.svd_n_components) Xsvd = self.svd.fit_transform(Xnode_onehot) else: Xsvd = self.svd.transform(Xnode_onehot) else: Xsvd = Xnode_onehot if do_fit: if self.do_svd: self._features_names = ["RFNODE_SVD_%d" % i for i in range(Xsvd.shape[1])] else: self._features_names = ["RFNODE_%d" % i for i in range(Xsvd.shape[1])] if do_transform: return Xsvd else: return self def get_feature_names(self): return self._features_names class _RandomForestClassifierTransformer(_RandomForestTransformerAbstract): __doc__ = _RandomForestTransformerAbstract.__doc__ is_regression = False class _RandomForestRegressorTransformer(_RandomForestTransformerAbstract): __doc__ = _RandomForestTransformerAbstract.__doc__ is_regression = True class RandomForestClassifierTransformer(ModelWrapper): __doc__ = _RandomForestTransformerAbstract.__doc__ def __init__( self, n_estimators=100, criterion="gini", max_features="auto", max_depth=None, random_state=None, nodes_to_keep=None, do_svd=False, svd_n_components=100, other_rf_params=None, columns_to_use=None, desired_output_type=None, ): self.n_estimators = n_estimators self.criterion = criterion self.max_features = max_features self.max_depth = max_depth self.random_state = random_state self.nodes_to_keep = nodes_to_keep self.do_svd = do_svd self.svd_n_components = svd_n_components self.other_rf_params = other_rf_params self.columns_to_use = columns_to_use self.desired_output_type = desired_output_type super(RandomForestClassifierTransformer, self).__init__( columns_to_use=columns_to_use, regex_match=False, work_on_one_column_only=False, all_columns_at_once=True, accepted_input_types=None, column_prefix=None, desired_output_type=desired_output_type, must_transform_to_get_features_name=False, dont_change_columns=False, ) def _get_model(self, X, y=None): return _RandomForestClassifierTransformer( n_estimators=self.n_estimators, criterion=self.criterion, max_features=self.max_features, random_state=self.random_state, nodes_to_keep=self.nodes_to_keep, do_svd=self.do_svd, svd_n_components=self.svd_n_components, other_rf_params=self.other_rf_params, ) class RandomForestRegressorTransformer(ModelWrapper): __doc__ = _RandomForestTransformerAbstract.__doc__ def __init__( self, n_estimators=100, criterion="mse", max_features="auto", max_depth=None, random_state=None, nodes_to_keep=None, do_svd=False, svd_n_components=100, other_rf_params=None, columns_to_use=None, desired_output_type=None, ): self.n_estimators = n_estimators self.criterion = criterion self.max_features = max_features self.max_depth = max_depth self.random_state = random_state self.nodes_to_keep = nodes_to_keep self.do_svd = do_svd self.svd_n_components = svd_n_components self.other_rf_params = other_rf_params self.columns_to_use = columns_to_use self.desired_output_type = desired_output_type super(RandomForestRegressorTransformer, self).__init__( columns_to_use=columns_to_use, regex_match=False, work_on_one_column_only=False, all_columns_at_once=True, accepted_input_types=None, column_prefix=None, desired_output_type=desired_output_type, must_transform_to_get_features_name=False, dont_change_columns=False, ) def _get_model(self, X, y=None): return _RandomForestRegressorTransformer( n_estimators=self.n_estimators, criterion=self.criterion, max_features=self.max_features, random_state=self.random_state, nodes_to_keep=self.nodes_to_keep, do_svd=self.do_svd, svd_n_components=self.svd_n_components, other_rf_params=self.other_rf_params, )

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1e79a0ecc10621a8f2e165c3a44af2b3c5a1e3e6

10,472

py

Python

function/sample_staging.py

the-fool/gcp-auto-net-tagger

552ec87e933df5714daba2fd2f5addd5dde48bff

[ "Apache-2.0" ]

null

function/sample_staging.py

the-fool/gcp-auto-net-tagger

552ec87e933df5714daba2fd2f5addd5dde48bff

[ "Apache-2.0" ]

null

function/sample_staging.py

the-fool/gcp-auto-net-tagger

552ec87e933df5714daba2fd2f5addd5dde48bff

[ "Apache-2.0" ]

1

2021-08-20T21:39:42.000Z

sample = { "asset": { "ancestors": [ "projects/163454223397", "organizations/673763744309" ], "assetType": "compute.googleapis.com/Instance", "name": "//compute.googleapis.com/projects/sc-vice-test/zones/us-central1-a/instances/instance-1", "resource": { "data": { "allocationAffinity": { "consumeAllocationType": "ANY_ALLOCATION" }, "canIpForward": False, "confidentialInstanceConfig": { "enableConfidentialCompute": False }, "cpuPlatform": "Unknown CPU Platform", "creationTimestamp": "2021-04-22T13:51:49.576-07:00", "deletionProtection": False, "description": "", "disks": [ { "autoDelete": True, "boot": True, "deviceName": "instance-1", "diskSizeGb": "10", "guestOsFeatures": [ { "type": "UEFI_COMPATIBLE" }, { "type": "VIRTIO_SCSI_MULTIQUEUE" } ], "index": 0, "interface": "SCSI", "licenses": [ "https://www.googleapis.com/compute/v1/projects/debian-cloud/global/licenses/debian-10-buster" ], "mode": "READ_WRITE", "source": 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"https://www.googleapis.com/compute/v1/projects/sc-vice-test/zones/us-central1-a/instances/instance-1", "serviceAccounts": [ { "email": "163454223397-compute@developer.gserviceaccount.com", "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only", "https://www.googleapis.com/auth/logging.write", "https://www.googleapis.com/auth/monitoring.write", "https://www.googleapis.com/auth/servicecontrol", "https://www.googleapis.com/auth/service.management.readonly", "https://www.googleapis.com/auth/trace.append" ] } ], "shieldedInstanceConfig": { "enableIntegrityMonitoring": True, "enableSecureBoot": False, "enableVtpm": True }, "shieldedInstanceIntegrityPolicy": { "updateAutoLearnPolicy": True }, "startRestricted": False, "status": "STAGING", "tags": { "fingerprint": "42WmSpB8rSM=" }, "zone": "https://www.googleapis.com/compute/v1/projects/sc-vice-test/zones/us-central1-a" }, "discoveryDocumentUri": "https://www.googleapis.com/discovery/v1/apis/compute/v1/rest", "discoveryName": 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"https://www.googleapis.com/discovery/v1/apis/compute/v1/rest", "discoveryName": "Instance", "location": "us-central1-a", "parent": "//cloudresourcemanager.googleapis.com/projects/163454223397", "version": "v1" }, "updateTime": "2021-04-22T20:51:49.759449Z" }, "priorAssetState": "PRESENT", "window": { "startTime": "2021-04-22T20:51:50.801629Z" } }

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Python

tests/test_examples.py

wilsonify/tensorflow-examples

2271c666b33c7a74047c7196783ab04e9aee8362

[ "MIT" ]

2

2019-11-21T02:43:24.000Z

2020-08-12T04:48:39.000Z

tests/test_examples.py

wilsonify/tensorflow-examples

2271c666b33c7a74047c7196783ab04e9aee8362

[ "MIT" ]

null

tests/test_examples.py

wilsonify/tensorflow-examples

2271c666b33c7a74047c7196783ab04e9aee8362

[ "MIT" ]

1

2021-02-06T12:36:58.000Z

import pytest from tensorflow_examples.examples import ( convolutional_neural_networks, distributed_tensorflow, queues_threads, text_and_visualizations, up_and_running, word_embeddings_and_rnns ) from tensorflow_examples.examples.convolutional_neural_networks import cifar_cnn, mnist_cnn def test_smoke(): print("is anything on fire") @pytest.mark.skip(reason='not implemented yet') def test_distribute(): distributed_tensorflow.distribute() @pytest.mark.skip(reason='not implemented yet') def test_distribute_run(): distributed_tensorflow.distribute_run() @pytest.mark.skip(reason='not implemented yet') def test_queue_basic(): queues_threads.queue_basic() @pytest.mark.skip(reason='not implemented yet') def test_tfrecords_end_to_end(): queues_threads.tfrecords_end_to_end() @pytest.mark.skip(reason='not implemented yet') def test_tfrecords_read_write(): queues_threads.tfrecords_read_write() @pytest.mark.skip(reason='not implemented yet') def test_BasicRNNCell(): text_and_visualizations.BasicRNNCell() @pytest.mark.skip(reason='not implemented yet') def test_LSTM_supervised_embeddings(): text_and_visualizations.LSTM_supervised_embeddings() @pytest.mark.skip(reason='not implemented yet') def test_scan_example(): text_and_visualizations.scan_example() @pytest.mark.skip(reason='not implemented yet') def test_vanilla_rnn_with_tfboard(): text_and_visualizations.vanilla_rnn_with_tfboard() @pytest.mark.skip(reason='not implemented yet') def test_softmax(): up_and_running.softmax() @pytest.mark.skip(reason='not implemented yet') def test_GRU_pretrained_GloVe(): word_embeddings_and_rnns.GRU_pretrained_GloVe() @pytest.mark.skip(reason='not implemented yet') def test_word2vec(): word_embeddings_and_rnns.word2vec() @pytest.mark.skip(reason='not implemented yet') def test_build_second_net(cifar_data_manager): cifar_data_manager.build_second_net() @pytest.mark.skip(reason='not implemented yet') def test_create_cifar_image(): convolutional_neural_networks.cifar_cnn.CifarDataManager.create_cifar_image() @pytest.mark.skip(reason='not implemented yet') def test_display_cifar(): convolutional_neural_networks.cifar_cnn.CifarDataManager.display_cifar() @pytest.mark.skip(reason='not implemented yet') def test_one_hot(): convolutional_neural_networks.cifar_cnn.CifarDataManager.one_hot() @pytest.mark.skip(reason='not implemented yet') def test_run_simple_net(): convolutional_neural_networks.cifar_cnn.CifarDataManager.run_simple_net() @pytest.mark.skip(reason='not implemented yet') def test_unpickle(): convolutional_neural_networks.cifar_cnn.CifarDataManager.unpickle() @pytest.mark.skip(reason='not implemented yet') def test_mnist_cnn(): convolutional_neural_networks.mnist_cnn() @pytest.mark.skip(reason='not implemented yet') def test_distribute(): distributed_tensorflow.distribute() @pytest.mark.skip(reason='not implemented yet') def test_distribute_run(): distributed_tensorflow.distribute_run() @pytest.mark.skip(reason='not implemented yet') def test_queue_basic(): queues_threads.queue_basic() @pytest.mark.skip(reason='not implemented yet') def test_tfrecords_end_to_end(): queues_threads.tfrecords_end_to_end() @pytest.mark.skip(reason='not implemented yet') def test_tfrecords_read_write(): queues_threads.tfrecords_read_write() @pytest.mark.skip(reason='not implemented yet') def test_BasicRNNCell(): text_and_visualizations.BasicRNNCell() @pytest.mark.skip(reason='not implemented yet') def test_LSTM_supervised_embeddings(): text_and_visualizations.LSTM_supervised_embeddings() @pytest.mark.skip(reason='not implemented yet') def test_get_sentence_batch(): text_and_visualizations.LSTM_supervised_embeddings.get_sentence_batch() @pytest.mark.skip(reason='not implemented yet') def test_scan_example(): text_and_visualizations.scan_example() @pytest.mark.skip(reason='not implemented yet') def test_vanilla_rnn_with_tfboard(): text_and_visualizations.vanilla_rnn_with_tfboard() @pytest.mark.skip(reason='not implemented yet') def test_hello_world_main_1(): from tensorflow_examples.examples.up_and_running import hello_world up_and_running.hello_world.main_1() @pytest.mark.skip(reason='not implemented yet') def test_hello_world_main_2(): from tensorflow_examples.examples.up_and_running import hello_world hello_world.main_2() @pytest.mark.skip(reason='not implemented yet') def test_softmax(): up_and_running.softmax() @pytest.mark.skip(reason='not implemented yet') def test_GRU_pretrained_GloVe(): word_embeddings_and_rnns.GRU_pretrained_GloVe() @pytest.mark.skip(reason='not implemented yet') def test_word2vec(): word_embeddings_and_rnns.word2vec()

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1

0

9

1ebfb5d5a4e7c7b6fd9f3f44b8153a8b24152e43

20,933

py

Python

port/modules/font/dvsm_21.py

diskman88/mpython-desktop-robot

01cd15fbeeba521ab874cf66f94d3909c4f8c39a

[ "MIT" ]

53

2018-10-15T12:01:24.000Z

2019-11-22T09:31:02.000Z

port/modules/font/dvsm_21.py

diskman88/mpython-desktop-robot

01cd15fbeeba521ab874cf66f94d3909c4f8c39a

[ "MIT" ]

10

2018-10-17T13:42:19.000Z

2019-11-25T06:42:40.000Z

port/modules/font/dvsm_21.py

diskman88/mpython-desktop-robot

01cd15fbeeba521ab874cf66f94d3909c4f8c39a

[ "MIT" ]

26

2018-12-04T03:53:39.000Z

2019-11-22T03:40:05.000Z

# Code generated by font-to-py.py. # Font: dsm.ttf version = '0.26' def height(): return 21 def max_width(): return 12 def hmap(): return True def reverse(): return False def monospaced(): return False def min_ch(): return 32 def max_ch(): return 126 _font =\ b'\x0c\x00\x00\x00\x7c\x00\xfe\x00\x87\x00\x03\x00\x03\x00\x07\x00'\ b'\x0e\x00\x1c\x00\x38\x00\x30\x00\x30\x00\x30\x00\x00\x00\x30\x00'\ b'\x30\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0c\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x0c\x00\x00\x00\xc0\x00\xc0\x00'\ b'\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00'\ b'\xc0\x00\x00\x00\x00\x00\xc0\x00\xc0\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x0c\x00\x00\x00\xcc\x00\xcc\x00\xcc\x00\xcc\x00'\ b'\xcc\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x0c\x00\x00\x00\x06\x60\x04\x40\x0c\xc0\x0c\xc0\x7f\xf0\x7f\xf0'\ b'\x08\x80\x19\x80\x19\x80\xff\xe0\xff\xe0\x33\x00\x33\x00\x22\x00'\ b'\x22\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0c\x00\x00\x00'\ b'\x08\x00\x08\x00\x3e\x00\x7f\x00\xe9\x00\xc8\x00\xc8\x00\x68\x00'\ b'\x3e\x00\x0b\x00\x09\x80\x09\x80\x8b\x80\xff\x00\x7e\x00\x08\x00'\ b'\x08\x00\x08\x00\x00\x00\x00\x00\x0c\x00\x00\x00\x78\x00\xcc\x00'\ b'\xcc\x00\xcc\x00\xcc\x00\x78\xc0\x03\x00\x06\x00\x18\x00\x63\xc0'\ b'\x06\x60\x06\x60\x06\x60\x06\x60\x03\xc0\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x0c\x00\x00\x00\x1f\x00\x3f\x00\x30\x00\x30\x00'\ b'\x30\x00\x18\x00\x18\x00\x7c\x00\x6e\x60\xc6\x60\xc3\x60\xc3\xc0'\ b'\xe1\x80\x7e\xc0\x3c\xe0\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x0c\x00\x00\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ 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b'\x00\x00\x00\x00\xc1\x80\x63\x00\x63\x00\x63\x00\x36\x00\x36\x00'\ b'\x3e\x00\x1c\x00\x1c\x00\x0c\x00\x18\x00\x18\x00\x18\x00\x70\x00'\ b'\x70\x00\x00\x00\x0c\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\xff\x80\xff\x80\x07\x00\x06\x00\x0e\x00\x1c\x00\x38\x00\x30\x00'\ b'\x60\x00\xff\x80\xff\x80\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x0c\x00\x00\x00\x0f\x00\x1f\x00\x18\x00\x18\x00\x18\x00\x18\x00'\ b'\x18\x00\x18\x00\xf0\x00\xf0\x00\x38\x00\x18\x00\x18\x00\x18\x00'\ b'\x18\x00\x18\x00\x1f\x00\x0f\x00\x00\x00\x00\x00\x0c\x00\x00\x00'\ b'\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00'\ b'\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00\xc0\x00'\ b'\xc0\x00\xc0\x00\xc0\x00\xc0\x00\x0c\x00\x00\x00\xf0\x00\xf8\x00'\ b'\x18\x00\x18\x00\x18\x00\x18\x00\x18\x00\x18\x00\x0f\x00\x0f\x00'\ b'\x1c\x00\x18\x00\x18\x00\x18\x00\x18\x00\x18\x00\xf8\x00\xf0\x00'\ b'\x00\x00\x00\x00\x0c\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x78\x40\xff\xc0\x87\x80\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ _index =\ b'\x00\x00\x2c\x00\x2c\x00\x58\x00\x58\x00\x84\x00\x84\x00\xb0\x00'\ b'\xb0\x00\xdc\x00\xdc\x00\x08\x01\x08\x01\x34\x01\x34\x01\x60\x01'\ b'\x60\x01\x8c\x01\x8c\x01\xb8\x01\xb8\x01\xe4\x01\xe4\x01\x10\x02'\ b'\x10\x02\x3c\x02\x3c\x02\x68\x02\x68\x02\x94\x02\x94\x02\xc0\x02'\ b'\xc0\x02\xec\x02\xec\x02\x18\x03\x18\x03\x44\x03\x44\x03\x70\x03'\ b'\x70\x03\x9c\x03\x9c\x03\xc8\x03\xc8\x03\xf4\x03\xf4\x03\x20\x04'\ b'\x20\x04\x4c\x04\x4c\x04\x78\x04\x78\x04\xa4\x04\xa4\x04\xd0\x04'\ b'\xd0\x04\xfc\x04\xfc\x04\x28\x05\x28\x05\x54\x05\x54\x05\x80\x05'\ b'\x80\x05\xac\x05\xac\x05\xd8\x05\xd8\x05\x04\x06\x04\x06\x30\x06'\ b'\x30\x06\x5c\x06\x5c\x06\x88\x06\x88\x06\xb4\x06\xb4\x06\xe0\x06'\ b'\xe0\x06\x0c\x07\x0c\x07\x38\x07\x38\x07\x64\x07\x64\x07\x90\x07'\ b'\x90\x07\xbc\x07\xbc\x07\xe8\x07\xe8\x07\x14\x08\x14\x08\x40\x08'\ b'\x40\x08\x6c\x08\x6c\x08\x98\x08\x98\x08\xc4\x08\xc4\x08\xf0\x08'\ b'\xf0\x08\x1c\x09\x1c\x09\x48\x09\x48\x09\x74\x09\x74\x09\xa0\x09'\ b'\xa0\x09\xcc\x09\xcc\x09\xf8\x09\xf8\x09\x24\x0a\x24\x0a\x50\x0a'\ b'\x50\x0a\x7c\x0a\x7c\x0a\xa8\x0a\xa8\x0a\xd4\x0a\xd4\x0a\x00\x0b'\ b'\x00\x0b\x2c\x0b\x2c\x0b\x58\x0b\x58\x0b\x84\x0b\x84\x0b\xb0\x0b'\ b'\xb0\x0b\xdc\x0b\xdc\x0b\x08\x0c\x08\x0c\x34\x0c\x34\x0c\x60\x0c'\ b'\x60\x0c\x8c\x0c\x8c\x0c\xb8\x0c\xb8\x0c\xe4\x0c\xe4\x0c\x10\x0d'\ b'\x10\x0d\x3c\x0d\x3c\x0d\x68\x0d\x68\x0d\x94\x0d\x94\x0d\xc0\x0d'\ b'\xc0\x0d\xec\x0d\xec\x0d\x18\x0e\x18\x0e\x44\x0e\x44\x0e\x70\x0e'\ b'\x70\x0e\x9c\x0e\x9c\x0e\xc8\x0e\xc8\x0e\xf4\x0e\xf4\x0e\x20\x0f'\ b'\x20\x0f\x4c\x0f\x4c\x0f\x78\x0f\x78\x0f\xa4\x0f\xa4\x0f\xd0\x0f'\ b'\xd0\x0f\xfc\x0f\xfc\x0f\x28\x10\x28\x10\x54\x10\x54\x10\x80\x10'\ _mvfont = memoryview(_font) def get_ch(ch): ordch = ord(ch) ordch = ordch + 1 if ordch >= 32 and ordch <= 126 else 63 idx_offs = 4 * (ordch - 32) offset = int.from_bytes(_index[idx_offs : idx_offs + 2], 'little') next_offs = int.from_bytes(_index[idx_offs + 2 : idx_offs + 4], 'little') width = int.from_bytes(_font[offset:offset + 2], 'little') return _mvfont[offset + 2:next_offs], 21, width

63.62614

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0.696317

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1

0

1

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null

1

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13

94ddee63eee94addcc86274304c15055c55dffb5

111

py

Python

Src/Plugins/Tests.Security/TestData/SecurePlaintextSecrets/Inputs/SEC101_005.SlackApiKey.py

microsoft/spam

025e147cb8deb8cfeeebe8a839c183e9b016b51d

[ "MIT" ]

24

2020-12-29T17:31:31.000Z

2022-03-25T15:18:07.000Z

Src/Plugins/Tests.Security/TestData/SecurePlaintextSecrets/Inputs/SEC101_005.SlackApiKey.py

microsoft/spam

025e147cb8deb8cfeeebe8a839c183e9b016b51d

[ "MIT" ]

113

2020-11-06T09:42:43.000Z

2022-02-15T23:29:36.000Z

Src/Plugins/Tests.Security/TestData/SecurePlaintextSecrets/Inputs/SEC101_005.SlackApiKey.py

microsoft/spam

025e147cb8deb8cfeeebe8a839c183e9b016b51d

[ "MIT" ]

11

2020-12-29T16:05:36.000Z

2021-12-10T19:19:31.000Z

xoxb-83112120353-1016171244646-sGMxuWapBw3w3qdK6OfTjORe dead-83112120353-1016171244646-sGMxuWapBw3w3qdK6OfTjORf

55.5

55

0.936937

8

111

13

0.75

0.461538

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0.490909

0.009009

111

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true

0

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null

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7

bfce1faea22500832ebbb3c0c563b6eba4f60548

74,283

py

Python

venv/lib/python3.6/site-packages/ansible_collections/cisco/ios/plugins/modules/ios_ospfv3.py

usegalaxy-no/usegalaxy

75dad095769fe918eb39677f2c887e681a747f3a

[ "MIT" ]

1

2020-01-22T13:11:23.000Z

venv/lib/python3.6/site-packages/ansible_collections/cisco/ios/plugins/modules/ios_ospfv3.py

usegalaxy-no/usegalaxy

75dad095769fe918eb39677f2c887e681a747f3a

[ "MIT" ]

12

2020-02-21T07:24:52.000Z

2020-04-14T09:54:32.000Z

venv/lib/python3.6/site-packages/ansible_collections/cisco/ios/plugins/modules/ios_ospfv3.py

usegalaxy-no/usegalaxy

75dad095769fe918eb39677f2c887e681a747f3a

[ "MIT" ]

null

#!/usr/bin/python # # -*- coding: utf-8 -*- # Copyright 2020 Red Hat # GNU General Public License v3.0+ # (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) ############################################# # WARNING # ############################################# # # This file is auto generated by the resource # module builder playbook. # # Do not edit this file manually. # # Changes to this file will be over written # by the resource module builder. # # Changes should be made in the model used to # generate this file or in the resource module # builder template. # ############################################# """ The module file for ios_ospfv3 """ from __future__ import absolute_import, division, print_function __metaclass__ = type DOCUMENTATION = """ module: ios_ospfv3 short_description: OSPFv3 resource module description: This module configures and manages the Open Shortest Path First (OSPF) version 3 on IOS platforms. version_added: 1.1.0 author: Sumit Jaiswal (@justjais) notes: - Tested against Cisco IOSv Version 15.2 on VIRL. - This module works with connection C(network_cli). See U(https://docs.ansible.com/ansible/latest/network/user_guide/platform_ios.html) options: config: description: A list of configurations for ospfv3. type: dict suboptions: processes: description: List of OSPF instance configurations. type: list elements: dict suboptions: process_id: description: Process ID required: true type: int address_family: description: Enter Address Family command mode type: list elements: dict suboptions: afi: description: Enter Address Family command mode type: str choices: - ipv4 - ipv6 unicast: description: Address Family modifier type: bool vrf: description: Specify parameters for a VPN Routing/Forwarding instance type: str adjacency: description: Control adjacency formation type: dict suboptions: min_adjacency: description: - Initial number of adjacencies allowed to be forming in an area - Please refer vendor documentation for valid values type: int none: description: No initial type: bool max_adjacency: description: - Maximum number of adjacencies allowed to be forming - Please refer vendor documentation for valid values type: int disable: description: Disable adjacency staggering type: bool areas: description: OSPF area parameters type: list elements: dict suboptions: area_id: description: - OSPF area ID as a decimal value. Please refer vendor documentation of Valid values. - OSPF area ID in IP address format(e.g. A.B.C.D) type: str authentication: description: Authentication parameters type: dict suboptions: key_chain: description: Use a key-chain for cryptographic authentication keys type: str 'null': description: Use no authentication type: bool default_cost: description: - Set the summary default-cost of a NSSA/stub area - Stub's advertised external route metric - Note, please refer vendor documentation for respective valid values type: int filter_list: description: Filter networks between OSPFv3 areas type: list elements: dict suboptions: name: description: Name of an IP prefix-list type: str direction: description: The direction to apply on the filter networks sent to and from this area. type: str choices: ['in', 'out'] required: True normal: description: Specify a normal area type type: bool nssa: description: Specify a NSSA area type: dict suboptions: set: description: Enable a NSSA area type: bool default_information_originate: description: Originate Type 7 default into NSSA area type: dict suboptions: metric: description: OSPF default metric type: int metric_type: description: - OSPF metric type for default routes - OSPF Link State type type: int choices: [1, 2] nssa_only: description: Limit default advertisement to this NSSA area type: bool no_redistribution: description: No redistribution into this NSSA area type: bool no_summary: description: Do not send summary LSA into NSSA type: bool translate: description: - Translate LSA - Always translate LSAs on this ABR - Suppress forwarding address in translated LSAs type: str choices: ['always', 'suppress-fa'] ranges: description: Summarize routes matching address/mask (border routers only) type: list elements: dict suboptions: address: description: IP address to match type: str netmask: description: IP mask for address type: str advertise: description: - Advertise this range (default) - Since, advertise when enabled is not shown in running-config idempotency won't be maintained for the play in the second or next run of the play. type: bool cost: description: User specified metric for this range type: int not_advertise: description: DoNotAdvertise this range type: bool sham_link: description: Define a sham link and its parameters type: dict suboptions: source: description: IPv6 address associated with sham-link source (X:X:X:X::X) type: str destination: description: IPv6 address associated with sham-link destination (X:X:X:X::X) type: str authentication: description: Authentication parameters type: dict suboptions: key_chain: description: Use a key-chain for cryptographic authentication keys type: str 'null': description: Use no authentication type: bool cost: description: - Associate a cost with the sham-link - Cost of the sham-link type: int ttl_security: description: - TTL security check - maximum number of hops allowed type: int stub: description: - Specify a stub area - Backbone can not be configured as stub area type: dict suboptions: set: description: Enable a stub area type: bool no_summary: description: Do not send summary LSA into stub area type: bool authentication: description: - Authentication parameters - Authentication operation mode type: dict suboptions: deployment: description: Deployment mode of operation type: bool normal: description: Normal mode of operation type: bool auto_cost: description: Calculate OSPF interface cost according to bandwidth type: dict suboptions: set: description: Enable OSPF auto-cost type: bool reference_bandwidth: description: - Use reference bandwidth method to assign OSPF cost - Note, refer vendor documentation for respective valid values type: int bfd: description: BFD configuration commands type: dict suboptions: all_interfaces: description: Enable BFD on all interfaces type: bool disable: description: Disable BFD on all interfaces type: bool capability: description: - Enable a specific feature - Do not perform PE specific checks type: bool compatible: description: OSPFv3 router compatibility list type: dict suboptions: rfc1583: description: compatible with RFC 1583 type: bool rfc1587: description: compatible with RFC 1587 type: bool rfc5243: description: supports DBD exchange optimization type: bool default_information: description: Control distribution of default information type: dict suboptions: originate: description: Distribute a default route type: bool always: description: Always advertise default route type: bool metric: description: - OSPF default metric - Note, refer vendor documentation for respective valid values type: int metric_type: description: - OSPF metric type for default routes - Note, please refer vendor documentation for respective valid range type: int route_map: description: Route-map reference name type: str default_metric: description: Set metric of redistributed routes type: int discard_route: description: Enable or disable discard-route installation type: dict suboptions: sham_link: description: Discard route for sham-link routes type: bool external: description: Discard route for summarised redistributed routes type: bool internal: description: Discard route for summarised inter-area routes type: bool distance: description: - Define an administrative distance - Note, please refer vendor documentation for respective valid range type: int distribute_list: description: Filter networks in routing updates type: dict suboptions: acls: description: IP access list type: list elements: dict suboptions: name: description: IP access list name/number type: str required: true direction: description: Filter incoming and outgoing routing updates. type: str required: true choices: ['in', 'out'] interface: description: - Interface configuration (GigabitEthernet A/B) - Valid with incoming traffic type: str protocol: description: - Protocol config (bgp 1). - Valid with outgoing traffic type: str prefix: description: Filter prefixes in routing updates type: dict suboptions: name: description: Name of an IP prefix-list type: str required: true gateway_name: description: Gateway name for filtering incoming updates based on gateway type: str direction: description: Filter incoming and outgoing routing updates. type: str required: true choices: ['in', 'out'] interface: description: - Interface configuration (GigabitEthernet A/B) - Valid with incoming traffic type: str protocol: description: - Protocol config (bgp 1). - Valid with outgoing traffic type: str route_map: description: Filter prefixes in routing updates type: dict suboptions: name: description: Route-map name type: str required: true event_log: description: Event Logging type: dict suboptions: enable: description: Enable event Logging type: bool one_shot: description: Disable Logging When Log Buffer Becomes Full type: bool pause: description: Pause Event Logging type: bool size: description: - Maximum Number of Events Stored in the Event Log - Note, refer vendor documentation for respective valid values type: int graceful_restart: description: - Graceful-restart options - helper support type: dict suboptions: enable: description: helper support enabled type: bool disable: description: disable helper support type: bool strict_lsa_checking: description: enable helper strict LSA checking type: bool interface_id: description: Source of the interface ID type: dict suboptions: ios_if_index: description: IOS interface number type: bool snmp_if_index: description: SNMP MIB ifIndex type: bool limit: description: Limit a specific OSPF feature type: dict suboptions: dc: description: Demand circuit retransmissions type: dict suboptions: number: description: The maximum number of retransmissions type: int disable: description: Disble the feature type: bool non_dc: description: Non-demand-circuit retransmissions type: dict suboptions: number: description: The maximum number of retransmissions type: int disable: description: Disble the feature type: bool local_rib_criteria: description: Enable or disable usage of local RIB as route criteria type: dict suboptions: enable: description: Enable usage of local RIB as route criteria type: bool forwarding_address: description: Local RIB used to validate external/NSSA forwarding addresses type: bool inter_area_summary: description: Local RIB used as criteria for inter-area summaries type: bool nssa_translation: description: Local RIB used as criteria for NSSA translation type: bool log_adjacency_changes: description: Log changes in adjacency state type: dict suboptions: set: description: Log changes in adjacency state type: bool detail: description: Log all state changes type: bool manet: description: Specify MANET OSPF parameters type: dict suboptions: cache: description: Specify MANET cache sizes type: dict suboptions: acknowledgement: description: - Specify MANET acknowledgement cache size - Maximum number of acknowledgements in cache type: int update: description: - Specify MANET LSA cache size - Maximum number of LSAs in cache type: int hello: description: Unicast Hellos rather than multicast type: dict suboptions: multicast: description: Multicast Hello requests and responses rather than unicast type: bool unicast: description: Unicast Hello requests and responses rather than multicast type: bool peering: description: MANET OSPF Smart Peering type: dict suboptions: set: description: Enable selective peering type: bool disable: description: Disable selective peering type: bool per_interface: description: Select peers per interface rather than per node type: bool redundancy: description: - Redundant paths - Number of redundant OSPF paths type: int willingness: description: Specify and Relay willingness value type: int max_lsa: description: Maximum number of non self-generated LSAs to accept type: dict suboptions: number: description: - Maximum number of non self-generated LSAs to accept - Note, refer vendor documentation for respective valid values type: int threshold_value: description: - Threshold value (%) at which to generate a warning msg - Note, refer vendor documentation for respective valid values type: int ignore_count: description: - Maximum number of times adjacencies can be suppressed - Note, refer vendor documentation for respective valid values type: int ignore_time: description: - Number of minutes during which all adjacencies are suppressed - Note, refer vendor documentation for respective valid values type: int reset_time: description: - Number of minutes after which ignore-count is reset to zero - Note, refer vendor documentation for respective valid values type: int warning_only: description: Only give a warning message when limit is exceeded type: bool max_metric: description: - Set maximum metric - Maximum metric in self-originated router-LSAs type: dict suboptions: disable: description: disable maximum metric in self-originated router-LSAs type: bool external_lsa: description: - Override external-lsa metric with max-metric value - Overriding metric in external-LSAs - Note, refer vendor documentation for respective valid values type: int inter_area_lsas: description: - Override inter-area-lsas metric with max-metric value - Overriding metric in inter-area-LSAs - Note, refer vendor documentation for respective valid values type: int on_startup: description: Set maximum metric temporarily after reboot type: dict suboptions: time: description: - Time, in seconds, router-LSAs are originated with max-metric - Note, please refer vendor documentation for respective valid range type: int wait_for_bgp: description: Let BGP decide when to originate router-LSA with normal metric type: bool stub_prefix_lsa: description: Set maximum metric for stub links in prefix LSAs type: bool maximum_paths: description: - Forward packets over multiple paths - Number of paths type: int passive_interface: description: Suppress routing updates on an interface type: str prefix_suppression: description: Prefix suppression type: dict suboptions: enable: description: Enable prefix suppression type: bool disable: description: Disable prefix suppression type: bool queue_depth: description: Hello/Router process queue depth type: dict suboptions: hello: description: OSPF Hello process queue depth type: dict suboptions: max_packets: description: maximum number of packets in the queue type: int unlimited: description: Unlimited queue depth type: bool update: description: OSPF Router process queue depth type: dict suboptions: max_packets: description: maximum number of packets in the queue type: int unlimited: description: Unlimited queue depth type: bool router_id: description: - Router-id address for this OSPF process - OSPF router-id in IP address format (A.B.C.D) type: str shutdown: description: Shutdown the router process type: dict suboptions: enable: description: Shutdown the router process type: bool disable: description: Disable Shutdown type: bool summary_prefix: description: Configure IP address summaries type: dict suboptions: address: description: - IP summary address (A.B.C.D) - IP prefix <network>/<length> (A.B.C.D/nn) type: str mask: description: IP Summary mask type: str not_advertise: description: Do not advertise or translate type: bool nssa_only: description: Limit summary to NSSA areas type: bool tag: description: Set tag type: int timers: description: Adjust routing timers type: dict suboptions: lsa: description: - OSPF LSA timers, arrival timer - The minimum interval in milliseconds between accepting the same LSA - Note, refer vendor documentation for respective valid values type: int manet: description: OSPF MANET timers type: dict suboptions: cache: description: Specify MANET cache sizes type: dict suboptions: acknowledgement: description: Specify MANET acknowledgement cache size type: int redundancy: description: Specify MANET LSA cache size type: int hello: description: - Unicast Hellos rather than multicast - Unicast Hello requests and responses rather than multicast type: bool peering: description: MANET OSPF Smart Peering type: dict suboptions: set: description: Enable selective peering type: bool per_interface: description: Select peers per interface rather than per node type: bool redundancy: description: - Redundant paths - Number of redundant OSPF paths type: int willingness: description: Specify and Relay willingness value type: int pacing: description: OSPF pacing timers type: dict suboptions: flood: description: - OSPF flood pacing timer - The minimum interval in msec to pace limit flooding on interface - Note, refer vendor documentation for respective valid values type: int lsa_group: description: - OSPF LSA group pacing timer - Interval in sec between group of LSA being refreshed or maxaged - Note, refer vendor documentation for respective valid values type: int retransmission: description: - OSPF retransmission pacing timer - The minimum interval in msec between neighbor retransmissions - Note, refer vendor documentation for respective valid values type: int throttle: description: OSPF throttle timers type: dict suboptions: lsa: description: OSPF LSA throttle timers type: dict suboptions: first_delay: description: - Delay to generate first occurrence of LSA in milliseconds - Note, refer vendor documentation for respective valid values type: int min_delay: description: - Minimum delay between originating the same LSA in milliseconds - Note, refer vendor documentation for respective valid values type: int max_delay: description: - Maximum delay between originating the same LSA in milliseconds - Note, refer vendor documentation for respective valid values type: int spf: description: OSPF SPF throttle timers - Delay between receiving a change to SPF calculation in milliseconds - Note, refer vendor documentation for respective valid values type: dict suboptions: receive_delay: description: - Delay between receiving a change to SPF calculation in milliseconds - Note, refer vendor documentation for respective valid values type: int between_delay: description: - Delay between first and second SPF calculation in milliseconds - Note, refer vendor documentation for respective valid values type: int max_delay: description: - Maximum wait time in milliseconds for SPF calculations - Note, refer vendor documentation for respective valid values type: int adjacency: description: Control adjacency formation type: dict suboptions: min_adjacency: description: - Initial number of adjacencies allowed to be forming in an area - Please refer vendor documentation for valid values type: int max_adjacency: description: - Maximum number of adjacencies allowed to be forming - Please refer vendor documentation for valid values type: int none: description: No initial type: bool areas: description: OSPF area parameters type: list elements: dict suboptions: area_id: description: - OSPF area ID as a decimal value. Please refer vendor documentation of Valid values. - OSPF area ID in IP address format(e.g. A.B.C.D) type: str authentication: description: Authentication parameters type: dict suboptions: key_chain: description: Use a key-chain for cryptographic authentication keys type: str ipsec: description: Use IPsec authentication type: dict suboptions: spi: description: Set the SPI (Security Parameters Index) type: int md5: description: Use MD5 authentication type: int sha1: description: Use SHA-1 authentication type: int hex_string: description: SHA-1 key (40 chars) type: str default_cost: description: - Set the summary default-cost of a NSSA/stub area - Stub's advertised external route metric - Note, please refer vendor documentation for respective valid values type: int nssa: description: Specify a NSSA area type: dict suboptions: set: description: Enable a NSSA area type: bool default_information_originate: description: Originate Type 7 default into NSSA area type: dict suboptions: metric: description: OSPF default metric type: int metric_type: description: - OSPF metric type for default routes - OSPF Link State type type: int choices: [1, 2] nssa_only: description: Limit default advertisement to this NSSA area type: bool no_redistribution: description: No redistribution into this NSSA area type: bool no_summary: description: Do not send summary LSA into NSSA type: bool translate: description: - Translate LSA - Always translate LSAs on this ABR - Suppress forwarding address in translated LSAs type: str choices: ['always', 'suppress-fa'] stub: description: - Specify a stub area - Backbone can not be configured as stub area type: dict suboptions: set: description: Enable a stub area type: bool no_summary: description: Do not send summary LSA into stub area type: bool authentication: description: - Authentication parameter mode - Deployment mode of operation type: bool auto_cost: description: Calculate OSPF interface cost according to bandwidth type: dict suboptions: set: description: Enable OSPF auto-cost type: bool reference_bandwidth: description: - Use reference bandwidth method to assign OSPF cost - Note, refer vendor documentation for respective valid values type: int bfd: description: - BFD configuration commands - Enable BFD on all interfaces type: bool compatible: description: OSPFv3 router compatibility list type: dict suboptions: rfc1583: description: compatible with RFC 1583 type: bool rfc1587: description: compatible with RFC 1587 type: bool rfc5243: description: supports DBD exchange optimization type: bool event_log: description: Event Logging type: dict suboptions: enable: description: Enable event Logging type: bool one_shot: description: Disable Logging When Log Buffer Becomes Full type: bool pause: description: Pause Event Logging type: bool size: description: - Maximum Number of Events Stored in the Event Log - Note, refer vendor documentation for respective valid values type: int graceful_restart: description: Graceful-restart options for helper support type: dict suboptions: disable: description: disable helper support type: bool strict_lsa_checking: description: enable helper strict LSA checking type: bool help: description: Description of the interactive help system type: bool interface_id: description: - Source of the interface ID - SNMP MIB ifIndex type: bool limit: description: Limit a specific OSPF feature and LS update, DBD, and LS request retransmissions type: dict suboptions: dc: description: Demand circuit retransmissions type: dict suboptions: number: description: The maximum number of retransmissions type: int disable: description: Disable the feature type: bool non_dc: description: Non-demand-circuit retransmissions type: dict suboptions: number: description: The maximum number of retransmissions type: int disable: description: Disable the feature type: bool local_rib_criteria: description: Enable or disable usage of local RIB as route criteria type: dict suboptions: enable: description: Enable usage of local RIB as route criteria type: bool forwarding_address: description: Local RIB used to validate external/NSSA forwarding addresses type: bool inter_area_summary: description: Local RIB used as criteria for inter-area summaries type: bool nssa_translation: description: Local RIB used as criteria for NSSA translation type: bool log_adjacency_changes: description: Log changes in adjacency state type: dict suboptions: set: description: Log changes in adjacency state type: bool detail: description: Log all state changes type: bool manet: description: Specify MANET OSPF parameters type: dict suboptions: cache: description: Specify MANET cache sizes type: dict suboptions: acknowledgement: description: Specify MANET acknowledgement cache size type: int redundancy: description: Specify MANET LSA cache size type: int hello: description: - Unicast Hellos rather than multicast - Unicast Hello requests and responses rather than multicast type: bool peering: description: MANET OSPF Smart Peering type: dict suboptions: set: description: Enable selective peering type: bool per_interface: description: Select peers per interface rather than per node type: bool redundancy: description: - Redundant paths - Number of redundant OSPF paths type: int willingness: description: Specify and Relay willingness value type: int max_lsa: description: Maximum number of non self-generated LSAs to accept type: dict suboptions: number: description: - Maximum number of non self-generated LSAs to accept - Note, refer vendor documentation for respective valid values type: int threshold_value: description: - Threshold value (%) at which to generate a warning msg - Note, refer vendor documentation for respective valid values type: int ignore_count: description: - Maximum number of times adjacencies can be suppressed - Note, refer vendor documentation for respective valid values type: int ignore_time: description: - Number of minutes during which all adjacencies are suppressed - Note, refer vendor documentation for respective valid values type: int reset_time: description: - Number of minutes after which ignore-count is reset to zero - Note, refer vendor documentation for respective valid values type: int warning_only: description: Only give a warning message when limit is exceeded type: bool max_metric: description: Set maximum metric type: dict suboptions: router_lsa: description: Maximum metric in self-originated router-LSAs type: bool required: true external_lsa: description: - Override external-lsa metric with max-metric value - Overriding metric in external-LSAs - Note, refer vendor documentation for respective valid values type: int include_stub: description: Set maximum metric for stub links in router-LSAs type: bool on_startup: description: Set maximum metric temporarily after reboot type: dict suboptions: time: description: - Time, in seconds, router-LSAs are originated with max-metric - Note, please refer vendor documentation for respective valid range type: int wait_for_bgp: description: Let BGP decide when to originate router-LSA with normal metric type: bool summary_lsa: description: - Override summary-lsa metric with max-metric value - Note, please refer vendor documentation for respective valid range type: int passive_interface: description: Suppress routing updates on an interface type: str prefix_suppression: description: Enable prefix suppression type: bool queue_depth: description: Hello/Router process queue depth type: dict suboptions: hello: description: OSPF Hello process queue depth type: dict suboptions: max_packets: description: maximum number of packets in the queue type: int unlimited: description: Unlimited queue depth type: bool router_id: description: - Router-id address for this OSPF process - OSPF router-id in IP address format (A.B.C.D) type: str shutdown: description: Shutdown the router process type: bool timers: description: Adjust routing timers type: dict suboptions: lsa: description: - OSPF LSA timers, arrival timer - The minimum interval in milliseconds between accepting the same LSA - Note, refer vendor documentation for respective valid values type: int manet: description: OSPF MANET timers type: dict suboptions: cache: description: Specify MANET cache sizes type: dict suboptions: acknowledgement: description: Specify MANET acknowledgement cache size type: int redundancy: description: Specify MANET LSA cache size type: int hello: description: - Unicast Hellos rather than multicast - Unicast Hello requests and responses rather than multicast type: bool peering: description: MANET OSPF Smart Peering type: dict suboptions: set: description: Enable selective peering type: bool per_interface: description: Select peers per interface rather than per node type: bool redundancy: description: - Redundant paths - Number of redundant OSPF paths type: int willingness: description: Specify and Relay willingness value type: int pacing: description: OSPF pacing timers type: dict suboptions: flood: description: - OSPF flood pacing timer - The minimum interval in msec to pace limit flooding on interface - Note, refer vendor documentation for respective valid values type: int lsa_group: description: - OSPF LSA group pacing timer - Interval in sec between group of LSA being refreshed or maxaged - Note, refer vendor documentation for respective valid values type: int retransmission: description: - OSPF retransmission pacing timer - The minimum interval in msec between neighbor retransmissions - Note, refer vendor documentation for respective valid values type: int throttle: description: OSPF throttle timers type: dict suboptions: lsa: description: OSPF LSA throttle timers type: dict suboptions: first_delay: description: - Delay to generate first occurrence of LSA in milliseconds - Note, refer vendor documentation for respective valid values type: int min_delay: description: - Minimum delay between originating the same LSA in milliseconds - Note, refer vendor documentation for respective valid values type: int max_delay: description: - Maximum delay between originating the same LSA in milliseconds - Note, refer vendor documentation for respective valid values type: int spf: description: OSPF SPF throttle timers - Delay between receiving a change to SPF calculation in milliseconds - Note, refer vendor documentation for respective valid values type: dict suboptions: receive_delay: description: - Delay between receiving a change to SPF calculation in milliseconds - Note, refer vendor documentation for respective valid values type: int between_delay: description: - Delay between first and second SPF calculation in milliseconds - Note, refer vendor documentation for respective valid values type: int max_delay: description: - Maximum wait time in milliseconds for SPF calculations - Note, refer vendor documentation for respective valid values type: int running_config: description: - This option is used only with state I(parsed). - The value of this option should be the output received from the IOS device by executing the command B(sh running-config | section ^router ospfv3). - The state I(parsed) reads the configuration from C(running_config) option and transforms it into Ansible structured data as per the resource module's argspec and the value is then returned in the I(parsed) key within the result. type: str state: description: - The state the configuration should be left in - The states I(rendered), I(gathered) and I(parsed) does not perform any change on the device. - The state I(rendered) will transform the configuration in C(config) option to platform specific CLI commands which will be returned in the I(rendered) key within the result. For state I(rendered) active connection to remote host is not required. - The state I(gathered) will fetch the running configuration from device and transform it into structured data in the format as per the resource module argspec and the value is returned in the I(gathered) key within the result. - The state I(parsed) reads the configuration from C(running_config) option and transforms it into JSON format as per the resource module parameters and the value is returned in the I(parsed) key within the result. The value of C(running_config) option should be the same format as the output of command I(show running-config | include ip route|ipv6 route) executed on device. For state I(parsed) active connection to remote host is not required. type: str choices: - merged - replaced - overridden - deleted - gathered - parsed - rendered default: merged """ EXAMPLES = """ # Using deleted # Before state: # ------------- # # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family - name: Delete provided OSPF V3 processes cisco.ios.ios_ospfv3: config: processes: - process_id: 1 state: deleted # Commands Fired: # --------------- # # "commands": [ # "no router ospfv3 1" # ] # After state: # ------------- # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family # Using deleted without any config passed (NOTE: This will delete all OSPFV3 configuration from device) # Before state: # ------------- # # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family - name: Delete all OSPF processes cisco.ios.ios_ospfv3: state: deleted # Commands Fired: # --------------- # # "commands": [ # "no router ospfv3 200", # "no router ospfv3 1" # ] # After state: # ------------- # router-ios#sh running-config | section ^router ospfv3 # router-ios# # Using merged # Before state: # ------------- # # router-ios#sh running-config | section ^router ospfv3 # router-ios# - name: Merge provided OSPFV3 configuration cisco.ios.ios_ospfv3: config: processes: - process_id: 1 max_metric: router_lsa: true on_startup: time: 110 address_family: - afi: ipv4 unicast: true vrf: blue adjacency: min_adjacency: 50 max_adjacency: 50 areas: - area_id: 25 nssa: default_information_originate: metric: 25 nssa_only: true areas: - area_id: "10" nssa: default_information_originate: metric: 10 timers: throttle: lsa: first_delay: 12 min_delay: 14 max_delay: 16 - process_id: 200 address_family: - afi: ipv4 unicast: true adjacency: min_adjacency: 200 max_adjacency: 200 max_metric: router_lsa: true on_startup: time: 100 auto_cost: reference_bandwidth: 4 state: merged # Commands Fired: # --------------- # # "commands": [ # "router ospfv3 1", # "max-metric router-lsa on-startup 110", # "area 10 nssa default-information-originate metric 10", # "address-family ipv4 unicast vrf blue", # "adjacency stagger 50 50", # "area 25 nssa default-information-originate metric 25 nssa-only", # "exit-address-family", # "router ospfv3 200", # "auto-cost reference-bandwidth 4", # "max-metric router-lsa on-startup 100", # "address-family ipv4 unicast", # "adjacency stagger 200 200", # "exit-address-family" # ] # After state: # ------------- # # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family # Using overridden # Before state: # ------------- # # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family - name: Override provided OSPFV3 configuration cisco.ios.ios_ospfv3: config: processes: - process_id: 200 max_metric: router_lsa: true on_startup: time: 200 address_family: - afi: ipv4 unicast: true adjacency: min_adjacency: 50 max_adjacency: 50 areas: - area_id: 200 nssa: default_information_originate: metric: 200 nssa_only: true areas: - area_id: "10" nssa: default_information_originate: metric: 10 state: overridden # Commands Fired: # --------------- # # "commands": [ # "no router ospfv3 1", # "router ospfv3 200", # "no auto-cost reference-bandwidth 4", # "max-metric router-lsa on-startup 200", # "area 10 nssa default-information-originate metric 10", # "address-family ipv4 unicast", # "adjacency stagger 50 50", # "area 200 nssa default-information-originate metric 200 nssa-only", # "exit-address-family" # ] # After state: # ------------- # # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 200 # max-metric router-lsa on-startup 200 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast # adjacency stagger 50 50 # area 200 nssa default-information-originate metric 200 nssa-only # exit-address-family # Using replaced # Before state: # ------------- # # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family - name: Replaced provided OSPFV3 configuration cisco.ios.ios_ospfv3: config: processes: - process_id: 200 max_metric: router_lsa: true on_startup: time: 200 address_family: - afi: ipv4 unicast: true adjacency: min_adjacency: 50 max_adjacency: 50 areas: - area_id: 200 nssa: default_information_originate: metric: 200 nssa_only: true areas: - area_id: "10" nssa: default_information_originate: metric: 10 state: replaced # Commands Fired: # --------------- # "commands": [ # "router ospfv3 200", # "no auto-cost reference-bandwidth 4", # "max-metric router-lsa on-startup 200", # "area 10 nssa default-information-originate metric 10", # "address-family ipv4 unicast", # "adjacency stagger 50 50", # "area 200 nssa default-information-originate metric 200 nssa-only", # "exit-address-family" # ] # After state: # ------------- # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 200 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast # adjacency stagger 50 50 # area 200 nssa default-information-originate metric 200 nssa-only # exit-address-family # Using Gathered # Before state: # ------------- # # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family - name: Gather OSPFV3 provided configurations cisco.ios.ios_ospfv3: config: state: gathered # Module Execution Result: # ------------------------ # # "gathered": { # "processes": [ # { # "address_family": [ # { # "adjacency": { # "max_adjacency": 50, # "min_adjacency": 50 # }, # "afi": "ipv4", # "areas": [ # { # "area_id": "25", # "nssa": { # "default_information_originate": { # "metric": 25, # "nssa_only": true # } # } # } # ], # "unicast": true, # "vrf": "blue" # } # ], # "areas": [ # { # "area_id": "10", # "nssa": { # "default_information_originate": { # "metric": 10 # } # } # } # ], # "max_metric": { # "on_startup": { # "time": 110 # }, # "router_lsa": true # }, # "process_id": 1 # }, # { # "address_family": [ # { # "adjacency": { # "max_adjacency": 200, # "min_adjacency": 200 # }, # "afi": "ipv4", # "unicast": true # } # ], # "auto_cost": { # "reference_bandwidth": 4 # }, # "max_metric": { # "on_startup": { # "time": 100 # }, # "router_lsa": true # }, # "process_id": 200 # } # ] # } # After state: # ------------ # # router-ios#sh running-config | section ^router ospfv3 # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family # Using Rendered - name: Render the commands for provided configuration cisco.ios.ios_ospfv3: config: processes: - process_id: 1 max_metric: router_lsa: true on_startup: time: 110 address_family: - afi: ipv4 unicast: true vrf: blue adjacency: min_adjacency: 50 max_adjacency: 50 areas: - area_id: 25 nssa: default_information_originate: metric: 25 nssa_only: true areas: - area_id: "10" nssa: default_information_originate: metric: 10 timers: throttle: lsa: first_delay: 12 min_delay: 14 max_delay: 16 - process_id: 200 address_family: - afi: ipv4 unicast: true adjacency: min_adjacency: 200 max_adjacency: 200 max_metric: router_lsa: true on_startup: time: 100 auto_cost: reference_bandwidth: 4 state: rendered # Module Execution Result: # ------------------------ # # "rendered": [ # "router ospfv3 1", # "max-metric router-lsa on-startup 110", # "area 10 nssa default-information-originate metric 10", # "address-family ipv4 unicast vrf blue", # "adjacency stagger 50 50", # "area 25 nssa default-information-originate metric 25 nssa-only", # "exit-address-family", # "router ospfv3 200", # "auto-cost reference-bandwidth 4", # "max-metric router-lsa on-startup 100", # "address-family ipv4 unicast", # "adjacency stagger 200 200", # "exit-address-family" # ] # Using Parsed # File: parsed.cfg # ---------------- # # router ospfv3 1 # max-metric router-lsa on-startup 110 # area 10 nssa default-information-originate metric 10 # ! # address-family ipv4 unicast vrf blue # adjacency stagger 50 50 # area 25 nssa default-information-originate metric 25 nssa-only # exit-address-family # router ospfv3 200 # max-metric router-lsa on-startup 100 # auto-cost reference-bandwidth 4 # ! # address-family ipv4 unicast # adjacency stagger 200 200 # exit-address-family - name: Parse the provided configuration with the existing running configuration cisco.ios.ios_ospfv3: running_config: "{{ lookup('file', 'parsed.cfg') }}" state: parsed # Module Execution Result: # ------------------------ # # "parsed": { # "processes": [ # { # "address_family": [ # { # "adjacency": { # "max_adjacency": 50, # "min_adjacency": 50 # }, # "afi": "ipv4", # "areas": [ # { # "area_id": "25", # "nssa": { # "default_information_originate": { # "metric": 25, # "nssa_only": true # } # } # } # ], # "unicast": true, # "vrf": "blue" # } # ], # "areas": [ # { # "area_id": "10", # "nssa": { # "default_information_originate": { # "metric": 10 # } # } # } # ], # "max_metric": { # "on_startup": { # "time": 110 # }, # "router_lsa": true # }, # "process_id": 1 # } # ] # } """ RETURN = """ before: description: The configuration prior to the model invocation. returned: always sample: > The configuration returned will always be in the same format of the parameters above. type: dict after: description: The resulting configuration model invocation. returned: when changed sample: > The configuration returned will always be in the same format of the parameters above. type: dict commands: description: The set of commands pushed to the remote device. returned: always type: list sample: ['router ospfv3 1', 'address-family ipv4 unicast vrf blue', 'adjacency stagger 50 50'] """ from ansible.module_utils.basic import AnsibleModule from ansible_collections.cisco.ios.plugins.module_utils.network.ios.argspec.ospfv3.ospfv3 import ( Ospfv3Args, ) from ansible_collections.cisco.ios.plugins.module_utils.network.ios.config.ospfv3.ospfv3 import ( Ospfv3, ) def main(): """ Main entry point for module execution :returns: the result form module invocation """ required_if = [ ("state", "merged", ("config",)), ("state", "replaced", ("config",)), ("state", "overridden", ("config",)), ("state", "rendered", ("config",)), ("state", "parsed", ("running_config",)), ] mutually_exclusive = [("config", "running_config")] module = AnsibleModule( argument_spec=Ospfv3Args.argument_spec, required_if=required_if, mutually_exclusive=mutually_exclusive, supports_check_mode=True, ) result = Ospfv3(module).execute_module() module.exit_json(**result) if __name__ == "__main__": main()

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Python

clayful/models/order.py

Clayful/clayful-python

ddd5f1f986fb0079d5128e17f4b0fdce83b4cec1

[ "MIT" ]

null

clayful/models/order.py

Clayful/clayful-python

ddd5f1f986fb0079d5128e17f4b0fdce83b4cec1

[ "MIT" ]

3

2020-04-17T05:24:06.000Z

2022-02-10T09:00:22.000Z

clayful/models/order.py

Clayful/clayful-python

ddd5f1f986fb0079d5128e17f4b0fdce83b4cec1

[ "MIT" ]

null

class Order: Clayful = None name = 'Order' path = 'orders' @staticmethod def config(clayful): Order.Clayful = clayful return Order @staticmethod def accept_refund(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'accept_refund', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/refunds/{refundId}/accepted', 'params': ('orderId', 'refundId', ), 'without_payload': True, 'args': args }) @staticmethod def authenticate(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'authenticate', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/auth', 'params': ('orderId', ), 'args': args }) @staticmethod def cancel(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'cancel', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/cancellation', 'params': ('orderId', ), 'args': args }) @staticmethod def cancel_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'cancel_for_me', 'http_method': 'POST', 'path': '/v1/me/orders/{orderId}/cancellation', 'params': ('orderId', ), 'args': args }) @staticmethod def cancel_refund(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'cancel_refund', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/refunds/{refundId}/cancellation', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def cancel_refund_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'cancel_refund_for_me', 'http_method': 'POST', 'path': '/v1/me/orders/{orderId}/refunds/{refundId}/cancellation', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def check_ticket(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'check_ticket', 'http_method': 'POST', 'path': '/v1/orders/tickets/{code}/validity', 'params': ('code', ), 'args': args }) @staticmethod def count(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'count', 'http_method': 'GET', 'path': '/v1/orders/count', 'params': (), 'args': args }) @staticmethod def count_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'count_for_me', 'http_method': 'GET', 'path': '/v1/me/orders/count', 'params': (), 'args': args }) @staticmethod def create_download_url(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'create_download_url', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/items/{itemId}/download/url', 'params': ('orderId', 'itemId', ), 'without_payload': True, 'args': args }) @staticmethod def create_download_url_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'create_download_url_for_me', 'http_method': 'POST', 'path': '/v1/me/orders/{orderId}/items/{itemId}/download/url', 'params': ('orderId', 'itemId', ), 'without_payload': True, 'args': args }) @staticmethod def create_fulfillment(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'create_fulfillment', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/fulfillments', 'params': ('orderId', ), 'args': args }) @staticmethod def delete(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'delete', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}', 'params': ('orderId', ), 'args': args }) @staticmethod def delete_fulfillment(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'delete_fulfillment', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/fulfillments/{fulfillmentId}', 'params': ('orderId', 'fulfillmentId', ), 'args': args }) @staticmethod def delete_inventory_operation(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'delete_inventory_operation', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/inventory/operations/{operationId}', 'params': ('orderId', 'operationId', ), 'args': args }) @staticmethod def delete_metafield(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'delete_metafield', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/meta/{field}', 'params': ('orderId', 'field', ), 'args': args }) @staticmethod def delete_refund(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'delete_refund', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/refunds/{refundId}', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def get(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'get', 'http_method': 'GET', 'path': '/v1/orders/{orderId}', 'params': ('orderId', ), 'args': args }) @staticmethod def get_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'get_for_me', 'http_method': 'GET', 'path': '/v1/me/orders/{orderId}', 'params': ('orderId', ), 'args': args }) @staticmethod def increase_metafield(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'increase_metafield', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/meta/{field}/inc', 'params': ('orderId', 'field', ), 'args': args }) @staticmethod def list(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'list', 'http_method': 'GET', 'path': '/v1/orders', 'params': (), 'args': args }) @staticmethod def list_by_subscription(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'list_by_subscription', 'http_method': 'GET', 'path': '/v1/subscriptions/{subscriptionId}/orders', 'params': ('subscriptionId', ), 'args': args }) @staticmethod def list_by_subscription_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'list_by_subscription_for_me', 'http_method': 'GET', 'path': '/v1/me/subscriptions/{subscriptionId}/orders', 'params': ('subscriptionId', ), 'args': args }) @staticmethod def list_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'list_for_me', 'http_method': 'GET', 'path': '/v1/me/orders', 'params': (), 'args': args }) @staticmethod def list_inventory_operations(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'list_inventory_operations', 'http_method': 'GET', 'path': '/v1/orders/{orderId}/inventory/operations', 'params': ('orderId', ), 'args': args }) @staticmethod def mark_as_done(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'mark_as_done', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/done', 'params': ('orderId', ), 'without_payload': True, 'args': args }) @staticmethod def mark_as_not_received(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'mark_as_not_received', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/received', 'params': ('orderId', ), 'args': args }) @staticmethod def mark_as_not_received_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'mark_as_not_received_for_me', 'http_method': 'DELETE', 'path': '/v1/me/orders/{orderId}/received', 'params': ('orderId', ), 'args': args }) @staticmethod def mark_as_received(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'mark_as_received', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/received', 'params': ('orderId', ), 'without_payload': True, 'args': args }) @staticmethod def mark_as_received_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'mark_as_received_for_me', 'http_method': 'POST', 'path': '/v1/me/orders/{orderId}/received', 'params': ('orderId', ), 'without_payload': True, 'args': args }) @staticmethod def mark_as_undone(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'mark_as_undone', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/done', 'params': ('orderId', ), 'args': args }) @staticmethod def pull_from_metafield(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'pull_from_metafield', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/meta/{field}/pull', 'params': ('orderId', 'field', ), 'args': args }) @staticmethod def push_to_metafield(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'push_to_metafield', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/meta/{field}/push', 'params': ('orderId', 'field', ), 'args': args }) @staticmethod def register_payment_method(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'register_payment_method', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/transactions/payments/methods', 'params': ('orderId', ), 'args': args }) @staticmethod def request_refund(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'request_refund', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/refunds', 'params': ('orderId', ), 'args': args }) @staticmethod def request_refund_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'request_refund_for_me', 'http_method': 'POST', 'path': '/v1/me/orders/{orderId}/refunds', 'params': ('orderId', ), 'args': args }) @staticmethod def restock_all_refund_items(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'restock_all_refund_items', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/refunds/{refundId}/restock/all', 'params': ('orderId', 'refundId', ), 'without_payload': True, 'args': args }) @staticmethod def restock_refund_items(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'restock_refund_items', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/refunds/{refundId}/restock', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def sync_inventory(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'sync_inventory', 'http_method': 'POST', 'path': '/v1/orders/{orderId}/synced', 'params': ('orderId', ), 'without_payload': True, 'args': args }) @staticmethod def unaccept_refund(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'unaccept_refund', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/refunds/{refundId}/accepted', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def unregister_payment_method(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'unregister_payment_method', 'http_method': 'DELETE', 'path': '/v1/orders/{orderId}/transactions/payments/methods/{paymentMethodId}', 'params': ('orderId', 'paymentMethodId', ), 'args': args }) @staticmethod def update(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update', 'http_method': 'PUT', 'path': '/v1/orders/{orderId}', 'params': ('orderId', ), 'args': args }) @staticmethod def update_cancellation(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_cancellation', 'http_method': 'PUT', 'path': '/v1/orders/{orderId}/cancellation', 'params': ('orderId', ), 'args': args }) @staticmethod def update_cancellation_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_cancellation_for_me', 'http_method': 'PUT', 'path': '/v1/me/orders/{orderId}/cancellation', 'params': ('orderId', ), 'args': args }) @staticmethod def update_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_for_me', 'http_method': 'PUT', 'path': '/v1/me/orders/{orderId}', 'params': ('orderId', ), 'args': args }) @staticmethod def update_fulfillment(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_fulfillment', 'http_method': 'PUT', 'path': '/v1/orders/{orderId}/fulfillments/{fulfillmentId}', 'params': ('orderId', 'fulfillmentId', ), 'args': args }) @staticmethod def update_item(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_item', 'http_method': 'PUT', 'path': '/v1/orders/{orderId}/items/{itemId}', 'params': ('orderId', 'itemId', ), 'args': args }) @staticmethod def update_refund(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_refund', 'http_method': 'PUT', 'path': '/v1/orders/{orderId}/refunds/{refundId}', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def update_refund_cancellation(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_refund_cancellation', 'http_method': 'PUT', 'path': '/v1/orders/{orderId}/refunds/{refundId}/cancellation', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def update_refund_cancellation_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_refund_cancellation_for_me', 'http_method': 'PUT', 'path': '/v1/me/orders/{orderId}/refunds/{refundId}/cancellation', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def update_refund_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_refund_for_me', 'http_method': 'PUT', 'path': '/v1/me/orders/{orderId}/refunds/{refundId}', 'params': ('orderId', 'refundId', ), 'args': args }) @staticmethod def update_transactions(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_transactions', 'http_method': 'PUT', 'path': '/v1/orders/{orderId}/transactions', 'params': ('orderId', ), 'args': args }) @staticmethod def update_transactions_for_me(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'update_transactions_for_me', 'http_method': 'PUT', 'path': '/v1/me/orders/{orderId}/transactions', 'params': ('orderId', ), 'without_payload': True, 'args': args }) @staticmethod def use_ticket(*args): return Order.Clayful.call_api({ 'model_name': Order.name, 'method_name': 'use_ticket', 'http_method': 'POST', 'path': '/v1/orders/tickets/{code}/used', 'params': ('code', ), 'without_payload': True, 'args': args })

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94

0.548675

1,817

18,264

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0.051183

0.069964

0.084331

0.123686

0.935867

0.911921

0.892868

0.769183

0.754086

0.709735

0

0.004147

0.286958

18,264

671

95

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0.733395

0

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0

null

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1

0

null

0

7

7834b6fddd81469412feac1fbb3b75d1909a5de7

224

py

Python

confu/tools/toolchains/__init__.py

tiny-dnn/confu

8f74d9fc0c04efe8cd1b92ae5f43a5d9b686500e

[ "MIT" ]

null

confu/tools/toolchains/__init__.py

tiny-dnn/confu

8f74d9fc0c04efe8cd1b92ae5f43a5d9b686500e

[ "MIT" ]

null

confu/tools/toolchains/__init__.py

tiny-dnn/confu

8f74d9fc0c04efe8cd1b92ae5f43a5d9b686500e

[ "MIT" ]

1

2020-11-16T18:06:25.000Z

from confu.tools.toolchains.base import Toolchain from confu.tools.toolchains.unix import UnixToolchain from confu.tools.toolchains.nacl import NaClToolchain from confu.tools.toolchains.emscripten import EmscriptenToolchain

44.8

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0.875

28

224

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0.489796

0

0.071429

224

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0.942308

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true

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1

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null

0

1

0

1

0

1

0

7

7862aa390f87b94b30627ed8e16cee4d3f02b084

169

py

Python

qutipy/misc/__init__.py

sumeetkhatri/QuTIPy

ca2a3344c1caa818504425496ea37278d80b1c44

[ "Apache-2.0" ]

19

2020-11-11T13:00:22.000Z

2022-03-14T11:18:04.000Z

qutipy/misc/__init__.py

sumeetkhatri/QuTIPy

ca2a3344c1caa818504425496ea37278d80b1c44

[ "Apache-2.0" ]

null

qutipy/misc/__init__.py

sumeetkhatri/QuTIPy

ca2a3344c1caa818504425496ea37278d80b1c44

[ "Apache-2.0" ]

1

2022-03-03T15:20:15.000Z

from qutipy.misc.base_number_to_int import base_number_to_int from qutipy.misc.cvxpy_to_numpy import cvxpy_to_numpy from qutipy.misc.numpy_to_cvxpy import numpy_to_cvxpy

56.333333

61

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32

169

4.3125

0.3125

0.217391

0.304348

0.217391

0

0.065089

169

3

62

56.333333

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1

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true

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null

1

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1

0

null

0

1

0

1

0

1

0

7

7883155b6611d7eac76ec25c2e1f69a3300e7e30

22,523

py

Python

tests/circuit_graph/test_circuit_graph_hash.py

Jaybsoni/pennylane

3871332dd962fb4f62bf4989d109bcb9f2128d7b

[ "Apache-2.0" ]

2

2019-09-02T00:28:31.000Z

2021-07-16T09:58:05.000Z

tests/circuit_graph/test_circuit_graph_hash.py

Jaybsoni/pennylane

3871332dd962fb4f62bf4989d109bcb9f2128d7b

[ "Apache-2.0" ]

null

tests/circuit_graph/test_circuit_graph_hash.py

Jaybsoni/pennylane

3871332dd962fb4f62bf4989d109bcb9f2128d7b

[ "Apache-2.0" ]

1

2019-09-02T00:29:26.000Z

# Copyright 2018-2020 Xanadu Quantum Technologies Inc. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Unit and integration tests for creating the :mod:`pennylane` :attr:`QNode.qtape.graph.hash` attribute. """ import pytest import numpy as np import pennylane as qml from pennylane.operation import Tensor from pennylane.circuit_graph import CircuitGraph from pennylane.wires import Wires class TestCircuitGraphHash: """Test the creation of a hash on a CircuitGraph""" numeric_queues = [ ([qml.RX(0.3, wires=[0])], [], "RX!0.3![0]|||"), ( [ qml.RX(0.3, wires=[0]), qml.RX(0.4, wires=[1]), qml.RX(0.5, wires=[2]), ], [], "RX!0.3![0]RX!0.4![1]RX!0.5![2]|||", ), ] @pytest.mark.parametrize("queue, observable_queue, expected_string", numeric_queues) def test_serialize_numeric_arguments(self, queue, observable_queue, expected_string): """Tests that the same hash is created for two circuitgraphs that have numeric arguments.""" circuit_graph_1 = CircuitGraph(queue, observable_queue, Wires([0, 1, 2])) circuit_graph_2 = CircuitGraph(queue, observable_queue, Wires([0, 1, 2])) assert circuit_graph_1.serialize() == circuit_graph_2.serialize() assert expected_string == circuit_graph_1.serialize() observable1 = qml.PauliZ(0) observable1.return_type = not None observable2 = qml.Hermitian(np.array([[1, 0], [0, -1]]), wires=[0]) observable2.return_type = not None observable3 = Tensor(qml.PauliZ(0) @ qml.PauliZ(1)) observable3.return_type = not None numeric_observable_queue = [ ([], [observable1], "|||PauliZ[0]"), ([], [observable2], "|||Hermitian![[ 1 0]\n [ 0 -1]]![0]"), ([], [observable3], "|||['PauliZ', 'PauliZ'][0, 1]"), ] @pytest.mark.parametrize("queue, observable_queue, expected_string", numeric_observable_queue) def test_serialize_numeric_arguments_observables( self, queue, observable_queue, expected_string ): """Tests that the same hash is created for two circuitgraphs that have identical queues and empty variable_deps.""" circuit_graph_1 = CircuitGraph(queue, observable_queue, Wires([0, 1])) circuit_graph_2 = CircuitGraph(queue, observable_queue, Wires([0, 1])) assert circuit_graph_1.serialize() == circuit_graph_2.serialize() assert expected_string == circuit_graph_1.serialize() class TestQNodeCircuitHashIntegration: """Test for the circuit hash that is being created for a QNode during evaluation (inside of _construct)""" def test_evaluate_circuit_hash_numeric(self): """Tests that the circuit hash of identical circuits containing only numeric parameters are equal""" dev = qml.device("default.qubit", wires=2) a = 0.3 b = 0.2 def circuit1(): qml.RX(a, wires=[0]) qml.RY(b, wires=[1]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node1 = qml.QNode(circuit1, dev) node1.construct([], {}) circuit_hash_1 = node1.qtape.graph.hash def circuit2(): qml.RX(a, wires=[0]) qml.RY(b, wires=[1]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node2 = qml.QNode(circuit2, dev) node2.construct([], {}) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 == circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_symbolic(self, x, y): """Tests that the circuit hash of identical circuits containing only symbolic parameters are equal""" dev = qml.device("default.qubit", wires=2) def circuit1(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 == circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_numeric_and_symbolic(self, x, y): """Tests that the circuit hash of identical circuits containing numeric and symbolic parameters are equal""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 == circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_numeric_and_symbolic_tensor_return(self, x, y): """Tests that the circuit hashes of identical circuits having a tensor product in the return statement are equal""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 == circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_same_operation_has_numeric_and_symbolic(self, x, y): """Tests that the circuit hashes of identical circuits where one operation has both numeric and symbolic arguments are equal""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 == circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_numeric_and_symbolic_return_type_does_not_matter(self, x, y): """Tests that the circuit hashes of identical circuits only differing on their return types are equal""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.var(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash def circuit3(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.sample(qml.PauliZ(0) @ qml.PauliX(1)) node3 = qml.QNode(circuit1, dev) node3(x, y) circuit_hash_3 = node3.qtape.graph.hash assert circuit_hash_1 == circuit_hash_2 == circuit_hash_3 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_hermitian(self, x, y): """Tests that the circuit hashes of identical circuits containing a Hermitian observable are equal""" dev = qml.device("default.qubit", wires=3) matrix = np.array([[1, 0], [0, 1]]) def circuit1(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.Hermitian(matrix, wires=[0]) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.Hermitian(matrix, wires=[0]) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 == circuit_hash_2 class TestQNodeCircuitHashDifferentHashIntegration: """Tests for checking that different circuit graph hashes are being created for different circuits in a QNode during evaluation (inside of _construct)""" def test_evaluate_circuit_hash_numeric_different(self): """Tests that the circuit hashes of identical circuits except for one numeric value are different""" dev = qml.device("default.qubit", wires=2) a = 0.3 b = 0.2 def circuit1(): qml.RX(a, wires=[0]) qml.RY(b, wires=[1]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1.construct([], {}) circuit_hash_1 = node1.qtape.graph.hash c = 0.6 def circuit2(): qml.RX(c, wires=[0]) qml.RY(b, wires=[1]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2.construct([], {}) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 def test_evaluate_circuit_hash_numeric_different_operation(self): """Tests that the circuit hashes of identical circuits except for one of the operations are different""" dev = qml.device("default.qubit", wires=2) a = 0.3 def circuit1(): qml.RX(a, wires=[0]) return qml.expval(qml.PauliZ(0)) node1 = qml.QNode(circuit1, dev) node1.construct([], {}) circuit_hash_1 = node1.qtape.graph.hash def circuit2(): qml.RY(a, wires=[0]) return qml.expval(qml.PauliZ(0)) node2 = qml.QNode(circuit2, dev) node2.construct([], {}) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_numeric_and_symbolic_operation_differs(self, x, y): """Tests that the circuit hashes of identical circuits that have numeric and symbolic arguments except for one of the operations are different""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.RX(x, wires=[0]) qml.RZ(y, wires=[1]) # <-------------------------------------- RZ qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) # <-------------------------------------- RY qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_different_return_observable_vs_tensor(self, x, y): """Tests that the circuit hashes of identical circuits except for the return statement are different""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0)) # <------------- qml.PauliZ(0) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.3, wires=[2]) qml.CNOT(wires=[0, 1]) return qml.expval( qml.PauliZ(0) @ qml.PauliX(1) ) # <------------- qml.PauliZ(0) @ qml.PauliX(1) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_same_operation_has_numeric_and_symbolic_different_order( self, x, y ): """Tests that the circuit hashes of identical circuits except for the order of numeric and symbolic arguments in one of the operations are different.""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.Rot(x, 0.3, y, wires=[0]) # <------------- x, 0.3, y qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.3, wires=[0]) # <------------- x, y, 0.3 qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_same_operation_has_numeric_and_symbolic_different_argument( self, x, y ): """Tests that the circuit hashes of identical circuits except for the numeric value in one of the operations are different.""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.Rot(x, y, 0.3, wires=[0]) # <------------- 0.3 qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.5, wires=[0]) # <------------- 0.5 qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 2), np.linspace(-2 * np.pi, 2 * np.pi, 2) ** 2 / 11), ) def test_evaluate_circuit_hash_same_operation_has_numeric_and_symbolic_different_wires( self, x, y ): """Tests that the circuit hashes of identical circuits except for the wires in one of the operations are different.""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) # <------ wires = [0, 1] return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[1, 0]) # <------ wires = [1, 0] return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 2), np.linspace(-2 * np.pi, 2 * np.pi, 2) ** 2 / 11), ) def test_evaluate_circuit_hash_same_operation_has_numeric_and_symbolic_different_wires_in_return( self, x, y ): """Tests that the circuit hashes of identical circuits except for the wires in the return statement are different.""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) # <----- (0) @ (1) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(2)) # <----- (0) @ (2) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 7), np.linspace(-2 * np.pi, 2 * np.pi, 7) ** 2 / 11), ) def test_evaluate_circuit_hash_numeric_and_symbolic_different_parameter(self, x, y): """Tests that the circuit hashes of identical circuits except for the numeric argument of a signle operation in the circuits are different""" dev = qml.device("default.qubit", wires=3) def circuit1(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.3, wires=[2]) # <------------- 0.3 qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.RX(x, wires=[0]) qml.RY(y, wires=[1]) qml.RZ(0.5, wires=[2]) # <------------- 0.5 qml.CNOT(wires=[0, 1]) return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.parametrize( "x,y", zip(np.linspace(-2 * np.pi, 2 * np.pi, 2), np.linspace(-2 * np.pi, 2 * np.pi, 2) ** 2 / 11), ) def test_evaluate_circuit_hash_hermitian_different_matrices(self, x, y): """Tests that the circuit hashes of identical circuits except for the matrix argument of the Hermitian observable in the return statement are different.""" dev = qml.device("default.qubit", wires=3) matrix_1 = np.array([[1, 0], [0, 1]]) matrix_2 = np.array([[1, 0], [0, -1]]) def circuit1(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.Hermitian(matrix_1, wires=[0]) @ qml.PauliX(1)) node1 = qml.QNode(circuit1, dev) node1(x, y) circuit_hash_1 = node1.qtape.graph.hash def circuit2(x, y): qml.Rot(x, y, 0.3, wires=[0]) qml.CNOT(wires=[0, 1]) return qml.expval(qml.Hermitian(matrix_2, wires=[0]) @ qml.PauliX(1)) node2 = qml.QNode(circuit2, dev) node2(x, y) circuit_hash_2 = node2.qtape.graph.hash assert circuit_hash_1 != circuit_hash_2 @pytest.mark.usefixtures("skip_if_no_dask_support") def test_compiled_program_was_stored(self): """Test that QVM device stores the compiled program correctly""" dev = qml.device("default.qubit", wires=3) def circuit(params, wires): qml.Hadamard(0) qml.CNOT(wires=[0, 1]) obs = [qml.PauliZ(0) @ qml.PauliZ(1)] obs_list = obs * 6 qnodes = qml.map(circuit, obs_list, dev) qnodes([], parallel=True) hashes = set() for qnode in qnodes: hashes.add(qnode.qtape.graph.hash) assert len(hashes) == 1

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78a9c4b81039214d92bcf1ead15d901162d57a66

148

py

Python

pyFT/__init__.py

lesibius/pyFT

509bb047d629d8de5049df74e02b09fb91610347

[ "MIT" ]

null

pyFT/__init__.py

lesibius/pyFT

509bb047d629d8de5049df74e02b09fb91610347

[ "MIT" ]

null

pyFT/__init__.py

lesibius/pyFT

509bb047d629d8de5049df74e02b09fb91610347

[ "MIT" ]

null

from pyFT.Request import * from pyFT.Result import * from pyFT.FTQuerySyntax import * from pyFT.FTError import * import pyFT.FTHelper as FTHelper

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py

Python

src/spaceone/board/error/__init__.py

spaceone-dev/board

1733756344240b1498bca85b6e1b88d741425ea0

[ "Apache-2.0" ]

null

src/spaceone/board/error/__init__.py

spaceone-dev/board

1733756344240b1498bca85b6e1b88d741425ea0

[ "Apache-2.0" ]

1

2022-03-23T06:44:15.000Z

2022-03-23T06:52:39.000Z

src/spaceone/board/error/__init__.py

spaceone-dev/board

1733756344240b1498bca85b6e1b88d741425ea0

[ "Apache-2.0" ]

1

2022-03-22T08:59:01.000Z

from spaceone.board.error.board import * from spaceone.board.error.post import *

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ecd71f4acde2201d880cb6e181bc9fe9efa1cc57

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py

Python

data/pytorch_example/model.py

YiRuitao/single-path-nas-pytorch

13de3e6162c868e94a79a836784f7219dfc9367a

[ "MIT" ]

1

2021-07-20T09:25:59.000Z

data/pytorch_example/model.py

YiRuitao/Single-Path-NAS-with-MAESTRO

13de3e6162c868e94a79a836784f7219dfc9367a

[ "MIT" ]

null

data/pytorch_example/model.py

YiRuitao/Single-Path-NAS-with-MAESTRO

13de3e6162c868e94a79a836784f7219dfc9367a

[ "MIT" ]

null

import torch import torchvision.models as models import torch from torch.autograd import Variable import torch.nn as nn import torch.nn.functional as F import csv from util import * def profile_MnasNet(dataflow): model_name = "MnasNet-A1" print("="*50) print("Profiling model: ", model_name) print("="*50) input_size = (3, 224, 224) num_classes = 1000 flops = 0 profiled_layers = [] blocks_args = [] with open("data/" + model_name + ".csv", mode='r') as model_file: model_reader = csv.reader(model_file, delimiter=',') for row in model_reader: blocks_args += row # Stem part layer_type, kernel_size, stride, out_channels = "Conv", 3, (2, 2), 32 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple((layer_type, input_size, output_size, stride, nb_params, R, S))) flops += flop # MnasNet-A1: SepConv layer_type, input_size, kernel_size, stride, out_channels = "SepConv", output_size, 3, (1, 1), 16 output_size1, nb_params1, R1, S1, output_size, nb_params2, R2, S2, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple(("DWConv", input_size, output_size1, stride, nb_params1, R1, S1))) profiled_layers.append(tuple(("Conv", output_size1, output_size, stride, nb_params2, R2, S2))) flops += flop # Backbone part for blocks_string in blocks_args: layers, output_size, flop = profile_blockargs(blocks_string, output_size) profiled_layers += layers flops += flop # Head part layer_type, input_size, kernel_size, stride, out_channels = "Conv", output_size, 1, (1, 1), 1280 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers += [tuple((layer_type, input_size, output_size, stride, nb_params, R, S))] flops += flop layer_type, input_size, out_features = "Linear", output_size, num_classes output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop print("Total number of flops:", flops) summary = make_summary(profiled_layers, dataflow=dataflow, model_name=model_name) # Get number of parameters layer_names = list(summary.keys()) params = list(map(lambda x: int(summary[x]['nb_params']), layer_names)) print("Total number of parameters:", sum(params)) def profile_MobileNetV2(dataflow): model_name = "MobileNet-V2" print("="*50) print("Profiling model: ", model_name) print("="*50) input_size = (3, 224, 224) num_classes = 1000 flops = 0 profiled_layers = [] blocks_args = [] with open("data/" + model_name + ".csv", mode='r') as model_file: model_reader = csv.reader(model_file, delimiter=',') for row in model_reader: blocks_args += row # Stem part layer_type, kernel_size, stride, out_channels = "Conv", 3, (2, 2), 32 output_size, nb_params, R, S, flop =\ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple((layer_type, input_size, output_size, stride, nb_params, R, S))) flops += flop # Mobilenet-V2: layer_type, input_size, kernel_size, stride, out_channels = "SepConv", output_size, 3, (1, 1), 16 output_size1, nb_params1, R1, S1, output_size, nb_params2, R2, S2, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple(("DWConv", input_size, output_size1, stride, nb_params1, R1, S1))) profiled_layers.append(tuple(("Conv", output_size1, output_size, stride, nb_params2, R2, S2))) flops += flop # Backbone part for blocks_string in blocks_args: layers, output_size, flop = profile_blockargs(blocks_string, output_size) profiled_layers += layers flops += flop # Head part layer_type, input_size, kernel_size, stride, out_channels = "Conv", output_size, 1, (1, 1), 1280 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers += [tuple((layer_type, input_size, output_size, stride, nb_params, R, S))] flops += flop layer_type, input_size, out_features = "Linear", output_size, num_classes output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop print("Total number of flops:", flops) summary = make_summary(profiled_layers, dataflow=dataflow, model_name=model_name) # Get number of parameters layer_names = list(summary.keys()) params = list(map(lambda x: int(summary[x]['nb_params']), layer_names)) print("Total number of parameters:", sum(params)) def profile_MobileNetV3_large(dataflow): model_name = "MobileNet-V3-large" print("="*50) print("Profiling model: ", model_name) print("="*50) input_size = (3, 224, 224) num_classes = 1000 flops = 0 profiled_layers = [] blocks_args = [] with open("data/" + model_name + ".csv", mode='r') as model_file: model_reader = csv.reader(model_file, delimiter=',') for row in model_reader: blocks_args += row # Stem part layer_type, kernel_size, stride, out_channels = "Conv", 3, (2, 2), 16 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple((layer_type, input_size, output_size, stride, nb_params, R, S))) flops += flop # MobileNet-V3-large: None # Backbone part for blocks_string in blocks_args: layers, output_size, flop = profile_blockargs(blocks_string, output_size, use_bias=False) profiled_layers += layers flops += flop # Head part layer_type, input_size, kernel_size, stride, out_channels = "Conv", output_size, 1, (1, 1), 960 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers += [tuple((layer_type, input_size, output_size, stride, nb_params, R, S))] flops += flop layer_type, input_size, out_features = "Linear", output_size, 1280 output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features, use_pool=True) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop layer_type, input_size, out_features = "Linear", output_size, num_classes output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features, use_pool=False) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop print("Total number of flops:", flops) summary = make_summary(profiled_layers, dataflow=dataflow, model_name=model_name) # Get number of parameters layer_names = list(summary.keys()) params = list(map(lambda x: int(summary[x]['nb_params']), layer_names)) print("Total number of parameters:", sum(params)) def profile_MobileNetV3_small(dataflow): model_name = "MobileNet-V3-small" print("="*50) print("Profiling model: ", model_name) print("="*50) input_size = (3, 224, 224) num_classes = 1000 flops = 0 profiled_layers = [] blocks_args = [] with open("data/" + model_name + ".csv", mode='r') as model_file: model_reader = csv.reader(model_file, delimiter=',') for row in model_reader: blocks_args += row # Stem part layer_type, kernel_size, stride, out_channels = "Conv", 3, (2, 2), 16 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple((layer_type, input_size, output_size, stride, nb_params, R, S))) flops += flop # MobileNet-V3: None # Backbone part for blocks_string in blocks_args: layers, output_size, flop = profile_blockargs(blocks_string, output_size, use_bias=False) profiled_layers += layers flops += flop # Head part layer_type, input_size, kernel_size, stride, out_channels = "Conv", output_size, 1, (1, 1), 576 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers += [tuple((layer_type, input_size, output_size, stride, nb_params, R, S))] flops += flop # MobileNet-V3-small: SE input_size, expansion = output_size, 0.25 output_size1, nb_params1, R1, S1, output_size, nb_params2, R2, S2, flop = \ get_se_output_and_params_and_flops(input_size, expansion=expansion, bias=False) layers.append(tuple(("Linear", input_size, output_size1, None, nb_params1, R1, S1))) layers.append(tuple(("Linear", output_size1, output_size, None, nb_params2, R2, S2))) flops += flop layer_type, input_size, out_features = "Linear", output_size, 1024 output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features, use_pool=True) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop layer_type, input_size, out_features = "Linear", output_size, num_classes output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features, use_pool=False) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop print("Total number of flops:", flops) summary = make_summary(profiled_layers, dataflow=dataflow, model_name=model_name) # Get number of parameters layer_names = list(summary.keys()) params = list(map(lambda x: int(summary[x]['nb_params']), layer_names)) print("Total number of parameters:", sum(params)) def profile_ProxylessNAS(dataflow): model_name = "ProxylessNAS" print("="*50) print("Profiling model: ", model_name) print("="*50) input_size = (3, 224, 224) num_classes = 1000 flops = 0 profiled_layers = [] blocks_args = [] with open("data/" + model_name + ".csv", mode='r') as model_file: model_reader = csv.reader(model_file, delimiter=',') for row in model_reader: blocks_args += row # Stem part layer_type, kernel_size, stride, out_channels = "Conv", 3, (2, 2), 32 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple((layer_type, input_size, output_size, stride, nb_params, R, S))) flops += flop # ProxylessNAS: layer_type, input_size, kernel_size, stride, out_channels = "SepConv", output_size, 3, (1, 1), 16 output_size1, nb_params1, R1, S1, output_size, nb_params2, R2, S2, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple(("DWConv", input_size, output_size1, stride, nb_params1, R1, S1))) profiled_layers.append(tuple(("Conv", output_size1, output_size, stride, nb_params2, R2, S2))) flops += flop # Backbone part for blocks_string in blocks_args: layers, output_size, flop = profile_blockargs(blocks_string, output_size) profiled_layers += layers flops += flop # Head part layer_type, input_size, kernel_size, stride, out_channels = "Conv", output_size, 1, (1, 1), 1280 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels, use_bn=True) profiled_layers += [tuple((layer_type, input_size, output_size, stride, nb_params, R, S))] flops += flop layer_type, input_size, out_features = "Linear", output_size, num_classes output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features, use_pool=True) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop print("Total number of flops:", flops) summary = make_summary(profiled_layers, dataflow=dataflow, model_name=model_name) # Get number of parameters layer_names = list(summary.keys()) params = list(map(lambda x: int(summary[x]['nb_params']), layer_names)) print("Total number of parameters:", sum(params)) def profile_SinglepathNAS(dataflow): model_name = "SinglepathNAS" print("="*50) print("Profiling model: ", model_name) print("="*50) input_size = (3, 224, 224) num_classes = 1000 flops = 0 profiled_layers = [] blocks_args = [] with open("data/" + model_name + ".csv", mode='r') as model_file: model_reader = csv.reader(model_file, delimiter=',') for row in model_reader: blocks_args += row # Stem part layer_type, kernel_size, stride, out_channels = "Conv", 3, (2, 2), 32 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers.append(tuple((layer_type, input_size, output_size, stride, nb_params, R, S))) flops += flop # SinglepathNAS: None # Backbone part for blocks_string in blocks_args: layers, output_size, flop = profile_blockargs(blocks_string, output_size) profiled_layers += layers flops += flop # Head part layer_type, input_size, kernel_size, stride, out_channels = "Conv", output_size, 1, (1, 1), 1280 output_size, nb_params, R, S, flop = \ get_conv_output_and_params_and_flops(input_size, layer_type, kernel_size, stride, out_channels=out_channels) profiled_layers += [tuple((layer_type, input_size, output_size, stride, nb_params, R, S))] flops += flop layer_type, input_size, out_features = "Linear", output_size, num_classes output_size, nb_params, R, S, flop = get_linear_output_size_and_nb_param(input_size, out_features, use_pool=True) profiled_layers += [tuple((layer_type, input_size, output_size, None, nb_params, R, S))] flops += flop print("Total number of flops:", flops) summary = make_summary(profiled_layers, dataflow=dataflow, model_name=model_name) # Get number of parameters layer_names = list(summary.keys()) params = list(map(lambda x: int(summary[x]['nb_params']), layer_names)) print("Total number of parameters:", sum(params))

44.695906

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0.086502

0.03621

0.040233

0.942265

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15,286

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null

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1

0

1

0

null

0

7

bf19f041da373831fcd1ff1a998734f4ca50f9de

147

py

Python

prettypyplot/gallery.py

braniii/prettypyplot

39d7d133fe0dc6699fafd57e00a0ec07672fd344

[ "BSD-3-Clause" ]

null

prettypyplot/gallery.py

braniii/prettypyplot

39d7d133fe0dc6699fafd57e00a0ec07672fd344

[ "BSD-3-Clause" ]

null

prettypyplot/gallery.py

braniii/prettypyplot

39d7d133fe0dc6699fafd57e00a0ec07672fd344

[ "BSD-3-Clause" ]

null

""" # Gallery .. include:: ../gallery/legend/README.md .. include:: ../gallery/colorbar/README.md .. include:: ../gallery/subplots/README.md """

16.333333

42

0.646259

16

147

5.9375

0.4375

0.442105

0.315789

0.463158

0

0.102041

147

8

43

18.375

0.719697

0.931973

0

null

0

null

0

null

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true

0

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null

1

0

1

0

1

0

null

0

1

0

7

1709e5de22ff390cf7b42040ee1d013227441504

10,181

py

Python

rlkit/samplers/data_collector/path_collector.py

HamzaHz2/rlkit

55f30c2f1830693624bc5d4085ab9a1ac80b30c4

[ "MIT" ]

1

2019-10-23T11:03:28.000Z

rlkit/samplers/data_collector/path_collector.py

HamzaHz2/rlkit

55f30c2f1830693624bc5d4085ab9a1ac80b30c4

[ "MIT" ]

null

rlkit/samplers/data_collector/path_collector.py

HamzaHz2/rlkit

55f30c2f1830693624bc5d4085ab9a1ac80b30c4

[ "MIT" ]

3

2020-11-30T15:15:31.000Z

2022-01-11T10:53:19.000Z

from collections import OrderedDict, deque import numpy as np from rlkit.core.eval_util import create_stats_ordered_dict from rlkit.samplers.data_collector.base import PathCollector from rlkit.samplers.rollout_functions import ( multiagent_multitask_rollout, vec_multitask_rollout, multitask_rollout, rollout, ) class MdpPathCollector(PathCollector): def __init__( self, env, policy, max_num_epoch_paths_saved=None, render=False, render_kwargs=None, ): if render_kwargs is None: render_kwargs = {} self._env = env self._policy = policy self._max_num_epoch_paths_saved = max_num_epoch_paths_saved self._epoch_paths = deque(maxlen=self._max_num_epoch_paths_saved) self._render = render self._render_kwargs = render_kwargs self._num_steps_total = 0 self._num_paths_total = 0 def collect_new_paths( self, max_path_length, num_steps, discard_incomplete_paths, ): paths = [] num_steps_collected = 0 while num_steps_collected < num_steps: max_path_length_this_loop = min( # Do not go over num_steps max_path_length, num_steps - num_steps_collected, ) path = rollout( self._env, self._policy, max_path_length=max_path_length_this_loop, ) path_len = len(path["actions"]) if ( path_len != max_path_length and not path["terminals"][-1] and discard_incomplete_paths ): break num_steps_collected += path_len paths.append(path) self._num_paths_total += len(paths) self._num_steps_total += num_steps_collected self._epoch_paths.extend(paths) return paths def get_epoch_paths(self): return self._epoch_paths def end_epoch(self, epoch): self._epoch_paths = deque(maxlen=self._max_num_epoch_paths_saved) def get_diagnostics(self): path_lens = [len(path["actions"]) for path in self._epoch_paths] stats = OrderedDict( [ ("num steps total", self._num_steps_total), ("num paths total", self._num_paths_total), ] ) stats.update( create_stats_ordered_dict( "path length", path_lens, always_show_all_stats=True, ) ) success = [path["rewards"][-1][0] > 0 for path in self._epoch_paths] stats["SuccessRate"] = sum(success) / len(success) return stats def get_snapshot(self): return dict( # env=self._env, policy=self._policy, ) class GoalConditionedPathCollector(PathCollector): def __init__( self, env, policy, max_num_epoch_paths_saved=None, render=False, render_kwargs=None, observation_key="observation", desired_goal_key="desired_goal", representation_goal_key="representation_goal", ): if render_kwargs is None: render_kwargs = {} self._env = env self._policy = policy self._max_num_epoch_paths_saved = max_num_epoch_paths_saved self._render = render self._render_kwargs = render_kwargs self._epoch_paths = deque(maxlen=self._max_num_epoch_paths_saved) self._observation_key = observation_key self._desired_goal_key = desired_goal_key self._representation_goal_key = representation_goal_key self._num_steps_total = 0 self._num_paths_total = 0 def collect_new_paths( self, max_path_length, num_steps, discard_incomplete_paths, ): paths = [] num_steps_collected = 0 while num_steps_collected < num_steps: max_path_length_this_loop = min( # Do not go over num_steps max_path_length, num_steps - num_steps_collected, ) path = multitask_rollout( self._env, self._policy, max_path_length=max_path_length_this_loop, render=self._render, render_kwargs=self._render_kwargs, observation_key=self._observation_key, desired_goal_key=self._desired_goal_key, representation_goal_key=self._representation_goal_key, return_dict_obs=True, ) path_len = len(path["actions"]) if ( path_len != max_path_length and not path["terminals"][-1] and discard_incomplete_paths ): break num_steps_collected += path_len paths.append(path) self._num_paths_total += len(paths) self._num_steps_total += num_steps_collected self._epoch_paths.extend(paths) return paths def get_epoch_paths(self): return self._epoch_paths def end_epoch(self, epoch): self._epoch_paths = deque(maxlen=self._max_num_epoch_paths_saved) def get_diagnostics(self): path_lens = [len(path["actions"]) for path in self._epoch_paths] stats = OrderedDict( [ ("num steps total", self._num_steps_total), ("num paths total", self._num_paths_total), ] ) stats.update( create_stats_ordered_dict( "path length", path_lens, always_show_all_stats=True, ) ) success = [path["env_infos"]["success"][-1] for path in self._epoch_paths] stats["SuccessRate"] = sum(success) / len(success) return stats def get_snapshot(self): return dict( # env=self._env, policy=self._policy, observation_key=self._observation_key, desired_goal_key=self._desired_goal_key, ) class ParallelGoalConditionedPathCollector(GoalConditionedPathCollector): def collect_new_paths( self, max_path_length, num_steps, discard_incomplete_paths, ): paths = [] num_steps_collected = 0 rollouts = None obs_reset = None while num_steps_collected < num_steps: max_path_length_this_loop = min( # Do not go over num_steps max_path_length, num_steps - num_steps_collected, ) collected_paths, rollouts, obs_reset = vec_multitask_rollout( self._env, self._policy, rollouts, obs_reset, max_path_length=max_path_length_this_loop, render=self._render, render_kwargs=self._render_kwargs, observation_key=self._observation_key, desired_goal_key=self._desired_goal_key, representation_goal_key=self._representation_goal_key, return_dict_obs=True, ) paths_len = [] for path in collected_paths: path_len = len(path["actions"]) paths_len.append(path_len) num_steps_collected += path_len paths.append(path) i = np.argmax(paths_len) if ( paths_len[i] != max_path_length and not paths[i]["terminals"][-1] and discard_incomplete_paths ): break self._num_paths_total += len(paths) self._num_steps_total += num_steps_collected self._epoch_paths.extend(paths) return paths class MultiAgentGoalConditionedPathCollector(GoalConditionedPathCollector): def __init__( self, env, policy, max_num_epoch_paths_saved=None, render=False, render_kwargs=None, observation_key="observation", achieved_q_key="achieved_q", desired_q_key="desired_q", representation_goal_key="representation_goal", ): if render_kwargs is None: render_kwargs = {} self._env = env self._policy = policy self._max_num_epoch_paths_saved = max_num_epoch_paths_saved self._render = render self._render_kwargs = render_kwargs self._epoch_paths = deque(maxlen=self._max_num_epoch_paths_saved) self._observation_key = observation_key self._achieved_q_key = achieved_q_key self._desired_q_key = desired_q_key self._representation_goal_key = representation_goal_key self._num_steps_total = 0 self._num_paths_total = 0 def collect_new_paths( self, max_path_length, num_steps, discard_incomplete_paths, ): paths = [] num_steps_collected = 0 while num_steps_collected < num_steps: max_path_length_this_loop = min( # Do not go over num_steps max_path_length, num_steps - num_steps_collected, ) path_a, path_b = multiagent_multitask_rollout( self._env, self._policy, max_path_length=max_path_length_this_loop, render=self._render, render_kwargs=self._render_kwargs, observation_key=self._observation_key, achieved_q_key=self._achieved_q_key, desired_q_key=self._desired_q_key, representation_goal_key=self._representation_goal_key, ) for path in [path_a, path_b]: path_len = len(path["actions"]) if path_len > 0: num_steps_collected += path_len paths.append(path) self._num_paths_total += len(paths) self._num_steps_total += num_steps_collected self._epoch_paths.extend(paths) return paths def get_snapshot(self): return dict( # env=self._env, policy=self._policy, observation_key=self._observation_key, achieved_q_key=self._achieved_q_key, desired_q_key=self._desired_q_key, )

34.511864

83

0.602593

1,144

10,181

4.891608

0.092657

0.067191

0.053431

0.040029

0.879199

0.853109

0.841673

0.834525

0.813974

0

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0.326883

10,181

294

84

34.629252

0.81395

0.014144

0

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0

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false

0

0.018727

0.134831

0

null

0

1

0

1

0

null

0

7

bdc5c98a5002facf815b4810f855515866fe9235

58

py

Python

pyDataHubImp/entities/satellites/__init__.py

bartcallaerts/Braindate_Tesla_Datahub

e5b3421eb228fca25f679004c140b883de8ac886

[ "MIT" ]

null

pyDataHubImp/entities/satellites/__init__.py

bartcallaerts/Braindate_Tesla_Datahub

e5b3421eb228fca25f679004c140b883de8ac886

[ "MIT" ]

null

pyDataHubImp/entities/satellites/__init__.py

bartcallaerts/Braindate_Tesla_Datahub

e5b3421eb228fca25f679004c140b883de8ac886

[ "MIT" ]

null

from .ODS_Supplier_Details_S import ODS_Supplier_Details_S

58

0.931034

10

58

4.8

0.6

0.458333

0.75

0.791667

0

0.051724

58

1

58

0.872727

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

bdcd1bc6b8215c84a638a09d6d383e9aeac6fbe3

17,554

py

Python

envision_table_to_html.py

hbuter-rubrik/rubrik-scripts-for-python

0e434854b778ff0f857425173e5cb7d6b83dddec

[ "MIT" ]

5

2019-10-04T18:09:24.000Z

2020-08-25T04:46:01.000Z

envision_table_to_html.py

hbuter-rubrik/rubrik-scripts-for-python

0e434854b778ff0f857425173e5cb7d6b83dddec

[ "MIT" ]

2

2020-01-07T18:25:11.000Z

2021-10-14T11:48:27.000Z

envision_table_to_html.py

hbuter-rubrik/rubrik-scripts-for-python

0e434854b778ff0f857425173e5cb7d6b83dddec

[ "MIT" ]

6

2019-04-25T10:26:30.000Z

2021-11-18T08:20:50.000Z

from RubrikSession import RubrikSession from getpass import getpass import requests import datetime import re #report_id = '44d1229d-6d22-418a-abfd-42100480439b' report_id = 'b306ba74-240f-4a23-a51e-e86ca2175956' BASE_HTML = '<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> \ <html xmlns="http://www.w3.org/1999/xhtml"> \ <head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"> \ <meta name="viewport" content="width=device-width, initial-scale=1.0"> \ <link href="https://fonts.googleapis.com/css?family=Ubuntu:500" rel="stylesheet"></head> \ <body> \ <style> \ #leftcolumn dl{display:block;margin-left:20px;} \ #leftcolumn dt{font-size:120%;color:#000;margin:10px 0 0;padding:0;} \ #leftcolumn dt.imp strong{font-weight:normal;color:red;} \ #leftcolumn dd{margin:0;padding:0;} \ #hor-minimalist-b{font-family:"Ubuntu", sans-serif;font-size:14px;background:#fff;width:480px;border-collapse:collapse;text-align:left;margin:20px;} \ #hor-minimalist-b th{font-size:16px;font-weight:600;color:#000;border-bottom:2px solid #000;padding:10px 30px;} \ #hor-minimalist-b td{border-bottom:1px solid #000;color:#000;padding:6px 8px;} \ #hor-minimalist-b tbody tr:hover td{color:#000;} \ h2, h3, h4 { margin-top: 0.65em; margin-bottom: 0.23em; } \ </style> \ \ <img 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"> \ <h2> Second & Third Run - Protection Details Report </h2> \ Report Run Time:    July 19, 2017 \ \ <table id="hor-minimalist-b" summary="Job Summary Details"><tr>' #Ask Initial Questions rubrik_mgmt_ip = raw_input("Enter Rubrik MGMT ip: ") rubrik_user = raw_input("Enter in Rubrik user: ") rubrik_password = getpass("Enter in Rubrik password: ") #Instantiate Rubrik Session rubrik = RubrikSession(rubrik_mgmt_ip, rubrik_user, rubrik_password) #Get Table Data from Report params = {} params['limit'] = '9999' table_data = rubrik.get_envision_table(report_id, params) #Add Row Header for header in table_data['columns']: BASE_HTML += '<th>' + header + '</th>' #Add Rows for row in table_data['data']: row_string = "" for value in row: index = row.index(value) column_title = table_data['columns'][index] if re.findall('Percent', column_title): value = "{:.1%}".format(float(value)) row_string += '<th>' + value + '</th>' BASE_HTML += '<tr>' + row_string + '</tr>' BASE_HTML += '</table>' #Output File with open('daily_report_2.html', 'w+') as f: f.write(BASE_HTML) f.close() print 'hello'

240.465753

14,984

0.928506

839

17,554

19.38975

0.75447

0.002459

0.004303

0.001475

0.002705

0

0.143205

0.018628

17,554

72

14,985

243.805556

0.801126

0.008887

0

0.211538

0.88993

0.862959

0

1

0

null

0.057692

0.096154

null

0.019231

0

1

null

0

1

0

1

null

1

0

1

0

1

0

9

bdeac09ff21f51cca86fee602e48a8abed17032f

114

py

Python

ramda/inc_test.py

Rafi993/pyramda

4fa7fe28d5eaa798b702d28bdd3948515cb88f48

[ "MIT" ]

56

2018-08-06T08:44:58.000Z

2022-03-17T09:49:03.000Z

ramda/inc_test.py

Rafi993/pyramda

4fa7fe28d5eaa798b702d28bdd3948515cb88f48

[ "MIT" ]

28

2019-06-17T11:09:52.000Z

2022-02-18T16:59:21.000Z

ramda/inc_test.py

slavaGanzin/pyramda

4fa7fe28d5eaa798b702d28bdd3948515cb88f48

[ "MIT" ]

5

2019-09-18T09:24:38.000Z

2021-07-21T08:40:23.000Z

from .inc import inc from ramda.private.asserts import assert_equal def inc_test(): assert_equal(inc(5), 6)

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8

bdf2ce3752f9f99c957e35f5e5f579560f2000ee

926

py

Python

src/finitestate/firmware/schemas/schema_products.py

FiniteStateInc/clearcode-toolkit

521c3a2ab9d9fa6d7b9059227c6af9d09b031c33

[ "Apache-2.0" ]

null

src/finitestate/firmware/schemas/schema_products.py

FiniteStateInc/clearcode-toolkit

521c3a2ab9d9fa6d7b9059227c6af9d09b031c33

[ "Apache-2.0" ]

null

src/finitestate/firmware/schemas/schema_products.py

FiniteStateInc/clearcode-toolkit

521c3a2ab9d9fa6d7b9059227c6af9d09b031c33

[ "Apache-2.0" ]

1

2020-12-22T16:51:40.000Z

import pyspark.sql.types products_schema = pyspark.sql.types.StructType([ pyspark.sql.types.StructField('firmware_sha256', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_model_id', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_model_name', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_brand_name', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_family_name', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_model_firmware_version', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_model_firmware_id', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_brand_id', pyspark.sql.types.StringType()), pyspark.sql.types.StructField('product_categories', pyspark.sql.types.ArrayType(pyspark.sql.types.StringType())), ])

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8

da40513dd6041841a20c55f294eb7af000b0fabe

1,107

py

Python

multiworld/envs/goals/multi_domain/push_door_v1.py

Neo-X/R_multiworld

839513a48ddf2f5ae2eadc43435ac6981ddea1f4

[ "MIT" ]

null

multiworld/envs/goals/multi_domain/push_door_v1.py

Neo-X/R_multiworld

839513a48ddf2f5ae2eadc43435ac6981ddea1f4

[ "MIT" ]

null

multiworld/envs/goals/multi_domain/push_door_v1.py

Neo-X/R_multiworld

839513a48ddf2f5ae2eadc43435ac6981ddea1f4

[ "MIT" ]

2

2020-06-02T05:24:03.000Z

2020-07-07T17:01:42.000Z

#import joblib import pickle import numpy as np tasks = [# Pushing {'task': 'push' , 'obj_init_pos': np.array([0, 0.6 , 0.02]) , 'goal_pos': np.array([0, 0.81, 0.02]) , 'door_pos': np.array([0, 1.0, 0.3])} , {'task': 'push' , 'obj_init_pos': np.array([0, 0.6 , 0.02]) , 'goal_pos': np.array([-0.15, 0.77 , 0.02]) , 'door_pos': np.array([0, 1.0, 0.3]) } , {'task': 'push' , 'obj_init_pos': np.array([0, 0.6 , 0.02]) , 'goal_pos': np.array([0.15, 0.77 , 0.02]) , 'door_pos': np.array([0, 1.0, 0.3]) } , #Door {'task': 'door' , 'door_pos': np.array([0, 1.0, 0.3]) , 'padded_target_angle': np.array([0.29 , 0, 0]) , 'obj_init_pos': np.array([0, 0.6 , 0.02]) } , {'task': 'door' , 'door_pos': np.array([0, 1.0, 0.3]) , 'padded_target_angle': np.array([0.6, 0 , 0] ) , 'obj_init_pos': np.array([0, 0.6 , 0.02]) } , {'task': 'door' , 'door_pos': np.array([0, 1.0, 0.3]) , 'padded_target_angle': np.array([0.87 , 0 ,0]) , 'obj_init_pos': np.array([0, 0.6 , 0.02]) } ] #joblib.dump(tasks , 'push_door_v1.pkl') fobj = open('push_door_v1.pkl' , 'wb') pickle.dump(tasks, fobj)

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null

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8

da7709ed718c5afbeb28c76bfeff652c8baad9ba

108

py

Python

mead/tf/__init__.py

sagnik/baseline

8d75616e04c1cca509dbebbb6d08ad7e1a7b9f88

[ "Apache-2.0" ]

241

2016-04-25T20:02:31.000Z

2019-09-03T05:44:09.000Z

mead/tf/__init__.py

sagnik/baseline

8d75616e04c1cca509dbebbb6d08ad7e1a7b9f88

[ "Apache-2.0" ]

131

2019-10-12T10:53:17.000Z

2021-12-03T19:52:47.000Z

mead/tf/__init__.py

sagnik/baseline

8d75616e04c1cca509dbebbb6d08ad7e1a7b9f88

[ "Apache-2.0" ]

75

2016-06-28T01:18:58.000Z

2019-08-29T06:47:22.000Z

from mead.tf.exporters import * from mead.tf.preproc_exporters import * from mead.tf.preprocessors import *

27

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null

0

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0

7

e54868497af7035575872a2275687bff2bc1606b

12,712

py

Python

src/tests/test_pagure_flask_ui_issues_private.py

yifengyou/learn-pagure

e54ba955368918c92ad2be6347b53bb2c24a228c

[ "Unlicense" ]

null

src/tests/test_pagure_flask_ui_issues_private.py

yifengyou/learn-pagure

e54ba955368918c92ad2be6347b53bb2c24a228c

[ "Unlicense" ]

null

src/tests/test_pagure_flask_ui_issues_private.py

yifengyou/learn-pagure

e54ba955368918c92ad2be6347b53bb2c24a228c

[ "Unlicense" ]

null

# -*- coding: utf-8 -*- """ (c) 2018 - Copyright Red Hat Inc Authors: Pierre-Yves Chibon <pingou@pingoured.fr> """ from __future__ import unicode_literals, absolute_import import unittest import sys import os from mock import patch, MagicMock sys.path.insert( 0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "..") ) import pagure.lib.query # noqa import tests # noqa class PagureFlaskIssuesPrivatetests(tests.Modeltests): """Tests for flask issues controller of pagure with private tickets""" @patch("pagure.lib.notify.send_email", MagicMock(return_value=True)) def setUp(self): """ Set up the environnment, ran before every tests. """ super(PagureFlaskIssuesPrivatetests, self).setUp() # Create a 3rd user item = pagure.lib.model.User( user="random", fullname="Random user", password="foo", default_email="random@bar.com", ) self.session.add(item) item = pagure.lib.model.UserEmail(user_id=3, email="random@bar.com") self.session.add(item) self.session.commit() tests.create_projects(self.session) tests.create_projects_git(os.path.join(self.path, "repos")) repo = pagure.lib.query.get_authorized_project(self.session, "test") msg = pagure.lib.query.new_issue( session=self.session, repo=repo, title="Test issue #1", content="We should work on this for the second time", user="foo", status="Open", private=True, ) self.session.commit() self.assertEqual(msg.title, "Test issue #1") msg = pagure.lib.query.new_issue( session=self.session, repo=repo, title="Test issue #2", content="We should work on this for the second time", user="foo", status="Open", private=False, ) self.session.commit() self.assertEqual(msg.title, "Test issue #2") def test_issue_list_anonymous(self): """ Test the list of issues when user is logged out. """ output = self.app.get("/test/issues") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn("<title>Issues - test - Pagure</title>", output_text) self.assertIn( ' 1 Open Issues\n', output_text, ) def test_issue_list_admin(self): """Test the list of issues when user is an admin of the project.""" user = tests.FakeUser(username="pingou") with tests.user_set(self.app.application, user): output = self.app.get("/test/issues") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn("<title>Issues - test - Pagure</title>", output_text) self.assertIn( ' 2 Open Issues\n', output_text, ) def test_issue_list_author(self): """Test the list of issues when user is an admin of the project.""" user = tests.FakeUser(username="foo") with tests.user_set(self.app.application, user): output = self.app.get("/test/issues") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn("<title>Issues - test - Pagure</title>", output_text) self.assertIn( ' 2 Open Issues\n', output_text, ) def test_issue_list_authenticated(self): """Test the list of issues when user is authenticated but has no special access to the project. """ user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issues") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn("<title>Issues - test - Pagure</title>", output_text) self.assertIn( ' 1 Open Issues\n', output_text, ) def test_issue_list_authenticated_ticket(self): """Test the list of issues when user is authenticated but has ticket level access to the project. """ repo = pagure.lib.query._get_project(self.session, "test") msg = pagure.lib.query.add_user_to_project( session=self.session, project=repo, new_user="random", user="pingou", access="ticket", ) self.session.commit() self.assertEqual(msg, "User added") user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issues") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn("<title>Issues - test - Pagure</title>", output_text) self.assertIn( ' 1 Open Issues\n', output_text, ) def test_issue_list_authenticated_commit(self): """Test the list of issues when user is authenticated but has commit level access to the project. """ repo = pagure.lib.query._get_project(self.session, "test") msg = pagure.lib.query.add_user_to_project( session=self.session, project=repo, new_user="random", user="pingou", access="commit", ) self.session.commit() self.assertEqual(msg, "User added") user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issues") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn("<title>Issues - test - Pagure</title>", output_text) self.assertIn( ' 2 Open Issues\n', output_text, ) def test_issue_list_authenticated_assigned(self): """Test the list of issues when user is authenticated and is assigned to one of the issue. """ repo = pagure.lib.query._get_project(self.session, "test") issue = pagure.lib.query.search_issues(self.session, repo, issueid=1) issue.assignee_id = 3 # random self.session.add(issue) self.session.commit() user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issues") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn("<title>Issues - test - Pagure</title>", output_text) self.assertIn( ' 2 Open Issues\n', output_text, ) def test_view_issue_anonymous(self): """ Test accessing a private ticket when user is logged out. """ output = self.app.get("/test/issue/1") self.assertEqual(output.status_code, 404) def test_view_issue_admin(self): """Test accessing a private ticket when user is an admin of the project. """ user = tests.FakeUser(username="pingou") with tests.user_set(self.app.application, user): output = self.app.get("/test/issue/1") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn( "<title>Issue #1: Test issue #1 - test - Pagure</title>", output_text, ) self.assertIn( '\n' ' #1\n', output_text, ) def test_view_issue_author(self): """Test accessing a private ticket when user opened the ticket.""" user = tests.FakeUser(username="foo") with tests.user_set(self.app.application, user): output = self.app.get("/test/issue/1") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn( "<title>Issue #1: Test issue #1 - test - Pagure</title>", output_text, ) self.assertIn( '\n' ' #1\n', output_text, ) def test_view_issue_authenticated(self): """Test accessing a private ticket when user is authenticated but has no special access to the project. """ user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issue/1") self.assertEqual(output.status_code, 404) def test_view_issue_authenticated_ticket(self): """Test accessing a private ticket when user is authenticated and has ticket level access to the project. """ repo = pagure.lib.query._get_project(self.session, "test") msg = pagure.lib.query.add_user_to_project( session=self.session, project=repo, new_user="random", user="pingou", access="ticket", ) self.session.commit() self.assertEqual(msg, "User added") user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issue/1") self.assertEqual(output.status_code, 404) def test_view_issue_authenticated_commit(self): """Test accessing a private ticket when user is authenticated and has commit level access to the project. """ repo = pagure.lib.query._get_project(self.session, "test") msg = pagure.lib.query.add_user_to_project( session=self.session, project=repo, new_user="random", user="pingou", access="commit", ) self.session.commit() self.assertEqual(msg, "User added") user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issue/1") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn( "<title>Issue #1: Test issue #1 - test - Pagure</title>", output_text, ) self.assertIn( '\n' ' #1\n', output_text, ) def test_view_issue_authenticated_assigned(self): """Test accessing a private ticket when user is authenticated and is assigned to one of the issue. """ repo = pagure.lib.query._get_project(self.session, "test") issue = pagure.lib.query.search_issues(self.session, repo, issueid=1) issue.assignee_id = 3 # random self.session.add(issue) self.session.commit() user = tests.FakeUser(username="random") with tests.user_set(self.app.application, user): output = self.app.get("/test/issue/1") self.assertEqual(output.status_code, 200) output_text = output.get_data(as_text=True) self.assertIn( "<title>Issue #1: Test issue #1 - test - Pagure</title>", output_text, ) self.assertIn( '\n' ' #1\n', output_text, ) if __name__ == "__main__": unittest.main(verbosity=2)

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00675ab9db11009528da3ff0bc385d770e6eda52

2,468

py

Python

amb.py

RN-JK/Ubiart-Tape-Serializer

879bfe27b11c290e5653dac8735ddba322bb5716

[ "MIT" ]

null

amb.py

RN-JK/Ubiart-Tape-Serializer

879bfe27b11c290e5653dac8735ddba322bb5716

[ "MIT" ]

null

amb.py

RN-JK/Ubiart-Tape-Serializer

879bfe27b11c290e5653dac8735ddba322bb5716

[ "MIT" ]

null

import os, struct, json, zlib print("AMB TPL Serializer by: JackLSummer15") #make output directory try: os.mkdir('amb') except: pass if __name__ == '__main__': with open('amb_inject.json') as inputfile: obj = json.load(inputfile) codenames = obj[0]['maps'] ambsounds = obj[0]['ambs'] jdversion = obj[0]['JDVersion'] file_count = 0 for i, codename in enumerate(codenames, 1): for ambsfx in ambsounds: codenamelow=codename.lower() ambname='amb_'+codenamelow+'_'+ambsfx.lower() if jdversion==2015: header=b'\x00\x00\x00\x01\x00\x00\x02\xB7\x1B\x85\x7B\xCE\x00\x00\x00\x6C\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\xD9\x4D\x6C\x53\x00\x00\x01\x18\x00\x00\x00\x01\x00\x00\x00\xF8\xD8\x46\x77\x1B\x00\x00\x00\x00\xEB\x53\x7A\x60\xFF\xFF\xFF\xFF\x00\x00\x00\x00\xFF\xFF\xFF\xFF\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01' path='world/jd2015/'+codenamelow+'/audio/amb/' else: header=b'\x00\x00\x00\x01\x00\x00\x02\xB5\x1B\x85\x7B\xCE\x00\x00\x00\x6C\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\xD9\x4D\x6C\x53\x00\x00\x01\x18\x00\x00\x00\x01\x00\x00\x00\xF8\x28\xB8\x81\xEC\x00\x00\x00\x00\xEB\x53\x7A\x60\xFF\xFF\xFF\xFF\x00\x00\x00\x00\xFF\xFF\xFF\xFF\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01' path='world/maps/'+codenamelow+'/audio/amb/' ambwav=ambname+'.wav' ambtpl=ambname+'.tpl.ckd' amb=open("amb/"+ambtpl,"wb") print("making "+codename+' + '+ambsfx+'...') #header amb.write(header) #making path amb.write(struct.pack(">I",len(ambwav))+ambwav.encode('utf-8')+struct.pack(">I",len(path))+path.encode('utf-8')+struct.pack("<I",zlib.crc32(ambwav.encode('utf-8')))) #ending amb.write(b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x60\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x01\xFF\xFF\xFF\xFF\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x3F\x80\x00\x00\x3F\x80\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\xFF\xFF\xFF\xFF\xFF\xFF\xFF\xFF\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\xFF\xFF\xFF\xFF\x00\x00\x00\x00') amb.close()

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null

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8

006b1e1bf7248ad6e3d677c22a91027bd235e32e

18,406

py

Python

model_search/metric_fns_test.py

dywsjtu/model_search

116c4f9016d8b89cf06d057dda020dae3371f211

[ "Apache-2.0" ]

3,315

2021-01-20T15:21:37.000Z

2022-03-30T18:21:29.000Z

model_search/metric_fns_test.py

dywsjtu/model_search

116c4f9016d8b89cf06d057dda020dae3371f211

[ "Apache-2.0" ]

57

2021-01-19T20:51:03.000Z

2022-03-24T11:04:07.000Z

model_search/metric_fns_test.py

dywsjtu/model_search

116c4f9016d8b89cf06d057dda020dae3371f211

[ "Apache-2.0" ]

380

2021-02-20T01:31:35.000Z

2022-03-31T16:48:58.000Z

# 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. # List as: python3 """Tests for model_search.metric_fns.""" from absl.testing import parameterized from model_search import metric_fns import numpy as np import tensorflow.compat.v2 as tf class MetricFnsTest(tf.test.TestCase, parameterized.TestCase): # pylint: disable=g-long-lambda # tf.constant must be called in a lambda, otherwise the Op would be created # in a different graph from where it would be used, which is not allowed. @parameterized.named_parameters( { 'testcase_name': 'int64_label_single_task', 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([1, 1, 1, 1, 1], dtype=tf.int64), 'predictions_fn': lambda: { 'predictions': tf.constant([1, 0, 0, 0, 0], dtype=tf.int64), }, 'expected_metric_dict': { 'accuracy': np.float32(0.2) } }, { 'testcase_name': 'string_label_single_task', 'label_vocabulary': ['A', 'B', 'C', 'D', 'E'], 'labels_fn': lambda: tf.constant(['A', 'B', 'C', 'D', 'E'], dtype=tf.string), 'predictions_fn': lambda: { 'predictions': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), }, 'expected_metric_dict': { 'accuracy': np.float32(0.2) } }, { 'testcase_name': 'string_label_no_vocab_single_task', 'label_vocabulary': None, 'labels_fn': lambda: tf.constant(['A', 'B', 'C', 'D', 'E'], dtype=tf.string), 'predictions_fn': lambda: { 'predictions': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), }, 'expected_metric_dict': {} }, { 'testcase_name': 'int64_label_multi_task', 'label_vocabulary': None, 'labels_fn': lambda: { 'task_a': tf.constant([1, 1, 1, 1, 1], dtype=tf.int64), 'task_b': tf.constant([1, 1, 1, 1, 1], dtype=tf.int64), }, 'predictions_fn': lambda: { 'predictions': tf.constant([1, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_a': tf.constant([1, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_b': tf.constant([1, 1, 1, 0, 0], dtype=tf.int64), }, 'expected_metric_dict': { 'accuracy/task_a': np.float32(0.2), 'accuracy/task_b': np.float32(0.6), }, }, { 'testcase_name': 'string_label_multi_task', 'label_vocabulary': { 'task_a': ['A', 'B', 'C', 'D', 'E'], 'task_b': ['F', 'G', 'H', 'I', 'J'], }, 'labels_fn': lambda: { 'task_a': tf.constant(['A', 'B', 'C', 'D', 'E'], dtype=tf.string), 'task_b': tf.constant(['F', 'G', 'H', 'I', 'J'], dtype=tf.string), }, 'predictions_fn': lambda: { 'predictions': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_a': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_b': tf.constant([1, 1, 1, 1, 1], dtype=tf.int64), }, 'expected_metric_dict': { 'accuracy/task_a': np.float32(0.2), 'accuracy/task_b': np.float32(0.2), }, }, { 'testcase_name': 'mixed_label_multi_task', 'label_vocabulary': { 'task_a': ['A', 'B', 'C', 'D', 'E'], }, 'labels_fn': lambda: { 'task_a': tf.constant(['A', 'B', 'C', 'D', 'E'], dtype=tf.string), 'task_b': tf.constant([1, 1, 0, 0, 0], dtype=tf.int64), }, 'predictions_fn': lambda: { 'predictions': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_a': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_b': tf.constant([1, 1, 1, 1, 1], dtype=tf.int64), }, 'expected_metric_dict': { 'accuracy/task_a': np.float32(0.2), 'accuracy/task_b': np.float32(0.4), }, }, { 'testcase_name': 'string_no_vocab_multi_task', 'label_vocabulary': None, 'labels_fn': lambda: { 'task_a': tf.constant(['A', 'B', 'C', 'D', 'E'], dtype=tf.string), 'task_b': tf.constant([1, 1, 0, 0, 0], dtype=tf.int64), }, 'predictions_fn': lambda: { 'predictions': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_a': tf.constant([0, 0, 0, 0, 0], dtype=tf.int64), 'predictions/task_b': tf.constant([1, 1, 1, 1, 1], dtype=tf.int64), }, 'expected_metric_dict': { 'accuracy/task_b': np.float32(0.4), }, }) # pylint: enable=g-long-lambda def test_make_accuracy_metric_fn(self, label_vocabulary, labels_fn, predictions_fn, expected_metric_dict): # Force graph mode with tf.compat.v1.Graph().as_default(): metric_fn = metric_fns.make_accuracy_metric_fn(label_vocabulary) actual_metric_dict = metric_fn(labels_fn(), predictions_fn()) with self.test_session() as sess: sess.run(tf.compat.v1.initializers.local_variables()) sess.run(tf.compat.v1.initializers.tables_initializer()) actual_metric_dict_val = sess.run(actual_metric_dict) actual_metric_dict_val_clean = { metric_key: metric_val[1] for metric_key, metric_val in actual_metric_dict_val.items() } self.assertEqual(expected_metric_dict, actual_metric_dict_val_clean) # pylint: disable=g-long-lambda @parameterized.named_parameters( { 'testcase_name': 'roc_perfect', 'metric_fn_factory': metric_fns.make_auc_roc_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), }, 'expected_metric_dict': { 'auc_roc': np.float32(1.0) } }, { 'testcase_name': 'roc_perfect_vocab', 'metric_fn_factory': metric_fns.make_auc_roc_metric_fn, 'label_vocabulary': ['ZERO', 'ONE'], 'labels_fn': lambda: tf.constant(['ONE', 'ZERO'], dtype=tf.string), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), }, 'expected_metric_dict': { 'auc_roc': np.float32(1.0) } }, { 'testcase_name': 'roc_random', 'metric_fn_factory': metric_fns.make_auc_roc_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.5, 0.5], [0.5, 0.5]], dtype=tf.float32), }, 'expected_metric_dict': { 'auc_roc': np.float32(0.5) } }, { 'testcase_name': 'pr_perfect', 'metric_fn_factory': metric_fns.make_auc_pr_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), }, 'expected_metric_dict': { 'auc_pr': np.float32(1.0) } }, { 'testcase_name': 'pr_perfect_vocab', 'metric_fn_factory': metric_fns.make_auc_pr_metric_fn, 'label_vocabulary': ['ZERO', 'ONE'], 'labels_fn': lambda: tf.constant(['ONE', 'ZERO'], dtype=tf.string), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), }, 'expected_metric_dict': { 'auc_pr': np.float32(1.0) } }, { 'testcase_name': 'pr_random', 'metric_fn_factory': metric_fns.make_auc_pr_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.5, 0.5], [0.5, 0.5]], dtype=tf.float32), }, 'expected_metric_dict': { 'auc_pr': np.float32(0.5) } }) # pylint: enable=g-long-lambda def test_auc_metric_fn(self, metric_fn_factory, label_vocabulary, labels_fn, predictions_fn, expected_metric_dict): # Force graph mode with tf.compat.v1.Graph().as_default(): metric_fn = metric_fn_factory(label_vocabulary) actual_metric_dict = metric_fn(labels_fn(), predictions_fn()) with self.test_session() as sess: sess.run(tf.compat.v1.initializers.local_variables()) sess.run(tf.compat.v1.initializers.tables_initializer()) actual_metric_dict_val = sess.run(actual_metric_dict) actual_metric_dict_val_clean = { metric_key: metric_val[1] for metric_key, metric_val in actual_metric_dict_val.items() } self.assertAllClose(expected_metric_dict, actual_metric_dict_val_clean) # pylint: disable=g-long-lambda @parameterized.named_parameters( { 'testcase_name': 'roc_multi_task', 'metric_fn_factory': metric_fns.make_auc_roc_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: { 'task_a': tf.constant([1, 0], dtype=tf.int64), 'task_b': tf.constant([1, 0], dtype=tf.int64), }, 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), 'probabilities/task_a': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), 'probabilities/task_b': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), }, 'exception_class': NotImplementedError, }, { 'testcase_name': 'roc_rank3_prob_tensor', 'metric_fn_factory': metric_fns.make_auc_roc_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[[0.5, 0.5], [0.5, 0.5]], [[0.5, 0.5], [0.5, 0.5]]], dtype=tf.float32), }, 'exception_class': ValueError, }, { 'testcase_name': 'roc_prob_tensor_3_classes', 'metric_fn_factory': metric_fns.make_auc_roc_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([2, 1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0, 0.0], [1.0, 0.0, 0.0]], dtype=tf.float32), }, 'exception_class': ValueError, }, { 'testcase_name': 'pr_multi_task', 'metric_fn_factory': metric_fns.make_auc_pr_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: { 'task_a': tf.constant([1, 0], dtype=tf.int64), 'task_b': tf.constant([1, 0], dtype=tf.int64), }, 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), 'probabilities/task_a': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), 'probabilities/task_b': tf.constant([[0.0, 1.0], [1.0, 0.0]], dtype=tf.float32), }, 'exception_class': NotImplementedError, }, { 'testcase_name': 'pr_rank3_prob_tensor', 'metric_fn_factory': metric_fns.make_auc_pr_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[[0.5, 0.5], [0.5, 0.5]], [[0.5, 0.5], [0.5, 0.5]]], dtype=tf.float32), }, 'exception_class': ValueError, }, { 'testcase_name': 'pr_prob_tensor_3_classes', 'metric_fn_factory': metric_fns.make_auc_pr_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant([2, 1, 0], dtype=tf.int64), 'predictions_fn': lambda: { 'probabilities': tf.constant([[0.0, 1.0, 0.0], [1.0, 0.0, 0.0]], dtype=tf.float32), }, 'exception_class': ValueError, }, { 'testcase_name': 'roc_string_label_no_vocab', 'metric_fn_factory': metric_fns.make_auc_roc_metric_fn, 'label_vocabulary': None, 'labels_fn': lambda: tf.constant(['ONE', 'ZERO'], dtype=tf.string), 'predictions_fn': lambda: { 'probabilities': tf.constant([[1.0, 0.0], [0.0, 1.0]], dtype=tf.float32), }, 'exception_class': ValueError, }) # pylint: enable=g-long-lambda def test_auc_metric_fn_error(self, metric_fn_factory, label_vocabulary, labels_fn, predictions_fn, exception_class): with self.assertRaises(exception_class): metric_fn = metric_fn_factory(label_vocabulary) metric_fn(labels_fn(), predictions_fn()) def test_create_num_parameters_metric_fn_no_tower(self): # Force graph mode with tf.compat.v1.Graph().as_default(): _ = tf.compat.v1.get_variable( name='w', shape=[10, 2], dtype=tf.float32, trainable=True) _ = tf.compat.v1.get_variable( name='b', shape=[2], dtype=tf.float32, trainable=True) metric_fn = metric_fns.create_num_parameters_metric_fn(None) metrics_dict = metric_fn(None, None) with self.test_session() as sess: self.assertEqual(22, sess.run(metrics_dict['num_parameters'][1])) def test_create_num_parameters_metric_fn_with_tower(self): # Force graph mode with tf.compat.v1.Graph().as_default(): _ = tf.compat.v1.get_variable( name='Phoenix/name', shape=[10, 2], dtype=tf.float32, trainable=True) _ = tf.compat.v1.get_variable( name='b', shape=[2], dtype=tf.float32, trainable=True) metric_fn = metric_fns.create_num_parameters_metric_fn('name') metrics_dict = metric_fn(None, None) with self.test_session() as sess: self.assertEqual(20, sess.run(metrics_dict['num_parameters'][1])) def test_combine_metric_fns(self): # Force graph mode with tf.compat.v1.Graph().as_default(): def metric_fn_1(labels, predictions, weights=None): del labels del predictions del weights one = tf.constant(1, dtype=tf.int32) return {'foo1': (one, one)} def metric_fn_2(labels, predictions, weights=None): del labels del predictions del weights two = tf.constant(2, dtype=tf.int32) return {'foo2': (two, two)} metric_fn_combined = metric_fns.combine_metric_fns( [metric_fn_1, metric_fn_2]) metrics_dict = metric_fn_combined(None, None) with self.test_session() as sess: self.assertEqual(1, sess.run(metrics_dict['foo1'][1])) self.assertEqual(2, sess.run(metrics_dict['foo2'][1])) if __name__ == '__main__': tf.enable_v2_behavior() tf.test.main()

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Python

benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_ml/backup_results_unknownr/cmp_gromacs/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_ml/backup_results_unknownr/cmp_gromacs/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_ml/backup_results_unknownr/cmp_gromacs/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': 0.306958, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.443787, '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': 1.76799, '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': 0.744131, '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': 1.28857, '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': 0.739029, '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': 2.77173, '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': 0.464485, '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': 8.91233, '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': 0.334012, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0269753, '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': 0.3055, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.199499, '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': 0.639512, 'Execution Unit/Register Files/Runtime Dynamic': 0.226475, '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': 0.822308, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 1.84225, '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': 5.68962, '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': 0.00124349, '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': 0.00124349, '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': 0.0010876, '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': 0.000423501, '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': 0.00286582, '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': 0.00644039, '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': 0.0117608, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 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'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': 0.000505076, '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': 0.000197493, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with 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'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00539152, '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': 0.0953318, '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': 6.06392, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 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'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': 3.95497, 'Load Store Unit/Data Cache/Runtime Dynamic': 1.30647, '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': 0.0879289, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.0879288, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 4.37019, 'Load Store Unit/Runtime Dynamic': 1.82803, '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': 0.155088, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.324501, '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': 0.89669, '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/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 6.04136, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.193978, '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': 0.322585, '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': 8.55307, 'Instruction Fetch Unit/Runtime Dynamic': 0.619415, 'Instruction Fetch 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'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': 0.274346, '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': 0.44251, 'Execution 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Unit/FP Front End RAT/Gate Leakage': 0.00351123, 'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468, 'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.346596, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885, 'Renaming Unit/Free List/Area': 0.0340654, 'Renaming Unit/Free List/Gate Leakage': 2.5481e-05, 'Renaming Unit/Free List/Peak Dynamic': 0.0306032, 'Renaming Unit/Free List/Runtime Dynamic': 0.0165957, 'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144, 'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064, 'Renaming Unit/Gate Leakage': 0.00708398, 'Renaming Unit/Int Front End RAT/Area': 0.0941223, 'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242, 'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965, 'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.133413, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228, 'Renaming Unit/Peak Dynamic': 3.58947, 'Renaming Unit/Runtime Dynamic': 0.496604, 'Renaming Unit/Subthreshold Leakage': 0.0552466, 'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461, 'Runtime Dynamic': 4.99551, 'Subthreshold Leakage': 6.16288, 'Subthreshold Leakage with power gating': 2.55328}], 'DRAM': {'Area': 0, 'Gate Leakage': 0, 'Peak Dynamic': 0.4907122877281571, 'Runtime Dynamic': 0.4907122877281571, 'Subthreshold Leakage': 4.252, 'Subthreshold Leakage with power gating': 4.252}, 'L3': [{'Area': 61.9075, 'Gate Leakage': 0.0484137, 'Peak Dynamic': 0.0912997, 'Runtime Dynamic': 0.0508145, 'Subthreshold Leakage': 6.80085, 'Subthreshold Leakage with power gating': 3.32364}], 'Processor': {'Area': 191.908, 'Gate Leakage': 1.53485, 'Peak Dynamic': 97.9256, 'Peak Power': 131.038, 'Runtime Dynamic': 29.2733, 'Subthreshold Leakage': 31.5774, 'Subthreshold Leakage with power gating': 13.9484, 'Total Cores/Area': 128.669, 'Total Cores/Gate Leakage': 1.4798, 'Total Cores/Peak Dynamic': 97.8343, 'Total Cores/Runtime Dynamic': 29.2225, 'Total Cores/Subthreshold Leakage': 24.7074, 'Total Cores/Subthreshold Leakage with power gating': 10.2429, 'Total L3s/Area': 61.9075, 'Total L3s/Gate Leakage': 0.0484137, 'Total L3s/Peak Dynamic': 0.0912997, 'Total L3s/Runtime Dynamic': 0.0508145, 'Total L3s/Subthreshold Leakage': 6.80085, 'Total L3s/Subthreshold Leakage with power gating': 3.32364, 'Total Leakage': 33.1122, 'Total NoCs/Area': 1.33155, 'Total NoCs/Gate Leakage': 0.00662954, 'Total NoCs/Peak Dynamic': 0.0, 'Total NoCs/Runtime Dynamic': 0.0, 'Total NoCs/Subthreshold Leakage': 0.0691322, 'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}

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1

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null

0

7

00f130bf5707d83239c652881424a9cfa340abcd

8,855

py

Python

parser/team24/classesQuerys.py

Mruiz-99/tytus

74a17fcbbe80c89eadf9111c5ecc04d82959c85b

[ "MIT" ]

null

parser/team24/classesQuerys.py

Mruiz-99/tytus

74a17fcbbe80c89eadf9111c5ecc04d82959c85b

[ "MIT" ]

null

parser/team24/classesQuerys.py

Mruiz-99/tytus

74a17fcbbe80c89eadf9111c5ecc04d82959c85b

[ "MIT" ]

null

# from mathtrig import * # class query(): ' Clase abstracta query' class select(query): def __init__(self, distinct=False, select_list=[], table_expression=[], condition=[], group=False, having=[], orderby=[], orderAscDesc='F', limit=0, offset=0): self.distinct = distinct self.select_list = select_list self.table_expression = table_expression self.condition = condition self.group = group self.having = having self.orderby = orderby self.orderascdesc = orderAscDesc self.limit = limit self.offset = offset class exp_query(): 'Abstract Class' class exp_id(exp_query): 'Esta expresion devuelve' 'el arreglo de la base de datos' def __init__(self, val, table): self.val = val self.table = table class exp_bool(exp_query): 'Esta expresion devuelve un' 'boolean' def __init__(self, val): self.val = val class exp_text(exp_query): 'Devuelve el texto' def __init__(self, val): self.val = val class exp_int(exp_query): 'Devuelve un entero' def __init__(self, val): self.val = val class exp_dec(exp_query): 'Devuelve un flotante' def __init__(self, val): self.val = val class exp_suma(exp_query): 'Suma las dos expresiones' def __init__(self, exp1, exp2): self.exp1 = exp1 self.exp2 = exp2 class exp_resta(exp_query): 'Suma las dos expresiones' def __init__(self, exp1, exp2): self.exp1 = exp1 self.exp2 = exp2 class exp_multiplicacion(exp_query): 'Suma las dos expresiones' def __init__(self, exp1, exp2): self.exp1 = exp1 self.exp2 = exp2 class exp_division(exp_query): 'Suma las dos expresiones' def __init__(self, exp1, exp2): self.exp1 = exp1 self.exp2 = exp2 class select_column(): 'Abstract Class' class column_id(select_column): def __init__(self, id, table, alias): self.id = id self. table = table self.alias = alias class column_mathtrig(select_column): 'Abstract Class' class math_abs(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_cbrt(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_ceil(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_degrees(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_div(column_mathtrig): def __init__(self, exp1, exp2, alias): self.exp1 = exp1 self.exp2 = exp2 self.alias = alias class math_factorial(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_floor(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_gcd(column_mathtrig): def __init__(self, exp1, exp2, alias): self.exp1 = exp1 self.exp2 = exp2 self.alias = alias class math_ln(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_log(column_mathtrig): def __init__(self, exp1, exp2, alias): self.exp1 = exp1 self.exp2 = exp2 self.alias = alias class math_log10(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_mod(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_pi(column_mathtrig): def __init__(self, alias): self.val = pi() self.alias = alias class math_power(column_mathtrig): def __init__(self, exp1, exp2, alias): self.exp1 = exp1 self.exp2 = exp2 self.alias = alias class math_radians(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_round(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_sign(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_sqrt(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_widthBucket(column_mathtrig): def __init__(self, exp1, exp2, exp3, exp4, alias): self.exp1 = exp1 self.exp2 = exp2 self.exp3 = exp3 self.exp4 = exp4 self.alias = alias class math_trunc(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class math_random(column_mathtrig): def __init__(self, alias): self.alias = alias class trig_acos(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_acosd(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_asin(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_asind(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_atan(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_atand(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_atan2(column_mathtrig): def __init__(self, exp1, exp2, alias): self.exp1 = exp1 self.exp2 = exp2 self.alias = alias class trig_atan2d(column_mathtrig): def __init__(self, exp1, exp2, alias): self.exp = exp1 self.exp2 = exp2 self.alias = alias class trig_cos(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_cosd(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_cot(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_cotd(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_sin(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_sind(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_tan(column_mathtrig): def __init__(self, exp, alias): self.exp = exp self.alias = alias class trig_tand(column_mathtrig): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class trig_sinh(column_mathtrig): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class trig_cosh(column_mathtrig): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class trig_tanh(column_mathtrig): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class trig_asinh(column_mathtrig): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class trig_acosh(column_mathtrig): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class trig_atanh(column_mathtrig): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class column_function(select_column): 'clase Abstracta' class fun_length(column_function): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class fun_substring(column_function): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class fun_trim(column_function): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class fun_md5(column_function): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class fun_sha256(column_function): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class fun_substr(column_function): def __init__ (self,exp,alias): self.exp = exp self.alias = alias class fun_convert(column_function): def __init__ (self,exp,type,alias): self.exp = exp self.type = type self.alias = alias class fun_greatest(column_function): def __init__ (self,lexps,alias): self.lexps = lexps self.alias = alias class fun_least(column_function): def __init__ (self,lexps,alias): self.lexps = lexps self.alias = alias

21.083333

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1,144

8,855

4.51049

0.103147

0.112597

0.134302

0.191473

0.800775

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0.74438

0.724806

0.718411

0.677132

0

0.012619

0.275099

8,855

420

164

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0.65625

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false

0

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0.458333

0

null

0

1

0

null

0

1

0

8

dae571122250d18334e8836a87dfc233490a38b1

47

py

Python

katas/kyu_6/what_is_the_point.py

the-zebulan/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

40

2016-03-09T12:26:20.000Z

2022-03-23T08:44:51.000Z

katas/kyu_6/what_is_the_point.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

null

katas/kyu_6/what_is_the_point.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

36

2016-11-07T19:59:58.000Z

2022-03-31T11:18:27.000Z

def pointless(*args): return "Rick Astley"

15.666667

24

0.680851

6

47

5.333333

1

0

0.191489

47

2

25

23.5

0.842105

0

0.234043

0

1

0.5

true

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

7

975ac5854c72dd714664faf801b386d64a60ea45

35,292

py

Python

feersum_nlu/api/dashboard_api.py

praekelt/feersum-nlu-api-wrappers

6580e2bab2c8a764fe868a505330b3fee6029074

[ "BSD-3-Clause" ]

9

2017-10-10T12:24:23.000Z

2021-08-18T14:07:51.000Z

feersum_nlu/api/dashboard_api.py

praekelt/feersum-nlu-api-wrappers

6580e2bab2c8a764fe868a505330b3fee6029074

[ "BSD-3-Clause" ]

1

2020-12-06T11:03:25.000Z

2021-04-14T05:21:23.000Z

feersum_nlu/api/dashboard_api.py

praekelt/feersum-nlu-api-wrappers

6580e2bab2c8a764fe868a505330b3fee6029074

[ "BSD-3-Clause" ]

2

2019-02-12T08:26:06.000Z

2022-02-01T09:39:47.000Z

# coding: utf-8 """ FeersumNLU API This is the HTTP API for Feersum NLU. See https://github.com/praekelt/feersum-nlu-api-wrappers for examples of how to use the API. # noqa: E501 OpenAPI spec version: 2.0.54.dev2 Contact: nlu@feersum.io 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 feersum_nlu.api_client import ApiClient class DashboardApi(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 dashboard_audio_get_details(self, **kwargs): # noqa: E501 """Your audio service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_audio_get_details(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_audio_get_details_with_http_info(**kwargs) # noqa: E501 else: (data) = self.dashboard_audio_get_details_with_http_info(**kwargs) # noqa: E501 return data def dashboard_audio_get_details_with_http_info(self, **kwargs): # noqa: E501 """Your audio service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_audio_get_details_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_audio_get_details" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/audio/v2/dashboard', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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 dashboard_audio_get_details_with_params(self, params, **kwargs): # noqa: E501 """Your audio service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_audio_get_details_with_params(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_audio_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 else: (data) = self.dashboard_audio_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 return data def dashboard_audio_get_details_with_params_with_http_info(self, params, **kwargs): # noqa: E501 """Your audio service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_audio_get_details_with_params_with_http_info(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['params', 'x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_audio_get_details_with_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'params' is set if ('params' not in params or params['params'] is None): raise ValueError("Missing the required parameter `params` when calling `dashboard_audio_get_details_with_params`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'params' in params: body_params = params['params'] # 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/audio/v2/dashboard', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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 dashboard_get_details(self, **kwargs): # noqa: E501 """Your root service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_get_details(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_get_details_with_http_info(**kwargs) # noqa: E501 else: (data) = self.dashboard_get_details_with_http_info(**kwargs) # noqa: E501 return data def dashboard_get_details_with_http_info(self, **kwargs): # noqa: E501 """Your root service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_get_details_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_get_details" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/dashboard/v2/dashboard', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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 dashboard_get_details_with_params(self, params, **kwargs): # noqa: E501 """Your root service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_get_details_with_params(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 else: (data) = self.dashboard_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 return data def dashboard_get_details_with_params_with_http_info(self, params, **kwargs): # noqa: E501 """Your root service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_get_details_with_params_with_http_info(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['params', 'x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_get_details_with_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'params' is set if ('params' not in params or params['params'] is None): raise ValueError("Missing the required parameter `params` when calling `dashboard_get_details_with_params`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'params' in params: body_params = params['params'] # 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/dashboard/v2/dashboard', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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 dashboard_nlu_get_details(self, **kwargs): # noqa: E501 """Your nlu service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_nlu_get_details(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_nlu_get_details_with_http_info(**kwargs) # noqa: E501 else: (data) = self.dashboard_nlu_get_details_with_http_info(**kwargs) # noqa: E501 return data def dashboard_nlu_get_details_with_http_info(self, **kwargs): # noqa: E501 """Your nlu service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_nlu_get_details_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_nlu_get_details" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/dashboard', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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 dashboard_nlu_get_details_with_params(self, params, **kwargs): # noqa: E501 """Your nlu service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_nlu_get_details_with_params(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_nlu_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 else: (data) = self.dashboard_nlu_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 return data def dashboard_nlu_get_details_with_params_with_http_info(self, params, **kwargs): # noqa: E501 """Your nlu service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_nlu_get_details_with_params_with_http_info(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['params', 'x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_nlu_get_details_with_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'params' is set if ('params' not in params or params['params'] is None): raise ValueError("Missing the required parameter `params` when calling `dashboard_nlu_get_details_with_params`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'params' in params: body_params = params['params'] # 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/dashboard', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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 dashboard_vision_get_details(self, **kwargs): # noqa: E501 """Your vision service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_vision_get_details(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_vision_get_details_with_http_info(**kwargs) # noqa: E501 else: (data) = self.dashboard_vision_get_details_with_http_info(**kwargs) # noqa: E501 return data def dashboard_vision_get_details_with_http_info(self, **kwargs): # noqa: E501 """Your vision service dashboard. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as POST endpoint, but doesn't allow params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_vision_get_details_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_vision_get_details" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/vision/v2/dashboard', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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 dashboard_vision_get_details_with_params(self, params, **kwargs): # noqa: E501 """Your vision service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_vision_get_details_with_params(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.dashboard_vision_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 else: (data) = self.dashboard_vision_get_details_with_params_with_http_info(params, **kwargs) # noqa: E501 return data def dashboard_vision_get_details_with_params_with_http_info(self, params, **kwargs): # noqa: E501 """Your vision service dashboard. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 Get your list of model instances, the API version, etc. Same as GET endpoint, but allows params to be supplied to the operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.dashboard_vision_get_details_with_params_with_http_info(params, async_req=True) >>> result = thread.get() :param async_req bool :param DashboardParams params: Params like 'show_data_objects' that influence the dashboard's response. (required) :param str x_caller: :return: DashboardDetail If the method is called asynchronously, returns the request thread. """ all_params = ['params', 'x_caller'] # noqa: E501 all_params.append('async_req') 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 dashboard_vision_get_details_with_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'params' is set if ('params' not in params or params['params'] is None): raise ValueError("Missing the required parameter `params` when calling `dashboard_vision_get_details_with_params`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'params' in params: body_params = params['params'] # 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 = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/vision/v2/dashboard', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DashboardDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _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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0.043766

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0.031635

0.027116

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0.974343

0.970059

0

0.015594

0.284087

35,292

826

159

42.726392

0.825141

0.384478

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0.842105

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97c1eddc0bff53038d000d479886ce72498671cc

6,699

py

Python

deep-rl/lib/python2.7/site-packages/OpenGL/raw/GL/SUN/vertex.py

ShujaKhalid/deep-rl

99c6ba6c3095d1bfdab81bd01395ced96bddd611

[ "MIT" ]

210

2016-04-09T14:26:00.000Z

2022-03-25T18:36:19.000Z

deep-rl/lib/python2.7/site-packages/OpenGL/raw/GL/SUN/vertex.py

ShujaKhalid/deep-rl

99c6ba6c3095d1bfdab81bd01395ced96bddd611

[ "MIT" ]

72

2016-09-04T09:30:19.000Z

2022-03-27T17:06:53.000Z

deep-rl/lib/python2.7/site-packages/OpenGL/raw/GL/SUN/vertex.py

ShujaKhalid/deep-rl

99c6ba6c3095d1bfdab81bd01395ced96bddd611

[ "MIT" ]

64

2016-04-09T14:26:49.000Z

2022-03-21T11:19:47.000Z

'''Autogenerated by xml_generate script, do not edit!''' from OpenGL import platform as _p, arrays # Code generation uses this from OpenGL.raw.GL import _types as _cs # End users want this... from OpenGL.raw.GL._types import * from OpenGL.raw.GL import _errors from OpenGL.constant import Constant as _C import ctypes _EXTENSION_NAME = 'GL_SUN_vertex' def _f( function ): return _p.createFunction( function,_p.PLATFORM.GL,'GL_SUN_vertex',error_checker=_errors._error_checker) @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glColor3fVertex3fSUN(r,g,b,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray) def glColor3fVertex3fvSUN(c,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glColor4fNormal3fVertex3fSUN(r,g,b,a,nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glColor4fNormal3fVertex3fvSUN(c,n,v):pass @_f @_p.types(None,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLfloat,_cs.GLfloat) def glColor4ubVertex2fSUN(r,g,b,a,x,y):pass @_f @_p.types(None,arrays.GLubyteArray,arrays.GLfloatArray) def glColor4ubVertex2fvSUN(c,v):pass @_f @_p.types(None,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glColor4ubVertex3fSUN(r,g,b,a,x,y,z):pass @_f @_p.types(None,arrays.GLubyteArray,arrays.GLfloatArray) def glColor4ubVertex3fvSUN(c,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glNormal3fVertex3fSUN(nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray) def glNormal3fVertex3fvSUN(n,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiColor3fVertex3fSUN(rc,r,g,b,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLfloatArray,arrays.GLfloatArray) def glReplacementCodeuiColor3fVertex3fvSUN(rc,c,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiColor4fNormal3fVertex3fSUN(rc,r,g,b,a,nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glReplacementCodeuiColor4fNormal3fVertex3fvSUN(rc,c,n,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiColor4ubVertex3fSUN(rc,r,g,b,a,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLubyteArray,arrays.GLfloatArray) def glReplacementCodeuiColor4ubVertex3fvSUN(rc,c,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiNormal3fVertex3fSUN(rc,nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLfloatArray,arrays.GLfloatArray) def glReplacementCodeuiNormal3fVertex3fvSUN(rc,n,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiTexCoord2fColor4fNormal3fVertex3fSUN(rc,s,t,r,g,b,a,nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glReplacementCodeuiTexCoord2fColor4fNormal3fVertex3fvSUN(rc,tc,c,n,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiTexCoord2fNormal3fVertex3fSUN(rc,s,t,nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glReplacementCodeuiTexCoord2fNormal3fVertex3fvSUN(rc,tc,n,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiTexCoord2fVertex3fSUN(rc,s,t,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLfloatArray,arrays.GLfloatArray) def glReplacementCodeuiTexCoord2fVertex3fvSUN(rc,tc,v):pass @_f @_p.types(None,_cs.GLuint,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glReplacementCodeuiVertex3fSUN(rc,x,y,z):pass @_f @_p.types(None,arrays.GLuintArray,arrays.GLfloatArray) def glReplacementCodeuiVertex3fvSUN(rc,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glTexCoord2fColor3fVertex3fSUN(s,t,r,g,b,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glTexCoord2fColor3fVertex3fvSUN(tc,c,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glTexCoord2fColor4fNormal3fVertex3fSUN(s,t,r,g,b,a,nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glTexCoord2fColor4fNormal3fVertex3fvSUN(tc,c,n,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLubyte,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glTexCoord2fColor4ubVertex3fSUN(s,t,r,g,b,a,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLubyteArray,arrays.GLfloatArray) def glTexCoord2fColor4ubVertex3fvSUN(tc,c,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glTexCoord2fNormal3fVertex3fSUN(s,t,nx,ny,nz,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glTexCoord2fNormal3fVertex3fvSUN(tc,n,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glTexCoord2fVertex3fSUN(s,t,x,y,z):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray) def glTexCoord2fVertex3fvSUN(tc,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glTexCoord4fColor4fNormal3fVertex4fSUN(s,t,p,q,r,g,b,a,nx,ny,nz,x,y,z,w):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray,arrays.GLfloatArray) def glTexCoord4fColor4fNormal3fVertex4fvSUN(tc,c,n,v):pass @_f @_p.types(None,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat,_cs.GLfloat) def glTexCoord4fVertex4fSUN(s,t,p,q,x,y,z,w):pass @_f @_p.types(None,arrays.GLfloatArray,arrays.GLfloatArray) def glTexCoord4fVertex4fvSUN(tc,v):pass

49.622222

195

0.81863

1,027

6,699

5.081792

0.104187

0.24315

0.25503

0.413872

0.680399

0.653573

0.652041

0.651466

0.650508

0.645334

0

0.015748

0.033139

6,699

134

196

49.992537

0.790026

0.014928

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1

0

0.003944

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1

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false

0.310078

0.046512

0.007752

0.372093

0

null

1

0

1

0

1

0

null

0

1

0

1

0

7

c13b593f88afef5498ea1e3579641b62dd58956f

108

py

Python

cvxgraphalgs/generators/__init__.py

hermish/cvx-graph-algorithms

733e137a906bd6c2965d5853d2798a8a01db945c

[ "MIT" ]

7

2020-05-11T10:01:31.000Z

2021-11-16T16:08:29.000Z

cvxgraphalgs/generators/__init__.py

hermish/graph-algorithms

733e137a906bd6c2965d5853d2798a8a01db945c

[ "MIT" ]

1

2020-05-12T16:15:33.000Z

2020-06-05T16:40:57.000Z

cvxgraphalgs/generators/__init__.py

hermish/cvx-graph-algorithms

733e137a906bd6c2965d5853d2798a8a01db945c

[ "MIT" ]

null

from cvxgraphalgs.generators.stochastic_block import * from cvxgraphalgs.generators.planted_models import *

36

54

0.87037

12

108

7.666667

0.666667

0.347826

0.565217

0

0.074074

108

2

55

54

0.92

0

1

0

true

0

1

0

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null

1

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1

0

null

0

1

0

1

0

1

0

7

c187ba31db1824816212ac1d876aca3e77248c46

77,338

py

Python

infoblox_netmri/api/broker/v3_6_0/device_support_bundle_broker.py

IngmarVG-IB/infoblox-netmri

b0c725fd64aee1890d83917d911b89236207e564

[ "Apache-2.0" ]

null

infoblox_netmri/api/broker/v3_6_0/device_support_bundle_broker.py

IngmarVG-IB/infoblox-netmri

b0c725fd64aee1890d83917d911b89236207e564

[ "Apache-2.0" ]

null

infoblox_netmri/api/broker/v3_6_0/device_support_bundle_broker.py

IngmarVG-IB/infoblox-netmri

b0c725fd64aee1890d83917d911b89236207e564

[ "Apache-2.0" ]

null

from ..broker import Broker class DeviceSupportBundleBroker(Broker): controller = "device_support_bundles" def index(self, **kwargs): """Lists the available device support bundles. Any of the inputs listed may be be used to narrow the list; other inputs will be ignored. Of the various ways to query lists, using this method is most efficient. **Inputs** | ``api version min:`` 2 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param id: The internal NetMRI identifier of the Device Support Bundle. :type id: Integer | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The internal NetMRI identifier of the Device Support Bundle. :type id: Array of Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 0 :param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information. :type start: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 1000 :param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000. :type limit: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` id :param sort: The data field(s) to use for sorting the output. Default is id. Valid values are id, name, version, author, enabled_ind, system_ind, neighbor_ind, inventory_ind, environmental_ind, cpu_ind, memory_ind, vlan_ind, forwarding_ind, port_ind, config_ind, created_by, updated_by, created_at, updated_at, valid_ind, unit_tests, status, integrated_ind. :type sort: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` asc :param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'. :type dir: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param select: The list of attributes to return for each DeviceSupportBundle. Valid values are id, name, version, author, enabled_ind, system_ind, neighbor_ind, inventory_ind, environmental_ind, cpu_ind, memory_ind, vlan_ind, forwarding_ind, port_ind, config_ind, created_by, updated_by, created_at, updated_at, valid_ind, unit_tests, status, integrated_ind. If empty or omitted, all attributes will be returned. :type select: Array | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_field: The field name for NIOS GOTO that is used for locating a row position of records. :type goto_field: String | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records. :type goto_value: String **Outputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :return device_support_bundles: An array of the DeviceSupportBundle objects that match the specified input criteria. :rtype device_support_bundles: Array of DeviceSupportBundle """ return self.api_list_request(self._get_method_fullname("index"), kwargs) def search(self, **kwargs): """Lists the available device support bundles matching the input criteria. This method provides a more flexible search interface than the index method, but searching using this method is more demanding on the system and will not perform to the same level as the index method. The input fields listed below will be used as in the index method, to filter the result, along with the optional query string and XML filter described below. **Inputs** | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param author: The author of the Device Support Bundle. :type author: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param author: The author of the Device Support Bundle. :type author: Array of String | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param config_ind: A flag indicating if configuration is shown in Device Viewer for devices. :type config_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param config_ind: A flag indicating if configuration is shown in Device Viewer for devices. :type config_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param cpu_ind: A flag indicating if CPU information is shown in Device Viewer for devices. :type cpu_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param cpu_ind: A flag indicating if CPU information is shown in Device Viewer for devices. :type cpu_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param created_at: The date and time the Device Support Bundle was created. :type created_at: DateTime | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param created_at: The date and time the Device Support Bundle was created. :type created_at: Array of DateTime | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param created_by: Indicates by whom Device Support Bundle was created. :type created_by: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param created_by: Indicates by whom Device Support Bundle was created. :type created_by: Array of String | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param enabled_ind: A flag indicating if the Device Support Bundle is enabled. :type enabled_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param enabled_ind: A flag indicating if the Device Support Bundle is enabled. :type enabled_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param environmental_ind: A flag indicating if environmental information is shown in Device Viewer for devices. :type environmental_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param environmental_ind: A flag indicating if environmental information is shown in Device Viewer for devices. :type environmental_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param forwarding_ind: A flag indicating if forwarding information is shown in Device Viewer for devices. :type forwarding_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param forwarding_ind: A flag indicating if forwarding information is shown in Device Viewer for devices. :type forwarding_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param id: The internal NetMRI identifier of the Device Support Bundle. :type id: Integer | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The internal NetMRI identifier of the Device Support Bundle. :type id: Array of Integer | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param integrated_ind: A flag indicating if the Device Support Bundle is integrated. :type integrated_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param integrated_ind: A flag indicating if the Device Support Bundle is integrated. :type integrated_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param inventory_ind: A flag indicating if inventory information is shown in Device Viewer for devices. :type inventory_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param inventory_ind: A flag indicating if inventory information is shown in Device Viewer for devices. :type inventory_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param memory_ind: A flag indicating if memory information is shown in Device Viewer for devices. :type memory_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param memory_ind: A flag indicating if memory information is shown in Device Viewer for devices. :type memory_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param name: The unique name of the Device Support Bundle. :type name: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param name: The unique name of the Device Support Bundle. :type name: Array of String | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param neighbor_ind: A flag indicating if neighbor information is shown in Device Viewer for devices. :type neighbor_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param neighbor_ind: A flag indicating if neighbor information is shown in Device Viewer for devices. :type neighbor_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param port_ind: A flag indicating if port config is shown in Device Viewer for devices. :type port_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param port_ind: A flag indicating if port config is shown in Device Viewer for devices. :type port_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param status: The current editing state of the Device Support Bundle. :type status: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param status: The current editing state of the Device Support Bundle. :type status: Array of String | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param system_ind: A flag indicating if system information is shown in Device Viewer for devices. :type system_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param system_ind: A flag indicating if system information is shown in Device Viewer for devices. :type system_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param unit_tests: The current state of unit testing for the Device Support Bundle. :type unit_tests: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param unit_tests: The current state of unit testing for the Device Support Bundle. :type unit_tests: Array of String | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param updated_at: The date and time the Device Support Bundle was updated. :type updated_at: DateTime | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param updated_at: The date and time the Device Support Bundle was updated. :type updated_at: Array of DateTime | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param updated_by: Indicates by whom the Device Support Bundle was updated. :type updated_by: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param updated_by: Indicates by whom the Device Support Bundle was updated. :type updated_by: Array of String | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param valid_ind: A flag indicating whether the Device Support Bundle is valid. :type valid_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param valid_ind: A flag indicating whether the Device Support Bundle is valid. :type valid_ind: Array of Boolean | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param version: The version of the Device Support Bundle. :type version: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param version: The version of the Device Support Bundle. :type version: Array of String | ``api version min:`` 2.3 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param vlan_ind: A flag indicating if VLAN information is shown in Device Viewer for devices. :type vlan_ind: Boolean | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param vlan_ind: A flag indicating if VLAN information is shown in Device Viewer for devices. :type vlan_ind: Array of Boolean | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 0 :param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information. :type start: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 1000 :param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000. :type limit: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` id :param sort: The data field(s) to use for sorting the output. Default is id. Valid values are id, name, version, author, enabled_ind, system_ind, neighbor_ind, inventory_ind, environmental_ind, cpu_ind, memory_ind, vlan_ind, forwarding_ind, port_ind, config_ind, created_by, updated_by, created_at, updated_at, valid_ind, unit_tests, status, integrated_ind. :type sort: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` asc :param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'. :type dir: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param select: The list of attributes to return for each DeviceSupportBundle. Valid values are id, name, version, author, enabled_ind, system_ind, neighbor_ind, inventory_ind, environmental_ind, cpu_ind, memory_ind, vlan_ind, forwarding_ind, port_ind, config_ind, created_by, updated_by, created_at, updated_at, valid_ind, unit_tests, status, integrated_ind. If empty or omitted, all attributes will be returned. :type select: Array | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_field: The field name for NIOS GOTO that is used for locating a row position of records. :type goto_field: String | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records. :type goto_value: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param query: This value will be matched against device support bundles, looking to see if one or more of the listed attributes contain the passed value. You may also surround the value with '/' and '/' to perform a regular expression search rather than a containment operation. Any record that matches will be returned. The attributes searched are: author, config_ind, cpu_ind, created_at, created_by, enabled_ind, environmental_ind, forwarding_ind, id, integrated_ind, inventory_ind, memory_ind, name, neighbor_ind, port_ind, status, system_ind, unit_tests, updated_at, updated_by, valid_ind, version, vlan_ind. :type query: String | ``api version min:`` 2.3 | ``api version max:`` None | ``required:`` False | ``default:`` None :param xml_filter: A SetFilter XML structure to further refine the search. The SetFilter will be applied AFTER any search query or field values, but before any limit options. The limit and pagination will be enforced after the filter. Remind that this kind of filter may be costly and inefficient if not associated with a database filtering. :type xml_filter: String **Outputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :return device_support_bundles: An array of the DeviceSupportBundle objects that match the specified input criteria. :rtype device_support_bundles: Array of DeviceSupportBundle """ return self.api_list_request(self._get_method_fullname("search"), kwargs) def find(self, **kwargs): """Lists the available device support bundles matching the input specification. This provides the most flexible search specification of all the query mechanisms, enabling searching using comparison operations other than equality. However, it is more complex to use and will not perform as efficiently as the index or search methods. In the input descriptions below, 'field names' refers to the following fields: author, config_ind, cpu_ind, created_at, created_by, enabled_ind, environmental_ind, forwarding_ind, id, integrated_ind, inventory_ind, memory_ind, name, neighbor_ind, port_ind, status, system_ind, unit_tests, updated_at, updated_by, valid_ind, version, vlan_ind. **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_author: The operator to apply to the field author. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. author: The author of the Device Support Bundle. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_author: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_author: If op_author is specified, the field named in this input will be compared to the value in author using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_author must be specified if op_author is specified. :type val_f_author: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_author: If op_author is specified, this value will be compared to the value in author using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_author must be specified if op_author is specified. :type val_c_author: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_config_ind: The operator to apply to the field config_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. config_ind: A flag indicating if configuration is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_config_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_config_ind: If op_config_ind is specified, the field named in this input will be compared to the value in config_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_config_ind must be specified if op_config_ind is specified. :type val_f_config_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_config_ind: If op_config_ind is specified, this value will be compared to the value in config_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_config_ind must be specified if op_config_ind is specified. :type val_c_config_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_cpu_ind: The operator to apply to the field cpu_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. cpu_ind: A flag indicating if CPU information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_cpu_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_cpu_ind: If op_cpu_ind is specified, the field named in this input will be compared to the value in cpu_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_cpu_ind must be specified if op_cpu_ind is specified. :type val_f_cpu_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_cpu_ind: If op_cpu_ind is specified, this value will be compared to the value in cpu_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_cpu_ind must be specified if op_cpu_ind is specified. :type val_c_cpu_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_created_at: The operator to apply to the field created_at. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. created_at: The date and time the Device Support Bundle was created. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_created_at: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_created_at: If op_created_at is specified, the field named in this input will be compared to the value in created_at using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_created_at must be specified if op_created_at is specified. :type val_f_created_at: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_created_at: If op_created_at is specified, this value will be compared to the value in created_at using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_created_at must be specified if op_created_at is specified. :type val_c_created_at: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_created_by: The operator to apply to the field created_by. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. created_by: Indicates by whom Device Support Bundle was created. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_created_by: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_created_by: If op_created_by is specified, the field named in this input will be compared to the value in created_by using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_created_by must be specified if op_created_by is specified. :type val_f_created_by: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_created_by: If op_created_by is specified, this value will be compared to the value in created_by using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_created_by must be specified if op_created_by is specified. :type val_c_created_by: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_enabled_ind: The operator to apply to the field enabled_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. enabled_ind: A flag indicating if the Device Support Bundle is enabled. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_enabled_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_enabled_ind: If op_enabled_ind is specified, the field named in this input will be compared to the value in enabled_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_enabled_ind must be specified if op_enabled_ind is specified. :type val_f_enabled_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_enabled_ind: If op_enabled_ind is specified, this value will be compared to the value in enabled_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_enabled_ind must be specified if op_enabled_ind is specified. :type val_c_enabled_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_environmental_ind: The operator to apply to the field environmental_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. environmental_ind: A flag indicating if environmental information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_environmental_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_environmental_ind: If op_environmental_ind is specified, the field named in this input will be compared to the value in environmental_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_environmental_ind must be specified if op_environmental_ind is specified. :type val_f_environmental_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_environmental_ind: If op_environmental_ind is specified, this value will be compared to the value in environmental_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_environmental_ind must be specified if op_environmental_ind is specified. :type val_c_environmental_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_forwarding_ind: The operator to apply to the field forwarding_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. forwarding_ind: A flag indicating if forwarding information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_forwarding_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_forwarding_ind: If op_forwarding_ind is specified, the field named in this input will be compared to the value in forwarding_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_forwarding_ind must be specified if op_forwarding_ind is specified. :type val_f_forwarding_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_forwarding_ind: If op_forwarding_ind is specified, this value will be compared to the value in forwarding_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_forwarding_ind must be specified if op_forwarding_ind is specified. :type val_c_forwarding_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_id: The operator to apply to the field id. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. id: The internal NetMRI identifier of the Device Support Bundle. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_id: If op_id is specified, the field named in this input will be compared to the value in id using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_id must be specified if op_id is specified. :type val_f_id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_id: If op_id is specified, this value will be compared to the value in id using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_id must be specified if op_id is specified. :type val_c_id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_integrated_ind: The operator to apply to the field integrated_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. integrated_ind: A flag indicating if the Device Support Bundle is integrated. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_integrated_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_integrated_ind: If op_integrated_ind is specified, the field named in this input will be compared to the value in integrated_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_integrated_ind must be specified if op_integrated_ind is specified. :type val_f_integrated_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_integrated_ind: If op_integrated_ind is specified, this value will be compared to the value in integrated_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_integrated_ind must be specified if op_integrated_ind is specified. :type val_c_integrated_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_inventory_ind: The operator to apply to the field inventory_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. inventory_ind: A flag indicating if inventory information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_inventory_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_inventory_ind: If op_inventory_ind is specified, the field named in this input will be compared to the value in inventory_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_inventory_ind must be specified if op_inventory_ind is specified. :type val_f_inventory_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_inventory_ind: If op_inventory_ind is specified, this value will be compared to the value in inventory_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_inventory_ind must be specified if op_inventory_ind is specified. :type val_c_inventory_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_memory_ind: The operator to apply to the field memory_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. memory_ind: A flag indicating if memory information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_memory_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_memory_ind: If op_memory_ind is specified, the field named in this input will be compared to the value in memory_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_memory_ind must be specified if op_memory_ind is specified. :type val_f_memory_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_memory_ind: If op_memory_ind is specified, this value will be compared to the value in memory_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_memory_ind must be specified if op_memory_ind is specified. :type val_c_memory_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_name: The operator to apply to the field name. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. name: The unique name of the Device Support Bundle. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_name: If op_name is specified, the field named in this input will be compared to the value in name using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_name must be specified if op_name is specified. :type val_f_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_name: If op_name is specified, this value will be compared to the value in name using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_name must be specified if op_name is specified. :type val_c_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_neighbor_ind: The operator to apply to the field neighbor_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. neighbor_ind: A flag indicating if neighbor information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_neighbor_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_neighbor_ind: If op_neighbor_ind is specified, the field named in this input will be compared to the value in neighbor_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_neighbor_ind must be specified if op_neighbor_ind is specified. :type val_f_neighbor_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_neighbor_ind: If op_neighbor_ind is specified, this value will be compared to the value in neighbor_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_neighbor_ind must be specified if op_neighbor_ind is specified. :type val_c_neighbor_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_port_ind: The operator to apply to the field port_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. port_ind: A flag indicating if port config is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_port_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_port_ind: If op_port_ind is specified, the field named in this input will be compared to the value in port_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_port_ind must be specified if op_port_ind is specified. :type val_f_port_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_port_ind: If op_port_ind is specified, this value will be compared to the value in port_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_port_ind must be specified if op_port_ind is specified. :type val_c_port_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_status: The operator to apply to the field status. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. status: The current editing state of the Device Support Bundle. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_status: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_status: If op_status is specified, the field named in this input will be compared to the value in status using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_status must be specified if op_status is specified. :type val_f_status: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_status: If op_status is specified, this value will be compared to the value in status using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_status must be specified if op_status is specified. :type val_c_status: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_system_ind: The operator to apply to the field system_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. system_ind: A flag indicating if system information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_system_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_system_ind: If op_system_ind is specified, the field named in this input will be compared to the value in system_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_system_ind must be specified if op_system_ind is specified. :type val_f_system_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_system_ind: If op_system_ind is specified, this value will be compared to the value in system_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_system_ind must be specified if op_system_ind is specified. :type val_c_system_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_unit_tests: The operator to apply to the field unit_tests. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. unit_tests: The current state of unit testing for the Device Support Bundle. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_unit_tests: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_unit_tests: If op_unit_tests is specified, the field named in this input will be compared to the value in unit_tests using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_unit_tests must be specified if op_unit_tests is specified. :type val_f_unit_tests: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_unit_tests: If op_unit_tests is specified, this value will be compared to the value in unit_tests using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_unit_tests must be specified if op_unit_tests is specified. :type val_c_unit_tests: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_updated_at: The operator to apply to the field updated_at. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. updated_at: The date and time the Device Support Bundle was updated. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_updated_at: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_updated_at: If op_updated_at is specified, the field named in this input will be compared to the value in updated_at using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_updated_at must be specified if op_updated_at is specified. :type val_f_updated_at: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_updated_at: If op_updated_at is specified, this value will be compared to the value in updated_at using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_updated_at must be specified if op_updated_at is specified. :type val_c_updated_at: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_updated_by: The operator to apply to the field updated_by. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. updated_by: Indicates by whom the Device Support Bundle was updated. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_updated_by: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_updated_by: If op_updated_by is specified, the field named in this input will be compared to the value in updated_by using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_updated_by must be specified if op_updated_by is specified. :type val_f_updated_by: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_updated_by: If op_updated_by is specified, this value will be compared to the value in updated_by using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_updated_by must be specified if op_updated_by is specified. :type val_c_updated_by: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_valid_ind: The operator to apply to the field valid_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. valid_ind: A flag indicating whether the Device Support Bundle is valid. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_valid_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_valid_ind: If op_valid_ind is specified, the field named in this input will be compared to the value in valid_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_valid_ind must be specified if op_valid_ind is specified. :type val_f_valid_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_valid_ind: If op_valid_ind is specified, this value will be compared to the value in valid_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_valid_ind must be specified if op_valid_ind is specified. :type val_c_valid_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_version: The operator to apply to the field version. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. version: The version of the Device Support Bundle. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_version: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_version: If op_version is specified, the field named in this input will be compared to the value in version using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_version must be specified if op_version is specified. :type val_f_version: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_version: If op_version is specified, this value will be compared to the value in version using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_version must be specified if op_version is specified. :type val_c_version: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_vlan_ind: The operator to apply to the field vlan_ind. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. vlan_ind: A flag indicating if VLAN information is shown in Device Viewer for devices. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_vlan_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_vlan_ind: If op_vlan_ind is specified, the field named in this input will be compared to the value in vlan_ind using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_vlan_ind must be specified if op_vlan_ind is specified. :type val_f_vlan_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_vlan_ind: If op_vlan_ind is specified, this value will be compared to the value in vlan_ind using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_vlan_ind must be specified if op_vlan_ind is specified. :type val_c_vlan_ind: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 0 :param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information. :type start: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 1000 :param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000. :type limit: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` id :param sort: The data field(s) to use for sorting the output. Default is id. Valid values are id, name, version, author, enabled_ind, system_ind, neighbor_ind, inventory_ind, environmental_ind, cpu_ind, memory_ind, vlan_ind, forwarding_ind, port_ind, config_ind, created_by, updated_by, created_at, updated_at, valid_ind, unit_tests, status, integrated_ind. :type sort: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` asc :param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'. :type dir: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param select: The list of attributes to return for each DeviceSupportBundle. Valid values are id, name, version, author, enabled_ind, system_ind, neighbor_ind, inventory_ind, environmental_ind, cpu_ind, memory_ind, vlan_ind, forwarding_ind, port_ind, config_ind, created_by, updated_by, created_at, updated_at, valid_ind, unit_tests, status, integrated_ind. If empty or omitted, all attributes will be returned. :type select: Array | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_field: The field name for NIOS GOTO that is used for locating a row position of records. :type goto_field: String | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records. :type goto_value: String | ``api version min:`` 2.3 | ``api version max:`` None | ``required:`` False | ``default:`` None :param xml_filter: A SetFilter XML structure to further refine the search. The SetFilter will be applied AFTER any search query or field values, but before any limit options. The limit and pagination will be enforced after the filter. Remind that this kind of filter may be costly and inefficient if not associated with a database filtering. :type xml_filter: String **Outputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :return device_support_bundles: An array of the DeviceSupportBundle objects that match the specified input criteria. :rtype device_support_bundles: Array of DeviceSupportBundle """ return self.api_list_request(self._get_method_fullname("find"), kwargs) def destroy(self, **kwargs): """Deletes the specified device support bundle from NetMRI. **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param id: The internal NetMRI identifier of the Device Support Bundle. :type id: Integer **Outputs** """ return self.api_request(self._get_method_fullname("destroy"), kwargs) def delete(self, **kwargs): """Delete a device support bundle specified by name **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param dsb_name: Unique device support bundle name :type dsb_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The id of the output file :type id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param read: The number of bytes to read from the delete output :type read: Integer **Outputs** """ return self.api_request(self._get_method_fullname("delete"), kwargs) def export(self, **kwargs): """Export specified device support bundle in tgz format. **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param dsb_name: Unique Device Support Bundle name indicating the bundle to export :type dsb_name: String **Outputs** """ return self.api_request(self._get_method_fullname("export"), kwargs) def import_data(self, **kwargs): """Import Device Support Bundles in bulk via a xml, tgz, tar, or zip file **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param file: Device Support Bundle file contents to be imported :type file: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The id of the output file :type id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param read: The number of bytes to read from the import output :type read: Integer **Outputs** """ return self.api_request(self._get_method_fullname("import"), kwargs) def discard(self, **kwargs): """Discard all changes to the modified Device Support Bundle **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param dsb_name: Name of the DSB for which changes should be discarded :type dsb_name: String **Outputs** """ return self.api_request(self._get_method_fullname("discard"), kwargs) def generate_templates(self, **kwargs): """Return DSB file templates **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param dsb_name: The unique name of the new DSB (it will be inserted into template files where necessary) :type dsb_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param type: The type of the DSB template :type type: String **Outputs** """ return self.api_request(self._get_method_fullname("generate_templates"), kwargs) def show(self, **kwargs): """Return all existing files for a DSB **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param dsb_name: DSB name :type dsb_name: String **Outputs** """ return self.api_request(self._get_method_fullname("show"), kwargs) def validate(self, **kwargs): """Validate DSB files **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param dsb_name: DSB name :type dsb_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param description: DSB config description content :type description: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param ccs_scripts: DSB Perl scripts content :type ccs_scripts: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param perl_scripts: DSB CCS scripts content :type perl_scripts: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The id of the output file :type id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param read: The number of bytes already read from the output :type read: Integer **Outputs** """ return self.api_request(self._get_method_fullname("validate"), kwargs) def save(self, **kwargs): """Save DSB scripts to working directory **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param dsb_name: DSB name :type dsb_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param description: DSB config description content :type description: String | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param ccs_scripts: DSB Perl scripts content :type ccs_scripts: String | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param perl_scripts: DSB CCS scripts content :type perl_scripts: String **Outputs** """ return self.api_request(self._get_method_fullname("save"), kwargs) def install(self, **kwargs): """Install a saved, validated DSB script **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param dsb_name: DSB name :type dsb_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The id of the output file :type id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param read: The number of bytes already read from the output :type read: Integer **Outputs** """ return self.api_request(self._get_method_fullname("install"), kwargs) def test_bundle(self, **kwargs): """Test DSB in real-time **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param dsb_name: Unique device support bundle name :type dsb_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param device_ip: Device IP to test the DSB against :type device_ip: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The id of the output file :type id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param read: The number of bytes already read from the test output :type read: Integer **Outputs** """ return self.api_request(self._get_method_fullname("test_bundle"), kwargs) def validate_bundle(self, **kwargs): """Validate DSB **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param dsb_name: Unique device support bundle name :type dsb_name: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param id: The id of the output file :type id: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param read: The number of bytes already read from the validation output :type read: Integer **Outputs** """ return self.api_request(self._get_method_fullname("validate_bundle"), kwargs)

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c1e4cfcc227dfa2ba6fc0733e8dea0f6d12e51df

87

py

Python

vttes/tests/common.py

forgedconcordance/vttestools

55f2b307010ec94e1fa0b5956cfac3381e28d732

[ "MIT" ]

null

vttes/tests/common.py

forgedconcordance/vttestools

55f2b307010ec94e1fa0b5956cfac3381e28d732

[ "MIT" ]

null

vttes/tests/common.py

forgedconcordance/vttestools

55f2b307010ec94e1fa0b5956cfac3381e28d732

[ "MIT" ]

null

import synapse.tests.utils as s_t_utils class VttTstBase(s_t_utils.SynTest): pass

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a9eb31d246ce6c1879597d9cf2a5e2ddb1e85af2

167

py

Python

pykeg/backend/__init__.py

theshiv303/kegbot-server

425b0f8779e0d97aa6ca032b29b2623d693f9fd4

[ "MIT" ]

75

2015-01-12T22:51:20.000Z

2022-02-23T02:09:50.000Z

pykeg/backend/__init__.py

theshiv303/kegbot-server

425b0f8779e0d97aa6ca032b29b2623d693f9fd4

[ "MIT" ]

83

2015-01-03T19:04:46.000Z

2021-07-11T19:06:39.000Z

pykeg/backend/__init__.py

theshiv303/kegbot-server

425b0f8779e0d97aa6ca032b29b2623d693f9fd4

[ "MIT" ]

66

2015-01-05T01:55:06.000Z

2021-11-27T17:07:24.000Z

from django.conf import settings from django.utils.module_loading import import_string def get_kegbot_backend(): return import_string(settings.KEGBOT_BACKEND)()

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e77fc5e64b6ddfdf69fd623c59ab8f10b29568f7

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py

Python

openshift/client/apis/project_openshift_io_v1_api.py

flaper87/openshift-restclient-python

13d5d86ca89035b9f596032e7a34f3cc33bf8f18

[ "Apache-2.0" ]

null

openshift/client/apis/project_openshift_io_v1_api.py

flaper87/openshift-restclient-python

13d5d86ca89035b9f596032e7a34f3cc33bf8f18

[ "Apache-2.0" ]

null

openshift/client/apis/project_openshift_io_v1_api.py

flaper87/openshift-restclient-python

13d5d86ca89035b9f596032e7a34f3cc33bf8f18

[ "Apache-2.0" ]

null

# coding: utf-8 """ OpenShift API (with Kubernetes) OpenShift provides builds, application lifecycle, image content management, and administrative policy on top of Kubernetes. The API allows consistent management of those objects. All API operations are authenticated via an Authorization bearer token that is provided for service accounts as a generated secret (in JWT form) or via the native OAuth endpoint located at /oauth/authorize. Core infrastructure components may use client certificates that require no authentication. All API operations return a 'resourceVersion' string that represents the version of the object in the underlying storage. The standard LIST operation performs a snapshot read of the underlying objects, returning a resourceVersion representing a consistent version of the listed objects. The WATCH operation allows all updates to a set of objects after the provided resourceVersion to be observed by a client. By listing and beginning a watch from the returned resourceVersion, clients may observe a consistent view of the state of one or more objects. Note that WATCH always returns the update after the provided resourceVersion. Watch may be extended a limited time in the past - using etcd 2 the watch window is 1000 events (which on a large cluster may only be a few tens of seconds) so clients must explicitly handle the \"watch to old error\" by re-listing. Objects are divided into two rough categories - those that have a lifecycle and must reflect the state of the cluster, and those that have no state. Objects with lifecycle typically have three main sections: * 'metadata' common to all objects * a 'spec' that represents the desired state * a 'status' that represents how much of the desired state is reflected on the cluster at the current time Objects that have no state have 'metadata' but may lack a 'spec' or 'status' section. Objects are divided into those that are namespace scoped (only exist inside of a namespace) and those that are cluster scoped (exist outside of a namespace). A namespace scoped resource will be deleted when the namespace is deleted and cannot be created if the namespace has not yet been created or is in the process of deletion. Cluster scoped resources are typically only accessible to admins - resources like nodes, persistent volumes, and cluster policy. All objects have a schema that is a combination of the 'kind' and 'apiVersion' fields. This schema is additive only for any given version - no backwards incompatible changes are allowed without incrementing the apiVersion. The server will return and accept a number of standard responses that share a common schema - for instance, the common error type is 'unversioned.Status' (described below) and will be returned on any error from the API server. The API is available in multiple serialization formats - the default is JSON (Accept: application/json and Content-Type: application/json) but clients may also use YAML (application/yaml) or the native Protobuf schema (application/vnd.kubernetes.protobuf). Note that the format of the WATCH API call is slightly different - for JSON it returns newline delimited objects while for Protobuf it returns length-delimited frames (4 bytes in network-order) that contain a 'versioned.Watch' Protobuf object. See the OpenShift documentation at https://docs.openshift.org for more information. OpenAPI spec version: v3.6.0-alpha.0 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 kubernetes.client.configuration import Configuration from ..api_client import ApiClient class ProjectOpenshiftIoV1Api(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 create_project_openshift_io_v1_project(self, body, **kwargs): """ create a 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_openshift_io_v1_project(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param V1Project body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.create_project_openshift_io_v1_project_with_http_info(body, **kwargs) else: (data) = self.create_project_openshift_io_v1_project_with_http_info(body, **kwargs) return data def create_project_openshift_io_v1_project_with_http_info(self, body, **kwargs): """ create a 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_openshift_io_v1_project_with_http_info(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param V1Project body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ all_params = ['body', 'pretty'] 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_openshift_io_v1_project" % 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 `create_project_openshift_io_v1_project`") collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projects'.replace('{format}', 'json') path_params = {} query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] 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', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['*/*']) # Authentication setting auth_settings = ['BearerToken'] 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='V1Project', 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_openshift_io_v1_project_request(self, body, **kwargs): """ create a ProjectRequest 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_openshift_io_v1_project_request(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param V1ProjectRequest body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1ProjectRequest If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.create_project_openshift_io_v1_project_request_with_http_info(body, **kwargs) else: (data) = self.create_project_openshift_io_v1_project_request_with_http_info(body, **kwargs) return data def create_project_openshift_io_v1_project_request_with_http_info(self, body, **kwargs): """ create a ProjectRequest 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_openshift_io_v1_project_request_with_http_info(body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param V1ProjectRequest body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1ProjectRequest If the method is called asynchronously, returns the request thread. """ all_params = ['body', 'pretty'] 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_openshift_io_v1_project_request" % 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 `create_project_openshift_io_v1_project_request`") collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projectrequests'.replace('{format}', 'json') path_params = {} query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] 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', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['*/*']) # Authentication setting auth_settings = ['BearerToken'] 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='V1ProjectRequest', 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_project_openshift_io_v1_project(self, name, **kwargs): """ delete a 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.delete_project_openshift_io_v1_project(name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param str pretty: If 'true', then the output is pretty printed. :return: UnversionedStatus If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.delete_project_openshift_io_v1_project_with_http_info(name, **kwargs) else: (data) = self.delete_project_openshift_io_v1_project_with_http_info(name, **kwargs) return data def delete_project_openshift_io_v1_project_with_http_info(self, name, **kwargs): """ delete a 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.delete_project_openshift_io_v1_project_with_http_info(name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param str pretty: If 'true', then the output is pretty printed. :return: UnversionedStatus If the method is called asynchronously, returns the request thread. """ all_params = ['name', 'pretty'] 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_project_openshift_io_v1_project" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'name' is set if ('name' not in params) or (params['name'] is None): raise ValueError("Missing the required parameter `name` when calling `delete_project_openshift_io_v1_project`") collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projects/{name}'.replace('{format}', 'json') path_params = {} if 'name' in params: path_params['name'] = params['name'] query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['*/*']) # Authentication setting auth_settings = ['BearerToken'] 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='UnversionedStatus', 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_project_openshift_io_v1_api_resources(self, **kwargs): """ get available resources 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_project_openshift_io_v1_api_resources(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: UnversionedAPIResourceList If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_project_openshift_io_v1_api_resources_with_http_info(**kwargs) else: (data) = self.get_project_openshift_io_v1_api_resources_with_http_info(**kwargs) return data def get_project_openshift_io_v1_api_resources_with_http_info(self, **kwargs): """ get available resources 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_project_openshift_io_v1_api_resources_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: UnversionedAPIResourceList 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_project_openshift_io_v1_api_resources" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/apis/project.openshift.io/v1/'.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', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # Authentication setting auth_settings = ['BearerToken'] 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='UnversionedAPIResourceList', 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 list_project_openshift_io_v1_project(self, **kwargs): """ list or watch objects of kind 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.list_project_openshift_io_v1_project(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str pretty: If 'true', then the output is pretty printed. :param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything. :param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything. :param str resource_version: When specified with a watch call, shows changes that occur after that particular version of a resource. Defaults to changes from the beginning of history. :param int timeout_seconds: Timeout for the list/watch call. :param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. :return: V1ProjectList If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.list_project_openshift_io_v1_project_with_http_info(**kwargs) else: (data) = self.list_project_openshift_io_v1_project_with_http_info(**kwargs) return data def list_project_openshift_io_v1_project_with_http_info(self, **kwargs): """ list or watch objects of kind 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.list_project_openshift_io_v1_project_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str pretty: If 'true', then the output is pretty printed. :param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything. :param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything. :param str resource_version: When specified with a watch call, shows changes that occur after that particular version of a resource. Defaults to changes from the beginning of history. :param int timeout_seconds: Timeout for the list/watch call. :param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. :return: V1ProjectList If the method is called asynchronously, returns the request thread. """ all_params = ['pretty', 'field_selector', 'label_selector', 'resource_version', 'timeout_seconds', 'watch'] 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 list_project_openshift_io_v1_project" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projects'.replace('{format}', 'json') path_params = {} query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] if 'field_selector' in params: query_params['fieldSelector'] = params['field_selector'] if 'label_selector' in params: query_params['labelSelector'] = params['label_selector'] if 'resource_version' in params: query_params['resourceVersion'] = params['resource_version'] if 'timeout_seconds' in params: query_params['timeoutSeconds'] = params['timeout_seconds'] if 'watch' in params: query_params['watch'] = params['watch'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json', 'application/yaml', 'application/vnd.kubernetes.protobuf', 'application/json;stream=watch', 'application/vnd.kubernetes.protobuf;stream=watch']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['*/*']) # Authentication setting auth_settings = ['BearerToken'] 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='V1ProjectList', 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 list_project_openshift_io_v1_project_request(self, **kwargs): """ list objects of kind ProjectRequest 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.list_project_openshift_io_v1_project_request(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str pretty: If 'true', then the output is pretty printed. :param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything. :param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything. :param str resource_version: When specified with a watch call, shows changes that occur after that particular version of a resource. Defaults to changes from the beginning of history. :param int timeout_seconds: Timeout for the list/watch call. :param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. :return: UnversionedStatus If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.list_project_openshift_io_v1_project_request_with_http_info(**kwargs) else: (data) = self.list_project_openshift_io_v1_project_request_with_http_info(**kwargs) return data def list_project_openshift_io_v1_project_request_with_http_info(self, **kwargs): """ list objects of kind ProjectRequest 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.list_project_openshift_io_v1_project_request_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str pretty: If 'true', then the output is pretty printed. :param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything. :param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything. :param str resource_version: When specified with a watch call, shows changes that occur after that particular version of a resource. Defaults to changes from the beginning of history. :param int timeout_seconds: Timeout for the list/watch call. :param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. :return: UnversionedStatus If the method is called asynchronously, returns the request thread. """ all_params = ['pretty', 'field_selector', 'label_selector', 'resource_version', 'timeout_seconds', 'watch'] 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 list_project_openshift_io_v1_project_request" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projectrequests'.replace('{format}', 'json') path_params = {} query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] if 'field_selector' in params: query_params['fieldSelector'] = params['field_selector'] if 'label_selector' in params: query_params['labelSelector'] = params['label_selector'] if 'resource_version' in params: query_params['resourceVersion'] = params['resource_version'] if 'timeout_seconds' in params: query_params['timeoutSeconds'] = params['timeout_seconds'] if 'watch' in params: query_params['watch'] = params['watch'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json', 'application/yaml', 'application/vnd.kubernetes.protobuf', 'application/json;stream=watch', 'application/vnd.kubernetes.protobuf;stream=watch']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['*/*']) # Authentication setting auth_settings = ['BearerToken'] 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='UnversionedStatus', 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 patch_project_openshift_io_v1_project(self, name, body, **kwargs): """ partially update the specified 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.patch_project_openshift_io_v1_project(name, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param UnversionedPatch body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.patch_project_openshift_io_v1_project_with_http_info(name, body, **kwargs) else: (data) = self.patch_project_openshift_io_v1_project_with_http_info(name, body, **kwargs) return data def patch_project_openshift_io_v1_project_with_http_info(self, name, body, **kwargs): """ partially update the specified 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.patch_project_openshift_io_v1_project_with_http_info(name, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param UnversionedPatch body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ all_params = ['name', 'body', 'pretty'] 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 patch_project_openshift_io_v1_project" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'name' is set if ('name' not in params) or (params['name'] is None): raise ValueError("Missing the required parameter `name` when calling `patch_project_openshift_io_v1_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 `patch_project_openshift_io_v1_project`") collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projects/{name}'.replace('{format}', 'json') path_params = {} if 'name' in params: path_params['name'] = params['name'] query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] 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', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json-patch+json', 'application/merge-patch+json', 'application/strategic-merge-patch+json']) # Authentication setting auth_settings = ['BearerToken'] 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='V1Project', 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 read_project_openshift_io_v1_project(self, name, **kwargs): """ read the specified 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.read_project_openshift_io_v1_project(name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.read_project_openshift_io_v1_project_with_http_info(name, **kwargs) else: (data) = self.read_project_openshift_io_v1_project_with_http_info(name, **kwargs) return data def read_project_openshift_io_v1_project_with_http_info(self, name, **kwargs): """ read the specified 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.read_project_openshift_io_v1_project_with_http_info(name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ all_params = ['name', 'pretty'] 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 read_project_openshift_io_v1_project" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'name' is set if ('name' not in params) or (params['name'] is None): raise ValueError("Missing the required parameter `name` when calling `read_project_openshift_io_v1_project`") collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projects/{name}'.replace('{format}', 'json') path_params = {} if 'name' in params: path_params['name'] = params['name'] query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['*/*']) # Authentication setting auth_settings = ['BearerToken'] 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='V1Project', 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 replace_project_openshift_io_v1_project(self, name, body, **kwargs): """ replace the specified 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.replace_project_openshift_io_v1_project(name, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param V1Project body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.replace_project_openshift_io_v1_project_with_http_info(name, body, **kwargs) else: (data) = self.replace_project_openshift_io_v1_project_with_http_info(name, body, **kwargs) return data def replace_project_openshift_io_v1_project_with_http_info(self, name, body, **kwargs): """ replace the specified 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.replace_project_openshift_io_v1_project_with_http_info(name, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str name: name of the Project (required) :param V1Project body: (required) :param str pretty: If 'true', then the output is pretty printed. :return: V1Project If the method is called asynchronously, returns the request thread. """ all_params = ['name', 'body', 'pretty'] 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 replace_project_openshift_io_v1_project" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'name' is set if ('name' not in params) or (params['name'] is None): raise ValueError("Missing the required parameter `name` when calling `replace_project_openshift_io_v1_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 `replace_project_openshift_io_v1_project`") collection_formats = {} resource_path = '/apis/project.openshift.io/v1/projects/{name}'.replace('{format}', 'json') path_params = {} if 'name' in params: path_params['name'] = params['name'] query_params = {} if 'pretty' in params: query_params['pretty'] = params['pretty'] 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', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['*/*']) # Authentication setting auth_settings = ['BearerToken'] 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='V1Project', 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)

48.605138

3,330

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99b784ea762fa79ecdc3e367501447aed934f052

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py

Python

multilingual_t5/r_indic_corp_hi/__init__.py

sumanthd17/mt5

c99b4e3ad1c69908c852c730a1323ccb52d48f58

[ "Apache-2.0" ]

null

multilingual_t5/r_indic_corp_hi/__init__.py

sumanthd17/mt5

c99b4e3ad1c69908c852c730a1323ccb52d48f58

[ "Apache-2.0" ]

null

multilingual_t5/r_indic_corp_hi/__init__.py

sumanthd17/mt5

c99b4e3ad1c69908c852c730a1323ccb52d48f58

[ "Apache-2.0" ]

null

"""r_indic_corp_hi dataset.""" from .r_indic_corp_hi import RIndicCorpHi

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82196da273f06f3d3a7635d9543ec944bb1c88dc

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py

Python

moonsense/models/__init__.py

moonsense/python-sdk

0ac6e03ded5c4c6fb001dd93bd29201555bce56c

[ "Apache-2.0" ]

6

2021-06-02T15:29:05.000Z

2022-03-21T20:13:40.000Z

moonsense/models/__init__.py

moonsense/python-sdk

0ac6e03ded5c4c6fb001dd93bd29201555bce56c

[ "Apache-2.0" ]

1

2021-12-16T09:45:49.000Z

moonsense/models/__init__.py

moonsense/python-sdk

0ac6e03ded5c4c6fb001dd93bd29201555bce56c

[ "Apache-2.0" ]

null

from .common_v2_pb2 import * from .bundle_v2_pb2 import * from .control_plane_v2_pb2 import * from .data_plane_v2_pb2 import *

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413582b3aa1150aa2583c89e3333be5d6a6eb0d1

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py

Python

ir_export_extended_ept/py/__init__.py

lester-lees/extra_addons_sz

cddaf972cf4ea64c553bcff0006eb006a115d5ee

[ "Apache-2.0" ]

null

ir_export_extended_ept/py/__init__.py

lester-lees/extra_addons_sz

cddaf972cf4ea64c553bcff0006eb006a115d5ee

[ "Apache-2.0" ]

null

ir_export_extended_ept/py/__init__.py

lester-lees/extra_addons_sz

cddaf972cf4ea64c553bcff0006eb006a115d5ee

[ "Apache-2.0" ]

null

import ir_exports import ir_exports_line

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4197dc883e284a4a71e71e025308ce1eec697df6

7,060

py

Python

components/core/qcg/pilotjob/tests/test_iterschedulers.py

LourensVeen/QCG-PilotJob

e78c35a9b16b1042a2d5b54352a2ca2e3a58c6b9

[ "Apache-2.0" ]

null

components/core/qcg/pilotjob/tests/test_iterschedulers.py

LourensVeen/QCG-PilotJob

e78c35a9b16b1042a2d5b54352a2ca2e3a58c6b9

[ "Apache-2.0" ]

null

components/core/qcg/pilotjob/tests/test_iterschedulers.py

LourensVeen/QCG-PilotJob

e78c35a9b16b1042a2d5b54352a2ca2e3a58c6b9

[ "Apache-2.0" ]

null

import pytest from qcg.pilotjob.iterscheduler import IterScheduler, MaximumIters, SplitInto, DefaultScheduler def test_iterscheduler_parsing(): assert IterScheduler.get_scheduler('maximum-iters') == MaximumIters assert IterScheduler.get_scheduler('MAXIMUM-ITERS') == MaximumIters assert IterScheduler.get_scheduler('Maximum-Iters') == MaximumIters assert IterScheduler.get_scheduler('split-into') == SplitInto assert IterScheduler.get_scheduler('SPLIT-INTO') == SplitInto assert IterScheduler.get_scheduler('SpliT-Into') == SplitInto assert IterScheduler.get_scheduler('unknown') == DefaultScheduler def test_iterscheduler_splitinto(): iters = 10 resources = 10 split_into = 10 si_sched_gen = IterScheduler.get_scheduler('split-into')({'min': 1}, iters, resources, parts=split_into).generate() for i in range(iters): job_iter_res = next(si_sched_gen) assert job_iter_res and all(('exact', job_iter_res['exact'] == resources / iters)),\ str(job_iter_res) with pytest.raises(StopIteration): next(si_sched_gen) resources = 10 split_into = 5 si_sched_gen = IterScheduler.get_scheduler('split-into')({'min': 1}, iters, resources, parts=split_into).generate() for i in range(iters): job_iter_res = next(si_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == resources / split_into)),\ str(job_iter_res) with pytest.raises(StopIteration): next(si_sched_gen) resources = 10 split_into = 2 si_sched_gen = IterScheduler.get_scheduler('split-into')({'min': 1}, iters, resources, parts=split_into).generate() for i in range(iters): job_iter_res = next(si_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == resources / split_into)), \ str(job_iter_res) with pytest.raises(StopIteration): next(si_sched_gen) # default 'parts' as number of iterations resources = 10 si_sched_gen = IterScheduler.get_scheduler('split-into')({'min': 1}, iters, resources).generate() for i in range(iters): job_iter_res = next(si_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == resources / iters)), \ str(job_iter_res) with pytest.raises(StopIteration): next(si_sched_gen) def test_iterscheduler_maximum_iters(): # all iterations in single round iters = 10 resources = 10 mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 1, }, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == 1)), \ str(job_iter_res) with pytest.raises(StopIteration): next(mi_sched_gen) # two rounds iters = 20 resources = 10 mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 1, }, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == 1)), \ str(job_iter_res) with pytest.raises(StopIteration): next(mi_sched_gen) # single rounds, with two resources iters = 5 resources = 10 mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 1, }, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == 2)), \ str(job_iter_res) with pytest.raises(StopIteration): next(mi_sched_gen) # single rounds, 4, 3, 3 iters = 3 resources = 10 res = [3, 3, 4] mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 1, }, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == res[i])), \ str(job_iter_res) with pytest.raises(StopIteration): next(mi_sched_gen) # single rounds, 4, 3, 3 iters = 3 resources = 10 res = [3, 3, 4] mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({}, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == res[i])), \ str(job_iter_res) with pytest.raises(StopIteration): next(mi_sched_gen) # single rounds, 4, 4, 3 iters = 3 resources = 11 res = [3, 4, 4] mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({}, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == res[i])), \ str(job_iter_res) with pytest.raises(StopIteration): next(mi_sched_gen) # single rounds, 4, 4, 3 iters = 3 resources = 11 res = [3, 4, 4] mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 3}, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == res[i])), \ str(job_iter_res) with pytest.raises(StopIteration): next(mi_sched_gen) # two rounds (two jobs in first, single in second), 6, 5, 11 iters = 3 resources = 11 res = [5, 6, 11] mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 5}, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == res[i])), \ "{} - {}".format(i, str(job_iter_res)) with pytest.raises(StopIteration): next(mi_sched_gen) # two rounds (2 jobs in single), 6, 5, 6, 5 iters = 4 resources = 11 res = [5, 6, 5, 6] mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 5}, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == res[i])), \ "{} - {}".format(i, str(job_iter_res)) with pytest.raises(StopIteration): next(mi_sched_gen) # four rounds (1 job in round), 11, 11, 11, 11 iters = 4 resources = 11 res = [11, 11, 11, 11] mi_sched_gen = IterScheduler.get_scheduler('maximum-iters')({'min': 6}, iters, resources).generate() for i in range(iters): job_iter_res = next(mi_sched_gen) assert job_iter_res and all(('exact' in job_iter_res, job_iter_res['exact'] == res[i])), \ "{} - {}".format(i, str(job_iter_res)) with pytest.raises(StopIteration): next(mi_sched_gen)

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419f5d28e8e6fa68d994dfffcd1cde45efc1f5ea

136

py

Python

api/views.py

annevandalfsen/screenbird

38b70302be3b3dc0c74b6aae8e09666115592aef

[ "MIT", "Unlicense" ]

121

2015-01-01T23:31:36.000Z

2021-05-27T04:24:44.000Z

api/views.py

annevandalfsen/screenbird

38b70302be3b3dc0c74b6aae8e09666115592aef

[ "MIT", "Unlicense" ]

1

2017-02-08T04:34:14.000Z

api/views.py

annevandalfsen/screenbird

38b70302be3b3dc0c74b6aae8e09666115592aef

[ "MIT", "Unlicense" ]

31

2015-01-13T00:23:33.000Z

2017-05-13T21:50:29.000Z

def config_record_on_account(request,account_id): pass def config_record_on_channel(request, channel_id): pass

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41bbf2787754bba6b1c72e243963d17373bc02e6

470

py

Python

exercises/exe11 - 20/exe014.py

thomas-rohde/Classes-Python

f862995510b7aabf68bc14aecf815f597034d8a1

[ "MIT" ]

null

exercises/exe11 - 20/exe014.py

thomas-rohde/Classes-Python

f862995510b7aabf68bc14aecf815f597034d8a1

[ "MIT" ]

null

exercises/exe11 - 20/exe014.py

thomas-rohde/Classes-Python

f862995510b7aabf68bc14aecf815f597034d8a1

[ "MIT" ]

null

'''import math n = float(input('Digite um nº: ')) print('O valor digitado foi {}, tendo sua parte inteira {}, e decimal {:.3f}'.format(n,math.trunc(n), n - math.trunc(n)))''' '''from math import trunc n = float(input('Digite um nº: ')) print('O valor digitado foi {}, tendo sua parte inteira {}, e decimal {:.3f}'.format(n, trunc(n), n - trunc(n)))''' n = float(input('Digite um nº: ')) print('O valor digitado foi {}, tendo sua parte inteira {}'.format(n, int(n)))

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ec0cf3fd597003746f562587b03aba68d0d218bd

82

py

Python

pbpl/common/meep_units.py

ucla-pbpl/pbpl-common

959aea73b6969e2c06654bc920cc5a57787f81a8

[ "MIT" ]

null

pbpl/common/meep_units.py

ucla-pbpl/pbpl-common

959aea73b6969e2c06654bc920cc5a57787f81a8

[ "MIT" ]

null

pbpl/common/meep_units.py

ucla-pbpl/pbpl-common

959aea73b6969e2c06654bc920cc5a57787f81a8

[ "MIT" ]

null

from .units import define_constants define_constants('MEEP') from .units import *

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7

ec15cb348ada2875583084f4181ad1e5e4399cc0

101

py

Python

craigsbot/parser/__init__.py

mohsinhaider/craigsbot

e7a6237024c1a06b17fed326b93069085bcb3e3d

[ "MIT" ]

null

craigsbot/parser/__init__.py

mohsinhaider/craigsbot

e7a6237024c1a06b17fed326b93069085bcb3e3d

[ "MIT" ]

null

craigsbot/parser/__init__.py

mohsinhaider/craigsbot

e7a6237024c1a06b17fed326b93069085bcb3e3d

[ "MIT" ]

null

from craigsbot.parser.craigslist_parser import CraigslistSearchResultsParser, CraigslistPostingParser

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7

ec1d4c88551a2cf8a9fc16177272d3e04d273afa

21,758

py

Python

data_analysis/gaze/pipelines.py

vedb/data_analysis

b46f58ba424680353d3abd0014a7d0a339bf6e6c

[ "MIT" ]

null

data_analysis/gaze/pipelines.py

vedb/data_analysis

b46f58ba424680353d3abd0014a7d0a339bf6e6c

[ "MIT" ]

null

data_analysis/gaze/pipelines.py

vedb/data_analysis

b46f58ba424680353d3abd0014a7d0a339bf6e6c

[ "MIT" ]

null

# Calibration script # import vm_preproc as vmp # import vedb_store import numpy as np import tqdm import os from . import pupil_detection_pl, calibrate_pl from . import marker_detection, gaze_utils from pupil_recording_interface.externals.gaze_mappers import Binocular_Gaze_Mapper # # def pupil_2d_monocular_v01( # session_folder, # sname=None, # Base for each file? # tag="pupil_2d_monocular_v01", # output_path=None, # batch_size_pupil="auto", # batch_size_marker="auto", # marker_rescale=0.5, # progress_bar=tqdm.tqdm, # properties=None, # ): # """ # Parameters # ---------- # tag : A short label for the pipeline # session_folder : string # file path to session. Ultimately want to replace this with a session # object from the database. # sname : format string # must contain {step}; if provided, tag and output_path are ignored # # Notes # ----- # Ultimately, for saving files, we want the output of each step saved # along with the function and parameters that were used to generate it. # # This is not the case now. Needs work. # """ # # Deal with inputs # if output_path is None: # output_path = session_folder # if sname is None: # sname = os.path.join(output_path, "gaze_vedb", tag + "_{step}.npz") # fdir, _ = os.path.split(sname) # if not os.path.exists(fdir): # print("creating", fdir) # os.makedirs(fdir) # # (0) Get session # ses = vedb_store.Session(folder=session_folder) # # (1) Pupil detection (L, R) # fn_pupil = pupil_detection_pl.plabs_detect_pupil # # pupil_file_left = sname.format(step="pupilpos_left") # if os.path.exists(pupil_file_left): # print("Loading pupils left") # pupil_arrays_left = {} # dat = np.load(pupil_file_left, allow_pickle=True) # for k in dat.keys(): # pupil_arrays_left[k] = dat[k] # pupil_list_left = gaze_utils.arraydict_to_dictlist(pupil_arrays_left) # else: # # Get eye files (Left eye) # eye_left_time_file, eye_left_video_file = ses.paths["eye_left"] # inputs_pupil_left = dict( # fpaths=dict(eye_video=eye_left_video_file, timestamps=eye_left_time_file,), # variable_names=None, # ) # print("\n\nRunning pupil detection for the left eye\n\n") # # Run pupil detection # pupil_list_left = vmp.utils.batch_run( # fn_pupil, # inputs_pupil_left, # batch_size=batch_size_pupil, # batch_combine_fn=vmp.utils.list_reduce, # progress_bar=progress_bar, # id=1, # left eye # FIX ME: OPTION HERE FOR R, L, or binocular # properties=properties, # ) # # Get arrays instead of list of dicts # pupil_arrays_left = gaze_utils.dictlist_to_arraydict(pupil_list_left) # # Save pupil detection # pupil_file_left = sname.format(step="pupilpos_left") # np.savez(pupil_file_left, **pupil_arrays_left) # # pupil_file_right = sname.format(step="pupilpos_right") # if os.path.exists(pupil_file_right): # print("Loading pupils right") # pupil_arrays_right = {} # dat = np.load(pupil_file_right, allow_pickle=True) # for k in dat.keys(): # pupil_arrays_right[k] = dat[k] # pupil_list_right = gaze_utils.arraydict_to_dictlist(pupil_arrays_right) # else: # # Get eye files (Right eye) # eye_right_time_file, eye_right_video_file = ses.paths["eye_right"] # inputs_pupil_right = dict( # fpaths=dict( # eye_video=eye_right_video_file, timestamps=eye_right_time_file, # ), # variable_names=None, # ) # print("\n\nRunning pupil detection for the right eye\n\n") # # Run pupil detection # pupil_list_right = vmp.utils.batch_run( # fn_pupil, # inputs_pupil_right, # batch_size=batch_size_pupil, # batch_combine_fn=vmp.utils.list_reduce, # progress_bar=progress_bar, # id=0, # right eye # FIX ME: OPTION HERE FOR R, L, or binocular # properties=properties, # ) # # Get arrays instead of list of dicts # pupil_arrays_right = gaze_utils.dictlist_to_arraydict(pupil_list_right) # # Save pupil detection # # np.savez(pupil_file_right, **pupil_arrays_right) # # # (2) Marker detection # ref_file = sname.format(step="markerpos") # # Get world video files # world_time_file, world_video_file = ses.paths["world_camera"] # # Load 1 second of data 10 seconds in (to allow time for camera to start) # world_time, world_video = ses.load("world_camera", idx=(10, 11)) # _, video_vdim, video_hdim = world_video.shape[:3] # # if os.path.exists(ref_file): # print("Loading markers") # ref_arrays = {} # dat = np.load(ref_file, allow_pickle=True) # for k in dat.keys(): # ref_arrays[k] = dat[k] # ref_list = gaze_utils.arraydict_to_dictlist(ref_arrays) # else: # fn_marker = marker_detection.find_concentric_circles # inputs_marker = dict( # fpaths=dict(video_data=world_video_file, timestamps=world_time_file), # variable_names=None, # ) # print("\n\nRunning marker detection \n\n") # # Run marker detection # ref_list = vmp.utils.batch_run( # fn_marker, # inputs_marker, # batch_size=batch_size_marker, # batch_combine_fn=vmp.utils.list_reduce, # scale=marker_rescale, # progress_bar=progress_bar, # ) # # Get arrays instead of dicts # ref_arrays = gaze_utils.dictlist_to_arraydict(ref_list) # # Save calibration markers # np.savez(ref_file, **ref_arrays) # # # (3) Calibrate # # Get data for pupil calibration # print("\n\nGetting data for calibration \n\n") # is_binocular, matched_data_left = calibrate_pl.get_data(pupil_list_left, ref_list) # # Run calibration # # NOTE: zero index for matched_data here is because this is simply monocular, # # and matched data only returns a 1-long tuple. If we want binocular, this will # # need changing. # print("\n\nRunning 2d monocular calibration [left eye] \n\n") # method, result_left = calibrate_pl.calibrate_2d_monocular( # matched_data_left[0], frame_size=(video_vdim, video_hdim) # ) # # Create mapper for gaze # cx, cy, n = result_left["args"]["params"] # mapper_left = calibrate_pl.calibrate_2d.make_map_function(cx, cy, n) # # # (4) Map gaze to video coordinates # # Mapper takes two inputs: normalized pupil x and y position # print("\n\nRunning gaze mapper [left eye] \n\n") # pupil_x, pupil_y = pupil_arrays_left["norm_pos"].T # gaze_left = mapper_left([pupil_x, pupil_y]) # # Transpose output so time is the first dimension # gaze_left = np.vstack(gaze_left).T # # is_binocular, matched_data_right = calibrate_pl.get_data(pupil_list_right, ref_list) # # Run calibration # # NOTE: zero index for matched_data here is because this is simply monocular, # # and matched data only returns a 1-long tuple. If we want binocular, this will # # need changing. # print("\n\nRunning 2d monocular calibration [right eye] \n\n") # method, result_right = calibrate_pl.calibrate_2d_monocular( # matched_data_right[0], frame_size=(video_vdim, video_hdim) # ) # # Create mapper for gaze # cx, cy, n = result_right["args"]["params"] # mapper_right = calibrate_pl.calibrate_2d.make_map_function(cx, cy, n) # # # (4) Map gaze to video coordinates # # Mapper takes two inputs: normalized pupil x and y position # print("\n\nRunning gaze mapper [right eye] \n\n") # pupil_x, pupil_y = pupil_arrays_right["norm_pos"].T # gaze_right = mapper_right([pupil_x, pupil_y]) # # Transpose output so time is the first dimension # gaze_right = np.vstack(gaze_right).T # # gaze_file = sname.format(step="gaze") # np.savez(gaze_file, gaze_left=gaze_left, gaze_right=gaze_right) # return gaze_left, gaze_right # # def pupil_2d_binocular_v01( # session_folder, # param_dict, # string_name=None, # Base for each file? # tag="pupil_2d_binocular_v02", # output_path=None, # batch_size_pupil="auto", # batch_size_marker="auto", # marker_rescale=1, # progress_bar=tqdm.tqdm, # properties=None, # ): # """ # Parameters # ---------- # tag : A short label for the pipeline # session_folder : string # file path to session. Ultimately want to replace this with a session # object from the database. # string_name : format string # must contain {step}; if provided, tag and output_path are ignored # # Notes # ----- # Ultimately, for saving files, we want the output of each step saved # along with the function and parameters that were used to generate it. # # This is not the case now. Needs work. # """ # print(param_dict.keys()) # # Todo: Read length of the session id from parameters? # session_id = session_folder[-19:] + '/' # output_path = param_dict['directory']['gaze_directory'] + session_id # # Deal with inputs # if output_path is None: # #output_path = session_folder # raise ValueError("parameters' yaml file doesn't have valid gaze saving_directory!") # else: # print("saving results to: ", output_path) # # tag = param_dict['calibration']['pupil_detection'] + '_' +\ # param_dict['calibration']['eye'] + '_' +\ # param_dict['calibration']['algorithm'] # print('tag : ', tag) # if string_name is None: # string_name = os.path.join(output_path, tag + "_{step}.npz") # print("file_name", string_name) # #fdir, _ = os.path.split(string_name) # if not os.path.exists(output_path): # print("creating", output_path) # os.makedirs(output_path) # # (0) Get session # session = vedb_store.Session(folder=session_folder) # # (1) Pupil detection (L, R) # fn_pupil = pupil_detection_pl.plabs_detect_pupil # # pupil_file_left = string_name.format(step="pupil_pos_left") # if os.path.exists(pupil_file_left): # print("Loading pupils left") # pupil_arrays_left = {} # data = np.load(pupil_file_left, allow_pickle=True) # for k in data.keys(): # pupil_arrays_left[k] = data[k] # pupil_list_left = gaze_utils.arraydict_to_dictlist(pupil_arrays_left) # else: # # Get eye files (Left eye) # eye_left_time_file, eye_left_video_file = session.paths["eye_left"] # inputs_pupil_left = dict( # fpaths=dict(eye_video=eye_left_video_file, timestamps=eye_left_time_file,), # variable_names=None, # ) # print("\n\nRunning pupil detection for the left eye\n\n") # # Run pupil detection # pupil_list_left = vmp.utils.batch_run( # fn_pupil, # inputs_pupil_left, # batch_size=batch_size_pupil, # batch_combine_fn=vmp.utils.list_reduce, # progress_bar=progress_bar, # id=1, # left eye # FIX ME: OPTION HERE FOR R, L, or binocular # properties=properties, # ) # # Get arrays instead of list of dicts # pupil_arrays_left = gaze_utils.dictlist_to_arraydict(pupil_list_left) # # Save pupil detection # pupil_file_left = string_name.format(step="pupil_pos_left") # np.savez(pupil_file_left, **pupil_arrays_left) # # pupil_file_right = string_name.format(step="pupil_pos_right") # if os.path.exists(pupil_file_right): # print("Loading pupils right") # pupil_arrays_right = {} # data = np.load(pupil_file_right, allow_pickle=True) # for k in data.keys(): # pupil_arrays_right[k] = data[k] # pupil_list_right = gaze_utils.arraydict_to_dictlist(pupil_arrays_right) # else: # # Get eye files (Right eye) # eye_right_time_file, eye_right_video_file = session.paths["eye_right"] # inputs_pupil_right = dict( # fpaths=dict( # eye_video=eye_right_video_file, timestamps=eye_right_time_file, # ), # variable_names=None, # ) # print("\n\nRunning pupil detection for the right eye\n\n") # # Run pupil detection # pupil_list_right = vmp.utils.batch_run( # fn_pupil, # inputs_pupil_right, # batch_size=batch_size_pupil, # batch_combine_fn=vmp.utils.list_reduce, # progress_bar=progress_bar, # id=0, # right eye # FIX ME: OPTION HERE FOR R, L, or binocular # properties=properties, # ) # # Get arrays instead of list of dicts # pupil_arrays_right = gaze_utils.dictlist_to_arraydict(pupil_list_right) # # Save pupil detection # # np.savez(pupil_file_right, **pupil_arrays_right) # # # (2) Calibration Marker detection # cal_ref_file = string_name.format(step="calibration_ref_pos") # # Get world video files # # Todo: Make sure this is loaded only if necessary # world_time_file, world_video_file = session.paths["world_camera"] # # Load 1 second of data 10 seconds in (to allow time for camera to start) # world_time, world_video = session.load("world_camera", idx=(10, 11)) # _, video_vdim, video_hdim = world_video.shape[:3] # # if os.path.exists(cal_ref_file): # print("Loading calibration markers") # ref_arrays = {} # data = np.load(cal_ref_file, allow_pickle=True) # for k in data.keys(): # ref_arrays[k] = data[k] # ref_list = gaze_utils.arraydict_to_dictlist(ref_arrays) # else: # fn_marker = marker_detection.find_concentric_circles # inputs_marker = dict( # fpaths=dict(video_data=world_video_file, timestamps=world_time_file), # variable_names=None, # ) # print("\n\nRunning Calibration marker detection \n\n") # # Run marker detection # ref_list = vmp.utils.batch_run( # fn_marker, # inputs_marker, # batch_size=batch_size_marker, # batch_combine_fn=vmp.utils.list_reduce, # scale=marker_rescale, # progress_bar=progress_bar, # ) # # Get arrays instead of dicts # ref_arrays = gaze_utils.dictlist_to_arraydict(ref_list) # # Save calibration markers # np.savez(cal_ref_file, **ref_arrays) # # # (3) Validation Marker detection # val_ref_file = string_name.format(step="validation_ref_pos_dict") # # Todo: Make sure this is handled correctly # # Get world video files # # world_time_file, world_video_file = session.paths["world_camera"] # # Load 1 second of data 10 seconds in (to allow time for camera to start) # # world_time, world_video = session.load("world_camera", idx=(10, 11)) # # _, video_vdim, video_hdim = world_video.shape[:3] # # if os.path.exists(val_ref_file): # print("Loading validation markers") # ref_arrays = {} # data = np.load(val_ref_file, allow_pickle=True) # for k in data.keys(): # ref_arrays[k] = data[k] # ref_list = gaze_utils.arraydict_to_dictlist(ref_arrays) # else: # fn_marker = marker_detection.find_checkerboard # inputs_marker = dict( # fpaths=dict(video_data=world_video_file, timestamps=world_time_file), # variable_names=None, # ) # print("\n\nRunning Validation marker detection \n\n") # # Run marker detection # val_ref_list = vmp.utils.batch_run( # fn_marker, # inputs_marker, # batch_size=batch_size_marker, # batch_combine_fn=vmp.utils.list_reduce, # scale=0.5, # progress_bar=progress_bar, # ) # print(val_ref_list) # np.savez(val_ref_file, val_ref_list) # val_ref_file = string_name.format(step="validation_ref_pos") # # Get arrays instead of dicts # val_ref_arrays = gaze_utils.dictlist_to_arraydict(val_ref_list) # # Save calibration markers # np.savez(val_ref_file, **val_ref_arrays) # # # (4) Append left and right pupil lists # # Append the two pupil lists (list of dicts compatible with pupil notation) # # And then pass the appended list to the calibration routine # # pupil_list_binocular = [] # pupil_list_binocular.extend(pupil_list_left) # pupil_list_binocular.extend(pupil_list_right) # # # Get arrays instead of list of dicts # pupil_arrays_binocular = gaze_utils.dictlist_to_arraydict(pupil_list_binocular) # pupil_arrays_right = gaze_utils.dictlist_to_arraydict(pupil_list_right) # pupil_arrays_left = gaze_utils.dictlist_to_arraydict(pupil_list_left) # # print("\n\nAppending left and right pupil positions") # print("left:{} right:{} binocular:{} \n\n".format(len(pupil_list_left), len(pupil_list_right), len(pupil_list_binocular))) # # # (5) Calibrate # # Get data for pupil calibration # print("\n\nGetting data for calibration \n\n") # is_binocular, matched_data_binocular = calibrate_pl.get_data(pupil_list_binocular, ref_list, mode="2d") # # Run calibration # print("\n\nRunning 2d binocular calibration \n\n") # method, result = calibrate_pl.calibrate_2d_binocular( # *matched_data_binocular, frame_size=(video_vdim, video_hdim) # ) # # (6) Map gaze to video coordinates # # Mapper takes two inputs: normalized pupil x and y position # print("\n\nRunning gaze mapper [binocular] \n\n") # # # Create mapper for gaze # if (result): # binocular_gaze_mapper = Binocular_Gaze_Mapper(result["args"]["params"], result["args"]["params_eye0"], result["args"]["params_eye1"]) # gaze_binocular = binocular_gaze_mapper.map_batch(pupil_list_binocular) # # Transpose output so time is the first dimension # # TODO: Make sure the format is consistent with the monocular gaze # # gaze_binocular = np.vstack(gaze_binocular).T # # gaze_file = string_name.format(step="gaze") # np.savez(gaze_file, gaze_binocular=gaze_binocular) # final_result = True # else: # print("\n\nGaze Mapping Failed for Subject: ", session_id) # final_result = False # return final_result # # # def pupil_2d_monocular_v02( # video_file_name, # session_folder, # sname=None, # Base for each file? # tag="pupil_2d_monocular_v02", # output_path=None, # batch_size_pupil="auto", # progress_bar=tqdm.tqdm, # properties=None, # ): # """ # Parameters # ---------- # tag : A short label for the pipeline # session_folder : string # file path to session. Ultimately want to replace this with a session # object from the database. # sname : format string # must contain {step}; if provided, tag and output_path are ignored # # Notes # ----- # Ultimately, for saving files, we want the output of each step saved # along with the function and parameters that were used to generate it. # # This is not the case now. Needs work. # """ # # Deal with inputs # if output_path is None: # output_path = session_folder # if sname is None: # sname = os.path.join(output_path, "gaze_vedb", tag + "_" + video_file_name[:-4] + "_{step}.npz") # fdir, _ = os.path.split(sname) # if not os.path.exists(fdir): # print("creating", fdir) # os.makedirs(fdir) # # (0) Get session # # ses = vedb_store.Session(folder=session_folder) # # (1) Pupil detection (L, R) # fn_pupil = pupil_detection_pl.plabs_detect_pupil # # pupil_file_left = sname.format(step="pupilpos_left") # if os.path.exists(pupil_file_left): # print("Loading pupils left") # pupil_arrays_left = {} # dat = np.load(pupil_file_left, allow_pickle=True) # for k in dat.keys(): # pupil_arrays_left[k] = dat[k] # pupil_list_left = gaze_utils.arraydict_to_dictlist(pupil_arrays_left) # print(pupil_list_left[0].keys()) # print("found pupil file for: ", pupil_file_left, "\n\n") # else: # # Get eye files (Left eye) # eye_left_video_file = session_folder + video_file_name # inputs_pupil_left = dict( # fpaths=dict(eye_video=eye_left_video_file,), # variable_names=None, # ) # print("\n\nRunning pupil detection for the left eye\n\n") # # Run pupil detection # pupil_list_left = vmp.utils.batch_run( # fn_pupil, # inputs_pupil_left, # batch_size=batch_size_pupil, # batch_combine_fn=vmp.utils.list_reduce, # progress_bar=progress_bar, # id=1, # left eye # FIX ME: OPTION HERE FOR R, L, or binocular # properties=properties, # ) # # Get arrays instead of list of dicts # pupil_arrays_left = gaze_utils.dictlist_to_arraydict(pupil_list_left) # # Save pupil detection # pupil_file_left = sname.format(step="pupilpos_left") # np.savez(pupil_file_left, **pupil_arrays_left) # print("\n\nSaved left pupil data into:",pupil_file_left,"\n\n") #

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Python

LabReport/Lab4/edit_post.py

Liu-Hong-De/Software_test

068bbadd7b6d369445994e16aea4289618337910

[ "Apache-2.0" ]

null

LabReport/Lab4/edit_post.py

Liu-Hong-De/Software_test

068bbadd7b6d369445994e16aea4289618337910

[ "Apache-2.0" ]

1

2022-01-21T23:39:34.000Z

LabReport/Lab4/edit_post.py

Liu-Hong-De/Software_test

068bbadd7b6d369445994e16aea4289618337910

[ "Apache-2.0" ]

null

import unittest import time from selenium import webdriver from selenium.webdriver.common.keys import Keys from selenium.webdriver.common.by import By from bs4 import BeautifulSoup from selenium.webdriver.support.ui import Select class EditPost(unittest.TestCase): # use the demo account to sign in and create a post to edit def setUp(self): self.driver = webdriver.Chrome() driver =self.driver driver.implicitly_wait(5) # set a waiting time at most 20 seconds driver.get("http://127.0.0.1:3000") driver.find_element_by_xpath("//*[@id=\"navbar-collapse\"]/ul[2]/li[2]/a").click() # click the sign in button time.sleep(1) driver.find_element_by_name("email").send_keys("demo@keystonejs.com") # enter the email and password driver.find_element_by_name("password").send_keys("demo") time.sleep(1) driver.find_element_by_xpath("//*[@id=\"signin-view\"]/div/div[1]/div/div[2]/form/button").click() # click to sign in time.sleep(2) driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div[2]/div/div[1]/div[2]/div[1]/span/a[2]").click() time.sleep(1) driver.find_element_by_name("name").send_keys("use selenium to edit a post") time.sleep(1) try: driver.find_element_by_class_name("css-h629qq").click() except: driver.find_element_by_class_name("css-nil").submit() time.sleep(1) driver.find_element_by_class_name("css-dmf4a8").click() time.sleep(2) # test case 1 # edit post with empty name # empty name is invalid def test_EditPostWithEmptyName(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() time.sleep(1) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) page_result = [] page_result.append(driver.page_source) NewExplain = [] for item0 in page_result: html_soup = BeautifulSoup(item0, "lxml") NewExplain = html_soup.select('#react-root > div > main > div > div > div.css-1xkojxp > form > div.css-1nqppvz > div') assert "Name is required" in NewExplain[0].text driver.back() time.sleep(2) # test case 2 # edit post with name def test_EditPostWithName(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_class_name("css-ctpeu").text driver.back() time.sleep(1) assert "edit OK" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[2]/a").text time.sleep(2) # test case 3 # edit post with state is Published def test_EditPostWithStatePublished(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListState = [] [inputListState.append(input) for input in inputList if input.is_displayed()] inputListState[2].send_keys("Published") inputListState[2].send_keys(Keys.ENTER) time.sleep(1) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_class_name("css-ctpeu").text driver.back() time.sleep(1) assert "edit OK" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[2]/a").text assert "Published" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[3]/div").text time.sleep(2) # test case 4 # edit post with state is Archived def test_EditPostWithStateArchived(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListState = [] [inputListState.append(input) for input in inputList if input.is_displayed()] inputListState[2].send_keys("Archived") inputListState[2].send_keys(Keys.ENTER) time.sleep(1) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_class_name("css-ctpeu").text driver.back() time.sleep(1) assert "edit OK" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[2]/a").text assert "Archived" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[3]/div").text time.sleep(2) # test case 5 # edit post with author is Demo User def test_EditPostWithAuthor(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListAuthor = [] [inputListAuthor.append(input) for input in inputList if input.is_displayed()] inputListAuthor[3].send_keys("Demo User") inputListAuthor[3].send_keys(Keys.ENTER) time.sleep(1) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_class_name("css-ctpeu").text driver.back() time.sleep(1) assert "edit OK" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[2]/a").text assert "Demo User" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr/td[4]/a").text time.sleep(2) # test case 6 # edit post with published date format is yyyy-mmdd def test_EditPostWithDate_yyyy_mmdd(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("2020-0603") time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_class_name("css-ctpeu").text driver.back() time.sleep(1) assert "edit OK" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[2]/a").text assert "June 3rd 2020" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr/td[5]/div").text time.sleep(2) # test case 7 # failed # expected：June 3rd 2020 # actual：March 1st 2020 # test post with published date format is yyyymm-dd def test_EditPostWithDate_yyyymm_dd(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("202006-03") time.sleep(1) time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_class_name("css-ctpeu").text driver.back() time.sleep(1) assert "edit OK" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[2]/a").text assert "June 3rd 2020" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr/td[5]/div").text time.sleep(2) # test case 8 # edit post with published date format is yyyymmdd def test_EditPostWithDate_yyyymmdd(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("20200603") time.sleep(1) time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_class_name("css-ctpeu").text driver.back() time.sleep(1) assert "edit OK" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr[1]/td[2]/a").text assert "June 3rd 2020" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[3]/div/div/table/tbody/tr/td[5]/div").text time.sleep(2) # test case 9 # test post with published date format is yyyymdd # date format is invalid def test_EditPostWithDate_yyyymdd(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("2020603") time.sleep(1) time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "PublishedDate is invalid" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[1]/form/div[1]/div").text driver.back() time.sleep(2) # test case 10 # test post with published date Month is bigger than 12 # date format is invalid def test_EditPostWithDate_Big_Month(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("2020-60-03") time.sleep(1) time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "PublishedDate is invalid" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[1]/form/div[1]/div").text driver.back() time.sleep(2) # test case 11 # test post with published date Day is bigger than the day of this year # date format is invalid def test_EditPostWithDate_Big_Day(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("2020-06-99") time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "PublishedDate is invalid" in driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[1]/form/div[1]/div").text driver.back() time.sleep(2) # test case 12 # failed # expected：PublishedDate is invalid # actual：Your changes have been saved successfully # test post with published date Month is more than two digits def test_EditPostWithDate_Month_MoreThanTwoDigits(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("2020-111-03") time.sleep(1) time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) NewExplain = [] NewExplain = driver.find_elements_by_css_selector("#react-root > div > main > div > div > div.css-1xkojxp > form > div.css-ctpeu") try: assert "PublishedDate is invalid" in NewExplain[0].text finally: driver.back() time.sleep(2) # test case 13 # failed # expected：PublishedDate is invalid # actual：Your changes have been saved successfully # test post with published date Day is more than two digits def test_EditPostWithDate_Day_MoreThanTwoDigits(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("2020-06-135") time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) NewExplain = [] NewExplain = driver.find_elements_by_css_selector("#react-root > div > main > div > div > div.css-1xkojxp > form > div.css-ctpeu") try: assert "PublishedDate is invalid" in NewExplain[0].text finally: driver.back() time.sleep(2) # test case 14 # test post with published date entering characters # date format is invalid def test_EditPostWithDate_Char(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) inputList = driver.find_elements_by_tag_name("input") inputListDate = [] [inputListDate.append(input) for input in inputList if input.is_displayed()] inputListDate[4].send_keys(Keys.CONTROL, "a") inputListDate[4].send_keys(Keys.BACK_SPACE) inputListDate[4].send_keys("date") time.sleep(1) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_DOWN) driver.find_element_by_class_name("css-2960tt").send_keys(Keys.ARROW_UP) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "PublishedDate is invalid" in driver.find_element_by_css_selector("#react-root > div > main > div > div > div.css-1xkojxp > form > div.css-1nqppvz > div").text driver.back() time.sleep(2) # test case 15 # test post with content brief def test_EditPostWithContentBrief(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) iframeList = driver.find_elements_by_tag_name('iframe') iframeList[0].send_keys(Keys.ARROW_DOWN) iframeList[0].send_keys(Keys.ARROW_UP) iframeList[0].send_keys('content brief') time.sleep(1) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_css_selector("#react-root > div > main > div > div > div.css-1xkojxp > form > div.css-ctpeu").text driver.back() time.sleep(1) driver.find_element_by_link_text("edit OK").click() time.sleep(1) driver.switch_to.frame(0) assert "content brief" in driver.find_element_by_tag_name('body').text driver.back() time.sleep(2) # test case 16 # test posr with content extended def test_EditPostWithContentExtended(self): driver = self.driver driver.find_element_by_link_text("use selenium to edit a post").click() time.sleep(1) driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("edit OK") time.sleep(1) iframeList = driver.find_elements_by_tag_name('iframe') iframeList[1].send_keys(Keys.ARROW_DOWN) iframeList[1].send_keys(Keys.ARROW_UP) iframeList[1].send_keys('content extended') time.sleep(1) driver.find_element_by_class_name("css-2960tt").click() time.sleep(1) assert "Your changes have been saved successfully" in driver.find_element_by_css_selector("#react-root > div > main > div > div > div.css-1xkojxp > form > div.css-ctpeu").text driver.back() time.sleep(1) driver.find_element_by_link_text("edit OK").click() time.sleep(1) driver.switch_to.frame(1) assert "content extended" in driver.find_element_by_tag_name('body').text driver.back() time.sleep(2) def tearDown(self): driver = self.driver driver.find_element_by_xpath("//*[@id=\"react-root\"]/div/main/div/div/div[2]/div/div[1]/div/div/button").click() time.sleep(1) driver.find_element_by_class_name("css-12yx24t").click() time.sleep(1) driver.find_element_by_class_name("css-rd63ky").click() time.sleep(1) driver.find_element_by_class_name("css-t4884").click() time.sleep(2) driver.close() if __name__ == "__main__": unittest.main()

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Python

test/test_add_and_remove_contact_from_group.py

yulia-baturina/python_training

ef29b64e284ef2a2526092c9cb474b9bb489e1d0

[ "Apache-2.0" ]

null

test/test_add_and_remove_contact_from_group.py

yulia-baturina/python_training

ef29b64e284ef2a2526092c9cb474b9bb489e1d0

[ "Apache-2.0" ]

null

test/test_add_and_remove_contact_from_group.py

yulia-baturina/python_training

ef29b64e284ef2a2526092c9cb474b9bb489e1d0

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from model.contact import Contact from model.group import Group import random def test_add_random_contact_to_random_group(app, orm): if len(orm.get_group_list()) == 0: app.group.create(Group(name="new", header="header", footer="footer")) if len(orm.get_contact_list()) == 0: app.contact.create(Contact(firstname="first", lastname="last", nickname="nick", company="company", homePhone="+11111111111", email="mail@mail.com")) groups = orm.get_group_list() group = random.choice(groups) group_index = groups.index(group) contacts = orm.get_contact_list() contact = random.choice(contacts) old_contacts_in_group = orm.get_contacts_in_group(group) app.contact.assign_contact_by_id_to_group(contact.id, group.name) new_groups = orm.get_group_list() new_group = new_groups[group_index] new_contacts_in_group = orm.get_contacts_in_group(new_group) old_contacts_in_group.append(contact) assert sorted(old_contacts_in_group, key=Contact.id_or_max) == sorted(new_contacts_in_group, key=Contact.id_or_max) def test_add_and_remove_random_contact_from_random_group(app, orm): if len(orm.get_group_list()) == 0: app.group.create(Group(name="new", header="header", footer="footer")) if len(orm.get_contact_list()) == 0: app.contact.create(Contact(firstname="first", lastname="last", nickname="nick", company="company", homePhone="+11111111111", email="mail@mail.com")) groups = orm.get_group_list() group = random.choice(groups) group_index = groups.index(group) contacts = orm.get_contact_list() contact = random.choice(contacts) app.contact.assign_contact_by_id_to_group(contact.id, group.name) old_groups = orm.get_group_list() old_group = old_groups[group_index] old_contacts_in_group = orm.get_contacts_in_group(old_group) app.group.remove_contact_by_id_from_group(contact.id) new_groups = orm.get_group_list() new_group = new_groups[group_index] new_contacts_in_group = orm.get_contacts_in_group(new_group) old_contacts_in_group.remove(contact) assert sorted(old_contacts_in_group, key=Contact.id_or_max) == sorted(new_contacts_in_group, key=Contact.id_or_max)

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Python

market/products/migrations/0007_auto_20201218_1541.py

hbvj99/market-api

489c9433556002cb391b93cbd6486da739c2418a

[ "MIT" ]

1

2021-08-28T05:30:40.000Z

market/products/migrations/0007_auto_20201218_1541.py

hbvj99/market-api

489c9433556002cb391b93cbd6486da739c2418a

[ "MIT" ]

1

2022-01-14T08:57:19.000Z

2022-01-14T08:57:20.000Z

market/products/migrations/0007_auto_20201218_1541.py

hbvj99/market-api

489c9433556002cb391b93cbd6486da739c2418a

[ "MIT" ]

1

2022-01-11T10:14:27.000Z

# Generated by Django 3.1.1 on 2020-12-18 15:41 import cuser.fields from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('products', '0006_auto_20201116_1718'), ] operations = [ migrations.AddField( model_name='category', name='created_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_category_created', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='category', name='deleted_at', field=models.DateTimeField(editable=False, null=True), ), migrations.AddField( model_name='category', name='updated_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_category_modified', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='comment', name='created_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_comment_created', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='comment', name='deleted_at', field=models.DateTimeField(editable=False, null=True), ), migrations.AddField( model_name='comment', name='updated_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_comment_modified', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='product', name='created_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_product_created', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='product', name='deleted_at', field=models.DateTimeField(editable=False, null=True), ), migrations.AddField( model_name='product', name='updated_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_product_modified', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='productvotes', name='created_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_productvotes_created', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='productvotes', name='deleted_at', field=models.DateTimeField(editable=False, null=True), ), migrations.AddField( model_name='productvotes', name='updated_by', field=cuser.fields.CurrentUserField(editable=False, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='products_productvotes_modified', to=settings.AUTH_USER_MODEL), ), ]

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0.012912

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0

null

0

1

0

1

0

null

0

8

d426fbf42f1ca4bcb5ff310655613f040c1cdc37

232

py

Python

swyft/utils/__init__.py

adam-coogan/swyft

c54bdd9f77ddf02fda857e26640df012cbe545fc

[ "MIT" ]

null

swyft/utils/__init__.py

adam-coogan/swyft

c54bdd9f77ddf02fda857e26640df012cbe545fc

[ "MIT" ]

null

swyft/utils/__init__.py

adam-coogan/swyft

c54bdd9f77ddf02fda857e26640df012cbe545fc

[ "MIT" ]

null

from swyft.utils.array import * from swyft.utils.device import * from swyft.utils.mutils import * from swyft.utils.parameters import * from swyft.utils.plot import * from swyft.utils.utils import * from swyft.utils.wmutils import *

29

36

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35

232

5.228571

0.285714

0.344262

0.535519

0.655738

0

0.12069

232

7

37

33.142857

0.897059

0

1

0

true

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1

0

null

1

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1

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null

0

1

0

1

0

1

0

7

2e0ff73729ac809e7efd19f8d2b3c0ed24d733e6

123

py

Python

code/exercises/04_ControlFlow/ex_04_02_for_before.py

chiachang100/LearnToCodeWithPython

fe16115cb3be612d5abd8ffdbd6a14a37d6b4d52

[ "Apache-2.0" ]

null

code/exercises/04_ControlFlow/ex_04_02_for_before.py

chiachang100/LearnToCodeWithPython

fe16115cb3be612d5abd8ffdbd6a14a37d6b4d52

[ "Apache-2.0" ]

null

code/exercises/04_ControlFlow/ex_04_02_for_before.py

chiachang100/LearnToCodeWithPython

fe16115cb3be612d5abd8ffdbd6a14a37d6b4d52

[ "Apache-2.0" ]

null

#!/usr/bin/python # Filename: ex_for_before.py print('Hello') print('Hello') print('Hello') print('Hello') print('Hello')

13.666667

28

0.691057

18

123

4.611111

0.555556

0.60241

0.722892

0.963855

0.60241

0

0.081301

123

8

29

15.375

0.734513

0.349594

0

1

0

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0

1

0

true

0

1

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null

1

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1

0

null

0

1

0

1

0

8

2e3dbe78d095cdb07e2d3eff292574e4df1c6d51

33,787

py

Python

lib/installed_clients/kb_uploadmethodsClient.py

abbyjerger/Snekmer

46640d8516289401258a83125483d502179f68d3

[ "MIT" ]

null

lib/installed_clients/kb_uploadmethodsClient.py

abbyjerger/Snekmer

46640d8516289401258a83125483d502179f68d3

[ "MIT" ]

null

lib/installed_clients/kb_uploadmethodsClient.py

abbyjerger/Snekmer

46640d8516289401258a83125483d502179f68d3

[ "MIT" ]

null

# -*- coding: utf-8 -*- ############################################################ # # Autogenerated by the KBase type compiler - # any changes made here will be overwritten # ############################################################ from __future__ import print_function # the following is a hack to get the baseclient to import whether we're in a # package or not. This makes pep8 unhappy hence the annotations. try: # baseclient and this client are in a package from .baseclient import BaseClient as _BaseClient # @UnusedImport except ImportError: # no they aren't from baseclient import BaseClient as _BaseClient # @Reimport class kb_uploadmethods(object): def __init__( self, url=None, timeout=30 * 60, user_id=None, password=None, token=None, ignore_authrc=False, trust_all_ssl_certificates=False, auth_svc='https://ci.kbase.us/services/auth/api/legacy/KBase/Sessions/Login', service_ver='release', async_job_check_time_ms=100, async_job_check_time_scale_percent=150, async_job_check_max_time_ms=300000): if url is None: raise ValueError('A url is required') self._service_ver = service_ver self._client = _BaseClient( url, timeout=timeout, user_id=user_id, password=password, token=token, ignore_authrc=ignore_authrc, trust_all_ssl_certificates=trust_all_ssl_certificates, auth_svc=auth_svc, async_job_check_time_ms=async_job_check_time_ms, async_job_check_time_scale_percent=async_job_check_time_scale_percent, async_job_check_max_time_ms=async_job_check_max_time_ms) def upload_fastq_file(self, params, context=None): """ :param params: instance of type "UploadMethodParams" (sequencing_tech: sequencing technology name: output reads file name workspace_name: workspace name/ID of the object For files in user's staging area: fwd_staging_file_name: single-end fastq file name or forward/left paired-end fastq file name from user's staging area rev_staging_file_name: reverse/right paired-end fastq file name user's staging area For files from web: download_type: download type for web source fastq file ('Direct Download', 'FTP', 'DropBox', 'Google Drive') fwd_file_url: single-end fastq file URL or forward/left paired-end fastq file URL rev_file_url: reverse/right paired-end fastq file URL urls_to_add: used for parameter-groups. dict of {fwd_file_url, rev_file_url, name, single_genome, interleaved, insert_size_mean and read_orientation_outward} Optional Params: single_genome: whether the reads are from a single genome or a metagenome. interleaved: whether reads is interleaved insert_size_mean: mean (average) insert length insert_size_std_dev: standard deviation of insert lengths read_orientation_outward: whether reads in a pair point outward) -> structure: parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "fwd_staging_file_name" of type "fwd_staging_file_name" (input and output file path/url), parameter "rev_staging_file_name" of type "rev_staging_file_name", parameter "download_type" of type "download_type", parameter "fwd_file_url" of type "fwd_file_url", parameter "rev_file_url" of type "rev_file_url", parameter "sequencing_tech" of type "sequencing_tech", parameter "name" of type "name", parameter "urls_to_add" of type "urls_to_add" -> structure: parameter "fwd_file_url" of type "fwd_file_url", parameter "rev_file_url" of type "rev_file_url", parameter "name" of type "name", parameter "single_genome" of type "single_genome", parameter "interleaved" of type "interleaved", parameter "insert_size_mean" of type "insert_size_mean", parameter "insert_size_std_dev" of type "insert_size_std_dev", parameter "read_orientation_outward" of type "read_orientation_outward", parameter "single_genome" of type "single_genome", parameter "interleaved" of type "interleaved", parameter "insert_size_mean" of type "insert_size_mean", parameter "insert_size_std_dev" of type "insert_size_std_dev", parameter "read_orientation_outward" of type "read_orientation_outward" :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.upload_fastq_file', [params], self._service_ver, context) def upload_fasta_gff_file(self, params, context=None): """ :param params: instance of type "UploadFastaGFFMethodParams" (Required: genome_name: output genome object name workspace_name: workspace name/ID of the object For staging area: fasta_file: fasta file containing assembled contigs/chromosomes gff_file: gff file containing predicted gene models and corresponding features Optional params: scientific_name - the scientific name of the genome. taxon_id - the numeric ID of the NCBI taxon to which this genome belongs. If defined, will try to link the Genome to the specified taxonomy id in lieu of performing the lookup during upload source: Source Of The GFF File. Default to 'User' taxon_wsname - where the reference taxons are. Default to 'ReferenceTaxons' release: Release Or Version Of The Source Data genetic_code: Genetic Code For The Organism type: 'Reference', 'User upload', 'Representative') -> structure: parameter "fasta_file" of String, parameter "gff_file" of String, parameter "genome_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "genome_type" of String, parameter "scientific_name" of String, parameter "source" of String, parameter "taxon_wsname" of String, parameter "taxon_id" of String, parameter "release" of String, parameter "genetic_code" of Long, parameter "type" of String, parameter "generate_missing_genes" of String :returns: instance of type "UploadFastaGFFMethodResult" -> structure: parameter "genome_ref" of String, parameter "genome_info" of String, parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.upload_fasta_gff_file', [params], self._service_ver, context) def upload_metagenome_fasta_gff_file(self, params, context=None): """ :param params: instance of type "UploadMetagenomeFastaGFFMethodParams" (Required: genome_name: output metagenome object name workspace_name: workspace name/ID of the object For staging area: fasta_file: fasta file containing assembled contigs/chromosomes gff_file: gff file containing predicted gene models and corresponding features Optional params: source: Source Of The GFF File. Default to 'User' taxon_wsname - where the reference taxons are. Default to 'ReferenceTaxons' taxon_id - if defined, will try to link the Genome to the specified taxonomy id in lieu of performing the lookup during upload release: Release Or Version Of The Source Data genetic_code: Genetic Code For The Organism type: 'Reference', 'User upload', 'Representative') -> structure: parameter "fasta_file" of String, parameter "gff_file" of String, parameter "genome_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "source" of String, parameter "taxon_wsname" of String, parameter "taxon_id" of String, parameter "release" of String, parameter "genetic_code" of Long, parameter "type" of String, parameter "generate_missing_genes" of String :returns: instance of type "UploadMetagenomeFastaGFFMethodResult" -> structure: parameter "metagenome_ref" of String, parameter "metagenome_info" of String, parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.upload_metagenome_fasta_gff_file', [params], self._service_ver, context) def batch_import_genomes_from_staging(self, params, context=None): """ :param params: instance of type "BatchGenomeImporterParams" -> structure: parameter "staging_subdir" of String, parameter "genome_set_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "genome_type" of String, parameter "source" of String, parameter "taxon_wsname" of String, parameter "taxon_id" of String, parameter "release" of String, parameter "genetic_code" of Long, parameter "generate_missing_genes" of String :returns: instance of type "BatchImporterResult" -> structure: parameter "set_ref" of String, parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.batch_import_genomes_from_staging', [params], self._service_ver, context) def batch_import_assemblies_from_staging(self, params, context=None): """ :param params: instance of type "BatchAssemblyImporterParams" -> structure: parameter "staging_subdir" of String, parameter "assembly_set_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "min_contig_length" of Long, parameter "type" of String :returns: instance of type "BatchImporterResult" -> structure: parameter "set_ref" of String, parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.batch_import_assemblies_from_staging', [params], self._service_ver, context) def unpack_staging_file(self, params, context=None): """ Unpack a staging area file :param params: instance of type "UnpackStagingFileParams" (Input parameters for the "unpack_staging_file" function. Required parameters: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name workspace_name: workspace name/ID of the object) -> structure: parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "staging_file_subdir_path" of String :returns: instance of type "UnpackStagingFileOutput" (Results from the unpack_staging_file function. unpacked_file_path: unpacked file path(s) in staging area) -> structure: parameter "unpacked_file_path" of String """ return self._client.run_job('kb_uploadmethods.unpack_staging_file', [params], self._service_ver, context) def unpack_web_file(self, params, context=None): """ Download and unpack a web file to staging area :param params: instance of type "UnpackWebFileParams" (Input parameters for the "unpack_web_file" function. Required parameters: workspace_name: workspace name/ID of the object file_url: file URL download_type: one of ['Direct Download', 'FTP', 'DropBox', 'Google Drive'] Optional: urls_to_add_web_unpack: used for parameter-groups. dict of {file_url}) -> structure: parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "file_url" of String, parameter "download_type" of String, parameter "urls_to_add_web_unpack" of type "urls_to_add_web_unpack" -> structure: parameter "file_url" of String :returns: instance of type "UnpackWebFileOutput" (Results from the unpack_web_file function. unpacked_file_path: unpacked file path(s) in staging area) -> structure: parameter "unpacked_file_path" of String """ return self._client.run_job('kb_uploadmethods.unpack_web_file', [params], self._service_ver, context) def import_genbank_from_staging(self, params, context=None): """ :param params: instance of type "GenbankToGenomeParams" (import_genbank_from_staging: wrapper method for GenomeFileUtil.genbank_to_genome required params: staging_file_subdir_path - subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name genome_name - becomes the name of the object workspace_name - the name of the workspace it gets saved to. source - Source of the file typically something like RefSeq or Ensembl optional params: scientific_name - the scientific name of the genome. taxon_id - the numeric ID of the NCBI taxon to which this genome belongs. If defined, will try to link the Genome to the specified taxonomy id in lieu of performing the lookup during upload release - Release or version number of the data per example Ensembl has numbered releases of all their data: Release 31 generate_ids_if_needed - If field used for feature id is not there, generate ids (default behavior is raising an exception) generate_missing_genes - Generate gene feature for CDSs that do not have a parent in file genetic_code - Genetic code of organism. Overwrites determined GC from taxon object type - Reference, Representative or User upload) -> structure: parameter "staging_file_subdir_path" of String, parameter "genome_name" of String, parameter "workspace_name" of String, parameter "source" of String, parameter "genome_type" of String, parameter "release" of String, parameter "genetic_code" of Long, parameter "type" of String, parameter "scientific_name" of String, parameter "taxon_id" of String, parameter "generate_ids_if_needed" of String, parameter "generate_missing_genes" of String :returns: instance of type "GenomeSaveResult" -> structure: parameter "genome_ref" of String """ return self._client.run_job('kb_uploadmethods.import_genbank_from_staging', [params], self._service_ver, context) def import_sra_from_staging(self, params, context=None): """ :param params: instance of type "SRAToReadsParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name sequencing_tech: sequencing technology name: output reads file name workspace_name: workspace name/ID of the object Optional Params: single_genome: whether the reads are from a single genome or a metagenome. insert_size_mean: mean (average) insert length insert_size_std_dev: standard deviation of insert lengths read_orientation_outward: whether reads in a pair point outward) -> structure: parameter "staging_file_subdir_path" of String, parameter "sequencing_tech" of type "sequencing_tech", parameter "name" of type "name", parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "single_genome" of type "single_genome", parameter "insert_size_mean" of type "insert_size_mean", parameter "insert_size_std_dev" of type "insert_size_std_dev", parameter "read_orientation_outward" of type "read_orientation_outward" :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_sra_from_staging', [params], self._service_ver, context) def import_sra_from_web(self, params, context=None): """ :param params: instance of type "WebSRAToReadsParams" -> structure: parameter "download_type" of String, parameter "sra_urls_to_add" of type "sra_urls_to_add" (download_type: download type for web source fastq file ('Direct Download', 'FTP', 'DropBox', 'Google Drive') sra_urls_to_add: dict of SRA file URLs required params: file_url: SRA file URL sequencing_tech: sequencing technology name: output reads file name workspace_name: workspace name/ID of the object Optional Params: single_genome: whether the reads are from a single genome or a metagenome. insert_size_mean: mean (average) insert length insert_size_std_dev: standard deviation of insert lengths read_orientation_outward: whether reads in a pair point outward) -> structure: parameter "file_url" of String, parameter "sequencing_tech" of type "sequencing_tech", parameter "name" of type "name", parameter "single_genome" of type "single_genome", parameter "insert_size_mean" of type "insert_size_mean", parameter "insert_size_std_dev" of type "insert_size_std_dev", parameter "read_orientation_outward" of type "read_orientation_outward", parameter "workspace_name" of type "workspace_name" (workspace name of the object) :returns: instance of type "WebSRAToReadsResult" -> structure: parameter "obj_refs" of list of String, parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_sra_from_web', [params], self._service_ver, context) def import_fasta_as_assembly_from_staging(self, params, context=None): """ :param params: instance of type "FastaToAssemblyParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name assembly_name: output Assembly file name workspace_name: workspace name/ID of the object) -> structure: parameter "staging_file_subdir_path" of String, parameter "assembly_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "min_contig_length" of Long, parameter "type" of String :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_fasta_as_assembly_from_staging', [params], self._service_ver, context) def import_tsv_as_media_from_staging(self, params, context=None): """ :param params: instance of type "FileToMediaParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name media_name: output Media file name workspace_name: workspace name/ID of the object) -> structure: parameter "staging_file_subdir_path" of String, parameter "media_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object) :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_tsv_as_media_from_staging', [params], self._service_ver, context) def import_excel_as_media_from_staging(self, params, context=None): """ :param params: instance of type "FileToMediaParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name media_name: output Media file name workspace_name: workspace name/ID of the object) -> structure: parameter "staging_file_subdir_path" of String, parameter "media_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object) :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_excel_as_media_from_staging', [params], self._service_ver, context) def import_tsv_or_excel_as_media_from_staging(self, params, context=None): """ :param params: instance of type "FileToMediaParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name media_name: output Media file name workspace_name: workspace name/ID of the object) -> structure: parameter "staging_file_subdir_path" of String, parameter "media_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object) :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_tsv_or_excel_as_media_from_staging', [params], self._service_ver, context) def import_file_as_fba_model_from_staging(self, params, context=None): """ :param params: instance of type "FileToFBAModelParams" (required params: model_file: subdirectory file path for model file e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name compounds_file: same as above for compound (only used for tsv) file_type: one of "tsv", "excel", "sbml" genome: the associated species genome biomasses: one or more biomass reactions in model model_name: output FBAModel object name workspace_name: workspace name/ID of the object) -> structure: parameter "model_file" of String, parameter "compounds_file" of String, parameter "file_type" of String, parameter "genome" of String, parameter "biomass" of String, parameter "model_name" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object) :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_file_as_fba_model_from_staging', [params], self._service_ver, context) def import_tsv_as_expression_matrix_from_staging(self, params, context=None): """ :param params: instance of type "FileToMatrixParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name matrix_name: output Expressin Matirx file name workspace_name: workspace name/ID of the object genome_ref: optional reference to a Genome object that will be used for mapping feature IDs to fill_missing_values: optional flag for filling in missing values in matrix (default value is false) data_type: optional filed, value is one of 'untransformed', 'log2_level', 'log10_level', 'log2_ratio', 'log10_ratio' or 'unknown' (last one is default value) data_scale: optional parameter (default value is '1.0')) -> structure: parameter "staging_file_subdir_path" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "matrix_name" of String, parameter "genome_ref" of String, parameter "fill_missing_values" of type "boolean" (Indicates true or false values, false = 0, true = 1 @range [0,1]), parameter "data_type" of String, parameter "data_scale" of String :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_tsv_as_expression_matrix_from_staging', [params], self._service_ver, context) def import_reads_from_staging(self, params, context=None): """ :param params: instance of type "UploadReadsParams" (sequencing_tech: sequencing technology name: output reads file name workspace_name: workspace name/ID of the object import_type: either FASTQ or SRA For files in user's staging area: fastq_fwd_or_sra_staging_file_name: single-end fastq file name Or forward/left paired-end fastq file name from user's staging area Or SRA staging file fastq_rev_staging_file_name: reverse/right paired-end fastq file name user's staging area e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name Optional Params: single_genome: whether the reads are from a single genome or a metagenome. interleaved: whether reads is interleaved insert_size_mean: mean (average) insert length insert_size_std_dev: standard deviation of insert lengths read_orientation_outward: whether reads in a pair point outward) -> structure: parameter "import_type" of String, parameter "fastq_fwd_staging_file_name" of String, parameter "fastq_rev_staging_file_name" of String, parameter "sra_staging_file_name" of String, parameter "sequencing_tech" of type "sequencing_tech", parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "name" of String, parameter "single_genome" of type "single_genome", parameter "interleaved" of type "interleaved", parameter "insert_size_mean" of type "insert_size_mean", parameter "insert_size_std_dev" of type "insert_size_std_dev", parameter "read_orientation_outward" of type "read_orientation_outward" :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_reads_from_staging', [params], self._service_ver, context) def import_tsv_as_phenotype_set_from_staging(self, params, context=None): """ :param params: instance of type "FileToPhenotypeSetParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name phenotype_set_name: output PhenotypeSet object name workspace_name: workspace name/ID of the object optional: genome: Genome object that contains features referenced by the Phenotype Set) -> structure: parameter "staging_file_subdir_path" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "phenotype_set_name" of String, parameter "genome" of type "obj_ref" :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_tsv_as_phenotype_set_from_staging', [params], self._service_ver, context) def import_attribute_mapping_from_staging(self, params, context=None): """ :param params: instance of type "FileToConditionSetParams" (required params: staging_file_subdir_path: subdirectory file path e.g. for file: /data/bulk/user_name/file_name staging_file_subdir_path is file_name for file: /data/bulk/user_name/subdir_1/subdir_2/file_name staging_file_subdir_path is subdir_1/subdir_2/file_name attribute_mapping_name: output ConditionSet object name workspace_id: workspace name/ID of the object) -> structure: parameter "staging_file_subdir_path" of String, parameter "workspace_name" of type "workspace_name" (workspace name of the object), parameter "attribute_mapping_name" of String :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_attribute_mapping_from_staging', [params], self._service_ver, context) def import_eschermap_from_staging(self, params, context=None): """ :param params: instance of type "EscherMapParams" -> structure: parameter "staging_file_subdir_path" of String, parameter "workspace_id" of Long, parameter "escher_map_name" of String :returns: instance of type "UploadMethodResult" -> structure: parameter "obj_ref" of type "obj_ref", parameter "report_name" of type "report_name", parameter "report_ref" of type "report_ref" """ return self._client.run_job('kb_uploadmethods.import_eschermap_from_staging', [params], self._service_ver, context) def status(self, context=None): return self._client.run_job('kb_uploadmethods.status', [], self._service_ver, context)

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2e841bb4ca470bac5c65419e1b8fc0661b9abc21

112

py

Python

edge_impulse_linux/__init__.py

ShawnHymel/linux-sdk-python

2619ec54729a5cfa4ce217aef371e15ad2cb5fbb

[ "Apache-2.0" ]

19

2021-04-11T13:40:50.000Z

2022-03-29T14:13:57.000Z

edge_impulse_linux/__init__.py

ShawnHymel/linux-sdk-python

2619ec54729a5cfa4ce217aef371e15ad2cb5fbb

[ "Apache-2.0" ]

8

2021-04-18T16:39:11.000Z

2022-01-06T05:12:42.000Z

edge_impulse_linux/__init__.py

ShawnHymel/linux-sdk-python

2619ec54729a5cfa4ce217aef371e15ad2cb5fbb

[ "Apache-2.0" ]

6

2021-04-12T17:34:04.000Z

2022-01-08T16:50:10.000Z

from edge_impulse_linux import runner from edge_impulse_linux import audio from edge_impulse_linux import image

28

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9

cf1d7f7cd9e5a961fffc6c088b772f608f6acb6d

17,089

py

Python

employer_engagement/training/levy_train_sql_functions.py

SkillsFundingAgency/das-data-management-ai

8b517a62f9d78b2af363634c5420e92a9faac03d

[ "MIT" ]

null

employer_engagement/training/levy_train_sql_functions.py

SkillsFundingAgency/das-data-management-ai

8b517a62f9d78b2af363634c5420e92a9faac03d

[ "MIT" ]

null

employer_engagement/training/levy_train_sql_functions.py

SkillsFundingAgency/das-data-management-ai

8b517a62f9d78b2af363634c5420e92a9faac03d

[ "MIT" ]

null

from azureml.core import Workspace from azureml.core.compute import ComputeTarget from azureml.pipeline.steps import PythonScriptStep from azureml.pipeline.core import Pipeline, PipelineData, StepSequence, PublishedPipeline from azureml.core.runconfig import RunConfiguration from azureml.pipeline.core import PipelineEndpoint import azureml.core import os from azureml.data.datapath import DataPath from azureml.core import Workspace, Datastore, Dataset, ComputeTarget, Experiment, ScriptRunConfig, Environment, Model from azureml.core.run import Run # Set up config of workspace and datastore aml_workspace = Run.get_context().experiment.workspace datastore = Datastore.get(aml_workspace, datastore_name='datamgmtdb') def levy_train_01_accounts(top_x: str) : query_levy_accounts = DataPath(datastore, "select A1, A2, A3, early_adopter from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter from PDS_AI.PT_A \ where a2 between '2017-01-01' and '2018-01-01' and a1=1 \ order by rand()) a \ union \ select A1, A2, A3, early_adopter from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A where a2 between '2017-01-01' and '2018-01-01' and a1=0 order by rand()) b \ union \ select A1, A2, A3, early_adopter from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2018-01-01' and '2019-01-01' and a1=1 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2018-01-01' and '2019-01-01' and a1=0 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2019-01-01' and '2020-01-01' and a1=1 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2019-01-01' and '2020-01-01' and a1=0 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2020-01-01' and '2021-01-01' and a1=1 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2020-01-01' and '2021-01-01' and a1=0 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2021-01-01' and '2022-01-01' and a1=1 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2021-01-01' and '2022-01-01' and a1=0 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2022-01-01' and '2023-01-01' and a1=1 \ order by rand()) c \ union \ select A1, A2, A3, early_adopter \ from \ (select top {} A1, A2, A3, CASE WHEN CAST(A2 AS DATE)<cast('2017-07-01' as date) THEN 1 ELSE 0 END AS early_adopter \ from PDS_AI.PT_A \ where a2 between '2022-01-01' and '2023-01-01' and a1=0 \ order by rand()) c".format(top_x,top_x,top_x,top_x,top_x,top_x,top_x,top_x,top_x,top_x,top_x,top_x)) tabular_levy_accounts = Dataset.Tabular.from_sql_query(query_levy_accounts, query_timeout=3600) levy_model_accounts = tabular_levy_accounts.to_pandas_dataframe() return levy_model_accounts def levy_train_02_levy_model_set_2018_2019_part1(sql_account_list: str) : query_2018_2019_part1 = DataPath(datastore, "SELECT A3 \ , '2019' as cohort \ , total_commitments \ , occupation_1 \ , occupation_2 \ , occupation_3 \ , occupation_7 \ , occupation_13 \ , occupation_14 \ , occupation_15 \ , occupation_17 \ , occupation_20 \ , occupation_22 \ , occupation_24 \ , occupation_null \ , prev_12m_new_commitments \ , prev_12m_new_levy_transfers \ , A7 as levy_sending_company \ FROM \ (SELECT A3, CONCAT(YEAR(A2),'-',month(A2)) as yearmon_created, A1 as levy_split, A2, A7 \ FROM PDS_AI.PT_A \ WHERE A2<'2018-04-01' AND A1=1 AND A3 in ({0}) \ ) A \ LEFT JOIN \ (SELECT B10, count(*) AS total_commitments \ FROM PDS_AI.PT_B \ WHERE cast(B2 as date) >= '2018-04-01' AND cast(B2 as date) < '2019-04-01' AND B10 in ({0}) \ GROUP BY B10 \ ) B \ ON A.A3=B.B10 \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS prev_12m_new_commitments \ , SUM(CASE WHEN B12=1 THEN 1 ELSE 0 END) AS prev_12m_new_levy_transfers \ , CAST(SUM(CASE WHEN B6 = '1' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_1 \ , CAST(SUM(CASE WHEN B6 = '2' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_2 \ , CAST(SUM(CASE WHEN B6 = '3' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_3 \ , CAST(SUM(CASE WHEN B6 = '7' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_7 \ , CAST(SUM(CASE WHEN B6 = '13' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_13 \ , CAST(SUM(CASE WHEN B6 = '14' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_14 \ , CAST(SUM(CASE WHEN B6 = '15' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_15 \ , CAST(SUM(CASE WHEN B6 = '17' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_17 \ , CAST(SUM(CASE WHEN B6 = '20' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_20 \ , CAST(SUM(CASE WHEN B6 = '22' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_22 \ , CAST(SUM(CASE WHEN B6 = '24' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_24 \ , CAST(SUM(CASE WHEN B6 = NULL THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_null \ FROM PDS_AI.PT_B \ WHERE cast(B2 as date) >= '2017-04-01' AND cast(B2 as date) < '2018-04-01' AND B10 in ({0}) \ GROUP BY B10 \ ) C \ ON A.A3=C.B10".format(sql_account_list)) tabular_2018_2019_part1 = Dataset.Tabular.from_sql_query(query_2018_2019_part1, query_timeout=3600) levy_model_set_2018_2019_part1 = tabular_2018_2019_part1.to_pandas_dataframe() return levy_model_set_2018_2019_part1 def levy_train_03_levy_model_set_2018_2019_part2(sql_account_list: str) : query_2018_2019_part2 = DataPath(datastore, "SELECT A3 \ , commitments_ending_12m \ , current_live_commitments \ FROM \ (SELECT A3, CONCAT(YEAR(A2),'-',month(A2)) as yearmon_created, A1 as levy_split, A2, A7 \ FROM PDS_AI.PT_A \ WHERE A2<'2018-04-01' and A1=1 AND A3 in ({0}) \ ) A \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS commitments_ending_12m \ FROM PDS_AI.PT_B \ WHERE CAST(B17 AS DATE) < '2019-04-01' AND CAST(B17 AS DATE)>='2018-04-01' \ AND (CAST(B20 AS DATE) >= '2018-04-01' OR B20 IS NULL) \ AND (CAST(B16 AS DATE) >= '2018-04-01' OR B16 IS NULL) \ AND B10 in ({0}) \ GROUP BY B10 \ ) D \ ON A.A3=D.B10 \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS current_live_commitments \ FROM PDS_AI.PT_B \ WHERE cast(B2 AS DATE) < '2018-04-01' AND \ (B20 IS NULL OR CAST(B20 AS DATE)>='2018-04-01') AND \ (B16 IS NULL OR CAST(B16 AS DATE)>='2018-04-01') \ AND B10 in ({0}) \ GROUP BY B10 \ ) E \ ON A.A3=E.B10".format(sql_account_list)) tabular_2018_2019_part2 = Dataset.Tabular.from_sql_query(query_2018_2019_part2, query_timeout=3600) levy_model_set_2018_2019_part2 = tabular_2018_2019_part2.to_pandas_dataframe() return levy_model_set_2018_2019_part2 def levy_train_04_levy_model_set_2019_2020_part1(sql_account_list: str) : query_2019_2020_part1 = DataPath(datastore, "SELECT A3 \ , '2020' as cohort \ , total_commitments \ , occupation_1 \ , occupation_2 \ , occupation_3 \ , occupation_7 \ , occupation_13 \ , occupation_14 \ , occupation_15 \ , occupation_17 \ , occupation_20 \ , occupation_22 \ , occupation_24 \ , occupation_null \ , prev_12m_new_commitments \ , prev_12m_new_levy_transfers \ , A7 as levy_sending_company \ FROM \ (SELECT A3, CONCAT(YEAR(A2),'-',month(A2)) as yearmon_created, A1 as levy_split, A2, A7 \ FROM PDS_AI.PT_A \ WHERE A2<'2019-04-01' AND A1=1 AND A3 in ({0}) \ ) A \ LEFT JOIN \ (SELECT B10, count(*) AS total_commitments \ FROM PDS_AI.PT_B \ WHERE cast(B2 as date) >= '2019-04-01' AND cast(B2 as date) < '2020-04-01' AND B10 in ({0}) \ GROUP BY B10 \ ) B \ ON A.A3=B.B10 \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS prev_12m_new_commitments \ , SUM(CASE WHEN B12=1 THEN 1 ELSE 0 END) AS prev_12m_new_levy_transfers \ , CAST(SUM(CASE WHEN B6 = '1' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_1 \ , CAST(SUM(CASE WHEN B6 = '2' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_2 \ , CAST(SUM(CASE WHEN B6 = '3' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_3 \ , CAST(SUM(CASE WHEN B6 = '7' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_7 \ , CAST(SUM(CASE WHEN B6 = '13' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_13 \ , CAST(SUM(CASE WHEN B6 = '14' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_14 \ , CAST(SUM(CASE WHEN B6 = '15' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_15 \ , CAST(SUM(CASE WHEN B6 = '17' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_17 \ , CAST(SUM(CASE WHEN B6 = '20' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_20 \ , CAST(SUM(CASE WHEN B6 = '22' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_22 \ , CAST(SUM(CASE WHEN B6 = '24' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_24 \ , CAST(SUM(CASE WHEN B6 = NULL THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_null \ FROM PDS_AI.PT_B \ WHERE cast(B2 as date) >= '2018-04-01' AND cast(B2 as date) < '2019-04-01' AND B10 in ({0}) \ GROUP BY B10 \ ) C \ ON A.A3=C.B10".format(sql_account_list)) tabular_2019_2020_part1 = Dataset.Tabular.from_sql_query(query_2019_2020_part1, query_timeout=3600) levy_model_set_2019_2020_part1 = tabular_2019_2020_part1.to_pandas_dataframe() return levy_model_set_2019_2020_part1 def levy_train_05_levy_model_set_2019_2020_part2(sql_account_list: str) : query_2019_2020_part2 = DataPath(datastore, "SELECT A3 \ , commitments_ending_12m \ , current_live_commitments \ FROM \ (SELECT A3, CONCAT(YEAR(A2),'-',month(A2)) as yearmon_created, A1 as levy_split, A2, A7 \ FROM PDS_AI.PT_A \ WHERE A2<'2019-04-01' AND A1=1 AND A3 in ({0}) \ ) A \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS commitments_ending_12m \ FROM PDS_AI.PT_B \ WHERE CAST(B17 AS DATE) < '2020-04-01' AND CAST(B17 AS DATE)>='2019-04-01' \ AND (CAST(B20 AS DATE) >= '2019-04-01' OR B20 IS NULL) \ AND (CAST(B16 AS DATE) >= '2019-04-01' OR B16 IS NULL) \ AND B10 in ({0}) \ GROUP BY B10 \ ) D \ ON A.A3=D.B10 \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS current_live_commitments \ FROM PDS_AI.PT_B \ WHERE cast(B2 AS DATE) < '2019-04-01' AND \ (B20 IS NULL OR CAST(B20 AS DATE)>='2019-04-01') AND \ (B16 IS NULL OR CAST(B16 AS DATE)>='2019-04-01') \ AND B10 in ({0}) \ GROUP BY B10 \ ) E \ ON A.A3=E.B10".format(sql_account_list)) tabular_2019_2020_part2 = Dataset.Tabular.from_sql_query(query_2019_2020_part2, query_timeout=3600) levy_model_set_2019_2020_part2 = tabular_2019_2020_part2.to_pandas_dataframe() return levy_model_set_2019_2020_part2 def levy_train_06_levy_model_set_2022_part1(sql_account_list: str) : query_2022_part1 = DataPath(datastore, "SELECT A3 \ , '2022' as cohort \ , total_commitments \ , occupation_1 \ , occupation_2 \ , occupation_3 \ , occupation_7 \ , occupation_13 \ , occupation_14 \ , occupation_15 \ , occupation_17 \ , occupation_20 \ , occupation_22 \ , occupation_24 \ , occupation_null \ , prev_12m_new_commitments \ , prev_12m_new_levy_transfers \ , A7 as levy_sending_company \ FROM \ (SELECT A3, CONCAT(YEAR(A2),'-',month(A2)) as yearmon_created, A1 as levy_split, A2, A7 \ FROM PDS_AI.PT_A \ WHERE A2<'2021-01-01' AND A1=1 AND A3 in ({0}) \ ) A \ LEFT JOIN \ (SELECT B10, count(*) AS total_commitments \ FROM PDS_AI.PT_B \ WHERE cast(B2 as date) >= '2021-01-01' AND cast(B2 as date) < '2022-01-01' AND B10 in ({0}) \ GROUP BY B10 \ ) B \ ON A.A3=B.B10 \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS prev_12m_new_commitments \ , SUM(CASE WHEN B12=1 THEN 1 ELSE 0 END) AS prev_12m_new_levy_transfers \ , CAST(SUM(CASE WHEN B6 = '1' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_1 \ , CAST(SUM(CASE WHEN B6 = '2' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_2 \ , CAST(SUM(CASE WHEN B6 = '3' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_3 \ , CAST(SUM(CASE WHEN B6 = '7' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_7 \ , CAST(SUM(CASE WHEN B6 = '13' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_13 \ , CAST(SUM(CASE WHEN B6 = '14' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_14 \ , CAST(SUM(CASE WHEN B6 = '15' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_15 \ , CAST(SUM(CASE WHEN B6 = '17' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_17 \ , CAST(SUM(CASE WHEN B6 = '20' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_20 \ , CAST(SUM(CASE WHEN B6 = '22' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_22 \ , CAST(SUM(CASE WHEN B6 = '24' THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_24 \ , CAST(SUM(CASE WHEN B6 = NULL THEN 1.000 ELSE 0 END) / COUNT(*) AS DECIMAL(10,3)) AS occupation_null \ FROM PDS_AI.PT_B \ WHERE cast(B2 as date) >= '2020-01-01' AND cast(B2 as date) < '2021-01-01' AND B10 in ({0}) \ GROUP BY B10 \ ) C \ ON A.A3=C.B10".format(sql_account_list)) tabular_2022_part1 = Dataset.Tabular.from_sql_query(query_2022_part1, query_timeout=3600) levy_model_set_2022_part1 = tabular_2022_part1.to_pandas_dataframe() return levy_model_set_2022_part1 def levy_train_07_levy_model_set_2022_part2(sql_account_list: str) : query_2022_part2 = DataPath(datastore, "SELECT A3 \ , commitments_ending_12m \ , current_live_commitments \ FROM \ (SELECT A3, CONCAT(YEAR(A2),'-',month(A2)) as yearmon_created, A1 as levy_split, A2, A7 \ FROM PDS_AI.PT_A \ WHERE A2<'2021-01-01' AND A1=1 AND A3 in ({0}) \ ) A \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS commitments_ending_12m \ FROM PDS_AI.PT_B \ WHERE cast(B17 as date) < '2022-01-01' AND CAST(B17 AS DATE)>='2021-01-01' \ AND (CAST(B20 AS DATE) >= '2021-01-01' OR B20 IS NULL) \ AND (CAST(B16 AS DATE) >= '2021-01-01' OR B16 IS NULL) \ AND B10 in ({0}) \ GROUP BY B10 \ ) D \ ON A.A3=D.B10 \ LEFT JOIN \ (SELECT B10 \ , COUNT(*) AS current_live_commitments \ FROM PDS_AI.PT_B \ WHERE cast(B2 AS DATE) < '2021-01-01' AND \ (B20 IS NULL OR CAST(B20 AS DATE)>='2021-01-01') AND \ (B16 IS NULL OR CAST(B16 AS DATE)>='2021-01-01') \ AND B10 in ({0}) \ GROUP BY B10 \ ) E \ ON A.A3=E.B10".format(sql_account_list)) tabular_2022_part2 = Dataset.Tabular.from_sql_query(query_2022_part2, query_timeout=3600) levy_model_set_2022_part2 = tabular_2022_part2.to_pandas_dataframe() return levy_model_set_2022_part2

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py

Python

tests/crypto/test_factory.py

reputage/didery

f94a3cf63a7be2a341fa06d173d068924e540e41

[ "Apache-2.0" ]

8

2018-09-07T09:26:52.000Z

2021-01-16T12:22:07.000Z

tests/crypto/test_factory.py

reputage/didery

f94a3cf63a7be2a341fa06d173d068924e540e41

[ "Apache-2.0" ]

184

2018-04-19T17:46:02.000Z

2019-05-21T19:04:30.000Z

tests/crypto/test_factory.py

reputage/didery

f94a3cf63a7be2a341fa06d173d068924e540e41

[ "Apache-2.0" ]

3

2018-09-26T19:16:30.000Z

2018-12-18T18:50:40.000Z

import didery.crypto.eddsa as eddsa import didery.crypto.ecdsa as ecdsa import didery.crypto.factory as factory from collections import OrderedDict as ODict from didery.help import helping as h def testECDSAFactory(): sigs = ODict() sigs["name"] = "ECDSA" validator = factory.signatureValidationFactory(sigs) assert validator is not None # test that factory returned ECDSA validator vk, sk, did, body = ecdsa.genDidHistory(numSigners=2) vk = h.bytesToStr64u(vk) signature = ecdsa.signResource(body, sk) valid = validator(signature, body.decode(), vk) assert valid sigs["name"] = "secp256k1" validator = factory.signatureValidationFactory(sigs) assert validator is not None # test that factory returned ECDSA validator vk, sk, did, body = ecdsa.genDidHistory(numSigners=2) vk = h.bytesToStr64u(vk) signature = ecdsa.signResource(body, sk) valid = validator(signature, body.decode(), vk) assert valid def testEdDSAFactory(): sigs = ODict() sigs["name"] = "EdDSA" validator = factory.signatureValidationFactory(sigs) assert validator is not None # test that factory returned EdDSA validator seed = b'\x92[\xcb\xf4\xee5+\xcf\xd4b*%/\xabw8\xd4d\xa2\xf8\xad\xa7U\x19,\xcfS\x12\xa6l\xba"' vk, sk, did, body = eddsa.genDidHistory(seed, signer=0, numSigners=2) vk = h.bytesToStr64u(vk) signature = eddsa.signResource(body, sk) valid = validator(signature, body.decode(), vk) assert valid sigs["name"] = "Ed25519" validator = factory.signatureValidationFactory(sigs) assert validator is not None # test that factory returned EdDSA validator seed = b'\x92[\xcb\xf4\xee5+\xcf\xd4b*%/\xabw8\xd4d\xa2\xf8\xad\xa7U\x19,\xcfS\x12\xa6l\xba"' vk, sk, did, body = eddsa.genDidHistory(seed, signer=0, numSigners=2) vk = h.bytesToStr64u(vk) signature = eddsa.signResource(body, sk) valid = validator(signature, body.decode(), vk) assert valid def testInvalidKind(): sigs = ODict() sigs["name"] = "InvalidSuperCrypto" validator = factory.signatureValidationFactory(sigs) assert validator is not None # test that factory returned default EdDSA validator seed = b'\x92[\xcb\xf4\xee5+\xcf\xd4b*%/\xabw8\xd4d\xa2\xf8\xad\xa7U\x19,\xcfS\x12\xa6l\xba"' vk, sk, did, body = eddsa.genDidHistory(seed, signer=0, numSigners=2) vk = h.bytesToStr64u(vk) signature = eddsa.signResource(body, sk) valid = validator(signature, body.decode(), vk) assert valid def testEmptyDict(): sigs = ODict() validator = factory.signatureValidationFactory(sigs) assert validator is not None # test that factory returned default EdDSA validator seed = b'\x92[\xcb\xf4\xee5+\xcf\xd4b*%/\xabw8\xd4d\xa2\xf8\xad\xa7U\x19,\xcfS\x12\xa6l\xba"' vk, sk, did, body = eddsa.genDidHistory(seed, signer=0, numSigners=2) vk = h.bytesToStr64u(vk) signature = eddsa.signResource(body, sk) valid = validator(signature, body.decode(), vk) assert valid

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cf8a8aa47a90f40ac457cec20891d94db4a3dbd3

177,014

py

Python

boto3_type_annotations_with_docs/boto3_type_annotations/ec2/waiter.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/ec2/waiter.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/ec2/waiter.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

11

2019-05-06T05:26:51.000Z

2021-09-28T15:27:59.000Z

from typing import Dict from typing import List from botocore.waiter import Waiter class BundleTaskComplete(Waiter): def wait(self, BundleIds: List = None, Filters: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_bundle_tasks` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeBundleTasks>`_ **Request Syntax** :: waiter.wait( BundleIds=[ 'string', ], Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type BundleIds: list :param BundleIds: The bundle task IDs. Default: Describes all your bundle tasks. - *(string) --* :type Filters: list :param Filters: The filters. * ``bundle-id`` - The ID of the bundle task. * ``error-code`` - If the task failed, the error code returned. * ``error-message`` - If the task failed, the error message returned. * ``instance-id`` - The ID of the instance. * ``progress`` - The level of task completion, as a percentage (for example, 20%). * ``s3-bucket`` - The Amazon S3 bucket to store the AMI. * ``s3-prefix`` - The beginning of the AMI name. * ``start-time`` - The time the task started (for example, 2013-09-15T17:15:20.000Z). * ``state`` - The state of the task (``pending`` | ``waiting-for-shutdown`` | ``bundling`` | ``storing`` | ``cancelling`` | ``complete`` | ``failed`` ). * ``update-time`` - The time of the most recent update for the task. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class ConversionTaskCancelled(Waiter): def wait(self, ConversionTaskIds: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_conversion_tasks` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeConversionTasks>`_ **Request Syntax** :: waiter.wait( ConversionTaskIds=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type ConversionTaskIds: list :param ConversionTaskIds: The conversion task IDs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class ConversionTaskCompleted(Waiter): def wait(self, ConversionTaskIds: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_conversion_tasks` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeConversionTasks>`_ **Request Syntax** :: waiter.wait( ConversionTaskIds=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type ConversionTaskIds: list :param ConversionTaskIds: The conversion task IDs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class ConversionTaskDeleted(Waiter): def wait(self, ConversionTaskIds: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_conversion_tasks` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeConversionTasks>`_ **Request Syntax** :: waiter.wait( ConversionTaskIds=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type ConversionTaskIds: list :param ConversionTaskIds: The conversion task IDs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class CustomerGatewayAvailable(Waiter): def wait(self, CustomerGatewayIds: List = None, Filters: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_customer_gateways` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeCustomerGateways>`_ **Request Syntax** :: waiter.wait( CustomerGatewayIds=[ 'string', ], Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type CustomerGatewayIds: list :param CustomerGatewayIds: One or more customer gateway IDs. Default: Describes all your customer gateways. - *(string) --* :type Filters: list :param Filters: One or more filters. * ``bgp-asn`` - The customer gateway\'s Border Gateway Protocol (BGP) Autonomous System Number (ASN). * ``customer-gateway-id`` - The ID of the customer gateway. * ``ip-address`` - The IP address of the customer gateway\'s Internet-routable external interface. * ``state`` - The state of the customer gateway (``pending`` | ``available`` | ``deleting`` | ``deleted`` ). * ``type`` - The type of customer gateway. Currently, the only supported type is ``ipsec.1`` . * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class ExportTaskCancelled(Waiter): def wait(self, ExportTaskIds: List = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_export_tasks` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeExportTasks>`_ **Request Syntax** :: waiter.wait( ExportTaskIds=[ 'string', ], WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type ExportTaskIds: list :param ExportTaskIds: The export task IDs. - *(string) --* :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class ExportTaskCompleted(Waiter): def wait(self, ExportTaskIds: List = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_export_tasks` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeExportTasks>`_ **Request Syntax** :: waiter.wait( ExportTaskIds=[ 'string', ], WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type ExportTaskIds: list :param ExportTaskIds: The export task IDs. - *(string) --* :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class ImageAvailable(Waiter): def wait(self, ExecutableUsers: List = None, Filters: List = None, ImageIds: List = None, Owners: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_images` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeImages>`_ **Request Syntax** :: waiter.wait( ExecutableUsers=[ 'string', ], Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], ImageIds=[ 'string', ], Owners=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type ExecutableUsers: list :param ExecutableUsers: Scopes the images by users with explicit launch permissions. Specify an AWS account ID, ``self`` (the sender of the request), or ``all`` (public AMIs). - *(string) --* :type Filters: list :param Filters: The filters. * ``architecture`` - The image architecture (``i386`` | ``x86_64`` ). * ``block-device-mapping.delete-on-termination`` - A Boolean value that indicates whether the Amazon EBS volume is deleted on instance termination. * ``block-device-mapping.device-name`` - The device name specified in the block device mapping (for example, ``/dev/sdh`` or ``xvdh`` ). * ``block-device-mapping.snapshot-id`` - The ID of the snapshot used for the EBS volume. * ``block-device-mapping.volume-size`` - The volume size of the EBS volume, in GiB. * ``block-device-mapping.volume-type`` - The volume type of the EBS volume (``gp2`` | ``io1`` | ``st1`` | ``sc1`` | ``standard`` ). * ``block-device-mapping.encrypted`` - A Boolean that indicates whether the EBS volume is encrypted. * ``description`` - The description of the image (provided during image creation). * ``ena-support`` - A Boolean that indicates whether enhanced networking with ENA is enabled. * ``hypervisor`` - The hypervisor type (``ovm`` | ``xen`` ). * ``image-id`` - The ID of the image. * ``image-type`` - The image type (``machine`` | ``kernel`` | ``ramdisk`` ). * ``is-public`` - A Boolean that indicates whether the image is public. * ``kernel-id`` - The kernel ID. * ``manifest-location`` - The location of the image manifest. * ``name`` - The name of the AMI (provided during image creation). * ``owner-alias`` - String value from an Amazon-maintained list (``amazon`` | ``aws-marketplace`` | ``microsoft`` ) of snapshot owners. Not to be confused with the user-configured AWS account alias, which is set from the IAM console. * ``owner-id`` - The AWS account ID of the image owner. * ``platform`` - The platform. To only list Windows-based AMIs, use ``windows`` . * ``product-code`` - The product code. * ``product-code.type`` - The type of the product code (``devpay`` | ``marketplace`` ). * ``ramdisk-id`` - The RAM disk ID. * ``root-device-name`` - The device name of the root device volume (for example, ``/dev/sda1`` ). * ``root-device-type`` - The type of the root device volume (``ebs`` | ``instance-store`` ). * ``state`` - The state of the image (``available`` | ``pending`` | ``failed`` ). * ``state-reason-code`` - The reason code for the state change. * ``state-reason-message`` - The message for the state change. * ``sriov-net-support`` - A value of ``simple`` indicates that enhanced networking with the Intel 82599 VF interface is enabled. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``virtualization-type`` - The virtualization type (``paravirtual`` | ``hvm`` ). - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type ImageIds: list :param ImageIds: The image IDs. Default: Describes all images available to you. - *(string) --* :type Owners: list :param Owners: Filters the images by the owner. Specify an AWS account ID, ``self`` (owner is the sender of the request), or an AWS owner alias (valid values are ``amazon`` | ``aws-marketplace`` | ``microsoft`` ). Omitting this option returns all images for which you have launch permissions, regardless of ownership. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class ImageExists(Waiter): def wait(self, ExecutableUsers: List = None, Filters: List = None, ImageIds: List = None, Owners: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_images` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeImages>`_ **Request Syntax** :: waiter.wait( ExecutableUsers=[ 'string', ], Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], ImageIds=[ 'string', ], Owners=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type ExecutableUsers: list :param ExecutableUsers: Scopes the images by users with explicit launch permissions. Specify an AWS account ID, ``self`` (the sender of the request), or ``all`` (public AMIs). - *(string) --* :type Filters: list :param Filters: The filters. * ``architecture`` - The image architecture (``i386`` | ``x86_64`` ). * ``block-device-mapping.delete-on-termination`` - A Boolean value that indicates whether the Amazon EBS volume is deleted on instance termination. * ``block-device-mapping.device-name`` - The device name specified in the block device mapping (for example, ``/dev/sdh`` or ``xvdh`` ). * ``block-device-mapping.snapshot-id`` - The ID of the snapshot used for the EBS volume. * ``block-device-mapping.volume-size`` - The volume size of the EBS volume, in GiB. * ``block-device-mapping.volume-type`` - The volume type of the EBS volume (``gp2`` | ``io1`` | ``st1`` | ``sc1`` | ``standard`` ). * ``block-device-mapping.encrypted`` - A Boolean that indicates whether the EBS volume is encrypted. * ``description`` - The description of the image (provided during image creation). * ``ena-support`` - A Boolean that indicates whether enhanced networking with ENA is enabled. * ``hypervisor`` - The hypervisor type (``ovm`` | ``xen`` ). * ``image-id`` - The ID of the image. * ``image-type`` - The image type (``machine`` | ``kernel`` | ``ramdisk`` ). * ``is-public`` - A Boolean that indicates whether the image is public. * ``kernel-id`` - The kernel ID. * ``manifest-location`` - The location of the image manifest. * ``name`` - The name of the AMI (provided during image creation). * ``owner-alias`` - String value from an Amazon-maintained list (``amazon`` | ``aws-marketplace`` | ``microsoft`` ) of snapshot owners. Not to be confused with the user-configured AWS account alias, which is set from the IAM console. * ``owner-id`` - The AWS account ID of the image owner. * ``platform`` - The platform. To only list Windows-based AMIs, use ``windows`` . * ``product-code`` - The product code. * ``product-code.type`` - The type of the product code (``devpay`` | ``marketplace`` ). * ``ramdisk-id`` - The RAM disk ID. * ``root-device-name`` - The device name of the root device volume (for example, ``/dev/sda1`` ). * ``root-device-type`` - The type of the root device volume (``ebs`` | ``instance-store`` ). * ``state`` - The state of the image (``available`` | ``pending`` | ``failed`` ). * ``state-reason-code`` - The reason code for the state change. * ``state-reason-message`` - The message for the state change. * ``sriov-net-support`` - A value of ``simple`` indicates that enhanced networking with the Intel 82599 VF interface is enabled. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``virtualization-type`` - The virtualization type (``paravirtual`` | ``hvm`` ). - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type ImageIds: list :param ImageIds: The image IDs. Default: Describes all images available to you. - *(string) --* :type Owners: list :param Owners: Filters the images by the owner. Specify an AWS account ID, ``self`` (owner is the sender of the request), or an AWS owner alias (valid values are ``amazon`` | ``aws-marketplace`` | ``microsoft`` ). Omitting this option returns all images for which you have launch permissions, regardless of ownership. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class InstanceExists(Waiter): def wait(self, Filters: List = None, InstanceIds: List = None, DryRun: bool = None, MaxResults: int = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_instances` every 5 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeInstances>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], InstanceIds=[ 'string', ], DryRun=True|False, MaxResults=123, NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``affinity`` - The affinity setting for an instance running on a Dedicated Host (``default`` | ``host`` ). * ``architecture`` - The instance architecture (``i386`` | ``x86_64`` ). * ``availability-zone`` - The Availability Zone of the instance. * ``block-device-mapping.attach-time`` - The attach time for an EBS volume mapped to the instance, for example, ``2010-09-15T17:15:20.000Z`` . * ``block-device-mapping.delete-on-termination`` - A Boolean that indicates whether the EBS volume is deleted on instance termination. * ``block-device-mapping.device-name`` - The device name specified in the block device mapping (for example, ``/dev/sdh`` or ``xvdh`` ). * ``block-device-mapping.status`` - The status for the EBS volume (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``block-device-mapping.volume-id`` - The volume ID of the EBS volume. * ``client-token`` - The idempotency token you provided when you launched the instance. * ``dns-name`` - The public DNS name of the instance. * ``group-id`` - The ID of the security group for the instance. EC2-Classic only. * ``group-name`` - The name of the security group for the instance. EC2-Classic only. * ``hibernation-options.configured`` - A Boolean that indicates whether the instance is enabled for hibernation. A value of ``true`` means that the instance is enabled for hibernation. * ``host-id`` - The ID of the Dedicated Host on which the instance is running, if applicable. * ``hypervisor`` - The hypervisor type of the instance (``ovm`` | ``xen`` ). * ``iam-instance-profile.arn`` - The instance profile associated with the instance. Specified as an ARN. * ``image-id`` - The ID of the image used to launch the instance. * ``instance-id`` - The ID of the instance. * ``instance-lifecycle`` - Indicates whether this is a Spot Instance or a Scheduled Instance (``spot`` | ``scheduled`` ). * ``instance-state-code`` - The state of the instance, as a 16-bit unsigned integer. The high byte is used for internal purposes and should be ignored. The low byte is set based on the state represented. The valid values are: 0 (pending), 16 (running), 32 (shutting-down), 48 (terminated), 64 (stopping), and 80 (stopped). * ``instance-state-name`` - The state of the instance (``pending`` | ``running`` | ``shutting-down`` | ``terminated`` | ``stopping`` | ``stopped`` ). * ``instance-type`` - The type of instance (for example, ``t2.micro`` ). * ``instance.group-id`` - The ID of the security group for the instance. * ``instance.group-name`` - The name of the security group for the instance. * ``ip-address`` - The public IPv4 address of the instance. * ``kernel-id`` - The kernel ID. * ``key-name`` - The name of the key pair used when the instance was launched. * ``launch-index`` - When launching multiple instances, this is the index for the instance in the launch group (for example, 0, 1, 2, and so on). * ``launch-time`` - The time when the instance was launched. * ``monitoring-state`` - Indicates whether detailed monitoring is enabled (``disabled`` | ``enabled`` ). * ``network-interface.addresses.private-ip-address`` - The private IPv4 address associated with the network interface. * ``network-interface.addresses.primary`` - Specifies whether the IPv4 address of the network interface is the primary private IPv4 address. * ``network-interface.addresses.association.public-ip`` - The ID of the association of an Elastic IP address (IPv4) with a network interface. * ``network-interface.addresses.association.ip-owner-id`` - The owner ID of the private IPv4 address associated with the network interface. * ``network-interface.association.public-ip`` - The address of the Elastic IP address (IPv4) bound to the network interface. * ``network-interface.association.ip-owner-id`` - The owner of the Elastic IP address (IPv4) associated with the network interface. * ``network-interface.association.allocation-id`` - The allocation ID returned when you allocated the Elastic IP address (IPv4) for your network interface. * ``network-interface.association.association-id`` - The association ID returned when the network interface was associated with an IPv4 address. * ``network-interface.attachment.attachment-id`` - The ID of the interface attachment. * ``network-interface.attachment.instance-id`` - The ID of the instance to which the network interface is attached. * ``network-interface.attachment.instance-owner-id`` - The owner ID of the instance to which the network interface is attached. * ``network-interface.attachment.device-index`` - The device index to which the network interface is attached. * ``network-interface.attachment.status`` - The status of the attachment (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``network-interface.attachment.attach-time`` - The time that the network interface was attached to an instance. * ``network-interface.attachment.delete-on-termination`` - Specifies whether the attachment is deleted when an instance is terminated. * ``network-interface.availability-zone`` - The Availability Zone for the network interface. * ``network-interface.description`` - The description of the network interface. * ``network-interface.group-id`` - The ID of a security group associated with the network interface. * ``network-interface.group-name`` - The name of a security group associated with the network interface. * ``network-interface.ipv6-addresses.ipv6-address`` - The IPv6 address associated with the network interface. * ``network-interface.mac-address`` - The MAC address of the network interface. * ``network-interface.network-interface-id`` - The ID of the network interface. * ``network-interface.owner-id`` - The ID of the owner of the network interface. * ``network-interface.private-dns-name`` - The private DNS name of the network interface. * ``network-interface.requester-id`` - The requester ID for the network interface. * ``network-interface.requester-managed`` - Indicates whether the network interface is being managed by AWS. * ``network-interface.status`` - The status of the network interface (``available`` ) | ``in-use`` ). * ``network-interface.source-dest-check`` - Whether the network interface performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the network interface to perform network address translation (NAT) in your VPC. * ``network-interface.subnet-id`` - The ID of the subnet for the network interface. * ``network-interface.vpc-id`` - The ID of the VPC for the network interface. * ``owner-id`` - The AWS account ID of the instance owner. * ``placement-group-name`` - The name of the placement group for the instance. * ``placement-partition-number`` - The partition in which the instance is located. * ``platform`` - The platform. To list only Windows instances, use ``windows`` . * ``private-dns-name`` - The private IPv4 DNS name of the instance. * ``private-ip-address`` - The private IPv4 address of the instance. * ``product-code`` - The product code associated with the AMI used to launch the instance. * ``product-code.type`` - The type of product code (``devpay`` | ``marketplace`` ). * ``ramdisk-id`` - The RAM disk ID. * ``reason`` - The reason for the current state of the instance (for example, shows \"User Initiated [date]\" when you stop or terminate the instance). Similar to the state-reason-code filter. * ``requester-id`` - The ID of the entity that launched the instance on your behalf (for example, AWS Management Console, Auto Scaling, and so on). * ``reservation-id`` - The ID of the instance\'s reservation. A reservation ID is created any time you launch an instance. A reservation ID has a one-to-one relationship with an instance launch request, but can be associated with more than one instance if you launch multiple instances using the same launch request. For example, if you launch one instance, you get one reservation ID. If you launch ten instances using the same launch request, you also get one reservation ID. * ``root-device-name`` - The device name of the root device volume (for example, ``/dev/sda1`` ). * ``root-device-type`` - The type of the root device volume (``ebs`` | ``instance-store`` ). * ``source-dest-check`` - Indicates whether the instance performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the instance to perform network address translation (NAT) in your VPC. * ``spot-instance-request-id`` - The ID of the Spot Instance request. * ``state-reason-code`` - The reason code for the state change. * ``state-reason-message`` - A message that describes the state change. * ``subnet-id`` - The ID of the subnet for the instance. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources that have a tag with a specific key, regardless of the tag value. * ``tenancy`` - The tenancy of an instance (``dedicated`` | ``default`` | ``host`` ). * ``virtualization-type`` - The virtualization type of the instance (``paravirtual`` | ``hvm`` ). * ``vpc-id`` - The ID of the VPC that the instance is running in. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type InstanceIds: list :param InstanceIds: The instance IDs. Default: Describes all your instances. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type MaxResults: integer :param MaxResults: The maximum number of results to return in a single call. To retrieve the remaining results, make another call with the returned ``NextToken`` value. This value can be between 5 and 1000. You cannot specify this parameter and the instance IDs parameter in the same call. :type NextToken: string :param NextToken: The token to request the next page of results. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 5 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class InstanceRunning(Waiter): def wait(self, Filters: List = None, InstanceIds: List = None, DryRun: bool = None, MaxResults: int = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_instances` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeInstances>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], InstanceIds=[ 'string', ], DryRun=True|False, MaxResults=123, NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``affinity`` - The affinity setting for an instance running on a Dedicated Host (``default`` | ``host`` ). * ``architecture`` - The instance architecture (``i386`` | ``x86_64`` ). * ``availability-zone`` - The Availability Zone of the instance. * ``block-device-mapping.attach-time`` - The attach time for an EBS volume mapped to the instance, for example, ``2010-09-15T17:15:20.000Z`` . * ``block-device-mapping.delete-on-termination`` - A Boolean that indicates whether the EBS volume is deleted on instance termination. * ``block-device-mapping.device-name`` - The device name specified in the block device mapping (for example, ``/dev/sdh`` or ``xvdh`` ). * ``block-device-mapping.status`` - The status for the EBS volume (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``block-device-mapping.volume-id`` - The volume ID of the EBS volume. * ``client-token`` - The idempotency token you provided when you launched the instance. * ``dns-name`` - The public DNS name of the instance. * ``group-id`` - The ID of the security group for the instance. EC2-Classic only. * ``group-name`` - The name of the security group for the instance. EC2-Classic only. * ``hibernation-options.configured`` - A Boolean that indicates whether the instance is enabled for hibernation. A value of ``true`` means that the instance is enabled for hibernation. * ``host-id`` - The ID of the Dedicated Host on which the instance is running, if applicable. * ``hypervisor`` - The hypervisor type of the instance (``ovm`` | ``xen`` ). * ``iam-instance-profile.arn`` - The instance profile associated with the instance. Specified as an ARN. * ``image-id`` - The ID of the image used to launch the instance. * ``instance-id`` - The ID of the instance. * ``instance-lifecycle`` - Indicates whether this is a Spot Instance or a Scheduled Instance (``spot`` | ``scheduled`` ). * ``instance-state-code`` - The state of the instance, as a 16-bit unsigned integer. The high byte is used for internal purposes and should be ignored. The low byte is set based on the state represented. The valid values are: 0 (pending), 16 (running), 32 (shutting-down), 48 (terminated), 64 (stopping), and 80 (stopped). * ``instance-state-name`` - The state of the instance (``pending`` | ``running`` | ``shutting-down`` | ``terminated`` | ``stopping`` | ``stopped`` ). * ``instance-type`` - The type of instance (for example, ``t2.micro`` ). * ``instance.group-id`` - The ID of the security group for the instance. * ``instance.group-name`` - The name of the security group for the instance. * ``ip-address`` - The public IPv4 address of the instance. * ``kernel-id`` - The kernel ID. * ``key-name`` - The name of the key pair used when the instance was launched. * ``launch-index`` - When launching multiple instances, this is the index for the instance in the launch group (for example, 0, 1, 2, and so on). * ``launch-time`` - The time when the instance was launched. * ``monitoring-state`` - Indicates whether detailed monitoring is enabled (``disabled`` | ``enabled`` ). * ``network-interface.addresses.private-ip-address`` - The private IPv4 address associated with the network interface. * ``network-interface.addresses.primary`` - Specifies whether the IPv4 address of the network interface is the primary private IPv4 address. * ``network-interface.addresses.association.public-ip`` - The ID of the association of an Elastic IP address (IPv4) with a network interface. * ``network-interface.addresses.association.ip-owner-id`` - The owner ID of the private IPv4 address associated with the network interface. * ``network-interface.association.public-ip`` - The address of the Elastic IP address (IPv4) bound to the network interface. * ``network-interface.association.ip-owner-id`` - The owner of the Elastic IP address (IPv4) associated with the network interface. * ``network-interface.association.allocation-id`` - The allocation ID returned when you allocated the Elastic IP address (IPv4) for your network interface. * ``network-interface.association.association-id`` - The association ID returned when the network interface was associated with an IPv4 address. * ``network-interface.attachment.attachment-id`` - The ID of the interface attachment. * ``network-interface.attachment.instance-id`` - The ID of the instance to which the network interface is attached. * ``network-interface.attachment.instance-owner-id`` - The owner ID of the instance to which the network interface is attached. * ``network-interface.attachment.device-index`` - The device index to which the network interface is attached. * ``network-interface.attachment.status`` - The status of the attachment (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``network-interface.attachment.attach-time`` - The time that the network interface was attached to an instance. * ``network-interface.attachment.delete-on-termination`` - Specifies whether the attachment is deleted when an instance is terminated. * ``network-interface.availability-zone`` - The Availability Zone for the network interface. * ``network-interface.description`` - The description of the network interface. * ``network-interface.group-id`` - The ID of a security group associated with the network interface. * ``network-interface.group-name`` - The name of a security group associated with the network interface. * ``network-interface.ipv6-addresses.ipv6-address`` - The IPv6 address associated with the network interface. * ``network-interface.mac-address`` - The MAC address of the network interface. * ``network-interface.network-interface-id`` - The ID of the network interface. * ``network-interface.owner-id`` - The ID of the owner of the network interface. * ``network-interface.private-dns-name`` - The private DNS name of the network interface. * ``network-interface.requester-id`` - The requester ID for the network interface. * ``network-interface.requester-managed`` - Indicates whether the network interface is being managed by AWS. * ``network-interface.status`` - The status of the network interface (``available`` ) | ``in-use`` ). * ``network-interface.source-dest-check`` - Whether the network interface performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the network interface to perform network address translation (NAT) in your VPC. * ``network-interface.subnet-id`` - The ID of the subnet for the network interface. * ``network-interface.vpc-id`` - The ID of the VPC for the network interface. * ``owner-id`` - The AWS account ID of the instance owner. * ``placement-group-name`` - The name of the placement group for the instance. * ``placement-partition-number`` - The partition in which the instance is located. * ``platform`` - The platform. To list only Windows instances, use ``windows`` . * ``private-dns-name`` - The private IPv4 DNS name of the instance. * ``private-ip-address`` - The private IPv4 address of the instance. * ``product-code`` - The product code associated with the AMI used to launch the instance. * ``product-code.type`` - The type of product code (``devpay`` | ``marketplace`` ). * ``ramdisk-id`` - The RAM disk ID. * ``reason`` - The reason for the current state of the instance (for example, shows \"User Initiated [date]\" when you stop or terminate the instance). Similar to the state-reason-code filter. * ``requester-id`` - The ID of the entity that launched the instance on your behalf (for example, AWS Management Console, Auto Scaling, and so on). * ``reservation-id`` - The ID of the instance\'s reservation. A reservation ID is created any time you launch an instance. A reservation ID has a one-to-one relationship with an instance launch request, but can be associated with more than one instance if you launch multiple instances using the same launch request. For example, if you launch one instance, you get one reservation ID. If you launch ten instances using the same launch request, you also get one reservation ID. * ``root-device-name`` - The device name of the root device volume (for example, ``/dev/sda1`` ). * ``root-device-type`` - The type of the root device volume (``ebs`` | ``instance-store`` ). * ``source-dest-check`` - Indicates whether the instance performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the instance to perform network address translation (NAT) in your VPC. * ``spot-instance-request-id`` - The ID of the Spot Instance request. * ``state-reason-code`` - The reason code for the state change. * ``state-reason-message`` - A message that describes the state change. * ``subnet-id`` - The ID of the subnet for the instance. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources that have a tag with a specific key, regardless of the tag value. * ``tenancy`` - The tenancy of an instance (``dedicated`` | ``default`` | ``host`` ). * ``virtualization-type`` - The virtualization type of the instance (``paravirtual`` | ``hvm`` ). * ``vpc-id`` - The ID of the VPC that the instance is running in. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type InstanceIds: list :param InstanceIds: The instance IDs. Default: Describes all your instances. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type MaxResults: integer :param MaxResults: The maximum number of results to return in a single call. To retrieve the remaining results, make another call with the returned ``NextToken`` value. This value can be between 5 and 1000. You cannot specify this parameter and the instance IDs parameter in the same call. :type NextToken: string :param NextToken: The token to request the next page of results. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class InstanceStatusOk(Waiter): def wait(self, Filters: List = None, InstanceIds: List = None, MaxResults: int = None, NextToken: str = None, DryRun: bool = None, IncludeAllInstances: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_instance_status` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeInstanceStatus>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], InstanceIds=[ 'string', ], MaxResults=123, NextToken='string', DryRun=True|False, IncludeAllInstances=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``availability-zone`` - The Availability Zone of the instance. * ``event.code`` - The code for the scheduled event (``instance-reboot`` | ``system-reboot`` | ``system-maintenance`` | ``instance-retirement`` | ``instance-stop`` ). * ``event.description`` - A description of the event. * ``event.instance-event-id`` - The ID of the event whose date and time you are modifying. * ``event.not-after`` - The latest end time for the scheduled event (for example, ``2014-09-15T17:15:20.000Z`` ). * ``event.not-before`` - The earliest start time for the scheduled event (for example, ``2014-09-15T17:15:20.000Z`` ). * ``event.not-before-deadline`` - The deadline for starting the event (for example, ``2014-09-15T17:15:20.000Z`` ). * ``instance-state-code`` - The code for the instance state, as a 16-bit unsigned integer. The high byte is used for internal purposes and should be ignored. The low byte is set based on the state represented. The valid values are 0 (pending), 16 (running), 32 (shutting-down), 48 (terminated), 64 (stopping), and 80 (stopped). * ``instance-state-name`` - The state of the instance (``pending`` | ``running`` | ``shutting-down`` | ``terminated`` | ``stopping`` | ``stopped`` ). * ``instance-status.reachability`` - Filters on instance status where the name is ``reachability`` (``passed`` | ``failed`` | ``initializing`` | ``insufficient-data`` ). * ``instance-status.status`` - The status of the instance (``ok`` | ``impaired`` | ``initializing`` | ``insufficient-data`` | ``not-applicable`` ). * ``system-status.reachability`` - Filters on system status where the name is ``reachability`` (``passed`` | ``failed`` | ``initializing`` | ``insufficient-data`` ). * ``system-status.status`` - The system status of the instance (``ok`` | ``impaired`` | ``initializing`` | ``insufficient-data`` | ``not-applicable`` ). - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type InstanceIds: list :param InstanceIds: The instance IDs. Default: Describes all your instances. Constraints: Maximum 100 explicitly specified instance IDs. - *(string) --* :type MaxResults: integer :param MaxResults: The maximum number of results to return in a single call. To retrieve the remaining results, make another call with the returned ``NextToken`` value. This value can be between 5 and 1000. You cannot specify this parameter and the instance IDs parameter in the same call. :type NextToken: string :param NextToken: The token to retrieve the next page of results. :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type IncludeAllInstances: boolean :param IncludeAllInstances: When ``true`` , includes the health status for all instances. When ``false`` , includes the health status for running instances only. Default: ``false`` :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class InstanceStopped(Waiter): def wait(self, Filters: List = None, InstanceIds: List = None, DryRun: bool = None, MaxResults: int = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_instances` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeInstances>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], InstanceIds=[ 'string', ], DryRun=True|False, MaxResults=123, NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``affinity`` - The affinity setting for an instance running on a Dedicated Host (``default`` | ``host`` ). * ``architecture`` - The instance architecture (``i386`` | ``x86_64`` ). * ``availability-zone`` - The Availability Zone of the instance. * ``block-device-mapping.attach-time`` - The attach time for an EBS volume mapped to the instance, for example, ``2010-09-15T17:15:20.000Z`` . * ``block-device-mapping.delete-on-termination`` - A Boolean that indicates whether the EBS volume is deleted on instance termination. * ``block-device-mapping.device-name`` - The device name specified in the block device mapping (for example, ``/dev/sdh`` or ``xvdh`` ). * ``block-device-mapping.status`` - The status for the EBS volume (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``block-device-mapping.volume-id`` - The volume ID of the EBS volume. * ``client-token`` - The idempotency token you provided when you launched the instance. * ``dns-name`` - The public DNS name of the instance. * ``group-id`` - The ID of the security group for the instance. EC2-Classic only. * ``group-name`` - The name of the security group for the instance. EC2-Classic only. * ``hibernation-options.configured`` - A Boolean that indicates whether the instance is enabled for hibernation. A value of ``true`` means that the instance is enabled for hibernation. * ``host-id`` - The ID of the Dedicated Host on which the instance is running, if applicable. * ``hypervisor`` - The hypervisor type of the instance (``ovm`` | ``xen`` ). * ``iam-instance-profile.arn`` - The instance profile associated with the instance. Specified as an ARN. * ``image-id`` - The ID of the image used to launch the instance. * ``instance-id`` - The ID of the instance. * ``instance-lifecycle`` - Indicates whether this is a Spot Instance or a Scheduled Instance (``spot`` | ``scheduled`` ). * ``instance-state-code`` - The state of the instance, as a 16-bit unsigned integer. The high byte is used for internal purposes and should be ignored. The low byte is set based on the state represented. The valid values are: 0 (pending), 16 (running), 32 (shutting-down), 48 (terminated), 64 (stopping), and 80 (stopped). * ``instance-state-name`` - The state of the instance (``pending`` | ``running`` | ``shutting-down`` | ``terminated`` | ``stopping`` | ``stopped`` ). * ``instance-type`` - The type of instance (for example, ``t2.micro`` ). * ``instance.group-id`` - The ID of the security group for the instance. * ``instance.group-name`` - The name of the security group for the instance. * ``ip-address`` - The public IPv4 address of the instance. * ``kernel-id`` - The kernel ID. * ``key-name`` - The name of the key pair used when the instance was launched. * ``launch-index`` - When launching multiple instances, this is the index for the instance in the launch group (for example, 0, 1, 2, and so on). * ``launch-time`` - The time when the instance was launched. * ``monitoring-state`` - Indicates whether detailed monitoring is enabled (``disabled`` | ``enabled`` ). * ``network-interface.addresses.private-ip-address`` - The private IPv4 address associated with the network interface. * ``network-interface.addresses.primary`` - Specifies whether the IPv4 address of the network interface is the primary private IPv4 address. * ``network-interface.addresses.association.public-ip`` - The ID of the association of an Elastic IP address (IPv4) with a network interface. * ``network-interface.addresses.association.ip-owner-id`` - The owner ID of the private IPv4 address associated with the network interface. * ``network-interface.association.public-ip`` - The address of the Elastic IP address (IPv4) bound to the network interface. * ``network-interface.association.ip-owner-id`` - The owner of the Elastic IP address (IPv4) associated with the network interface. * ``network-interface.association.allocation-id`` - The allocation ID returned when you allocated the Elastic IP address (IPv4) for your network interface. * ``network-interface.association.association-id`` - The association ID returned when the network interface was associated with an IPv4 address. * ``network-interface.attachment.attachment-id`` - The ID of the interface attachment. * ``network-interface.attachment.instance-id`` - The ID of the instance to which the network interface is attached. * ``network-interface.attachment.instance-owner-id`` - The owner ID of the instance to which the network interface is attached. * ``network-interface.attachment.device-index`` - The device index to which the network interface is attached. * ``network-interface.attachment.status`` - The status of the attachment (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``network-interface.attachment.attach-time`` - The time that the network interface was attached to an instance. * ``network-interface.attachment.delete-on-termination`` - Specifies whether the attachment is deleted when an instance is terminated. * ``network-interface.availability-zone`` - The Availability Zone for the network interface. * ``network-interface.description`` - The description of the network interface. * ``network-interface.group-id`` - The ID of a security group associated with the network interface. * ``network-interface.group-name`` - The name of a security group associated with the network interface. * ``network-interface.ipv6-addresses.ipv6-address`` - The IPv6 address associated with the network interface. * ``network-interface.mac-address`` - The MAC address of the network interface. * ``network-interface.network-interface-id`` - The ID of the network interface. * ``network-interface.owner-id`` - The ID of the owner of the network interface. * ``network-interface.private-dns-name`` - The private DNS name of the network interface. * ``network-interface.requester-id`` - The requester ID for the network interface. * ``network-interface.requester-managed`` - Indicates whether the network interface is being managed by AWS. * ``network-interface.status`` - The status of the network interface (``available`` ) | ``in-use`` ). * ``network-interface.source-dest-check`` - Whether the network interface performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the network interface to perform network address translation (NAT) in your VPC. * ``network-interface.subnet-id`` - The ID of the subnet for the network interface. * ``network-interface.vpc-id`` - The ID of the VPC for the network interface. * ``owner-id`` - The AWS account ID of the instance owner. * ``placement-group-name`` - The name of the placement group for the instance. * ``placement-partition-number`` - The partition in which the instance is located. * ``platform`` - The platform. To list only Windows instances, use ``windows`` . * ``private-dns-name`` - The private IPv4 DNS name of the instance. * ``private-ip-address`` - The private IPv4 address of the instance. * ``product-code`` - The product code associated with the AMI used to launch the instance. * ``product-code.type`` - The type of product code (``devpay`` | ``marketplace`` ). * ``ramdisk-id`` - The RAM disk ID. * ``reason`` - The reason for the current state of the instance (for example, shows \"User Initiated [date]\" when you stop or terminate the instance). Similar to the state-reason-code filter. * ``requester-id`` - The ID of the entity that launched the instance on your behalf (for example, AWS Management Console, Auto Scaling, and so on). * ``reservation-id`` - The ID of the instance\'s reservation. A reservation ID is created any time you launch an instance. A reservation ID has a one-to-one relationship with an instance launch request, but can be associated with more than one instance if you launch multiple instances using the same launch request. For example, if you launch one instance, you get one reservation ID. If you launch ten instances using the same launch request, you also get one reservation ID. * ``root-device-name`` - The device name of the root device volume (for example, ``/dev/sda1`` ). * ``root-device-type`` - The type of the root device volume (``ebs`` | ``instance-store`` ). * ``source-dest-check`` - Indicates whether the instance performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the instance to perform network address translation (NAT) in your VPC. * ``spot-instance-request-id`` - The ID of the Spot Instance request. * ``state-reason-code`` - The reason code for the state change. * ``state-reason-message`` - A message that describes the state change. * ``subnet-id`` - The ID of the subnet for the instance. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources that have a tag with a specific key, regardless of the tag value. * ``tenancy`` - The tenancy of an instance (``dedicated`` | ``default`` | ``host`` ). * ``virtualization-type`` - The virtualization type of the instance (``paravirtual`` | ``hvm`` ). * ``vpc-id`` - The ID of the VPC that the instance is running in. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type InstanceIds: list :param InstanceIds: The instance IDs. Default: Describes all your instances. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type MaxResults: integer :param MaxResults: The maximum number of results to return in a single call. To retrieve the remaining results, make another call with the returned ``NextToken`` value. This value can be between 5 and 1000. You cannot specify this parameter and the instance IDs parameter in the same call. :type NextToken: string :param NextToken: The token to request the next page of results. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class InstanceTerminated(Waiter): def wait(self, Filters: List = None, InstanceIds: List = None, DryRun: bool = None, MaxResults: int = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_instances` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeInstances>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], InstanceIds=[ 'string', ], DryRun=True|False, MaxResults=123, NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``affinity`` - The affinity setting for an instance running on a Dedicated Host (``default`` | ``host`` ). * ``architecture`` - The instance architecture (``i386`` | ``x86_64`` ). * ``availability-zone`` - The Availability Zone of the instance. * ``block-device-mapping.attach-time`` - The attach time for an EBS volume mapped to the instance, for example, ``2010-09-15T17:15:20.000Z`` . * ``block-device-mapping.delete-on-termination`` - A Boolean that indicates whether the EBS volume is deleted on instance termination. * ``block-device-mapping.device-name`` - The device name specified in the block device mapping (for example, ``/dev/sdh`` or ``xvdh`` ). * ``block-device-mapping.status`` - The status for the EBS volume (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``block-device-mapping.volume-id`` - The volume ID of the EBS volume. * ``client-token`` - The idempotency token you provided when you launched the instance. * ``dns-name`` - The public DNS name of the instance. * ``group-id`` - The ID of the security group for the instance. EC2-Classic only. * ``group-name`` - The name of the security group for the instance. EC2-Classic only. * ``hibernation-options.configured`` - A Boolean that indicates whether the instance is enabled for hibernation. A value of ``true`` means that the instance is enabled for hibernation. * ``host-id`` - The ID of the Dedicated Host on which the instance is running, if applicable. * ``hypervisor`` - The hypervisor type of the instance (``ovm`` | ``xen`` ). * ``iam-instance-profile.arn`` - The instance profile associated with the instance. Specified as an ARN. * ``image-id`` - The ID of the image used to launch the instance. * ``instance-id`` - The ID of the instance. * ``instance-lifecycle`` - Indicates whether this is a Spot Instance or a Scheduled Instance (``spot`` | ``scheduled`` ). * ``instance-state-code`` - The state of the instance, as a 16-bit unsigned integer. The high byte is used for internal purposes and should be ignored. The low byte is set based on the state represented. The valid values are: 0 (pending), 16 (running), 32 (shutting-down), 48 (terminated), 64 (stopping), and 80 (stopped). * ``instance-state-name`` - The state of the instance (``pending`` | ``running`` | ``shutting-down`` | ``terminated`` | ``stopping`` | ``stopped`` ). * ``instance-type`` - The type of instance (for example, ``t2.micro`` ). * ``instance.group-id`` - The ID of the security group for the instance. * ``instance.group-name`` - The name of the security group for the instance. * ``ip-address`` - The public IPv4 address of the instance. * ``kernel-id`` - The kernel ID. * ``key-name`` - The name of the key pair used when the instance was launched. * ``launch-index`` - When launching multiple instances, this is the index for the instance in the launch group (for example, 0, 1, 2, and so on). * ``launch-time`` - The time when the instance was launched. * ``monitoring-state`` - Indicates whether detailed monitoring is enabled (``disabled`` | ``enabled`` ). * ``network-interface.addresses.private-ip-address`` - The private IPv4 address associated with the network interface. * ``network-interface.addresses.primary`` - Specifies whether the IPv4 address of the network interface is the primary private IPv4 address. * ``network-interface.addresses.association.public-ip`` - The ID of the association of an Elastic IP address (IPv4) with a network interface. * ``network-interface.addresses.association.ip-owner-id`` - The owner ID of the private IPv4 address associated with the network interface. * ``network-interface.association.public-ip`` - The address of the Elastic IP address (IPv4) bound to the network interface. * ``network-interface.association.ip-owner-id`` - The owner of the Elastic IP address (IPv4) associated with the network interface. * ``network-interface.association.allocation-id`` - The allocation ID returned when you allocated the Elastic IP address (IPv4) for your network interface. * ``network-interface.association.association-id`` - The association ID returned when the network interface was associated with an IPv4 address. * ``network-interface.attachment.attachment-id`` - The ID of the interface attachment. * ``network-interface.attachment.instance-id`` - The ID of the instance to which the network interface is attached. * ``network-interface.attachment.instance-owner-id`` - The owner ID of the instance to which the network interface is attached. * ``network-interface.attachment.device-index`` - The device index to which the network interface is attached. * ``network-interface.attachment.status`` - The status of the attachment (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``network-interface.attachment.attach-time`` - The time that the network interface was attached to an instance. * ``network-interface.attachment.delete-on-termination`` - Specifies whether the attachment is deleted when an instance is terminated. * ``network-interface.availability-zone`` - The Availability Zone for the network interface. * ``network-interface.description`` - The description of the network interface. * ``network-interface.group-id`` - The ID of a security group associated with the network interface. * ``network-interface.group-name`` - The name of a security group associated with the network interface. * ``network-interface.ipv6-addresses.ipv6-address`` - The IPv6 address associated with the network interface. * ``network-interface.mac-address`` - The MAC address of the network interface. * ``network-interface.network-interface-id`` - The ID of the network interface. * ``network-interface.owner-id`` - The ID of the owner of the network interface. * ``network-interface.private-dns-name`` - The private DNS name of the network interface. * ``network-interface.requester-id`` - The requester ID for the network interface. * ``network-interface.requester-managed`` - Indicates whether the network interface is being managed by AWS. * ``network-interface.status`` - The status of the network interface (``available`` ) | ``in-use`` ). * ``network-interface.source-dest-check`` - Whether the network interface performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the network interface to perform network address translation (NAT) in your VPC. * ``network-interface.subnet-id`` - The ID of the subnet for the network interface. * ``network-interface.vpc-id`` - The ID of the VPC for the network interface. * ``owner-id`` - The AWS account ID of the instance owner. * ``placement-group-name`` - The name of the placement group for the instance. * ``placement-partition-number`` - The partition in which the instance is located. * ``platform`` - The platform. To list only Windows instances, use ``windows`` . * ``private-dns-name`` - The private IPv4 DNS name of the instance. * ``private-ip-address`` - The private IPv4 address of the instance. * ``product-code`` - The product code associated with the AMI used to launch the instance. * ``product-code.type`` - The type of product code (``devpay`` | ``marketplace`` ). * ``ramdisk-id`` - The RAM disk ID. * ``reason`` - The reason for the current state of the instance (for example, shows \"User Initiated [date]\" when you stop or terminate the instance). Similar to the state-reason-code filter. * ``requester-id`` - The ID of the entity that launched the instance on your behalf (for example, AWS Management Console, Auto Scaling, and so on). * ``reservation-id`` - The ID of the instance\'s reservation. A reservation ID is created any time you launch an instance. A reservation ID has a one-to-one relationship with an instance launch request, but can be associated with more than one instance if you launch multiple instances using the same launch request. For example, if you launch one instance, you get one reservation ID. If you launch ten instances using the same launch request, you also get one reservation ID. * ``root-device-name`` - The device name of the root device volume (for example, ``/dev/sda1`` ). * ``root-device-type`` - The type of the root device volume (``ebs`` | ``instance-store`` ). * ``source-dest-check`` - Indicates whether the instance performs source/destination checking. A value of ``true`` means that checking is enabled, and ``false`` means that checking is disabled. The value must be ``false`` for the instance to perform network address translation (NAT) in your VPC. * ``spot-instance-request-id`` - The ID of the Spot Instance request. * ``state-reason-code`` - The reason code for the state change. * ``state-reason-message`` - A message that describes the state change. * ``subnet-id`` - The ID of the subnet for the instance. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources that have a tag with a specific key, regardless of the tag value. * ``tenancy`` - The tenancy of an instance (``dedicated`` | ``default`` | ``host`` ). * ``virtualization-type`` - The virtualization type of the instance (``paravirtual`` | ``hvm`` ). * ``vpc-id`` - The ID of the VPC that the instance is running in. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type InstanceIds: list :param InstanceIds: The instance IDs. Default: Describes all your instances. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type MaxResults: integer :param MaxResults: The maximum number of results to return in a single call. To retrieve the remaining results, make another call with the returned ``NextToken`` value. This value can be between 5 and 1000. You cannot specify this parameter and the instance IDs parameter in the same call. :type NextToken: string :param NextToken: The token to request the next page of results. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class KeyPairExists(Waiter): def wait(self, Filters: List = None, KeyNames: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_key_pairs` every 5 seconds until a successful state is reached. An error is returned after 6 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeKeyPairs>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], KeyNames=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``fingerprint`` - The fingerprint of the key pair. * ``key-name`` - The name of the key pair. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type KeyNames: list :param KeyNames: The key pair names. Default: Describes all your key pairs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 5 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 6 :returns: None """ pass class NatGatewayAvailable(Waiter): def wait(self, Filters: List = None, MaxResults: int = None, NatGatewayIds: List = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_nat_gateways` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeNatGateways>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NatGatewayIds=[ 'string', ], NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``nat-gateway-id`` - The ID of the NAT gateway. * ``state`` - The state of the NAT gateway (``pending`` | ``failed`` | ``available`` | ``deleting`` | ``deleted`` ). * ``subnet-id`` - The ID of the subnet in which the NAT gateway resides. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``vpc-id`` - The ID of the VPC in which the NAT gateway resides. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type MaxResults: integer :param MaxResults: The maximum number of results to return with a single call. To retrieve the remaining results, make another call with the returned ``nextToken`` value. :type NatGatewayIds: list :param NatGatewayIds: One or more NAT gateway IDs. - *(string) --* :type NextToken: string :param NextToken: The token for the next page of results. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class NetworkInterfaceAvailable(Waiter): def wait(self, Filters: List = None, DryRun: bool = None, NetworkInterfaceIds: List = None, NextToken: str = None, MaxResults: int = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_network_interfaces` every 20 seconds until a successful state is reached. An error is returned after 10 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeNetworkInterfaces>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], DryRun=True|False, NetworkInterfaceIds=[ 'string', ], NextToken='string', MaxResults=123, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``addresses.private-ip-address`` - The private IPv4 addresses associated with the network interface. * ``addresses.primary`` - Whether the private IPv4 address is the primary IP address associated with the network interface. * ``addresses.association.public-ip`` - The association ID returned when the network interface was associated with the Elastic IP address (IPv4). * ``addresses.association.owner-id`` - The owner ID of the addresses associated with the network interface. * ``association.association-id`` - The association ID returned when the network interface was associated with an IPv4 address. * ``association.allocation-id`` - The allocation ID returned when you allocated the Elastic IP address (IPv4) for your network interface. * ``association.ip-owner-id`` - The owner of the Elastic IP address (IPv4) associated with the network interface. * ``association.public-ip`` - The address of the Elastic IP address (IPv4) bound to the network interface. * ``association.public-dns-name`` - The public DNS name for the network interface (IPv4). * ``attachment.attachment-id`` - The ID of the interface attachment. * ``attachment.attach.time`` - The time that the network interface was attached to an instance. * ``attachment.delete-on-termination`` - Indicates whether the attachment is deleted when an instance is terminated. * ``attachment.device-index`` - The device index to which the network interface is attached. * ``attachment.instance-id`` - The ID of the instance to which the network interface is attached. * ``attachment.instance-owner-id`` - The owner ID of the instance to which the network interface is attached. * ``attachment.nat-gateway-id`` - The ID of the NAT gateway to which the network interface is attached. * ``attachment.status`` - The status of the attachment (``attaching`` | ``attached`` | ``detaching`` | ``detached`` ). * ``availability-zone`` - The Availability Zone of the network interface. * ``description`` - The description of the network interface. * ``group-id`` - The ID of a security group associated with the network interface. * ``group-name`` - The name of a security group associated with the network interface. * ``ipv6-addresses.ipv6-address`` - An IPv6 address associated with the network interface. * ``mac-address`` - The MAC address of the network interface. * ``network-interface-id`` - The ID of the network interface. * ``owner-id`` - The AWS account ID of the network interface owner. * ``private-ip-address`` - The private IPv4 address or addresses of the network interface. * ``private-dns-name`` - The private DNS name of the network interface (IPv4). * ``requester-id`` - The ID of the entity that launched the instance on your behalf (for example, AWS Management Console, Auto Scaling, and so on). * ``requester-managed`` - Indicates whether the network interface is being managed by an AWS service (for example, AWS Management Console, Auto Scaling, and so on). * ``source-dest-check`` - Indicates whether the network interface performs source/destination checking. A value of ``true`` means checking is enabled, and ``false`` means checking is disabled. The value must be ``false`` for the network interface to perform network address translation (NAT) in your VPC. * ``status`` - The status of the network interface. If the network interface is not attached to an instance, the status is ``available`` ; if a network interface is attached to an instance the status is ``in-use`` . * ``subnet-id`` - The ID of the subnet for the network interface. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``vpc-id`` - The ID of the VPC for the network interface. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type NetworkInterfaceIds: list :param NetworkInterfaceIds: One or more network interface IDs. Default: Describes all your network interfaces. - *(string) --* :type NextToken: string :param NextToken: The token to retrieve the next page of results. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this request. The request returns a token that you can specify in a subsequent call to get the next set of results. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 20 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 10 :returns: None """ pass class PasswordDataAvailable(Waiter): def wait(self, InstanceId: str, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.get_password_data` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/GetPasswordData>`_ **Request Syntax** :: waiter.wait( InstanceId='string', DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type InstanceId: string :param InstanceId: **[REQUIRED]** The ID of the Windows instance. :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class SnapshotCompleted(Waiter): def wait(self, Filters: List = None, MaxResults: int = None, NextToken: str = None, OwnerIds: List = None, RestorableByUserIds: List = None, SnapshotIds: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_snapshots` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeSnapshots>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string', OwnerIds=[ 'string', ], RestorableByUserIds=[ 'string', ], SnapshotIds=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``description`` - A description of the snapshot. * ``encrypted`` - Indicates whether the snapshot is encrypted (``true`` | ``false`` ) * ``owner-alias`` - Value from an Amazon-maintained list (``amazon`` | ``self`` | ``all`` | ``aws-marketplace`` | ``microsoft`` ) of snapshot owners. Not to be confused with the user-configured AWS account alias, which is set from the IAM console. * ``owner-id`` - The ID of the AWS account that owns the snapshot. * ``progress`` - The progress of the snapshot, as a percentage (for example, 80%). * ``snapshot-id`` - The snapshot ID. * ``start-time`` - The time stamp when the snapshot was initiated. * ``status`` - The status of the snapshot (``pending`` | ``completed`` | ``error`` ). * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``volume-id`` - The ID of the volume the snapshot is for. * ``volume-size`` - The size of the volume, in GiB. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type MaxResults: integer :param MaxResults: The maximum number of snapshot results returned by ``DescribeSnapshots`` in paginated output. When this parameter is used, ``DescribeSnapshots`` only returns ``MaxResults`` results in a single page along with a ``NextToken`` response element. The remaining results of the initial request can be seen by sending another ``DescribeSnapshots`` request with the returned ``NextToken`` value. This value can be between 5 and 1000; if ``MaxResults`` is given a value larger than 1000, only 1000 results are returned. If this parameter is not used, then ``DescribeSnapshots`` returns all results. You cannot specify this parameter and the snapshot IDs parameter in the same request. :type NextToken: string :param NextToken: The ``NextToken`` value returned from a previous paginated ``DescribeSnapshots`` request where ``MaxResults`` 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. This value is ``null`` when there are no more results to return. :type OwnerIds: list :param OwnerIds: Describes the snapshots owned by these owners. - *(string) --* :type RestorableByUserIds: list :param RestorableByUserIds: The IDs of the AWS accounts that can create volumes from the snapshot. - *(string) --* :type SnapshotIds: list :param SnapshotIds: The snapshot IDs. Default: Describes the snapshots for which you have create volume permissions. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class SpotInstanceRequestFulfilled(Waiter): def wait(self, Filters: List = None, DryRun: bool = None, SpotInstanceRequestIds: List = None, NextToken: str = None, MaxResults: int = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_spot_instance_requests` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeSpotInstanceRequests>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], DryRun=True|False, SpotInstanceRequestIds=[ 'string', ], NextToken='string', MaxResults=123, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``availability-zone-group`` - The Availability Zone group. * ``create-time`` - The time stamp when the Spot Instance request was created. * ``fault-code`` - The fault code related to the request. * ``fault-message`` - The fault message related to the request. * ``instance-id`` - The ID of the instance that fulfilled the request. * ``launch-group`` - The Spot Instance launch group. * ``launch.block-device-mapping.delete-on-termination`` - Indicates whether the EBS volume is deleted on instance termination. * ``launch.block-device-mapping.device-name`` - The device name for the volume in the block device mapping (for example, ``/dev/sdh`` or ``xvdh`` ). * ``launch.block-device-mapping.snapshot-id`` - The ID of the snapshot for the EBS volume. * ``launch.block-device-mapping.volume-size`` - The size of the EBS volume, in GiB. * ``launch.block-device-mapping.volume-type`` - The type of EBS volume: ``gp2`` for General Purpose SSD, ``io1`` for Provisioned IOPS SSD, ``st1`` for Throughput Optimized HDD, ``sc1`` for Cold HDD, or ``standard`` for Magnetic. * ``launch.group-id`` - The ID of the security group for the instance. * ``launch.group-name`` - The name of the security group for the instance. * ``launch.image-id`` - The ID of the AMI. * ``launch.instance-type`` - The type of instance (for example, ``m3.medium`` ). * ``launch.kernel-id`` - The kernel ID. * ``launch.key-name`` - The name of the key pair the instance launched with. * ``launch.monitoring-enabled`` - Whether detailed monitoring is enabled for the Spot Instance. * ``launch.ramdisk-id`` - The RAM disk ID. * ``launched-availability-zone`` - The Availability Zone in which the request is launched. * ``network-interface.addresses.primary`` - Indicates whether the IP address is the primary private IP address. * ``network-interface.delete-on-termination`` - Indicates whether the network interface is deleted when the instance is terminated. * ``network-interface.description`` - A description of the network interface. * ``network-interface.device-index`` - The index of the device for the network interface attachment on the instance. * ``network-interface.group-id`` - The ID of the security group associated with the network interface. * ``network-interface.network-interface-id`` - The ID of the network interface. * ``network-interface.private-ip-address`` - The primary private IP address of the network interface. * ``network-interface.subnet-id`` - The ID of the subnet for the instance. * ``product-description`` - The product description associated with the instance (``Linux/UNIX`` | ``Windows`` ). * ``spot-instance-request-id`` - The Spot Instance request ID. * ``spot-price`` - The maximum hourly price for any Spot Instance launched to fulfill the request. * ``state`` - The state of the Spot Instance request (``open`` | ``active`` | ``closed`` | ``cancelled`` | ``failed`` ). Spot request status information can help you track your Amazon EC2 Spot Instance requests. For more information, see `Spot Request Status <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/spot-bid-status.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . * ``status-code`` - The short code describing the most recent evaluation of your Spot Instance request. * ``status-message`` - The message explaining the status of the Spot Instance request. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``type`` - The type of Spot Instance request (``one-time`` | ``persistent`` ). * ``valid-from`` - The start date of the request. * ``valid-until`` - The end date of the request. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type SpotInstanceRequestIds: list :param SpotInstanceRequestIds: One or more Spot Instance request IDs. - *(string) --* :type NextToken: string :param NextToken: The token to request the next set of results. This value is ``null`` when there are no more results to return. :type MaxResults: integer :param MaxResults: The maximum number of results to return in a single call. Specify a value between 5 and 1000. To retrieve the remaining results, make another call with the returned ``NextToken`` value. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class SubnetAvailable(Waiter): def wait(self, Filters: List = None, SubnetIds: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_subnets` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeSubnets>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], SubnetIds=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``availability-zone`` - The Availability Zone for the subnet. You can also use ``availabilityZone`` as the filter name. * ``availability-zone-id`` - The ID of the Availability Zone for the subnet. You can also use ``availabilityZoneId`` as the filter name. * ``available-ip-address-count`` - The number of IPv4 addresses in the subnet that are available. * ``cidr-block`` - The IPv4 CIDR block of the subnet. The CIDR block you specify must exactly match the subnet\'s CIDR block for information to be returned for the subnet. You can also use ``cidr`` or ``cidrBlock`` as the filter names. * ``default-for-az`` - Indicates whether this is the default subnet for the Availability Zone. You can also use ``defaultForAz`` as the filter name. * ``ipv6-cidr-block-association.ipv6-cidr-block`` - An IPv6 CIDR block associated with the subnet. * ``ipv6-cidr-block-association.association-id`` - An association ID for an IPv6 CIDR block associated with the subnet. * ``ipv6-cidr-block-association.state`` - The state of an IPv6 CIDR block associated with the subnet. * ``owner-id`` - The ID of the AWS account that owns the subnet. * ``state`` - The state of the subnet (``pending`` | ``available`` ). * ``subnet-arn`` - The Amazon Resource Name (ARN) of the subnet. * ``subnet-id`` - The ID of the subnet. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``vpc-id`` - The ID of the VPC for the subnet. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type SubnetIds: list :param SubnetIds: One or more subnet IDs. Default: Describes all your subnets. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class SystemStatusOk(Waiter): def wait(self, Filters: List = None, InstanceIds: List = None, MaxResults: int = None, NextToken: str = None, DryRun: bool = None, IncludeAllInstances: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_instance_status` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeInstanceStatus>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], InstanceIds=[ 'string', ], MaxResults=123, NextToken='string', DryRun=True|False, IncludeAllInstances=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``availability-zone`` - The Availability Zone of the instance. * ``event.code`` - The code for the scheduled event (``instance-reboot`` | ``system-reboot`` | ``system-maintenance`` | ``instance-retirement`` | ``instance-stop`` ). * ``event.description`` - A description of the event. * ``event.instance-event-id`` - The ID of the event whose date and time you are modifying. * ``event.not-after`` - The latest end time for the scheduled event (for example, ``2014-09-15T17:15:20.000Z`` ). * ``event.not-before`` - The earliest start time for the scheduled event (for example, ``2014-09-15T17:15:20.000Z`` ). * ``event.not-before-deadline`` - The deadline for starting the event (for example, ``2014-09-15T17:15:20.000Z`` ). * ``instance-state-code`` - The code for the instance state, as a 16-bit unsigned integer. The high byte is used for internal purposes and should be ignored. The low byte is set based on the state represented. The valid values are 0 (pending), 16 (running), 32 (shutting-down), 48 (terminated), 64 (stopping), and 80 (stopped). * ``instance-state-name`` - The state of the instance (``pending`` | ``running`` | ``shutting-down`` | ``terminated`` | ``stopping`` | ``stopped`` ). * ``instance-status.reachability`` - Filters on instance status where the name is ``reachability`` (``passed`` | ``failed`` | ``initializing`` | ``insufficient-data`` ). * ``instance-status.status`` - The status of the instance (``ok`` | ``impaired`` | ``initializing`` | ``insufficient-data`` | ``not-applicable`` ). * ``system-status.reachability`` - Filters on system status where the name is ``reachability`` (``passed`` | ``failed`` | ``initializing`` | ``insufficient-data`` ). * ``system-status.status`` - The system status of the instance (``ok`` | ``impaired`` | ``initializing`` | ``insufficient-data`` | ``not-applicable`` ). - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type InstanceIds: list :param InstanceIds: The instance IDs. Default: Describes all your instances. Constraints: Maximum 100 explicitly specified instance IDs. - *(string) --* :type MaxResults: integer :param MaxResults: The maximum number of results to return in a single call. To retrieve the remaining results, make another call with the returned ``NextToken`` value. This value can be between 5 and 1000. You cannot specify this parameter and the instance IDs parameter in the same call. :type NextToken: string :param NextToken: The token to retrieve the next page of results. :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type IncludeAllInstances: boolean :param IncludeAllInstances: When ``true`` , includes the health status for all instances. When ``false`` , includes the health status for running instances only. Default: ``false`` :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VolumeAvailable(Waiter): def wait(self, Filters: List = None, VolumeIds: List = None, DryRun: bool = None, MaxResults: int = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_volumes` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVolumes>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], VolumeIds=[ 'string', ], DryRun=True|False, MaxResults=123, NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``attachment.attach-time`` - The time stamp when the attachment initiated. * ``attachment.delete-on-termination`` - Whether the volume is deleted on instance termination. * ``attachment.device`` - The device name specified in the block device mapping (for example, ``/dev/sda1`` ). * ``attachment.instance-id`` - The ID of the instance the volume is attached to. * ``attachment.status`` - The attachment state (``attaching`` | ``attached`` | ``detaching`` ). * ``availability-zone`` - The Availability Zone in which the volume was created. * ``create-time`` - The time stamp when the volume was created. * ``encrypted`` - Indicates whether the volume is encrypted (``true`` | ``false`` ) * ``size`` - The size of the volume, in GiB. * ``snapshot-id`` - The snapshot from which the volume was created. * ``status`` - The status of the volume (``creating`` | ``available`` | ``in-use`` | ``deleting`` | ``deleted`` | ``error`` ). * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``volume-id`` - The volume ID. * ``volume-type`` - The Amazon EBS volume type. This can be ``gp2`` for General Purpose SSD, ``io1`` for Provisioned IOPS SSD, ``st1`` for Throughput Optimized HDD, ``sc1`` for Cold HDD, or ``standard`` for Magnetic volumes. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type VolumeIds: list :param VolumeIds: The volume IDs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type MaxResults: integer :param MaxResults: The maximum number of volume results returned by ``DescribeVolumes`` in paginated output. When this parameter is used, ``DescribeVolumes`` only returns ``MaxResults`` results in a single page along with a ``NextToken`` response element. The remaining results of the initial request can be seen by sending another ``DescribeVolumes`` request with the returned ``NextToken`` value. This value can be between 5 and 500; if ``MaxResults`` is given a value larger than 500, only 500 results are returned. If this parameter is not used, then ``DescribeVolumes`` returns all results. You cannot specify this parameter and the volume IDs parameter in the same request. :type NextToken: string :param NextToken: The ``NextToken`` value returned from a previous paginated ``DescribeVolumes`` request where ``MaxResults`` 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. This value is ``null`` when there are no more results to return. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VolumeDeleted(Waiter): def wait(self, Filters: List = None, VolumeIds: List = None, DryRun: bool = None, MaxResults: int = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_volumes` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVolumes>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], VolumeIds=[ 'string', ], DryRun=True|False, MaxResults=123, NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``attachment.attach-time`` - The time stamp when the attachment initiated. * ``attachment.delete-on-termination`` - Whether the volume is deleted on instance termination. * ``attachment.device`` - The device name specified in the block device mapping (for example, ``/dev/sda1`` ). * ``attachment.instance-id`` - The ID of the instance the volume is attached to. * ``attachment.status`` - The attachment state (``attaching`` | ``attached`` | ``detaching`` ). * ``availability-zone`` - The Availability Zone in which the volume was created. * ``create-time`` - The time stamp when the volume was created. * ``encrypted`` - Indicates whether the volume is encrypted (``true`` | ``false`` ) * ``size`` - The size of the volume, in GiB. * ``snapshot-id`` - The snapshot from which the volume was created. * ``status`` - The status of the volume (``creating`` | ``available`` | ``in-use`` | ``deleting`` | ``deleted`` | ``error`` ). * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``volume-id`` - The volume ID. * ``volume-type`` - The Amazon EBS volume type. This can be ``gp2`` for General Purpose SSD, ``io1`` for Provisioned IOPS SSD, ``st1`` for Throughput Optimized HDD, ``sc1`` for Cold HDD, or ``standard`` for Magnetic volumes. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type VolumeIds: list :param VolumeIds: The volume IDs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type MaxResults: integer :param MaxResults: The maximum number of volume results returned by ``DescribeVolumes`` in paginated output. When this parameter is used, ``DescribeVolumes`` only returns ``MaxResults`` results in a single page along with a ``NextToken`` response element. The remaining results of the initial request can be seen by sending another ``DescribeVolumes`` request with the returned ``NextToken`` value. This value can be between 5 and 500; if ``MaxResults`` is given a value larger than 500, only 500 results are returned. If this parameter is not used, then ``DescribeVolumes`` returns all results. You cannot specify this parameter and the volume IDs parameter in the same request. :type NextToken: string :param NextToken: The ``NextToken`` value returned from a previous paginated ``DescribeVolumes`` request where ``MaxResults`` 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. This value is ``null`` when there are no more results to return. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VolumeInUse(Waiter): def wait(self, Filters: List = None, VolumeIds: List = None, DryRun: bool = None, MaxResults: int = None, NextToken: str = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_volumes` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVolumes>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], VolumeIds=[ 'string', ], DryRun=True|False, MaxResults=123, NextToken='string', WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: The filters. * ``attachment.attach-time`` - The time stamp when the attachment initiated. * ``attachment.delete-on-termination`` - Whether the volume is deleted on instance termination. * ``attachment.device`` - The device name specified in the block device mapping (for example, ``/dev/sda1`` ). * ``attachment.instance-id`` - The ID of the instance the volume is attached to. * ``attachment.status`` - The attachment state (``attaching`` | ``attached`` | ``detaching`` ). * ``availability-zone`` - The Availability Zone in which the volume was created. * ``create-time`` - The time stamp when the volume was created. * ``encrypted`` - Indicates whether the volume is encrypted (``true`` | ``false`` ) * ``size`` - The size of the volume, in GiB. * ``snapshot-id`` - The snapshot from which the volume was created. * ``status`` - The status of the volume (``creating`` | ``available`` | ``in-use`` | ``deleting`` | ``deleted`` | ``error`` ). * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``volume-id`` - The volume ID. * ``volume-type`` - The Amazon EBS volume type. This can be ``gp2`` for General Purpose SSD, ``io1`` for Provisioned IOPS SSD, ``st1`` for Throughput Optimized HDD, ``sc1`` for Cold HDD, or ``standard`` for Magnetic volumes. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type VolumeIds: list :param VolumeIds: The volume IDs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type MaxResults: integer :param MaxResults: The maximum number of volume results returned by ``DescribeVolumes`` in paginated output. When this parameter is used, ``DescribeVolumes`` only returns ``MaxResults`` results in a single page along with a ``NextToken`` response element. The remaining results of the initial request can be seen by sending another ``DescribeVolumes`` request with the returned ``NextToken`` value. This value can be between 5 and 500; if ``MaxResults`` is given a value larger than 500, only 500 results are returned. If this parameter is not used, then ``DescribeVolumes`` returns all results. You cannot specify this parameter and the volume IDs parameter in the same request. :type NextToken: string :param NextToken: The ``NextToken`` value returned from a previous paginated ``DescribeVolumes`` request where ``MaxResults`` 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. This value is ``null`` when there are no more results to return. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VpcAvailable(Waiter): def wait(self, Filters: List = None, VpcIds: List = None, DryRun: bool = None, NextToken: str = None, MaxResults: int = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_vpcs` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVpcs>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], VpcIds=[ 'string', ], DryRun=True|False, NextToken='string', MaxResults=123, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``cidr`` - The primary IPv4 CIDR block of the VPC. The CIDR block you specify must exactly match the VPC\'s CIDR block for information to be returned for the VPC. Must contain the slash followed by one or two digits (for example, ``/28`` ). * ``cidr-block-association.cidr-block`` - An IPv4 CIDR block associated with the VPC. * ``cidr-block-association.association-id`` - The association ID for an IPv4 CIDR block associated with the VPC. * ``cidr-block-association.state`` - The state of an IPv4 CIDR block associated with the VPC. * ``dhcp-options-id`` - The ID of a set of DHCP options. * ``ipv6-cidr-block-association.ipv6-cidr-block`` - An IPv6 CIDR block associated with the VPC. * ``ipv6-cidr-block-association.association-id`` - The association ID for an IPv6 CIDR block associated with the VPC. * ``ipv6-cidr-block-association.state`` - The state of an IPv6 CIDR block associated with the VPC. * ``isDefault`` - Indicates whether the VPC is the default VPC. * ``owner-id`` - The ID of the AWS account that owns the VPC. * ``state`` - The state of the VPC (``pending`` | ``available`` ). * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``vpc-id`` - The ID of the VPC. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type VpcIds: list :param VpcIds: One or more VPC IDs. Default: Describes all your VPCs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type NextToken: string :param NextToken: The token for the next page of results. :type MaxResults: integer :param MaxResults: The maximum number of results to return with a single call. To retrieve the remaining results, make another call with the returned ``nextToken`` value. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VpcExists(Waiter): def wait(self, Filters: List = None, VpcIds: List = None, DryRun: bool = None, NextToken: str = None, MaxResults: int = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_vpcs` every 1 seconds until a successful state is reached. An error is returned after 5 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVpcs>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], VpcIds=[ 'string', ], DryRun=True|False, NextToken='string', MaxResults=123, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``cidr`` - The primary IPv4 CIDR block of the VPC. The CIDR block you specify must exactly match the VPC\'s CIDR block for information to be returned for the VPC. Must contain the slash followed by one or two digits (for example, ``/28`` ). * ``cidr-block-association.cidr-block`` - An IPv4 CIDR block associated with the VPC. * ``cidr-block-association.association-id`` - The association ID for an IPv4 CIDR block associated with the VPC. * ``cidr-block-association.state`` - The state of an IPv4 CIDR block associated with the VPC. * ``dhcp-options-id`` - The ID of a set of DHCP options. * ``ipv6-cidr-block-association.ipv6-cidr-block`` - An IPv6 CIDR block associated with the VPC. * ``ipv6-cidr-block-association.association-id`` - The association ID for an IPv6 CIDR block associated with the VPC. * ``ipv6-cidr-block-association.state`` - The state of an IPv6 CIDR block associated with the VPC. * ``isDefault`` - Indicates whether the VPC is the default VPC. * ``owner-id`` - The ID of the AWS account that owns the VPC. * ``state`` - The state of the VPC (``pending`` | ``available`` ). * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``vpc-id`` - The ID of the VPC. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type VpcIds: list :param VpcIds: One or more VPC IDs. Default: Describes all your VPCs. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type NextToken: string :param NextToken: The token for the next page of results. :type MaxResults: integer :param MaxResults: The maximum number of results to return with a single call. To retrieve the remaining results, make another call with the returned ``nextToken`` value. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 1 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 5 :returns: None """ pass class VpcPeeringConnectionDeleted(Waiter): def wait(self, Filters: List = None, DryRun: bool = None, VpcPeeringConnectionIds: List = None, NextToken: str = None, MaxResults: int = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_vpc_peering_connections` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVpcPeeringConnections>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], DryRun=True|False, VpcPeeringConnectionIds=[ 'string', ], NextToken='string', MaxResults=123, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``accepter-vpc-info.cidr-block`` - The IPv4 CIDR block of the accepter VPC. * ``accepter-vpc-info.owner-id`` - The AWS account ID of the owner of the accepter VPC. * ``accepter-vpc-info.vpc-id`` - The ID of the accepter VPC. * ``expiration-time`` - The expiration date and time for the VPC peering connection. * ``requester-vpc-info.cidr-block`` - The IPv4 CIDR block of the requester\'s VPC. * ``requester-vpc-info.owner-id`` - The AWS account ID of the owner of the requester VPC. * ``requester-vpc-info.vpc-id`` - The ID of the requester VPC. * ``status-code`` - The status of the VPC peering connection (``pending-acceptance`` | ``failed`` | ``expired`` | ``provisioning`` | ``active`` | ``deleting`` | ``deleted`` | ``rejected`` ). * ``status-message`` - A message that provides more information about the status of the VPC peering connection, if applicable. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``vpc-peering-connection-id`` - The ID of the VPC peering connection. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type VpcPeeringConnectionIds: list :param VpcPeeringConnectionIds: One or more VPC peering connection IDs. Default: Describes all your VPC peering connections. - *(string) --* :type NextToken: string :param NextToken: The token for the next page of results. :type MaxResults: integer :param MaxResults: The maximum number of results to return with a single call. To retrieve the remaining results, make another call with the returned ``nextToken`` value. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VpcPeeringConnectionExists(Waiter): def wait(self, Filters: List = None, DryRun: bool = None, VpcPeeringConnectionIds: List = None, NextToken: str = None, MaxResults: int = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_vpc_peering_connections` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVpcPeeringConnections>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], DryRun=True|False, VpcPeeringConnectionIds=[ 'string', ], NextToken='string', MaxResults=123, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``accepter-vpc-info.cidr-block`` - The IPv4 CIDR block of the accepter VPC. * ``accepter-vpc-info.owner-id`` - The AWS account ID of the owner of the accepter VPC. * ``accepter-vpc-info.vpc-id`` - The ID of the accepter VPC. * ``expiration-time`` - The expiration date and time for the VPC peering connection. * ``requester-vpc-info.cidr-block`` - The IPv4 CIDR block of the requester\'s VPC. * ``requester-vpc-info.owner-id`` - The AWS account ID of the owner of the requester VPC. * ``requester-vpc-info.vpc-id`` - The ID of the requester VPC. * ``status-code`` - The status of the VPC peering connection (``pending-acceptance`` | ``failed`` | ``expired`` | ``provisioning`` | ``active`` | ``deleting`` | ``deleted`` | ``rejected`` ). * ``status-message`` - A message that provides more information about the status of the VPC peering connection, if applicable. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``vpc-peering-connection-id`` - The ID of the VPC peering connection. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type VpcPeeringConnectionIds: list :param VpcPeeringConnectionIds: One or more VPC peering connection IDs. Default: Describes all your VPC peering connections. - *(string) --* :type NextToken: string :param NextToken: The token for the next page of results. :type MaxResults: integer :param MaxResults: The maximum number of results to return with a single call. To retrieve the remaining results, make another call with the returned ``nextToken`` value. :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VpnConnectionAvailable(Waiter): def wait(self, Filters: List = None, VpnConnectionIds: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_vpn_connections` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVpnConnections>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], VpnConnectionIds=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``customer-gateway-configuration`` - The configuration information for the customer gateway. * ``customer-gateway-id`` - The ID of a customer gateway associated with the VPN connection. * ``state`` - The state of the VPN connection (``pending`` | ``available`` | ``deleting`` | ``deleted`` ). * ``option.static-routes-only`` - Indicates whether the connection has static routes only. Used for devices that do not support Border Gateway Protocol (BGP). * ``route.destination-cidr-block`` - The destination CIDR block. This corresponds to the subnet used in a customer data center. * ``bgp-asn`` - The BGP Autonomous System Number (ASN) associated with a BGP device. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``type`` - The type of VPN connection. Currently the only supported type is ``ipsec.1`` . * ``vpn-connection-id`` - The ID of the VPN connection. * ``vpn-gateway-id`` - The ID of a virtual private gateway associated with the VPN connection. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type VpnConnectionIds: list :param VpnConnectionIds: One or more VPN connection IDs. Default: Describes your VPN connections. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass class VpnConnectionDeleted(Waiter): def wait(self, Filters: List = None, VpnConnectionIds: List = None, DryRun: bool = None, WaiterConfig: Dict = None): """ Polls :py:meth:`EC2.Client.describe_vpn_connections` every 15 seconds until a successful state is reached. An error is returned after 40 failed checks. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/ec2-2016-11-15/DescribeVpnConnections>`_ **Request Syntax** :: waiter.wait( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], VpnConnectionIds=[ 'string', ], DryRun=True|False, WaiterConfig={ 'Delay': 123, 'MaxAttempts': 123 } ) :type Filters: list :param Filters: One or more filters. * ``customer-gateway-configuration`` - The configuration information for the customer gateway. * ``customer-gateway-id`` - The ID of a customer gateway associated with the VPN connection. * ``state`` - The state of the VPN connection (``pending`` | ``available`` | ``deleting`` | ``deleted`` ). * ``option.static-routes-only`` - Indicates whether the connection has static routes only. Used for devices that do not support Border Gateway Protocol (BGP). * ``route.destination-cidr-block`` - The destination CIDR block. This corresponds to the subnet used in a customer data center. * ``bgp-asn`` - The BGP Autonomous System Number (ASN) associated with a BGP device. * ``tag`` :<key> - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value. For example, to find all resources that have a tag with the key ``Owner`` and the value ``TeamA`` , specify ``tag:Owner`` for the filter name and ``TeamA`` for the filter value. * ``tag-key`` - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value. * ``type`` - The type of VPN connection. Currently the only supported type is ``ipsec.1`` . * ``vpn-connection-id`` - The ID of the VPN connection. * ``vpn-gateway-id`` - The ID of a virtual private gateway associated with the VPN connection. - *(dict) --* A filter name and value pair that is used to return a more specific list of results from a describe operation. Filters can be used to match a set of resources by specific criteria, such as tags, attributes, or IDs. The filters supported by a describe operation are documented with the describe operation. For example: * DescribeAvailabilityZones * DescribeImages * DescribeInstances * DescribeKeyPairs * DescribeSecurityGroups * DescribeSnapshots * DescribeSubnets * DescribeTags * DescribeVolumes * DescribeVpcs - **Name** *(string) --* The name of the filter. Filter names are case-sensitive. - **Values** *(list) --* The filter values. Filter values are case-sensitive. - *(string) --* :type VpnConnectionIds: list :param VpnConnectionIds: One or more VPN connection IDs. Default: Describes your VPN connections. - *(string) --* :type DryRun: boolean :param DryRun: Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is ``DryRunOperation`` . Otherwise, it is ``UnauthorizedOperation`` . :type WaiterConfig: dict :param WaiterConfig: A dictionary that provides parameters to control waiting behavior. - **Delay** *(integer) --* The amount of time in seconds to wait between attempts. Default: 15 - **MaxAttempts** *(integer) --* The maximum number of attempts to be made. Default: 40 :returns: None """ pass

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exaslct_src/cli/__init__.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

null

exaslct_src/cli/__init__.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

1

2019-05-06T07:36:11.000Z

exaslct_src/cli/__init__.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

1

2019-05-03T08:49:29.000Z

from exaslct_src.cli.cli import cli from exaslct_src.cli.commands import *

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Python

mutation_loc_figures.py

martynaut/mirnome-mutations

2bcee735a3620a0ae6fc91a57500f19b8851ff60

[ "MIT" ]

null

mutation_loc_figures.py

martynaut/mirnome-mutations

2bcee735a3620a0ae6fc91a57500f19b8851ff60

[ "MIT" ]

1

2021-09-10T12:07:49.000Z

2021-09-24T07:04:02.000Z

mutation_loc_figures.py

martynaut/mirnome-mutations

2bcee735a3620a0ae6fc91a57500f19b8851ff60

[ "MIT" ]

null

import os import pandas as pd import matplotlib import click from matplotlib import rc from matplotlib import lines # matplotlib.use('TkAgg') import matplotlib.pyplot as plt import seaborn as sns import numpy as np import gc plt.rcParams['svg.fonttype'] = 'none' image_path = 'reference_files/primirna_background.tiff' im = plt.imread(image_path) SMALL_SIZE = 18 MEDIUM_SIZE = 20 BIGGER_SIZE = 22 rc('font', size=MEDIUM_SIZE) # controls default text sizes rc('axes', titlesize=MEDIUM_SIZE) # fontsize of the axes title rc('axes', labelsize=MEDIUM_SIZE) # fontsize of the x and y labels rc('xtick', labelsize=MEDIUM_SIZE) # fontsize of the tick labels rc('ytick', labelsize=MEDIUM_SIZE) # fontsize of the tick labels rc('legend', fontsize=SMALL_SIZE) # legend fontsize rc('figure', titlesize=BIGGER_SIZE) # fontsize of the figure title def create_plot(data_df, output_name, mutations=0, genes=0, mirna_type='both'): df_plot_5, loop_value = prepare_data_5p(data_df) df_plot_3 = prepare_data_3p(data_df) max_value = max(df_plot_5['pos'].max(), df_plot_3['pos'].max()) rc("pdf", fonttype=42) sns.set_style(style='white') palette = {'flanking-5': 'grey', 'flanking-3': 'grey', 'pre-seed': '#5481A6', 'seed': 'darkblue', 'post-seed': '#5481A6', 'loop': 'grey', 'silent-pre': '#5481A6', 'silent-post': '#5481A6', 'silent-seed': '#5481A6' } fig = plt.figure(figsize=(25, 10)) ax = fig.add_axes([0, 0, 1, 1]) ax.axis('off') plt.imshow(im) plt.xticks([]) plt.yticks([]) y_min, y_max = ax.get_ylim() x_min, x_max = ax.get_xlim() plt.text(x_max * 0.92, y_min * 1, str(mutations), horizontalalignment='center', verticalalignment='center', fontdict={'size': '42'}) plt.text(x_max * 0.92, y_min * 1.09, str(genes), horizontalalignment='center', verticalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.89, x_max * 0.95], [y_min * 1.04, y_min * 1.04], lw=0.5, color='black') ax.add_line(line) line.set_clip_on(False) plt.text(x_max * 0.24, y_min * -0.09, 'flanking region', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.02, x_max * 0.46], [y_min * -0.07, y_min * -0.07], lw=0.5, color='grey', alpha=0.8) ax.add_line(line) line.set_clip_on(False) plt.text(x_max * 0.65, y_min * -0.09, 'miRNA', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.47, x_max * 0.83], [y_min * -0.07, y_min * -0.07], lw=0.5, color='#5481A6', alpha=0.8) ax.add_line(line) line.set_clip_on(False) plt.text(x_max * 0.91, y_min * -0.09, 'loop', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.84, x_max * 0.98], [y_min * -0.07, y_min * -0.07], lw=0.5, color='grey', alpha=0.8) ax.add_line(line) line.set_clip_on(False) if mirna_type != '3p': plt.text(x_max * 0.54, y_min * 0, 'seed', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.49, x_max * 0.59], [y_min * 0.03, y_min * 0.03], lw=0.5, color='darkblue', alpha=0.8) ax.add_line(line) line.set_clip_on(False) if mirna_type != '5p': line = lines.Line2D([x_max * 0.675, x_max * 0.775], [y_min * 1.125, y_min * 1.125], lw=0.5, color='darkblue', alpha=0.8) ax.add_line(line) line.set_clip_on(False) plt.text(x_max * 0.725, y_min * 1.195, 'seed', horizontalalignment='center', fontdict={'size': '42'}) if loop_value > 0: plt.text( x_max * 0.92, y_min * 0.6, '+ {} loop\nmutations'.format(loop_value), horizontalalignment='center', verticalalignment='center', fontdict={'size': '30'} ) a = plt.axes([.058, .52, .82, .35]) hue_order = ['flanking-5', 'pre-seed', 'seed', 'post-seed', 'loop'] if mirna_type == '3p': hue_order = ['flanking-5', 'silent-pre', 'silent-seed', 'silent-post', 'loop'] df_plot_5['type'] = df_plot_5['type'].apply( lambda x: 'silent-seed' if x == 'seed' else ( 'silent-pre' if x == 'pre-seed' else ( 'silent-post' if x == 'post-seed' else x ) ) ) labels = [str(x) for x in range(-25, 0)] + \ [str(x) for x in range(1, 23)] + ['+' + str(x) for x in range(1, 4)] labels = ['L' if x == '+4' else x for x in labels] ax = sns.barplot(x="from_start", y="pos", hue="type", data=df_plot_5, dodge=False, hue_order=hue_order, palette=palette, ax=a) for loc in ['right', 'top', 'left', 'bottom']: ax.spines[loc].set_visible(False) ax.set_xlabel('') ax.set_ylabel('') ax.legend(loc='upper right', ncol=2) plt.setp(ax.get_legend().get_texts(), fontsize='18') plt.setp(ax.get_legend().get_title(), fontsize='22') plt.grid(b=True, which='major', axis='y', color='lightgrey', linestyle='-', linewidth=0.75, zorder=2, alpha=0.5) ax.set_xticklabels(labels) for tick in ax.xaxis.get_major_ticks(): tick.label.set_fontsize(30) for tick in ax.yaxis.get_major_ticks(): tick.label.set_fontsize(30) if max_value > 5: plt.yticks(np.arange(0, max_value + 1, np.floor(max_value/3))) plot_limit = max_value + 2 else: plt.yticks(np.arange(0, max_value + 1, 1)) plot_limit = max_value + 1 ax.set_ylim([0, plot_limit]) ax.xaxis.tick_bottom() for label in ax.get_xticklabels(): if label.get_text() not in ['-25', '-20', '-15', '-10', '-5', '1', '5', '10', '15', '20', '+1']: label.set_visible(False) new_width = 0.35 for patch in ax.patches: current_width = patch.get_width() diff = current_width - new_width # we change the bar width patch.set_width(new_width) # we recenter the bar patch.set_x(patch.get_x() + diff * .5) ax.tick_params(axis='both', which='major', pad=8, width=0.5) plt.setp(ax.patches, linewidth=0) ax.get_legend().remove() b = plt.axes([.025, .02, .82, .35], facecolor='w') hue_order = ['flanking-3', 'pre-seed', 'seed', 'post-seed', 'loop'] labels = ['+' + str(x) for x in range(1, 26)][::-1] + [str(x) for x in range(1, 23)][::-1] + \ ['-' + str(x) for x in range(1, 4)] if mirna_type == '5p': hue_order = ['flanking-3', 'silent-pre', 'silent-seed', 'silent-post', 'loop'] df_plot_3['type'] = df_plot_3['type'].apply( lambda x: 'silent-seed' if x == 'seed' else ( 'silent-pre' if x == 'pre-seed' else( 'silent-post' if x == 'post-seed' else x ) ) ) ax = sns.barplot(x="from_start", y="pos", hue="type", data=df_plot_3, dodge=False, hue_order=hue_order, palette=palette, ax=b) for loc in ['right', 'top', 'left', 'bottom']: ax.spines[loc].set_visible(False) ax.set_xlabel('') ax.set_ylabel('') plt.grid(b=True, which='major', axis='y', color='lightgrey', linestyle='-', linewidth=0.75, zorder=1, alpha=0.5) ax.set_xticklabels(labels) if max_value > 5: plt.yticks(np.arange(0, max_value + 1, np.floor(max_value/3))) plot_limit = max_value + 2 else: plt.yticks(np.arange(0, max_value + 1, 1)) plot_limit = max_value + 1 ax.get_legend().remove() ax.set_ylim([plot_limit, 0]) ax.xaxis.tick_top() for tick in ax.xaxis.get_major_ticks(): tick.label2.set_fontsize(30) for tick in ax.yaxis.get_major_ticks(): tick.label.set_fontsize(30) for label in ax.get_xticklabels(): if label.get_text() not in ['+25', '+20', '+15', '+10', '+5', '+1', '1', '5', '10', '15', '20', '-5']: label.set_visible(False) new_width = 0.35 for patch in ax.patches: current_width = patch.get_width() diff = current_width - new_width # we change the bar width patch.set_width(new_width) # we recenter the bar patch.set_x(patch.get_x() + diff * .5) plt.setp(ax.patches, linewidth=0) plt.savefig(output_name, format='svg', dpi=300, transparent=True, bbox_inches='tight') plt.cla() plt.clf() plt.close("all") plt.close(fig) gc.collect() def prepare_data_5p(df_temp): add_loop = df_temp[(df_temp['arm'] == 'loop') & ((df_temp['from_start'] >= 4) & (df_temp['from_end'] <= -4))] add_loop_value = add_loop.shape[0] # add_loop_df = pd.DataFrame([['loop', 'loop', 51, add_loop_value]], columns=['arm', 'type', # 'from_start', # 'pos']) dataframe = df_temp[(df_temp['arm'] == '5p') | ((df_temp['arm'] == 'loop') & (df_temp['from_start'] < 4))].groupby(['arm', 'type', 'from_start'], as_index=False )[['pos']]. \ count()[[ 'arm', 'type', 'from_start', 'pos' ]] dataframe.loc[(dataframe['type'] == 'pre-seed') & (dataframe['arm'] == '5p'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'pre-seed') & (dataframe['arm'] == '5p'), 'from_start'] + 25 dataframe.loc[(dataframe['type'] == 'seed') & (dataframe['arm'] == '5p'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'seed') & (dataframe['arm'] == '5p'), 'from_start'] + 26 dataframe.loc[(dataframe['type'] == 'post-seed') & (dataframe['arm'] == '5p'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'post-seed') & (dataframe['arm'] == '5p'), 'from_start'] + 33 dataframe.loc[(dataframe['type'] == 'loop') & (dataframe['arm'] == 'loop'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'loop') & (dataframe['arm'] == 'loop'), 'from_start'] + 47 for x in range(1, 26): if dataframe[(dataframe['type'] == 'flanking-5') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['5p', 'flanking-5', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) for x in range(26, 27): if dataframe[(dataframe['type'] == 'pre-seed') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['5p', 'pre-seed', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) for x in range(27, 34): if dataframe[(dataframe['type'] == 'seed') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['5p', 'seed', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) for x in range(34, 48): if dataframe[(dataframe['type'] == 'post-seed') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['5p', 'post-seed', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) dataframe.loc[(dataframe['type'] == 'post-seed') & (dataframe['from_start'] > 47), 'from_start'] = 47 for x in range(48, 53 - 2): if dataframe[(dataframe['type'] == 'loop') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['loop', 'loop', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) # dataframe = pd.concat([dataframe, add_loop_df]) dataframe = dataframe.groupby(['arm', 'type', 'from_start'], as_index=False)[['pos']].sum()[['arm', 'type', 'from_start', 'pos']] return dataframe, add_loop_value def prepare_data_3p(df_temp): dataframe = df_temp[(df_temp['arm'] == '3p')].groupby(['arm', 'type', 'from_start'], as_index=False)[['pos']].count()[['arm', 'type', 'from_start', 'pos']] try: dataframe_loop = df_temp[(df_temp['arm'] == 'loop') & (df_temp['from_end'] > -4)].groupby(['arm', 'type', 'from_end'], as_index=False)[['pos']].count()[['arm', 'type', 'from_end', 'pos']] dataframe_loop['from_start'] = dataframe_loop['from_end'].apply( lambda start: start + 4 ) dataframe_loop.drop('from_end', inplace=True, axis=1) except KeyError: dataframe_loop = df_temp[(df_temp['arm'] == 'loop') & (df_temp['from_end'] > -4)].groupby(['arm', 'type', 'from_end'], as_index=False)[['pos']].count()[['arm', 'type', 'from_end', 'pos']] dataframe_loop['from_start'] = dataframe_loop['from_end'].apply( lambda start: start + 4 ) dataframe_loop.drop('from_end', inplace=True, axis=1) dataframe = pd.concat([dataframe, dataframe_loop], sort=False) dataframe.loc[(dataframe['type'] == 'post-seed') & (dataframe['arm'] == '3p'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'post-seed') & (dataframe['arm'] == '3p'), 'from_start'] + 13 - 2 dataframe.loc[(dataframe['type'] == 'seed') & (dataframe['arm'] == '3p'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'seed') & (dataframe['arm'] == '3p'), 'from_start'] + 6 - 2 dataframe.loc[(dataframe['type'] == 'pre-seed') & (dataframe['arm'] == '3p'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'pre-seed') & (dataframe['arm'] == '3p'), 'from_start'] + 5 - 2 dataframe.loc[(dataframe['type'] == 'flanking-3') & (dataframe['arm'] == '3p'), 'from_start'] = \ dataframe.loc[(dataframe['type'] == 'flanking-3') & (dataframe['arm'] == '3p'), 'from_start'] + 27 - 2 for x in range(28 - 2, 53 - 2): if dataframe[(dataframe['type'] == 'flanking-3') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['3p', 'flanking-3', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) for x in range(14 - 2, 28 - 2): if dataframe[(dataframe['type'] == 'post-seed') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['3p', 'post-seed', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) dataframe.loc[(dataframe['type'] == 'post-seed') & (dataframe['from_start'] > 27 - 2), 'from_start'] = 27 - 2 for x in range(7 - 2, 14 - 2): if dataframe[(dataframe['type'] == 'seed') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['3p', 'seed', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) for x in range(6 - 2, 7 - 2): if dataframe[(dataframe['type'] == 'pre-seed') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['3p', 'pre-seed', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) for x in range(1, 6 - 2): if dataframe[(dataframe['type'] == 'loop') & (dataframe['from_start'] == x)].shape[0] == 0: new_row = pd.DataFrame([['loop', 'loop', x, 0]], columns=['arm', 'type', 'from_start', 'pos']) dataframe = pd.concat([dataframe, new_row]) dataframe['from_start'] = dataframe['from_start'].apply(lambda start: start * -1) dataframe = dataframe.groupby(['arm', 'type', 'from_start'], as_index=False)[['pos']].sum()[['arm', 'type', 'from_start', 'pos']] return dataframe def prepare_figure(output_folder): if not os.path.exists(output_folder + '/plots'): os.makedirs(output_folder + '/plots') df_temp = pd.read_csv(output_folder + '/all_mutations_with_n_hgvs.csv') # df_temp = df_temp[df_temp['mutation_type'] == 'subst'] mutations = df_temp.shape[0] genes = df_temp['pre_name'].nunique() create_plot(df_temp, output_folder + '/plots/plot_miRNA.svg', mutations, genes, mirna_type='both') # 5' dominant miRNAs df_5_dominant = df_temp[df_temp['balance'] == '5p'] mutations = df_5_dominant.shape[0] genes = df_5_dominant['pre_name'].nunique() create_plot(df_5_dominant, output_folder + '/plots/plot_5p_balance_miRNA.svg', mutations, genes, mirna_type='5p') # 3p dominant miRNAs df_3_dominant = df_temp[df_temp['balance'] == '3p'] mutations = df_3_dominant.shape[0] genes = df_3_dominant['pre_name'].nunique() create_plot(df_3_dominant, output_folder + '/plots/plot_3p_balance_miRNA.svg', mutations, genes, mirna_type='3p') # balanced miRNAs df_no_dominant = df_temp[df_temp['balance'] == 'both'] mutations = df_no_dominant.shape[0] genes = df_no_dominant['pre_name'].nunique() create_plot(df_no_dominant, output_folder + '/plots/plot_balanced_miRNA.svg', mutations, genes, mirna_type='both') def create_plot_per_mirna(data_df, output_name, mutations=0, types='both', title1='title1', title='title'): df_plot_5, loop_value = prepare_data_5p(data_df) df_plot_3 = prepare_data_3p(data_df) max_value = max(df_plot_5['pos'].max(), df_plot_3['pos'].max()) rc("pdf", fonttype=42) sns.set_style(style='white') palette = {'flanking-5': 'grey', 'flanking-3': 'grey', 'pre-seed': '#5481A6', 'seed': 'darkblue', 'post-seed': '#5481A6', 'loop': 'grey', 'silent-pre': '#5481A6', 'silent-post': '#5481A6', 'silent-seed': '#5481A6' } fig = plt.figure(figsize=(25, 10)) ax = fig.add_axes([0, 0, 1, 1]) ax.axis('off') plt.imshow(im) plt.xticks([]) plt.yticks([]) y_min, y_max = ax.get_ylim() x_min, x_max = ax.get_xlim() plt.text(0, y_min * -0.5, title1.replace('mir', 'miR'), horizontalalignment='left', weight='bold', verticalalignment='center', fontdict={'size': '38'}) plt.text(0, y_min * -0.35, title, horizontalalignment='left', verticalalignment='center', fontdict={'size': '38'}) plt.text(x_max * 0.92, y_min * 1, str(mutations), horizontalalignment='center', verticalalignment='center', fontdict={'size': '42'}) plt.text(x_max * 0.24, y_min * -0.09, 'flanking region', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.02, x_max * 0.46], [y_min * -0.07, y_min * -0.07], lw=0.5, color='grey', alpha=0.8) ax.add_line(line) line.set_clip_on(False) plt.text(x_max * 0.65, y_min * -0.09, 'miRNA', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.47, x_max * 0.83], [y_min * -0.07, y_min * -0.07], lw=0.5, color='#5481A6', alpha=0.8) ax.add_line(line) line.set_clip_on(False) plt.text(x_max * 0.91, y_min * -0.09, 'loop', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.84, x_max * 0.98], [y_min * -0.07, y_min * -0.07], lw=0.5, color='grey', alpha=0.8) ax.add_line(line) line.set_clip_on(False) if types != '3p': plt.text(x_max * 0.54, y_min * 0, 'seed', horizontalalignment='center', fontdict={'size': '42'}) line = lines.Line2D([x_max * 0.49, x_max * 0.59], [y_min * 0.03, y_min * 0.03], lw=0.5, color='darkblue', alpha=0.8) ax.add_line(line) line.set_clip_on(False) if types != '5p': line = lines.Line2D([x_max * 0.675, x_max * 0.775], [y_min * 1.125, y_min * 1.125], lw=0.5, color='darkblue', alpha=0.8) ax.add_line(line) line.set_clip_on(False) plt.text(x_max * 0.725, y_min * 1.195, 'seed', horizontalalignment='center', fontdict={'size': '42'}) if loop_value > 0: plt.text( x_max * 0.92, y_min * 0.6, '+ {} loop\nmutations'.format(loop_value), horizontalalignment='center', verticalalignment='center', fontdict={'size': '30'} ) a = plt.axes([.058, .52, .82, .35]) hue_order = ['flanking-5', 'pre-seed', 'seed', 'post-seed', 'loop'] if types == '3p': hue_order = ['flanking-5', 'silent-pre', 'silent-seed', 'silent-post', 'loop'] df_plot_5['type'] = df_plot_5['type'].apply( lambda x: 'silent-seed' if x == 'seed' else ( 'silent-pre' if x == 'pre-seed' else ( 'silent-post' if x == 'post-seed' else x ) ) ) labels = [str(x) for x in range(-25, 0)] + \ [str(x) for x in range(1, 23)] + ['+' + str(x) for x in range(1, 4)] labels = ['L' if x == '+4' else x for x in labels] ax = sns.barplot(x="from_start", y="pos", hue="type", data=df_plot_5, dodge=False, hue_order=hue_order, palette=palette, ax=a) for loc in ['right', 'top', 'left', 'bottom']: ax.spines[loc].set_visible(False) ax.set_xlabel('') ax.set_ylabel('') ax.legend(loc='upper right', ncol=2) plt.setp(ax.get_legend().get_texts(), fontsize='18') plt.setp(ax.get_legend().get_title(), fontsize='22') plt.grid(b=True, which='major', axis='y', color='lightgrey', linestyle='-', linewidth=0.75, zorder=2, alpha=0.5) ax.set_xticklabels(labels) for tick in ax.xaxis.get_major_ticks(): tick.label.set_fontsize(30) for tick in ax.yaxis.get_major_ticks(): tick.label.set_fontsize(30) if max_value > 5: plt.yticks(np.arange(0, max_value + 1, np.floor(max_value / 3))) plot_limit = max_value + 2 else: plt.yticks(np.arange(0, max_value + 1, 1)) plot_limit = max_value + 1 ax.set_ylim([0, plot_limit]) ax.xaxis.tick_bottom() for label in ax.get_xticklabels(): if label.get_text() not in ['-25', '-20', '-15', '-10', '-5', '1', '5', '10', '15', '20', '+1']: label.set_visible(False) new_width = 0.35 for patch in ax.patches: current_width = patch.get_width() diff = current_width - new_width # we change the bar width patch.set_width(new_width) # we recenter the bar patch.set_x(patch.get_x() + diff * .5) ax.tick_params(axis='both', which='major', pad=8, width=0.5) plt.setp(ax.patches, linewidth=0) ax.get_legend().remove() b = plt.axes([.025, .02, .82, .35], facecolor='w') hue_order = ['flanking-3', 'pre-seed', 'seed', 'post-seed', 'loop'] labels = ['+' + str(x) for x in range(1, 26)][::-1] + [str(x) for x in range(1, 23)][::-1] + \ ['-' + str(x) for x in range(1, 4)] if types == '5p': hue_order = ['flanking-3', 'silent-pre', 'silent-seed', 'silent-post', 'loop'] df_plot_3['type'] = df_plot_3['type'].apply( lambda x: 'silent-seed' if x == 'seed' else ( 'silent-pre' if x == 'pre-seed' else ( 'silent-post' if x == 'post-seed' else x ) ) ) ax = sns.barplot(x="from_start", y="pos", hue="type", data=df_plot_3, dodge=False, hue_order=hue_order, palette=palette, ax=b) for loc in ['right', 'top', 'left', 'bottom']: ax.spines[loc].set_visible(False) ax.set_xlabel('') ax.set_ylabel('') plt.grid(b=True, which='major', axis='y', color='lightgrey', linestyle='-', linewidth=0.75, zorder=1, alpha=0.5) ax.set_xticklabels(labels) if max_value > 5: plt.yticks(np.arange(0, max_value + 1, np.floor(max_value / 3))) plot_limit = max_value + 2 else: plt.yticks(np.arange(0, max_value + 1, 1)) plot_limit = max_value + 1 ax.get_legend().remove() ax.set_ylim([plot_limit, 0]) ax.xaxis.tick_top() for tick in ax.xaxis.get_major_ticks(): tick.label2.set_fontsize(30) for tick in ax.yaxis.get_major_ticks(): tick.label.set_fontsize(30) for label in ax.get_xticklabels(): if label.get_text() not in ['+25', '+20', '+15', '+10', '+5', '+1', '1', '5', '10', '15', '20', '-5']: label.set_visible(False) new_width = 0.35 for patch in ax.patches: current_width = patch.get_width() diff = current_width - new_width # we change the bar width patch.set_width(new_width) # we recenter the bar patch.set_x(patch.get_x() + diff * .5) plt.setp(ax.patches, linewidth=0) plt.savefig(output_name, format='svg', dpi=300, transparent=True, bbox_inches='tight') plt.cla() plt.clf() plt.close("all") plt.close(fig) gc.collect() def prepare_figures_per_mirna(output_folder): if not os.path.exists(output_folder + '/plots'): os.makedirs(output_folder + '/plots') if not os.path.exists(output_folder + '/plots/miRNAs'): os.makedirs(output_folder + '/plots/miRNAs') df_temp = pd.read_csv(output_folder + '/all_mutations_with_n_hgvs.csv') # df_temp = df_temp[df_temp['mutation_type'] == 'subst'] mirnas = list(set(df_temp['pre_name'].unique())) for mirna in mirnas: title = '' title1 = mirna df_temp2 = df_temp[df_temp['pre_name'] == mirna].copy() type_of_miRNA = list(df_temp2['balance'].unique())[0] mutations = df_temp2.shape[0] create_plot_per_mirna(df_temp2, output_folder + '/plots/miRNAs/plot_miRNA_{}.svg'.format(mirna), mutations, types=type_of_miRNA, title1=title1, title=title) del df_temp2 gc.collect() @click.command() @click.argument('output_folder') def main(output_folder): prepare_figure(output_folder) prepare_figures_per_mirna(output_folder) if __name__ == "__main__": main()

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Python

scvelo/core/tests/test_arithmetic.py

WeilerP/scvelo

1805ab4a72d3f34496f0ef246500a159f619d3a2

[ "BSD-3-Clause" ]

272

2018-08-21T08:59:11.000Z

2022-03-30T11:24:19.000Z

scvelo/core/tests/test_arithmetic.py

theislab/scvelo

1805ab4a72d3f34496f0ef246500a159f619d3a2

[ "BSD-3-Clause" ]

570

2018-08-21T14:04:03.000Z

2022-03-30T08:48:04.000Z

scvelo/core/tests/test_arithmetic.py

WeilerP/scvelo

1805ab4a72d3f34496f0ef246500a159f619d3a2

[ "BSD-3-Clause" ]

105

2018-09-04T14:08:58.000Z

2022-03-17T16:20:14.000Z

from typing import List from hypothesis import given from hypothesis import strategies as st from hypothesis.extra.numpy import arrays import numpy as np from numpy import ndarray from numpy.testing import assert_almost_equal, assert_array_equal from scvelo.core import clipped_log, invert, prod_sum, sum class TestClippedLog: @given( a=arrays( float, shape=st.integers(min_value=1, max_value=100), elements=st.floats( min_value=-1e3, max_value=1e3, allow_infinity=False, allow_nan=False ), ), bounds=st.lists( st.floats( min_value=0, max_value=100, allow_infinity=False, allow_nan=False ), min_size=2, max_size=2, unique=True, ), eps=st.floats( min_value=1e-6, max_value=1, allow_infinity=False, allow_nan=False ), ) def test_flat_arrays(self, a: ndarray, bounds: List[float], eps: float): lb = min(bounds) ub = max(bounds) + 2 * eps a_logged = clipped_log(a, lb=lb, ub=ub, eps=eps) assert a_logged.shape == a.shape if (a <= lb).any(): assert_almost_equal(np.abs(a_logged - np.log(lb + eps)).min(), 0) else: assert (a_logged >= np.log(lb + eps)).all() if (a >= ub).any(): assert_almost_equal(np.abs(a_logged - np.log(ub - eps)).min(), 0) else: assert (a_logged <= np.log(ub - eps)).all() @given( a=arrays( float, shape=st.tuples( st.integers(min_value=1, max_value=100), st.integers(min_value=1, max_value=100), ), elements=st.floats( min_value=-1e3, max_value=1e3, allow_infinity=False, allow_nan=False ), ), bounds=st.lists( st.floats( min_value=0, max_value=100, allow_infinity=False, allow_nan=False ), min_size=2, max_size=2, unique=True, ), eps=st.floats( min_value=1e-6, max_value=1, allow_infinity=False, allow_nan=False ), ) def test_2d_arrays(self, a: ndarray, bounds: List[float], eps: float): lb = min(bounds) ub = max(bounds) + 2 * eps a_logged = clipped_log(a, lb=lb, ub=ub, eps=eps) assert a_logged.shape == a.shape if (a <= lb).any(): assert_almost_equal(np.abs(a_logged - np.log(lb + eps)).min(), 0) else: assert (a_logged >= np.log(lb + eps)).all() if (a >= ub).any(): assert_almost_equal(np.abs(a_logged - np.log(ub - eps)).min(), 0) else: assert (a_logged <= np.log(ub - eps)).all() class TestInvert: @given( a=arrays( float, shape=st.integers(min_value=1, max_value=100), elements=st.floats(max_value=1e3, allow_infinity=False, allow_nan=False), ) ) def test_flat_arrays(self, a: ndarray): a_inv = invert(a) if a[a != 0].size == 0: assert a_inv[a != 0].size == 0 else: assert_array_equal(a_inv[a != 0], 1 / a[a != 0]) if 0 in a: assert np.isnan(a_inv[a == 0]).all() else: assert set(a_inv[a == 0]) == set() @given( a=arrays( float, shape=st.tuples( st.integers(min_value=1, max_value=100), st.integers(min_value=1, max_value=100), ), elements=st.floats(max_value=1e3, allow_infinity=False, allow_nan=False), ) ) def test_2d_arrays(self, a: ndarray): a_inv = invert(a) if a[a != 0].size == 0: assert a_inv[a != 0].size == 0 else: assert_array_equal(a_inv[a != 0], 1 / a[a != 0]) if 0 in a: assert np.isnan(a_inv[a == 0]).all() else: assert set(a_inv[a == 0]) == set() # TODO: Extend test to generate sparse inputs as well # TODO: Make test to generate two different arrays a1, a2 # TODO: Check why tests fail with assert_almost_equal class TestProdSum: @given( a=arrays( float, shape=st.integers(min_value=1, max_value=100), elements=st.floats(max_value=1e3, allow_infinity=False, allow_nan=False), ), axis=st.integers(min_value=0, max_value=1), ) def test_flat_array(self, a: ndarray, axis: int): assert np.allclose((a * a).sum(axis=0), prod_sum(a, a, axis=axis)) @given( a=arrays( float, shape=st.tuples( st.integers(min_value=1, max_value=100), st.integers(min_value=1, max_value=100), ), elements=st.floats(max_value=1e3, allow_infinity=False, allow_nan=False), ), axis=st.integers(min_value=0, max_value=1), ) def test_2d_array(self, a: ndarray, axis: int): assert np.allclose((a * a).sum(axis=axis), prod_sum(a, a, axis=axis)) # TODO: Extend test to generate sparse inputs as well class TestSum: @given( a=arrays( float, shape=st.integers(min_value=1, max_value=100), elements=st.floats(max_value=1e3, allow_infinity=False, allow_nan=False), ), ) def test_flat_arrays(self, a: ndarray): a_summed = sum(a=a, axis=0) assert_array_equal(a_summed, a.sum(axis=0)) @given( a=arrays( float, shape=st.tuples( st.integers(min_value=1, max_value=100), st.integers(min_value=1, max_value=100), ), elements=st.floats(max_value=1e3, allow_infinity=False, allow_nan=False), ), axis=st.integers(min_value=0, max_value=1), ) def test_2d_arrays(self, a: ndarray, axis: int): a_summed = sum(a=a, axis=axis) if a.ndim == 1: axis = 0 assert_array_equal(a_summed, a.sum(axis=axis))

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null

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0

1

0

null

0

7

2b171d110e18d90880f80a77c7b0a728a6c26712

3,636

py

Python

ivy/functional/ivy/array_api/utility_functions.py

sert121/ivy

286f86e487b0c83d46a3ef8d30aa96316337db32

[ "Apache-2.0" ]

1

2022-03-24T20:09:20.000Z

ivy/functional/ivy/array_api/utility_functions.py

sert121/ivy

286f86e487b0c83d46a3ef8d30aa96316337db32

[ "Apache-2.0" ]

null

ivy/functional/ivy/array_api/utility_functions.py

sert121/ivy

286f86e487b0c83d46a3ef8d30aa96316337db32

[ "Apache-2.0" ]

null

# global from typing import Union, Optional, Tuple, List # local import ivy from ivy.framework_handler import current_framework as _cur_framework # noinspection PyShadowingBuiltins def all(x: Union[ivy.Array, ivy.NativeArray], axis: Optional[Union[int, Tuple[int], List[int]]] = None, keepdims: bool = False)\ -> ivy.Array: """ Tests whether all input array elements evaluate to True along a specified axis. :param x: input array. :param axis: axis or axes along which to perform a logical AND reduction. By default, a logical AND reduction must be performed over the entire array. If a tuple of integers, logical AND reductions must be performed over multiple axes. A valid axis must be an integer on the interval [-N, N), where N is the rank (number of dimensions) of x. If an axis is specified as a negative integer, the function must determine the axis along which to perform a reduction by counting backward from the last dimension (where -1 refers to the last dimension). If provided an invalid axis, the function must raise an exception. Default: None. :param keepdims: If True, the reduced axes (dimensions) must be included in the result as singleton dimensions, and, accordingly, the result must be compatible with the input array (see Broadcasting). Otherwise, if False, the reduced axes (dimensions) must not be included in the result. Default is False. :return: if a logical AND reduction was performed over the entire array, the returned array must be a zero-dimensional array containing the test result; otherwise, the returned array must be a non-zero-dimensional array containing the test results. The returned array must have a data type of bool. """ return _cur_framework(x).all(x, axis, keepdims) # noinspection PyShadowingBuiltins def any(x: Union[ivy.Array, ivy.NativeArray], axis: Optional[Union[int, Tuple[int], List[int]]] = None, keepdims: bool = False)\ -> ivy.Array: """ Tests whether any input array element evaluate to True along a specified axis. :param x: input array. :param axis: axis or axes along which to perform a logical OR reduction. By default, a logical OR reduction must be performed over the entire array. If a tuple of integers, logical OR reductions must be performed over multiple axes. A valid axis must be an integer on the interval [-N, N), where N is the rank (number of dimensions) of x. If an axis is specified as a negative integer, the function must determine the axis along which to perform a reduction by counting backward from the last dimension (where -1 refers to the last dimension). If provided an invalid axis, the function must raise an exception. Default: None. :param keepdims: If True, the reduced axes (dimensions) must be included in the result as singleton dimensions, and, accordingly, the result must be compatible with the input array (see Broadcasting). Otherwise, if False, the reduced axes (dimensions) must not be included in the result. Default is False. :return: if a logical OR reduction was performed over the entire array, the returned array must be a zero-dimensional array containing the test result; otherwise, the returned array must be a non-zero-dimensional array containing the test results. The returned array must have a data type of bool. """ return _cur_framework(x).any(x, axis, keepdims)

63.789474

122

0.706821

533

3,636

4.806754

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56

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null

0

1

0

8

2b4dd386cfee73b3c69f545c796d28cb1d986830

44,902

py

Python

keras_segmentation/train.py

mwaseema/image-segmentation-keras-implementation

e137b55c3a19787309f086744e3f7ed1b4df4520

[ "MIT" ]

1

2021-12-09T10:33:18.000Z

keras_segmentation/train.py

mwaseema/image-segmentation-keras-implementation

e137b55c3a19787309f086744e3f7ed1b4df4520

[ "MIT" ]

null

keras_segmentation/train.py

mwaseema/image-segmentation-keras-implementation

e137b55c3a19787309f086744e3f7ed1b4df4520

[ "MIT" ]

1

2022-02-11T18:59:43.000Z

import json import os import six from keras import optimizers from keras.callbacks import ReduceLROnPlateau from . import custom_losses from .custom_losses import smooth_l1_loss from .data_utils.bounding_box_based_network_utils import bounding_box_based_network_loss_gpu from .data_utils.bounding_box_iou_based_network_utils import bounding_box_iou_based_network_loss, \ bounding_box_iou_based_network_metric from .data_utils.data_loader import image_segmentation_generator, IoU_network_image_segmentation_generator, \ verify_segmentation_dataset, two_stream_verify_segmentation_dataset, two_stream_image_segmentation_generator, \ image_segmentation_generator_i3d, image_segmentation_generator_bounding_box_based_network, \ image_segmentation_generator_bounding_box_iou_based_network, image_segmentation_generator_with_weighted_output, \ image_segmentation_generator_i3d_inception, image_segmentation_temporal_generator_with_weighted_output from .data_utils.iou_utils import iou_metric_wrapper from .models import model_from_name def find_latest_checkpoint(checkpoints_path): ep = 0 r = None while True: if os.path.isfile(checkpoints_path + "." + str(ep)): r = checkpoints_path + "." + str(ep) else: return r ep += 1 def replace_previous_checkpoint_with_empty_file(checkpoint_path, epoch_number): if epoch_number > 0: previous_check_point_path = f"{checkpoint_path}.{epoch_number - 1}" if os.path.exists(previous_check_point_path): os.remove(previous_check_point_path) # make new empty file f = open(previous_check_point_path, mode='w') f.close() def train(model, train_images, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam' ): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width output_height = model.output_height output_width = model.output_width if validate: assert not (val_images is None) assert not (val_annotations is None) if not optimizer_name is None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) # model.compile(loss=[custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model)], # optimizer=optimizer_name, # metrics=['accuracy', iou_metric_wrapper(output_height, output_width, n_classes)]) model.compile(loss=[custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model)], optimizer=optimizer_name, metrics=['accuracy']) if not checkpoints_path is None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_images, train_annotations, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(val_images, val_annotations, n_classes) train_gen = image_segmentation_generator(train_images, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = image_segmentation_generator(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_i3d_inception(model, train_features_folder, train_annotations_folder, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam' ): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width output_height = model.output_height output_width = model.output_width if validate: assert not (val_images is None) assert not (val_annotations is None) if not optimizer_name is None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) # model.compile(loss=[custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model)], # optimizer=optimizer_name, # metrics=['accuracy', iou_metric_wrapper(output_height, output_width, n_classes)]) model.compile(loss=[custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model)], optimizer=optimizer_name, metrics=['accuracy']) if not checkpoints_path is None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_features_folder, train_annotations_folder, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(train_features_folder, train_annotations_folder, n_classes) train_gen = image_segmentation_generator_i3d_inception(train_features_folder, train_annotations_folder, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = image_segmentation_generator_i3d_inception(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_with_weighted_output(model, train_images, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam' ): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width output_height = model.output_height output_width = model.output_width if validate: assert not (val_images is None) assert not (val_annotations is None) if not optimizer_name is None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) # model.compile(loss=[custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model)], # optimizer=optimizer_name, # metrics=['accuracy', iou_metric_wrapper(output_height, output_width, n_classes)]) model.compile(loss={ "main_output_activation": custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model), "second_output_activation": smooth_l1_loss, }, optimizer=optimizer_name, metrics=['accuracy']) if not checkpoints_path is None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_images, train_annotations, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(val_images, val_annotations, n_classes) train_gen = image_segmentation_generator_with_weighted_output(train_images, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = image_segmentation_generator_with_weighted_output(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_temporal_with_weighted_output(model, train_images, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam' ): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width output_height = model.output_height output_width = model.output_width if validate: assert not (val_images is None) assert not (val_annotations is None) if not optimizer_name is None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) # model.compile(loss=[custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model)], # optimizer=optimizer_name, # metrics=['accuracy', iou_metric_wrapper(output_height, output_width, n_classes)]) model.compile(loss={ "main_output_activation": custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model), "second_output_activation": smooth_l1_loss, }, optimizer=optimizer_name, metrics=['accuracy']) if not checkpoints_path is None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_images, train_annotations, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(val_images, val_annotations, n_classes) train_gen = image_segmentation_temporal_generator_with_weighted_output(train_images, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = image_segmentation_temporal_generator_with_weighted_output(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_bounding_box_based_network(model, train_images, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam', optimizer_lr=0.001, optimizer_decay=0.001): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width # output_height = model.output_height # output_width = model.output_width output_height = input_height output_width = input_width if validate: assert not (val_images is None) assert not (val_annotations is None) if optimizer_name is not None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) adam = optimizers.Adam(lr=optimizer_lr, decay=optimizer_decay) model.compile(loss=bounding_box_based_network_loss_gpu, optimizer=adam, metrics=['accuracy']) if checkpoints_path is not None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_images, train_annotations, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(val_images, val_annotations, n_classes) train_gen = image_segmentation_generator_bounding_box_based_network(train_images, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = image_segmentation_generator_bounding_box_based_network(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_bounding_box_iou_based_network(model, train_images, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam', optimizer_lr=0.001, optimizer_decay=0.001): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width # output_height = model.output_height # output_width = model.output_width output_height = input_height output_width = input_width if validate: assert not (val_images is None) assert not (val_annotations is None) if optimizer_name is not None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) adam = optimizers.Adam(lr=optimizer_lr, decay=optimizer_decay) model.compile(loss=bounding_box_iou_based_network_loss, optimizer=adam, metrics=['accuracy', bounding_box_iou_based_network_metric]) if checkpoints_path is not None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_images, train_annotations, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(val_images, val_annotations, n_classes) train_gen = image_segmentation_generator_bounding_box_iou_based_network(train_images, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = image_segmentation_generator_bounding_box_iou_based_network(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_IoU_network(model, train_images, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam' ): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width # output_height = model.output_height # output_width = model.output_width output_height = None output_width = None if validate: assert not (val_images is None) assert not (val_annotations is None) if not optimizer_name is None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) model.compile(loss=custom_losses.smooth_l1_loss, optimizer=optimizer_name, metrics=['accuracy']) if not checkpoints_path is None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_images, train_annotations, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(val_images, val_annotations, n_classes) train_gen = IoU_network_image_segmentation_generator(train_images, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = IoU_network_image_segmentation_generator(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_i3d(model, train_images, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam', lr_custom=0.001, lr_decay=0.0 ): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width output_height = model.output_height output_width = model.output_width if validate: assert not (val_images is None) assert not (val_annotations is None) if not optimizer_name is None: # model.compile(loss='categorical_crossentropy', # optimizer= optimizer_name , # metrics=['accuracy']) adam = optimizers.Adam(lr=lr_custom, beta_1=0.9, beta_2=0.999, decay=lr_decay) model.compile(loss={ "main_output_activation": custom_losses.categorical_focal_loss_with_iou(alpha=0.50, gamma=1.25, model=model), "second_output_activation": smooth_l1_loss, }, optimizer=adam, metrics=['accuracy']) if not checkpoints_path is None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") verify_segmentation_dataset(train_images, train_annotations, n_classes) if validate: print("Verifying val dataset") verify_segmentation_dataset(val_images, val_annotations, n_classes) train_gen = image_segmentation_generator_i3d(train_images, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = image_segmentation_generator_i3d(val_images, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) # reduce_lr = ReduceLROnPlateau(monitor='loss', factor=0.5, patience=3, min_lr=1e-6, verbose=1) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) # model.fit_generator(train_gen, steps_per_epoch, epochs=1, callbacks=[reduce_lr]) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) # model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1, # callbacks=[reduce_lr]) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) def train_two_stream(model, train_images, train_flows, train_annotations, input_height=None, input_width=None, n_classes=None, verify_dataset=True, checkpoints_path=None, epochs=5, batch_size=2, validate=False, val_images=None, val_flows=None, val_annotations=None, val_batch_size=2, auto_resume_checkpoint=False, load_weights=None, steps_per_epoch=512, optimizer_name='adam' ): if isinstance(model, six.string_types): # check if user gives model name insteead of the model object # create the model from the name assert (not n_classes is None), "Please provide the n_classes" if (not input_height is None) and (not input_width is None): model = model_from_name[model](n_classes, input_height=input_height, input_width=input_width) else: model = model_from_name[model](n_classes) n_classes = model.n_classes input_height = model.input_height input_width = model.input_width output_height = model.output_height output_width = model.output_width if validate: assert not (val_images is None) assert not (val_flows is None) assert not (val_annotations is None) if not optimizer_name is None: model.compile(loss='categorical_crossentropy', optimizer=optimizer_name, metrics=['accuracy']) if not checkpoints_path is None: open(checkpoints_path + "_config.json", "w").write(json.dumps({ "model_class": model.model_name, "n_classes": n_classes, "input_height": input_height, "input_width": input_width, "output_height": output_height, "output_width": output_width })) if (not (load_weights is None)) and len(load_weights) > 0: print("Loading weights from ", load_weights) model.load_weights(load_weights) if auto_resume_checkpoint and (not checkpoints_path is None): latest_checkpoint = find_latest_checkpoint(checkpoints_path) if not latest_checkpoint is None: print("Loading the weights from latest checkpoint ", latest_checkpoint) model.load_weights(latest_checkpoint) if verify_dataset: print("Verifying train dataset") two_stream_verify_segmentation_dataset(train_images, train_flows, train_annotations, n_classes) if validate: print("Verifying val dataset") two_stream_verify_segmentation_dataset(val_images, train_flows, val_annotations, n_classes) train_gen = two_stream_image_segmentation_generator(train_images, train_flows, train_annotations, batch_size, n_classes, input_height, input_width, output_height, output_width) if validate: val_gen = two_stream_image_segmentation_generator(val_images, val_flows, val_annotations, val_batch_size, n_classes, input_height, input_width, output_height, output_width) if not validate: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep) else: for ep in range(epochs): print("Starting Epoch ", ep) model.fit_generator(train_gen, steps_per_epoch, validation_data=val_gen, validation_steps=200, epochs=1) if not checkpoints_path is None: model.save_weights(checkpoints_path + "." + str(ep)) print("saved ", checkpoints_path + ".model." + str(ep)) ## replace_previous_checkpoint_with_empty_file(checkpoints_path, ep) print("Finished Epoch", ep)

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Python

neural_network_lyapunov/examples/car/test/test_unicycle.py

hongkai-dai/neural-network-lyapunov-1

8843c13f69f7f39cbb939ab250413e76f61843f6

[ "MIT" ]

58

2021-06-21T08:59:52.000Z

2022-03-31T14:35:23.000Z

neural_network_lyapunov/examples/car/test/test_unicycle.py

StanfordASL/neural-network-lyapunov

9e5db1c7f91b42df729026c9aa8575bc126f66b6

[ "MIT" ]

8

2021-08-22T05:31:23.000Z

2022-03-29T03:47:07.000Z

neural_network_lyapunov/examples/car/test/test_unicycle.py

StanfordASL/neural-network-lyapunov

9e5db1c7f91b42df729026c9aa8575bc126f66b6

[ "MIT" ]

11

2021-06-21T04:29:59.000Z

2022-03-30T05:54:43.000Z

import neural_network_lyapunov.examples.car.unicycle as unicycle import neural_network_lyapunov.utils as utils import neural_network_lyapunov.gurobi_torch_mip as gurobi_torch_mip import unittest import numpy as np import torch import scipy.integrate import scipy.linalg import gurobipy class TestUnicycle(unittest.TestCase): def test_dynamics(self): plant = unicycle.Unicycle(torch.float64) # Test with pytorch tensor. x = torch.tensor([2., 3., 0.5], dtype=torch.float64) u = torch.tensor([0.5, -0.2], dtype=torch.float64) xdot_torch = plant.dynamics(x, u) np.testing.assert_allclose( xdot_torch.detach().numpy(), np.array([u[0] * torch.cos(x[2]), u[0] * torch.sin(x[2]), u[1]])) xdot_np = plant.dynamics(x.detach().numpy(), u.detach().numpy()) np.testing.assert_allclose(xdot_torch.detach().numpy(), xdot_np) def test_dynamics_gradient(self): plant = unicycle.Unicycle(torch.float64) def tester(x_val: np.ndarray, u_val: np.ndarray): A, B = plant.dynamics_gradient(x_val, u_val) A_torch, B_torch = plant.dynamics_gradient(torch.from_numpy(x_val), torch.from_numpy(u_val)) np.testing.assert_allclose(A, A_torch.detach().numpy()) np.testing.assert_allclose(B, B_torch.detach().numpy()) """ Compute gradint through pytorch autograd. """ x_torch = torch.from_numpy(x_val) x_torch.requires_grad = True u_torch = torch.from_numpy(u_val) u_torch.requires_grad = True for i in range(3): if x_torch.grad is not None: x_torch.grad.zero_() if u_torch.grad is not None: u_torch.grad.zero_() xdot = plant.dynamics(x_torch, u_torch) xdot[i].backward() np.testing.assert_allclose(A_torch[i].detach().numpy(), x_torch.grad.detach().numpy()) np.testing.assert_allclose(B_torch[i].detach().numpy(), u_torch.grad.detach().numpy()) tester(np.array([0.5, 0.4, 0.2]), np.array([-0.3, 0.8])) tester(np.array([-0.5, 0.7, -2.2]), np.array([-1.3, -.8])) tester(np.array([-2.5, 0.7, -1.5]), np.array([-1.9, -.8])) def test_next_pose(self): plant = unicycle.Unicycle(torch.float64) x = torch.tensor([2., 3., 0.5], dtype=torch.float64) u = torch.tensor([0.5, -0.2], dtype=torch.float64) x_next = plant.next_pose(x, u, 0.1) result = scipy.integrate.solve_ivp( lambda t, x_val: plant.dynamics(x_val, u.detach().numpy()), [0, 0.1], x.detach().numpy()) np.testing.assert_allclose(x_next, result.y[:, -1]) class TestUnicycleReLUModel(unittest.TestCase): def setUp(self): self.dtype = torch.float64 # Arbitrarily initialize the relu network. All the tests should pass # even if the network doesn't approximate the unicycle dynamics. dynamics_relu_no_thetadot = utils.setup_relu((2, 4, 3, 2), params=None, negative_slope=0.1, bias=True, dtype=self.dtype) dynamics_relu_no_thetadot[0].weight.data = torch.tensor( [[0.2, 0.5], [-1.3, 0.5], [-0.3, -0.2], [-0.4, -1.4]], dtype=self.dtype) dynamics_relu_no_thetadot[0].bias.data = torch.tensor( [0.4, -1.2, 0.1, 2.3], dtype=self.dtype) dynamics_relu_no_thetadot[2].weight.data = torch.tensor( [[0.4, 0.1, -1.4, 0.2], [0.1, -0.2, -0.5, -1.1], [0.3, 0.5, 1.1, -0.2]], dtype=self.dtype) dynamics_relu_no_thetadot[2].bias.data = torch.tensor([0.2, 0.1, -0.3], dtype=self.dtype) dynamics_relu_no_thetadot[4].weight.data = torch.tensor( [[0.1, -0.3, 0.5], [0.3, -0.2, 2.1]], dtype=self.dtype) dynamics_relu_no_thetadot[4].bias.data = torch.tensor([0.4, -1.2], dtype=self.dtype) self.dut_thetadot_not_input = unicycle.UnicycleReLUModel( self.dtype, x_lo=torch.tensor([-3, -3, -np.pi], dtype=self.dtype), x_up=torch.tensor([3, 3, np.pi], dtype=self.dtype), u_lo=torch.tensor([-2, -0.5], dtype=self.dtype), u_up=torch.tensor([5, 0.5], dtype=self.dtype), dynamics_relu=dynamics_relu_no_thetadot, dt=0.01, thetadot_as_input=False) dynamics_relu_thetadot = utils.setup_relu((3, 4, 3, 2), params=None, negative_slope=0.1, bias=True, dtype=self.dtype) dynamics_relu_thetadot[0].weight.data = torch.tensor( [[0.2, 0.5, 0.1], [-1.3, 0.5, -1.2], [-0.3, -0.2, 0.4], [-0.4, -1.4, 0.5]], dtype=self.dtype) dynamics_relu_no_thetadot[0].bias.data = torch.tensor( [0.4, -1.2, 0.1, 2.3], dtype=self.dtype) dynamics_relu_thetadot[2].weight.data = dynamics_relu_no_thetadot[ 2].weight.data dynamics_relu_thetadot[2].bias.data = dynamics_relu_no_thetadot[ 2].bias.data dynamics_relu_thetadot[4].weight.data = dynamics_relu_no_thetadot[ 4].weight.data dynamics_relu_thetadot[4].bias.data = dynamics_relu_thetadot[ 4].bias.data self.dut_thetadot_input = unicycle.UnicycleReLUModel( self.dtype, x_lo=torch.tensor([-3, -3, -np.pi], dtype=self.dtype), x_up=torch.tensor([3, 3, np.pi], dtype=self.dtype), u_lo=torch.tensor([-2, -0.5], dtype=self.dtype), u_up=torch.tensor([5, 0.5], dtype=self.dtype), dynamics_relu=dynamics_relu_thetadot, dt=0.01, thetadot_as_input=True) def step_forward_tester(self, dut): # First test a single x_start and u_start x_start = torch.tensor([0.2, 0.5, -0.1], dtype=self.dtype) u_start = torch.tensor([2.1, 0.3], dtype=self.dtype) x_next = dut.step_forward(x_start, u_start) def eval_next_state(x_val, u_val): if dut.thetadot_as_input: network_input = torch.tensor([x_val[2], u_val[0], u_val[1]], dtype=self.dtype) network_input_zero = torch.zeros((3,), dtype=self.dtype) else: network_input = torch.tensor([x_val[2], u_val[0]], dtype=self.dtype) network_input_zero = torch.zeros((2,), dtype=self.dtype) position_next = x_val[:2] + \ dut.dynamics_relu(network_input) - dut.dynamics_relu( network_input_zero) theta_next = x_val[2] + u_val[1] * dut.dt return np.array([ position_next[0].item(), position_next[1].item(), theta_next.item() ]) np.testing.assert_allclose(x_next.detach().numpy(), eval_next_state(x_start, u_start)) # Now test a batch of x_start and u_start x_start = torch.tensor([[0.2, 0.5, -0.1], [0.4, 0.3, 0.5]], dtype=self.dtype) u_start = torch.tensor([[2.1, 0.3], [-0.3, 0.4]], dtype=self.dtype) x_next = dut.step_forward(x_start, u_start) self.assertEqual(x_next.shape, (2, 3)) for i in range(x_start.shape[0]): np.testing.assert_allclose(x_next[i].detach().numpy(), eval_next_state(x_start[i], u_start[i])) def test_step_forward_thetadot_not_input(self): self.step_forward_tester(self.dut_thetadot_not_input) def test_step_forward_thetadot_as_input(self): self.step_forward_tester(self.dut_thetadot_input) def add_dynamics_constraint_tester(self, dut): def tester(x_val, u_val): # Setup an MILP with fixed x_var and u_var, check if x_next_var is # solved to the right value. mip = gurobi_torch_mip.GurobiTorchMILP(self.dtype) x_var = mip.addVars(3, lb=-gurobipy.GRB.INFINITY) u_var = mip.addVars(2, lb=-gurobipy.GRB.INFINITY) x_next_var = mip.addVars(3, lb=-gurobipy.GRB.INFINITY) dut.add_dynamics_constraint(mip, x_var, x_next_var, u_var, "slack", "binary") # Fix x_var to x_val, u_var to u_val mip.addMConstrs([torch.eye(3, dtype=self.dtype)], [x_var], sense=gurobipy.GRB.EQUAL, b=x_val) mip.addMConstrs([torch.eye(2, dtype=self.dtype)], [u_var], sense=gurobipy.GRB.EQUAL, b=u_val) mip.gurobi_model.setParam(gurobipy.GRB.Param.OutputFlag, False) mip.gurobi_model.optimize() self.assertEqual(mip.gurobi_model.status, gurobipy.GRB.Status.OPTIMAL) x_next_val = np.array([var.xn for var in x_next_var]) x_next_val_expected = dut.step_forward(x_val, u_val) np.testing.assert_allclose(x_next_val, x_next_val_expected.detach().numpy(), atol=1e-8) tester(torch.tensor([0., 0., 0.], dtype=self.dtype), torch.tensor([0., 0.], dtype=self.dtype)) tester(torch.tensor([0.5, -0.3, 0.4], dtype=self.dtype), torch.tensor([0., 0.], dtype=self.dtype)) tester(torch.tensor([0.6, -1.3, 0.4], dtype=self.dtype), torch.tensor([4., 0.3], dtype=self.dtype)) tester(torch.tensor([0.6, -1.3, 0.4], dtype=self.dtype), torch.tensor([-2., 0.3], dtype=self.dtype)) def test_add_dynamics_constraint_thetadot_not_input(self): self.add_dynamics_constraint_tester(self.dut_thetadot_not_input) def test_add_dynamics_constraint_thetadot_as_input(self): self.add_dynamics_constraint_tester(self.dut_thetadot_input) class TestUnicycleReLUZeroVelModel(unittest.TestCase): def setUp(self): self.dtype = torch.float64 # Arbitrarily initialize the relu network. All the tests should pass # even if the network doesn't approximate the unicycle dynamics. dynamics_relu_no_thetadot = utils.setup_relu((2, 4, 3, 2), params=None, negative_slope=0.1, bias=True, dtype=self.dtype) dynamics_relu_no_thetadot[0].weight.data = torch.tensor( [[0.2, 0.5], [-1.3, 0.5], [-0.3, -0.2], [-0.4, -1.4]], dtype=self.dtype) dynamics_relu_no_thetadot[0].bias.data = torch.tensor( [0.4, -1.2, 0.1, 2.3], dtype=self.dtype) dynamics_relu_no_thetadot[2].weight.data = torch.tensor( [[0.4, 0.1, -1.4, 0.2], [0.1, -0.2, -0.5, -1.1], [0.3, 0.5, 1.1, -0.2]], dtype=self.dtype) dynamics_relu_no_thetadot[2].bias.data = torch.tensor([0.2, 0.1, -0.3], dtype=self.dtype) dynamics_relu_no_thetadot[4].weight.data = torch.tensor( [[0.1, -0.3, 0.5], [0.3, -0.2, 2.1]], dtype=self.dtype) dynamics_relu_no_thetadot[4].bias.data = torch.tensor([0.4, -1.2], dtype=self.dtype) self.dut_thetadot_not_input = unicycle.UnicycleReLUZeroVelModel( self.dtype, x_lo=torch.tensor([-3, -3, -np.pi], dtype=self.dtype), x_up=torch.tensor([3, 3, np.pi], dtype=self.dtype), u_lo=torch.tensor([-2, -0.5], dtype=self.dtype), u_up=torch.tensor([5, 0.5], dtype=self.dtype), dynamics_relu=dynamics_relu_no_thetadot, dt=0.01, thetadot_as_input=False) dynamics_relu_thetadot = utils.setup_relu((3, 4, 3, 2), params=None, negative_slope=0.1, bias=True, dtype=self.dtype) dynamics_relu_thetadot[0].weight.data = torch.tensor( [[0.2, 0.5, 0.1], [-1.3, 0.5, -1.2], [-0.3, -0.2, 0.4], [-0.4, -1.4, 0.5]], dtype=self.dtype) dynamics_relu_no_thetadot[0].bias.data = torch.tensor( [0.4, -1.2, 0.1, 2.3], dtype=self.dtype) dynamics_relu_thetadot[2].weight.data = dynamics_relu_no_thetadot[ 2].weight.data dynamics_relu_thetadot[2].bias.data = dynamics_relu_no_thetadot[ 2].bias.data dynamics_relu_thetadot[4].weight.data = dynamics_relu_no_thetadot[ 4].weight.data dynamics_relu_thetadot[4].bias.data = dynamics_relu_thetadot[ 4].bias.data self.dut_thetadot_input = unicycle.UnicycleReLUZeroVelModel( self.dtype, x_lo=torch.tensor([-3, -3, -np.pi], dtype=self.dtype), x_up=torch.tensor([3, 3, np.pi], dtype=self.dtype), u_lo=torch.tensor([-2, -0.5], dtype=self.dtype), u_up=torch.tensor([5, 0.5], dtype=self.dtype), dynamics_relu=dynamics_relu_thetadot, dt=0.01, thetadot_as_input=True) def step_forward_tester(self, dut): # First make sure that if vel = 0, then pos[n+1] = pos[n] x_start = torch.tensor([0.5, 0.3, -1.2], dtype=self.dtype) u_start = torch.tensor([0, 0.5], dtype=self.dtype) np.testing.assert_allclose( dut.step_forward(x_start, u_start)[:2].detach().numpy(), x_start[:2].detach().numpy()) # First test a single x_start and u_start x_start = torch.tensor([0.2, 0.5, -0.1], dtype=self.dtype) u_start = torch.tensor([2.1, 0.3], dtype=self.dtype) x_next = dut.step_forward(x_start, u_start) def eval_next_state(x_val, u_val): if dut.thetadot_as_input: network_input = torch.tensor([x_val[2], u_val[0], u_val[1]], dtype=self.dtype) network_input_zero_vel = torch.tensor([x_val[2], 0, u_val[1]], dtype=self.dtype) else: network_input = torch.tensor([x_val[2], u_val[0]], dtype=self.dtype) network_input_zero_vel = torch.tensor([x_val[2], 0], dtype=self.dtype) position_next = x_val[:2] + \ dut.dynamics_relu(network_input) - dut.dynamics_relu( network_input_zero_vel) theta_next = x_val[2] + u_val[1] * dut.dt return np.array([ position_next[0].item(), position_next[1].item(), theta_next.item() ]) np.testing.assert_allclose(x_next.detach().numpy(), eval_next_state(x_start, u_start)) # Now test a batch of x_start and u_start x_start = torch.tensor([[0.2, 0.5, -0.1], [0.4, 0.3, 0.5]], dtype=self.dtype) u_start = torch.tensor([[2.1, 0.3], [-0.3, 0.4]], dtype=self.dtype) x_next = dut.step_forward(x_start, u_start) self.assertEqual(x_next.shape, (2, 3)) for i in range(x_start.shape[0]): np.testing.assert_allclose(x_next[i].detach().numpy(), eval_next_state(x_start[i], u_start[i])) def test_step_forward_thetadot_not_input(self): self.step_forward_tester(self.dut_thetadot_not_input) def test_step_forward_thetadot_as_input(self): self.step_forward_tester(self.dut_thetadot_input) def add_dynamics_constraint_tester(self, dut): def tester(x_val, u_val): # Setup an MILP with fixed x_var and u_var, check if x_next_var is # solved to the right value. mip = gurobi_torch_mip.GurobiTorchMILP(self.dtype) x_var = mip.addVars(3, lb=-gurobipy.GRB.INFINITY) u_var = mip.addVars(2, lb=-gurobipy.GRB.INFINITY) x_next_var = mip.addVars(3, lb=-gurobipy.GRB.INFINITY) dut.add_dynamics_constraint(mip, x_var, x_next_var, u_var, "slack", "binary") # Fix x_var to x_val, u_var to u_val mip.addMConstrs([torch.eye(3, dtype=self.dtype)], [x_var], sense=gurobipy.GRB.EQUAL, b=x_val) mip.addMConstrs([torch.eye(2, dtype=self.dtype)], [u_var], sense=gurobipy.GRB.EQUAL, b=u_val) mip.gurobi_model.setParam(gurobipy.GRB.Param.OutputFlag, False) mip.gurobi_model.optimize() self.assertEqual(mip.gurobi_model.status, gurobipy.GRB.Status.OPTIMAL) x_next_val = np.array([var.xn for var in x_next_var]) x_next_val_expected = dut.step_forward(x_val, u_val) np.testing.assert_allclose(x_next_val, x_next_val_expected.detach().numpy(), atol=1e-8) tester(torch.tensor([0., 0., 0.], dtype=self.dtype), torch.tensor([0., 0.], dtype=self.dtype)) tester(torch.tensor([0.5, -0.3, 0.4], dtype=self.dtype), torch.tensor([0., 0.], dtype=self.dtype)) tester(torch.tensor([0.6, -1.3, 0.4], dtype=self.dtype), torch.tensor([4., 0.3], dtype=self.dtype)) tester(torch.tensor([0.6, -1.3, 0.4], dtype=self.dtype), torch.tensor([-2., 0.3], dtype=self.dtype)) def test_add_dynamics_constraint_thetadot_not_input(self): self.add_dynamics_constraint_tester(self.dut_thetadot_not_input) def test_add_dynamics_constraint_thetadot_as_input(self): self.add_dynamics_constraint_tester(self.dut_thetadot_input) if __name__ == "__main__": unittest.main()

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7

2b5f15fc1346fc0b8a38460066380ca206ff4637

2,850

py

Python

opp_function.py

LukeKort/OCM

674f73dcfeb86aa58d67fbe0abf8a997dff439a7

[ "MIT" ]

null

opp_function.py

LukeKort/OCM

674f73dcfeb86aa58d67fbe0abf8a997dff439a7

[ "MIT" ]

null

opp_function.py

LukeKort/OCM

674f73dcfeb86aa58d67fbe0abf8a997dff439a7

[ "MIT" ]

null

# Objectives and constraints functions (Aug. 04, 2021) import math import numpy as np def objective(var_o): #objetive functions Weibull #confiabilidade gamma_ = theta = t = int(math.floor(var_o.copy())) r_t = math.exp(-((t/theta)**(gamma_))) #custo c_m = 1000 c_r = 2500 c_inc = 10000 t_ser = 87600 mttf = c_t = (t_ser/t)*c_m*r_t + (t_ser/mttf)*(c_r+c_inc)*(1-r_t) #função objetivo y = c_t return y def constraints(var_c): #constraint functions #confiabilidade gamma_ = theta = lim = #limite t = int(math.floor(var_c.copy())) r_t = math.exp(-((t/theta)**(gamma_))) #disponibilidade t_m = #tempo de reparo t_r = #tempo de manutenção a_t = t/(t + r_t*t_m + (1-r_t)*t_r) #Substituir r_t por a_t para usar função de confiabilidade como restrição #constraint functions 1 to n if (r_t >= lim): #test conditions 1 to n return True #all conditions has been met else: return False #one or mor_t condition hasn't been met def objective(var_o): #objetive functions Lognormal #confiabilidade mu = 5.9093828021596 sigma = 0.486238331177103 t = int(math.floor(var_o.copy())) z = (mu - math.log(var_o))/sigma termo_1 = ((4-math.pi)*abs(abs(z)) + math.sqrt(2*math.pi)*(math.pi-2)) termo_2 = (((4-math.pi)*math.sqrt(2*math.pi)*abs(z)**2)+(2*math.pi*abs(z))+(2*math.sqrt(2*math.pi)*(math.pi-2))) termo_3 = math.exp(-(abs(z)**2)/2) if z < 0: r_t = 1-((termo_1/termo_2)*termo_3) else: r_t = 1 - (1-((termo_1/termo_2)*termo_3)) #custo c_m = 1000 c_r = 2500 c_inc = 10000 t_ser = 87600 mttf = 413 c_t = (t_ser/t)*c_m*r_t + (t_ser/mttf)*(c_r+c_inc)*(1-r_t) #função objetivo y = c_t return y def constraints(var_c): #constraint functions #confiabilidade mu = 5.9093828021596 sigma = 0.486238331177103 t = int(math.floor(var_c.copy())) z = (mu - math.log(var_c))/sigma termo_1 = ((4-math.pi)*abs(abs(z)) + math.sqrt(2*math.pi)*(math.pi-2)) termo_2 = (((4-math.pi)*math.sqrt(2*math.pi)*abs(z)**2)+(2*math.pi*abs(z))+(2*math.sqrt(2*math.pi)*(math.pi-2))) termo_3 = math.exp(-(abs(z)**2)/2) if z < 0: r_t = 1-((termo_1/termo_2)*termo_3) else: r_t = 1 - (1-((termo_1/termo_2)*termo_3)) #disponibilidade t_m = 3 #tempo de reparo t_r = 5 #tempo de manutenção a_t = t/(t + r_t*t_m + (1-r_t)*t_r) #Substituir r_t por a_t para usar função de confiabilidade como restrição #constraint functions 1 to n if (a_t >= 0.99): #test conditions 1 to n return True #all conditions has been met else: return False #one or mor_t condition hasn't been met

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0

8

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3,293

py

Python

选拔赛/code/折线图2.py

775269512/WHUT_CUMCM20

a966c09e46c1789a86d4532f46d503a2226e0a47

[ "MIT" ]

73

2020-09-20T15:39:26.000Z

2022-03-10T23:37:17.000Z

选拔赛/code/折线图2.py

HHHTTY/WHUT_CUMCM20

a966c09e46c1789a86d4532f46d503a2226e0a47

[ "MIT" ]

3

2021-09-18T04:43:08.000Z

2021-12-02T08:10:53.000Z

选拔赛/code/折线图2.py

HHHTTY/WHUT_CUMCM20

a966c09e46c1789a86d4532f46d503a2226e0a47

[ "MIT" ]

27

2020-09-20T15:39:29.000Z

2022-02-28T12:15:06.000Z

from pylab import * mpl.rcParams['font.sans-serif'] = ['SimHei'] # import matplotlib.pyplot as plt import numpy import matplotlib.colors as colors import matplotlib.cm as cmx dicts = {"1":[3,2], "2":[1,5], "3":[5,4],"4":[4,7], "5":[0,8],"6":[3,11],"7":[7,9], "8":[9,6],"9":[10,2], "10":[14,0],"11":[2,16], "12":[6,18],"13":[11,17],"14":[15,12], "15":[19,9],"16":[22,5], "17":[21,0],"18":[27,9], "19":[15,19],"0":[10,10],} x_axis_data = [] y_axis_data = [] cars = [12 ,11 ,0 ,15, 16, 0 ,5 ,2, 0, 14, 19, 13, 0, 4 ,6, 0, 18, 0 ,17, 10,0, 7, 0, 9, 1,0] #0, 3, 8, c_ = [] x = [0] for j in range(len(cars)): x.append(cars[j]) if cars[j]==0: c_.append(x) x = [0] print(c_) cmap = plt.cm.jet cNorm = colors.Normalize(vmin=0, vmax=len(c_)) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap) for fff in range(len(c_)): ########### x_axis_data = [] y_axis_data = [] road = c_[fff] x_tem = [] y_tem = [] for i in range(len(road)): x = str(road[i]) x_axis_data.append(dicts[x][0]) y_axis_data.append(dicts[x][1]) try: x_tem.append(dicts[str(road[i + 1])][0]) y_tem.append(dicts[str(road[i])][1]) except: pass x_ = [] y_ = [] for i in range(len(x_tem)): x_.append(x_axis_data[i]) y_.append(y_axis_data[i]) x_.append(x_tem[i]) y_.append(y_tem[i]) colorVal = scalarMap.to_rgba(fff) x_.append(x_axis_data[i + 1]) y_.append(y_axis_data[i + 1]) plt.plot(x_, y_, 'ro-', alpha=0.8) for i in range(0,len(x_)-1): plt.arrow(x_[i], y_[i], x_[i+1] - x_[i], y_[i+1] - y_[i], length_includes_head=True, head_width=0.3, lw=2,) for x, y in zip(x_axis_data, y_axis_data): plt.text(x, y + 0.3, '({},{})'.format(x, y),) plt.xlabel('X轴/km') plt.ylabel('Y轴/km') cars = [3, 8,0] #0, 3, 8, c_ = [] x = [0] for j in range(len(cars)): x.append(cars[j]) if cars[j]==0: c_.append(x) x = [0] print(c_) cmap = plt.cm.jet cNorm = colors.Normalize(vmin=0, vmax=len(c_)) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap) for fff in range(len(c_)): ########### x_axis_data = [] y_axis_data = [] road = c_[fff] x_tem = [] y_tem = [] for i in range(len(road)): x = str(road[i]) x_axis_data.append(dicts[x][0]) y_axis_data.append(dicts[x][1]) try: x_tem.append(dicts[str(road[i + 1])][0]) y_tem.append(dicts[str(road[i])][1]) except: pass x_ = [] y_ = [] for i in range(len(x_tem)): x_.append(x_axis_data[i]) y_.append(y_axis_data[i]) x_.append(x_tem[i]) y_.append(y_tem[i]) colorVal = scalarMap.to_rgba(fff) x_.append(x_axis_data[i + 1]) y_.append(y_axis_data[i + 1]) plt.plot(x_, y_, 'o-', alpha=0.8) # for i in range(0,len(x_)-1): # plt.arrow(x_[i], y_[i], x_[i+1] - x_[i], y_[i+1] - y_[i], # length_includes_head=True, head_width=0.3, lw=2,) for x, y in zip(x_axis_data, y_axis_data): plt.text(x, y + 0.3, '({},{})'.format(x, y),) plt.xlabel('X轴/km') plt.ylabel('Y轴/km') plt.show() # plt.savefig('demo.jpg') # 保存该图片

25.330769

93

0.51898

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3,293

2.711375

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0.041327

0.809017

0.797746

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0.071778

0.25539

3,293

130

94

25.330769

0.579527

0.07106

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0.836735

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1

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false

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0.020408

0

null

0

1

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0

null

0

7

992796fdb5509a43c66de22e35452020e2354baf

930

py

Python

LeetCode/easy - Hash Table/771. Jewels and Stones/solution.py

vincent507cpu/Comprehensive-Algorithm-Solution

04e01e49622457f09af2e1133954f043c0c92cb9

[ "MIT" ]

4

2020-06-26T00:45:53.000Z

2021-04-19T12:23:32.000Z

LeetCode/easy - Hash Table/771. Jewels and Stones/solution.py

vincent507cpu/LeetCode-Comprehensive-Solution

04e01e49622457f09af2e1133954f043c0c92cb9

[ "MIT" ]

null

LeetCode/easy - Hash Table/771. Jewels and Stones/solution.py

vincent507cpu/LeetCode-Comprehensive-Solution

04e01e49622457f09af2e1133954f043c0c92cb9

[ "MIT" ]

null

# comprehensive solution class Solution: def numJewelsInStones(self, J: str, S: str) -> int: # https://leetcode.com/problems/jewels-and-stones/discuss/527360/Several-Python-solution.-w-Explanation jewel = set(J) return sum( 1 for item in S if item in jewel ) def numJewelsInStones(self, J: str, S: str) -> int: # https://leetcode.com/problems/jewels-and-stones/discuss/527360/Several-Python-solution.-w-Explanation return sum( S.count(jewel) for jewel in J ) def numJewelsInStones(self, J: str, S: str) -> int: # https://leetcode.com/problems/jewels-and-stones/discuss/?currentPage=1&orderBy=most_votes&query= return sum(s in J for s in S) def numJewelsInStones(self, J: str, S: str) -> int: # https://leetcode.com/problems/jewels-and-stones/discuss/?currentPage=1&orderBy=most_votes&query= return sum(map(J.count, S))

48.947368

111

0.662366

130

930

4.723077

0.3

0.130293

0.156352

0.162866

0.791531

0

0.02027

0.204301

930

19

112

48.947368

0.809459

0.451613

0

0.4

0

1

0.4

false

0

0.3

0.9

0

null

0

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0

1

0

null

0

1

0

1

0

9

996523a41a0eb3794adde74163976cf3f1b14f36

7,502

py

Python

penduduk/kabupaten/hitunggolongandarah.py

bowo-anakdesa/count-sidekem

8737d6cc788ba51ec6f919dbc2cedcced76ea139

[ "MIT" ]

1

2019-06-28T02:02:51.000Z

penduduk/kabupaten/hitunggolongandarah.py

bowo-anakdesa/count-sidekem

8737d6cc788ba51ec6f919dbc2cedcced76ea139

[ "MIT" ]

1

2019-08-03T18:39:33.000Z

penduduk/kabupaten/hitunggolongandarah.py

bowo-anakdesa/count-sidekem

8737d6cc788ba51ec6f919dbc2cedcced76ea139

[ "MIT" ]

null

import pymysql db = pymysql.connect(host="localhost",user="root",passwd="12345678", db="sidekem") cur = db.cursor() cur.execute("SELECT id FROM `statistik_goldarah_kab` WHERE id LIKE '%3327%' ") kabupaten=cur.fetchall() for a in kabupaten: #Total Golongan Darah cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'A' ") goldar1 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'B' ") goldar2 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'AB' ") goldar3 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'O' ") goldar4 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'A+' ") goldar5 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'A-' ") goldar6 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'B+' ") goldar7 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'B-' ") goldar8 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'AB+' ") goldar9 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'AB-' ") goldar10 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'O+' ") goldar11 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah LIKE 'O-' ") goldar12 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND goldarah IN('-','','Tidak Tahu','Tdk Tahu') ") goldar13 = str(cur.fetchone()[0]) #Laki-laki cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'A' ") goldar14 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'B' ") goldar15 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'AB' ") goldar16 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'O' ") goldar17 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'A+' ") goldar18 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'A-' ") goldar19 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'B+' ") goldar20 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'B-' ") goldar21 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'AB+' ") goldar22 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'AB-' ") goldar23 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'O+' ") goldar24 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah LIKE 'O-' ") goldar25 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'L%' AND goldarah IN('-','','Tidak Tahu','Tdk Tahu') ") goldar26 = str(cur.fetchone()[0]) #Perempuan cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'A' ") goldar27 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'B' ") goldar28 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'AB' ") goldar29 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'O' ") goldar30 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'A+' ") goldar31 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'A-' ") goldar32 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'B+' ") goldar33 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'B-' ") goldar34 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'AB+' ") goldar35 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'AB-' ") goldar36 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'O+' ") goldar37 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah LIKE 'O-' ") goldar38 = str(cur.fetchone()[0]) cur.execute("SELECT COUNT(*) FROM `datapenduduk-33` WHERE kab_id='"+a[0]+"' AND jk LIKE 'P%' AND goldarah IN('-','','Tidak Tahu','Tdk Tahu') ") goldar39 = str(cur.fetchone()[0]) #Eksekusi cur.execute("UPDATE `statistik_goldarah_kab` SET `total_a`='"+goldar1+"', `total_b`='"+goldar2+"', `total_ab`='"+goldar3+"', `total_o`='"+goldar4+"', `total_a+`='"+goldar5+"', `total_a-`='"+goldar6+"', `total_b+`='"+goldar7+"', `total_b-`='"+goldar8+"', `total_ab+`='"+goldar9+"', `total_ab-`='"+goldar10+"', `total_o+`='"+goldar11+"', `total_o-`='"+goldar12+"', `total_tdk_tahu`='"+goldar13+"', `lk_a`='"+goldar14+"', `lk_b`='"+goldar15+"', `lk_ab`='"+goldar16+"', `lk_o`='"+goldar17+"', `lk_a+`='"+goldar18+"', `lk_a-`='"+goldar19+"', `lk_b+`='"+goldar20+"', `lk_b-`='"+goldar21+"', `lk_ab+`='"+goldar22+"', `lk_ab-`='"+goldar23+"', `lk_o+`='"+goldar24+"', `lk_o-`='"+goldar25+"', `lk_tdk_tahu`='"+goldar26+"', `pr_a`='"+goldar27+"', `pr_b`='"+goldar28+"', `pr_ab`='"+goldar29+"', `pr_o`='"+goldar30+"', `pr_a+`='"+goldar31+"', `pr_a-`='"+goldar32+"', `pr_b+`='"+goldar33+"', `pr_b-`='"+goldar34+"', `pr_ab+`='"+goldar35+"', `pr_ab-`='"+goldar36+"', `pr_o+`='"+goldar37+"', `pr_o-`='"+goldar38+"', `pr_tdk_tahu`='"+goldar39+"' WHERE id='"+a[0]+"' ") db.commit()

83.355556

1,055

0.620501

1,107

7,502

4.128275

0.084914

0.089716

0.140044

0.179212

0.75733

0.745514

0

0.047678

0.141696

7,502

90

1,056

83.355556

0.662059

0.006132

0

0.565678

0.00644

0

1

0

false

0.011628

0

0.011628

0

null

0

1

0

1

0

1

0

null

0

7

9984290ad62ac9fca12bf6d7cea4d184b367d13a

13,405

py

Python

essentials_kit_management/tests/interactors/test_get_form_interactor.py

RajeshKumar1490/iB_hubs_mini_project

f7126092400fb9a62fb4bff643dae7cda3a8d9d2

[ "MIT" ]

null

essentials_kit_management/tests/interactors/test_get_form_interactor.py

RajeshKumar1490/iB_hubs_mini_project

f7126092400fb9a62fb4bff643dae7cda3a8d9d2

[ "MIT" ]

2

2021-09-07T07:06:00.000Z

2021-09-07T07:24:26.000Z

essentials_kit_management/tests/interactors/test_get_form_interactor.py

RajeshKumar1490/iB_hubs_mini_project

f7126092400fb9a62fb4bff643dae7cda3a8d9d2

[ "MIT" ]

null

import pytest from mock import create_autospec from django_swagger_utils.drf_server.exceptions import NotFound from essentials_kit_management.interactors.get_form_interactor \ import GetFormInteractor from essentials_kit_management.interactors.storages.dtos \ import FormMetricsDto, FormDetailsDto, CompleteFormDetailsDto from essentials_kit_management.interactors.storages.form_storage_interface \ import FormStorageInterface from essentials_kit_management.interactors.storages.\ order_item_storage_interface import OrderItemStorageInterface from essentials_kit_management.interactors.presenters.presenter_interface \ import PresenterInterface def test_get_form_interactor_with_valid_form_id_returns_forms_details( section_dtos, item_dtos, brand_dtos, ordered_item_dtos, form_mock_presenter_response): #Arrange form_id = 1 user_id = 1 form_storage = create_autospec(FormStorageInterface) order_item_storage = create_autospec(OrderItemStorageInterface) presenter = create_autospec(PresenterInterface) interactor = GetFormInteractor( form_storage=form_storage, order_item_storage=order_item_storage, presenter=presenter ) mock_form_details = FormDetailsDto( form_id=1, form_name='SnacksForm', form_description='This is form', close_date='2020-05-17 20:22:46', section_dtos=section_dtos, item_dtos=item_dtos, brand_dtos=brand_dtos ) mock_ordered_items = ordered_item_dtos mock_presenter_response = form_mock_presenter_response complete_form_details_dto = CompleteFormDetailsDto( form_details_dto=mock_form_details, ordered_item_dtos=mock_ordered_items ) expected_form_metrics_dto = \ FormMetricsDto(total_cost=4500.0, total_items=15) form_storage.validate_form_id.return_value = True form_storage.get_form_details_dto.return_value = mock_form_details order_item_storage.get_user_ordered_item_dtos_of_form.return_value = \ mock_ordered_items presenter.get_form_details_response.return_value = mock_presenter_response #Act form_details = interactor.get_form_details( form_id=form_id, user_id=user_id ) #Assert assert form_details == mock_presenter_response form_storage.validate_form_id.assert_called_once_with(form_id=form_id) form_storage.get_form_details_dto.assert_called_once_with( form_id=form_id, user_id=user_id ) order_item_storage.get_user_ordered_item_dtos_of_form.\ assert_called_once_with(item_dtos=item_dtos, user_id=user_id) presenter.get_form_details_response.assert_called_once_with( complete_form_details_dto=complete_form_details_dto, form_metrics_dto=expected_form_metrics_dto ) def test_get_form_interactor_when_no_sections_returns_empty_section_list( item_dtos, brand_dtos, ordered_item_dtos, form_mock_presenter_response): #Arrange form_id = 1 user_id = 1 form_storage = create_autospec(FormStorageInterface) order_item_storage = create_autospec(OrderItemStorageInterface) presenter = create_autospec(PresenterInterface) interactor = GetFormInteractor( form_storage=form_storage, order_item_storage=order_item_storage, presenter=presenter ) mock_form_details = FormDetailsDto( form_id=1, form_name='SnacksForm', form_description='This is form', close_date='2020-05-17 20:22:46', section_dtos=[], item_dtos=item_dtos, brand_dtos=brand_dtos ) mock_ordered_items = ordered_item_dtos mock_presenter_response = form_mock_presenter_response complete_form_details_dto = CompleteFormDetailsDto( form_details_dto=mock_form_details, ordered_item_dtos=mock_ordered_items ) expected_form_metrics_dto = \ FormMetricsDto(total_cost=4500.0, total_items=15) form_storage.validate_form_id.return_value = True form_storage.get_form_details_dto.return_value = mock_form_details order_item_storage.get_user_ordered_item_dtos_of_form.return_value = \ mock_ordered_items presenter.get_form_details_response.return_value = mock_presenter_response #Act form_details = interactor.get_form_details( form_id=form_id, user_id=user_id ) #Assert assert form_details == mock_presenter_response form_storage.validate_form_id.assert_called_once_with(form_id=form_id) form_storage.get_form_details_dto.assert_called_once_with( form_id=form_id, user_id=user_id ) order_item_storage.get_user_ordered_item_dtos_of_form.\ assert_called_once_with(item_dtos=item_dtos, user_id=user_id) presenter.get_form_details_response.assert_called_once_with( complete_form_details_dto=complete_form_details_dto, form_metrics_dto=expected_form_metrics_dto ) def test_get_form_interactor_when_no_items_returns_empty_items_list( section_dtos, brand_dtos, ordered_item_dtos, form_mock_presenter_response): #Arrange form_id = 1 user_id = 1 form_storage = create_autospec(FormStorageInterface) order_item_storage = create_autospec(OrderItemStorageInterface) presenter = create_autospec(PresenterInterface) interactor = GetFormInteractor( form_storage=form_storage, order_item_storage=order_item_storage, presenter=presenter ) item_dtos = [] mock_form_details = FormDetailsDto( form_id=1, form_name='SnacksForm', form_description='This is form', close_date='2020-05-17 20:22:46', section_dtos=section_dtos, item_dtos=item_dtos, brand_dtos=brand_dtos ) mock_ordered_items = ordered_item_dtos mock_presenter_response = form_mock_presenter_response complete_form_details_dto = CompleteFormDetailsDto( form_details_dto=mock_form_details, ordered_item_dtos=mock_ordered_items ) expected_form_metrics_dto = \ FormMetricsDto(total_cost=4500.0, total_items=15) form_storage.validate_form_id.return_value = True form_storage.get_form_details_dto.return_value = mock_form_details order_item_storage.get_user_ordered_item_dtos_of_form.return_value = \ mock_ordered_items presenter.get_form_details_response.return_value = mock_presenter_response #Act form_details = interactor.get_form_details( form_id=form_id, user_id=user_id ) #Assert assert form_details == mock_presenter_response form_storage.validate_form_id.assert_called_once_with(form_id=form_id) form_storage.get_form_details_dto.assert_called_once_with( form_id=form_id, user_id=user_id ) order_item_storage.get_user_ordered_item_dtos_of_form.\ assert_called_once_with(item_dtos=item_dtos, user_id=user_id) presenter.get_form_details_response.assert_called_once_with( complete_form_details_dto=complete_form_details_dto, form_metrics_dto=expected_form_metrics_dto ) def test_get_form_interactor_when_no_brands_returns_empty_brands_list( item_dtos, section_dtos, ordered_item_dtos, form_mock_presenter_response): #Arrange form_id = 1 user_id = 1 form_storage = create_autospec(FormStorageInterface) order_item_storage = create_autospec(OrderItemStorageInterface) presenter = create_autospec(PresenterInterface) interactor = GetFormInteractor( form_storage=form_storage, order_item_storage=order_item_storage, presenter=presenter ) mock_form_details = FormDetailsDto( form_id=1, form_name='SnacksForm', form_description='This is form', close_date='2020-05-17 20:22:46', section_dtos=section_dtos, item_dtos=item_dtos, brand_dtos=[] ) mock_ordered_items = ordered_item_dtos mock_presenter_response = form_mock_presenter_response complete_form_details_dto = CompleteFormDetailsDto( form_details_dto=mock_form_details, ordered_item_dtos=mock_ordered_items ) expected_form_metrics_dto = \ FormMetricsDto(total_cost=4500.0, total_items=15) form_storage.validate_form_id.return_value = True form_storage.get_form_details_dto.return_value = mock_form_details order_item_storage.get_user_ordered_item_dtos_of_form.return_value = \ mock_ordered_items presenter.get_form_details_response.return_value = mock_presenter_response #Act form_details = interactor.get_form_details( form_id=form_id, user_id=user_id ) #Assert assert form_details == mock_presenter_response form_storage.validate_form_id.assert_called_once_with(form_id=form_id) form_storage.get_form_details_dto.assert_called_once_with( form_id=form_id, user_id=user_id ) order_item_storage.get_user_ordered_item_dtos_of_form.\ assert_called_once_with(item_dtos=item_dtos, user_id=user_id) presenter.get_form_details_response.assert_called_once_with( complete_form_details_dto=complete_form_details_dto, form_metrics_dto=expected_form_metrics_dto ) def test_get_form_interactor_when_no_ordered_items_returns_empty_ordered_items_list( item_dtos, section_dtos, brand_dtos, form_mock_presenter_response): #Arrange form_id = 1 user_id = 1 form_storage = create_autospec(FormStorageInterface) order_item_storage = create_autospec(OrderItemStorageInterface) presenter = create_autospec(PresenterInterface) interactor = GetFormInteractor( form_storage=form_storage, order_item_storage=order_item_storage, presenter=presenter ) mock_form_details = FormDetailsDto( form_id=1, form_name='SnacksForm', form_description='This is form', close_date='2020-05-17 20:22:46', section_dtos=section_dtos, item_dtos=item_dtos, brand_dtos=brand_dtos ) mock_ordered_items = [] mock_presenter_response = form_mock_presenter_response complete_form_details_dto = CompleteFormDetailsDto( form_details_dto=mock_form_details, ordered_item_dtos=mock_ordered_items ) expected_form_metrics_dto = \ FormMetricsDto(total_cost=0.0, total_items=0) form_storage.validate_form_id.return_value = True form_storage.get_form_details_dto.return_value = mock_form_details order_item_storage.get_user_ordered_item_dtos_of_form.return_value = \ mock_ordered_items presenter.get_form_details_response.return_value = mock_presenter_response #Act form_details = interactor.get_form_details( form_id=form_id, user_id=user_id ) #Assert assert form_details == mock_presenter_response form_storage.validate_form_id.assert_called_once_with(form_id=form_id) form_storage.get_form_details_dto.assert_called_once_with( form_id=form_id, user_id=user_id ) order_item_storage.get_user_ordered_item_dtos_of_form.\ assert_called_once_with(item_dtos=item_dtos, user_id=user_id) presenter.get_form_details_response.assert_called_once_with( complete_form_details_dto=complete_form_details_dto, form_metrics_dto=expected_form_metrics_dto ) def test_get_form_interactor_when_no_ordered_items_returns_metrics_values_zero( item_dtos, section_dtos, brand_dtos, form_mock_presenter_response): #Arrange form_id = 1 user_id = 1 form_storage = create_autospec(FormStorageInterface) order_item_storage = create_autospec(OrderItemStorageInterface) presenter = create_autospec(PresenterInterface) interactor = GetFormInteractor( form_storage=form_storage, order_item_storage=order_item_storage, presenter=presenter ) mock_form_details = FormDetailsDto( form_id=1, form_name='SnacksForm', form_description='This is form', close_date='2020-05-17 20:22:46', section_dtos=section_dtos, item_dtos=item_dtos, brand_dtos=brand_dtos ) mock_ordered_items = [] mock_presenter_response = form_mock_presenter_response complete_form_details_dto = CompleteFormDetailsDto( form_details_dto=mock_form_details, ordered_item_dtos=mock_ordered_items ) expected_form_metrics_dto = \ FormMetricsDto(total_cost=0.0, total_items=0) form_storage.validate_form_id.return_value = True form_storage.get_form_details_dto.return_value = mock_form_details order_item_storage.get_user_ordered_item_dtos_of_form.return_value = \ mock_ordered_items presenter.get_form_details_response.return_value = mock_presenter_response #Act form_details = interactor.get_form_details( form_id=form_id, user_id=user_id ) #Assert assert form_details == mock_presenter_response form_storage.validate_form_id.assert_called_once_with(form_id=form_id) form_storage.get_form_details_dto.assert_called_once_with( form_id=form_id, user_id=user_id ) order_item_storage.get_user_ordered_item_dtos_of_form.\ assert_called_once_with(item_dtos=item_dtos, user_id=user_id) presenter.get_form_details_response.assert_called_once_with( complete_form_details_dto=complete_form_details_dto, form_metrics_dto=expected_form_metrics_dto )

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999b9c18282b9bc65244eb14654afc97bc2b6dde

259

py

Python

03_GraphBasedPlanner/graph_ltpl/helper_funcs/src/__init__.py

f1tenth/ESweek2021_educationclassA3

7620a36d21c1824efba8a83f0671926bf8e028f3

[ "MIT" ]

15

2021-10-09T13:48:49.000Z

2022-03-27T04:36:44.000Z

03_GraphBasedPlanner/graph_ltpl/helper_funcs/src/__init__.py

yinflight/ESweek2021_educationclassA3

7a32bacdb7f3154a773d28b6b6abffdaa154a526

[ "MIT" ]

1

2021-11-27T01:47:25.000Z

2021-11-27T02:44:04.000Z

03_GraphBasedPlanner/graph_ltpl/helper_funcs/src/__init__.py

yinflight/ESweek2021_educationclassA3

7a32bacdb7f3154a773d28b6b6abffdaa154a526

[ "MIT" ]

2

2021-11-03T19:32:55.000Z

2021-11-27T02:43:13.000Z

import graph_ltpl.helper_funcs.src.calc_vel_profile_follow import graph_ltpl.helper_funcs.src.closest_path_index import graph_ltpl.helper_funcs.src.get_s_coord import graph_ltpl.helper_funcs.src.Logging import graph_ltpl.helper_funcs.src.calc_brake_emergency

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510a89e957ea22ea9acb65a1bf4c6b9c217069b3

194

py

Python

vnegmas/backend/api/nnegmas/__init__.py

YueNing/vnegmas

e95adc56ee9aab8d6cd6f28cce04383e199dc2b8

[ "MIT" ]

3

2019-06-29T11:40:29.000Z

2019-09-07T02:15:09.000Z

vnegmas/backend/api/nnegmas/__init__.py

YueNing/vnegmas

e95adc56ee9aab8d6cd6f28cce04383e199dc2b8

[ "MIT" ]

null

vnegmas/backend/api/nnegmas/__init__.py

YueNing/vnegmas

e95adc56ee9aab8d6cd6f28cce04383e199dc2b8

[ "MIT" ]

null

from vnegmas.backend.src import nnegmas from vnegmas.backend.src.nnegmas import negmas_draw from vnegmas.backend.api.nnegmas.negmas_api import * from vnegmas.backend.src.nnegmas import watch_fs

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510b206e3ad1fd0485010cb46e4d3eb0f14f22a5

121

py

Python

tests/context.py

lzutao/classical_cipher

95612f03600a31d7fe325f637335a4c69b56cf6c

[ "MIT" ]

null

tests/context.py

lzutao/classical_cipher

95612f03600a31d7fe325f637335a4c69b56cf6c

[ "MIT" ]

null

tests/context.py

lzutao/classical_cipher

95612f03600a31d7fe325f637335a4c69b56cf6c

[ "MIT" ]

null

#!/usr/bin/env python2 import sys import os sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

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1

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8

5ad32114346358b0ba04fcead845f3e40b3b8323

171

py

Python

apps/configuration/admin.py

Sunbird-Ed/evolve-api

371b39422839762e32401340456c13858cb8e1e9

[ "MIT" ]

1

2019-02-27T15:26:11.000Z

apps/configuration/admin.py

Sunbird-Ed/evolve-api

371b39422839762e32401340456c13858cb8e1e9

[ "MIT" ]

9

2019-12-16T10:09:46.000Z

2022-03-11T23:42:12.000Z

apps/configuration/admin.py

Sunbird-Ed/evolve-api

371b39422839762e32401340456c13858cb8e1e9

[ "MIT" ]

null

from django.contrib import admin # Register your models here. from .models import Book,State,Subject,Grade,Medium admin.site.register([Book,State,Subject,Grade,Medium])

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7

5c8a4475ba59114657523865785d3cbc17c30a33

11,761

py

Python

test/selenium/smoke/Service_Offering.py

elShiaLabeouf/cloudstack

3c5580632425ded5a468c3cd82cd141e7410ef39

[ "Apache-2.0" ]

1

2020-03-22T14:55:12.000Z

test/selenium/smoke/Service_Offering.py

elShiaLabeouf/cloudstack

3c5580632425ded5a468c3cd82cd141e7410ef39

[ "Apache-2.0" ]

null

test/selenium/smoke/Service_Offering.py

elShiaLabeouf/cloudstack

3c5580632425ded5a468c3cd82cd141e7410ef39

[ "Apache-2.0" ]

null

# 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 sys, os sys.path.append(os.path.abspath(os.path.dirname(__file__) + '/'+'../lib')) from selenium import webdriver from selenium.webdriver.common.by import By from selenium.webdriver.support.ui import Select from selenium.common.exceptions import NoSuchElementException import unittest, time import initialize import Global_Locators class Disk_offering_Add(unittest.TestCase): def setUp(self): self.driver = initialize.getOrCreateWebdriver() self.verificationErrors = [] def test_diskadd(self): driver = self.driver self.driver.implicitly_wait(200) #Make sure you are on Dashboard driver.find_element_by_xpath(Global_Locators.dashboard_xpath).click() time.sleep(2) # Go to Service Offerings driver.find_element_by_xpath(Global_Locators.serviceOfferings_xpath).click() #Select Disk offering driver.find_element_by_xpath(Global_Locators.Offering_disk_xpath).click() # Add offering driver.find_element_by_xpath(Global_Locators.Offering_add_xpath).click() # Following have names.. so they do not have their global entries. driver.find_element_by_name("name").clear() driver.find_element_by_name("name").send_keys("Test Disk Name") driver.find_element_by_name("description").clear() driver.find_element_by_name("description").send_keys("Test Disk Description") driver.find_element_by_name("disksize").clear() driver.find_element_by_name("disksize").send_keys("1") driver.find_element_by_xpath("//button[@type='button']").click() time.sleep(20) ##Verification will be if this offering shows up into table and we can actually edit it. def is_element_present(self, how, what): try: self.driver.find_element(by=how, value=what) except NoSuchElementException, e: return False return True def tearDown(self): self.assertEqual([], self.verificationErrors) class Disk_offering_Edit(unittest.TestCase): def setUp(self): self.driver = initialize.getOrCreateWebdriver() self.verificationErrors = [] def test_diskedit(self): driver = self.driver self.driver.implicitly_wait(200) #Make sure you are on Dashboard driver.find_element_by_xpath(Global_Locators.dashboard_xpath).click() time.sleep(2) # Go to Service Offerings driver.find_element_by_xpath(Global_Locators.serviceOfferings_xpath).click() #Select Disk offering driver.find_element_by_xpath(Global_Locators.Offering_disk_xpath).click() # We will be searching for our disk offering into the table linkclass = None linkclass = driver.find_elements_by_xpath(Global_Locators.Offering_table_xpath) # This returns a list of all Offerings in table for link in linkclass: if link.text == "Test Disk Name": link.click() time.sleep(2) # Click Edit driver.find_element_by_css_selector(Global_Locators.Offering_edit_css).click() #Change name driver.find_element_by_name(Global_Locators.Offering_editname_name).clear() driver.find_element_by_name(Global_Locators.Offering_editname_name).send_keys("Test Name") # Change Description driver.find_element_by_name(Global_Locators.Offering_editdescription_name).clear() driver.find_element_by_name(Global_Locators.Offering_editdescription_name).send_keys("Test Description") #Click Done driver.find_element_by_css_selector(Global_Locators.Offering_editdone_css).click() time.sleep(10) def is_element_present(self, how, what): try: self.driver.find_element(by=how, value=what) except NoSuchElementException, e: return False return True def tearDown(self): self.assertEqual([], self.verificationErrors) # Now we will find this offering and delete it!! class Disk_offering_Delete(unittest.TestCase): def setUp(self): self.driver = initialize.getOrCreateWebdriver() self.verificationErrors = [] def test_diskdelete(self): driver = self.driver self.driver.implicitly_wait(200) #Make sure you are on Dashboard driver.find_element_by_xpath(Global_Locators.dashboard_xpath).click() time.sleep(2) # Go to Service Offerings driver.find_element_by_xpath(Global_Locators.serviceOfferings_xpath).click() #Select Disk offering driver.find_element_by_xpath(Global_Locators.Offering_disk_xpath).click() ## Action part # We will be searching for our disk offering into the table linkclass = None linkclass = driver.find_elements_by_xpath(Global_Locators.Offering_table_xpath) # This returns a list of all Offerings in table for link in linkclass: if link.text == "Test Name": link.click() time.sleep(2) # Click Delete driver.find_element_by_css_selector(Global_Locators.Offering_delete_css).click() time.sleep(2) driver.find_element_by_xpath(Global_Locators.yesconfirmation_xapth).click() time.sleep(20) def is_element_present(self, how, what): try: self.driver.find_element(by=how, value=what) except NoSuchElementException, e: return False return True def tearDown(self): self.assertEqual([], self.verificationErrors) class Compute_offering_Add(unittest.TestCase): def setUp(self): self.driver = initialize.getOrCreateWebdriver() self.verificationErrors = [] def test_computeadd(self): driver = self.driver self.driver.implicitly_wait(200) #Make sure you are on Dashboard driver.find_element_by_xpath(Global_Locators.dashboard_xpath).click() time.sleep(2) # Go to Service Offerings driver.find_element_by_xpath(Global_Locators.serviceOfferings_xpath).click() #Select Compute offering driver.find_element_by_xpath(Global_Locators.Offering_compute_xpath).click() ## Action part # Add offering driver.find_element_by_xpath(Global_Locators.Offering_add_xpath).click() # Following do not have Global locators driver.find_element_by_id("label_name").clear() driver.find_element_by_id("label_name").send_keys("Test Compute Name") driver.find_element_by_id("label_description").clear() driver.find_element_by_id("label_description").send_keys("Test Compute Description") driver.find_element_by_id("label_num_cpu_cores").clear() driver.find_element_by_id("label_num_cpu_cores").send_keys("2") driver.find_element_by_id("label_cpu_mhz").clear() driver.find_element_by_id("label_cpu_mhz").send_keys("2000") driver.find_element_by_id("label_memory_mb").clear() driver.find_element_by_id("label_memory_mb").send_keys("2048") driver.find_element_by_id("label_network_rate").clear() driver.find_element_by_id("label_network_rate").send_keys("10") driver.find_element_by_id("label_offer_ha").click() driver.find_element_by_xpath("//button[@type='button']").click() time.sleep(2) #Make sure you are on Dashboard driver.find_element_by_xpath(Global_Locators.dashboard_xpath).click() time.sleep(30) def is_element_present(self, how, what): try: self.driver.find_element(by=how, value=what) except NoSuchElementException, e: return False return True def tearDown(self): self.assertEqual([], self.verificationErrors) class Compute_offering_Edit(unittest.TestCase): def setUp(self): self.driver = initialize.getOrCreateWebdriver() self.verificationErrors = [] def test_computeedit(self): driver = self.driver self.driver.implicitly_wait(200) #Make sure you are on Dashboard driver.find_element_by_xpath(Global_Locators.dashboard_xpath).click() time.sleep(2) ## Action part # Go to Service Offerings driver.find_element_by_xpath(Global_Locators.serviceOfferings_xpath).click() #Select Compute offering driver.find_element_by_xpath(Global_Locators.Offering_compute_xpath).click() # We will be searching for our disk offering into the table linkclass = None linkclass = driver.find_elements_by_xpath(Global_Locators.Offering_table_xpath) # This returns a list of all Offerings in table for link in linkclass: if link.text == "Test Compute Name": link.click() time.sleep(2) # Click Edit driver.find_element_by_css_selector(Global_Locators.Offering_edit_css).click() #Change name driver.find_element_by_name(Global_Locators.Offering_editname_name).clear() driver.find_element_by_name(Global_Locators.Offering_editname_name).send_keys("Test Name") # Change Description driver.find_element_by_name(Global_Locators.Offering_editdescription_name).clear() driver.find_element_by_name(Global_Locators.Offering_editdescription_name).send_keys("Test Description") #Click Done driver.find_element_by_css_selector(Global_Locators.Offering_editdone_css).click() time.sleep(10) def is_element_present(self, how, what): try: self.driver.find_element(by=how, value=what) except NoSuchElementException, e: return False return True def tearDown(self): self.assertEqual([], self.verificationErrors) class Compute_offering_Delete(unittest.TestCase): def setUp(self): self.driver = initialize.getOrCreateWebdriver() self.verificationErrors = [] def test_computedelete(self): driver = self.driver self.driver.implicitly_wait(200) #Make sure you are on Dashboard driver.find_element_by_xpath(Global_Locators.dashboard_xpath).click() time.sleep(2) # Go to Service Offerings driver.find_element_by_xpath(Global_Locators.serviceOfferings_xpath).click() #Select Compute offering driver.find_element_by_xpath(Global_Locators.Offering_compute_xpath).click() ## Action part # We will be searching for our disk offering into the table linkclass = None linkclass = driver.find_elements_by_xpath(Global_Locators.Offering_table_xpath) # This returns a list of all Offerings in table for link in linkclass: if link.text == "Test Name": link.click() time.sleep(2) # Click Delete driver.find_element_by_css_selector(Global_Locators.Offering_deletecompute_css).click() driver.find_element_by_xpath(Global_Locators.yesconfirmation_xapth).click() time.sleep(20) def is_element_present(self, how, what): try: self.driver.find_element(by=how, value=what) except NoSuchElementException, e: return False return True def tearDown(self): self.assertEqual([], self.verificationErrors)

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0.004998

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0.032787

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0.043716

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8

5cc17aac179e8f86aeefe515f5f4dd4eb5ddbe90

33,816

py

Python

test_pytest/test_sys/test_monitor/test_workflow.py

hrvojekeserica/hat-core

759def68620cf4f8c11e7bbbdbfd1e701dbafb09

[ "MIT" ]

null

test_pytest/test_sys/test_monitor/test_workflow.py

hrvojekeserica/hat-core

759def68620cf4f8c11e7bbbdbfd1e701dbafb09

[ "MIT" ]

null

test_pytest/test_sys/test_monitor/test_workflow.py

hrvojekeserica/hat-core

759def68620cf4f8c11e7bbbdbfd1e701dbafb09

[ "MIT" ]

null

import asyncio import pytest from hat import util from test_sys.test_monitor import common @pytest.mark.timeout(10) def test_server_listens(monitor_factory): server_info = monitor_factory() connections = server_info.process.connections() for port in {server_info.ui_port, server_info.monitor_port, server_info.master_port}: assert util.first(connections, lambda c: (c.laddr.ip == '0.0.0.0' and c.laddr.port == port)) @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_single_component(monitor_factory, component_factory, ui_client_factory): server_info = monitor_factory() component_name = 'name' component_group = 'group' component = await component_factory(component_name, component_group, server_info) ui_client = await ui_client_factory(server_info) info, components = await component.next_state() assert info is None assert components == [] info, components = await component.next_state() assert info.name == component_name assert info.group == component_group assert info.rank == 1 assert info.blessing is not None assert info.ready is None assert components == [info] ui_state = await ui_client.get_state() ui_info = common.find_ui_info(ui_state, info) assert ui_info assert ui_info['name'] == info.name assert ui_info['group'] == info.group component.client.set_ready(info.blessing) info, components = await component.next_state() assert info.blessing is not None assert info.ready is not None assert info.ready == info.blessing assert components == [info] ui_state = await ui_client.get_state() ui_info = common.find_ui_info(ui_state, info) assert ui_info assert ui_info['blessing'] == info.blessing assert ui_info['ready'] == ui_info['blessing'] component.client.set_ready(None) info, components = await component.next_state() assert info.ready is None assert info.blessing != info.ready assert components == [info] ui_state = await ui_client.get_state() ui_info = common.find_ui_info(ui_state, info) assert ui_info assert ui_info['blessing'] == info.blessing assert ui_info['ready'] is None await ui_client.set_rank(info, 5) info, components = await component.next_state() assert info.rank == 5 ui_state = await ui_client.get_state() ui_info = common.find_ui_info(ui_state, info) assert ui_info['rank'] == 5 @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_bless_all(cluster_factory): cluster = await cluster_factory({ 'g1': {'components': ['c1', 'c2']}, 'g2': {'components': ['c3']}}) component1 = cluster.components['g1']['c1'] component2 = cluster.components['g1']['c2'] component3 = cluster.components['g2']['c3'] ui_client = cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() info3, components3 = await component3.newest_state() ui_state = await ui_client.get_state() assert components1 == components2 and components2 == components3 assert info1.blessing is not None assert info2.blessing is not None assert info3.blessing is not None ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) ui_info3 = common.find_ui_info(ui_state, info3) assert ui_info1 and ui_info2 and ui_info3 assert ui_info1['blessing'] is not None assert ui_info2['blessing'] is not None assert ui_info3['blessing'] is not None component1.client.set_ready(info1.blessing) component2.client.set_ready(info2.blessing) component3.client.set_ready(info3.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() info3, components3 = await component3.newest_state() ui_state = await ui_client.get_state() assert info1.blessing is not None assert info2.blessing is not None assert info3.blessing is not None assert info1.ready == info1.blessing assert info2.ready == info2.blessing assert info3.ready == info3.blessing ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) ui_info3 = common.find_ui_info(ui_state, info3) assert ui_info1 and ui_info2 and ui_info3 assert ui_info1['ready'] == ui_info1['blessing'] assert ui_info2['ready'] == ui_info2['blessing'] assert ui_info3['ready'] == ui_info3['blessing'] await ui_client.set_rank(info1, 6) await ui_client.set_rank(info2, 2) await ui_client.set_rank(info3, 4) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() info3, components3 = await component3.newest_state() ui_state = await ui_client.get_state() assert info1.blessing is not None assert info2.blessing is not None assert info3.blessing is not None assert info1.rank == 6 assert info2.rank == 2 assert info3.rank == 4 @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_bless_one(cluster_factory): cluster = await cluster_factory({ 'group': { 'components': ['c1', 'c2']} }, default_algorithm='BLESS_ONE') component1 = cluster.components['group']['c1'] component2 = cluster.components['group']['c2'] ui_client = cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is not None assert info2.blessing is None assert ui_info1['blessing'] == info1.blessing assert ui_info2['blessing'] is None component1.client.set_ready(info1.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) assert info1.ready == info1.blessing assert ui_info1['ready'] == info1.ready assert ui_info1['blessing'] == ui_info1['ready'] await ui_client.set_rank(info1, 10) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is None assert info2.blessing is None assert ui_info1['blessing'] is None assert ui_info2['blessing'] is None component1.client.set_ready(None) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is None assert info2.blessing is not None assert ui_info1['blessing'] is None assert ui_info2['blessing'] == info2.blessing component2.client.set_ready(info2.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is None assert info2.blessing is not None and info2.blessing == info2.ready assert ui_info1['blessing'] is None assert ui_info2['ready'] == info2.ready @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_bless_all_group_setting(cluster_factory): cluster = await cluster_factory({ 'group': { 'algorithm': 'BLESS_ALL', 'components': ['c1', 'c2']} }, default_algorithm='BLESS_ONE') component1 = cluster.components['group']['c1'] component2 = cluster.components['group']['c2'] ui_client = cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() assert components1 == components2 assert info1.blessing is not None assert info2.blessing is not None ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert ui_info1 and ui_info2 assert ui_info1['blessing'] assert ui_info2['blessing'] component1.client.set_ready(info1.blessing) component2.client.set_ready(info2.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() assert info1.ready == info1.blessing assert info2.ready == info2.blessing ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert ui_info1 and ui_info2 assert ui_info1['ready'] == ui_info1['blessing'] assert ui_info2['ready'] == ui_info2['blessing'] await ui_client.set_rank(info1, 6) await ui_client.set_rank(info2, 2) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state = await ui_client.get_state() assert info1.blessing is not None and info2.blessing is not None assert info1.rank == 6 assert info2.rank == 2 @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_bless_one_group_setting(cluster_factory): cluster = await cluster_factory(group_conf={ 'redundant': { 'algorithm': 'BLESS_ONE', 'components': ['primary', 'secondary']}}) primary = cluster.components['redundant']['primary'] secondary = cluster.components['redundant']['secondary'] ui_client = cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await primary.newest_state() info2, components2 = await secondary.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is not None assert info2.blessing is None assert ui_info1['blessing'] == info1.blessing assert ui_info2['blessing'] is None primary.client.set_ready(info1.blessing) await asyncio.sleep(0.5) info1, components1 = await primary.newest_state() info2, components2 = await secondary.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) assert info1.ready == info1.blessing assert ui_info1['ready'] == info1.ready assert ui_info1['blessing'] == ui_info1['ready'] await ui_client.set_rank(info1, 10) await asyncio.sleep(0.5) info1, components1 = await primary.newest_state() info2, components2 = await secondary.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is None assert info2.blessing is None assert ui_info1['blessing'] is None assert ui_info2['blessing'] is None primary.client.set_ready(None) await asyncio.sleep(0.5) info1, components1 = await primary.newest_state() info2, components2 = await secondary.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is None assert info2.blessing is not None assert ui_info1['blessing'] is None assert ui_info2['blessing'] == info2.blessing secondary.client.set_ready(info2.blessing) await asyncio.sleep(0.5) info1, components1 = await primary.newest_state() info2, components2 = await secondary.newest_state() ui_state = await ui_client.get_state() ui_info1 = common.find_ui_info(ui_state, info1) ui_info2 = common.find_ui_info(ui_state, info2) assert info1.blessing is None assert info2.blessing is not None and info2.blessing == info2.ready assert ui_info1['blessing'] is None assert ui_info2['ready'] == info2.ready @pytest.mark.timeout(10) def test_master_slave(monitor_factory): slave = monitor_factory() master = monitor_factory(parent_infos=[slave]) assert util.first(master.process.connections(), lambda conn: (conn.raddr.port == slave.master_port and conn.raddr.ip == '127.0.0.1' if conn.raddr else False)) @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_peers_bless_all(cluster_factory): group_name = 'group' c1_name = 'c1' c2_name = 'c2' master_cluster = await cluster_factory({ group_name: {'components': [c1_name]}}) slave_cluster = await cluster_factory({ group_name: {'components': [c2_name]}}, parent_infos=[master_cluster.server_info]) component1 = master_cluster.components[group_name][c1_name] component2 = slave_cluster.components[group_name][c2_name] master_ui_client = master_cluster.ui_client slave_ui_client = slave_cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state_master = await master_ui_client.get_state() ui_state_slave = await slave_ui_client.get_state() assert components1 == components2 assert info1.blessing is not None assert info2.blessing is not None assert ui_state_master['components'] == ui_state_slave['components'] ui_info1 = common.find_ui_info(ui_state_master, info1) ui_info2 = common.find_ui_info(ui_state_master, info2) assert ui_info1 and ui_info2 assert ui_info1['blessing'] is not None assert ui_info2['blessing'] is not None component1.client.set_ready(info1.blessing) component2.client.set_ready(info2.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state_master = await master_ui_client.get_state() assert info1.ready == info1.blessing assert info2.ready == info2.blessing ui_info1 = common.find_ui_info(ui_state_master, info1) ui_info2 = common.find_ui_info(ui_state_master, info2) assert ui_info1 and ui_info2 assert ui_info1['ready'] == ui_info1['blessing'] assert ui_info2['ready'] == ui_info2['blessing'] await master_ui_client.set_rank(info1, 6) await master_ui_client.set_rank(info2, 2) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() ui_state_master = await master_ui_client.get_state() assert info1.blessing is not None and info2.blessing is not None assert info1.rank == 6 assert info2.rank == 2 @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_peers_bless_one(cluster_factory): group_name = 'group' c1_name = 'c1' c2_name = 'c2' master_cluster = await cluster_factory({ group_name: {'components': [c1_name]}}, default_algorithm='BLESS_ONE') slave_cluster = await cluster_factory({ group_name: {'components': [c2_name]}}, parent_infos=[master_cluster.server_info]) component1 = master_cluster.components[group_name][c1_name] component2 = slave_cluster.components[group_name][c2_name] master_ui_client = master_cluster.ui_client slave_ui_client = slave_cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is not None assert info2.blessing is None assert ui_info1['blessing'] == info1.blessing assert ui_info2['blessing'] is None component1.client.set_ready(info1.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) assert info1.ready == info1.blessing assert ui_info1['ready'] == info1.ready assert ui_info1['blessing'] == ui_info1['ready'] await master_ui_client.set_rank(info1, 10) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is None assert info2.blessing is None assert ui_info1['blessing'] is None assert ui_info2['blessing'] is None component1.client.set_ready(None) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is None assert info2.blessing is not None assert ui_info1['blessing'] is None assert ui_info2['blessing'] == info2.blessing component2.client.set_ready(info2.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is None assert info2.blessing is not None and info2.blessing == info2.ready assert ui_info1['blessing'] is None assert ui_info2['ready'] == info2.ready @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_peers_bless_all_group(cluster_factory): group_name = 'group' c1_name = 'c1' c2_name = 'c2' master_cluster = await cluster_factory({ group_name: { 'components': [c1_name], 'algorithm': 'BLESS_ALL'}}, default_algorithm='BLESS_ONE') slave_cluster = await cluster_factory({ group_name: {'components': [c2_name]}}, parent_infos=[master_cluster.server_info]) component1 = master_cluster.components[group_name][c1_name] component2 = slave_cluster.components[group_name][c2_name] master_ui_client = master_cluster.ui_client slave_ui_client = slave_cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert components1 == components2 assert info1.blessing is not None assert info2.blessing is not None assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert ui_info1 and ui_info2 assert ui_info1['blessing'] assert ui_info2['blessing'] component1.client.set_ready(info1.blessing) component2.client.set_ready(info2.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert info1.ready == info1.blessing assert info2.ready == info2.blessing assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert ui_info1 and ui_info2 assert ui_info1['ready'] == ui_info1['blessing'] assert ui_info2['ready'] == ui_info2['blessing'] await master_ui_client.set_rank(info1, 6) await master_ui_client.set_rank(info2, 2) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() assert info1.blessing is not None and info2.blessing is not None assert info1.rank == 6 assert info2.rank == 2 @pytest.mark.timeout(10) @pytest.mark.asyncio async def test_peers_bless_one_group(cluster_factory): group_name = 'group' c1_name = 'c1' c2_name = 'c2' master_cluster = await cluster_factory({ group_name: { 'components': [c1_name], 'algorithm': 'BLESS_ONE'}}) slave_cluster = await cluster_factory({ group_name: {'components': [c2_name]}}, parent_infos=[master_cluster.server_info]) component1 = master_cluster.components[group_name][c1_name] component2 = slave_cluster.components[group_name][c2_name] master_ui_client = master_cluster.ui_client slave_ui_client = slave_cluster.ui_client await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is not None assert info2.blessing is None assert ui_info1['blessing'] == info1.blessing assert ui_info2['blessing'] is None component1.client.set_ready(info1.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) assert info1.ready == info1.blessing assert ui_info1['ready'] == info1.ready assert ui_info1['blessing'] == ui_info1['ready'] await master_ui_client.set_rank(info1, 10) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is None assert info2.blessing is None assert ui_info1['blessing'] is None assert ui_info2['blessing'] is None component1.client.set_ready(None) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is None assert info2.blessing is not None assert ui_info1['blessing'] is None assert ui_info2['blessing'] == info2.blessing component2.client.set_ready(info2.blessing) await asyncio.sleep(0.5) info1, components1 = await component1.newest_state() info2, components2 = await component2.newest_state() master_ui_state = await master_ui_client.get_state() slave_ui_state = await slave_ui_client.get_state() assert master_ui_state['components'] == slave_ui_state['components'] ui_info1 = common.find_ui_info(master_ui_state, info1) ui_info2 = common.find_ui_info(master_ui_state, info2) assert info1.blessing is None assert ui_info2['ready'] == info2.ready @pytest.mark.timeout(10) @pytest.mark.asyncio @pytest.mark.parametrize('cluster_confs', [ [{ 'groups': { 'target_group': { 'components': ['c1', 'c2', 'c3']}}, 'default_algorithm': 'BLESS_ALL'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2', 'c3'], 'algorithm': 'BLESS_ALL'}}, 'default_algorithm': 'BLESS_ONE'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2']}}, 'default_algorithm': 'BLESS_ALL'}, { 'groups': { 'target_group': { 'components': ['c3', 'c4']}}, 'default_algorithm': 'BLESS_ALL'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2'], 'algorithm': 'BLESS_ALL'}}, 'default_algorithm': 'BLESS_ONE'}, { 'groups': { 'target_group': { 'components': ['c3', 'c4']}}, 'default_algorithm': 'BLESS_ALL'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2'], 'algorithm': 'BLESS_ALL'}}, 'default_algorithm': 'BLESS_ONE'}, { 'groups': { 'target_group': { 'components': ['c3', 'c4'], 'algorithm': 'BLESS_ONE'}}, 'default_algorithm': 'BLESS_ONE'}], ]) async def test_bless_all_behavior(cluster_factory, cluster_confs): clusters = [] target_components = [] ui_clients = [] for conf in cluster_confs: cluster = await cluster_factory( group_conf=conf['groups'], default_algorithm=conf['default_algorithm'], parent_infos=[cluster.server_info for cluster in clusters], default_rank=1) target_components.extend( cluster.components['target_group'].values()) clusters.append(cluster) ui_clients.append(cluster.ui_client) await asyncio.sleep(0.5) ui_states = [await ui_client.get_state() for ui_client in ui_clients] assert all([state['components'] == ui_states[0]['components'] for state in ui_states]) master_ui_state = ui_states[0] for component in target_components: info, components = await component.newest_state() ui_info = common.find_ui_info(master_ui_state, info) assert info.blessing is not None assert ui_info['blessing'] is not None assert info.blessing == ui_info['blessing'] component.client.set_ready(info.blessing) await asyncio.sleep(0.5) ui_states = [await ui_client.get_state() for ui_client in ui_clients] assert all([state['components'] == ui_states[0]['components'] for state in ui_states]) master_ui_state = ui_states[0] for component in target_components: info, components = await component.newest_state() ui_info = common.find_ui_info(master_ui_state, info) assert info.blessing is not None assert info.ready is not None assert info.blessing == info.ready assert ui_info['blessing'] is not None assert ui_info['ready'] is not None assert ui_info['blessing'] == ui_info['ready'] assert ui_info['blessing'] == info.ready @pytest.mark.timeout(10) @pytest.mark.asyncio @pytest.mark.parametrize('cluster_confs', [ [{ 'groups': { 'target_group': { 'components': ['c1', 'c2', 'c3']}}, 'default_algorithm': 'BLESS_ONE'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2', 'c3'], 'algorithm': 'BLESS_ONE'}}, 'default_algorithm': 'BLESS_ALL'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2']}}, 'default_algorithm': 'BLESS_ONE'}, { 'groups': { 'target_group': { 'components': ['c3', 'c4']}}, 'default_algorithm': 'BLESS_ONE'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2'], 'algorithm': 'BLESS_ONE'}}, 'default_algorithm': 'BLESS_ONE'}, { 'groups': { 'target_group': { 'components': ['c3', 'c4']}}, 'default_algorithm': 'BLESS_ONE'}], [{ 'groups': { 'target_group': { 'components': ['c1', 'c2'], 'algorithm': 'BLESS_ONE'}}, 'default_algorithm': 'BLESS_ALL'}, { 'groups': { 'target_group': { 'components': ['c3', 'c4'], 'algorithm': 'BLESS_ALL'}}, 'default_algorithm': 'BLESS_ALL'}], ]) async def test_bless_one_behavior(cluster_factory, cluster_confs): clusters = [] target_components = [] ui_clients = [] for conf in cluster_confs: cluster = await cluster_factory( group_conf=conf['groups'], default_algorithm=conf['default_algorithm'], parent_infos=[cluster.server_info for cluster in clusters], default_rank=1) target_components.extend( cluster.components['target_group'].values()) clusters.append(cluster) ui_clients.append(cluster.ui_client) await asyncio.sleep(0.5) ui_states = [await ui_client.get_state() for ui_client in ui_clients] assert all([state['components'] == ui_states[0]['components'] for state in ui_states]) ui_state = ui_states[0] blessings_count = 0 for component in target_components: info, components = await component.newest_state() ui_info = common.find_ui_info(ui_state, info) if info.blessing is not None: assert ui_info['blessing'] == info.blessing blessings_count += 1 else: assert ui_info['blessing'] is None component.client.set_ready(info.blessing) assert blessings_count == 1 await asyncio.sleep(0.5) ui_states = [await ui_client.get_state() for ui_client in ui_clients] assert all([state['components'] == ui_states[0]['components'] for state in ui_states]) ui_state = ui_states[0] blessed_index = None for (i, component) in enumerate(target_components): info, components = await component.newest_state() ui_info = common.find_ui_info(ui_state, info) if info.blessing is not None: assert info.blessing == info.ready assert ui_info['ready'] == info.ready assert ui_info['blessing'] == ui_info['ready'] await ui_clients[0].set_rank(info, 5) blessed_index = i else: assert info.ready is None assert ui_info['ready'] is None assert ui_info['blessing'] is None await asyncio.sleep(0.5) ui_states = [await ui_client.get_state() for ui_client in ui_clients] assert all([state['components'] == ui_states[0]['components'] for state in ui_states]) ui_state = ui_states[0] for (i, component) in enumerate(target_components): info, components = await component.newest_state() ui_info = common.find_ui_info(ui_state, info) assert info.blessing is None assert ui_info['blessing'] is None component.client.set_ready(info.blessing) await asyncio.sleep(0.5) ui_states = [await ui_client.get_state() for ui_client in ui_clients] assert all([state['components'] == ui_states[0]['components'] for state in ui_states]) ui_state = ui_states[0] blessings_count = 0 for (i, component) in enumerate(target_components): info, components = await component.newest_state() ui_info = common.find_ui_info(ui_state, info) if info.blessing is not None: assert i != blessed_index assert ui_info['blessing'] == info.blessing blessings_count += 1 component.client.set_ready(info.blessing) assert blessings_count == 1

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Python

webapp/tests/forms/steps/lotse/test_merkzeichen.py

digitalservice4germany/steuerlotse

ef3e094e4d7d4768431a50ac4be60672cd03221d

[ "MIT" ]

20

2021-07-02T07:49:08.000Z

2022-03-18T22:26:10.000Z

webapp/tests/forms/steps/lotse/test_merkzeichen.py

digitalservice4germany/steuerlotse

ef3e094e4d7d4768431a50ac4be60672cd03221d

[ "MIT" ]

555

2021-06-28T15:35:15.000Z

2022-03-31T11:51:55.000Z

webapp/tests/forms/steps/lotse/test_merkzeichen.py

digitalservice4germany/steuerlotse

ef3e094e4d7d4768431a50ac4be60672cd03221d

[ "MIT" ]

1

2021-07-04T20:34:12.000Z

import datetime import pytest from flask.sessions import SecureCookieSession from flask_babel import ngettext, lazy_gettext as _l from pydantic import ValidationError from werkzeug.datastructures import ImmutableMultiDict, MultiDict from app.forms.flows.lotse_step_chooser import LotseStepChooser, _LOTSE_DATA_KEY from app.forms.steps.lotse.merkzeichen import StepMerkzeichenPersonA, StepMerkzeichenPersonB, \ HasMerkzeichenPersonAPrecondition, HasMerkzeichenPersonBPrecondition from tests.utils import create_session_form_data _POSITIVE_CHECKBOX_VALUE = 'on' # The value in standard checkboxes is 'on'. def new_merkzeichen_person_a_step(form_data): return LotseStepChooser().get_correct_step(StepMerkzeichenPersonA.name, True, ImmutableMultiDict(form_data)) @pytest.fixture def test_request_context_with_person_a_disability(new_test_request_context): with new_test_request_context(stored_data={'person_a_has_disability': 'yes'}) as req: yield req @pytest.mark.usefixtures('test_request_context_with_person_a_disability') class TestStepMerkzeichenPersonAValidation: @pytest.fixture() def valid_form_data(self): return {'person_a_has_pflegegrad': 'no'} def test_if_has_pflegegrad_not_given_then_fail_validation(self): data = MultiDict({}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False def test_if_has_pflegegrad_given_then_succ_validation(self): data = MultiDict({'person_a_has_pflegegrad': 'no'}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_disability_degree_has_allowed_value_then_succ_validation(self): for allowed_value in [20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100]: data = MultiDict({'person_a_has_pflegegrad': 'no', 'person_a_disability_degree': allowed_value}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_disability_degree_has_not_allowed_value_then_fail_validation(self): for not_allowed_value in [21, 105]: data = MultiDict({'person_a_has_pflegegrad': 'no', 'person_a_disability_degree': not_allowed_value}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False def test_if_disability_degree_zero_and_has_no_merkzeichen_g_or_ag_then_succ_validation(self): data = MultiDict({'person_a_has_pflegegrad': 'no', 'person_a_disability_degree': 0, 'person_a_has_merkzeichen_g': False, 'person_a_has_merkzeichen_ag': False}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_disability_degree_below_20_and_not_zero_and_has_no_merkzeichen_g_or_ag_then_fail_validation(self): for not_allowed_value in [1, 19]: data = MultiDict({'person_a_has_pflegegrad': 'no', 'person_a_disability_degree': not_allowed_value, 'person_a_has_merkzeichen_g': False, 'person_a_has_merkzeichen_ag': False}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False def test_if_disability_degree_below_20_and_has_merkzeichen_g_then_fail_validation(self): for not_allowed_value in [0, 1, 19]: data = MultiDict({'person_a_has_pflegegrad': 'no', 'person_a_disability_degree': not_allowed_value, 'person_a_has_merkzeichen_g': True}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False def test_if_disability_degree_below_20_and_has_merkzeichen_ag_then_fail_validation(self): for not_allowed_value in [0, 1, 19]: data = MultiDict({'person_a_has_pflegegrad': 'no', 'person_a_disability_degree': not_allowed_value, 'person_a_has_merkzeichen_ag': True}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False def test_if_merkzeichen_g_and_ag_and_disability_degree_not_set_then_succ_validation(self, valid_form_data): data = MultiDict(valid_form_data) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_set_and_disability_degree_not_set_then_fail_validation_with_correct_message(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False assert form.errors['person_a_disability_degree'] == [_l('form.lotse.validation-disability_degree.merkzeichen_g_selected.required')] def test_if_merkzeichen_g_set_and_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE, 'person_a_disability_degree': 20}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_ag_set_and_disability_degree_not_set_then_fail_validation_with_correct_message(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False assert form.errors['person_a_disability_degree'] == [_l('form.lotse.validation-disability_degree.merkzeichen_ag_selected.required')] def test_if_merkzeichen_ag_set_and_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE, 'person_a_disability_degree': 20}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_and_ag_set_and_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE, 'person_a_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE, 'person_a_disability_degree': 20}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_and_ag_not_set_but_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_disability_degree': 20}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_set_and_disability_degree_under_20_then_fail_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE, 'person_a_disability_degree': 15}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False def test_if_merkzeichen_ag_set_and_disability_degree_under_20_then_fail_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_a_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE, 'person_a_disability_degree': 15}}) form = new_merkzeichen_person_a_step(form_data=data).render_info.form assert form.validate() is False class TestStepMerkzeichenPersonATexts: def test_if_multiple_users_then_show_multiple_title(self, new_test_request_context): expected_step_title = ngettext('form.lotse.merkzeichen_person_a.title', 'form.lotse.merkzeichen_person_a.title', num=2) session_data = { 'familienstand': 'married', 'familienstand_date': datetime.date(2000, 1, 31), 'familienstand_married_lived_separated': 'no', 'familienstand_confirm_zusammenveranlagung': True, 'person_a_has_disability': 'yes', } with new_test_request_context(stored_data=session_data): step = new_merkzeichen_person_a_step({}) step._pre_handle() assert step.title == expected_step_title def test_if_multiple_users_then_show_multiple_label(self, new_test_request_context): expected_step_label = ngettext('form.lotse.merkzeichen_person_a.label', 'form.lotse.merkzeichen_person_a.label', num=2) session_data = { 'familienstand': 'married', 'familienstand_date': datetime.date(2000, 1, 31), 'familienstand_married_lived_separated': 'no', 'familienstand_confirm_zusammenveranlagung': True, 'person_a_has_disability': 'yes', } with new_test_request_context(stored_data=session_data): step = new_merkzeichen_person_a_step({}) step._pre_handle() assert step.label == expected_step_label def test_if_single_user_then_show_single_title(self, new_test_request_context): expected_step_title = ngettext('form.lotse.merkzeichen_person_a.title', 'form.lotse.merkzeichen_person_a.title', num=1) session_data = { 'familienstand': 'single', 'person_a_has_disability': 'yes', } with new_test_request_context(stored_data=session_data): step = new_merkzeichen_person_a_step({}) step._pre_handle() assert step.title == expected_step_title def test_if_single_user_then_show_single_label(self, new_test_request_context): expected_step_label = ngettext('form.lotse.merkzeichen_person_a.label', 'form.lotse.merkzeichen_person_a.label', num=1) session_data = { 'familienstand': 'single', 'person_a_has_disability': 'yes', } with new_test_request_context(stored_data=session_data): step = new_merkzeichen_person_a_step({}) step._pre_handle() assert step.label == expected_step_label def new_merkzeichen_person_b_step(form_data): return LotseStepChooser().get_correct_step(StepMerkzeichenPersonB.name, True, ImmutableMultiDict(form_data)) @pytest.fixture def test_request_context_with_person_b_disability(app): with app.test_request_context(method="POST") as req: req.session = SecureCookieSession({_LOTSE_DATA_KEY: create_session_form_data({'person_b_has_disability': 'yes'})}) yield req @pytest.mark.usefixtures('test_request_context_with_person_b_disability') class TestStepMerkzeichenPersonBValidation: @pytest.fixture() def valid_form_data(self): return {'person_b_has_pflegegrad': 'no'} def test_if_has_pflegegrad_not_given_then_fail_validation(self): data = MultiDict({}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False def test_if_has_pflegegrad_given_then_succ_validation(self): data = MultiDict({'person_b_has_pflegegrad': 'no'}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_disability_degree_has_allowed_value_then_succ_validation(self): for allowed_value in [20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100]: data = MultiDict({'person_b_has_pflegegrad': 'no', 'person_b_disability_degree': allowed_value}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_disability_degree_has_not_allowed_value_then_fail_validation(self): for not_allowed_value in [21, 105]: data = MultiDict({'person_b_has_pflegegrad': 'no', 'person_b_disability_degree': not_allowed_value}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False def test_if_disability_degree_zero_and_has_no_merkzeichen_g_or_ag_then_succ_validation(self): data = MultiDict({'person_b_has_pflegegrad': 'no', 'person_b_disability_degree': 0, 'person_b_has_merkzeichen_g': False, 'person_b_has_merkzeichen_ag': False}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_disability_degree_below_20_and_not_zero_and_has_no_merkzeichen_g_or_ag_then_fail_validation(self): for not_allowed_value in [1, 19]: data = MultiDict({'person_b_has_pflegegrad': 'no', 'person_b_disability_degree': not_allowed_value, 'person_b_has_merkzeichen_g': False, 'person_b_has_merkzeichen_ag': False}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False def test_if_disability_degree_below_20_and_has_merkzeichen_g_then_fail_validation(self): for not_allowed_value in [0, 1, 19]: data = MultiDict({'person_b_has_pflegegrad': 'no', 'person_b_disability_degree': not_allowed_value, 'person_b_has_merkzeichen_g': True}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False def test_if_disability_degree_below_20_and_has_merkzeichen_ag_then_fail_validation(self): for not_allowed_value in [0, 1, 19]: data = MultiDict({'person_b_has_pflegegrad': 'no', 'person_b_disability_degree': not_allowed_value, 'person_b_has_merkzeichen_ag': True}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False def test_if_merkzeichen_g_and_ag_and_disability_degree_not_set_then_succ_validation(self, valid_form_data): data = MultiDict(valid_form_data) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_set_and_disability_degree_not_set_then_fail_validation_with_correct_message(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False assert form.errors['person_b_disability_degree'] == [_l('form.lotse.validation-disability_degree.merkzeichen_g_selected.required')] def test_if_merkzeichen_g_set_and_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE, 'person_b_disability_degree': 20}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_ag_set_and_disability_degree_not_set_then_fail_validation_with_correct_message(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False assert form.errors['person_b_disability_degree'] == [_l('form.lotse.validation-disability_degree.merkzeichen_ag_selected.required')] def test_if_merkzeichen_ag_set_and_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE, 'person_b_disability_degree': 20}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_and_ag_set_and_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE, 'person_b_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE, 'person_b_disability_degree': 20}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_and_ag_not_set_but_disability_degree_set_then_succ_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_disability_degree': 20}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is True def test_if_merkzeichen_g_set_and_disability_degree_under_20_then_fail_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_has_merkzeichen_g': _POSITIVE_CHECKBOX_VALUE, 'person_b_disability_degree': 15}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False def test_if_merkzeichen_ag_set_and_disability_degree_under_20_then_fail_validation(self, valid_form_data): data = MultiDict({**valid_form_data, **{'person_b_has_merkzeichen_ag': _POSITIVE_CHECKBOX_VALUE, 'person_b_disability_degree': 15}}) form = new_merkzeichen_person_b_step(form_data=data).render_info.form assert form.validate() is False class TestHasMerkzeichenPersonAPrecondition: def test_if_person_a_has_no_merkzeichen_set_then_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', } with pytest.raises(ValidationError): HasMerkzeichenPersonAPrecondition.parse_obj(data) def test_if_person_a_has_pflegegrad_set_then_do_not_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', 'person_a_has_pflegegrad': 'yes' } try: HasMerkzeichenPersonAPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_a_disability_degree_set_then_do_not_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', 'person_a_disability_degree': 20 } try: HasMerkzeichenPersonAPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_a_has_merkzeichen_g_set_then_do_not_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', 'person_a_has_merkzeichen_g': True } try: HasMerkzeichenPersonAPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_a_has_merkzeichen_ag_set_then_do_not_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', 'person_a_has_merkzeichen_ag': True } try: HasMerkzeichenPersonAPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_a_has_merkzeichen_bl_set_then_do_not_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', 'person_a_has_merkzeichen_bl': True, } try: HasMerkzeichenPersonAPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_a_has_merkzeichen_tbl_set_then_do_not_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', 'person_a_has_merkzeichen_tbl': True, } try: HasMerkzeichenPersonAPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_a_has_merkzeichen_h_set_then_do_not_raise_validation_error(self): data = { 'person_a_has_disability': 'yes', 'person_a_has_merkzeichen_h': True } try: HasMerkzeichenPersonAPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") class TestHasMerkzeichenPersonBPrecondition: def test_if_person_b_has_no_merkzeichen_set_then_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', } with pytest.raises(ValidationError): HasMerkzeichenPersonBPrecondition.parse_obj(data) def test_if_person_b_has_pflegegrad_set_then_do_not_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', 'person_b_has_pflegegrad': 'yes', } try: HasMerkzeichenPersonBPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_b_disability_degree_set_then_do_not_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', 'person_b_disability_degree': 20, } try: HasMerkzeichenPersonBPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_b_has_merkzeichen_g_set_then_do_not_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', 'person_b_has_merkzeichen_g': True, } try: HasMerkzeichenPersonBPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_b_has_merkzeichen_ag_set_then_do_not_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', 'person_b_has_merkzeichen_ag': True, } try: HasMerkzeichenPersonBPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_b_has_merkzeichen_bl_set_then_do_not_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', 'person_b_has_merkzeichen_bl': True } try: HasMerkzeichenPersonBPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_b_has_merkzeichen_tbl_set_then_do_not_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', 'person_b_has_merkzeichen_tbl': True, } try: HasMerkzeichenPersonBPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error") def test_if_person_b_has_merkzeichen_h_set_then_do_not_raise_validation_error(self): data = { 'person_b_has_disability': 'yes', 'person_b_has_merkzeichen_h': True } try: HasMerkzeichenPersonBPrecondition.parse_obj(data) except ValidationError: pytest.fail("Should not raise a validation error")

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1

0

1

0

null

0

7

7aa08fc66955a759d90000d4aa623d83cb6fe2c6

2,108

py

Python

tests/test_Downloader.py

korn-alex/toolbox

e0d8038d9579d59340020cc29de8cfc1f88425a1

[ "MIT" ]

null

tests/test_Downloader.py

korn-alex/toolbox

e0d8038d9579d59340020cc29de8cfc1f88425a1

[ "MIT" ]

null

tests/test_Downloader.py

korn-alex/toolbox

e0d8038d9579d59340020cc29de8cfc1f88425a1

[ "MIT" ]

null

import unittest from pathlib import Path # print(Path.cwd()) from toolbox.web import Downloader class TestDownloader(unittest.TestCase): @classmethod def setUpClass(cls): print('setUpClass') def setUp(self): self.d = Downloader() self.url = Path('https://images.pexels.com/photos/459793/pexels-photo-459793.jpeg?auto=compress&cs=tinysrgb&dpr=2&h=750&w=1260') def test_make_name(self): self.assertEqual(self.d._make_name(self.url,'Полное собрание сочинений. Братья Карамазовы. Части II-III, Федор Достоевский.djvu'),'Полное собрание сочинений. Братья Карамазовы. Части II-III, Федор Достоевский.djvu') self.assertEqual(self.d._make_name(self.url,'_3_'),'_3_.jpeg') self.assertEqual(self.d._make_name(self.url, None),'pexels-photo-459793.jpeg') self.assertEqual(self.d._make_name(self.url,''),'pexels-photo-459793.jpeg') self.assertEqual(self.d._make_name(self.url,'?'),'pexels-photo-459793.jpeg') self.assertEqual(self.d._make_name(self.url,'?..?..?'),'pexels-photo-459793.jpeg') self.assertEqual(self.d._make_name(self.url,'?..?..?**\\//- -'),'pexels-photo-459793.jpeg') self.assertEqual(self.d._make_name(self.url,'___'),'___.jpeg') self.assertEqual(self.d._make_name(self.url,'_3.png_'),'_3.png_') self.assertEqual(self.d._make_name(self.url,'_3.png*'),'_3.jpeg') self.assertEqual(self.d._make_name(self.url,'ok'),'ok.jpeg') self.assertEqual(self.d._make_name(self.url,'ok.jpeg'),'ok.jpeg') self.assertEqual(self.d._make_name(self.url,'ok.png'),'ok.png') self.assertEqual(self.d._make_name(self.url,'ok.png.jpeg'),'ok.png.jpeg') self.assertEqual(self.d._make_name(self.url,123),'123.jpeg') self.assertEqual(self.d._make_name(self.url,123.44),'123.44') self.assertEqual(self.d._make_name(self.url,'123'),'123.jpeg') self.assertEqual(self.d._make_name(self.url,'123.jpeg'),'123.jpeg') self.assertEqual(self.d._make_name(self.url,'123.png'),'123.png') if __name__ == '__main__': unittest.main()

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305

2,108

4.472131

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224

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7ab0387933acfa254802144573d963906129cbe8

114

py

Python

research/object_detection/python-tkinter-gui-master/GUITools/WindowTools/__init__.py

r08in279/Traffic-Management-Using-Drones

15fdba219cef04b3cb59a68901a8064c3795d8e3

[ "Apache-2.0" ]

null

research/object_detection/python-tkinter-gui-master/GUITools/WindowTools/__init__.py

r08in279/Traffic-Management-Using-Drones

15fdba219cef04b3cb59a68901a8064c3795d8e3

[ "Apache-2.0" ]

null

research/object_detection/python-tkinter-gui-master/GUITools/WindowTools/__init__.py

r08in279/Traffic-Management-Using-Drones

15fdba219cef04b3cb59a68901a8064c3795d8e3

[ "Apache-2.0" ]

null

#WindowTools packaging file from GUITools.WindowTools.Buttons import * from GUITools.WindowTools.Windows import *

28.5

42

0.842105

13

114

7.384615

0.615385

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114

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7

8f9c9a5c23ed8979faaa144a4b68d7b11375fc98

3,277

py

Python

result/migrations/nn/0015_auto_20190627_0733.py

0Jihad/uqhs

16e16742022142d47d0a423aa27ca50fe706a06b

[ "MIT" ]

null

result/migrations/nn/0015_auto_20190627_0733.py

0Jihad/uqhs

16e16742022142d47d0a423aa27ca50fe706a06b

[ "MIT" ]

11

2019-10-13T11:05:26.000Z

2022-03-11T23:48:57.000Z

result/migrations/nn/0015_auto_20190627_0733.py

0Jihad/uqhs

16e16742022142d47d0a423aa27ca50fe706a06b

[ "MIT" ]

null

# Generated by Django 2.1.3 on 2019-06-26 18:33 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('result', '0014_auto_20190627_0718'), ] operations = [ migrations.AlterField( model_name='overall_annual', name='acc', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='acc', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='agr', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='agr', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='bst', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='bst', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='bus', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='bus', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='eng', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='eng', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='his', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='his', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='ict', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='arb', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='irs', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='irs', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='mat', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='mat', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='nva', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='nva', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='prv', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='prv', to='result.TERM'), ), migrations.AlterField( model_name='overall_annual', name='yor', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='yor', to='result.TERM'), ), ]

43.693333

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0

null

0

1

0

1

0

null

0

7

8fe44b20abe3244f8b6eb1119635f14754a50213

11,505

py

Python

game2048/my_agents.py

snuffle-PX/2048-api

a43c74c3cfcf47e3f79ab631705b46ddbe3add1e

[ "Apache-2.0" ]

null

game2048/my_agents.py

snuffle-PX/2048-api

a43c74c3cfcf47e3f79ab631705b46ddbe3add1e

[ "Apache-2.0" ]

null

game2048/my_agents.py

snuffle-PX/2048-api

a43c74c3cfcf47e3f79ab631705b46ddbe3add1e

[ "Apache-2.0" ]

null

""" author: 赵阳桁 TrainAgent use buffer to train TrainAgent2 train without buffer TestAgent is a simple agent for webapp, evaluate and figerprint. """ from .agents import Agent from utils import try_to_move, get_train_data, conv_to_onehot, ReplayMemory, Transition, conv_to_onehot_12, get_train_data_12 import numpy as np import torch import torch.nn import torch.nn.functional as F import torch.optim from model import nn2048, nn2048_2, nn2048_3, nn2048_4 from .expectimax import board_to_move import time BATCH_SIZE = 64 learning_rate = 1e-4 THRESHOLD = 0.5 DEFAULT_PATH = 'model_dict.pkl' class TrainAgent(Agent): def __init__(self, game, display=None, train=True, load_data=False, path=None): super().__init__(game, display) self.train = train self.statistics = {2 ** i: 0 for i in range(1, 16)} self.threshold = THRESHOLD self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") self.step_counter = 0 self.error_counter = 0 self.diff_counter = 0 self.t = 0 if self.train: self.teacher = board_to_move if load_data: if path is None: path = DEFAULT_PATH else: pass try: self.net = nn2048_3().to(self.device) self.net.load_state_dict(torch.load(path, map_location=self.device)) except FileNotFoundError: print('No model loaded! Create new model') self.net = nn2048_3().to(self.device) else: self.net = nn2048_3().to(self.device) self.criterion = torch.nn.CrossEntropyLoss() self.optimizer = torch.optim.Adam(self.net.parameters(), lr=learning_rate) # configure.learning_rate) self.buffer = ReplayMemory(5 * BATCH_SIZE) else: try: if path is None: path = DEFAULT_PATH self.net = nn2048_3().to(self.device) self.net.load_state_dict(torch.load(path, map_location=self.device)) self.net.eval() except FileNotFoundError: print('No model loaded!') self.net = nn2048_3().to(self.device) def train_net(self, board, target_direction): # target_direction = self.teacher(board) train_data, train_targets = get_train_data(board, target_direction) self.buffer.push6(train_data, train_targets) transitions = self.buffer.sample(BATCH_SIZE) batch = Transition(*zip(*transitions)) train_data = torch.Tensor(batch.board).to(self.device).float() train_targets = torch.Tensor(batch.direction).to(self.device).long().squeeze(1) # train_data = torch.Tensor(train_data).to(self.device).float() # train_targets = torch.Tensor(train_targets).to(self.device).long().squeeze(1) # squeeze() delete the dimention of 1 y = self.net.forward(train_data) loss = self.criterion(y, train_targets) self.optimizer.zero_grad() loss.backward() self.optimizer.step() def step(self): start = time.time() board = self.game.board oh_board = conv_to_onehot(board) self.step_counter += 1 if self.train: target_direction = self.teacher(board) self.train_net(board, target_direction) if np.random.rand() > self.threshold or self.game.score < 512 : direction = self.net.predict(torch.Tensor(oh_board.reshape(1, *oh_board.shape)).to(self.device).float()) if direction != target_direction: self.error_counter += 1 # _, score = try_to_move(board, direction) # if score == -1: # cannot move to the selected direction # # direction = target_direction # #print("score -1") # self.error_counter += 1 else: direction = target_direction else: """ Only test without train """ direction = self.net.predict(torch.Tensor(oh_board.reshape(1, *oh_board.shape)).to(self.device).float()) _, score = try_to_move(board, direction) if score == -1: # cannot move to the selected direction self.error_counter += 1 if direction != board_to_move(board): self.diff_counter += 1 # direction = board_to_move(board) # print("score -1") end = time.time() self.t += start - end return direction def play(self, max_iter=np.inf, verbose=False): super(TrainAgent, self).play(max_iter=max_iter, verbose=verbose) self.statistics[self.game.score] += 1 def new_game(self, game): self.game = game class TrainAgent2(TrainAgent): def train_net(self, board, target_direction): train_data, train_targets = get_train_data(board, target_direction) train_data = torch.Tensor(train_data).to(self.device).float() train_targets = torch.Tensor(train_targets).to(self.device).long().squeeze(1) # y = self.net.forward(train_data) loss = self.criterion(y, train_targets) self.optimizer.zero_grad() loss.backward() self.optimizer.step() class RLAgent(Agent): def __init__(self, game, display=None, train=True, load_data=False, path=None): super().__init__(game, display) self.train = train self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") self.optimizer = torch.optim.Adam(betas=(0.5, 0.999)) self.criterion = torch.nn.MSELoss(size_average=True) self.net = nn2048() self.last_board = None def step(self): board = self.game.board oh_board = conv_to_onehot(board) board_list = [] for d in range(4): _, score = try_to_move(board, d) if score >= 0: board_list.append((d, score)) if board_list: s = [self.net.predict(torch.Tensor(oh_board.reshape(1, *oh_board.shape)).to(self.device).float()) + score*2 for d, score in board_list] idx = np.argmax(s) value = np.max(s) direction = board_list[idx][1] if self.train and any(self.last_board): self.train_net(self.last_board, value) self.last_board = board return direction def train_net(self, last_board, value): train_data, _ = get_train_data(last_board, 0) train_targets = np.array([value]*6).reshape(-1, 1) train_data = torch.Tensor(train_data).to(self.device).float() train_targets = torch.Tensor(train_targets).to(self.device).long().squeeze(1) # y = self.net.forward(train_data) loss = self.criterion(y, train_targets) self.optimizer.zero_grad() loss.backward() self.optimizer.step() class TrainAgent_12(Agent): def __init__(self, game, display=None, train=True, load_data=False, path=None): super().__init__(game, display) self.train = train self.statistics = {2 ** i: 0 for i in range(1, 16)} self.threshold = THRESHOLD self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") self.step_counter = 0 self.error_counter = 0 self.diff_counter = 0 self.t = 0 if self.train: self.teacher = board_to_move if load_data: if path is None: path = DEFAULT_PATH else: pass try: self.net = nn2048_4().to(self.device) self.net.load_state_dict(torch.load(path, map_location=self.device)) except FileNotFoundError: print('No model loaded! Create new model') self.net = nn2048_4().to(self.device) else: self.net = nn2048_4().to(self.device) self.criterion = torch.nn.CrossEntropyLoss() self.optimizer = torch.optim.Adam(self.net.parameters(), lr=learning_rate) # configure.learning_rate) # self.buffer = ReplayMemory(5 * BATCH_SIZE) else: try: if path is None: path = DEFAULT_PATH self.net = nn2048_4().to(self.device) self.net.load_state_dict(torch.load(path, map_location=self.device)) self.net.eval() except FileNotFoundError: print('No model loaded!') self.net = nn2048_4().to(self.device) def train_net(self, board, target_direction): train_data, train_targets = get_train_data_12(board, target_direction) train_data = torch.Tensor(train_data).to(self.device).float() train_targets = torch.Tensor(train_targets).to(self.device).long().squeeze(1) # y = self.net.forward(train_data) loss = self.criterion(y, train_targets) self.optimizer.zero_grad() loss.backward() self.optimizer.step() def step(self): start = time.time() board = self.game.board oh_board = conv_to_onehot_12(board) self.step_counter += 1 if self.train: target_direction = self.teacher(board) self.train_net(board, target_direction) if np.random.rand() > self.threshold or self.game.score < 512: direction = self.net.predict(torch.Tensor(oh_board.reshape(1, *oh_board.shape)).to(self.device).float()) if direction != target_direction: self.error_counter += 1 else: direction = target_direction else: """ Only test without train """ direction = self.net.predict(torch.Tensor(oh_board.reshape(1, *oh_board.shape)).to(self.device).float()) _, score = try_to_move(board, direction) if score == -1: # cannot move to the selected direction self.error_counter += 1 if direction != board_to_move(board): self.diff_counter += 1 # direction = board_to_move(board) # print("score -1") end = time.time() self.t += start - end return direction def play(self, max_iter=np.inf, verbose=False): super(TrainAgent_12, self).play(max_iter=max_iter, verbose=verbose) self.statistics[self.game.score] += 1 def new_game(self, game): self.game = game DEFAULT_TEST_PATH = 'model3_dict_01_11.pkl' class TestAgent(Agent): def __init__(self, game, display=None): super().__init__(game, display) self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") self.net = nn2048_3().to(self.device) self.net.load_state_dict(torch.load(DEFAULT_TEST_PATH, map_location=self.device)) self.net.eval() def step(self): board = self.game.board oh_board = conv_to_onehot(board) direction = self.net.predict(torch.Tensor(oh_board.reshape(1, *oh_board.shape)).to(self.device).float()) direction = int(direction.data.numpy()) return direction

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null

0

7

8908af31afe8f43f94988a790c4fd5eb4b22fa41

138

py

Python

python/Lesson1-Secrets/s3_secrets_usingconst.py

franTarkenton/IntroToJenkins

cbdd5933b8e0315fe747523f9b94b3728db9a585

[ "MIT" ]

null

python/Lesson1-Secrets/s3_secrets_usingconst.py

franTarkenton/IntroToJenkins

cbdd5933b8e0315fe747523f9b94b3728db9a585

[ "MIT" ]

null

python/Lesson1-Secrets/s3_secrets_usingconst.py

franTarkenton/IntroToJenkins

cbdd5933b8e0315fe747523f9b94b3728db9a585

[ "MIT" ]

null

import constants # you can now access any of your constants from constants module print(f"bills password is {constants.BILLS_PASSWORD}")

27.6

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138

5.238095

0.761905

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138

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7

8918d9792bc9bf0be6b01759909e9c4eedf32494

2,158

py

Python

code/text_data_utils.py

ZengHaihong/Smart-network

f4143e2018641adc1dbe1bf51a0d76258ea449ac

[ "MIT" ]

7

2019-10-11T08:02:49.000Z

2022-02-27T12:28:09.000Z

code/text_data_utils.py

qmylzx/Smart-network

f4143e2018641adc1dbe1bf51a0d76258ea449ac

[ "MIT" ]

null

code/text_data_utils.py

qmylzx/Smart-network

f4143e2018641adc1dbe1bf51a0d76258ea449ac

[ "MIT" ]

7

2019-10-11T08:02:42.000Z

2021-07-20T07:19:37.000Z

def generate_data_replace_string(): ''' 为了将日期字符串 /2/5 转换成 0205这样, 构建一个map,key为原始字符串,value为目标字符串 :return: date_replace_str_map ''' ori_str_list = [] new_str_list = [] for idx in range(1,9): str_num = '/'+str(idx); new_str_num = '0'+str(idx); ori_str_list.append(str_num); new_str_list.append(new_str_num); ori_str_map = {k:v+1 for v,k in enumerate(ori_str_list)} date_replace_str_map= {k:new_str_list[idx] for idx,k in enumerate(ori_str_map.keys())} ori_str_list = [] new_str_list = [] for idx in range(10,32): str_num = '/' + str(idx); new_str_num = str(idx) ori_str_list.append(str_num) new_str_list.append(new_str_num) ori_str_map = {k:v+1 for v,k in enumerate(ori_str_list)} replace_str_map_part2= {k:new_str_list[idx] for idx,k in enumerate(ori_str_map.keys())} for key in replace_str_map_part2.keys(): date_replace_str_map[key] = replace_str_map_part2.get(key) #print(replace_str_map) return date_replace_str_map def generate_time_replace_string(): ''' 为了将日期字符串 ' 0:05' 转换成 '0005' 这样, 构建一个map,key为原始字符串,value为目标字符串 :return: time_replace_str_map ''' ori_str_list = [] new_str_list = [] for idx in range(9): str_num = ' '+str(idx) + ':'; new_str_num = '0'+str(idx); ori_str_list.append(str_num); new_str_list.append(new_str_num); ori_str_map = {k:v+1 for v,k in enumerate(ori_str_list)} time_replace_str_map= {k:new_str_list[idx] for idx,k in enumerate(ori_str_map.keys())} ori_str_list = [] new_str_list = [] for idx in range(10,24): str_num = ' ' + str(idx) + ':'; new_str_num = str(idx) ori_str_list.append(str_num) new_str_list.append(new_str_num) ori_str_map = {k:v+1 for v,k in enumerate(ori_str_list)} replace_str_map_part2= {k:new_str_list[idx] for idx,k in enumerate(ori_str_map.keys())} for key in replace_str_map_part2.keys(): time_replace_str_map[key] = replace_str_map_part2.get(key) #print(replace_str_map) return time_replace_str_map

31.275362

91

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0

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null

0

8

64f825db678a5077d947194db0105d6708941ce0

6,120

py

Python

JigsawInferenceGizmo.py

shrutiichandra/JigsawInferenceGizmo

da9d60afa6b0a8d219fbab55bff2ce37f2013f73

[ "MIT" ]

25

2022-03-03T19:47:05.000Z

2022-03-25T16:22:51.000Z

JigsawInferenceGizmo.py

shrutiichandra/JigsawInferenceGizmo

da9d60afa6b0a8d219fbab55bff2ce37f2013f73

[ "MIT" ]

2

2022-03-04T08:10:21.000Z

2022-03-06T03:36:37.000Z

JigsawInferenceGizmo.py

shrutiichandra/JigsawInferenceGizmo

da9d60afa6b0a8d219fbab55bff2ce37f2013f73

[ "MIT" ]

11

2022-03-03T22:49:46.000Z

2022-03-18T10:00:11.000Z

# JIG code from Stand-up Maths video "Why don't Jigsaw Puzzles have the correct number of pieces?" def low_factors(n): # all the factors which are the lower half of each factor pair lf = [] for i in range(1, int(n**0.5)+1): if n % i == 0: lf.append(i) return lf def jig(w,h,n,b=0): # percentage we'll check in either direction threshold = 0.1 # the extra badness per piece penalty = 1.005 ratio = max(w,h)/min(w,h) # switched to be greater than 1 print("") print(f"{w} by {h} is picture ratio {round(ratio,4)}") print("") max_cap = int((1+threshold)*n) min_cap = int((1-threshold)*n) up_range = [i for i in range(n,max_cap+1)] down_range = [i for i in range(min_cap,n)] # do not want n included again down_range.reverse() # start at 100 which is silly high and then move down. up_best = 100 up_best_deets = [] down_best = 100 down_best_deets = [] # I am using the run marker so I know if looking above or below n run = 0 for dis_range in [up_range,down_range]: best_n = 0 best_n_ratio = 0 best_n_sides = [] if run == 0: print(f"Looking for >= {n} solutions:") print("") else: print("") print("Just out of interest, here are smaller options:") print("") for i in dis_range: this_best = 0 for j in low_factors(i): j2 = int(i/j) # must be a whole number anyway this_ratio = j2/j if this_best == 0: this_best = this_ratio best_sides = [j,j2] else: if abs(this_ratio/ratio - 1) < abs(this_best/ratio - 1): this_best = this_ratio best_sides = [j,j2] yes = 0 if best_n == 0: yes = 1 else: if abs(this_best/ratio - 1) < abs(best_n_ratio/ratio - 1): yes = 1 if yes == 1: best_n = i best_n_ratio = this_best best_n_sides = best_sides piece_ratio = max(ratio,this_best)/min(ratio,this_best) badness_score = (penalty**(abs(i-n)))*piece_ratio if run == 0: if badness_score < up_best: up_best = badness_score up_best_deets = [best_n,best_n_sides,best_n_ratio] else: if badness_score < down_best: down_best = badness_score down_best_deets = [best_n,best_n_sides,best_n_ratio] print(f"{best_n} pieces in {best_n_sides} (grid ratio {round(best_n_ratio,4)}) needs piece ratio {round(piece_ratio,4)}") if b==1: print(f"[badness = {round(badness_score,5)}]") print(f"for {n} the best is {best_n} pieces with size {best_n_sides}") run += 1 print("") print(f"If I had to guess: I think it's {up_best_deets[0]} pieces.") if down_best < up_best: print("") print(f"BUT, fun fact, {down_best_deets[0]} would be even better.") print("") return 'DONE' # I duplicated jig_v0 to make is easier to show in the video def jig_v0(w,h,n,b=0): # percentage we'll check in either direction threshold = 0.1 penalty = 1.005 ratio = max(w,h)/min(w,h) # switched to be greater than 1 print("") print(f"{w} by {h} is picture ratio {round(ratio,4)}") print("") max_cap = int((1+threshold)*n) min_cap = int((1-threshold)*n) up_range = [i for i in range(n,max_cap+1)] down_range = [i for i in range(min_cap,n)] # do not want n included again down_range.reverse() # start at 100 which is silly high and then move down. up_best = 100 up_best_deets = [] down_best = 100 down_best_deets = [] run = 0 for dis_range in [up_range,down_range]: best_n = 0 best_n_ratio = 0 best_n_sides = [] if run == 0: print(f"Looking for >= {n} solutions:") print("") else: print("") print("Just out of interest, here are smaller options:") print("") for i in dis_range: this_best = 0 for j in low_factors(i): j2 = int(i/j) # must be a whole number anyway this_ratio = j2/j if this_best == 0: this_best = this_ratio best_sides = [j,j2] else: if abs(this_ratio/ratio - 1) < abs(this_best/ratio - 1): this_best = this_ratio best_sides = [j,j2] yes = 0 if best_n == 0: yes = 1 else: if abs(this_best/ratio - 1) < abs(best_n_ratio/ratio - 1): yes = 1 if yes == 1: best_n = i best_n_ratio = this_best best_n_sides = best_sides piece_ratio = max(ratio,this_best)/min(ratio,this_best) badness_score = (penalty**(abs(i-n)))*piece_ratio if run == 0: if badness_score < up_best: up_best = badness_score up_best_deets = [best_n,best_n_sides,best_n_ratio] else: if badness_score < down_best: down_best = badness_score down_best_deets = [best_n,best_n_sides,best_n_ratio] print(f"{best_n} pieces in {best_n_sides} (grid ratio {round(best_n_ratio,4)}) needs piece ratio {round(piece_ratio,4)}") if b==1: print(f"[badness = {round(badness_score,5)}]") run += 1 print("") return 'DONE'

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false

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0

null

0

1

0

1

0

null

0

7

8f69683541c0d2ae8fb633f190dba96a193f6fc5

148

py

Python

stable_baselines3/dqn/__init__.py

koulakis/stable-baselines3

08e7519381e800edc6bbd09577f14381b7341873

[ "MIT" ]

null

stable_baselines3/dqn/__init__.py

koulakis/stable-baselines3

08e7519381e800edc6bbd09577f14381b7341873

[ "MIT" ]

null

stable_baselines3/dqn/__init__.py

koulakis/stable-baselines3

08e7519381e800edc6bbd09577f14381b7341873

[ "MIT" ]

null

from stable_baselines3.dqn.dqn import DQN from stable_baselines3.dqn.policies import MlpPolicy from stable_baselines3.dqn.policies import CnnPolicy

37

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148

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null

0

1

0

1

0

7

713915d7d71c455fffc0203cbff522495c364eeb

24,445

py

Python

booking/tests.py

broskh/restaurants

665fe69c8eeaae80c9a802abe6d5ca3343ab1689

[ "MIT" ]

null

booking/tests.py

broskh/restaurants

665fe69c8eeaae80c9a802abe6d5ca3343ab1689

[ "MIT" ]

null

booking/tests.py

broskh/restaurants

665fe69c8eeaae80c9a802abe6d5ca3343ab1689

[ "MIT" ]

null

from datetime import datetime, timedelta from django.test import TestCase, Client from django.urls import reverse from django.utils import timezone from booking.models import Booking from restaurants.utils import get_coordinates from user_management.models import Restaurant, User class BookingMethodsTests(TestCase): def setUp(self): self.restaurant = Restaurant.objects.create( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) self.client_user = User.objects.create( first_name='paolo', last_name='verdi', email='paolo.verdi@mail.com', username='paolo1', user_type=User.TYPES[0][0] ) self.client_user.set_password('password') self.restaurant_user = User.objects.create( first_name='mario', last_name='rossi', email='mario.rossi@mail.com', username='mario1', user_type=User.TYPES[1][0], restaurant_information=self.restaurant ) self.restaurant_user.set_password('password') restaurant_position = get_coordinates(self.restaurant.city + ', ' + self.restaurant.address) self.restaurant.latitude = restaurant_position['lat'] self.restaurant.longitude = restaurant_position['lng'] self.booking = Booking( client=self.client_user, restaurant=self.restaurant, n_places=2, start_time=timezone.make_aware(datetime.now(), timezone.get_current_timezone()).replace(microsecond=0), state=Booking.STATES[0][0] ) self.booking.end_time = self.booking.calculate_end_time() def test_end_is_after_start(self): self.assertEqual(self.booking.end_time <= self.booking.start_time, False) class IndexWiewTests(TestCase): def setUp(self): self.url = reverse('booking:index') self.client = Client() self.password = 'password' self.restaurant = Restaurant.objects.create( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) restaurant_position = get_coordinates(self.restaurant.city + ', ' + self.restaurant.address) self.restaurant.latitude = restaurant_position['lat'] self.restaurant.longitude = restaurant_position['lng'] self.restaurant.save() self.client_user = User.objects.create( first_name='paolo', last_name='verdi', email='paolo.verdi@mail.com', username='paolo1', user_type=User.TYPES[0][0] ) self.client_user.set_password(self.password) self.client_user.save() self.restaurant_user = User.objects.create( first_name='mario', last_name='rossi', email='mario.rossi@mail.com', username='mario1', user_type=User.TYPES[1][0], restaurant_information=self.restaurant ) self.restaurant_user.set_password(self.password) self.restaurant_user.save() def test_not_logged_user(self): response = self.client.get(self.url) self.assertEqual(response.status_code, 200) self.assertNotContains(response, 'Logout') def test_client_logged(self): self.client.login(username=self.client_user.username, password=self.password) response = self.client.get(self.url) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Gestione prenotazioni') def test_restaurant_logged(self): self.client.login(username=self.restaurant_user.username, password=self.password) response = self.client.get(self.url) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Gestione ristorante') class ResultsWiewTests(TestCase): def setUp(self): self.url = reverse('booking:search_results') self.client = Client() self.datetime = timezone.make_aware(datetime.now(), timezone.get_current_timezone()).replace(microsecond=0) self.restaurant1 = Restaurant( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) restaurant_position = get_coordinates(self.restaurant1.city + ', ' + self.restaurant1.address) self.restaurant1.latitude = restaurant_position['lat'] self.restaurant1.longitude = restaurant_position['lng'] self.restaurant2 = Restaurant( name='da paolo', city='san cesario sul panaro', address='via della meccanica', n_places=80, booking_duration=90 ) restaurant_position = get_coordinates(self.restaurant2.city + ', ' + self.restaurant2.address) self.restaurant2.latitude = restaurant_position['lat'] self.restaurant2.longitude = restaurant_position['lng'] self.restaurant3 = Restaurant( name='da paolo', city='alba adriatica', address='via pompeo', n_places=120, booking_duration=150 ) restaurant_position = get_coordinates(self.restaurant3.city + ', ' + self.restaurant3.address) self.restaurant3.latitude = restaurant_position['lat'] self.restaurant3.longitude = restaurant_position['lng'] def test_with_results(self): self.restaurant1.save() self.restaurant2.save() self.restaurant3.save() data = { 'site': 'savignano sul panaro', 'date': self.datetime.strftime("%d/%m/%Y"), 'time': self.datetime.strftime("%H:%M"), 'n_clients': 2 } response = self.client.get(self.url, data=data) self.assertEqual(response.status_code, 200) self.assertNotEqual(response.context['restaurants_available'], []) def test_without_results(self): data = { 'site': 'savignano sul panaro', 'date': self.datetime.strftime("%d/%m/%Y"), 'time': self.datetime.strftime("%H:%M"), 'n_clients': 2 } response = self.client.get(self.url, data=data) self.assertEqual(response.status_code, 200) self.assertEqual(response.context['restaurants_available'], []) self.assertEqual(response.context['restaurants_busy'], []) def test_ordered_results_and_closer_or_equal_than_50_km(self): self.restaurant1.save() self.restaurant2.save() self.restaurant3.save() data = { 'site': 'savignano sul panaro', 'date': self.datetime.strftime("%d/%m/%Y"), 'time': self.datetime.strftime("%H:%M"), 'n_clients': 2 } response = self.client.get(self.url, data=data) self.assertEqual(response.status_code, 200) self.assertEqual(response.context['restaurants_available'][0]['restaurant'], self.restaurant1) self.assertEqual(response.context['restaurants_available'][1]['restaurant'], self.restaurant2) self.assertEqual(len(response.context['restaurants_available']), 2) class RestaurantBookingsWiewTests(TestCase): def setUp(self): self.url = reverse('booking:restaurant_bookings') self.client = Client() self.password = 'password' self.restaurant = Restaurant.objects.create( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) restaurant_position = get_coordinates(self.restaurant.city + ', ' + self.restaurant.address) self.restaurant.latitude = restaurant_position['lat'] self.restaurant.longitude = restaurant_position['lng'] self.restaurant.save() self.client_user = User.objects.create( first_name='paolo', last_name='verdi', email='paolo.verdi@mail.com', username='paolo1', user_type=User.TYPES[0][0] ) self.client_user.set_password(self.password) self.client_user.save() self.restaurant_user = User.objects.create( first_name='mario', last_name='rossi', email='mario.rossi@mail.com', username='mario1', user_type=User.TYPES[1][0], restaurant_information=self.restaurant ) self.restaurant_user.set_password(self.password) self.restaurant_user.save() def test_not_logged_user(self): response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_client_logged(self): self.client.login(username=self.client_user.username, password=self.password) response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_restaurant_logged_with_restaurant_information(self): self.restaurant_user.restaurant_information = self.restaurant self.restaurant_user.save() self.client.login(username=self.restaurant_user.username, password=self.password) response = self.client.get(self.url) self.assertEqual(response.status_code, 200) class ClientBookingsWiewTests(TestCase): def setUp(self): self.url = reverse('booking:client_bookings') self.client = Client() self.password = 'password' self.datetime = timezone.make_aware(datetime.now(), timezone.get_current_timezone()).replace(microsecond=0) self.restaurant = Restaurant.objects.create( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) restaurant_position = get_coordinates(self.restaurant.city + ', ' + self.restaurant.address) self.restaurant.latitude = restaurant_position['lat'] self.restaurant.longitude = restaurant_position['lng'] self.restaurant.save() self.client_user = User.objects.create( first_name='paolo', last_name='verdi', email='paolo.verdi@mail.com', username='paolo1', user_type=User.TYPES[0][0] ) self.client_user.set_password(self.password) self.client_user.save() self.restaurant_user = User.objects.create( first_name='mario', last_name='rossi', email='mario.rossi@mail.com', username='mario1', user_type=User.TYPES[1][0], restaurant_information=self.restaurant ) self.restaurant_user.set_password(self.password) self.restaurant_user.save() self.booking = Booking( client=self.client_user, restaurant=self.restaurant, start_time=self.datetime, n_places=2, state=Booking.STATES[1][0] ) self.booking.end_time = self.booking.calculate_end_time() def test_not_logged_user(self): response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_restaurant_logged(self): self.restaurant_user.client_information = self.restaurant self.restaurant_user.save() self.client.login(username=self.restaurant_user.username, password=self.password) response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_client_logged_without_results(self): self.client.login(username=self.client_user.username, password=self.password) response = self.client.get(self.url) self.assertEqual(response.status_code, 200) self.assertQuerysetEqual(response.context['booking_list'], []) def test_client_logged_with_results(self): self.booking.save() self.client.login(username=self.client_user.username, password=self.password) response = self.client.get(self.url) self.assertEqual(response.status_code, 200) self.assertEqual(response.context['booking_list'][0], self.booking) def test_booking_before_now(self): self.booking.start_time = self.datetime - timedelta(minutes=1) self.booking.save() self.client.login(username=self.client_user.username, password=self.password) response = self.client.get(self.url) self.assertEqual(response.status_code, 200) self.assertQuerysetEqual(response.context['booking_list'], []) class DeleteBookingsWiewTests(TestCase): def setUp(self): self.url = reverse('booking:delete_booking') self.client = Client() self.password = 'password' self.datetime = timezone.make_aware(datetime.now(), timezone.get_current_timezone()).replace(microsecond=0) self.restaurant = Restaurant.objects.create( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) restaurant_position = get_coordinates(self.restaurant.city + ', ' + self.restaurant.address) self.restaurant.latitude = restaurant_position['lat'] self.restaurant.longitude = restaurant_position['lng'] self.restaurant.save() self.client_user = User.objects.create( first_name='paolo', last_name='verdi', email='paolo.verdi@mail.com', username='paolo1', user_type=User.TYPES[0][0] ) self.client_user.set_password(self.password) self.client_user.save() self.restaurant_user = User.objects.create( first_name='mario', last_name='rossi', email='mario.rossi@mail.com', username='mario1', user_type=User.TYPES[1][0], restaurant_information=self.restaurant ) self.restaurant_user.set_password(self.password) self.restaurant_user.save() self.booking = Booking( client=self.client_user, restaurant=self.restaurant, start_time=self.datetime, n_places=2, state=Booking.STATES[1][0] ) self.booking.end_time = self.booking.calculate_end_time() def test_not_logged_user(self): response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_restaurant_logged(self): self.client.login(username=self.restaurant_user.username, password=self.password) response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_client_logged_ajax_call(self): self.client.login(username=self.client_user.username, password=self.password) response = self.client.post(self.url, {}, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) def test_client_logged_no_ajax_call(self): self.client.login(username=self.client_user.username, password=self.password) response = self.client.post(self.url, {}) self.assertEqual(response.status_code, 404) def test_client_logged_ajax_call_with_booking(self): self.booking.save() self.client.login(username=self.client_user.username, password=self.password) data = { 'id': self.booking.id } data_result = { 'result': 'success' } response = self.client.post(self.url, data, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) self.assertJSONEqual(str(response.content, encoding='utf8'), data_result) def test_client_logged_ajax_call_without_booking(self): self.client.login(username=self.client_user.username, password=self.password) data = { 'id': 0 } data_result = { 'result': 'error' } response = self.client.post(self.url, data, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) self.assertJSONEqual(str(response.content, encoding='utf8'), data_result) class EditBookingsWiewTests(TestCase): def setUp(self): self.url = reverse('booking:edit_booking') self.client = Client() self.password = 'password' self.datetime = timezone.make_aware(datetime.now(), timezone.get_current_timezone()).replace(microsecond=0) self.restaurant = Restaurant.objects.create( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) restaurant_position = get_coordinates(self.restaurant.city + ', ' + self.restaurant.address) self.restaurant.latitude = restaurant_position['lat'] self.restaurant.longitude = restaurant_position['lng'] self.restaurant.save() self.client_user = User.objects.create( first_name='paolo', last_name='verdi', email='paolo.verdi@mail.com', username='paolo1', user_type=User.TYPES[0][0] ) self.client_user.set_password(self.password) self.client_user.save() self.restaurant_user = User.objects.create( first_name='mario', last_name='rossi', email='mario.rossi@mail.com', username='mario1', user_type=User.TYPES[1][0], restaurant_information=self.restaurant ) self.restaurant_user.set_password(self.password) self.restaurant_user.save() self.booking = Booking( client=self.client_user, restaurant=self.restaurant, start_time=self.datetime, n_places=2, state=Booking.STATES[1][0] ) self.booking.end_time = self.booking.calculate_end_time() def test_not_logged_user(self): response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_restaurant_logged(self): self.client.login(username=self.restaurant_user.username, password=self.password) response = self.client.get(self.url) expected_url = reverse('login') + '?next=' + self.url self.assertRedirects(response, expected_url, status_code=302, target_status_code=200) def test_client_logged_ajax_call(self): self.client.login(username=self.client_user.username, password=self.password) response = self.client.post(self.url, {}, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) def test_client_logged_no_ajax_call(self): self.client.login(username=self.client_user.username, password=self.password) response = self.client.post(self.url, {}) self.assertEqual(response.status_code, 404) def test_client_logged_ajax_call_with_booking(self): self.booking.save() self.client.login(username=self.client_user.username, password=self.password) data = { 'id': self.booking.id, 'n_places': 10, 'start_time': (self.datetime + timedelta(minutes=30)).strftime("%Y-%m-%d-%H-%M-%S"), 'state': Booking.STATES[0][0] } data_result = { 'result': 'success' } response = self.client.post(self.url, data, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) self.assertJSONEqual(str(response.content, encoding='utf8'), data_result) def test_client_logged_ajax_call_without_booking(self): self.client.login(username=self.client_user.username, password=self.password) data = { 'id': 0, 'n_places': 10, 'start_time': (self.datetime + timedelta(minutes=30)).strftime("%Y-%m-%d-%H-%M-%S"), 'state': Booking.STATES[0][0] } data_result = { 'result': 'error' } response = self.client.post(self.url, data, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) self.assertJSONEqual(str(response.content, encoding='utf8'), data_result) class CheckAvailabilityWiewTests(TestCase): def setUp(self): self.url = reverse('booking:check_availability') self.client = Client() self.password = 'password' self.datetime = timezone.make_aware(datetime.now(), timezone.get_current_timezone()).replace(microsecond=0) self.restaurant = Restaurant.objects.create( name='da mario', city='vignola', address='via baracchini, 95', n_places=50, booking_duration=120 ) restaurant_position = get_coordinates(self.restaurant.city + ', ' + self.restaurant.address) self.restaurant.latitude = restaurant_position['lat'] self.restaurant.longitude = restaurant_position['lng'] self.restaurant.save() self.client_user = User.objects.create( first_name='paolo', last_name='verdi', email='paolo.verdi@mail.com', username='paolo1', user_type=User.TYPES[0][0] ) self.client_user.set_password(self.password) self.client_user.save() self.restaurant_user = User.objects.create( first_name='mario', last_name='rossi', email='mario.rossi@mail.com', username='mario1', user_type=User.TYPES[1][0], restaurant_information=self.restaurant ) self.restaurant_user.set_password(self.password) self.restaurant_user.save() self.booking = Booking( client=self.client_user, restaurant=self.restaurant, start_time=self.datetime, n_places=2, state=Booking.STATES[1][0] ) self.booking.end_time = self.booking.calculate_end_time() def test_client_logged_ajax_call(self): response = self.client.post(self.url, {}, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) def test_client_logged_no_ajax_call(self): response = self.client.post(self.url, {}) self.assertEqual(response.status_code, 404) def test_client_logged_ajax_call_with_data(self): self.booking.save() self.client.login(username=self.client_user.username, password=self.password) data = { 'restaurant_id': self.restaurant.id, 'n_places': 10, 'start_time': self.datetime.strftime("%Y-%m-%d-%H-%M-%S") } data_result = { 'result': 'success', 'state': Booking.STATES[1][0] } response = self.client.post(self.url, data, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) self.assertJSONEqual(str(response.content, encoding='utf8'), data_result) def test_client_logged_ajax_call_without_data(self): data = { 'restaurant_id': 0, 'n_places': 10, 'start_time': self.datetime.strftime("%Y-%m-%d-%H-%M-%S") } data_result = { 'result': 'error' } response = self.client.post(self.url, data, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(response.status_code, 200) self.assertJSONEqual(str(response.content, encoding='utf8'), data_result)

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85417f819edd7802b362c96f8f5a411bc62c7664

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Python

app/tests/unit/modules/entity/test_request_entity.py

Clivern/Kevin

dfa6fe99d2599a3f1a9da7c9690e2fba6a825f1d

[ "Apache-2.0" ]

2

2018-06-18T09:37:36.000Z

2021-06-23T02:09:41.000Z

app/tests/unit/modules/entity/test_request_entity.py

Clivern/Kevin

dfa6fe99d2599a3f1a9da7c9690e2fba6a825f1d

[ "Apache-2.0" ]

45

2018-04-08T11:53:05.000Z

2018-06-12T20:45:38.000Z

app/tests/unit/modules/entity/test_request_entity.py

Clivern/Kevin

dfa6fe99d2599a3f1a9da7c9690e2fba6a825f1d

[ "Apache-2.0" ]

null

""" Request Entity Test Cases """ from django.test import TestCase from pprint import pprint from app.modules.entity.namespace_entity import Namespace_Entity from app.modules.entity.endpoint_entity import Endpoint_Entity from app.modules.entity.request_entity import Request_Entity from django.contrib.auth.models import User class Test_Request_Entity(TestCase): def test_insert_one(self): user = User( first_name = "Joe", last_name = "Doe", username = "joe", email = "joe@kevin.com", password = "joe_doe" ) user.save() namespace_entity = Namespace_Entity() endpoint_entity = Endpoint_Entity() request_entity = Request_Entity() namespace = namespace_entity.insert_one({ "name": "kevin", "is_public": True, "user_id": user.pk }) endpoint = endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id }) self.assertTrue(namespace) self.assertTrue(namespace.id > 0) endpoint_entity = Endpoint_Entity(); self.assertTrue(endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id })) request = request_entity.insert_one({ "uri": "/", "method": Request_Entity.GET, "headers": "{}", "body": "{}", "status": Request_Entity.DEBUG, "endpoint_id": endpoint.id }) self.assertTrue(request) self.assertTrue(request.id > 0) def test_insert_many(self): user = User( first_name = "Joe", last_name = "Doe", username = "joe", email = "joe@kevin.com", password = "joe_doe" ) user.save() namespace_entity = Namespace_Entity() endpoint_entity = Endpoint_Entity() request_entity = Request_Entity() namespace = namespace_entity.insert_one({ "name": "kevin", "is_public": True, "user_id": user.pk }) endpoint = endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id }) self.assertTrue(namespace) self.assertTrue(namespace.id > 0) endpoint_entity = Endpoint_Entity(); self.assertTrue(endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id })) request = request_entity.insert_many([ {"uri": "/","method": Request_Entity.GET,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id}, {"uri": "/","method": Request_Entity.POST,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id}, {"uri": "/{id}","method": Request_Entity.GET,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id}, {"uri": "/{id}","method": Request_Entity.PUT,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id} ]) self.assertTrue(request) def test_get_one_by_id(self): user = User( first_name = "Joe", last_name = "Doe", username = "joe", email = "joe@kevin.com", password = "joe_doe" ) user.save() namespace_entity = Namespace_Entity() endpoint_entity = Endpoint_Entity() request_entity = Request_Entity() namespace = namespace_entity.insert_one({ "name": "kevin", "is_public": True, "user_id": user.pk }) endpoint = endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id }) self.assertTrue(namespace) self.assertTrue(namespace.id > 0) endpoint_entity = Endpoint_Entity(); self.assertTrue(endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id })) request = request_entity.insert_one({ "uri": "/", "method": Request_Entity.GET, "headers": "{}", "body": "{}", "status": Request_Entity.DEBUG, "endpoint_id": endpoint.id }) self.assertTrue(request) self.assertTrue(request.id > 0) request = request_entity.get_one_by_id(request.id) self.assertEqual("get/debug", request.method + request.uri + request.status) def test_get_many_by_endpoint(self): user = User( first_name = "Joe", last_name = "Doe", username = "joe", email = "joe@kevin.com", password = "joe_doe" ) user.save() namespace_entity = Namespace_Entity() endpoint_entity = Endpoint_Entity() request_entity = Request_Entity() namespace = namespace_entity.insert_one({ "name": "kevin", "is_public": True, "user_id": user.pk }) endpoint = endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id }) self.assertTrue(namespace) self.assertTrue(namespace.id > 0) endpoint_entity = Endpoint_Entity(); self.assertTrue(endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id })) request = request_entity.insert_many([ {"uri": "/","method": Request_Entity.GET,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id}, {"uri": "/","method": Request_Entity.POST,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id}, {"uri": "/{id}","method": Request_Entity.GET,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id}, {"uri": "/{id}","method": Request_Entity.PUT,"headers": "{}","body": "{}","status": Request_Entity.DEBUG,"endpoint_id": endpoint.id} ]) self.assertEqual(request_entity.get_many_by_endpoint(endpoint.id, "create_at", True).count(), 4) def test_update_one_by_id(self): user = User( first_name = "Joe", last_name = "Doe", username = "joe", email = "joe@kevin.com", password = "joe_doe" ) user.save() namespace_entity = Namespace_Entity() endpoint_entity = Endpoint_Entity() request_entity = Request_Entity() namespace = namespace_entity.insert_one({ "name": "kevin", "is_public": True, "user_id": user.pk }) endpoint = endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id }) self.assertTrue(namespace) self.assertTrue(namespace.id > 0) endpoint_entity = Endpoint_Entity(); self.assertTrue(endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id })) request = request_entity.insert_one({ "uri": "/", "method": Request_Entity.GET, "headers": "{}", "body": "{}", "status": Request_Entity.DEBUG, "endpoint_id": endpoint.id }) self.assertTrue(request) self.assertTrue(request.id > 0) self.assertTrue(request_entity.update_one_by_id(request.id, {"uri" : "/new"})) request = request_entity.get_one_by_id(request.id) self.assertEqual("get/newdebug", request.method + request.uri + request.status) def test_delete_one_by_id(self): user = User( first_name = "Joe", last_name = "Doe", username = "joe", email = "joe@kevin.com", password = "joe_doe" ) user.save() namespace_entity = Namespace_Entity() endpoint_entity = Endpoint_Entity() request_entity = Request_Entity() namespace = namespace_entity.insert_one({ "name": "kevin", "is_public": True, "user_id": user.pk }) endpoint = endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id }) self.assertTrue(namespace) self.assertTrue(namespace.id > 0) endpoint_entity = Endpoint_Entity(); self.assertTrue(endpoint_entity.insert_one({ "route": "/", "method": Endpoint_Entity.GET, "target": Endpoint_Entity.DEBUG, "route_rules": "{}", "headers_rules": "{}", "body_rules": "{}", "namespace_id": namespace.id })) request = request_entity.insert_one({ "uri": "/", "method": Request_Entity.GET, "headers": "{}", "body": "{}", "status": Request_Entity.DEBUG, "endpoint_id": endpoint.id }) self.assertTrue(request) self.assertTrue(request.id > 0) self.assertTrue(request_entity.delete_one_by_id(request.id)) self.assertFalse(request_entity.delete_one_by_id(1000))

36.423077

145

0.529391

1,059

11,364

5.409821

0.061379

0.15151

0.057602

0.058649

0.923721

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0.902775

0.887764

0

0.001945

0.321454

11,364

312

146

36.423077

0.741019

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false

0.02027

0

0.043919

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0

null

0

1

0

1

0

null

0

7

859383108cc9e4ced082f12dfb83fe29d05bf98c

12,668

py

Python

lib/ult/Generate_HICO_detection.py

abreza/HOI-CL

c5be517bb26eac73ef88a39d6ec9e564c3379714

[ "MIT" ]

40

2021-04-09T17:53:08.000Z

2022-03-30T02:38:10.000Z

lib/ult/Generate_HICO_detection.py

abreza/HOI-CL

c5be517bb26eac73ef88a39d6ec9e564c3379714

[ "MIT" ]

21

2021-04-09T19:05:47.000Z

2022-01-31T23:17:16.000Z

lib/ult/Generate_HICO_detection.py

abreza/HOI-CL

c5be517bb26eac73ef88a39d6ec9e564c3379714

[ "MIT" ]

8

2021-05-30T12:37:00.000Z

2022-03-14T03:13:57.000Z

# -------------------------------------------------------- # Tensorflow VCL # Licensed under The MIT License [see LICENSE for details] # Written by Zhi Hou # -------------------------------------------------------- """ Change the HICO-DET detection results to the right format. """ import pickle import numpy as np import scipy.io as sio import os # HICO = None from ult.tools import get_convert_matrix def save_HICO(HICO, HICO_dir, classid, begin, finish, fuse_type='spho'): all_boxes = [] for i in range(finish - begin + 1): total = [] score = [] for key, value in HICO.items(): for element in value: if element[2] == classid: temp = [] temp.append(element[0].tolist()) # Human box temp.append(element[1].tolist()) # Object box temp.append(int(key)) # image id temp.append(int(i)) # action id (0-599) # if fuse_type == 'spv': # preds = element[11] # else: preds = obtain_fuse_preds(element, fuse_type) # preds = obtain_fuse_preds(element, fuse_type) # cls_prob_sp * (cls_prob_O + cls_prob_H) + cls_prob_verbs # preds = pSp * (pO + pH + pVerbs) # preds = pSp * (pO + pH) # preds = pSp # preds = pO + pH # preds = pSp * pVerbs # preds = pVerbs # print(preds, element[4], element[5]) temp.append(preds[begin - 1 + i] * element[4] * element[5]) total.append(temp) score.append(preds[begin - 1 + i] * element[4] * element[5]) idx = np.argsort(score, axis=0)[::-1] for i_idx in range(min(len(idx), 19999)): all_boxes.append(total[idx[i_idx]]) savefile = HICO_dir + 'detections_' + str(classid).zfill(2) + '.mat' # print('length:', classid, len(all_boxes)) sio.savemat(savefile, {'all_boxes': all_boxes}) return all_boxes verb_to_HO_matrix, obj_to_HO_matrix = get_convert_matrix() hoi_2_obj = {} for i in range(600): for j in range(80): if obj_to_HO_matrix[j][i] > 0: hoi_2_obj[i] = j def obtain_fuse_preds(element, fuse_type): preds = element[3] if fuse_type != 'preds': pH = element[6] pO = element[7] pSp = element[8] pHoi = element[9] if fuse_type == 'preds': preds = preds elif fuse_type == 'spho': preds = pSp * (pO + pH) elif fuse_type == 'ho': preds = pO + pH elif fuse_type == 'spv': preds = pSp * pHoi elif fuse_type == 'sp': preds = pSp elif fuse_type == 'v': preds = pHoi else: raise Exception('fuse_type error, you must select those types{spho, spv, sp, sphov}') return preds def save_HICO3(HICO, HICO_dir, classid, begin, finish, fuse_type='spho'): # "spho" is from iCAN which includes three branch: sp, v, o global hoi_2_obj global obj_to_HO_matrix all_boxes = [] ones = np.ones(600) for i in range(finish - begin + 1): total = [] score = [] for key, value in HICO.items(): for element in value: if fuse_type == 'spv': preds = element[11] else: preds = obtain_fuse_preds(element, fuse_type) # st1 = time.time() obj_scores = element[12] # here is the different objid = element[13] # objid = label_trans_map[objid] + 1 objid += 1 element[5] = obj_scores if objid == classid: temp = [] temp.append(element[0].tolist()) # Human box temp.append(element[1].tolist()) # Object box temp.append(int(key)) # image id temp.append(int(i)) # action id (0-599) temp.append(preds[begin - 1 + i] * element[4] * element[5]) total.append(temp) score.append(preds[begin - 1 + i] * element[4] * element[5]) idx = np.argsort(score, axis=0)[::-1] for i_idx in range(min(len(idx), 19999)): all_boxes.append(total[idx[i_idx]]) savefile = HICO_dir + 'detections_' + str(classid).zfill(2) + '.mat' # print('length:', classid, len(all_boxes)) sio.savemat(savefile, {'all_boxes': all_boxes}) return all_boxes def Generate_HICO_detection3(HICO, HICO_dir, fuse_type, gpool, func_type = 0): if not os.path.exists(HICO_dir): os.makedirs(HICO_dir) # Remove previous results filelist = [ f for f in os.listdir(HICO_dir)] for f in filelist: os.remove(os.path.join(HICO_dir, f)) params = [[1 ,161, 170], # 1 person [2 ,11, 24],# 2 bicycle [3, 66, 76 ], # 3 car [ 4, 147, 160], # 4 motorcycle [ 5, 1, 10], # 5 airplane [ 6, 55, 65], # 6 bus [ 7, 187, 194], # 7 train [ 8, 568, 576], # 8 truck [ 9, 32, 46], # 9 boat [ 10, 563, 567], # 10 traffic light [ 11, 326, 330], # 11 fire_hydrant [ 12, 503, 506], # 12 stop_sign [ 13, 415, 418], # 13 parking_meter [ 14, 244, 247], # 14 bench [ 15, 25, 31], # 15 bird [ 16, 77, 86], # 16 cat [ 17, 112, 129], # 17 dog [ 18, 130, 146], # 18 horse [ 19, 175, 186], # 19 sheep [ 20, 97, 107], # 20 cow [ 21, 314, 325], # 21 elephant [ 22, 236, 239], # 22 bear [ 23, 596, 600], # 23 zebra [ 24, 343, 348], # 24 giraffe [ 25, 209, 214], # 25 backpack [ 26, 577, 584], # 26 umbrella [ 27, 353, 356], # 27 handbag [ 28, 539, 546], # 28 tie [ 29, 507, 516], # 29 suitcase [ 30, 337, 342], # 30 Frisbee [ 31, 464, 474], # 31 skis [ 32, 475, 483], # 32 snowboard [ 33, 489, 502], # 33 sports_ball [ 34, 369, 376], # 34 kite [ 35, 225, 232], # 35 baseball_bat [ 36, 233, 235], # 36 baseball_glove [ 37, 454, 463], # 37 skateboard [ 38, 517, 528], # 38 surfboard [ 39, 534, 538], # 39 tennis_racket [ 40, 47, 54], # 40 bottle [ 41, 589, 595], # 41 wine_glass [ 42, 296, 305], # 42 cup [ 43, 331, 336], # 43 fork [ 44, 377, 383], # 44 knife [ 45, 484, 488], # 45 spoon [ 46, 253, 257], # 46 bowl [ 47, 215, 224], # 47 banana [ 48, 199, 208], # 48 apple [ 49, 439, 445], # 49 sandwich [ 50, 398, 407], # 50 orange [ 51, 258, 264], # 51 broccoli [ 52, 274, 283], # 52 carrot [ 53, 357, 363], # 53 hot_dog [ 54, 419, 429], # 54 pizza [ 55, 306, 313], # 55 donut [ 56, 265, 273], # 56 cake [ 57, 87, 92], # 57 chair [ 58, 93, 96], # 58 couch [ 59, 171, 174], # 59 potted_plant [ 60, 240, 243], # 60 bed [ 61, 108, 111], # 61 dining_table [ 62, 551, 558], # 62 toilet [ 63, 195, 198], # 63 TV [ 64, 384, 389], # 64 laptop [ 65, 394, 397], # 65 mouse [ 66, 435, 438], # 66 remote [ 67, 364, 368], # 67 keyboard [ 68, 284, 290], # 68 cell_phone [ 69, 390, 393], # 69 microwave [ 70, 408, 414], # 70 oven [ 71, 547, 550], # 71 toaster [ 72, 450, 453], # 72 sink [ 73, 430, 434], # 73 refrigerator [ 74, 248, 252], # 74 book [ 75, 291, 295], # 75 clock [ 76, 585, 588], # 76 vase [ 77, 446, 449], # 77 scissors [ 78, 529, 533], # 78 teddy_bear [ 79, 349, 352], # 79 hair_drier [ 80, 559, 562], # 80 toothbrush ] import datetime # from multiprocessing import Pool # # process_num = 16 if fuse_type == 'spv' else 2 # # global pool # # if pool is None: # pool = Pool(processes=process_num) # def func(item): # # save_HICO(HICO, HICO_dir, item[0], item[1], item[2]) # from itertools import repeat # gpool.starmap(save_HICO1, zip(repeat(output_file), repeat(HICO_dir), params, repeat(fuse_type))) from sys import version_info print('Load HICO sucessfully', datetime.datetime.now()) all_boxes = [] for p in params: # print(p) res = save_HICO3(HICO, HICO_dir, p[0], p[1], p[2], fuse_type) # all_boxes.extend(res) # savefile = HICO_dir + 'detections.mat' # sio.savemat(savefile, {'all_boxes': all_boxes}) # print('end', p) print("Finish save HICO", datetime.datetime.now()) def Generate_HICO_detection(output_file, HICO_dir, fuse_type, gpool): if not os.path.exists(HICO_dir): os.makedirs(HICO_dir) # Remove previous results filelist = [ f for f in os.listdir(HICO_dir)] for f in filelist: os.remove(os.path.join(HICO_dir, f)) params = [[1 ,161, 170], # 1 person [2 ,11, 24],# 2 bicycle [3, 66, 76 ], # 3 car [ 4, 147, 160], # 4 motorcycle [ 5, 1, 10], # 5 airplane [ 6, 55, 65], # 6 bus [ 7, 187, 194], # 7 train [ 8, 568, 576], # 8 truck [ 9, 32, 46], # 9 boat [ 10, 563, 567], # 10 traffic light [ 11, 326, 330], # 11 fire_hydrant [ 12, 503, 506], # 12 stop_sign [ 13, 415, 418], # 13 parking_meter [ 14, 244, 247], # 14 bench [ 15, 25, 31], # 15 bird [ 16, 77, 86], # 16 cat [ 17, 112, 129], # 17 dog [ 18, 130, 146], # 18 horse [ 19, 175, 186], # 19 sheep [ 20, 97, 107], # 20 cow [ 21, 314, 325], # 21 elephant [ 22, 236, 239], # 22 bear [ 23, 596, 600], # 23 zebra [ 24, 343, 348], # 24 giraffe [ 25, 209, 214], # 25 backpack [ 26, 577, 584], # 26 umbrella [ 27, 353, 356], # 27 handbag [ 28, 539, 546], # 28 tie [ 29, 507, 516], # 29 suitcase [ 30, 337, 342], # 30 Frisbee [ 31, 464, 474], # 31 skis [ 32, 475, 483], # 32 snowboard [ 33, 489, 502], # 33 sports_ball [ 34, 369, 376], # 34 kite [ 35, 225, 232], # 35 baseball_bat [ 36, 233, 235], # 36 baseball_glove [ 37, 454, 463], # 37 skateboard [ 38, 517, 528], # 38 surfboard [ 39, 534, 538], # 39 tennis_racket [ 40, 47, 54], # 40 bottle [ 41, 589, 595], # 41 wine_glass [ 42, 296, 305], # 42 cup [ 43, 331, 336], # 43 fork [ 44, 377, 383], # 44 knife [ 45, 484, 488], # 45 spoon [ 46, 253, 257], # 46 bowl [ 47, 215, 224], # 47 banana [ 48, 199, 208], # 48 apple [ 49, 439, 445], # 49 sandwich [ 50, 398, 407], # 50 orange [ 51, 258, 264], # 51 broccoli [ 52, 274, 283], # 52 carrot [ 53, 357, 363], # 53 hot_dog [ 54, 419, 429], # 54 pizza [ 55, 306, 313], # 55 donut [ 56, 265, 273], # 56 cake [ 57, 87, 92], # 57 chair [ 58, 93, 96], # 58 couch [ 59, 171, 174], # 59 potted_plant [ 60, 240, 243], # 60 bed [ 61, 108, 111], # 61 dining_table [ 62, 551, 558], # 62 toilet [ 63, 195, 198], # 63 TV [ 64, 384, 389], # 64 laptop [ 65, 394, 397], # 65 mouse [ 66, 435, 438], # 66 remote [ 67, 364, 368], # 67 keyboard [ 68, 284, 290], # 68 cell_phone [ 69, 390, 393], # 69 microwave [ 70, 408, 414], # 70 oven [ 71, 547, 550], # 71 toaster [ 72, 450, 453], # 72 sink [ 73, 430, 434], # 73 refrigerator [ 74, 248, 252], # 74 book [ 75, 291, 295], # 75 clock [ 76, 585, 588], # 76 vase [ 77, 446, 449], # 77 scissors [ 78, 529, 533], # 78 teddy_bear [ 79, 349, 352], # 79 hair_drier [ 80, 559, 562], # 80 toothbrush ] import datetime # from multiprocessing import Pool # # process_num = 16 if fuse_type == 'spv' else 2 # # global pool # # if pool is None: # pool = Pool(processes=process_num) # def func(item): # # save_HICO(HICO, HICO_dir, item[0], item[1], item[2]) # # gpool.starmap(save_HICO1, zip(repeat(output_file), repeat(HICO_dir), params, repeat(fuse_type))) from sys import version_info if version_info.major == 3: HICO = pickle.load(open(output_file, "rb"), encoding='latin1') else: HICO = pickle.load(open(output_file, "rb")) print('Load HICO sucessfully', datetime.datetime.now()) for p in params: # print(p) save_HICO(HICO, HICO_dir, p[0], p[1], p[2], fuse_type) # print('end', p) # pool.close() # pool.join() # pool.terminate() # del pool # import gc # gc.collect() # pool.map(save_HICO, params) print("Finish save HICO", datetime.datetime.now())

33.162304

102

0.511762

1,744

12,668

3.623853

0.287271

0.03038

0.012184

0.012658

0.804747

0.787975

0.782278

0.730696

0.717722

0

0.192285

0.334938

12,668

381

103

33.249344

0.557864

0.279918

0

0.80427

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0.017794

false

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0

null

0

1

0

1

0

null

0

7

85bbee7a72432baab70dcf67b4519676dc5248b6

9,997

py

Python

tests/query/v2/match/test_variable_length_relationships.py

tom-chensf/nebula-graph

0f2f0d02879bfd2421815a26158e8fa030f19b62

[ "Apache-2.0" ]

null

tests/query/v2/match/test_variable_length_relationships.py

tom-chensf/nebula-graph

0f2f0d02879bfd2421815a26158e8fa030f19b62

[ "Apache-2.0" ]

null

tests/query/v2/match/test_variable_length_relationships.py

tom-chensf/nebula-graph

0f2f0d02879bfd2421815a26158e8fa030f19b62

[ "Apache-2.0" ]

null

# --coding:utf-8-- # # Copyright (c) 2020 vesoft inc. All rights reserved. # # This source code is licensed under Apache 2.0 License, # attached with Common Clause Condition 1.0, found in the LICENSES directory. import pytest from tests.common.nebula_test_suite import NebulaTestSuite @pytest.mark.usefixtures('set_vertices_and_edges') class TestVariableLengthRelationshipMatch(NebulaTestSuite): @classmethod def prepare(cls): cls.use_nba() @pytest.mark.skip def test_to_be_deleted(self): # variable steps stmt = 'MATCH (v:player:{name: "abc"}) -[r*1..3]-> () return *' self.fail_query(stmt) stmt = 'MATCH (v:player:{name: "abc"}) -[r*..3]-> () return *' self.fail_query(stmt) stmt = 'MATCH (v:player:{name: "abc"}) -[r*1..]-> () return *' self.fail_query(stmt) @pytest.mark.skip def test_hops_0_to_1(self, like, serve): VERTICES, EDGES = self.VERTEXS, self.EDGS def like_row(dst: str): return [[like('Tracy McGrady', dst)], VERTICES[dst]] def serve_row(dst): return [[serve('Tracy McGrady', dst)], VERTICES[dst]] # single both direction edge with properties stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:serve*0..1{start_year: 2000}]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], serve_row("Magic") ] } self.check_rows_with_header(stmt, expected) stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:like*0..1{likeness: 90}]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), like_row("Vince Carter"), like_row("Yao Ming"), like_row("Grant Hill"), # like each other ] } self.check_rows_with_header(stmt, expected) stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:like*1{likeness: 90}]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), like_row("Vince Carter"), like_row("Yao Ming"), like_row("Grant Hill"), # like each other ] } self.check_rows_with_header(stmt, expected) stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:like*0{likeness: 90}]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], ] } self.check_rows_with_header(stmt, expected) # single direction edge with properties stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:like*0..1{likeness: 90}]->(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), ] } self.check_rows_with_header(stmt, expected) stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:like*0{likeness: 90}]->(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], ] } self.check_rows_with_header(stmt, expected) stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:like*1{likeness: 90}]->(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), ] } self.check_rows_with_header(stmt, expected) # single both direction edge without properties stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:serve*0..1]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], serve_row("Raptors"), serve_row("Magic"), serve_row("Spurs"), serve_row("Rockets"), ] } self.check_rows_with_header(stmt, expected) stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:like*0..1]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), like_row("Vince Carter"), like_row("Yao Ming"), like_row("Grant Hill"), # like each other ] } self.check_rows_with_header(stmt, expected) # multiple both direction edge with properties stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:serve|like*0..1{start_year: 2000}]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], serve_row("Magic"), ] } self.check_rows_with_header(stmt, expected) # multiple single direction edge with properties stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:serve|like*0..1{start_year: 2000}]->(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], serve_row("Magic"), ] } self.check_rows_with_header(stmt, expected) stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:serve|like*0..1{likeness: 90}]->(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), ] } self.check_rows_with_header(stmt, expected) # multiple both direction edge with properties stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:serve|like*0..1]-(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), like_row("Vince Carter"), like_row("Yao Ming"), like_row("Grant Hill"), serve_row("Raptors"), serve_row("Magic"), serve_row("Spurs"), serve_row("Rockets"), ] } self.check_rows_with_header(stmt, expected) # multiple single direction edge with properties stmt = ''' MATCH (:player{name:"Tracy McGrady"})-[e:serve|like*0..1]->(v) RETURN e, v ''' expected = { "column_names": ['e', 'v'], "rows": [ [[], VERTICES["Tracy McGrady"]], like_row("Kobe Bryant"), like_row("Grant Hill"), like_row("Rudy Gay"), serve_row("Raptors"), serve_row("Magic"), serve_row("Spurs"), serve_row("Rockets"), ] } self.check_rows_with_header(stmt, expected) @pytest.mark.skip def test_mix_hops(self): stmt = ''' MATCH (:player{name: "Tim Duncan"})-[e1:like]->()-[e2:serve*0..3]->()<-[e3:serve]-(v) RETURN e1, e2, e3, v ''' expected = { "column_names": ['e', 'v'], "rows": [] } self.check_rows_with_header(stmt, expected) def test_more_cases(self, like, serve, like_2hop): # stmt = ''' # MATCH (v:player{name: 'Tim Duncan'})-[e:like*0]-() # RETURN e # ''' # stmt = ''' # MATCH (v:player{name: 'Tim Duncan'})-[e:like*0..0]-() # RETURN e # ''' # stmt = ''' # MATCH (v:player{name: 'Tim Duncan'})-[e:like*]-() # RETURN e # ''' # stmt = ''' # MATCH (v:player{name: 'Tim Duncan'})-[e:like*0..0]-()-[e2:like*0..0]-() # RETURN e, e2 # ''' stmt=''' MATCH p=(v:player{name: 'Tim Duncan'})-[:like|:serve*1..3]->(v1) WHERE e[0].likeness>90 RETURN p ''' resp = self.execute(stmt) self.check_resp_failed(resp) self.check_error_msg(resp, "SemanticError: Alias used but not defined: `e'") stmt=''' MATCH p=(v:player{name: 'Tim Duncan'})-[:like|:serve*1..3]->(v1) RETURN e ''' resp = self.execute(stmt) self.check_resp_failed(resp) self.check_error_msg(resp, "SemanticError: Alias used but not defined: `e'") stmt=''' MATCH p=(v:player{name: 'Tim Duncan'})-[:like|:serve*1..3]->(v1) WHERE e[0].likeness+e[1].likeness>90 RETURN p ''' resp = self.execute(stmt) self.check_resp_failed(resp) self.check_error_msg(resp, "SemanticError: Alias used but not defined: `e'")

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a472d9dbbef1548c74841070f5d2c899c69f8e82

14,181

py

Python

drf_tester/viewsets/staff.py

samuelmovi/drf-tester

5ad4cfadbec98f13f73b656c8d690c591d09c216

[ "MIT" ]

1

2021-09-10T11:46:29.000Z

drf_tester/viewsets/staff.py

samuelmovi/drf-tester

5ad4cfadbec98f13f73b656c8d690c591d09c216

[ "MIT" ]

null

drf_tester/viewsets/staff.py

samuelmovi/drf-tester

5ad4cfadbec98f13f73b656c8d690c591d09c216

[ "MIT" ]

null

""" Collection of classes to be used in the testing of access to a Viewset by a STAFF user """ from rest_framework import status from rest_framework.test import force_authenticate from ..utils import BaseDrfTest class NoList(BaseDrfTest): def test_staff_user_cannot_list_existing_instance(self): """Staff user cannot list existing instances""" # get user user = self.get_active_staff(self.user_data) # Create instance instances = self.get_model_instances() # Query endpoint request = self.requests.get(self.endpoint, data={}) force_authenticate(request, user=user) response = self.view(request) # Assert forbidden access self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) class NoListOwned(BaseDrfTest): def test_staff_user_cannot_list_owned_instance(self): """Staff user cannot list owned instances""" # get user user = self.get_active_staff(self.user_data) # Create instance instances = self.get_model_instances() for x in instances: setattr(x, self.USER_FIELD_NAME, user) x.save() # Query endpoint request = self.requests.get(self.endpoint, data={}) force_authenticate(request, user=user) response = self.view(request) # Assert forbidden access self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) class NoRetrieve(BaseDrfTest): def test_staff_user_cannot_get_existing_instance(self): """Staff user cannot get details on existing instance""" # get user user = self.get_active_staff(self.user_data) # Create instance instance = self.factory() # Query endpoint request = self.requests.get(self.endpoint, data={}) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert forbidden access self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) class NoRetrieveOwned(BaseDrfTest): def test_staff_user_cannot_get_owned_instance(self): """Staff user cannot get details on own instance""" # get user user = self.get_active_staff(self.user_data) # Create instance instance = self.factory() setattr(instance, self.USER_FIELD_NAME, user) instance.save() # Query endpoint request = self.requests.get(self.endpoint, data={}) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert forbidden access self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) class NoCreate(BaseDrfTest): def test_staff_user_cannot_create_instance(self): """Staff user cannot create new instance""" # get user user = self.get_active_staff(self.user_data) # Query endpoint request = self.requests.post(self.endpoint, data={}) force_authenticate(request, user=user) response = self.view(request) # Assert access is forbidden self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) class NoUpdate(BaseDrfTest): def test_staff_user_cannot_modify_existing_instance(self): """Staff user cannot modify existing instance""" # get user user = self.get_active_staff(self.user_data) # Create instance instance = self.factory() # Query endpoint request = self.requests.put(self.endpoint, data={}) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert forbidden access self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) class NoUpdateOwned(BaseDrfTest): def test_staff_user_cannot_modify_owned_instance(self): """Staff user cannot modify owned instance""" # get user user = self.get_active_staff(self.user_data) # Create instance instance = self.factory() setattr(instance, self.USER_FIELD_NAME, user) instance.save() # Query endpoint request = self.requests.put(self.endpoint, data={}) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert forbidden access self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) class NoDestroy(BaseDrfTest): def test_staff_user_cannot_delete_existing_instance(self): """Staff user cannot delete existing instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() # Query endpoint request = self.requests.delete(self.endpoint) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert access forbidden self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) # Assert instance still exists on db self.assertTrue(self.model.objects.filter(id=instance.pk).exists()) class NoDestroyOwned(BaseDrfTest): def test_staff_user_cannot_delete_owned_instance(self): """Staff user cannot delete owned instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() setattr(instance, self.USER_FIELD_NAME, user) instance.save() # Query endpoint request = self.requests.delete(self.endpoint) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert access forbidden self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) # Assert instance still exists on db self.assertTrue(self.model.objects.filter(id=instance.pk).exists()) class CanList(BaseDrfTest): def test_staff_user_can_list_instances(self): """Staff user can list instances""" # get user user = self.get_active_staff(self.user_data) # Create instances instances = self.get_model_instances() # Request list request = self.requests.get(self.endpoint) force_authenticate(request, user=user) response = self.view(request) # Assert access is allowed self.assertEqual(response.status_code, status.HTTP_200_OK) # Assert all instances are returned self.assertEqual(len(instances), len(response.data)) class CanListOwned(BaseDrfTest): def test_staff_user_can_list_owned_instances(self): """Staff user can list owned instances""" # get user user = self.get_active_staff(self.user_data) # Create instances instances = self.get_model_instances() for x in instances: setattr(x, self.USER_FIELD_NAME, user) x.save() # Request list request = self.requests.get(self.endpoint) force_authenticate(request, user=user) response = self.view(request) # Assert access is allowed self.assertEqual(response.status_code, status.HTTP_200_OK) # Assert all instances are returned self.assertEqual(len(instances), len(response.data)) class CanRetrieve(BaseDrfTest): def test_staff_user_can_get_instance(self): """Staff user can get existing instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() # Request list request = self.requests.get(self.endpoint) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert access is allowed self.assertEqual(response.status_code, status.HTTP_200_OK) class CanRetrieveOwned(BaseDrfTest): def test_staff_user_can_get_owned_instance(self): """Staff user can get owned instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() setattr(instance, self.USER_FIELD_NAME, user) instance.save() # Request list request = self.requests.get(self.endpoint) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert access is allowed self.assertEqual(response.status_code, status.HTTP_200_OK) class CanCreate(BaseDrfTest): def test_staff_user_can_create_instance(self): """Staff user can create new instance""" # get user user = self.get_active_staff(self.user_data) # Query endpoint request = self.requests.post(self.endpoint, data=self.instance_data) force_authenticate(request, user=user) response = self.view(request) # Assert endpoint returns created status self.assertEqual(response.status_code, status.HTTP_201_CREATED) # Assert instance exists on db self.assertTrue(self.model.objects.filter(id=response.data["id"]).exists()) self.check_equal_data(self.instance_data, response.data) class CanCreateOwned(BaseDrfTest): def test_staff_user_can_create_owned_instance(self): """Staff user can create new owned instance""" # get user user = self.get_active_staff(self.user_data) # add as owner self.instance_data[self.USER_FIELD_NAME] = user.id # Query endpoint request = self.requests.post(self.endpoint, data=self.instance_data) force_authenticate(request, user=user) response = self.view(request) # Assert endpoint returns created status self.assertEqual(response.status_code, status.HTTP_201_CREATED) # Assert instance exists on db self.assertTrue(self.model.objects.filter(id=response.data["id"]).exists()) self.check_equal_data(self.instance_data, response.data) class CanUpdate(BaseDrfTest): def test_staff_user_can_modify_instance(self): """Staff user can modify existing instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() # Query endpoint request = self.requests.put(self.endpoint, self.instance_data) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert endpoint returns OK code self.assertEqual(response.status_code, status.HTTP_200_OK) self.check_equal_data(self.instance_data, response.data) class CanUpdateOwned(BaseDrfTest): def test_staff_user_can_modify_owned_instance(self): """Staff user can modify owned instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() setattr(instance, self.USER_FIELD_NAME, user) instance.save() # Query endpoint request = self.requests.put(self.endpoint, self.instance_data) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # Assert endpoint returns OK code self.assertEqual(response.status_code, status.HTTP_200_OK) self.check_equal_data(self.instance_data, response.data) class CanDestroy(BaseDrfTest): def test_staff_user_can_delete_instance(self): """Staff user can delete existing instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() # Query endpoint request = self.requests.delete(self.endpoint) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # assert 204 no content self.assertEqual(response.status_code, status.HTTP_204_NO_CONTENT) # Assert instance doesn't exists anymore on db self.assertFalse(self.model.objects.filter(id=instance.pk).exists()) class CanDestroyOwned(BaseDrfTest): def test_staff_user_can_delete_owned_instance(self): """Staff user can delete owned instance""" # get user user = self.get_active_staff(self.user_data) # Create instances instance = self.factory() setattr(instance, self.USER_FIELD_NAME, user) instance.save() # Query endpoint request = self.requests.delete(self.endpoint) force_authenticate(request, user=user) response = self.view(request, pk=instance.id) # assert 204 no content self.assertEqual(response.status_code, status.HTTP_204_NO_CONTENT) # Assert instance doesn't exists anymore on db self.assertFalse(self.model.objects.filter(id=instance.pk).exists()) class CanPaginate(BaseDrfTest): def test_staff_user_can_paginate_instances(self): """Staff user can paginate instances""" limit = 5 offset = 10 # get user user = self.get_active_staff(self.user_data) # create instances instances = self.get_model_instances() # Request list url = f"{self.endpoint}?limit={limit}&offset={offset}" request = self.requests.get(url) force_authenticate(request, user=user) response = self.view(request) # Assert access is allowed self.assertEqual(response.status_code, status.HTTP_200_OK) # assert only 2 instances in response payload = response.json() self.assertTrue(len(payload["results"]) <= 5) # EXTENDED CLASSES class StaffFullAccess(CanList, CanRetrieve, CanCreate, CanUpdate, CanDestroy): """ Staff user has full access to endopint """ pass class StaffNoAccess(NoList, NoRetrieve, NoCreate, NoUpdate, NoDestroy): """ Staff user has no access to endopint """ pass class StaffReadOnly(CanList, CanRetrieve, NoCreate, NoUpdate, NoDestroy): """ Staff user has only read access to endopint """ pass class StaffOwner(CanListOwned, CanRetrieveOwned, CanCreateOwned, CanUpdateOwned, CanDestroyOwned): """ Staff user can access intances owned by user """ pass

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null

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7

a494b54b716174578140bc992363b676003a99ac

116

py

Python

ocr/data_helper/__init__.py

aksharsramesh/optical-character-recognition

ccd9b9eb17aeab8d67be2fc842228e3280f3ff2b

[ "MIT" ]

null

ocr/data_helper/__init__.py

aksharsramesh/optical-character-recognition

ccd9b9eb17aeab8d67be2fc842228e3280f3ff2b

[ "MIT" ]

null

ocr/data_helper/__init__.py

aksharsramesh/optical-character-recognition

ccd9b9eb17aeab8d67be2fc842228e3280f3ff2b

[ "MIT" ]

null

# import the necessary packages from .data_helper import load_mnist_dataset from .data_helper import load_az_dataset

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1

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1

0

7

a49d295aabcb67672071aae5309dcbad5b403a40

4,718

py

Python

data/config.py

isLouisHsu/Pytorch_Retinaface

2db5e9aaec42d9605494032a5fa70fb7b82831de

[ "MIT" ]

null

data/config.py

isLouisHsu/Pytorch_Retinaface

2db5e9aaec42d9605494032a5fa70fb7b82831de

[ "MIT" ]

null

data/config.py

isLouisHsu/Pytorch_Retinaface

2db5e9aaec42d9605494032a5fa70fb7b82831de

[ "MIT" ]

null

# config.py cfg_mnet = { 'name': 'mobilenet0.25', 'in_channels': 3, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 64, 'ngpu': 1, 'epoch': 200, 'decay1': 190, 'decay2': 220, 'image_size': 480, 'pretrain': "./weights/pretrained/mobilenetV1X0.25_pretrain.tar", 'return_layers': {'stage1': 1, 'stage2': 2, 'stage3': 3}, 'in_channel': 32, 'out_channel': 64 } cfg_re50 = { 'name': 'Resnet50', 'in_channels': 3, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 8, 'ngpu': 1, 'epoch': 100, 'decay1': 70, 'decay2': 90, 'image_size': 840, 'pretrain': "/home/louishsu/.cache/torch/hub/checkpoints/resnet50-19c8e357.pth", 'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3}, 'in_channel': 256, 'out_channel': 256 } # -------------------------------------------------------------------------------------- cfg_re18 = { 'name': 'Resnet18', 'in_channels': 3, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 48, 'ngpu': 1, 'epoch': 100, 'decay1': 70, 'decay2': 90, 'image_size': 480, 'pretrain': "/home/louishsu/.cache/torch/hub/checkpoints/resnet18-5c106cde.pth", 'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3}, 'in_channel': 64, 'out_channel': 256 } cfg_re34 = { 'name': 'Resnet34', 'in_channels': 3, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 48, 'ngpu': 1, 'epoch': 100, 'decay1': 70, 'decay2': 90, 'image_size': 480, 'pretrain': "/home/louishsu/.cache/torch/hub/checkpoints/resnet34-333f7ec4.pth", 'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3}, 'in_channel': 64, 'out_channel': 256 } cfg_eff_b0 = { 'name': 'Efficientnet-b0', 'in_channels': 3, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 12, 'ngpu': 1, 'epoch': 100, 'decay1': 70, 'decay2': 90, 'image_size': 480, 'pretrain': "/home/louishsu/.cache/torch/hub/checkpoints/tf_efficientnet_b0_ns-c0e6a31c.pth", 'return_layers': {'2': 3, '4': 5, '6': 7}, 'in_channel': None, 'out_channel': 256 } cfg_eff_b4 = { 'name': 'Efficientnet-b4', 'in_channels': 3, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 12, 'ngpu': 1, 'epoch': 100, 'decay1': 70, 'decay2': 90, 'image_size': 480, 'pretrain': "/home/louishsu/.cache/torch/hub/checkpoints/tf_efficientnet_b4_ns-d6313a46.pth", 'return_layers': {'2': 3, '4': 5, '6': 7}, 'in_channel': None, 'out_channel': 256 } # -------------------------------------------------------------------------------------- cfg_re34_hsfd_finetune = { 'name': 'Resnet34', 'used_channels': [12, 19, 13, 6, 3], 'in_channels': 5, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 32, 'ngpu': 1, 'epoch': 20, 'decay1': 70, 'decay2': 90, 'image_size': 320, 'pretrain': "/home/louishsu/.cache/torch/hub/checkpoints/resnet34-333f7ec4.pth", 'finetune': "outputs/resnet34_v1/Resnet34_iter_21000_2.5562_.pth", 'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3}, 'in_channel': 64, 'out_channel': 256 } cfg_re34_hsfd_not_finetune = { 'name': 'Resnet34', 'used_channels': [12, 19, 13, 6, 3], 'in_channels': 5, 'min_sizes': [[16, 32], [64, 128], [256, 512]], 'steps': [8, 16, 32], 'variance': [0.1, 0.2], 'clip': False, 'loc_weight': 2.0, 'gpu_train': True, 'batch_size': 32, 'ngpu': 1, 'epoch': 100, 'decay1': 70, 'decay2': 90, 'image_size': 320, 'pretrain': "/home/louishsu/.cache/torch/hub/checkpoints/resnet34-333f7ec4.pth", 'finetune': None, 'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3}, 'in_channel': 64, 'out_channel': 256 }

26.655367

97

0.523527

609

4,718

3.889984

0.172414

0.027016

0.03377

0.040523

0.832419

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0.824821

0.806247

0

0.144102

0.221916

4,718

177

98

26.655367

0.501226

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0.762195

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1

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false

0

null

0

1

0

1

0

null

0

7

f10e46f519a19547d255f39dd520b21ce38ebe18

1,867

py

Python

checkFolderIntegrity.py

armstjc/Retrosheet_DB

d4eea9dd244f92a8b9e7680a59f174af67498b6c

[ "MIT" ]

2

2021-12-17T04:08:13.000Z

2021-12-19T14:05:20.000Z

checkFolderIntegrity.py

armstjc/Retrosheet_DB

d4eea9dd244f92a8b9e7680a59f174af67498b6c

[ "MIT" ]

null

checkFolderIntegrity.py

armstjc/Retrosheet_DB

d4eea9dd244f92a8b9e7680a59f174af67498b6c

[ "MIT" ]

null

import os def checkFolderCreation(): try: os.mkdir('raw_data') except: pass try: os.mkdir('raw_data/zip') except: pass try: os.mkdir('raw_data/retrosheet') except: pass try: os.mkdir('raw_data/retrosplit') except: pass try: os.mkdir('raw_data/retrosheet/team_gamelog') except: pass try: os.mkdir('raw_data/retrosheet/play_by_play') except: pass try: os.mkdir('raw_data/retrosheet/play_by_play') except: pass try: os.mkdir('raw_data/retrosplit/player_gamelog') except: pass try: os.mkdir('raw_data/retrosplit/team_gamelog') except: pass try: os.mkdir('raw_data/retrosplit/batting_by_position') except: pass try: os.mkdir('raw_data/retrosplit/batting_by_runners') except: pass try: os.mkdir('raw_data/retrosplit/batting_platoon') except: pass try: os.mkdir('raw_data/retrosplit/batting_platoon') except: pass try: os.mkdir('raw_data/retrosplit/batting_head_to_head') except: pass try: os.mkdir('raw_data/retrosplit/pitching_by_runners') except: pass try: os.mkdir('raw_data/retrosplit/pitching_platoon') except: pass try: os.mkdir('raw_data/retrosheet/ejections') except: pass try: os.mkdir('raw_data/retrosheet/transactions') except: pass try: os.mkdir('raw_data/retrosheet/schedules') except: pass try: os.mkdir('data') except: pass def main(): checkFolderCreation() if __name__ == "__main__": main()

16.972727

60

0.546867

202

1,867

4.826733

0.153465

0.102564

0.205128

0.253333

0.855385

0.817436

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0.544615

0.422564

0

0.352437

1,867

110

61

16.972727

0.806452

0

0.744186

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0.312634

0.275161

0

1

0.023256

true

0.232558

0.011628

0

0.034884

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null

0

1

0

1

0

null

0

1

0

9

f11f1c43cde469c2d94f69913987d2fd8aa363d2

5,654

py

Python

romantic-revolutionaries/test/test_viewcontrol.py

LaFeeVert/code-jam-6

f65b284c58ae653f9212923c6d3296cf252b6453

[ "MIT" ]

null

romantic-revolutionaries/test/test_viewcontrol.py

LaFeeVert/code-jam-6

f65b284c58ae653f9212923c6d3296cf252b6453

[ "MIT" ]

2

2020-01-21T19:46:57.000Z

2020-01-21T20:33:05.000Z

romantic-revolutionaries/test/test_viewcontrol.py

LaFeeVert/code-jam-6

f65b284c58ae653f9212923c6d3296cf252b6453

[ "MIT" ]

2

2020-01-20T23:46:14.000Z

2020-01-21T05:50:15.000Z

"""Unitest the view control. Run these tests with either with "pytest" or python -m "unittest" from within the same directory. """ import unittest from modules.view.viewcontrol import ViewControl from modules.navigation.navcont import NavControl, Directions from modules.map.MapControl import DungeonMap class Observer: def __init__(self): self.descriptive_text = '' def callback(self, descriptive_text): self.descriptive_text = descriptive_text # print(self.descriptive_text) class TestViewControl(unittest.TestCase): def setUp(self): # setup the initial test map DungeonMap.map_vector = [ [1, 0, 0, 0], [0, 1, 6, 0], [0, 9, 1, 0], [0, 0, 0, 0]] self.ob = Observer() self.mc = DungeonMap() self.nc = NavControl() self.vc = ViewControl() self.nc.subscribe(self.mc.callback) self.mc.subscribe(self.vc.callback) self.vc.subscribe(self.ob.callback) def test_look(self): self.nc.go(Directions.NORTH) self.vc.look(Directions.NORTH) expected = """You have run into a wall. There is a wall in front of you. It is bordered to the left with a dark passage. It is bordered to the right with a wall. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.SOUTH) expected = """You have run into a wall. There is a dark passage ahead of you. It is bordered to the left with a dark passage. It is bordered to the right with a wall. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.EAST) expected = """You have run into a wall. There is a dark passage ahead of you. It is bordered to the left with a wall. It is bordered to the right with a dark passage. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.WEST) expected = """You have run into a wall. There is a wall in front of you. It is bordered to the left with a wall. It is bordered to the right with a dark passage. """ self.assertEqual(self.ob.descriptive_text, expected) self.nc.go(Directions.SOUTH) self.vc.look(Directions.NORTH) expected = """There is a dark passage ahead of you. It is bordered to the left with a wall. It is bordered to the right with a 6. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) expected = """There is a dark passage ahead of you. It is bordered to the left with a wall. It is bordered to the right with a 6. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.SOUTH) expected = """There is a wall in front of you. It is bordered to the left with a wall. It is bordered to the right with a wall. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.EAST) expected = """There is a dark passage ahead of you. It is bordered to the left with a 6. It is bordered to the right with a wall. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.WEST) expected = """There is a wall in front of you. It is bordered to the left with a wall. It is bordered to the right with a wall. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) self.nc.go(Directions.EAST) self.vc.look(Directions.NORTH) expected = """There is a dark passage ahead of you. It is bordered to the left with a dark passage. It is bordered to the right with a wall. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.SOUTH) expected = """There is a wall in front of you. It is bordered to the left with a wall. It is bordered to the right with a wall. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.EAST) expected = """There is a wall in front of you. It is bordered to the left with a wall. It is bordered to the right with a wall. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.WEST) expected = """There is a dark passage ahead of you. It is bordered to the left with a wall. It is bordered to the right with a dark passage. """ self.assertEqual(self.ob.descriptive_text, expected) self.nc.go(Directions.WEST) self.vc.look(Directions.NORTH) expected = """There is a dark passage ahead of you. It is bordered to the left with a wall. It is bordered to the right with a 6. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.SOUTH) expected = """There is a wall in front of you. It is bordered to the left with a wall. It is bordered to the right with a wall. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.EAST) expected = """There is a dark passage ahead of you. It is bordered to the left with a 6. It is bordered to the right with a wall. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected) self.vc.look(Directions.WEST) expected = """There is a wall in front of you. It is bordered to the left with a wall. It is bordered to the right with a wall. At your feet there is 9. """ self.assertEqual(self.ob.descriptive_text, expected)

32.494253

65

0.671737

890

5,654

4.235955

0.091011

0.046419

0.108223

0.12626

0.820955

0.818302

0.811671

0

0.006988

0.240715

5,654

173

66

32.682081

0.871186

0.032013

0

0.802817

0

0.429094

0

0.119718

1

0.028169

false

0.105634

0.028169

0

0.070423

0

null

0

1

0

1

0

null

0

1

0

8

f12aabd1f6418eee7af037f399cf036bc5f2db08

165

py

Python

google_images_download/__init__.py

Aerobautics/google-images-download

52ed15b3aae9abdb68b0b8567115ac0a42d0a93a

[ "MIT" ]

null

google_images_download/__init__.py

Aerobautics/google-images-download

52ed15b3aae9abdb68b0b8567115ac0a42d0a93a

[ "MIT" ]

null

google_images_download/__init__.py

Aerobautics/google-images-download

52ed15b3aae9abdb68b0b8567115ac0a42d0a93a

[ "MIT" ]

null

#!/usr/bin/env python from __future__ import absolute_import def main(): import google_images_download.google_images_download if __name__ == '__main__': main()

18.333333

53

0.781818

22

165

5.090909

0.681818

0.214286

0.357143

0

0.121212

165

8

54

20.625

0.772414

0.121212

0

0.055556

0

1

0.2

true

0

0.4

0

0.6

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

2d20150f4ff1fc76d598cb2fa324cba41a39aa2a

266

py

Python

torchvision_3d/models/__init__.py

rubythalib33/3D-Torchvision

7dab0a3d1d83e6046320f879af2bff28b31310ab

[ "MIT" ]

4

2022-03-09T02:53:12.000Z

2022-03-10T14:35:06.000Z

torchvision_3d/models/__init__.py

rubythalib33/3D-Torchvision

7dab0a3d1d83e6046320f879af2bff28b31310ab

[ "MIT" ]

null

torchvision_3d/models/__init__.py

rubythalib33/3D-Torchvision

7dab0a3d1d83e6046320f879af2bff28b31310ab

[ "MIT" ]

1

2022-03-10T14:35:08.000Z

from torchvision_3d.models.alexnet import * from torchvision_3d.models.vgg import * from torchvision_3d.models.resnet import * from torchvision_3d.models.densenet import * from torchvision_3d.models.squeezenet import * from torchvision_3d.models.mobilenetv2 import *

44.333333

47

0.845865

36

266

6.083333

0.305556

0.410959

0.465753

0.630137

0.6621

0

0.028807

0.086466

266

6

47

44.333333

0.872428

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

2d205b4bdbb6b2e7797ab66ee1b73933fe7ac633

248

py

Python

src/behavior_tree_learning/gp.py

dgerod/behavior_tree_learning

71da80c91ecd48fd5da377f83604b62112ba9629

[ "Apache-2.0" ]

7

2022-02-09T12:51:51.000Z

2022-03-19T14:40:16.000Z

src/behavior_tree_learning/gp.py

dgerod/behavior_tree_learning

71da80c91ecd48fd5da377f83604b62112ba9629

[ "Apache-2.0" ]

2

2022-02-03T10:54:41.000Z

2022-02-15T10:32:03.000Z

src/behavior_tree_learning/gp.py

dgerod/behavior_tree_learning

71da80c91ecd48fd5da377f83604b62112ba9629

[ "Apache-2.0" ]

null

from behavior_tree_learning.core.gp import GeneticEnvironment, GeneticOperators from behavior_tree_learning.core.gp import GeneticParameters, GeneticSelectionMethods, TraceConfiguration from behavior_tree_learning.core.gp import GeneticProgramming

62

105

0.903226

27

248

8.074074

0.481481

0.165138

0.220183

0.330275

0.495413

0

0.060484

248

3

106

82.666667

0.935622

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

7469eebdd1b10b1d2ecf28291f3dbd2919696c12

9,724

py

Python

axelrod/tests/unit/test_qlearner.py

t0nyt93/Axelroddd

66d95378d3ece8b32afeb1c77d305397bd9a815e

[ "MIT" ]

null

axelrod/tests/unit/test_qlearner.py

t0nyt93/Axelroddd

66d95378d3ece8b32afeb1c77d305397bd9a815e

[ "MIT" ]

null

axelrod/tests/unit/test_qlearner.py

t0nyt93/Axelroddd

66d95378d3ece8b32afeb1c77d305397bd9a815e

[ "MIT" ]

1

2019-03-11T08:56:09.000Z

"""Tests for the QLearner strategies.""" import random import axelrod from axelrod import simulate_play, Game from .test_player import TestPlayer, test_responses C, D = axelrod.Actions.C, axelrod.Actions.D class TestRiskyQLearner(TestPlayer): name = 'Risky QLearner' player = axelrod.RiskyQLearner expected_classifier = { 'memory_depth': float('inf'), 'stochastic': True, 'makes_use_of': set(["game"]), 'long_run_time': False, 'inspects_source': False, 'manipulates_source': False, 'manipulates_state': False } def test_payoff_matrix(self): (R, P, S, T) = Game().RPST() payoff_matrix = {C: {C: R, D: S}, D: {C: T, D: P}} p1 = self.player() self.assertEqual(p1.payoff_matrix, payoff_matrix) def test_qs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.RiskyQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.Qs, {'': {C: 0, D: 0.9}, '0.0': {C: 0, D: 0}}) simulate_play(p1, p2) self.assertEqual(p1.Qs, {'': {C: 0, D: 0.9}, '0.0': {C: 2.7, D: 0}, 'C1.0': {C: 0, D: 0}}) def test_vs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.RiskyQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.Vs, {'': 0.9, '0.0': 0}) simulate_play(p1, p2) self.assertEqual(p1.Vs,{'': 0.9, '0.0': 2.7, 'C1.0': 0}) def test_prev_state_updates(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.RiskyQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.prev_state, '0.0') simulate_play(p1, p2) self.assertEqual(p1.prev_state, 'C1.0') def test_strategy(self): """Tests that it chooses the best strategy.""" random.seed(5) p1 = axelrod.RiskyQLearner() p1.state = 'CCDC' p1.Qs = {'': {C: 0, D: 0}, 'CCDC': {C: 2, D: 6}} p2 = axelrod.Cooperator() test_responses(self, p1, p2, [C, D, C, C, D, C, C]) def test_reset_method(self): """Test the reset method.""" P1 = axelrod.RiskyQLearner() P1.Qs = {'': {C: 0, D: -0.9}, '0.0': {C: 0, D: 0}} P1.Vs = {'': 0, '0.0': 0} P1.history = [C, D, D, D] P1.prev_state = C P1.reset() self.assertEqual(P1.prev_state, '') self.assertEqual(P1.Vs, {'': 0}) self.assertEqual(P1.Qs, {'': {C: 0, D: 0}}) class TestArrogantQLearner(TestPlayer): name = 'Arrogant QLearner' player = axelrod.ArrogantQLearner expected_classifier = { 'memory_depth': float('inf'), # Long memory 'stochastic': True, 'makes_use_of': set(["game"]), 'long_run_time': False, 'inspects_source': False, 'manipulates_source': False, 'manipulates_state': False } def test_qs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.ArrogantQLearner() p2 = axelrod.Cooperator() play_1, play_2 = simulate_play(p1, p2) self.assertEqual(p1.Qs, {'': {C: 0, D: 0.9}, '0.0': {C: 0, D: 0}}) simulate_play(p1, p2) self.assertEqual(p1.Qs,{'': {C: 0, D: 0.9}, '0.0': {C: 2.7, D: 0}, 'C1.0': {C: 0, D: 0}}) def test_vs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.ArrogantQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.Vs, {'': 0.9, '0.0': 0}) simulate_play(p1, p2) self.assertEqual(p1.Vs,{'': 0.9, '0.0': 2.7, 'C1.0': 0}) def test_prev_state_updates(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.ArrogantQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.prev_state, '0.0') simulate_play(p1, p2) self.assertEqual(p1.prev_state, 'C1.0') def test_strategy(self): """Tests that it chooses the best strategy.""" random.seed(9) p1 = axelrod.ArrogantQLearner() p1.state = 'CCDC' p1.Qs = {'': {C: 0, D: 0}, 'CCDC': {C: 2, D: 6}} p2 = axelrod.Cooperator() test_responses(self, p1, p2, [C, C, C, C, C, C, C]) def test_reset_method(self): """Tests the reset method.""" P1 = axelrod.ArrogantQLearner() P1.Qs = {'': {C: 0, D: -0.9}, '0.0': {C: 0, D: 0}} P1.Vs = {'': 0, '0.0': 0} P1.history = [C, D, D, D] P1.prev_state = C P1.reset() self.assertEqual(P1.prev_state, '') self.assertEqual(P1.Vs, {'':0}) self.assertEqual(P1.Qs, {'':{C:0, D:0}}) class TestHesitantQLearner(TestPlayer): name = 'Hesitant QLearner' player = axelrod.HesitantQLearner expected_classifier = { 'memory_depth': float('inf'), # Long memory 'stochastic': True, 'makes_use_of': set(["game"]), 'long_run_time': False, 'inspects_source': False, 'manipulates_source': False, 'manipulates_state': False } def test_qs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.HesitantQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.Qs, {'': {C: 0, D: 0.1}, '0.0': {C: 0, D: 0}}) simulate_play(p1, p2) self.assertEqual(p1.Qs,{'': {C: 0, D: 0.1}, '0.0': {C: 0.30000000000000004, D: 0}, 'C1.0': {C: 0, D: 0}}) def test_vs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.HesitantQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.Vs, {'': 0.1, '0.0': 0}) simulate_play(p1, p2) self.assertEqual(p1.Vs,{'': 0.1, '0.0': 0.30000000000000004, 'C1.0': 0}) def test_prev_state_updates(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.HesitantQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.prev_state, '0.0') simulate_play(p1, p2) self.assertEqual(p1.prev_state, 'C1.0') def test_strategy(self): """Tests that it chooses the best strategy.""" random.seed(9) p1 = axelrod.HesitantQLearner() p1.state = 'CCDC' p1.Qs = {'': {C: 0, D: 0}, 'CCDC': {C: 2, D: 6}} p2 = axelrod.Cooperator() test_responses(self, p1, p2, [C, C, C, C, C, C, C]) def test_reset_method(self): """Tests the reset method.""" P1 = axelrod.HesitantQLearner() P1.Qs = {'': {C: 0, D: -0.9}, '0.0': {C: 0, D: 0}} P1.Vs = {'': 0, '0.0': 0} P1.history = [C, D, D, D] P1.prev_state = C P1.reset() self.assertEqual(P1.prev_state, '') self.assertEqual(P1.Vs, {'': 0}) self.assertEqual(P1.Qs, {'': {C: 0, D: 0}}) class TestCautiousQLearner(TestPlayer): name = 'Cautious QLearner' player = axelrod.CautiousQLearner expected_classifier = { 'memory_depth': float('inf'), # Long memory 'stochastic': True, 'makes_use_of': set(["game"]), 'long_run_time': False, 'inspects_source': False, 'manipulates_source': False, 'manipulates_state': False } def test_qs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.CautiousQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.Qs, {'': {C: 0, D: 0.1}, '0.0': {C: 0, D: 0}}) simulate_play(p1, p2) self.assertEqual(p1.Qs,{'': {C: 0, D: 0.1}, '0.0': {C: 0.30000000000000004, D: 0}, 'C1.0': {C: 0, D: 0.0}}) def test_vs_update(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.CautiousQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.Vs, {'': 0.1, '0.0': 0}) simulate_play(p1, p2) self.assertEqual(p1.Vs,{'': 0.1, '0.0': 0.30000000000000004, 'C1.0': 0}) def test_prev_state_updates(self): """Test that the q and v values update.""" random.seed(5) p1 = axelrod.CautiousQLearner() p2 = axelrod.Cooperator() simulate_play(p1, p2) self.assertEqual(p1.prev_state, '0.0') simulate_play(p1, p2) self.assertEqual(p1.prev_state, 'C1.0') def test_strategy(self): """Tests that it chooses the best strategy.""" random.seed(9) p1 = axelrod.CautiousQLearner() p1.state = 'CCDC' p1.Qs = {'': {C: 0, D: 0}, 'CCDC': {C: 2, D: 6}} p2 = axelrod.Cooperator() test_responses(self, p1, p2, [C, C, C, C, C, C, C]) def test_reset_method(self): """Tests the reset method.""" P1 = axelrod.CautiousQLearner() P1.Qs = {'': {C: 0, D: -0.9}, '0.0': {C: 0, D: 0}} P1.Vs = {'': 0, '0.0': 0} P1.history = [C, D, D, D] P1.prev_state = C P1.reset() self.assertEqual(P1.prev_state, '') self.assertEqual(P1.Vs, {'': 0}) self.assertEqual(P1.Qs, {'': {C: 0, D: 0}})

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Python

sketch2image/log_wgan/models_crn_gan_enc_stack_gru_small.py

xuhuaren/GoogleAIWinterCamp-img2poem

4bb697b46f7ffa50dd45939acc9973632a3b84f8

[ "Apache-2.0" ]

1

2019-01-17T11:02:40.000Z

sketch2image/log_wgan/models_crn_gan_enc_stack_gru_small.py

xuhuaren/GoogleAIWinterCamp-img2poem

4bb697b46f7ffa50dd45939acc9973632a3b84f8

[ "Apache-2.0" ]

null

sketch2image/log_wgan/models_crn_gan_enc_stack_gru_small.py

xuhuaren/GoogleAIWinterCamp-img2poem

4bb697b46f7ffa50dd45939acc9973632a3b84f8

[ "Apache-2.0" ]

null

import functools import numpy as np import tensorflow as tf import tensorflow.contrib.layers as ly from tensorflow.python.framework import ops from resnet_rnn import resnet_block, resnet_deconv_block, resnet_conv, resnet_deconv, upsample_conv, mean_pool, unrolled_lstm_conv, unrolled_lstm_deconv, unrolled_gru_conv, unrolled_gru_deconv print('small') USE_BOTTLENECK = False SIZE = 64 NUM_BLOCKS = 1 CRAMER = False def one_hot_to_dense(labels): # Assume on value is 1 batch_size = int(labels.get_shape()[0]) return tf.reshape(tf.where(tf.equal(labels, 1))[:, 1], (batch_size,)) def batchnorm(inputs, data_format=None, activation_fn=None, labels=None, n_labels=None): """conditional batchnorm (dumoulin et al 2016) for BCHW conv filtermaps""" if data_format != 'NCHW': raise Exception('unsupported') mean, var = tf.nn.moments(inputs, (0, 2, 3), keep_dims=True) shape = mean.get_shape().as_list() # shape is [1,n,1,1] offset_m = tf.get_variable('offset', initializer=np.zeros([n_labels, shape[1]], dtype='float32')) scale_m = tf.get_variable('scale', initializer=np.ones([n_labels, shape[1]], dtype='float32')) offset = tf.nn.embedding_lookup(offset_m, labels) scale = tf.nn.embedding_lookup(scale_m, labels) result = tf.nn.batch_normalization(inputs, mean, var, offset[:, :, None, None], scale[:, :, None, None], 1e-5) return result def lrelu(x, leak=0.3, name="lrelu"): with tf.variable_scope(name): return tf.maximum(leak * x, x) def prelu(x, name="prelu"): with tf.variable_scope(name): leak = tf.get_variable("param", shape=None, initializer=0.2, regularizer=None, trainable=True, caching_device=None) return tf.maximum(leak * x, x) def miu_relu(x, miu=0.7, name="miu_relu"): with tf.variable_scope(name): return (x + tf.sqrt((1 - miu) ** 2 + x ** 2)) / 2. def p_miu_relu(x, name="p_miu_relu"): with tf.variable_scope(name): miu = tf.get_variable("param_miu", shape=None, initializer=0.7, regularizer=None, trainable=True, caching_device=None) return (x + tf.sqrt((1 - miu) ** 2 + x ** 2)) / 2. def matsushita_entropy(x, name="matsushita_entropy"): with tf.variable_scope(name): return (1 + x / tf.sqrt(1 + x ** 2)) / 2. def image_encoder_s1_gru(x, num_classes, reuse=False, data_format='NCHW', labels=None, scope_name=None): print("CONV_GRU") assert data_format == 'NCHW' size = SIZE num_blocks = NUM_BLOCKS resize_func = tf.image.resize_bilinear if normalizer_params_e is not None and normalizer_fn_e != ly.batch_norm and normalizer_fn_e != ly.layer_norm: normalizer_params_e['labels'] = labels normalizer_params_e['n_labels'] = num_classes if data_format == 'NCHW': resized_x = [] resized_ = x resized_x.append(resized_) for i in range(4): resized_ = mean_pool(resized_, data_format=data_format) resized_x.append(resized_) resized_x = resized_x[::-1] else: raise NotImplementedError output_list = [] # with tf.variable_scope(scope_name) as scope: # if reuse: # scope.reuse_variables() x_list = resized_x h0 = ly.conv2d(x_list[-1], size * 1, kernel_size=7, stride=2, data_format=data_format, activation_fn=activation_fn_e, normalizer_fn=normalizer_fn_e, normalizer_params=normalizer_params_e, weights_initializer=weight_initializer) # Initial memory state hidden_state_shape = h0.get_shape().as_list() batch_size = hidden_state_shape[0] hidden_state_shape[0] = 1 hts_0 = [h0] for i in range(1, num_blocks): h0 = tf.tile(tf.get_variable("initial_hidden_state_%d" % i, shape=hidden_state_shape, dtype=tf.float32, initializer=tf.zeros_initializer()), [batch_size, 1, 1, 1]) hts_0.append(h0) hts_1 = unrolled_gru_conv(x_list[-2], hts_0, size * 1, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=True, last_unit=False, activation_fn=activation_fn_e, normalizer_fn=normalizer_fn_e, normalizer_params=normalizer_params_e, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=1) output_list.append(hts_1[-1]) hts_2 = unrolled_gru_conv(x_list[-3], hts_1, size * 2, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_e, normalizer_fn=normalizer_fn_e, normalizer_params=normalizer_params_e, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=2) output_list.append(hts_2[-1]) hts_3 = unrolled_gru_conv(x_list[-4], hts_2, size * 4, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_e, normalizer_fn=normalizer_fn_e, normalizer_params=normalizer_params_e, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=3) output_list.append(hts_3[-1]) hts_4 = unrolled_gru_conv(x_list[-5], hts_3, size * 8, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=True, activation_fn=activation_fn_e, normalizer_fn=normalizer_fn_e, normalizer_params=normalizer_params_e, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=4) output_list.append(hts_4[-1]) return output_list # GRU def generator_l_s1_skip(z, output_channel, num_classes, reuse=False, data_format='NCHW', labels=None, scope_name=None): print("DECONV_GRU") size = SIZE num_blocks = NUM_BLOCKS input_dims = z.get_shape().as_list() resize_func = tf.image.resize_area if data_format == 'NCHW': height = input_dims[2] width = input_dims[3] z_orig = tf.identity(z) z = tf.transpose(z, [0, 2, 3, 1]) resized_z = [ tf.transpose(resize_func(z, [int(height / 32), int(width / 32)]), [0, 3, 1, 2]), tf.transpose(resize_func(z, [int(height / 16), int(width / 16)]), [0, 3, 1, 2]), tf.transpose(resize_func(z, [int(height / 8), int(width / 8)]), [0, 3, 1, 2]), tf.transpose(resize_func(z, [int(height / 4), int(width / 4)]), [0, 3, 1, 2]), tf.transpose(resize_func(z, [int(height / 2), int(width / 2)]), [0, 3, 1, 2]), ] z = z_orig else: height = input_dims[1] width = input_dims[2] resized_z = [ resize_func(z, [int(height / 32), int(width / 32)]), resize_func(z, [int(height / 16), int(width / 16)]), resize_func(z, [int(height / 8), int(width / 8)]), resize_func(z, [int(height / 4), int(width / 4)]), resize_func(z, [int(height / 2), int(width / 2)]), ] if data_format == 'NCHW': concat_axis = 1 else: concat_axis = 3 output_list = [] if normalizer_params_g is not None and normalizer_fn_g != ly.batch_norm and normalizer_fn_g != ly.layer_norm: normalizer_params_g['labels'] = labels normalizer_params_g['n_labels'] = num_classes with tf.variable_scope(scope_name) as scope: if reuse: scope.reuse_variables() z_encoded = image_encoder_s1_gru(z, num_classes=num_classes, reuse=reuse, data_format=data_format, labels=labels, scope_name=scope_name) input_e_dims = z_encoded[-1].get_shape().as_list() input_e_dims[concat_axis] = int(input_e_dims[concat_axis] / 2.) noise = tf.random_normal(shape=(input_e_dims[0], 256), dtype=tf.float32) noise = ly.fully_connected(noise, int(np.prod(input_e_dims[1:])), activation_fn=activation_fn_g) noise = tf.reshape(noise, shape=input_e_dims) # Initial memory state hidden_state_shape = z_encoded[-1].get_shape().as_list() batch_size = hidden_state_shape[0] hidden_state_shape[0] = 1 hts_0 = [z_encoded[-1]] for i in range(1, num_blocks): h0 = tf.tile(tf.get_variable("initial_hidden_state_%d" % i, shape=hidden_state_shape, dtype=tf.float32, initializer=tf.random_normal_initializer()), [batch_size, 1, 1, 1]) hts_0.append(h0) input_0 = tf.concat([resized_z[0], noise], axis=concat_axis) hts_1 = unrolled_gru_deconv(input_0, hts_0, size * 6, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=True, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=0) # output_list.append(ly.conv2d(hts_1[-1], 3, 3, stride=1, data_format=data_format, # normalizer_fn=None, activation_fn=tf.nn.tanh, # weights_initializer=weight_initializer)) input_1 = tf.concat([resized_z[1], z_encoded[-2]], axis=concat_axis) hts_2 = unrolled_gru_deconv(input_1, hts_1, size * 4, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=2) # output_list.append(ly.conv2d(hts_2[-1], 3, 3, stride=1, data_format=data_format, # normalizer_fn=None, activation_fn=tf.nn.tanh, # weights_initializer=weight_initializer)) input_2 = tf.concat([resized_z[2], z_encoded[-3]], axis=concat_axis) hts_3 = unrolled_gru_deconv(input_2, hts_2, size * 2, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=4) # output_list.append(ly.conv2d(hts_3[-1], 3, 3, stride=1, data_format=data_format, # normalizer_fn=None, activation_fn=tf.nn.tanh, # weights_initializer=weight_initializer)) input_3 = tf.concat([resized_z[3], z_encoded[-4]], axis=concat_axis) hts_4 = unrolled_gru_deconv(input_3, hts_3, size * 2, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=6) # output_list.append(ly.conv2d(hts_4[-1], 3, 3, stride=1, data_format=data_format, # normalizer_fn=None, activation_fn=tf.nn.tanh, # weights_initializer=weight_initializer)) hts_5 = unrolled_gru_deconv(resized_z[4], hts_4, size * 1, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=True, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=8) output_list.append(ly.conv2d(hts_5[-1], 3, 7, stride=1, data_format=data_format, normalizer_fn=None, activation_fn=tf.nn.tanh, weights_initializer=weight_initializer)) # out = ly.conv2d(train, output_channel, 7, stride=1, data_format=data_format, # activation_fn=tf.nn.tanh, weights_initializer=weight_initializer) assert output_list[-1].get_shape().as_list()[2] == 64 return output_list # GRU def generator_l_s2(z, extra, output_channel, num_classes, reuse=False, data_format='NCHW', labels=None, scope_name=None): print("DECONV_GRU") size = SIZE num_blocks = NUM_BLOCKS if type(z) is list: z = z[-1] input_dims = extra.get_shape().as_list() resize_func = tf.image.resize_area if data_format == 'NCHW': height = input_dims[2] width = input_dims[3] extra_orig = tf.identity(extra) extra = tf.transpose(extra, [0, 2, 3, 1]) resized_extra = [ tf.transpose(resize_func(extra, [int(height / 32), int(width / 32)]), [0, 3, 1, 2]), tf.transpose(resize_func(extra, [int(height / 16), int(width / 16)]), [0, 3, 1, 2]), # tf.transpose(resize_func(extra, [int(height / 8), int(width / 8)]), [0, 3, 1, 2]), tf.transpose(resize_func(extra, [int(height / 8), int(width / 8)]), [0, 3, 1, 2]), tf.transpose(resize_func(extra, [int(height / 4), int(width / 4)]), [0, 3, 1, 2]), tf.transpose(resize_func(extra, [int(height / 2), int(width / 2)]), [0, 3, 1, 2]), ] extra = extra_orig else: raise NotImplementedError height = input_dims[1] width = input_dims[2] resized_extra = [ # resize_func(extra, [int(height / 32), int(width / 32)]), # resize_func(extra, [int(height / 16), int(width / 16)]), resize_func(extra, [int(height / 8), int(width / 8)]), resize_func(extra, [int(height / 4), int(width / 4)]), resize_func(extra, [int(height / 2), int(width / 2)]), ] if data_format == 'NCHW': concat_axis = 1 else: concat_axis = 3 output_list = [] if normalizer_params_g is not None and normalizer_fn_g != ly.batch_norm and normalizer_fn_g != ly.layer_norm: normalizer_params_g['labels'] = labels normalizer_params_g['n_labels'] = num_classes with tf.variable_scope(scope_name) as scope: if reuse: scope.reuse_variables() z_encoded = image_encoder_s2(z, num_classes=num_classes, reuse=reuse, data_format=data_format, labels=labels, scope_name=scope_name) # Initial memory state hidden_state_shape = z_encoded.get_shape().as_list() batch_size = hidden_state_shape[0] hidden_state_shape[0] = 1 hts_0 = [z_encoded] for i in range(1, num_blocks): h0 = tf.tile(tf.get_variable("initial_hidden_state_%d" % i, shape=hidden_state_shape, dtype=tf.float32, initializer=tf.random_normal_initializer()), [batch_size, 1, 1, 1]) hts_0.append(h0) hts_1 = unrolled_gru_deconv(resized_extra[0], hts_0, size * 8, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=True, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=0) # hts_1 = unrolled_gru_deconv(resized_extra[0], hts_1, # size * 8, stride=1, data_format=data_format, num_blocks=num_blocks, # first_unit=False, last_unit=False, # activation_fn=activation_fn_g, # normalizer_fn=normalizer_fn_g, # normalizer_params=normalizer_params_g, # weights_initializer=weight_initializer, # use_bottleneck=USE_BOTTLENECK, # unit_num=1) hts_1 = unrolled_gru_deconv(resized_extra[1], hts_1, size * 8, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=2) hts_2 = unrolled_gru_deconv(resized_extra[2], hts_1, size * 4, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=11) hts_3 = unrolled_gru_deconv(resized_extra[3], hts_2, size * 2, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=12) hts_4 = unrolled_gru_deconv(resized_extra[4], hts_3, size * 1, stride=2, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=True, activation_fn=activation_fn_g, normalizer_fn=normalizer_fn_g, normalizer_params=normalizer_params_g, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=13) output_list.append(ly.conv2d(hts_4[-1], 3, 7, stride=1, data_format=data_format, normalizer_fn=None, activation_fn=tf.nn.tanh, weights_initializer=weight_initializer)) print("G_s2 out: %d" % output_list[-1].get_shape().as_list()[2]) return output_list # GRU def critic_l_multiple_s1(x, num_classes, reuse=False, data_format='NCHW', scope_name=None, cramer=CRAMER): print("CONV_GRU") assert data_format == 'NCHW' size = SIZE num_blocks = NUM_BLOCKS resize_func = tf.image.resize_bilinear if data_format == 'NCHW': concat_axis = 1 else: concat_axis = 3 if type(x) is list: x = x[-1] # if cond is not None: # x = tf.concat([x, cond], axis=concat_axis) if data_format == 'NCHW': resized_x = [] resized_ = x resized_x.append(resized_) for i in range(4): resized_ = mean_pool(resized_, data_format=data_format) resized_x.append(resized_) resized_x = resized_x[::-1] else: raise NotImplementedError output_list = [] output_dim = 256 if cramer else 1 with tf.variable_scope(scope_name) as scope: if reuse: scope.reuse_variables() x_list = resized_x h0 = ly.conv2d(x_list[-1], 6, kernel_size=7, stride=1, data_format=data_format, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer) # Initial memory state hidden_state_shape = h0.get_shape().as_list() batch_size = hidden_state_shape[0] hidden_state_shape[0] = 1 hts_0 = [h0] for i in range(1, num_blocks): h0 = tf.tile(tf.get_variable("initial_hidden_state_%d" % i, shape=hidden_state_shape, dtype=tf.float32, initializer=tf.zeros_initializer()), [batch_size, 1, 1, 1]) hts_0.append(h0) hts_1 = unrolled_gru_conv(x_list[-1], hts_0, size * 2, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=True, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=1) hts_2 = unrolled_gru_conv(x_list[-2], hts_1, size * 4, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=2) hts_3 = unrolled_gru_conv(x_list[-3], hts_2, size * 8, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=3) hts_4 = unrolled_gru_conv(x_list[-4], hts_3, size * 16, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=True, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=4) img = hts_4[-1] # discriminator end disc = ly.conv2d(img, output_dim, kernel_size=1, stride=1, data_format=data_format, activation_fn=None, normalizer_fn=None, weights_initializer=weight_initializer) # classification end img = tf.reduce_mean(img, axis=(2, 3) if data_format == 'NCHW' else (1, 2)) logits = ly.fully_connected(img, num_classes, activation_fn=None, normalizer_fn=None) return disc, logits # GRU def critic_l_multiple_s2(x, num_classes, reuse=False, data_format='NCHW', scope_name=None, cramer=CRAMER): print("CONV_GRU") assert data_format == 'NCHW' size = SIZE num_blocks = NUM_BLOCKS resize_func = tf.image.resize_bilinear if data_format == 'NCHW': concat_axis = 1 else: concat_axis = 3 if type(x) is list: x = x[-1] # if cond is not None: # x = tf.concat([x, cond], axis=concat_axis) if data_format == 'NCHW': resized_x = [] resized_ = x resized_x.append(resized_) resized_ = mean_pool(resized_, data_format=data_format) for i in range(6): resized_ = mean_pool(resized_, data_format=data_format) resized_x.append(resized_) resized_x = resized_x[::-1] else: raise NotImplementedError output_list = [] output_dim = 256 if cramer else 1 with tf.variable_scope(scope_name) as scope: if reuse: scope.reuse_variables() x_list = resized_x h0 = ly.conv2d(x_list[-1], 6, kernel_size=7, stride=2, data_format=data_format, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer) # Initial memory state hidden_state_shape = h0.get_shape().as_list() batch_size = hidden_state_shape[0] hidden_state_shape[0] = 1 hts_0 = [h0] for i in range(1, num_blocks): h0 = tf.tile(tf.get_variable("initial_hidden_state_%d" % i, shape=hidden_state_shape, dtype=tf.float32, initializer=tf.zeros_initializer()), [batch_size, 1, 1, 1]) hts_0.append(h0) inp_0 = ly.conv2d(x_list[-1], 6, kernel_size=7, stride=2, data_format=data_format, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer) hts_1 = unrolled_gru_conv(inp_0, hts_0, size * 1, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=True, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=1) hts_2 = unrolled_gru_conv(x_list[-2], hts_1, size * 2, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=2) hts_3 = unrolled_gru_conv(x_list[-3], hts_2, size * 4, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=3) hts_4 = unrolled_gru_conv(x_list[-4], hts_3, size * 8, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=4) hts_5 = unrolled_gru_conv(x_list[-5], hts_4, size * 16, stride=2, dilate_rate=1, data_format=data_format, num_blocks=num_blocks, first_unit=False, last_unit=False, activation_fn=activation_fn_d, normalizer_fn=normalizer_fn_d, normalizer_params=normalizer_params_d, weights_initializer=weight_initializer, use_bottleneck=USE_BOTTLENECK, unit_num=5) # hts_6 = unrolled_gru_conv(x_list[-6], hts_5, # size * 16, stride=2, dilate_rate=1, # data_format=data_format, num_blocks=num_blocks, # first_unit=False, last_unit=True, # activation_fn=activation_fn_d, # normalizer_fn=normalizer_fn_d, # normalizer_params=normalizer_params_d, # weights_initializer=weight_initializer, # use_bottleneck=USE_BOTTLENECK, # unit_num=6) img = hts_5[-1] # img = tf.concat(output_list, axis=concat_axis) # img = tf.add_n( # [img[:, :, ::2, ::2], img[:, :, 1::2, ::2], img[:, :, ::2, 1::2], img[:, :, 1::2, 1::2]]) / 4. # discriminator end disc = ly.conv2d(img, output_dim, kernel_size=1, stride=1, data_format=data_format, activation_fn=None, normalizer_fn=None, weights_initializer=weight_initializer) # classification end img = tf.reduce_mean(img, axis=(2, 3) if data_format == 'NCHW' else (1, 2)) logits = ly.fully_connected(img, num_classes, activation_fn=None, normalizer_fn=None) return disc, logits weight_initializer = tf.random_normal_initializer(0, 0.02) # weight_initializer = ly.xavier_initializer_conv2d() def set_param(data_format='NCHW'): global model_data_format, normalizer_fn_e, normalizer_fn_g, normalizer_fn_d, normalizer_fn_ce,\ normalizer_params_e, normalizer_params_g, normalizer_params_d, normalizer_params_ce model_data_format = data_format # normalizer_fn_e = ly.batch_norm # normalizer_params_e = {'fused': True, 'data_format': model_data_format, # 'is_training': True} normalizer_fn_e = batchnorm normalizer_params_e = {'data_format': model_data_format} normalizer_fn_g = batchnorm normalizer_params_g = {'data_format': model_data_format} # normalizer_fn_e = None # normalizer_params_e = None # normalizer_fn_g = None # normalizer_params_g = None # normalizer_fn_g = ly.layer_norm # normalizer_params_g = None normalizer_fn_d = None normalizer_params_d = None normalizer_fn_ce = None normalizer_params_ce = None model_data_format = None normalizer_fn_e = ly.batch_norm normalizer_params_e = {'fused': True, 'data_format': model_data_format, 'is_training': True} # normalizer_params_e = {'fused': True, 'data_format': model_data_format, # 'is_training': True, 'decay': 0.95} normalizer_fn_g = ly.batch_norm normalizer_params_g = {'fused': True, 'data_format': model_data_format, 'is_training': True} # normalizer_params_g = {'fused': True, 'data_format': model_data_format, # 'is_training': True, 'decay': 0.95} normalizer_fn_d = None normalizer_params_d = None normalizer_fn_ce = None normalizer_params_ce = None activation_fn_e = miu_relu activation_fn_g = miu_relu activation_fn_d = prelu print('prelu') activation_fn_d_last = None # activation_fn_d_last = None # activation_fn_ce = prelu generator_s1 = generator_l_s1_skip generator_s2 = generator_l_s2 critic_s1 = critic_l_multiple_s1 critic_s2 = critic_l_multiple_s2 # critic_e = critic_e_fc

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Python

referencesrv/tests/unittests/stubdata/dataXML.py

romanchyla/reference_service

f192c4627750258d25776617d8acd09fe0a8cead

[ "MIT" ]

null

referencesrv/tests/unittests/stubdata/dataXML.py

romanchyla/reference_service

f192c4627750258d25776617d8acd09fe0a8cead

[ "MIT" ]

null

referencesrv/tests/unittests/stubdata/dataXML.py

romanchyla/reference_service

f192c4627750258d25776617d8acd09fe0a8cead

[ "MIT" ]

null

train_1 = [[[('AUTHOR_FIRST_NAME', u'J.D.'), ('AUTHOR_LAST_NAME', u'Adams'), ('AUTHOR_FIRST_NAME', u'T.L.'), ('AUTHOR_LAST_NAME', u'Herter'), ('AUTHOR_FIRST_NAME', u'G.E.'), ('AUTHOR_LAST_NAME', u'Gull'), ('AUTHOR_FIRST_NAME', u'J.'), ('AUTHOR_LAST_NAME', u'Shoenwald'), ('AUTHOR_FIRST_NAME', u'C.P.'), ('AUTHOR_LAST_NAME', u'Henderson'), ('AUTHOR_FIRST_NAME', u'L.D.'), ('AUTHOR_LAST_NAME', u'Keller'), ('AUTHOR_FIRST_NAME', u'J.M.'), ('AUTHOR_LAST_NAME', u'DeBuizer'), ('AUTHOR_FIRST_NAME', u'G.J.'), ('AUTHOR_LAST_NAME', u'Stacey'), ('AUTHOR_FIRST_NAME', u'T.'), ('AUTHOR_LAST_NAME', u'Nikola'), ('TITLE', u'FORCAST:'), ('TITLE', u'A'), ('TITLE', u'first'), ('TITLE', u'light'), ('TITLE', u'facility'), ('TITLE', u'instrument'), ('TITLE', u'for'), ('TITLE', u'SOFIA:'), ('JOURNAL', u'Proc.'), ('JOURNAL', u'SPIE'), ('VOLUME', u'7735'), ('YEAR', u'2010'), ('PAGE', u'eid7735 1U')], [('AUTHOR_FIRST_NAME', u'M.'), ('AUTHOR_LAST_NAME', u'Bertero'), ('AUTHOR_FIRST_NAME', u'P.'), ('AUTHOR_LAST_NAME', u'Boccacci'), ('TITLE', u'Introduction'), ('TITLE', u'to'), ('TITLE', u'Inverse'), ('TITLE', u'Problems'), ('TITLE', u'in'), ('TITLE', u'Imaging:'), ('PUBLISHER', u'CRC'), ('PUBLISHER', u'Press'), ('YEAR', u'1998'), ('PAGE', u'352')], [('AUTHOR_FIRST_NAME', u'B.J.'), ('AUTHOR_LAST_NAME', u'Conrath'), ('AUTHOR_FIRST_NAME', u'P.J.'), ('AUTHOR_LAST_NAME', u'Gierasch'), ('AUTHOR_FIRST_NAME', u'E.A.'), ('AUTHOR_LAST_NAME', u'Ustinov'), ('TITLE', u'Thermal'), ('TITLE', u'structure'), ('TITLE', u'and'), ('TITLE', u'para'), ('TITLE', u'hydrogen'), ('TITLE', u'fraction'), ('TITLE', u'on'), ('TITLE', u'the'), ('TITLE', u'outer'), ('TITLE', u'planets'), ('TITLE', u'from'), ('TITLE', u'Voyager'), ('TITLE', u'IRIS'), ('TITLE', u'measurements:'), ('JOURNAL', u'Icarus'), ('VOLUME', u'135'), ('YEAR', u'1998'), ('PAGE', u'501-517')], [('AUTHOR_FIRST_NAME', u'B.J.'), ('AUTHOR_LAST_NAME', u'Conrath'), ('AUTHOR_FIRST_NAME', u'P.J.'), ('AUTHOR_LAST_NAME', u'Gierasch'), ('TITLE', u'Global'), ('TITLE', 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Int. J. Eng. Sci. 34, 227\u2013241 (1996)'), ('REFSTR', "{u'bibunstructured': u'Teymur, M.: Small but finite amplitude waves in a two-layered incompressible elastic medium. Int. J. Eng. Sci. 34, 227\\u2013241 (1996)', u'bibarticle': {u'bibauthorname': {u'familyname': u'Teymur', u'initials': u'M'}, u'occurrence': [{u'handle': u'1367605', u'@type': u'AMSID'}, {u'handle': u'10.1016/0020-7225(95)00084-4', u'@type': u'DOI'}], u'journaltitle': u'Int. J. Eng. Sci.', u'volumeid': u'34', u'firstpage': u'227', u'lastpage': u'241', u'year': u'1996', u'articletitle': {u'#text': u'Small but finite amplitude waves in a two-layered incompressible elastic medium', u'@language': u'En'}}, u'citationnumber': u'33.', u'@id': u'CR33'}")], [('AUTHOR_FIRST_NAME', u'M'), ('AUTHOR_LAST_NAME', u'Teymur'), ('AUTHOR_FIRST_NAME', u'A'), ('AUTHOR_LAST_NAME', u'Demirci'), ('AUTHOR_FIRST_NAME', u'S'), ('AUTHOR_LAST_NAME', u'Ahmetolan'), ('TITLE', u'Propagation'), ('TITLE', u'of'), ('TITLE', u'surface'), ('TITLE', u'SH'), ('TITLE', u'waves'), ('TITLE', u'on'), ('TITLE', u'a'), ('TITLE', u'half'), ('TITLE', u'space'), ('TITLE', u'covered'), ('TITLE', u'by'), ('TITLE', u'a'), ('TITLE', u'nonlinear'), ('TITLE', u'thin'), ('TITLE', u'layer'), ('JOURNAL', u'Int.'), ('JOURNAL', u'J.'), ('JOURNAL', u'Eng.'), ('JOURNAL', u'Sci.'), ('VOLUME', u'85'), ('YEAR', u'2014'), ('PAGE', u'150'), ('REFPLAINTEXT', u'Teymur, M., Demirci, A., Ahmetolan, S.: Propagation of surface SH waves on a half space covered by a nonlinear thin layer. Int. J. Eng. Sci. 85, 150\u2013162 (2014)'), ('REFSTR', "{u'bibunstructured': u'Teymur, M., Demirci, A., Ahmetolan, S.: Propagation of surface SH waves on a half space covered by a nonlinear thin layer. Int. J. Eng. Sci. 85, 150\\u2013162 (2014)', u'bibarticle': {u'bibauthorname': [{u'familyname': u'Teymur', u'initials': u'M'}, {u'familyname': u'Demirci', u'initials': u'A'}, {u'familyname': u'Ahmetolan', u'initials': u'S'}], u'occurrence': {u'handle': u'10.1016/j.ijengsci.2014.08.005', u'@type': u'DOI'}, u'journaltitle': u'Int. J. Eng. Sci.', u'volumeid': u'85', u'firstpage': u'150', u'lastpage': u'162', u'year': u'2014', u'articletitle': {u'#text': u'Propagation of surface SH waves on a half space covered by a nonlinear thin layer', u'@language': u'En'}}, u'citationnumber': u'34.', u'@id': u'CR34'}")], [('AUTHOR_FIRST_NAME', u'M'), ('AUTHOR_LAST_NAME', u'Teymur'), ('AUTHOR_FIRST_NAME', u'H&Idot'), ('AUTHOR_LAST_NAME', u'Var'), ('AUTHOR_FIRST_NAME', u'E'), ('AUTHOR_LAST_NAME', u'Deliktas'), ('YEAR', u'2019'), ('PUBLISHER', u'Dynamical'), ('PUBLISHER', u'Processes'), ('PUBLISHER', u'in'), ('PUBLISHER', u'Generalized'), ('PUBLISHER', u'Continua'), ('PUBLISHER', u'and'), ('PUBLISHER', u'Structures'), ('REFPLAINTEXT', u'Teymur, M., Var, H&Idot., Deliktas, E.: Nonlinear modulation of surface SH waves in a double layered elastic half space. In: Altenbach, H., Belyaev, A., Eremeyev, V., Krivtsov, A., Porubov, A. (eds.) Dynamical Processes in Generalized Continua and Structures. Advanced Structured Materials, vol. 103. Springer, Cham (2019)'), ('REFSTR', "{u'bibunstructured': u'Teymur, M., Var, H&Idot., Deliktas, E.: Nonlinear modulation of surface SH waves in a double layered elastic half space. In: Altenbach, H., Belyaev, A., Eremeyev, V., Krivtsov, A., Porubov, A. (eds.) Dynamical Processes in Generalized Continua and Structures. Advanced Structured Materials, vol. 103. Springer, Cham (2019)', u'bibchapter': {u'eds': {u'seriestitle': {u'#text': u'Advanced Structured Materials', u'@language': u'En'}, u'publisherlocation': u'Cham', u'occurrence': {u'handle': u'10.1007/978-3-030-11665-1_27', u'@type': u'DOI'}, u'booktitle': u'Dynamical Processes in Generalized Continua and Structures', u'numberinseries': u'103', u'publishername': u'Springer'}, u'bibauthorname': [{u'familyname': u'Teymur', u'initials': u'M'}, {u'familyname': u'Var', u'initials': u'H&Idot'}, {u'familyname': u'Deliktas', u'initials': u'E'}], u'chaptertitle': {u'#text': u'Nonlinear modulation of surface SH waves in a double layered elastic half space', u'@language': u'En'}, u'bibeditorname': [{u'familyname': u'Altenbach', u'initials': u'H'}, {u'familyname': u'Belyaev', u'initials': u'A'}, {u'familyname': u'Eremeyev', u'initials': u'V'}, {u'familyname': u'Krivtsov', u'initials': u'A'}, {u'familyname': u'Porubov', u'initials': u'A'}], u'year': u'2019'}, u'citationnumber': u'35.', u'@id': u'CR35'}")], [('AUTHOR_FIRST_NAME', u'GB'), ('AUTHOR_LAST_NAME', u'Whitham'), ('YEAR', u'1974'), ('PUBLISHER', u'Linear'), ('PUBLISHER', u'and'), ('PUBLISHER', u'Nonlinear'), ('PUBLISHER', u'Waves'), ('REFPLAINTEXT', u'Whitham, G.B.: Linear and Nonlinear Waves. Wiley, New York (1974)'), ('REFSTR', "{u'bibunstructured': u'Whitham, G.B.: Linear and Nonlinear Waves. Wiley, New York (1974)', u'citationnumber': u'36.', u'@id': u'CR36', u'bibbook': {u'bibauthorname': {u'familyname': u'Whitham', u'initials': u'GB'}, u'publisherlocation': u'New York', u'occurrence': {u'handle': u'0373.76001', u'@type': u'ZLBID'}, u'booktitle': u'Linear and Nonlinear Waves', u'year': u'1974', u'publishername': u'Wiley'}}")], [('AUTHOR_FIRST_NAME', u'VE'), ('AUTHOR_LAST_NAME', u'Zakharov'), ('AUTHOR_FIRST_NAME', u'AB'), ('AUTHOR_LAST_NAME', u'Shabat'), ('TITLE', u'Interaction'), ('TITLE', u'between'), ('TITLE', u'solitons'), ('TITLE', u'in'), ('TITLE', u'a'), ('TITLE', u'stable'), ('TITLE', u'medium'), ('JOURNAL', u'Sov.'), ('JOURNAL', u'Phys.'), ('JOURNAL', u'JETP'), ('VOLUME', u'37'), ('YEAR', u'1973'), ('PAGE', u'823'), ('REFPLAINTEXT', u'Zakharov, V.E., Shabat, A.B.: Interaction between solitons in a stable medium. Sov. Phys. JETP 37, 823 (1973)'), ('REFSTR', "{u'bibunstructured': u'Zakharov, V.E., Shabat, A.B.: Interaction between solitons in a stable medium. Sov. Phys. JETP 37, 823 (1973)', u'bibarticle': {u'bibauthorname': [{u'familyname': u'Zakharov', u'initials': u'VE'}, {u'familyname': u'Shabat', u'initials': u'AB'}], u'journaltitle': u'Sov. Phys. JETP', u'volumeid': u'37', u'firstpage': u'823', u'year': u'1973', u'articletitle': {u'#text': u'Interaction between solitons in a stable medium', u'@language': u'En'}}, u'citationnumber': u'37.', u'@id': u'CR37'}")]]

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Python

stable_baselines3/sac_latent/__init__.py

NicholasCorrado/stable-baselines3

77793947335c6b14747c2c5179a7c05c93289ffd

[ "MIT" ]

null

stable_baselines3/sac_latent/__init__.py

NicholasCorrado/stable-baselines3

77793947335c6b14747c2c5179a7c05c93289ffd

[ "MIT" ]

null

stable_baselines3/sac_latent/__init__.py

NicholasCorrado/stable-baselines3

77793947335c6b14747c2c5179a7c05c93289ffd

[ "MIT" ]

null

from stable_baselines3.sac_latent.policies import MlpPolicy from stable_baselines3.sac_latent.sac_latent import SACLatent

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Python

tccli/services/cpdp/cpdp_client.py

ws0416/tencentcloud-cli

0a90fa77c8be1efa30b196a3eeb31b8be1f6a325

[ "Apache-2.0" ]

null

tccli/services/cpdp/cpdp_client.py

ws0416/tencentcloud-cli

0a90fa77c8be1efa30b196a3eeb31b8be1f6a325

[ "Apache-2.0" ]

null

tccli/services/cpdp/cpdp_client.py

ws0416/tencentcloud-cli

0a90fa77c8be1efa30b196a3eeb31b8be1f6a325

[ "Apache-2.0" ]

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# -*- coding: utf-8 -*- import os import json import tccli.options_define as OptionsDefine import tccli.format_output as FormatOutput from tccli import __version__ from tccli.utils import Utils from tccli.exceptions import ConfigurationError from tencentcloud.common import credential from tencentcloud.common.profile.http_profile import HttpProfile from tencentcloud.common.profile.client_profile import ClientProfile from tencentcloud.cpdp.v20190820 import cpdp_client as cpdp_client_v20190820 from tencentcloud.cpdp.v20190820 import models as models_v20190820 def doModifyAgentTaxPaymentInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ModifyAgentTaxPaymentInfoRequest() model.from_json_string(json.dumps(args)) rsp = client.ModifyAgentTaxPaymentInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doModifyMntMbrBindRelateAcctBankCode(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ModifyMntMbrBindRelateAcctBankCodeRequest() model.from_json_string(json.dumps(args)) rsp = client.ModifyMntMbrBindRelateAcctBankCode(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doWithdrawCashMembership(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.WithdrawCashMembershipRequest() model.from_json_string(json.dumps(args)) rsp = client.WithdrawCashMembership(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryBankTransactionDetails(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryBankTransactionDetailsRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryBankTransactionDetails(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryCommonTransferRecharge(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryCommonTransferRechargeRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryCommonTransferRecharge(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDownloadBill(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DownloadBillRequest() model.from_json_string(json.dumps(args)) rsp = client.DownloadBill(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryCustAcctIdBalance(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryCustAcctIdBalanceRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryCustAcctIdBalance(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryPayerInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryPayerInfoRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryPayerInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryTrade(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryTradeRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryTrade(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryTransferDetail(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryTransferDetailRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryTransferDetail(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQuerySingleTransactionStatus(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QuerySingleTransactionStatusRequest() model.from_json_string(json.dumps(args)) rsp = client.QuerySingleTransactionStatus(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doApplyApplicationMaterial(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ApplyApplicationMaterialRequest() model.from_json_string(json.dumps(args)) rsp = client.ApplyApplicationMaterial(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doModifyMerchant(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ModifyMerchantRequest() model.from_json_string(json.dumps(args)) rsp = client.ModifyMerchant(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateInvoiceV2(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateInvoiceV2Request() model.from_json_string(json.dumps(args)) rsp = client.CreateInvoiceV2(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryInvoice(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryInvoiceRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryInvoice(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryExchangeRate(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryExchangeRateRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryExchangeRate(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doUnbindRelateAcct(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.UnbindRelateAcctRequest() model.from_json_string(json.dumps(args)) rsp = client.UnbindRelateAcct(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doContractOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ContractOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.ContractOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateTransferBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateTransferBatchRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateTransferBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doUploadTaxPayment(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.UploadTaxPaymentRequest() model.from_json_string(json.dumps(args)) rsp = client.UploadTaxPayment(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryMemberBind(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryMemberBindRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryMemberBind(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeChargeDetail(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeChargeDetailRequest() model.from_json_string(json.dumps(args)) rsp = client.DescribeChargeDetail(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryMerchantBalance(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryMerchantBalanceRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryMerchantBalance(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDeleteAgentTaxPaymentInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DeleteAgentTaxPaymentInfoRequest() model.from_json_string(json.dumps(args)) rsp = client.DeleteAgentTaxPaymentInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateAgentTaxPaymentInfos(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateAgentTaxPaymentInfosRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateAgentTaxPaymentInfos(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDeleteAgentTaxPaymentInfos(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DeleteAgentTaxPaymentInfosRequest() model.from_json_string(json.dumps(args)) rsp = client.DeleteAgentTaxPaymentInfos(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreatePayMerchant(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreatePayMerchantRequest() model.from_json_string(json.dumps(args)) rsp = client.CreatePayMerchant(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRegisterBehavior(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RegisterBehaviorRequest() model.from_json_string(json.dumps(args)) rsp = client.RegisterBehavior(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRegisterBillSupportWithdraw(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RegisterBillSupportWithdrawRequest() model.from_json_string(json.dumps(args)) rsp = client.RegisterBillSupportWithdraw(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doUnifiedOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.UnifiedOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.UnifiedOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doUnBindAcct(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.UnBindAcctRequest() model.from_json_string(json.dumps(args)) rsp = client.UnBindAcct(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doConfirmOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ConfirmOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.ConfirmOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCheckAmount(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CheckAmountRequest() model.from_json_string(json.dumps(args)) rsp = client.CheckAmount(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryTransferResult(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryTransferResultRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryTransferResult(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryOutwardOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryOutwardOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryOutwardOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doMigrateOrderRefund(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.MigrateOrderRefundRequest() model.from_json_string(json.dumps(args)) rsp = client.MigrateOrderRefund(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryAcctInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryAcctInfoRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryAcctInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryBankWithdrawCashDetails(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryBankWithdrawCashDetailsRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryBankWithdrawCashDetails(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCheckAcct(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CheckAcctRequest() model.from_json_string(json.dumps(args)) rsp = client.CheckAcct(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryMerchantOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryMerchantOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryMerchantOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateRedInvoiceV2(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateRedInvoiceV2Request() model.from_json_string(json.dumps(args)) rsp = client.CreateRedInvoiceV2(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doSyncContractData(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.SyncContractDataRequest() model.from_json_string(json.dumps(args)) rsp = client.SyncContractData(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryAnchorContractInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryAnchorContractInfoRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryAnchorContractInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryInvoiceV2(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryInvoiceV2Request() model.from_json_string(json.dumps(args)) rsp = client.QueryInvoiceV2(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doBindAcct(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.BindAcctRequest() model.from_json_string(json.dumps(args)) rsp = client.BindAcct(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doBindRelateAcctSmallAmount(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.BindRelateAcctSmallAmountRequest() model.from_json_string(json.dumps(args)) rsp = client.BindRelateAcctSmallAmount(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doTransferSinglePay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.TransferSinglePayRequest() model.from_json_string(json.dumps(args)) rsp = client.TransferSinglePay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryMerchant(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryMerchantRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryMerchant(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doReviseMbrProperty(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ReviseMbrPropertyRequest() model.from_json_string(json.dumps(args)) rsp = client.ReviseMbrProperty(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryBalance(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryBalanceRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryBalance(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRevokeRechargeByThirdPay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RevokeRechargeByThirdPayRequest() model.from_json_string(json.dumps(args)) rsp = client.RevokeRechargeByThirdPay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doApplyReWithdrawal(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ApplyReWithdrawalRequest() model.from_json_string(json.dumps(args)) rsp = client.ApplyReWithdrawal(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryAgentTaxPaymentBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryAgentTaxPaymentBatchRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryAgentTaxPaymentBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeOrderStatus(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeOrderStatusRequest() model.from_json_string(json.dumps(args)) rsp = client.DescribeOrderStatus(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryAcctBinding(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryAcctBindingRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryAcctBinding(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doUploadTaxList(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.UploadTaxListRequest() model.from_json_string(json.dumps(args)) rsp = client.UploadTaxList(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doApplyPayerInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ApplyPayerInfoRequest() model.from_json_string(json.dumps(args)) rsp = client.ApplyPayerInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doApplyTrade(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ApplyTradeRequest() model.from_json_string(json.dumps(args)) rsp = client.ApplyTrade(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryBankClear(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryBankClearRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryBankClear(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doBindRelateAccReUnionPay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.BindRelateAccReUnionPayRequest() model.from_json_string(json.dumps(args)) rsp = client.BindRelateAccReUnionPay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doApplyWithdrawal(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ApplyWithdrawalRequest() model.from_json_string(json.dumps(args)) rsp = client.ApplyWithdrawal(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRevResigterBillSupportWithdraw(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RevResigterBillSupportWithdrawRequest() model.from_json_string(json.dumps(args)) rsp = client.RevResigterBillSupportWithdraw(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryApplicationMaterial(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryApplicationMaterialRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryApplicationMaterial(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRefund(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RefundRequest() model.from_json_string(json.dumps(args)) rsp = client.Refund(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRechargeMemberThirdPay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RechargeMemberThirdPayRequest() model.from_json_string(json.dumps(args)) rsp = client.RechargeMemberThirdPay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateMerchant(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateMerchantRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateMerchant(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateAcct(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateAcctRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateAcct(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doExecuteMemberTransaction(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ExecuteMemberTransactionRequest() model.from_json_string(json.dumps(args)) rsp = client.ExecuteMemberTransaction(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRegisterBill(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RegisterBillRequest() model.from_json_string(json.dumps(args)) rsp = client.RegisterBill(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQuerySinglePay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QuerySinglePayRequest() model.from_json_string(json.dumps(args)) rsp = client.QuerySinglePay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateRedInvoice(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateRedInvoiceRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateRedInvoice(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRechargeByThirdPay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RechargeByThirdPayRequest() model.from_json_string(json.dumps(args)) rsp = client.RechargeByThirdPay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateSinglePay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateSinglePayRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateSinglePay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateCustAcctId(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateCustAcctIdRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateCustAcctId(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCloseOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CloseOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.CloseOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryMerchantInfoForManagement(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryMerchantInfoForManagementRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryMerchantInfoForManagement(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRevokeMemberRechargeThirdPay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RevokeMemberRechargeThirdPayRequest() model.from_json_string(json.dumps(args)) rsp = client.RevokeMemberRechargeThirdPay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doBindRelateAcctUnionPay(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.BindRelateAcctUnionPayRequest() model.from_json_string(json.dumps(args)) rsp = client.BindRelateAcctUnionPay(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryMemberTransaction(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryMemberTransactionRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryMemberTransaction(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryBillDownloadURL(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryBillDownloadURLRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryBillDownloadURL(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateInvoice(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateInvoiceRequest() model.from_json_string(json.dumps(args)) rsp = client.CreateInvoice(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryRefund(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryRefundRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryRefund(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRefundMemberTransaction(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RefundMemberTransactionRequest() model.from_json_string(json.dumps(args)) rsp = client.RefundMemberTransaction(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doMigrateOrderRefundQuery(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.MigrateOrderRefundQueryRequest() model.from_json_string(json.dumps(args)) rsp = client.MigrateOrderRefundQuery(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryAgentStatements(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryAgentStatementsRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryAgentStatements(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryContract(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryContractRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryContract(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doApplyOutwardOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ApplyOutwardOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.ApplyOutwardOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQuerySmallAmountTransfer(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QuerySmallAmountTransferRequest() model.from_json_string(json.dumps(args)) rsp = client.QuerySmallAmountTransfer(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryTransferBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryTransferBatchRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryTransferBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doTerminateContract(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.TerminateContractRequest() model.from_json_string(json.dumps(args)) rsp = client.TerminateContract(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryAcctInfoList(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryAcctInfoListRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryAcctInfoList(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doQueryReconciliationDocument(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.QueryReconciliationDocumentRequest() model.from_json_string(json.dumps(args)) rsp = client.QueryReconciliationDocument(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRefundOrder(args, parsed_globals): g_param = parse_global_arg(parsed_globals) cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.CpdpClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RefundOrderRequest() model.from_json_string(json.dumps(args)) rsp = client.RefundOrder(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) CLIENT_MAP = { "v20190820": cpdp_client_v20190820, } MODELS_MAP = { "v20190820": models_v20190820, } ACTION_MAP = { "ModifyAgentTaxPaymentInfo": doModifyAgentTaxPaymentInfo, "ModifyMntMbrBindRelateAcctBankCode": doModifyMntMbrBindRelateAcctBankCode, "QueryOrder": doQueryOrder, "WithdrawCashMembership": doWithdrawCashMembership, "QueryBankTransactionDetails": doQueryBankTransactionDetails, "QueryCommonTransferRecharge": doQueryCommonTransferRecharge, "DownloadBill": doDownloadBill, "QueryCustAcctIdBalance": doQueryCustAcctIdBalance, "QueryPayerInfo": doQueryPayerInfo, "QueryTrade": doQueryTrade, "QueryTransferDetail": doQueryTransferDetail, "QuerySingleTransactionStatus": doQuerySingleTransactionStatus, "ApplyApplicationMaterial": doApplyApplicationMaterial, "ModifyMerchant": doModifyMerchant, "CreateInvoiceV2": doCreateInvoiceV2, "QueryInvoice": doQueryInvoice, "QueryExchangeRate": doQueryExchangeRate, "UnbindRelateAcct": doUnbindRelateAcct, "ContractOrder": doContractOrder, "CreateTransferBatch": doCreateTransferBatch, "UploadTaxPayment": doUploadTaxPayment, "QueryMemberBind": doQueryMemberBind, "DescribeChargeDetail": doDescribeChargeDetail, "QueryMerchantBalance": doQueryMerchantBalance, "DeleteAgentTaxPaymentInfo": doDeleteAgentTaxPaymentInfo, "CreateAgentTaxPaymentInfos": doCreateAgentTaxPaymentInfos, "DeleteAgentTaxPaymentInfos": doDeleteAgentTaxPaymentInfos, "CreatePayMerchant": doCreatePayMerchant, "RegisterBehavior": doRegisterBehavior, "RegisterBillSupportWithdraw": doRegisterBillSupportWithdraw, "UnifiedOrder": doUnifiedOrder, "UnBindAcct": doUnBindAcct, "ConfirmOrder": doConfirmOrder, "CheckAmount": doCheckAmount, "QueryTransferResult": doQueryTransferResult, "QueryOutwardOrder": doQueryOutwardOrder, "MigrateOrderRefund": doMigrateOrderRefund, "QueryAcctInfo": doQueryAcctInfo, "QueryBankWithdrawCashDetails": doQueryBankWithdrawCashDetails, "CheckAcct": doCheckAcct, "QueryMerchantOrder": doQueryMerchantOrder, "CreateRedInvoiceV2": doCreateRedInvoiceV2, "SyncContractData": doSyncContractData, "QueryAnchorContractInfo": doQueryAnchorContractInfo, "QueryInvoiceV2": doQueryInvoiceV2, "BindAcct": doBindAcct, "BindRelateAcctSmallAmount": doBindRelateAcctSmallAmount, "CreateOrder": doCreateOrder, "TransferSinglePay": doTransferSinglePay, "QueryMerchant": doQueryMerchant, "ReviseMbrProperty": doReviseMbrProperty, "QueryBalance": doQueryBalance, "RevokeRechargeByThirdPay": doRevokeRechargeByThirdPay, "ApplyReWithdrawal": doApplyReWithdrawal, "QueryAgentTaxPaymentBatch": doQueryAgentTaxPaymentBatch, "DescribeOrderStatus": doDescribeOrderStatus, "QueryAcctBinding": doQueryAcctBinding, "UploadTaxList": doUploadTaxList, "ApplyPayerInfo": doApplyPayerInfo, "ApplyTrade": doApplyTrade, "QueryBankClear": doQueryBankClear, "BindRelateAccReUnionPay": doBindRelateAccReUnionPay, "ApplyWithdrawal": doApplyWithdrawal, "RevResigterBillSupportWithdraw": doRevResigterBillSupportWithdraw, "QueryApplicationMaterial": doQueryApplicationMaterial, "Refund": doRefund, "RechargeMemberThirdPay": doRechargeMemberThirdPay, "CreateMerchant": doCreateMerchant, "CreateAcct": doCreateAcct, "ExecuteMemberTransaction": doExecuteMemberTransaction, "RegisterBill": doRegisterBill, "QuerySinglePay": doQuerySinglePay, "CreateRedInvoice": doCreateRedInvoice, "RechargeByThirdPay": doRechargeByThirdPay, "CreateSinglePay": doCreateSinglePay, "CreateCustAcctId": doCreateCustAcctId, "CloseOrder": doCloseOrder, "QueryMerchantInfoForManagement": doQueryMerchantInfoForManagement, "RevokeMemberRechargeThirdPay": doRevokeMemberRechargeThirdPay, "BindRelateAcctUnionPay": doBindRelateAcctUnionPay, "QueryMemberTransaction": doQueryMemberTransaction, "QueryBillDownloadURL": doQueryBillDownloadURL, "CreateInvoice": doCreateInvoice, "QueryRefund": doQueryRefund, "RefundMemberTransaction": doRefundMemberTransaction, "MigrateOrderRefundQuery": doMigrateOrderRefundQuery, "QueryAgentStatements": doQueryAgentStatements, "QueryContract": doQueryContract, "ApplyOutwardOrder": doApplyOutwardOrder, "QuerySmallAmountTransfer": doQuerySmallAmountTransfer, "QueryTransferBatch": doQueryTransferBatch, "TerminateContract": doTerminateContract, "QueryAcctInfoList": doQueryAcctInfoList, "QueryReconciliationDocument": doQueryReconciliationDocument, "RefundOrder": doRefundOrder, } AVAILABLE_VERSION_LIST = [ "v20190820", ] def action_caller(): return ACTION_MAP def parse_global_arg(parsed_globals): g_param = parsed_globals is_exist_profile = True if not parsed_globals["profile"]: is_exist_profile = False g_param["profile"] = "default" configure_path = os.path.join(os.path.expanduser("~"), ".tccli") is_conf_exist, conf_path = Utils.file_existed(configure_path, g_param["profile"] + ".configure") is_cred_exist, cred_path = Utils.file_existed(configure_path, g_param["profile"] + ".credential") conf = {} cred = {} if is_conf_exist: conf = Utils.load_json_msg(conf_path) if is_cred_exist: cred = Utils.load_json_msg(cred_path) if not (isinstance(conf, dict) and isinstance(cred, dict)): raise ConfigurationError( "file: %s or %s is not json format" % (g_param["profile"] + ".configure", g_param["profile"] + ".credential")) if OptionsDefine.Token not in cred: cred[OptionsDefine.Token] = None if not is_exist_profile: if os.environ.get(OptionsDefine.ENV_SECRET_ID) and os.environ.get(OptionsDefine.ENV_SECRET_KEY): cred[OptionsDefine.SecretId] = os.environ.get(OptionsDefine.ENV_SECRET_ID) cred[OptionsDefine.SecretKey] = os.environ.get(OptionsDefine.ENV_SECRET_KEY) cred[OptionsDefine.Token] = os.environ.get(OptionsDefine.ENV_TOKEN) if os.environ.get(OptionsDefine.ENV_REGION): conf[OptionsDefine.Region] = os.environ.get(OptionsDefine.ENV_REGION) for param in g_param.keys(): if g_param[param] is None: if param in [OptionsDefine.SecretKey, OptionsDefine.SecretId, OptionsDefine.Token]: if param in cred: g_param[param] = cred[param] else: raise ConfigurationError("%s is invalid" % param) elif param in [OptionsDefine.Region, OptionsDefine.Output]: if param in conf: g_param[param] = conf[param] else: raise ConfigurationError("%s is invalid" % param) try: if g_param[OptionsDefine.ServiceVersion]: g_param[OptionsDefine.Version] = "v" + g_param[OptionsDefine.ServiceVersion].replace('-', '') else: version = conf["cpdp"][OptionsDefine.Version] g_param[OptionsDefine.Version] = "v" + version.replace('-', '') if g_param[OptionsDefine.Endpoint] is None: g_param[OptionsDefine.Endpoint] = conf["cpdp"][OptionsDefine.Endpoint] except Exception as err: raise ConfigurationError("config file:%s error, %s" % (conf_path, str(err))) if g_param[OptionsDefine.Version] not in AVAILABLE_VERSION_LIST: raise Exception("available versions: %s" % " ".join(AVAILABLE_VERSION_LIST)) return g_param

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