xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

a97400b9f8653bf8e2e4366b42d6746d2d0250eb

38,782

py

Python

lightly/openapi_generated/swagger_client/api/predictions_api.py

CodeGuy-007/lightly

64143fe8a477c04288009c65fa1265cef8aa48f8

[ "MIT" ]

null

lightly/openapi_generated/swagger_client/api/predictions_api.py

CodeGuy-007/lightly

64143fe8a477c04288009c65fa1265cef8aa48f8

[ "MIT" ]

null

lightly/openapi_generated/swagger_client/api/predictions_api.py

CodeGuy-007/lightly

64143fe8a477c04288009c65fa1265cef8aa48f8

[ "MIT" ]

null

# coding: utf-8 """ Lightly API Lightly.ai enables you to do self-supervised learning in an easy and intuitive way. The lightly.ai OpenAPI spec defines how one can interact with our REST API to unleash the full potential of lightly.ai # noqa: E501 OpenAPI spec version: 1.0.0 Contact: support@lightly.ai 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 lightly.openapi_generated.swagger_client.api_client import ApiClient class PredictionsApi(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 create_or_update_prediction_by_sample_id(self, body, dataset_id, sample_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """create_or_update_prediction_by_sample_id # noqa: E501 Create/Update all the prediction singletons for a sampleId in the order/index of them being discovered # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_or_update_prediction_by_sample_id(body, dataset_id, sample_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param list[PredictionSingleton] body: (required) :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param MongoObjectID sample_id: ObjectId of the sample (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :return: CreateEntityResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_or_update_prediction_by_sample_id_with_http_info(body, dataset_id, sample_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 else: (data) = self.create_or_update_prediction_by_sample_id_with_http_info(body, dataset_id, sample_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 return data def create_or_update_prediction_by_sample_id_with_http_info(self, body, dataset_id, sample_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """create_or_update_prediction_by_sample_id # noqa: E501 Create/Update all the prediction singletons for a sampleId in the order/index of them being discovered # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_or_update_prediction_by_sample_id_with_http_info(body, dataset_id, sample_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param list[PredictionSingleton] body: (required) :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param MongoObjectID sample_id: ObjectId of the sample (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :return: CreateEntityResponse If the method is called asynchronously, returns the request thread. """ all_params = ['body', 'dataset_id', 'sample_id', 'prediction_uuid_timestamp'] # 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 create_or_update_prediction_by_sample_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'body' is set if self.api_client.client_side_validation and ('body' not in params or params['body'] is None): # noqa: E501 raise ValueError("Missing the required parameter `body` when calling `create_or_update_prediction_by_sample_id`") # noqa: E501 # verify the required parameter 'dataset_id' is set if self.api_client.client_side_validation and ('dataset_id' not in params or params['dataset_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `dataset_id` when calling `create_or_update_prediction_by_sample_id`") # noqa: E501 # verify the required parameter 'sample_id' is set if self.api_client.client_side_validation and ('sample_id' not in params or params['sample_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `sample_id` when calling `create_or_update_prediction_by_sample_id`") # noqa: E501 # verify the required parameter 'prediction_uuid_timestamp' is set if self.api_client.client_side_validation and ('prediction_uuid_timestamp' not in params or params['prediction_uuid_timestamp'] is None): # noqa: E501 raise ValueError("Missing the required parameter `prediction_uuid_timestamp` when calling `create_or_update_prediction_by_sample_id`") # noqa: E501 collection_formats = {} path_params = {} if 'dataset_id' in params: path_params['datasetId'] = params['dataset_id'] # noqa: E501 if 'sample_id' in params: path_params['sampleId'] = params['sample_id'] # noqa: E501 query_params = [] if 'prediction_uuid_timestamp' in params: query_params.append(('predictionUUIDTimestamp', params['prediction_uuid_timestamp'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['ApiKeyAuth', 'auth0Bearer'] # noqa: E501 return self.api_client.call_api( '/v1/datasets/{datasetId}/predictions/samples/{sampleId}', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CreateEntityResponse', # 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 create_or_update_prediction_task_schema_by_dataset_id(self, body, dataset_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """create_or_update_prediction_task_schema_by_dataset_id # noqa: E501 Creates/updates a prediction task schema with the task name # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_or_update_prediction_task_schema_by_dataset_id(body, dataset_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param PredictionTaskSchema body: (required) :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :return: CreateEntityResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_or_update_prediction_task_schema_by_dataset_id_with_http_info(body, dataset_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 else: (data) = self.create_or_update_prediction_task_schema_by_dataset_id_with_http_info(body, dataset_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 return data def create_or_update_prediction_task_schema_by_dataset_id_with_http_info(self, body, dataset_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """create_or_update_prediction_task_schema_by_dataset_id # noqa: E501 Creates/updates a prediction task schema with the task name # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_or_update_prediction_task_schema_by_dataset_id_with_http_info(body, dataset_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param PredictionTaskSchema body: (required) :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :return: CreateEntityResponse If the method is called asynchronously, returns the request thread. """ all_params = ['body', 'dataset_id', 'prediction_uuid_timestamp'] # 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 create_or_update_prediction_task_schema_by_dataset_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'body' is set if self.api_client.client_side_validation and ('body' not in params or params['body'] is None): # noqa: E501 raise ValueError("Missing the required parameter `body` when calling `create_or_update_prediction_task_schema_by_dataset_id`") # noqa: E501 # verify the required parameter 'dataset_id' is set if self.api_client.client_side_validation and ('dataset_id' not in params or params['dataset_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `dataset_id` when calling `create_or_update_prediction_task_schema_by_dataset_id`") # noqa: E501 # verify the required parameter 'prediction_uuid_timestamp' is set if self.api_client.client_side_validation and ('prediction_uuid_timestamp' not in params or params['prediction_uuid_timestamp'] is None): # noqa: E501 raise ValueError("Missing the required parameter `prediction_uuid_timestamp` when calling `create_or_update_prediction_task_schema_by_dataset_id`") # noqa: E501 collection_formats = {} path_params = {} if 'dataset_id' in params: path_params['datasetId'] = params['dataset_id'] # noqa: E501 query_params = [] if 'prediction_uuid_timestamp' in params: query_params.append(('predictionUUIDTimestamp', params['prediction_uuid_timestamp'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['ApiKeyAuth', 'auth0Bearer'] # noqa: E501 return self.api_client.call_api( '/v1/datasets/{datasetId}/predictions/tasks', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CreateEntityResponse', # 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 get_prediction_by_sample_id(self, dataset_id, sample_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """get_prediction_by_sample_id # noqa: E501 Get all prediction singletons of a specific sample of a dataset # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_prediction_by_sample_id(dataset_id, sample_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param MongoObjectID sample_id: ObjectId of the sample (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :return: PredictionSingletons If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_prediction_by_sample_id_with_http_info(dataset_id, sample_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 else: (data) = self.get_prediction_by_sample_id_with_http_info(dataset_id, sample_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 return data def get_prediction_by_sample_id_with_http_info(self, dataset_id, sample_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """get_prediction_by_sample_id # noqa: E501 Get all prediction singletons of a specific sample of a dataset # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_prediction_by_sample_id_with_http_info(dataset_id, sample_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param MongoObjectID sample_id: ObjectId of the sample (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :return: PredictionSingletons If the method is called asynchronously, returns the request thread. """ all_params = ['dataset_id', 'sample_id', 'prediction_uuid_timestamp'] # 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 get_prediction_by_sample_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'dataset_id' is set if self.api_client.client_side_validation and ('dataset_id' not in params or params['dataset_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `dataset_id` when calling `get_prediction_by_sample_id`") # noqa: E501 # verify the required parameter 'sample_id' is set if self.api_client.client_side_validation and ('sample_id' not in params or params['sample_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `sample_id` when calling `get_prediction_by_sample_id`") # noqa: E501 # verify the required parameter 'prediction_uuid_timestamp' is set if self.api_client.client_side_validation and ('prediction_uuid_timestamp' not in params or params['prediction_uuid_timestamp'] is None): # noqa: E501 raise ValueError("Missing the required parameter `prediction_uuid_timestamp` when calling `get_prediction_by_sample_id`") # noqa: E501 collection_formats = {} path_params = {} if 'dataset_id' in params: path_params['datasetId'] = params['dataset_id'] # noqa: E501 if 'sample_id' in params: path_params['sampleId'] = params['sample_id'] # noqa: E501 query_params = [] if 'prediction_uuid_timestamp' in params: query_params.append(('predictionUUIDTimestamp', params['prediction_uuid_timestamp'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['ApiKeyAuth', 'auth0Bearer'] # noqa: E501 return self.api_client.call_api( '/v1/datasets/{datasetId}/predictions/samples/{sampleId}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PredictionSingletons', # 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 get_prediction_task_schema_by_task_name(self, dataset_id, prediction_uuid_timestamp, task_name, **kwargs): # noqa: E501 """get_prediction_task_schema_by_task_name # noqa: E501 Get a prediction task schemas named taskName for a datasetId # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_prediction_task_schema_by_task_name(dataset_id, prediction_uuid_timestamp, task_name, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :param TaskName task_name: The prediction task name for which one wants to list the predictions (required) :return: PredictionTaskSchema If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_prediction_task_schema_by_task_name_with_http_info(dataset_id, prediction_uuid_timestamp, task_name, **kwargs) # noqa: E501 else: (data) = self.get_prediction_task_schema_by_task_name_with_http_info(dataset_id, prediction_uuid_timestamp, task_name, **kwargs) # noqa: E501 return data def get_prediction_task_schema_by_task_name_with_http_info(self, dataset_id, prediction_uuid_timestamp, task_name, **kwargs): # noqa: E501 """get_prediction_task_schema_by_task_name # noqa: E501 Get a prediction task schemas named taskName for a datasetId # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_prediction_task_schema_by_task_name_with_http_info(dataset_id, prediction_uuid_timestamp, task_name, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :param TaskName task_name: The prediction task name for which one wants to list the predictions (required) :return: PredictionTaskSchema If the method is called asynchronously, returns the request thread. """ all_params = ['dataset_id', 'prediction_uuid_timestamp', 'task_name'] # 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 get_prediction_task_schema_by_task_name" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'dataset_id' is set if self.api_client.client_side_validation and ('dataset_id' not in params or params['dataset_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `dataset_id` when calling `get_prediction_task_schema_by_task_name`") # noqa: E501 # verify the required parameter 'prediction_uuid_timestamp' is set if self.api_client.client_side_validation and ('prediction_uuid_timestamp' not in params or params['prediction_uuid_timestamp'] is None): # noqa: E501 raise ValueError("Missing the required parameter `prediction_uuid_timestamp` when calling `get_prediction_task_schema_by_task_name`") # noqa: E501 # verify the required parameter 'task_name' is set if self.api_client.client_side_validation and ('task_name' not in params or params['task_name'] is None): # noqa: E501 raise ValueError("Missing the required parameter `task_name` when calling `get_prediction_task_schema_by_task_name`") # noqa: E501 collection_formats = {} path_params = {} if 'dataset_id' in params: path_params['datasetId'] = params['dataset_id'] # noqa: E501 if 'task_name' in params: path_params['taskName'] = params['task_name'] # noqa: E501 query_params = [] if 'prediction_uuid_timestamp' in params: query_params.append(('predictionUUIDTimestamp', params['prediction_uuid_timestamp'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['ApiKeyAuth', 'auth0Bearer'] # noqa: E501 return self.api_client.call_api( '/v1/datasets/{datasetId}/predictions/tasks/{taskName}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PredictionTaskSchema', # 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 get_prediction_task_schemas_by_dataset_id(self, dataset_id, **kwargs): # noqa: E501 """get_prediction_task_schemas_by_dataset_id # noqa: E501 Get list of all the prediction task schemas for a datasetId at a specific predictionUUIDTimestamp. If no predictionUUIDTimestamp is set, it defaults to the newest # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_prediction_task_schemas_by_dataset_id(dataset_id, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. :return: list[PredictionTaskSchema] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_prediction_task_schemas_by_dataset_id_with_http_info(dataset_id, **kwargs) # noqa: E501 else: (data) = self.get_prediction_task_schemas_by_dataset_id_with_http_info(dataset_id, **kwargs) # noqa: E501 return data def get_prediction_task_schemas_by_dataset_id_with_http_info(self, dataset_id, **kwargs): # noqa: E501 """get_prediction_task_schemas_by_dataset_id # noqa: E501 Get list of all the prediction task schemas for a datasetId at a specific predictionUUIDTimestamp. If no predictionUUIDTimestamp is set, it defaults to the newest # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_prediction_task_schemas_by_dataset_id_with_http_info(dataset_id, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. :return: list[PredictionTaskSchema] If the method is called asynchronously, returns the request thread. """ all_params = ['dataset_id', 'prediction_uuid_timestamp'] # 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 get_prediction_task_schemas_by_dataset_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'dataset_id' is set if self.api_client.client_side_validation and ('dataset_id' not in params or params['dataset_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `dataset_id` when calling `get_prediction_task_schemas_by_dataset_id`") # noqa: E501 collection_formats = {} path_params = {} if 'dataset_id' in params: path_params['datasetId'] = params['dataset_id'] # noqa: E501 query_params = [] if 'prediction_uuid_timestamp' in params: query_params.append(('predictionUUIDTimestamp', params['prediction_uuid_timestamp'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['ApiKeyAuth', 'auth0Bearer'] # noqa: E501 return self.api_client.call_api( '/v1/datasets/{datasetId}/predictions/tasks', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[PredictionTaskSchema]', # 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 get_predictions_by_dataset_id(self, dataset_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """get_predictions_by_dataset_id # noqa: E501 Get all prediction singletons of all samples of a dataset ordered by the sample mapping # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_predictions_by_dataset_id(dataset_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :param TaskName task_name: If provided, only gets all prediction singletons of all samples of a dataset that were yielded by a specific prediction task name :return: list[PredictionSingletons] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_predictions_by_dataset_id_with_http_info(dataset_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 else: (data) = self.get_predictions_by_dataset_id_with_http_info(dataset_id, prediction_uuid_timestamp, **kwargs) # noqa: E501 return data def get_predictions_by_dataset_id_with_http_info(self, dataset_id, prediction_uuid_timestamp, **kwargs): # noqa: E501 """get_predictions_by_dataset_id # noqa: E501 Get all prediction singletons of all samples of a dataset ordered by the sample mapping # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_predictions_by_dataset_id_with_http_info(dataset_id, prediction_uuid_timestamp, async_req=True) >>> result = thread.get() :param async_req bool :param MongoObjectID dataset_id: ObjectId of the dataset (required) :param Timestamp prediction_uuid_timestamp: The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. (required) :param TaskName task_name: If provided, only gets all prediction singletons of all samples of a dataset that were yielded by a specific prediction task name :return: list[PredictionSingletons] If the method is called asynchronously, returns the request thread. """ all_params = ['dataset_id', 'prediction_uuid_timestamp', 'task_name'] # 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 get_predictions_by_dataset_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'dataset_id' is set if self.api_client.client_side_validation and ('dataset_id' not in params or params['dataset_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `dataset_id` when calling `get_predictions_by_dataset_id`") # noqa: E501 # verify the required parameter 'prediction_uuid_timestamp' is set if self.api_client.client_side_validation and ('prediction_uuid_timestamp' not in params or params['prediction_uuid_timestamp'] is None): # noqa: E501 raise ValueError("Missing the required parameter `prediction_uuid_timestamp` when calling `get_predictions_by_dataset_id`") # noqa: E501 collection_formats = {} path_params = {} if 'dataset_id' in params: path_params['datasetId'] = params['dataset_id'] # noqa: E501 query_params = [] if 'prediction_uuid_timestamp' in params: query_params.append(('predictionUUIDTimestamp', params['prediction_uuid_timestamp'])) # noqa: E501 if 'task_name' in params: query_params.append(('taskName', params['task_name'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['ApiKeyAuth', 'auth0Bearer'] # noqa: E501 return self.api_client.call_api( '/v1/datasets/{datasetId}/predictions/samples', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[PredictionSingletons]', # 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

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0

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0

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0

1

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false

0

0.010554

0

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0

null

0

1

0

1

0

null

0

7

8d1b6b2a336d0d6d21b1cb23ba26ac2f090134e2

15,512

py

Python

utils/attr_computing.py

GlowingHorse/Class-Discriminative-Vis

c4dec263f13225eed8598544b46c984784953c50

[ "MIT" ]

2

2020-06-25T15:35:19.000Z

2020-07-08T11:14:46.000Z

utils/attr_computing.py

GlowingHorse/class-discriminative-vis

c4dec263f13225eed8598544b46c984784953c50

[ "MIT" ]

1

2020-06-25T15:59:54.000Z

2020-10-23T06:09:39.000Z

utils/attr_computing.py

GlowingHorse/Class-Discriminative-Vis

c4dec263f13225eed8598544b46c984784953c50

[ "MIT" ]

null

""" The attr_computing.py provides two methods for computing channel Shapley and transform them to feature attributions. """ import numpy as np import tensorflow as tf import lucid.optvis.render as render from lucid.misc.gradient_override import gradient_override_map def compute_shap(img, model, attr_class, layers, flag1, flag_read_attr=True, iter_num=2 ** 8, labels=None, save_directory=None): """ Using sampling based Shapley method to compute feature attributions """ with tf.Graph().as_default(), tf.Session() as sess, gradient_override_map({}): # img = tf.image.resize_image_with_crop_or_pad(img, model.image_shape[0], model.image_shape[0]) # imgnp = sess.run(img) # imgnp = imgnp.reshape(224, 224, 3) # plt.imsave("./doghead224.jpeg", imgnp) t_input = tf.placeholder_with_default(img, [None, None, 3]) T = render.import_model(model, t_input, t_input) # grads_cam_T = [T(layer) for layer in layers] # logit = T("softmax2_pre_activation")[0] # score = T("output2")[0, labels.index(attr_class)] logit = T("softmax2_pre_activation")[0] AM_T = list(range(len(layers))) AM_T_reverse = list(range(len(layers))) channel_attr_list = list(range(len(layers))) kept_channel_list = list(range(len(layers))) kept_channel_list_reverse = list(range(len(layers))) ori_logit = logit.eval() y_label = np.zeros_like(ori_logit) y_label[labels.index(attr_class)] = 1 # index_class_logit = ori_logit[labels.index(attr_class)] # detected_label_index = ori_logit.argmax() # print("detected label index: {}, real label index: {}, label name: {}" # .format(detected_label_index, labels.index(attr_class), attr_class)) for i_wanted_layer in range(len(layers)): layer = layers[i_wanted_layer] acts = T(layer).eval() acts_shape = list(acts.shape) # part_name = "import/{}:0".format(layer) # t_part_input = tf.placeholder(acts.dtype, acts_shape) # T_part = import_part_model(model, t_part_input, part_name) # part_logit = T_part("softmax2_pre_activation")[0] n_features = acts.shape[-1] if not flag_read_attr: result = np.zeros((1, n_features)) run_shape = acts_shape.copy() # run_shape = np.delete(run_shape, -1).tolist() # run_shape.insert(-1, -1) reconstruction_shape = [1, acts_shape[-1]] for r in range(iter_num): p = np.random.permutation(n_features) x = acts.copy().reshape(run_shape) y = None for i in p: if y is None: y = logit.eval({T(layer): x}) # y = model.predict(x.reshape(acts_shape)) x[..., i] = 0 y0 = logit.eval({T(layer): x}) # print("Ori logit score: {}, new logit score: {}" # .format(index_class_logit, y0[labels.index(attr_class)])) # y0 = model.predict(x.reshape(acts_shape)) assert y0.shape == y_label.shape, y0.shape prediction_delta = np.sum((y - y0) * y_label) # if i == 139: # print("AM 139: attr is {}".format(prediction_delta)) result[:, i] += prediction_delta y = y0 attr = np.squeeze( (result.copy() / iter_num).reshape(reconstruction_shape).astype(np.float32)) np.savetxt(save_directory + "/{}_{}_{}.txt".format(flag1, layer, attr_class), attr) else: attr = np.loadtxt(save_directory + "/{}_{}_{}.txt".format(flag1, layer, attr_class)).astype(np.float32) # arg_attr = attr.argsort()[::-1][:] # shap_attr_trans = np.transpose(shap_attr, (2, 0, 1)) # acts_squeeze_trans = np.transpose(acts_squeeze, (2, 0, 1)) ''' # # Use it for debug the attribution maps # sort_AMs_idx_b2s = np.argsort(-attr) # sort_AMs_idx_s2b = np.argsort(attr) # for i_sort_AMs in range(20): # if i_sort_AMs < 10: # AM_backup_idx = sort_AMs_idx_b2s[i_sort_AMs] # print("big shap value: {:+.3f} in channel {} of all {}" # .format(attr[AM_backup_idx], AM_backup_idx, acts.shape[-1])) # print(" for class: {}, image No:{}" # .format(attr_class, i_sort_AMs)) # else: # AM_backup_idx = sort_AMs_idx_s2b[i_sort_AMs-10] # print("small shap value: {:+.3f} in channel {} of all {}" # .format(attr[AM_backup_idx], AM_backup_idx, acts.shape[-1])) # print(" for class: {}, image No:{}" # .format(attr_class, i_sort_AMs-10)) # AM_backup = acts[..., AM_backup_idx] # AM_backup = AM_backup.reshape([AM_backup.shape[-1], AM_backup.shape[-1]]) # AM_backup = resize(AM_backup, (model.image_shape[0], model.image_shape[1]), order=1, # mode='constant', anti_aliasing=False) # AM_backup = AM_backup / AM_backup.max() * 255 # resize_show(AM_backup, xi=img) # kept_channel_idx = np.squeeze(np.argwhere(attr > 0)) ''' kept_channel_idx = np.squeeze(np.argwhere(attr > np.nanmean(np.where(attr > 0, attr, np.nan)))) acts_squeeze = np.squeeze(acts) attr_temp = np.squeeze(attr).astype(np.float32) # print(np.count_nonzero(clear_channel_idx)) channel_attr_list[i_wanted_layer] = attr_temp AM_T[i_wanted_layer] = acts_squeeze[..., kept_channel_idx] kept_channel_list[i_wanted_layer] = kept_channel_idx kept_channel_idx = np.squeeze(np.argwhere(attr < np.nanmean(np.where(attr < 0, attr, np.nan)))) AM_T_reverse[i_wanted_layer] = acts_squeeze[..., kept_channel_idx] kept_channel_list_reverse[i_wanted_layer] = kept_channel_idx # test_AM = acts_squeeze * clear_channel_idx * attr_temp # test_AM = np.sum(np.transpose(test_AM, (2, 0, 1)), axis=0) # acts_squeeze_trans = np.transpose(AM_T[i_wanted_layer], (2, 0, 1)) # acts_squeeze_trans_sum = np.sum(acts_squeeze_trans, axis=0) AM_list = AM_T logit_list = sess.run([logit])[0] return [AM_list, AM_T_reverse], logit_list, channel_attr_list, \ [kept_channel_list, kept_channel_list_reverse] def compute_igsg(img, model, attr_class, layers, flag1, flag_read_attr=True, iter_num=100, SG_path=False, labels=None, save_directory=None): """ Using Aumann Shapley values as feature attributions """ with tf.Graph().as_default(), tf.Session() as sess, gradient_override_map({}): # img = tf.image.resize_image_with_crop_or_pad(img, model.image_shape[0], model.image_shape[0]) # imgnp = sess.run(img) # imgnp = imgnp.reshape(224, 224, 3) # plt.imsave("./doghead224.jpeg", imgnp) t_input = tf.placeholder_with_default(img, [None, None, 3]) T = render.import_model(model, t_input, t_input) # grads_cam_T = [T(layer) for layer in layers] # logit = T("softmax2_pre_activation")[0] # logit = T("output2")[0] # score = T("output2")[0, labels.index(attr_class)] logit = T("softmax2_pre_activation")[0] logit4grad = T("softmax2_pre_activation")[0, labels.index(attr_class)] AM_T = list(range(len(layers))) AM_T_reverse = list(range(len(layers))) channel_attr_list = list(range(len(layers))) kept_channel_list = list(range(len(layers))) kept_channel_list_reverse = list(range(len(layers))) for i_wanted_layer in range(len(layers)): layer = layers[i_wanted_layer] acts = T(layer).eval() attr = np.zeros(acts.shape[1:]) t_grad = tf.gradients([logit4grad], [T(layer)])[0] if not flag_read_attr: for n in range(iter_num): acts_ = acts * float(n) / iter_num if SG_path: acts_ *= (np.random.uniform(0, 1, [528]) + np.random.uniform(0, 1, [528])) / 1.5 grad = t_grad.eval({T(layer): acts_}) attr += grad[0] attr = attr * (1.0 / iter_num) * acts[0] attr = np.sum(np.sum(attr, 0), 0) np.savetxt(save_directory + "/{}_{}_{}.txt".format(flag1, layer, attr_class), attr) else: attr = np.loadtxt(save_directory + "/{}_{}_{}.txt". format(flag1, layer, attr_class)).astype(np.float32) # AM_T[i_wanted_layer] = attr * (attr > 0) kept_channel_idx = np.squeeze(np.argwhere(attr > np.nanmean(np.where(attr > 0, attr, np.nan)))) acts_squeeze = np.squeeze(acts) attr_temp = np.squeeze(attr).astype(np.float32) # print(np.count_nonzero(clear_channel_idx)) channel_attr_list[i_wanted_layer] = attr_temp AM_T[i_wanted_layer] = acts_squeeze[..., kept_channel_idx] kept_channel_list[i_wanted_layer] = kept_channel_idx # # alltests_Shap/test0_4 # kept_channel_idx = np.squeeze(np.argwhere(attr < 0)) # # alltests_Shap/test0_6 kept_channel_idx = np.squeeze(np.argwhere(attr < np.nanmean(np.where(attr < 0, attr, np.nan)))) AM_T_reverse[i_wanted_layer] = acts_squeeze[..., kept_channel_idx] kept_channel_list_reverse[i_wanted_layer] = kept_channel_idx AM_list = AM_T logit_list = sess.run([logit])[0] return [AM_list, AM_T_reverse], logit_list, channel_attr_list, \ [kept_channel_list, kept_channel_list_reverse] def compute_all_am_shap(img, model, attr_class, layers, flag1, flag_read_attr=True, iter_num=2 ** 8, labels=None, save_directory=None): """ Using sampling based Shapley method to compute feature attributions Return all attributions and AM not just positive or negative ones """ with tf.Graph().as_default(), tf.Session() as sess, gradient_override_map({}): # img = tf.image.resize_image_with_crop_or_pad(img, model.image_shape[0], model.image_shape[0]) # imgnp = sess.run(img) # imgnp = imgnp.reshape(224, 224, 3) # plt.imsave("./doghead224.jpeg", imgnp) t_input = tf.placeholder_with_default(img, [None, None, 3]) T = render.import_model(model, t_input, t_input) # grads_cam_T = [T(layer) for layer in layers] # logit = T("softmax2_pre_activation")[0] # score = T("output2")[0, labels.index(attr_class)] logit = T("softmax2_pre_activation")[0] AM_T = list(range(len(layers))) channel_attr_list = list(range(len(layers))) ori_logit = logit.eval() y_label = np.zeros_like(ori_logit) y_label[labels.index(attr_class)] = 1 # index_class_logit = ori_logit[labels.index(attr_class)] # detected_label_index = ori_logit.argmax() # print("detected label index: {}, real label index: {}, label name: {}" # .format(detected_label_index, labels.index(attr_class), attr_class)) for i_wanted_layer in range(len(layers)): layer = layers[i_wanted_layer] acts = T(layer).eval() acts_shape = list(acts.shape) # part_name = "import/{}:0".format(layer) # t_part_input = tf.placeholder(acts.dtype, acts_shape) # T_part = import_part_model(model, t_part_input, part_name) # part_logit = T_part("softmax2_pre_activation")[0] n_features = acts.shape[-1] if not flag_read_attr: result = np.zeros((1, n_features)) run_shape = acts_shape.copy() # run_shape = np.delete(run_shape, -1).tolist() # run_shape.insert(-1, -1) reconstruction_shape = [1, acts_shape[-1]] for r in range(iter_num): p = np.random.permutation(n_features) x = acts.copy().reshape(run_shape) y = None for i in p: if y is None: y = logit.eval({T(layer): x}) # y = model.predict(x.reshape(acts_shape)) x[..., i] = 0 y0 = logit.eval({T(layer): x}) # print("Ori logit score: {}, new logit score: {}" # .format(index_class_logit, y0[labels.index(attr_class)])) # y0 = model.predict(x.reshape(acts_shape)) assert y0.shape == y_label.shape, y0.shape prediction_delta = np.sum((y - y0) * y_label) result[:, i] += prediction_delta y = y0 attr = np.squeeze( (result.copy() / iter_num).reshape(reconstruction_shape).astype(np.float32)) np.savetxt(save_directory + "/{}_{}_{}.txt".format(flag1, layer, attr_class), attr) else: attr = np.loadtxt(save_directory + "/{}_{}_{}.txt".format(flag1, layer, attr_class)).astype(np.float32) acts_squeeze = np.squeeze(acts) attr_temp = np.squeeze(attr).astype(np.float32) channel_attr_list[i_wanted_layer] = attr_temp AM_T[i_wanted_layer] = acts_squeeze AM_list = AM_T logit_list = sess.run([logit])[0] return AM_list, logit_list, channel_attr_list def compute_all_am_igsg(img, model, attr_class, layers, flag1, flag_read_attr=True, iter_num=2 ** 8, SG_path=False, labels=None, save_directory=None): """ Using Aumann Shapley values as feature attributions Return all attributions and AM not just positive or negative ones """ with tf.Graph().as_default(), tf.Session() as sess, gradient_override_map({}): # img = tf.image.resize_image_with_crop_or_pad(img, model.image_shape[0], model.image_shape[0]) # imgnp = sess.run(img) # imgnp = imgnp.reshape(224, 224, 3) # plt.imsave("./doghead224.jpeg", imgnp) t_input = tf.placeholder_with_default(img, [None, None, 3]) T = render.import_model(model, t_input, t_input) # grads_cam_T = [T(layer) for layer in layers] # logit = T("softmax2_pre_activation")[0] # score = T("output2")[0, labels.index(attr_class)] logit = T("softmax2_pre_activation")[0] logit4grad = T("softmax2_pre_activation")[0, labels.index(attr_class)] AM_T = list(range(len(layers))) channel_attr_list = list(range(len(layers))) ori_logit = logit.eval() ori_single_logit = logit4grad.eval() y_label = np.zeros_like(ori_logit) y_label[labels.index(attr_class)] = 1 # index_class_logit = ori_logit[labels.index(attr_class)] # detected_label_index = ori_logit.argmax() # print("detected label index: {}, real label index: {}, label name: {}" # .format(detected_label_index, labels.index(attr_class), attr_class)) for i_wanted_layer in range(len(layers)): layer = layers[i_wanted_layer] acts = T(layer).eval() attr = np.zeros(acts.shape[1:]) t_grad = tf.gradients([logit4grad], [T(layer)])[0] if not flag_read_attr: for n in range(iter_num): acts_ = acts * float(n) / iter_num if SG_path: acts_ *= (np.random.uniform(0, 1, [528]) + np.random.uniform(0, 1, [528])) / 1.5 grad = t_grad.eval({T(layer): acts_}) attr += grad[0] attr = attr * (1.0 / iter_num) * acts[0] attr = np.sum(np.sum(attr, 0), 0) # normalize IG result for degub differences attr = attr * ori_single_logit / np.sum(attr) np.savetxt(save_directory + "/{}_{}_{}.txt".format(flag1, layer, attr_class), attr) else: attr = np.loadtxt(save_directory + "/{}_{}_{}.txt". format(flag1, layer, attr_class)).astype(np.float32) attr_temp = np.squeeze(attr).astype(np.float32) channel_attr_list[i_wanted_layer] = attr_temp acts_squeeze = np.squeeze(acts) AM_T[i_wanted_layer] = acts_squeeze AM_list = AM_T logit_list = sess.run([logit])[0] return AM_list, logit_list, channel_attr_list

42.615385

111

0.629771

2,193

15,512

4.181943

0.097583

0.033366

0.031403

0.037073

0.903827

0.891724

0.876895

0.873514

0.865773

0

0.022388

0.231176

15,512

363

112

42.732782

0.746604

0.271338

0

0.937173

0

0.024549

0.013999

0

0.010471

1

0.020942

false

0

0.041885

0

0.08377

0

null

0

1

0

1

0

null

0

7

8d856bc05540e61179326b029317841542a00d5e

134

py

Python

cuchem/cuchem/wf/generative/__init__.py

dorukozturk/cheminformatics

c0fa66dd4f4e6650d7286ae2be533c66b7a2b270

[ "Apache-2.0" ]

null

cuchem/cuchem/wf/generative/__init__.py

dorukozturk/cheminformatics

c0fa66dd4f4e6650d7286ae2be533c66b7a2b270

[ "Apache-2.0" ]

null

cuchem/cuchem/wf/generative/__init__.py

dorukozturk/cheminformatics

c0fa66dd4f4e6650d7286ae2be533c66b7a2b270

[ "Apache-2.0" ]

null

from cuchem.wf.generative.cddd import Cddd as Cddd from cuchem.wf.generative.megatronmolbart import MegatronMolBART as MegatronMolBART

67

83

0.873134

18

134

6.5

0.444444

0.17094

0.205128

0.376068

0

0.08209

134

2

83

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0

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null

0

1

0

1

0

1

0

7

a5fea24c770834f56924b44ab5355614dd1bd962

10,794

py

Python

maze_test.py

wadiim/maze

ff0509ef2cf9b3acf90a8647ba712ba2b7c99aba

[ "MIT" ]

1

2020-10-28T05:49:04.000Z

maze_test.py

wadiim/maze

ff0509ef2cf9b3acf90a8647ba712ba2b7c99aba

[ "MIT" ]

null

maze_test.py

wadiim/maze

ff0509ef2cf9b3acf90a8647ba712ba2b7c99aba

[ "MIT" ]

null

# -*- coding: utf-8 -*- from maze import Shape, get_shape, cell_to_string, maze_to_string, solve_maze import unittest class GetShapeTest(unittest.TestCase): def test_inner_cell(self): maze = [[0, 0, 0, 0], [0, 1, 1, 0], [0, 0, 1, 0], [0, 0, 0, 0]] shape = Shape(down = True, right = True) self.assertEqual(get_shape(maze, x = 1, y = 2), shape) def test_outer_cell(self): maze = [[0, 0, 0, 0], [0, 0, 0, 0], [1, 0, 0, 0], [1, 1, 0, 0]] shape = Shape(left = True, up = True) self.assertEqual(get_shape(maze, x = 3, y = 0), shape) def test_different_values(self): maze = [[3, 1, 5, 4], [2, 2, 2, 8], [0, 2, 6, 7], [1, 7, 1, 3]] shape = Shape(up = True, down = True, right = True) self.assertEqual(get_shape(maze, x = 1, y = 1), shape) class CellToStringTest(unittest.TestCase): def test_empty_cell(self): maze = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), ' ') def test_horizontal(self): maze = [[0, 1, 0, 0], [0, 1, 0, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '───') def test_vertical(self): maze = [[0, 0, 0, 0], [1, 1, 1, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), ' │ ') def test_down_and_right(self): maze = [[0, 0, 0, 0], [1, 1, 0, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), ' ┌─') def test_down_and_left(self): maze = [[0, 1, 0, 0], [1, 1, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '─┐ ') def test_up_and_right(self): maze = [[0, 0, 0, 0], [0, 1, 1, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), ' └─') def test_up_and_left(self): maze = [[0, 1, 0, 0], [0, 1, 1, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '─┘ ') def test_vertical_and_right(self): maze = [[0, 0, 0, 0], [1, 1, 1, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), ' ├─') def test_vertical_and_left(self): maze = [[0, 1, 0, 0], [1, 1, 1, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '─┤ ') def test_down_and_horizontal(self): maze = [[0, 1, 0, 0], [1, 1, 0, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '─┬─') def test_up_and_horizontal(self): maze = [[0, 1, 0, 0], [0, 1, 1, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '─┴─') def test_vertical_and_horizontal(self): maze = [[0, 1, 0, 0], [1, 1, 1, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '─┼─') def test_up(self): maze = [[0, 0, 0, 0], [0, 1, 1, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), ' │ ') def test_down(self): maze = [[0, 0, 0, 0], [1, 1, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), ' │ ') def test_left(self): maze = [[0, 1, 0, 0], [0, 1, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '───') def test_right(self): maze = [[0, 0, 0, 0], [0, 1, 0, 0], [0, 1, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 1, y = 1), '───') def test_top_left_corner(self): maze = [[0, 0, 0, 1], [0, 0, 0, 1], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 0, y = 3), ' ┌─') def test_top_right_corner(self): maze = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 1, 1]] self.assertEqual(cell_to_string(maze, x = 3, y = 3), '─┐ ') def test_bottom_left_corner(self): maze = [[1, 1, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 0, y = 0), ' └─') def test_bottom_right_corner(self): maze = [[0, 0, 0, 0], [0, 0, 0, 0], [1, 0, 0, 0], [1, 0, 0, 0]] self.assertEqual(cell_to_string(maze, x = 3, y = 0), '─┘ ') class MazeToStringTest(unittest.TestCase): def test_empty_maze(self): maze = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] str = (" \n" " \n" " \n" " ") self.assertEqual(maze_to_string(maze), str) def test_complex_maze(self): maze = [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1], [1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1], [1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1], [1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1], [1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1], [1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1], [0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1], [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]] str = (" ┌──── ┌──────────────┬─────┐ \n" " │ │ │ │ \n" " ├──── │ ┌──── │ │ \n" " │ │ │ \n" " │ ┌────────┴──┐ ───────┤ \n" " │ │ │ │ \n" " │ │ │ │ │ │ \n" " │ │ ├─────┼─────┤ \n" " │ ┌─────┘ │ │ │ \n" " │ │ │ \n" " └─────┴──────────────── ────┘ ") self.assertEqual(maze_to_string(maze), str) def test_complex_maze_with_solution(self): maze = [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 0, 0, 2, 2, 2, 2, 2, 1, 0, 1], [1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 2], [1, 0, 1, 2, 2, 2, 1, 0, 1, 1, 1], [1, 0, 1, 1, 1, 2, 1, 0, 0, 0, 1], [1, 2, 2, 2, 2, 2, 1, 1, 1, 0, 1], [1, 2, 1, 1, 1, 1, 1, 0, 1, 0, 1], [1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 1], [2, 2, 1, 1, 1, 0, 1, 0, 1, 1, 1], [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]] str = (" ┌──── │ ┌──────────────┬─────┐ \n" " │ │ │ │ │ \n" " ├──── │ │ ┌──── │ │ \n" " │ ┌──┘ │ │ \n" " │ │ ┌────────┴──┐ ───────┤ \n" " │ │ │ ┌─────┐ │ │ \n" " │ │ │ │ │ │ │ │ │ \n" " │ └─────┘ │ │ ├─────┼─────┤ \n" " │ ┌─────┘ │ │ │ │ \n" " │ │ └────────┐ │ \n" " └─────┴──────────────── │ ────┘ ") self.assertEqual(maze_to_string(maze), str) class SolveMazeTest(unittest.TestCase): def test_horizontal_single_path(self): maze = [[1, 0, 1], [1, 0, 1], [1, 0, 1], [1, 0, 1], [1, 0, 1]] solution = [[1, 2, 1], [1, 2, 1], [1, 2, 1], [1, 2, 1], [1, 2, 1]] solve_maze(maze) self.assertEqual(maze, solution) def test_vertical_single_path(self): maze = [[1, 1, 1, 1, 1], [0, 0, 0, 0, 0], [1, 1, 1, 1, 1]] solution = [[1, 1, 1, 1, 1], [2, 2, 2, 2, 2], [1, 1, 1, 1, 1]] solve_maze(maze) self.assertEqual(maze, solution) def test_curved_path(self): maze = [[1, 1, 1, 1, 1], [0, 0, 1, 0, 0], [1, 0, 1, 0, 1], [1, 0, 0, 0, 1], [1, 1, 1, 1, 1]] solution = [[1, 1, 1, 1, 1], [2, 2, 1, 2, 2], [1, 2, 1, 2, 1], [1, 2, 2, 2, 1], [1, 1, 1, 1, 1]] solve_maze(maze) self.assertEqual(maze, solution) def test_multiple_pathes(self): maze = [[1, 1, 1, 1, 1], [0, 0, 0, 0, 1], [1, 0, 1, 1, 1], [1, 0, 0, 0, 1], [1, 0, 1, 1, 1]] solution = [[1, 1, 1, 1, 1], [2, 2, 0, 0, 1], [1, 2, 1, 1, 1], [1, 2, 0, 0, 1], [1, 2, 1, 1, 1]] solve_maze(maze) self.assertEqual(maze, solution) def test_complex_maze(self): maze = [[1, 1, 1, 1, 1, 1, 1], [1, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 1, 1, 1], [1, 0, 1, 0, 0, 0, 1], [1, 0, 1, 1, 1, 0, 1], [1, 0, 0, 0, 0, 0, 1], [1, 0, 1, 1, 1, 1, 1]] solution = [[1, 1, 1, 1, 1, 1, 1], [1, 0, 0, 2, 2, 2, 2], [1, 1, 1, 2, 1, 1, 1], [1, 0, 1, 2, 2, 2, 1], [1, 0, 1, 1, 1, 2, 1], [1, 2, 2, 2, 2, 2, 1], [1, 2, 1, 1, 1, 1, 1]] solve_maze(maze) self.assertEqual(maze, solution) if __name__ == '__main__': unittest.main()

34.707395

77

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1,572

10,794

2.284351

0.054707

0.173768

0.191312

0.186021

0.802005

0.77555

0.753551

0.710944

0.68616

0.629351

0

0.166966

0.483417

10,794

310

78

34.819355

0.413917

0.001946

0

0.5

0

0.082444

0.008356

0

0.113971

1

0.113971

false

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0.136029

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null

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1

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null

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8

574e5de1f23065be99d681f0425ed5fae7b1fe47

111,564

py

Python

scripts/securitygroup/test_regression.py

vkolli/contrail-test-perf

db04b8924a2c330baabe3059788b149d957a7d67

[ "Apache-2.0" ]

1

2017-06-13T04:42:34.000Z

scripts/securitygroup/test_regression.py

vkolli/contrail-test-perf

db04b8924a2c330baabe3059788b149d957a7d67

[ "Apache-2.0" ]

null

scripts/securitygroup/test_regression.py

vkolli/contrail-test-perf

db04b8924a2c330baabe3059788b149d957a7d67

[ "Apache-2.0" ]

null

import unittest from tcutils.wrappers import preposttest_wrapper from vnc_api.vnc_api import NoIdError from verify import VerifySecGroup from policy_test import PolicyFixture from vn_test import MultipleVNFixture from vm_test import MultipleVMFixture from base import BaseSGTest from common.policy.config import ConfigPolicy from security_group import SecurityGroupFixture,get_secgrp_id_from_name from vn_test import VNFixture from vm_test import VMFixture from tcutils.topo.topo_helper import * import os import sys sys.path.append(os.path.realpath('scripts/flow_tests')) from tcutils.topo.sdn_topo_setup import * import test import sdn_sg_test_topo from tcutils.tcpdump_utils import * from time import sleep from tcutils.util import get_random_name from base_traffic import * from tcutils.util import skip_because import test_regression_basic class SecurityGroupRegressionTests2(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests2, cls).setUpClass() cls.option = 'openstack' def setUp(self): super(SecurityGroupRegressionTests2, self).setUp() self.create_sg_test_resources() def tearDown(self): self.logger.debug("Tearing down SecurityGroupRegressionTests2.") super(SecurityGroupRegressionTests2, self).tearDown() def runTest(self): pass @preposttest_wrapper def test_sec_group_with_proto(self): """ Description: Verify security group with allow specific protocol on all ports and policy with allow all between VN's Steps: 1. create the resources VN,VM,policy,SG 2. update the SG rules with proto tcp(for sg1) and udp(sg2) 3. verify if traffic allowed is as per the proto allowed in SG rule Pass criteria: step 3 should pass """ self.logger.info("Configure the policy with allow any") rules = [ { 'direction': '<>', 'protocol': 'any', 'source_network': self.vn1_name, 'src_ports': [0, -1], 'dest_network': self.vn2_name, 'dst_ports': [0, -1], 'simple_action': 'pass', }, ] self.config_policy_and_attach_to_vn(rules) rule = [{'direction': '<>', 'protocol': 'tcp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'tcp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg1_fix.replace_rules(rule) rule = [{'direction': '<>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg2_fix.replace_rules(rule) self.verify_sec_group_port_proto() return True @preposttest_wrapper def test_sec_group_with_port(self): """ Description: Verify security group with allow specific protocol/port and policy with allow all between VN's Steps: 1. create the resources VN,VM,policy,SG 2. update the SG rules with proto tcp(for sg1) and udp(sg2) and open port 8000-9000 3. verify if traffic allowed is as per the proto/port allowed in SG rule Pass criteria: step 3 should pass """ self.logger.info("Configure the policy with allow any") rules = [ { 'direction': '<>', 'protocol': 'any', 'source_network': self.vn1_name, 'src_ports': [0, -1], 'dest_network': self.vn2_name, 'dst_ports': [0, -1], 'simple_action': 'pass', }, ] self.config_policy_and_attach_to_vn(rules) rule = [{'direction': '<>', 'protocol': 'tcp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 8000, 'end_port': 9000}], 'src_ports': [{'start_port': 8000, 'end_port': 9000}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'tcp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 8000, 'end_port': 9000}], 'dst_ports': [{'start_port': 8000, 'end_port': 9000}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg1_fix.replace_rules(rule) rule = [{'direction': '<>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 8000, 'end_port': 9000}], 'src_ports': [{'start_port': 8000, 'end_port': 9000}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 8000, 'end_port': 9000}], 'dst_ports': [{'start_port': 8000, 'end_port': 9000}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg2_fix.replace_rules(rule) self.verify_sec_group_port_proto(port_test=True) return True #end class SecurityGroupRegressionTests2 class SecurityGroupRegressionTests3(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests3, cls).setUpClass() cls.option = 'openstack' def setUp(self): super(SecurityGroupRegressionTests3, self).setUp() self.create_sg_test_resources() def tearDown(self): self.logger.debug("Tearing down SecurityGroupRegressionTests3.") super(SecurityGroupRegressionTests3, self).tearDown() def runTest(self): pass @preposttest_wrapper def test_sec_group_with_proto_and_policy_to_allow_only_tcp(self): """ Description: Verify security group with allow specific protocol on all ports and policy with allow only TCP between VN's Steps: 1. create the resources VN,VM,policy,SG 2. update the SG rules with proto tcp(for sg1) and udp(sg2) 3. verify if traffic allowed is as per the proto allowed in SG rule and policy Pass criteria: step 3 should pass """ self.logger.info("Configure the policy with allow TCP only rule.") rules = [ { 'direction': '<>', 'protocol': 'tcp', 'source_network': self.vn1_name, 'src_ports': [0, -1], 'dest_network': self.vn2_name, 'dst_ports': [0, -1], 'simple_action': 'pass', }, ] self.config_policy_and_attach_to_vn(rules) rule = [{'direction': '<>', 'protocol': 'tcp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'tcp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg1_fix.replace_rules(rule) rule = [{'direction': '<>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg2_fix.replace_rules(rule) self.verify_sec_group_with_udp_and_policy_with_tcp() return True @preposttest_wrapper def test_sec_group_with_proto_and_policy_to_allow_only_tcp_ports(self): """ Description: Verify security group with allow specific protocol on all ports and policy with allow only TCP on specifif ports between VN's Steps: 1. create the resources VN,VM,policy,SG 2. update the SG rules with proto tcp(for sg1) and udp(sg2) 3. verify if traffic allowed is as per the proto allowed in SG rule and port in policy Pass criteria: step 3 should pass """ self.logger.info( "Configure the policy with allow TCP port 8000/9000 only rule.") rules = [ { 'direction': '<>', 'protocol': 'tcp', 'source_network': self.vn1_name, 'src_ports': [8000, 8000], 'dest_network': self.vn2_name, 'dst_ports': [9000, 9000], 'simple_action': 'pass', }, ] self.config_policy_and_attach_to_vn(rules) rule = [{'direction': '<>', 'protocol': 'tcp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'tcp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg1_fix.replace_rules(rule) rule = [{'direction': '<>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg2_fix.replace_rules(rule) self.verify_sec_group_with_udp_and_policy_with_tcp_port() return True #end class SecurityGroupRegressionTests3 class SecurityGroupRegressionTests4(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests4, cls).setUpClass() cls.option = 'openstack' def runTest(self): pass @preposttest_wrapper @skip_because(feature='multi-subnet') def test_vn_compute_sg_comb(self): """ Description: Verify traffic between intra/inter VN,intra/inter compute and same/diff default/user-define SG Steps: 1. define the topology for intra/inter VN,intra/inter compute and same/diff default/user-define SG 2. create the resources as defined in the topo 3. verify the traffic Pass criteria: step 3 should pass """ topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_4vn_xvm_config self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) try: # provided by wrapper module if run in parallel test env topo = topology_class_name( project=self.project.project_name, username=self.project.username, password=self.project.password, compute_node_list=self.connections.orch.get_hosts(),config_option=self.option) except (AttributeError,NameError): topo = topology_class_name(compute_node_list=self.connections.orch.get_hosts(),config_option=self.option) # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(VmToNodeMapping=topo.vm_node_map,config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] self.start_traffic_and_verify_negative_cases(topo_obj, config_topo) return True #end test_vn_compute_sg_comb #end class SecurityGroupRegressionTests4 class SecurityGroupRegressionTests5(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests5, cls).setUpClass() cls.option = 'openstack' def setUp(self): super(SecurityGroupRegressionTests5, self).setUp() self.create_sg_test_resources() def tearDown(self): self.logger.debug("Tearing down SecurityGroupRegressionTests2.") super(SecurityGroupRegressionTests5, self).tearDown() def runTest(self): pass @preposttest_wrapper def test_sec_group_with_proto_double_rules_sg1(self): """ Description: Verify security group with allow tcp/udp protocol on all ports and policy with allow all between VN's Steps: 1. create the resources VN,VM,policy,SG 2. update the SG rules with proto tcp/udp 3. verify if traffic allowed is as per the proto allowed in SG rule Pass criteria: step 3 should pass """ self.logger.info("Configure the policy with allow any") rules = [ { 'direction': '<>', 'protocol': 'any', 'source_network': self.vn1_name, 'src_ports': [0, -1], 'dest_network': self.vn2_name, 'dst_ports': [0, -1], 'simple_action': 'pass', }, ] self.config_policy_and_attach_to_vn(rules) rule = [{'direction': '<>', 'protocol': 'tcp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'tcp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg1_fix.replace_rules(rule) rule = [{'direction': '<>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] self.sg2_fix.replace_rules(rule) self.verify_sec_group_port_proto(double_rule=True) return True #end test_sec_group_with_proto_double_rules_sg1 @preposttest_wrapper def test_default_sg(self): """ Description: test default security group Steps: 1. try to delete default sg, should fail 2. add/delete rules and verify the rules with traffic Pass criteria: step 1 and 2 should pass """ self.logger.info("Configure the policy with allow any") rules = [ { 'direction': '<>', 'protocol': 'any', 'source_network': self.vn1_name, 'src_ports': [0, -1], 'dest_network': self.vn2_name, 'dst_ports': [0, -1], 'simple_action': 'pass', }, ] self.config_policy_and_attach_to_vn(rules) #try to delete default sg secgrp_fq_name = ':'.join(['default-domain', self.inputs.project_name, 'default']) sg_id = get_secgrp_id_from_name( self.connections, secgrp_fq_name) try: self.orch.delete_security_group(sg_id) except Exception, msg: self.logger.info(msg) self.logger.info( "Not able to delete the default security group as expected") else: try: secgroup = self.vnc_lib.security_group_read( fq_name=secgrp_fq_name) self.logger.info( "Not able to delete the default security group as expected") except NoIdError: errmsg = "default Security group deleted" self.logger.error(errmsg) assert False, errmsg #delete egress rule and add new rules and verify with traffic self.sg1_fix.delete_all_rules(sg_id) rule = [{'direction': '<>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '10.1.1.0', 'ip_prefix_len': 24}}, {'subnet': {'ip_prefix': '20.1.1.0', 'ip_prefix_len': 24}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] secgrp_rules = self.sg1_fix.create_sg_rule(sg_id,secgrp_rules=rule) assert secgrp_rules sender = (self.vm1_fix, self.sg2_fix.secgrp_name) receiver = (self.vm6_fix, 'default') self.assert_traffic(sender, receiver, 'udp', 8000, 9000, 'pass') #revert back default sg self.sg1_fix.delete_all_rules(sg_id) rule = [{'direction': '<>', 'protocol': 'any', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '<>', 'protocol': 'any', 'src_addresses': [{'security_group':secgrp_fq_name}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] secgrp_rules = self.sg1_fix.create_sg_rule(sg_id,secgrp_rules=rule) assert secgrp_rules return True #end test_default_sg #end class SecurityGroupRegressionTests5 class SecurityGroupRegressionTests6(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests6, cls).setUpClass() cls.option = 'openstack' def runTest(self): pass @preposttest_wrapper @skip_because(feature='multi-subnet') def test_sg_stateful(self): """ Description: Test if SG is stateful 1. test if inbound traffic without allowed ingress rule is allowed 2. Test if outbound traffic without allowed egress rule is allowed 3. test traffic betwen SG with only ingress/egress rule Steps: 1. define the topology for the test 2. create the resources as defined in the topo 3. verify the traffic Pass criteria: step 3 should pass """ topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_config self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo_sg_stateful( project=self.project.project_name, username=self.project.username, password=self.project.password,config_option=self.option) except (AttributeError,NameError): topo.build_topo_sg_stateful(config_option=self.option) # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] self.start_traffic_and_verify(topo_obj, config_topo, traffic_reverse=False) return True #end test_sg_stateful @preposttest_wrapper @skip_because(feature='multi-tenant') def test_sg_multiproject(self): """ Description: Test SG across projects Steps: 1. define the topology for the test 2. create the resources as defined in the topo 3. verify the traffic Pass criteria: step 3 should pass """ topology_class_name = None result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_config_multiproject self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() self.topo = topo # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} topo_objs = {} config_topo = {} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.sdn_topo_setup(config_option=self.option) self.assertEqual(out['result'], True, out['msg']) if out['result'] == True: topo_objs, config_topo, vm_fip_info = out['data'] self.start_traffic_and_verify_multiproject(topo_objs, config_topo, traffic_reverse=False) return True #end test_sg_multiproject @preposttest_wrapper @skip_because(feature='multi-subnet') def test_sg_no_rule(self): """ Description: Test SG without any rule, it should deny all traffic Steps: 1. define the topology for the test 2. create the resources as defined in the topo 3. verify the traffic denied Pass criteria: step 3 should pass """ topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_1vn_2vm_config self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo( project=self.project.project_name, username=self.project.username, password=self.project.password,config_option=self.option) except (AttributeError,NameError): topo.build_topo(config_option=self.option) # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] self.start_traffic_and_verify(topo_obj, config_topo, traffic_reverse=True) return True #end test_sg_no_rule #end class SecurityGroupRegressionTests6 class SecurityGroupRegressionTests7(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests7, cls).setUpClass() cls.option = 'openstack' def runTest(self): pass @preposttest_wrapper def test_icmp_error_handling1(self): """ Description: Test ICMP error handling 1. ingress-udp from same SG, egress-all 2. Test with SG rule, ingress-egress-udp only 3. Test with SG rule, ingress-egress-all Steps: 1. define the topology for the test 2. create the resources as defined in the topo 3. verify the traffic for each of the cases mentioned in description Pass criteria: step 3 should pass """ topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_icmp_error_handling self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo( project=self.project.project_name, username=self.project.username, password=self.project.password,config_option=self.option) except (AttributeError,NameError): topo.build_topo(config_option=self.option) # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] #Test SG rule, ingress-udp same SG, egress-all port = 10000 pkt_cnt = 10 src_vm_name = 'vm1' dst_vm_name = 'vm3' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] if self.option == 'openstack': src_vn_fq_name = src_vn_fix.vn_fq_name else: src_vn_fq_name = ':'.join(src_vn_fix._obj.get_fq_name()) #start tcpdump on src VM filters = '\'(icmp[0]=3 and icmp[1]=3 and src host %s and dst host %s)\'' % (dst_vm_fix.vm_ip, src_vm_fix.vm_ip) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) #start traffic sender, receiver = self.start_traffic_scapy(src_vm_fix, dst_vm_fix, 'udp', port, port,recvr=False) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap) #stop traffic sent, recv = self.stop_traffic_scapy(sender, receiver,recvr=False) #Test with SG rule, ingress-egress-udp only rule = [{'direction': '>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][topo_obj.sg_list[0]].replace_rules(rule) #start tcpdump on src VM filters = '\'(icmp[0]=3 and icmp[1]=3 and src host %s and dst host %s)\'' % (dst_vm_fix.vm_ip, src_vm_fix.vm_ip) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) #start traffic sender, receiver = self.start_traffic_scapy(src_vm_fix, dst_vm_fix, 'udp', port, port,recvr=False) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap) #stop traffic sent, recv = self.stop_traffic_scapy(sender, receiver,recvr=False) #Test with SG rule, ingress-egress-all dst_vm_fix = config_topo['vm']['vm2'] rule = [{'direction': '>', 'protocol': 'any', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'any', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][topo_obj.sg_list[0]].replace_rules(rule) #start tcpdump on src VM filters = '\'(icmp[0]=3 and icmp[1]=3 and src host %s and dst host %s)\'' % (dst_vm_fix.vm_ip, src_vm_fix.vm_ip) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) #start traffic sender, receiver = self.start_traffic_scapy(src_vm_fix, dst_vm_fix, 'udp', port, port,recvr=False) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap) #stop traffic sent, recv = self.stop_traffic_scapy(sender, receiver,recvr=False) return True #end test_icmp_error_handling1 @preposttest_wrapper def test_icmp_error_handling2(self): """ Description: 1. Test ICMP error handling with SG rules egress-udp only 2. Test ICMP error from agent Steps: 1. define the topology for the test 2. create the resources as defined in the topo 3. verify the traffic for each of the cases mentioned in description Pass criteria: step 3 should pass """ topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_icmp_error_handling self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo2( project=self.project.project_name, username=self.project.username, password=self.project.password, compute_node_list=self.connections.orch.get_hosts(),config_option=self.option) except (AttributeError,NameError): topo.build_topo2(compute_node_list=self.connections.orch.get_hosts(),config_option=self.option) # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(VmToNodeMapping=topo.vm_node_map,config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] #Test with SG rule, egress-udp only port = 10000 pkt_cnt = 10 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] if self.option == 'openstack': src_vn_fq_name = src_vn_fix.vn_fq_name else: src_vn_fq_name = ':'.join(src_vn_fix._obj.get_fq_name()) #start tcpdump on src VM filters = '\'(icmp[0]=3 and icmp[1]=3 and src host %s and dst host %s)\'' % (dst_vm_fix.vm_ip, src_vm_fix.vm_ip) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) #start traffic sender, receiver = self.start_traffic_scapy(src_vm_fix, dst_vm_fix, 'udp', port, port,recvr=False) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap) #stop traffic sent, recv = self.stop_traffic_scapy(sender, receiver,recvr=False) #Test ICMP error from agent if len(self.connections.orch.get_hosts()) < 2: self.logger.info("Skipping second case(Test ICMP error from agent), \ this test needs atleast 2 compute nodes") raise self.skipTest("Skipping second case(Test ICMP error from agent), \ this test needs atleast 2 compute nodes") return True rule = [{'direction': '>', 'protocol': 'icmp', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'icmp', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][topo_obj.sg_list[0]].replace_rules(rule) vn1_name = "test_vnv6sr" vn1_net = ['2001::101:0/120'] #vn1_fixture = self.config_vn(vn1_name, vn1_net) vn1_fixture = self.useFixture(VNFixture( project_name=self.inputs.project_name, connections=self.connections, vn_name=vn1_name, inputs=self.inputs, subnets=vn1_net)) assert vn1_fixture.verify_on_setup() vn2_name = "test_vnv6dn" vn2_net = ['2001::201:0/120'] #vn2_fixture = self.config_vn(vn2_name, vn2_net) vn2_fixture = self.useFixture(VNFixture( project_name=self.inputs.project_name, connections=self.connections, vn_name=vn2_name, inputs=self.inputs, subnets=vn2_net)) assert vn2_fixture.verify_on_setup() vm1_name = 'source_vm' vm2_name = 'dest_vm' #vm1_fixture = self.config_vm(vn1_fixture, vm1_name) #vm2_fixture = self.config_vm(vn2_fixture, vm2_name) self.inputs.set_af('dual') vm1_fixture = self.useFixture(VMFixture( project_name=self.inputs.project_name, connections=self.connections, vn_obj=vn1_fixture.obj, vm_name=vm1_name, node_name=None, image_name='ubuntu-traffic', flavor='contrail_flavor_small')) vm2_fixture = self.useFixture(VMFixture( project_name=self.inputs.project_name, connections=self.connections, vn_obj=vn2_fixture.obj, vm_name=vm2_name, node_name=None, image_name='ubuntu-traffic', flavor='contrail_flavor_small')) assert vm1_fixture.verify_on_setup() assert vm2_fixture.verify_on_setup() vm1_fixture.wait_till_vm_is_up() vm2_fixture.wait_till_vm_is_up() rule = [ { 'direction': '<>', 'protocol': 'any', 'source_network': vn1_name, 'src_ports': [0, -1], 'dest_network': vn2_name, 'dst_ports': [0, -1], 'simple_action': 'pass', }, ] policy_name = 'allow_all' policy_fixture = self.config_policy(policy_name, rule) vn1_policy_fix = self.attach_policy_to_vn( policy_fixture, vn1_fixture) vn2_policy_fix = self.attach_policy_to_vn( policy_fixture, vn2_fixture) if self.option == 'openstack': src_vn_fq_name = src_vn_fix.vn_fq_name else: src_vn_fq_name = ':'.join(src_vn_fix._obj.get_fq_name()) self.logger.info("Increasing MTU on src VM and ping with bigger size and reverting MTU") cmd_ping = ('ping -M want -s 2500 -c 10 %s | grep \"Frag needed and DF set\"' % (dst_vm_fix.vm_ip)) # cmd_tcpdump = 'tcpdump -vvv -c 5 -ni eth0 -v icmp > /tmp/op1.log' output = src_vm_fix.run_cmd_on_vm(cmds=['''netstat -anr |grep ^0.0.0.0 | awk '{ print $2 }' '''], as_sudo=True) gw = output.values()[0].split('\r\n')[-1] filters = 'icmp' session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) cmds = ['ifconfig eth0 mtu 3000', cmd_ping, 'ifconfig eth0 mtu 1500'] output = src_vm_fix.run_cmd_on_vm(cmds=cmds, as_sudo=True, as_daemon=True) cmd = 'tcpdump -r %s' % pcap cmd_check_icmp, err = execute_cmd_out(session, cmd, self.logger) cmd_df = re.search('need to frag', cmd_check_icmp) self.logger.debug("output for ping cmd: %s" % output[cmd_ping]) cmd_next_icmp = re.search('.+ seq 2, length (\d\d\d\d).*', cmd_check_icmp) icmpmatch = ("%s > %s: ICMP %s unreachable - need to frag" % (gw, src_vm_fix.vm_ip, dst_vm_fix.vm_ip)) if not ((icmpmatch in cmd_check_icmp) and ("need to frag" in cmd_df.group(0)) and (cmd_next_icmp.group(1) < '1500') and ("Frag needed and DF set" in output[cmd_ping])): self.logger.error("expected ICMP error for type 3 code 4 not found") stop_tcpdump_for_vm_intf(self, session, pcap) return False stop_tcpdump_for_vm_intf(self, session, pcap) self.logger.info("increasing MTU on src VM and ping6 with bigger size and reverting MTU") cmd_ping = 'ping6 -s 2500 -c 10 %s | grep \"Packet too big\"' % (vm2_fixture.vm_ip) src_vn_fq_name = vn1_fixture.vn_fq_name gw = vm1_fixture.vm_ip gw = gw.split(':') gw[-1] = '1' gw = ':'.join(gw) filters = 'icmp6' session, pcap = start_tcpdump_for_vm_intf(self, vm1_fixture, src_vn_fq_name, filters = filters) cmds = ['ifconfig eth0 mtu 3000', cmd_ping, 'ifconfig eth0 mtu 1500'] output = vm1_fixture.run_cmd_on_vm(cmds=cmds, as_sudo=True, as_daemon=True) cmd = 'tcpdump -r %s' % pcap cmd_check_icmp, err = execute_cmd_out(session, cmd, self.logger) self.logger.debug("output for ping cmd: %s" % output[cmd_ping]) cmd_next_icmp = re.search('.+ ICMP6, packet too big, mtu (\d\d\d\d).*', cmd_check_icmp) icmpmatch = ("ICMP6, packet too big") if not ((icmpmatch in cmd_check_icmp) and (cmd_next_icmp.group(1) < '1500') and ("Packet too big" in output[cmd_ping])): self.logger.error("expected ICMP6 error for type 2 packet too big message not found") stop_tcpdump_for_vm_intf(self, session, pcap) # output = vm1_fixture.run_cmd_on_vm(cmds='rm /tmp/op.log', as_sudo=True) return False stop_tcpdump_for_vm_intf(self, session, pcap) return True #end test_icmp_error_handling2 @preposttest_wrapper @skip_because(feature='service-instance') def test_icmp_error_handling_from_mx_with_si(self): """ Description: Test ICMP error handling from MX with SI in the middle 1. uses traceroute util on the VM Steps: 1. define the topology for the test 2. create the resources as defined in the topo 3. copy the traceroute pkg to VM and install 4. run the traceroute to 8.8.8.8 5. verify through tcpdump if icmp error recvd on VM Pass criteria: step 5 should pass """ if ('MX_GW_TEST' not in os.environ) or (('MX_GW_TEST' in os.environ) and (os.environ.get('MX_GW_TEST') != '1')): self.logger.info( "Skipping Test. Env variable MX_GW_TEST is not set. Skipping the test") raise self.skipTest( "Skipping Test. Env variable MX_GW_TEST is not set. Skipping the test") return True public_vn_info = {'subnet':[self.inputs.fip_pool], 'router_asn':self.inputs.router_asn, 'rt_number':self.inputs.mx_rt} topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_mx_with_si self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo( project=self.project.project_name, username=self.project.username, password=self.project.password, public_vn_info=public_vn_info,config_option=self.option) except (AttributeError,NameError): topo.build_topo(public_vn_info=public_vn_info,config_option=self.option) # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(skip_verify='no',config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] pol_fix = config_topo['policy'][topo_obj.policy_list[0]] if self.option == 'openstack': policy_id = pol_fix.policy_obj['policy']['id'] new_policy_entries = config_topo['policy'][topo_obj.policy_list[1]].policy_obj['policy']['entries'] data = {'policy': {'entries': new_policy_entries}} pol_fix.update_policy(policy_id, data) else: policy_name = topo_obj.policy_list[0] proj_obj = pol_fix._conn_drv.project_read(['default-domain',self.project.project_name]) new_policy_entries = pol_fix._conn_drv.network_policy_read(['default-domain', self.project.project_name, topo_obj.policy_list[1]]).network_policy_entries net_policy_obj = NetworkPolicy( policy_name, network_policy_entries=new_policy_entries, parent_obj=proj_obj) pol_fix._conn_drv.network_policy_update(net_policy_obj) src_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] if self.option == 'openstack': src_vn_fq_name = src_vn_fix.vn_fq_name else: src_vn_fq_name = ':'.join(src_vn_fix._obj.get_fq_name()) pkg = 'traceroute_2.0.18-1_amd64.deb' self.logger.info("copying traceroute pkg to the compute node.") path = os.getcwd() + '/tcutils/pkgs/' + pkg host_compute = {'username': self.inputs.username, 'password': self.inputs.password, 'ip': src_vm_fix.vm_node_ip} copy_file_to_server(host_compute,path, '/tmp',pkg) self.logger.info("copying traceroute from compute node to VM") with settings(host_string='%s@%s' % (self.inputs.username, src_vm_fix.vm_node_ip), password=self.inputs.password, warn_only=True, abort_on_prompts=False): path = '/tmp/' + pkg output = fab_put_file_to_vm( host_string='%s@%s' % (src_vm_fix.vm_username, src_vm_fix.local_ip), password=src_vm_fix.vm_password, src=path, dest='/tmp') self.logger.info("installing traceroute") cmd = 'dpkg -i /tmp/' + pkg output_cmd_dict = src_vm_fix.run_cmd_on_vm(cmds=[cmd], as_sudo=True) assert "Setting up traceroute" in output_cmd_dict[cmd], "traceroute pkg installation error, output:%s" % output_cmd_dict[cmd] self.logger.info("starting tcpdump on src VM") filters = '\'(icmp[0]=11 and icmp[1]=0)\'' session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) self.logger.info("starting traceroute to out of cluster, 8.8.8.8") cmd = 'traceroute 8.8.8.8' for i in range(0,4): output_cmd_dict = src_vm_fix.run_cmd_on_vm(cmds=[cmd], as_sudo=True) self.logger.info(output_cmd_dict[cmd]) if verify_tcpdump_count(self, session, pcap): return True return False #end test_icmp_error_handling_from_mx_with_si @preposttest_wrapper def test_icmp_error_payload_matching(self): """ Description: Test ICMP error handling with payload diff. from original packet 1. icmp pakcet with payload matching should be accepted and others should be denied Steps: 1. define the topology for the test 2. create the resources as defined in the topo 3. send the traffic from sender to unreachable port on recvr side(port 10000 used here), recvr will send icmp error to sender for "destination port unreachable" 4. from recvr side send many other icmp error types in loop 5. sender should recv only icmp error mentioned in step 3 and should NOT recv errors mentioned in step4 Pass criteria: step 5 should pass """ topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_icmp_error_handling self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo2( project=self.project.project_name, username=self.project.username, password=self.project.password, compute_node_list=self.connections.orch.get_hosts(),config_option=self.option) except (AttributeError,NameError): topo.build_topo2(compute_node_list=self.connections.orch.get_hosts(),config_option=self.option) # # Test setup: Configure policy, VN, & VM # return {'result':result, 'msg': err_msg, 'data': [self.topo, config_topo]} # Returned topo is of following format: # config_topo= {'policy': policy_fixt, 'vn': vn_fixture, 'vm': vm_fixture} setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(VmToNodeMapping=topo.vm_node_map,config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] #Test with SG rule, egress-udp only and also send diff ICMP error with diff payload port = 10000 pkt_cnt = 2 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] if self.option == 'openstack': src_vn_fq_name = src_vn_fix.vn_fq_name else: src_vn_fq_name = ':'.join(src_vn_fix._obj.get_fq_name()) #start tcpdump on src VM filters = '\'(icmp[0]=3 and icmp[1]=3)\'' session1, pcap1 = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) #start traffic sender1, receiver1 = self.start_traffic_scapy(src_vm_fix, dst_vm_fix, 'udp', port, port,recvr=False) icmp_code = 0 for icmp_type in xrange(0,3): #start tcpdump on src VM filters = '\'(icmp[0] = %s and icmp[1] = %s)\'' % (icmp_type, icmp_code) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) sender, receiver = self.start_traffic_scapy(dst_vm_fix, src_vm_fix, 'icmp', port, port, payload="payload", icmp_type=icmp_type, icmp_code=icmp_code,count=pkt_cnt) sent, recv = self.stop_traffic_scapy(sender, receiver) assert sent != 0, "sent count is ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap, exp_count=0), "pkt count in tcpdump is not ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #type 3 , code (0,3) icmp_type = 3 for icmp_code in xrange(0,3): #start tcpdump on src VM filters = '\'(icmp[0] = %s and icmp[1] = %s)\'' % (icmp_type, icmp_code) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) sender, receiver = self.start_traffic_scapy(dst_vm_fix, src_vm_fix, 'icmp', port, port, payload="payload", icmp_type=icmp_type, icmp_code=icmp_code,count=pkt_cnt) sent, recv = self.stop_traffic_scapy(sender, receiver) assert sent != 0, "sent count is ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap, exp_count=0), "pkt count in tcpdump is not ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #type 3 , code (4,15) icmp_type = 3 for icmp_code in xrange(4,16): #start tcpdump on src VM filters = '\'(icmp[0] = %s and icmp[1] = %s)\'' % (icmp_type, icmp_code) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) sender, receiver = self.start_traffic_scapy(dst_vm_fix, src_vm_fix, 'icmp', port, port, payload="payload", icmp_type=icmp_type, icmp_code=icmp_code,count=pkt_cnt) sent, recv = self.stop_traffic_scapy(sender, receiver) assert sent != 0, "sent count is ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap, exp_count=0), "pkt count in tcpdump is not ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #type (4,11), code 0 icmp_code = 0 for icmp_type in xrange(4,12): #start tcpdump on src VM filters = '\'(icmp[0] = %s and icmp[1] = %s)\'' % (icmp_type, icmp_code) session, pcap = start_tcpdump_for_vm_intf(self, src_vm_fix, src_vn_fq_name, filters = filters) sender, receiver = self.start_traffic_scapy(dst_vm_fix, src_vm_fix, 'icmp', port, port, payload="payload", icmp_type=icmp_type, icmp_code=icmp_code,count=pkt_cnt) sent, recv = self.stop_traffic_scapy(sender, receiver) assert sent != 0, "sent count is ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session, pcap, exp_count=0), "pkt count in tcpdump is not ZERO for icmp type %s and code %s" % (icmp_type, icmp_code) #verify packet count and stop tcpdump assert verify_tcpdump_count(self, session1, pcap1) #stop traffic sent, recv = self.stop_traffic_scapy(sender1, receiver1,recvr=False) return True #end test_icmp_error_payload_matching #end class SecurityGroupRegressionTests7 class SecurityGroupRegressionTests8(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests8, cls).setUpClass() cls.option = 'openstack' def runTest(self): pass @preposttest_wrapper def test_flow_to_sg_rule_mapping(self): """ Description: test flow to security group rule uuid mapping for 1. default SG 2. user-defined SG Steps: 1. create resources as defined in topology 2. start traffic for specific protocol which matches with specific security group rule 3. get flow records from agent and verify if sg rule uuid matches with corresponding ingress/egress rule id Pass criteria: step 3 should PASS """ topology_class_name = sdn_sg_test_topo.sdn_topo_flow_to_sg_rule_mapping topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo( project=self.project.project_name, username=self.project.username, password=self.project.password, compute_node_list=self.inputs.compute_ips, config_option=self.option) except (AttributeError, NameError): topo.build_topo(compute_node_list=self.inputs.compute_ips, config_option=self.option) setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(VmToNodeMapping=topo.vm_node_map, config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] proto = 'udp' port = 10000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] default_secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, 'default'])) # test with default SG traffic_obj = BaseTraffic.factory(proto=proto) assert traffic_obj assert traffic_obj.start(src_vm_fix, dst_vm_fix, proto, port, port) assert self.verify_flow_to_sg_rule_mapping( src_vm_fix, dst_vm_fix, src_vn_fix, dst_vn_fix, default_secgrp_id, proto, port) sent, recv = traffic_obj.stop() # test with user-defined SG sg_name = topo_obj.sg_list[0] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) src_vm_fix.remove_security_group(secgrp=default_secgrp_id) dst_vm_fix.remove_security_group(secgrp=default_secgrp_id) src_vm_fix.add_security_group(secgrp=secgrp_id) dst_vm_fix.add_security_group(secgrp=secgrp_id) traffic_obj = BaseTraffic.factory(proto=proto) assert traffic_obj assert traffic_obj.start(src_vm_fix, dst_vm_fix, proto, port, port) assert self.verify_flow_to_sg_rule_mapping( src_vm_fix, dst_vm_fix, src_vn_fix, dst_vn_fix, secgrp_id, proto, port) sent, recv = traffic_obj.stop() return True # end test_flow_to_sg_rule_mapping @preposttest_wrapper def test_flow_to_sg_rule_mapping_multiple_rules(self): """ Description: test flow to security group rule uuid mapping for 1. SG with multiple rules and diff active flows matching diff. rules 2. Multiple SG attached to VMs and diff active flows matching diff. SG Steps: 1. create resources as defined in topology 2. start traffic for specific protocol which matches with specific security group rule 3. get flow records from agent and verify if sg rule uuid matches with corresponding ingress/egress rule id Pass criteria: step 3 should PASS """ topology_class_name = sdn_sg_test_topo.sdn_topo_flow_to_sg_rule_mapping topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo2( project=self.project.project_name, username=self.project.username, password=self.project.password, compute_node_list=self.inputs.compute_ips, config_option=self.option) except (AttributeError, NameError): topo.build_topo2(compute_node_list=self.inputs.compute_ips, config_option=self.option) setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(VmToNodeMapping=topo.vm_node_map, config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] port = 10000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] # start traffic traffic_obj_udp = BaseTraffic.factory(proto='udp') assert traffic_obj_udp assert traffic_obj_udp.start(src_vm_fix, dst_vm_fix, 'udp', port, port) traffic_obj_tcp = BaseTraffic.factory(proto='tcp') assert traffic_obj_tcp assert traffic_obj_tcp.start(src_vm_fix, dst_vm_fix, 'tcp', port, port) sender_icmp, receiver_icmp = self.start_traffic_scapy( src_vm_fix, dst_vm_fix, 'icmp', port, port, payload="payload") sg_name = topo_obj.sg_list[0] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) assert self.verify_flow_to_sg_rule_mapping( src_vm_fix, dst_vm_fix, src_vn_fix, dst_vn_fix, secgrp_id, 'udp', port) sg_name = topo_obj.sg_list[1] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) assert self.verify_flow_to_sg_rule_mapping( src_vm_fix, dst_vm_fix, src_vn_fix, dst_vn_fix, secgrp_id, 'tcp', port) port = 0 sg_name = topo_obj.sg_list[0] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) assert self.verify_flow_to_sg_rule_mapping( src_vm_fix, dst_vm_fix, src_vn_fix, dst_vn_fix, secgrp_id, 'icmp', port) # stop traffic sent, recv = traffic_obj_udp.stop() sent, recv = traffic_obj_tcp.stop() sent, recv = self.stop_traffic_scapy(sender_icmp, receiver_icmp) return True #end test_flow_to_sg_rule_mapping_multiple_rules @preposttest_wrapper def test_flow_to_sg_rule_mapping_intra_vn(self): """ Description: test flow to security group rule uuid mapping for 1. intra VN traffic with diff SG in src and dst VM Steps: 1. create resources as defined in topology 2. start traffic for specific protocol which matches with specific security group rule 3. get flow records from agent and verify if sg rule uuid matches with corresponding ingress/egress rule id Pass criteria: step 3 should PASS """ topology_class_name = sdn_sg_test_topo.sdn_topo_icmp_error_handling topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo2( project=self.project.project_name, username=self.project.username, password=self.project.password, config_option=self.option) except (AttributeError, NameError): topo.build_topo2(config_option=self.option) setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] rule = [{'direction': '>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][topo_obj.sg_list[0]].replace_rules(rule) proto = 'udp' port = 10000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] src_sg_name = topo_obj.sg_list[0] dst_sg_name = topo_obj.sg_list[1] if self.option == 'openstack': src_vn_fq_name = src_vn_fix.vn_fq_name dst_vn_fq_name = dst_vn_fix.vn_fq_name else: src_vn_fq_name = ':'.join(src_vn_fix._obj.get_fq_name()) dst_vn_fq_name = ':'.join(dst_vn_fix._obj.get_fq_name()) secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, src_sg_name])) # start traffic traffic_obj = BaseTraffic.factory(proto=proto) assert traffic_obj assert traffic_obj.start(src_vm_fix, dst_vm_fix, proto, port, port) # get the egress rule uuid rule_uuid = None rules = list_sg_rules(self.connections, secgrp_id) for rule in rules: if rule['direction'] == 'egress' and (rule['ethertype'] == 'IPv4' or \ rule['remote_ip_prefix'] == '0.0.0.0/0') and \ (rule['protocol'] == 'any' or rule['protocol'] == proto): rule_uuid = rule['id'] break assert rule_uuid, "Egress rule id could not be found" test_result = True nh_dst = dst_vm_fix.tap_intf[dst_vn_fq_name]['flow_key_idx'] nh = src_vm_fix.tap_intf[src_vn_fq_name]['flow_key_idx'] # verify forward flow on src compute node if not self.fetch_flow_verify_sg_uuid( nh, src_vm_fix, dst_vm_fix, port, port, '17', rule_uuid, src_vm_fix.vm_node_ip): test_result = False # verify reverse flow on src compute node if src_vm_fix.vm_node_ip == dst_vm_fix.vm_node_ip: nh = nh_dst if not self.fetch_flow_verify_sg_uuid( nh, dst_vm_fix, src_vm_fix, port, port, '17', rule_uuid, src_vm_fix.vm_node_ip): test_result = False if src_vm_fix.vm_node_ip != dst_vm_fix.vm_node_ip: secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, dst_sg_name])) # get the ingress rule uuid rule_uuid = None rules = list_sg_rules(self.connections, secgrp_id) for rule in rules: if rule['direction'] == 'ingress' and \ (rule['protocol'] == 'any' or rule['protocol'] == proto): rule_uuid = rule['id'] break assert rule_uuid, "Ingress rule id could not be found" # verify forward flow on dst compute node if not self.fetch_flow_verify_sg_uuid( nh_dst, src_vm_fix, dst_vm_fix, port, port, '17', rule_uuid, dst_vm_fix.vm_node_ip): test_result = False # verify reverse flow on dst compute node if not self.fetch_flow_verify_sg_uuid( nh_dst, dst_vm_fix, src_vm_fix, port, port, '17', rule_uuid, dst_vm_fix.vm_node_ip): test_result = False # stop traffic sent, recv = traffic_obj.stop() assert test_result return True #end test_flow_to_sg_rule_mapping_intra_vn @preposttest_wrapper def test_verify_sg_rule_uuid_in_control_api(self): """ 1. Verify uuid for each sg rule in api/control introspect and neutron cli""" topology_class_name = None # # Get config for test from topology result = True msg = [] if not topology_class_name: topology_class_name = sdn_sg_test_topo.sdn_topo_icmp_error_handling self.logger.info("Scenario for the test used is: %s" % (topology_class_name)) topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo2( project=self.project.project_name, username=self.project.username, password=self.project.password, config_option=self.option) except (AttributeError, NameError): topo.build_topo2(config_option=self.option) setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(config_option=self.option) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] rule = [{'direction': '>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], 'ethertype': 'IPv4' }, {'direction': '>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], 'ethertype': 'IPv4' }] config_topo['sec_grp'][topo_obj.sg_list[0]].replace_rules(rule) sg_list = ['default', topo_obj.sg_list[0]] proto = 'udp' try: prj_name = self.project.project_name except (AttributeError, NameError): prj_name = 'admin' for sg_name in sg_list: secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) # get the egress and ingress rule uuid egress_ipv4_id = None egress_ipv6_id = None ingress_ipv4_id = None ingress_ipv6_id = None rules = list_sg_rules(self.connections, secgrp_id) for rule in rules: if rule['direction'] == 'egress' and rule['ethertype'] == 'IPv4': egress_ipv4_id = rule['id'] elif rule['direction'] == 'ingress' and rule['ethertype'] == 'IPv4': ingress_ipv4_id = rule['id'] elif rule['direction'] == 'ingress' and rule['ethertype'] == 'IPv6': ingress_ipv6_id = rule['id'] elif rule['direction'] == 'egress' and rule['ethertype'] == 'IPv6': egress_ipv6_id = rule['id'] assert egress_ipv4_id, "Egress rule id could not be found" assert ingress_ipv4_id, "Ingress rule id could not be found" # get SG rule uuid from api and match with neutron uuid api_secgrp_obj = self.api_s_inspect.get_cs_secgrp( project=prj_name, secgrp=sg_name, refresh=True) uuid_egress_ipv4 = None uuid_ingress_ipv4 = None uuid_egress_ipv6 = None uuid_ingress_ipv6 = None for rule in api_secgrp_obj['security-group']['security_group_entries']['policy_rule']: if rule['src_addresses'][0]['security_group'] == "local" and rule['ethertype'] == 'IPv4': uuid_egress_ipv4 = rule['rule_uuid'] elif rule['dst_addresses'][0]['security_group'] == "local" and rule['ethertype'] == 'IPv4': uuid_ingress_ipv4 = rule['rule_uuid'] elif rule['src_addresses'][0]['security_group'] == "local" and rule['ethertype'] == 'IPv6': uuid_egress_ipv6 = rule['rule_uuid'] elif rule['dst_addresses'][0]['security_group'] == "local" and rule['ethertype'] == 'IPv6': uuid_ingress_ipv6 = rule['rule_uuid'] assert uuid_egress_ipv4 == egress_ipv4_id, "egress IPv4 rule uuid is not same in API and \ neutron for SG:%s" % (sg_name) assert uuid_ingress_ipv4 == ingress_ipv4_id, "ingress IPv4 rule uuid is not same in API \ and neutron for SG:%s" % (sg_name) if ingress_ipv6_id: assert ingress_ipv6_id == uuid_ingress_ipv6, "ingress IPv6 rule uuid is not same in API \ and neutron for SG:%s" % (sg_name) if egress_ipv6_id: assert egress_ipv6_id == uuid_egress_ipv6, "egress IPv6 rule uuid is not same in API \ and neutron for SG:%s" % (sg_name) self.logger.info("%s security group rule uuid matches in API with neutron" % (sg_name)) # get SG rule uuid from control node and match with neutron uuid for cn in self.inputs.bgp_ips: uuid_egress_ipv4 = None uuid_ingress_ipv4 = None cn_secgrp_obj = self.cn_inspect[cn].get_cn_sec_grp( project=prj_name, secgrp=sg_name) for rule in cn_secgrp_obj['obj_info'][0]['data']['security-group-entries']: if rule['src-addresses']['security-group'] == 'local' and rule['ethertype'] == 'IPv4': uuid_egress_ipv4 = rule['rule-uuid'] elif rule['dst-addresses']['security-group'] == 'local' and rule['ethertype'] == 'IPv4': uuid_ingress_ipv4 = rule['rule-uuid'] elif rule['src-addresses']['security-group'] == 'local' and rule['ethertype'] == 'IPv6': uuid_egress_ipv6 = rule['rule-uuid'] elif rule['dst-addresses']['security-group'] == 'local' and rule['ethertype'] == 'IPv6': uuid_ingress_ipv6 = rule['rule-uuid'] assert uuid_egress_ipv4 == egress_ipv4_id, "egress rule uuid are not same in control \ and neutron for SG:%s" % (sg_name) assert uuid_ingress_ipv4 == ingress_ipv4_id, "ingress rule uuid are not same in control \ and neutron for SG:%s" % (sg_name) if ingress_ipv6_id: assert ingress_ipv6_id == uuid_ingress_ipv6, "ingress IPv6 rule uuid is not same in control \ and neutron for SG:%s" % (sg_name) if egress_ipv6_id: assert egress_ipv6_id == uuid_egress_ipv6, "egress IPv6 rule uuid is not same in control \ and neutron for SG:%s" % (sg_name) self.logger.info("%s security group rule uuid matches in control with neutron" % (sg_name)) return True # end test_verify_sg_rule_uuid_in_control_api #end class SecurityGroupRegressionTests8 class SecurityGroupRegressionTests9(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests9, cls).setUpClass() cls.option = 'openstack' def runTest(self): pass @preposttest_wrapper def test_add_remove_default_sg_active_flow(self): """ add/remove default SG from VM when flow is active and traffic from both ends""" topology_class_name = sdn_sg_test_topo.sdn_topo_flow_to_sg_rule_mapping topo_obj, config_topo = self.create_topo_setup(topology_class_name, "build_topo") port = 10000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] sg_name = 'default' secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) filters1 = '\'(udp and src host %s and dst host %s)\'' % ( src_vm_fix.vm_ip, dst_vm_fix.vm_ip) filters2 = '\'(tcp and src host %s and dst host %s)\'' % ( dst_vm_fix.vm_ip, src_vm_fix.vm_ip) sender1, receiver1 = self.start_traffic_scapy( src_vm_fix, dst_vm_fix, 'udp', port, port, payload="payload") sender2, receiver2 = self.start_traffic_scapy( dst_vm_fix, src_vm_fix, 'tcp', port, port, payload="payload") assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1) src_vm_fix.remove_security_group(secgrp=secgrp_id) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1, src_exp_count=0, dst_exp_count=0) src_vm_fix.add_security_group(secgrp=secgrp_id) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1) # stop traffic sent, recv = self.stop_traffic_scapy(sender1, receiver1) sent, recv = self.stop_traffic_scapy(sender2, receiver2) return True # end test_add_remove_default_sg_active_flow @preposttest_wrapper def test_add_remove_sg_active_flow1(self): """ add/remove SG from VM when flow is active 1.Traffic from both ends 2.Test for SG with rule with remote as sg for both ingress-egress""" topology_class_name = sdn_sg_test_topo.sdn_topo_flow_to_sg_rule_mapping topo_obj, config_topo = self.create_topo_setup(topology_class_name, "build_topo") sg_allow_all = self.create_sec_group_allow_all() port = 10000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] sg_name = topo_obj.sg_list[0] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) default_sg_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, 'default'])) src_vm_fix.remove_security_group(secgrp=default_sg_id) dst_vm_fix.remove_security_group(secgrp=default_sg_id) src_vm_fix.add_security_group(secgrp=secgrp_id) dst_vm_fix.add_security_group(secgrp=secgrp_id) # ingress-egress from same sg rule = [{'direction': '>', 'protocol': 'udp', 'dst_addresses': [{'security_group': topo_obj.domain + ':' + topo_obj.project + ':' + sg_name}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'udp', 'src_addresses': [{'security_group': topo_obj.domain + ':' + topo_obj.project + ':' + sg_name}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][sg_name].replace_rules(rule) filters1 = '\'(udp and src host %s and dst host %s)\'' % ( src_vm_fix.vm_ip, dst_vm_fix.vm_ip) filters2 = '\'(udp and src host %s and dst host %s)\'' % ( dst_vm_fix.vm_ip, src_vm_fix.vm_ip) sender1, receiver1 = self.start_traffic_scapy( src_vm_fix, dst_vm_fix, 'udp', port, port, payload="payload") sender2, receiver2 = self.start_traffic_scapy( dst_vm_fix, src_vm_fix, 'udp', port, port, payload="payload") assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1) src_vm_fix.remove_security_group(secgrp=secgrp_id) src_vm_fix.add_security_group(secgrp=sg_allow_all) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1, src_exp_count=0, dst_exp_count=0) # stop traffic sent, recv = self.stop_traffic_scapy(sender1, receiver1) sent, recv = self.stop_traffic_scapy(sender2, receiver2) src_vm_fix.remove_security_group(secgrp=sg_allow_all) return True # end test_add_remove_sg_active_flow1 @preposttest_wrapper def test_add_remove_sg_active_flow2(self): """ add/remove SG from VM when flow is active 1.Traffic from both ends 2.Test for SG with egress cidr rule,ingress sg""" topology_class_name = sdn_sg_test_topo.sdn_topo_flow_to_sg_rule_mapping topo_obj, config_topo = self.create_topo_setup(topology_class_name, "build_topo") sg_allow_all = self.create_sec_group_allow_all() port = 10000 port2 = 11000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] sg_name = topo_obj.sg_list[0] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) default_sg_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, 'default'])) src_vm_fix.remove_security_group(secgrp=default_sg_id) dst_vm_fix.remove_security_group(secgrp=default_sg_id) src_vm_fix.add_security_group(secgrp=secgrp_id) dst_vm_fix.add_security_group(secgrp=secgrp_id) # start the traffic from src VM sender1, receiver1 = self.start_traffic_scapy( src_vm_fix, dst_vm_fix, 'udp', port, port, payload="payload") # start the traffic from dst VM sender2, receiver2 = self.start_traffic_scapy( dst_vm_fix, src_vm_fix, 'udp', port2, port2, payload="payload") # ingress from same sg and egress to all rule = [{'direction': '>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'udp', 'src_addresses': [{'security_group': topo_obj.domain + ':' + topo_obj.project + ':' + sg_name}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][sg_name].replace_rules(rule) filters1 = '\'(udp and src host %s and dst host %s)\'' % ( src_vm_fix.vm_ip, dst_vm_fix.vm_ip) filters2 = '\'(udp and src host %s and dst host %s)\'' % ( dst_vm_fix.vm_ip, src_vm_fix.vm_ip) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1) src_vm_fix.remove_security_group(secgrp=secgrp_id) src_vm_fix.add_security_group(secgrp=sg_allow_all) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1, dst_exp_count=0) # stop traffic sent, recv = self.stop_traffic_scapy(sender1, receiver1) sent, recv = self.stop_traffic_scapy(sender2, receiver2) src_vm_fix.remove_security_group(secgrp=sg_allow_all) return True # end test_add_remove_sg_active_flow2 @preposttest_wrapper def test_add_remove_sg_active_flow3(self): """ add/remove SG from VM when flow is active 1. Traffic from both ends 2. Test for SG with ingress cidr and egress sg""" topology_class_name = sdn_sg_test_topo.sdn_topo_flow_to_sg_rule_mapping topo_obj, config_topo = self.create_topo_setup(topology_class_name, "build_topo") sg_allow_all = self.create_sec_group_allow_all() port = 10000 port2 = 11000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] sg_name = topo_obj.sg_list[0] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) default_sg_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, 'default'])) src_vm_fix.remove_security_group(secgrp=default_sg_id) dst_vm_fix.remove_security_group(secgrp=default_sg_id) src_vm_fix.add_security_group(secgrp=secgrp_id) dst_vm_fix.add_security_group(secgrp=secgrp_id) # start the traffic from src VM sender1, receiver1 = self.start_traffic_scapy( src_vm_fix, dst_vm_fix, 'udp', port, port, payload="payload") # start the traffic from dst VM sender2, receiver2 = self.start_traffic_scapy( dst_vm_fix, src_vm_fix, 'udp', port2, port2, payload="payload") # egress to same sg and ingress from all rule = [{'direction': '>', 'protocol': 'udp', 'dst_addresses': [{'security_group': topo_obj.domain + ':' + topo_obj.project + ':' + sg_name}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][sg_name].replace_rules(rule) filters1 = '\'(udp and src host %s and dst host %s)\'' % ( src_vm_fix.vm_ip, dst_vm_fix.vm_ip) filters2 = '\'(udp and src host %s and dst host %s)\'' % ( dst_vm_fix.vm_ip, src_vm_fix.vm_ip) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1) src_vm_fix.remove_security_group(secgrp=secgrp_id) src_vm_fix.add_security_group(secgrp=sg_allow_all) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1, src_exp_count=0) # stop traffic sent, recv = self.stop_traffic_scapy(sender1, receiver1) sent, recv = self.stop_traffic_scapy(sender2, receiver2) src_vm_fix.remove_security_group(secgrp=sg_allow_all) return True # end test_add_remove_sg_active_flow3 @preposttest_wrapper def test_add_remove_sg_active_flow4(self): """ add/remove SG from VM when flow is active 1. Traffic from both ends 2. Test for SG with cidr both ingress-egress""" topology_class_name = sdn_sg_test_topo.sdn_topo_flow_to_sg_rule_mapping topo_obj, config_topo = self.create_topo_setup(topology_class_name, "build_topo") port = 10000 src_vm_name = 'vm1' dst_vm_name = 'vm2' src_vm_fix = config_topo['vm'][src_vm_name] dst_vm_fix = config_topo['vm'][dst_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] sg_name = topo_obj.sg_list[0] secgrp_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, sg_name])) default_sg_id = get_secgrp_id_from_name( self.connections, ':'.join([self.inputs.domain_name, self.inputs.project_name, 'default'])) src_vm_fix.remove_security_group(secgrp=default_sg_id) dst_vm_fix.remove_security_group(secgrp=default_sg_id) src_vm_fix.add_security_group(secgrp=secgrp_id) dst_vm_fix.add_security_group(secgrp=secgrp_id) # start the traffic from src VM sender1, receiver1 = self.start_traffic_scapy( src_vm_fix, dst_vm_fix, 'udp', port, port, payload="payload") # start the traffic from dst VM sender2, receiver2 = self.start_traffic_scapy( dst_vm_fix, src_vm_fix, 'udp', port, port, payload="payload") # ingress-egress from all rule = [{'direction': '>', 'protocol': 'udp', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'udp', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] config_topo['sec_grp'][sg_name].replace_rules(rule) filters1 = '\'(udp and src host %s and dst host %s)\'' % ( src_vm_fix.vm_ip, dst_vm_fix.vm_ip) filters2 = '\'(udp and src host %s and dst host %s)\'' % ( dst_vm_fix.vm_ip, src_vm_fix.vm_ip) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1) src_vm_fix.remove_security_group(secgrp=secgrp_id) src_vm_fix.add_security_group(secgrp=secgrp_id) assert self.verify_traffic_on_vms(src_vm_fix, src_vn_fix, dst_vm_fix, dst_vn_fix, filters2, filters1) # stop traffic sent, recv = self.stop_traffic_scapy(sender1, receiver1) sent, recv = self.stop_traffic_scapy(sender2, receiver2) return True # end test_add_remove_sg_active_flow4 #end class SecurityGroupRegressionTests9 class SecurityGroupSynAckTest(BaseSGTest, VerifySecGroup, ConfigPolicy): @classmethod def setUpClass(cls): super(SecurityGroupSynAckTest, cls).setUpClass() cls.option = 'openstack' def runTest(self): pass @preposttest_wrapper def test_syn_ack_create_flow(self): """ Description: verify if SYN ack is allowed and flow is created again after flow is expired Steps: 1. configure secgroupA with egress rule 2. configure secgroupB with ingress/egress rule 3. Make sure traffic from VM(secgrpB) to VM(secgrpA) fails as the VM(secgrpA) doesn't allow ingress traffic 4. Send traffic from VM(secgrpA) to VM(secgrpB), expected to pass through 5. Send SYN from VM(secgrpA) to VM(secgrpB). 6. recv SYN at VM(secgrpB) and Wait for flow to expire(180 sec) 7. Send SYN+ACK from VM(secgrpB) to VM(secgrpA), though the flow is expired and VM(secgrpA) denies ingress traffic, SYN_ACK packet of intial SYN should go through. Pass criteria: step 7 should PASS """ topology_class_name = sdn_sg_test_topo.sdn_topo_icmp_error_handling topo = topology_class_name() try: # provided by wrapper module if run in parallel test env topo.build_topo2( project=self.project.project_name, username=self.project.username, password=self.project.password, compute_node_list=self.inputs.compute_ips) except (AttributeError,NameError): topo.build_topo2(compute_node_list=self.inputs.compute_ips) topo.sg_rules[topo.sg_list[0]] = [ {'direction': '>', 'protocol': 'any', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }] topo.sg_rules[topo.sg_list[1]] = [ {'direction': '>', 'protocol': 'any', 'dst_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'src_addresses': [{'security_group': 'local'}], }, {'direction': '>', 'protocol': 'any', 'src_addresses': [{'subnet': {'ip_prefix': '0.0.0.0', 'ip_prefix_len': 0}}], 'dst_ports': [{'start_port': 0, 'end_port': -1}], 'src_ports': [{'start_port': 0, 'end_port': -1}], 'dst_addresses': [{'security_group': 'local'}], }] setup_obj = self.useFixture( sdnTopoSetupFixture(self.connections, topo)) out = setup_obj.topo_setup(vms_on_single_compute=True) self.logger.info("Setup completed with result %s" % (out['result'])) self.assertEqual(out['result'], True, out['msg']) if out['result']: topo_obj, config_topo = out['data'] src_vm_name = 'vm1' src_vm_fix = config_topo['vm'][src_vm_name] src_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[src_vm_name]] dst_vm_name = 'vm2' dst_vm_fix = config_topo['vm'][dst_vm_name] dst_vn_fix = config_topo['vn'][topo_obj.vn_of_vm[dst_vm_name]] pkg = 'syn_client.py' self.logger.info("copying syn client to the compute node.") path = os.getcwd() + '/tcutils/pkgs/syn_ack_test/' + pkg host_compute = { 'username': self.inputs.host_data[src_vm_fix.vm_node_ip]['username'], 'password': self.inputs.host_data[src_vm_fix.vm_node_ip]['password'], 'ip': src_vm_fix.vm_node_ip} copy_file_to_server(host_compute, path, '/tmp', pkg) self.logger.info("copying syn client from compute node to VM") with settings(host_string='%s@%s' % (self.inputs.username, src_vm_fix.vm_node_ip), password=self.inputs.password, warn_only=True, abort_on_prompts=False): path = '/tmp/' + pkg output = fab_put_file_to_vm( host_string='%s@%s' % (src_vm_fix.vm_username, src_vm_fix.local_ip), password=src_vm_fix.vm_password, src=path, dest='/tmp') pkg = 'syn_server.py' self.logger.info("copying syn server to the compute node.") path = os.getcwd() + '/tcutils/pkgs/syn_ack_test/' + pkg host_compute = { 'username': self.inputs.username, 'password': self.inputs.password, 'ip': dst_vm_fix.vm_node_ip} copy_file_to_server(host_compute, path, '/tmp', pkg) self.logger.info("copying syn server from compute node to VM") with settings(host_string='%s@%s' % (self.inputs.username, dst_vm_fix.vm_node_ip), password=self.inputs.password, warn_only=True, abort_on_prompts=False): path = '/tmp/' + pkg output = fab_put_file_to_vm( host_string='%s@%s' % (dst_vm_fix.vm_username, dst_vm_fix.local_ip), password=dst_vm_fix.vm_password, src=path, dest='/tmp') cmd1 = 'chmod +x /tmp/syn_server.py;/tmp/syn_server.py %s %s \ 2>/tmp/server.log 1>/tmp/server.log' \ % (src_vm_fix.vm_ip, dst_vm_fix.vm_ip) cmd2 = 'chmod +x /tmp/syn_client.py;/tmp/syn_client.py %s %s \ 2>/tmp/client.log 1>/tmp/client.log' \ % (dst_vm_fix.vm_ip, src_vm_fix.vm_ip) output_cmd_dict = dst_vm_fix.run_cmd_on_vm(cmds=[cmd1], as_sudo=True, as_daemon=True) output_cmd_dict = src_vm_fix.run_cmd_on_vm(cmds=[cmd2], as_sudo=True, as_daemon=True) sleep(1) #verify flow created inspect_h1 = self.agent_inspect[src_vm_fix.vm_node_ip] flow_rec1 = None sport = '8100' dport = '8000' vn_fq_name=src_vm_fix.vn_fq_name flow_timeout = 180 flow_rec1 = inspect_h1.get_vna_fetchflowrecord( nh=src_vm_fix.tap_intf[vn_fq_name]['flow_key_idx'], sip=src_vm_fix.vm_ip, dip=dst_vm_fix.vm_ip, sport=sport, dport=dport, protocol='6') assert flow_rec1 #wait for flow to expire sleep(flow_timeout+2) #verify flow created again flow_rec1 = inspect_h1.get_vna_fetchflowrecord( nh=src_vm_fix.tap_intf[vn_fq_name]['flow_key_idx'], sip=src_vm_fix.vm_ip, dip=dst_vm_fix.vm_ip, sport=sport, dport=dport, protocol='6') assert flow_rec1 flow_rec1 = inspect_h1.get_vna_fetchflowrecord( nh=dst_vm_fix.tap_intf[vn_fq_name]['flow_key_idx'], sip=dst_vm_fix.vm_ip, dip=src_vm_fix.vm_ip, sport=dport, dport=sport, protocol='6') assert flow_rec1 return True #end test_syn_ack_create_flow # end class SecurityGroupSynAckTest #creating new classes to run all tests with contrail apis class SecurityGroupBasicRegressionTests1_contrail(test_regression_basic.SecurityGroupBasicRegressionTests1): @classmethod def setUpClass(cls): super(SecurityGroupBasicRegressionTests1_contrail, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests2_contrail(SecurityGroupRegressionTests2): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests2, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests3_contrail(SecurityGroupRegressionTests3): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests3, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests4_contrail(SecurityGroupRegressionTests4): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests4, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests5_contrail(SecurityGroupRegressionTests5): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests5, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests6_contrail(SecurityGroupRegressionTests6): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests6, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests7_contrail(SecurityGroupRegressionTests7): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests7, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests8_contrail(SecurityGroupRegressionTests8): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests8, cls).setUpClass() cls.option = 'contrail' class SecurityGroupRegressionTests9_contrail(SecurityGroupRegressionTests9): @classmethod def setUpClass(cls): super(SecurityGroupRegressionTests9, cls).setUpClass() cls.option = 'contrail'

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test/orchestrate/options_validator/service_test.py

emattia/sigopt-python

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test/orchestrate/options_validator/service_test.py

emattia/sigopt-python

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import pytest from mock import Mock from sigopt.orchestrate.options_validator.service import OptionsValidatorService class TestOptionsValidatorService(object): @pytest.fixture() def options_validator_service(self): services = Mock() return OptionsValidatorService(services) @pytest.mark.parametrize('resource', [ {'requests': {'cpu': 1, 'memory': '200Gi'}, 'gpus': 1}, {'limits': {'cpu': '200m', 'memory': 200}}, {'requests': None, 'gpus': 1}, {'requests': {'cpu': 1, 'memory': '200Gi'}, 'gpus': None}, ]) def test_validate_resources(self, options_validator_service, resource): options_validator_service.validate_resources(**resource) @pytest.mark.parametrize('resource', [ {'requests': {'cpu': 1, 'memory': '200Gi'}, 'gpus': -1}, {'limits': {'cpu': '200m', 'memory': 200}, 'requests': 55}, ]) def test_orchestrate_resources_bad(self, options_validator_service, resource): with pytest.raises(AssertionError): options_validator_service.validate_resources(**resource) @pytest.mark.parametrize('gpus', [-1, [], dict()]) def test_validate_resources_wrong_type(self, options_validator_service, gpus): with pytest.raises(AssertionError): options_validator_service.validate_resources(gpus=gpus) def test_validate_aws(self, options_validator_service): options_validator_service.validate_aws_for_orchestrate( aws_access_key_id='foobar', aws_secret_access_key='barfoo', ) options_validator_service.validate_aws_for_cluster( aws_access_key_id='foobar', aws_secret_access_key='barfoo', additional_policies=['bar'] ) def test_validate_aws_simple(self, options_validator_service): options_validator_service.validate_aws_for_orchestrate() options_validator_service.validate_aws_for_cluster() def test_validate_aws_rejects_ecr(self, options_validator_service): with pytest.raises(TypeError): options_validator_service.validate_aws_for_cluster( ecr=dict( image='orchestrate/test', ), ) with pytest.raises(TypeError): options_validator_service.validate_aws_for_orchestrate( ecr=dict( image='orchestrate/test', ), ) with pytest.raises(TypeError): options_validator_service.validate_aws_for_orchestrate( ecr=dict(), ) def test_validate_aws_additional_policies(self, options_validator_service): options_validator_service.validate_aws_for_cluster(additional_policies=[]) options_validator_service.validate_aws_for_cluster(additional_policies=None) with pytest.raises(AssertionError): options_validator_service.validate_aws_for_cluster(additional_policies='policy') def test_validate_sigopt(self, options_validator_service): options_validator_service.validate_sigopt( api_token='foobar', ) def test_validate_sigopt_simple(self, options_validator_service): options_validator_service.validate_sigopt() @pytest.mark.parametrize('api_token', ['', 0]) def test_validate_sigopt_wrong_value(self, options_validator_service, api_token): with pytest.raises(AssertionError): options_validator_service.validate_sigopt( api_token=api_token, ) def test_validate_cluster_options(self, options_validator_service): options_validator_service.validate_cluster_options( provider='aws', cluster_name='test-cluster', cpu=dict( instance_type='t2.small', min_nodes=1, max_nodes=1, ), gpu=dict( instance_type='p3.2xlarge', min_nodes=2, max_nodes=2, ), system=dict( instance_type='t3.small', min_nodes=1, max_nodes=2, ), ) def test_validate_cluster_options_ok_missing_values(self, options_validator_service): options_validator_service.validate_cluster_options( cluster_name='test-cluster', provider='custom', cpu=dict( instance_type='t2.small', min_nodes=1, max_nodes=1, ), gpu=dict( instance_type='p3.2xlarge', min_nodes=2, max_nodes=2, ), system=dict( instance_type='t3.small', min_nodes=1, max_nodes=2, ), ) options_validator_service.validate_cluster_options( provider='aws', cluster_name='test-cluster', gpu=dict( instance_type='p3.2xlarge', min_nodes=2, max_nodes=2, ), system=dict( instance_type='t3.small', min_nodes=1, max_nodes=2, ), ) options_validator_service.validate_cluster_options( provider='aws', cluster_name='test-cluster', cpu=dict( instance_type='t2.small', min_nodes=1, max_nodes=1, ), system=dict( instance_type='t3.small', min_nodes=1, max_nodes=2, ), ) @pytest.mark.parametrize('cluster_name', ['', None, dict()]) def test_validate_cluster_options_cluster_name(self, options_validator_service, cluster_name): with pytest.raises(AssertionError): options_validator_service.validate_cluster_options( provider='aws', cluster_name=cluster_name, cpu=dict( instance_type='t2.small', min_nodes=1, max_nodes=1, ), system=dict( instance_type='t3.small', min_nodes=1, max_nodes=2, ), ) def test_validate_cluster_options_extra_options(self, options_validator_service): with pytest.raises(AssertionError): options_validator_service.validate_cluster_options( provider='aws', cluster_name='test-cluster', tpu=dict( instance_type='p3.2xlarge', min_nodes=2, max_nodes=2, ), ) def test_validate_cluster_options_wrong_type(self, options_validator_service): with pytest.raises(AssertionError): options_validator_service.validate_cluster_options( provider='aws', cluster_name='test-cluster', gpu=[dict( instance_type='p3.2xlarge', min_nodes=2, max_nodes=2, )], ) with pytest.raises(AssertionError): options_validator_service.validate_cluster_options( provider='aws', cluster_name='test-cluster', cpu=[dict( instance_type='t2.small', min_nodes=1, max_nodes=1, )], system=dict( instance_type='t3.small', min_nodes=1, max_nodes=2, ), ) def test_validate_cluster_options_ignore_values(self, options_validator_service): options_validator_service.validate_cluster_options( provider='aws', cluster_name='test-cluster', cpu=dict( instance_type='t2.small', min_nodes=1, max_nodes=1, ), system=dict( instance_type='t3.small', min_nodes=1, max_nodes=2, ), ) def test_validate_worker_stack(self, options_validator_service): options_validator_service.validate_worker_stack( name='cpu', instance_type='t2.small', min_nodes=1, max_nodes=1, ) def test_validate_worker_stack_ignores_values(self, options_validator_service): options_validator_service.validate_worker_stack( name='foobar', instance_type='bazzle', min_nodes=2, max_nodes=19, ) def test_validate_worker_stack_missing_options(self, options_validator_service): with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', min_nodes=1, max_nodes=1, ) with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', instance_type='t2.small', max_nodes=1, ) with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', instance_type='t2.small', min_nodes=1, ) def test_validate_worker_stack_wrong_type(self, options_validator_service): with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', instance_type=2, min_nodes=1, max_nodes=1, ) with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', instance_type='t2.small', min_nodes='1', max_nodes=1, ) with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', instance_type='t2.small', min_nodes=1, max_nodes='1', ) def test_validate_worker_stack_negative(self, options_validator_service): with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', instance_type='t2.small', min_nodes=-1, max_nodes=1, ) with pytest.raises(AssertionError): options_validator_service.validate_worker_stack( name='cpu', instance_type='t2.small', min_nodes=1, max_nodes=-1, )

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Python

GcMessageProtocol/__init__.py

GameCompanyGC/Python-GCDiscordMessageProtocol

fc4b565ea7b0df8d26e43d997efa17d1eef09c69

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GcMessageProtocol/__init__.py

GameCompanyGC/Python-GCDiscordMessageProtocol

fc4b565ea7b0df8d26e43d997efa17d1eef09c69

[ "MIT" ]

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GcMessageProtocol/__init__.py

GameCompanyGC/Python-GCDiscordMessageProtocol

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Python

peripy/test/test_integrators.py

jd-bartlett96/PeriPy

04cae072e22568e29b9ab8f84d821f9576ecb728

[ "MIT" ]

17

2020-12-16T15:17:47.000Z

2022-03-03T08:04:54.000Z

peripy/test/test_integrators.py

jd-bartlett96/PeriPy

04cae072e22568e29b9ab8f84d821f9576ecb728

[ "MIT" ]

49

2020-01-29T16:50:23.000Z

2020-09-02T10:27:25.000Z

peripy/test/test_integrators.py

jd-bartlett96/PeriPy

04cae072e22568e29b9ab8f84d821f9576ecb728

[ "MIT" ]

11

2021-07-05T14:03:58.000Z

2022-03-20T14:22:44.000Z

"""Tests for the integrators module.""" from .conftest import context_available from ..integrators import ( Integrator, Euler, EulerCL, EulerCromerCL, VelocityVerletCL, ContextError) from ..model import Model, initial_crack_helper from ..cl import get_context import pytest import numpy as np import pyopencl as cl @initial_crack_helper def is_crack(x, y): """Determine whether a pair of particles define the crack.""" crack_length = 0.3 output = 0 p1 = x p2 = y if x[0] > y[0]: p2 = x p1 = y # 1e-6 makes it fall one side of central line of particles if p1[0] < 0.5 + 1e-6 and p2[0] > 0.5 + 1e-6: # draw a straight line between them m = (p2[1] - p1[1]) / (p2[0] - p1[0]) c = p1[1] - m * p1[0] # height a x = 0.5 height = m * 0.5 + c if (height > 0.5 * (1 - crack_length) and height < 0.5 * (1 + crack_length)): output = 1 return output def is_density(x): """Return the density of the nodal volume.""" return 1.0 @pytest.fixture(scope="module") def euler_integrator(data_path, simple_displacement_boundary): """Run the example simulation on the Euler integrator.""" path = data_path mesh_file = path / "example_mesh.vtk" euler = Euler(dt=1e-3) # Create model model = Model(mesh_file, integrator=euler, horizon=0.1, critical_stretch=0.005, bond_stiffness=18.0 * 0.05 / (np.pi * 0.1**4), is_displacement_boundary=simple_displacement_boundary, initial_crack=is_crack) return model, euler @pytest.fixture(scope="module") def euler_cl_integrator(data_path, simple_displacement_boundary): """Run the example simulation on the EulerCL integrator.""" path = data_path mesh_file = path / "example_mesh.vtk" euler = EulerCL(dt=1e-3) # Create model model = Model(mesh_file, integrator=euler, horizon=0.1, critical_stretch=0.005, bond_stiffness=18.0 * 0.05 / (np.pi * 0.1**4), is_displacement_boundary=simple_displacement_boundary, initial_crack=is_crack) return model, euler @pytest.fixture(scope="module") def euler_cromer_cl_integrator(data_path, simple_displacement_boundary): """Run the example simulation on the EulerCromerCL integrator.""" path = data_path mesh_file = path / "example_mesh.vtk" euler = EulerCromerCL(dt=1e-3, damping=0.0) # Create model model = Model(mesh_file, integrator=euler, horizon=0.1, critical_stretch=0.005, bond_stiffness=18.0 * 0.05 / (np.pi * 0.1**4), is_displacement_boundary=simple_displacement_boundary, initial_crack=is_crack, is_density=is_density) return model, euler @pytest.fixture(scope="module") def velocity_verlet_cl_integrator(data_path, simple_displacement_boundary): """Run the example simulation on the VelocityVerletCL integrator =.""" path = data_path mesh_file = path / "example_mesh.vtk" euler = VelocityVerletCL(dt=1e-3, damping=0.0) # Create model model = Model(mesh_file, integrator=euler, horizon=0.1, critical_stretch=0.005, bond_stiffness=18.0 * 0.05 / (np.pi * 0.1**4), is_displacement_boundary=simple_displacement_boundary, initial_crack=is_crack, is_density=is_density) return model, euler def test_no_context(data_path, monkeypatch): """Test raising error when no suitable device is found.""" from .. import integrators # Mock the get_context function to return None as it would if no suitable # device is found. def return_none(): return None monkeypatch.setattr(integrators, "get_context", return_none) with pytest.raises(ContextError) as exception: EulerCL(dt=1) assert "No suitable context was found." in exception.value @context_available def test_custom_context(): """Test constructing an EulerCL object using the context argument.""" context = get_context() integrator = EulerCL(dt=1, context=context) assert integrator.context is context def test_invalid_custom_context(): """Test constructing an EulerCL object using the context argument.""" with pytest.raises(TypeError) as exception: EulerCL(dt=1, context=5) assert "context must be a pyopencl Context object" in exception.value class TestIntegrator: """ABC class tests.""" def test_not_implemented_error(self): """Ensure the ABC cannot be instantiated.""" with pytest.raises(TypeError): Integrator(dt=1) class TestEuler: """EulerCL integrator tests. See test_euler.py for more tests.""" def test_call(self, data_path, euler_integrator): """Regression test for the Euler integrator.""" path = data_path model, integrator = euler_integrator nlist, n_neigh = model.initial_connectivity u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = None integrator.create_buffers( nlist, n_neigh, model.bond_stiffness, model.critical_stretch, model.plus_cs, u, ud, udd, force, body_force, damage, regimes, model.nregimes, model.nbond_types) displacement_bc_magnitudes = 0.00001 / 2 * np.linspace( 1, 10, 10) for step in range(10): integrator.__call__( displacement_bc_magnitude=displacement_bc_magnitudes[step], force_bc_magnitude=0.0) u_expected = np.load(path/"expected_displacements.npy") force_expected = np.load(path/"expected_force.npy") damage_expected = np.load(path/"expected_damage.npy") expected_connectivity = np.load(path/"expected_connectivity_crack.npz") nlist_expected = expected_connectivity["nlist"] n_neigh_expected = expected_connectivity["n_neigh"] (u_actual, _, _, force_actual, _, damage_actual, nlist_actual, n_neigh_actual ) = integrator.write( u, ud, udd, force, body_force, damage, nlist, n_neigh) assert np.allclose(u_actual, u_expected) assert np.allclose(force_actual, force_expected) assert np.allclose(damage_actual, damage_expected) assert np.allclose(nlist_actual, nlist_expected) assert np.allclose(n_neigh_actual, n_neigh_expected) def test_create_buffers_nregimes(self, euler_integrator): """Test exception when n_regimes is supplied to Euler.""" model, integrator = euler_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = model.plus_cs u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = None nregimes = 2 nbond_types = 1 with pytest.raises(ValueError) as exception: integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert ( str("n-linear damage model's are not") in exception.value) def test_create_buffers_n_bond_types(self, euler_integrator): """Test exception when n_bond_types is supplied to Euler.""" model, integrator = euler_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = model.plus_cs u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = None nregimes = 1 nbond_types = 2 with pytest.raises(ValueError) as exception: integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert ( str("n-material composite models are not") in exception.value) def test_create_buffers(self, euler_integrator): """Test initiation of arrays that are dependent on simulation.""" model, integrator = euler_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = model.plus_cs u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes), dtype=np.float64) regimes = None nregimes = 1 nbond_types = 1 integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert np.allclose(integrator.nlist, nlist) assert np.allclose(integrator.n_neigh, n_neigh) assert np.allclose(integrator.bond_stiffness, bond_stiffness) assert np.allclose(integrator.critical_stretch, critical_stretch) assert np.allclose(integrator.u, u) assert np.allclose(integrator.ud, ud) assert np.allclose(integrator.udd, udd) assert np.allclose(integrator.force, force) assert np.allclose(integrator.body_force, body_force) def test_build(self, euler_integrator): """Test initiate integrator arrays.""" model, integrator = euler_integrator nnodes = model.nnodes degrees_freedom = model.degrees_freedom max_neighbours = model.max_neighbours coords = model.coords family = model.family volume = model.volume bc_types = model.bc_types bc_values = model.bc_values force_bc_types = model.force_bc_types force_bc_values = model.force_bc_values stiffness_corrections = None bond_types = None densities = None integrator.build( nnodes, degrees_freedom, max_neighbours, coords, volume, family, bc_types, bc_values, force_bc_types, force_bc_values, stiffness_corrections, bond_types, densities) assert np.allclose(integrator.nnodes, nnodes) assert np.allclose(integrator.coords, coords) assert np.allclose(integrator.family, family) assert np.allclose(integrator.volume, volume) assert np.allclose(integrator.bc_types, bc_types) assert np.allclose(integrator.bc_values, bc_values) assert np.allclose(integrator.force_bc_types, force_bc_types) assert np.allclose(integrator.force_bc_values, force_bc_values) def test_build_exception(self, euler_integrator): """Test initiatiation of integrator arrays.""" model, integrator = euler_integrator nnodes = model.nnodes degrees_freedom = model.degrees_freedom max_neighbours = model.max_neighbours coords = model.coords family = model.family volume = model.volume bc_types = model.bc_types bc_values = model.bc_values force_bc_types = model.force_bc_types force_bc_values = model.force_bc_values stiffness_corrections = None bond_types = 1 densities = None with pytest.raises(ValueError) as exception: integrator.build( nnodes, degrees_freedom, max_neighbours, coords, volume, family, bc_types, bc_values, force_bc_types, force_bc_values, stiffness_corrections, bond_types, densities) assert ( str("bond_types are not supported by this") in exception.value) def test_build_exception_stiffness_corrections(self, euler_integrator): """Test exception when stiffness_corrections are applied to Euler.""" model, integrator = euler_integrator nnodes = model.nnodes degrees_freedom = model.degrees_freedom max_neighbours = model.max_neighbours coords = model.coords family = model.family volume = model.volume bc_types = model.bc_types bc_values = model.bc_values force_bc_types = model.force_bc_types force_bc_values = model.force_bc_values stiffness_corrections = 1 bond_types = None densities = None with pytest.raises(ValueError) as exception: integrator.build( nnodes, degrees_freedom, max_neighbours, coords, volume, family, bc_types, bc_values, force_bc_types, force_bc_values, stiffness_corrections, bond_types, densities) assert ( str("stiffness_corrections are not") in exception.value) def test_build_exception_densities(self, euler_integrator): """Test exception when densities are applied to Euler.""" model, integrator = euler_integrator nnodes = model.nnodes degrees_freedom = model.degrees_freedom max_neighbours = model.max_neighbours coords = model.coords family = model.family volume = model.volume bc_types = model.bc_types bc_values = model.bc_values force_bc_types = model.force_bc_types force_bc_values = model.force_bc_values stiffness_corrections = None bond_types = None densities = 1 with pytest.raises(ValueError) as exception: integrator.build( nnodes, degrees_freedom, max_neighbours, coords, volume, family, bc_types, bc_values, force_bc_types, force_bc_values, stiffness_corrections, bond_types, densities) assert ( str("densities are not supported") in exception.value) def test_create_special_buffers(self, euler_integrator): """Test for no special buffers for this integrator.""" model, integrator = euler_integrator value = integrator._create_special_buffers() assert value is None def test_build_special(self, euler_integrator): """There for no special programs for this integrator.""" model, integrator = euler_integrator value = integrator._build_special() assert value is None class TestEulerCL: """Euler integrator tests. See test_euler.py for more tests.""" @context_available def test_call(self, data_path, euler_cl_integrator): """Regression test for the EulerCL integrator.""" path = data_path model, integrator = euler_cl_integrator nlist, n_neigh = model.initial_connectivity u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes), dtype=np.float64) regimes = None integrator.create_buffers( nlist, n_neigh, model.bond_stiffness, model.critical_stretch, model.plus_cs, u, ud, udd, force, body_force, damage, regimes, model.nregimes, model.nbond_types) displacement_bc_magnitudes = 0.00001 / 2 * np.linspace( 1, 10, 10) for step in range(10): integrator.__call__( displacement_bc_magnitude=displacement_bc_magnitudes[step], force_bc_magnitude=0.0) u_expected = np.load(path/"expected_displacements.npy") force_expected = np.load(path/"expected_force.npy") damage_expected = np.load(path/"expected_damage.npy") expected_connectivity = np.load( path/"expected_connectivity_crack_cl.npz") nlist_expected = expected_connectivity["nlist"] n_neigh_expected = expected_connectivity["n_neigh"] (u_actual, _, _, force_actual, _, damage_actual, nlist_actual, n_neigh_actual ) = integrator.write( u, ud, udd, force, body_force, damage, nlist, n_neigh) assert np.allclose(u_actual, u_expected) assert np.allclose(force_actual, force_expected) assert np.allclose(damage_actual, damage_expected) assert np.allclose(nlist_actual, nlist_expected) assert np.allclose(n_neigh_actual, n_neigh_expected) @context_available def test_create_buffers_float(self, euler_cl_integrator): """Test initiation of arrays that are dependent on simulation.""" model, integrator = euler_cl_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = model.plus_cs u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = None nregimes = 1 nbond_types = 1 integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert(type(integrator.bond_stiffness_d) is np.float64) assert(type(integrator.critical_stretch_d) is np.float64) @context_available def test_create_buffers_array(self, euler_cl_integrator): """Test initiation of arrays that are dependent on simulation.""" model, integrator = euler_cl_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = np.zeros((2, 2), dtype=np.float64) u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = np.zeros( (model.nnodes, model.max_neighbours), dtype=np.float64) nregimes = 2 nbond_types = 2 integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert(type(integrator.bond_stiffness_d) is cl._cl.Buffer) assert(type(integrator.critical_stretch_d) is cl._cl.Buffer) @context_available def test_build_exception(self, euler_cl_integrator): """Test exception when densities are supplied to EulerCL.""" model, integrator = euler_cl_integrator nnodes = model.nnodes degrees_freedom = model.degrees_freedom max_neighbours = model.max_neighbours coords = model.coords family = model.family volume = model.volume bc_types = model.bc_types bc_values = model.bc_values force_bc_types = model.force_bc_types force_bc_values = model.force_bc_values stiffness_corrections = None bond_types = None densities = 1 with pytest.raises(ValueError) as exception: integrator.build( nnodes, degrees_freedom, max_neighbours, coords, volume, family, bc_types, bc_values, force_bc_types, force_bc_values, stiffness_corrections, bond_types, densities) assert ( str("densities are not supported") in exception.value) @context_available def test_create_special_buffers(self, euler_cl_integrator): """There are no special buffers so this method does nothing.""" model, integrator = euler_cl_integrator value = integrator._create_special_buffers() assert value is None class TestEulerCromerCL: """EulerCromerCL integrator tests. See test_euler.py for more tests.""" @context_available def test_call(self, data_path, euler_cromer_cl_integrator): """Regression test for the EulerCromerCL integrator.""" path = data_path model, integrator = euler_cromer_cl_integrator nlist, n_neigh = model.initial_connectivity u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes), dtype=np.float64) regimes = None integrator.create_buffers( nlist, n_neigh, model.bond_stiffness, model.critical_stretch, model.plus_cs, u, ud, udd, force, body_force, damage, regimes, model.nregimes, model.nbond_types) displacement_bc_magnitudes = 0.00001 / 2 * np.linspace( 1, 10, 10) for step in range(10): integrator.__call__( displacement_bc_magnitude=displacement_bc_magnitudes[step], force_bc_magnitude=0.0) (u_actual, ud_actual, _, force_actual, _, damage_actual, nlist_actual, n_neigh_actual ) = integrator.write( u, ud, udd, force, body_force, damage, nlist, n_neigh) u_expected = np.load(path/"expected_displacements_euler_cromer.npy") force_expected = np.load(path/"expected_force_euler_cromer.npy") damage_expected = np.load(path/"expected_damage_euler_cromer.npy") expected_connectivity = np.load( path/"expected_connectivity_euler_cromer_cl.npz") nlist_expected = expected_connectivity["nlist"] n_neigh_expected = expected_connectivity["n_neigh"] assert np.allclose(u_actual, u_expected) assert np.allclose(force_actual, force_expected) assert np.allclose(damage_actual, damage_expected) assert np.allclose(nlist_actual, nlist_expected) assert np.allclose(n_neigh_actual, n_neigh_expected) @context_available def test_create_buffers_float(self, euler_cromer_cl_integrator): """Test initiation of arrays that are dependent on simulation.""" model, integrator = euler_cromer_cl_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = model.plus_cs u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = None nregimes = 1 nbond_types = 1 integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert(type(integrator.bond_stiffness_d) is np.float64) assert(type(integrator.critical_stretch_d) is np.float64) @context_available def test_create_buffers_array(self, euler_cromer_cl_integrator): """Test initiation of arrays that are dependent on simulation.""" model, integrator = euler_cromer_cl_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = np.zeros((2, 2), dtype=np.float64) u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = np.zeros( (model.nnodes, model.max_neighbours), dtype=np.float64) nregimes = 2 nbond_types = 2 integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert(type(integrator.bond_stiffness_d) is cl._cl.Buffer) assert(type(integrator.critical_stretch_d) is cl._cl.Buffer) @context_available def test_build_exception(self, euler_cromer_cl_integrator): """Test exception when densities are not supplied to EulerCromerCL.""" model, integrator = euler_cromer_cl_integrator nnodes = model.nnodes degrees_freedom = model.degrees_freedom max_neighbours = model.max_neighbours coords = model.coords family = model.family volume = model.volume bc_types = model.bc_types bc_values = model.bc_values force_bc_types = model.force_bc_types force_bc_values = model.force_bc_values stiffness_corrections = None bond_types = None densities = None with pytest.raises(ValueError) as exception: integrator.build( nnodes, degrees_freedom, max_neighbours, coords, volume, family, bc_types, bc_values, force_bc_types, force_bc_values, stiffness_corrections, bond_types, densities) assert ( str("densities must be supplied") in exception.value) @context_available def test_create_special_buffers(self, euler_cromer_cl_integrator): """There are no special buffers so this method does nothing.""" model, integrator = euler_cromer_cl_integrator value = integrator._create_special_buffers() assert value is None class TestVelocityVerletCL: """VelocityVerletCL integrator tests. See test_euler.py for more tests.""" @context_available def test_call(self, data_path, velocity_verlet_cl_integrator): """Regression test for the VelocityVerletCL integrator.""" path = data_path model, integrator = velocity_verlet_cl_integrator nlist, n_neigh = model.initial_connectivity u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes), dtype=np.float64) regimes = None integrator.create_buffers( nlist, n_neigh, model.bond_stiffness, model.critical_stretch, model.plus_cs, u, ud, udd, force, body_force, damage, regimes, model.nregimes, model.nbond_types) displacement_bc_magnitudes = 0.00001 / 2 * np.linspace( 1, 10, 10) for step in range(10): integrator.__call__( displacement_bc_magnitude=displacement_bc_magnitudes[step], force_bc_magnitude=0.0) (u_actual, ud_actual, udd_actual, force_actual, _, damage_actual, nlist_actual, n_neigh_actual ) = integrator.write( u, ud, udd, force, body_force, damage, nlist, n_neigh) u_expected = np.load(path/"expected_displacements_velocity_verlet.npy") ud_expected = np.load(path/"expected_velocities_velocity_verlet.npy") udd_expected = np.load( path/"expected_accelerations_velocity_verlet.npy") force_expected = np.load(path/"expected_force_velocity_verlet.npy") damage_expected = np.load(path/"expected_damage_velocity_verlet.npy") expected_connectivity = np.load( path/"expected_connectivity_velocity_verlet_cl.npz") nlist_expected = expected_connectivity["nlist"] n_neigh_expected = expected_connectivity["n_neigh"] assert np.allclose(u_actual, u_expected) assert np.allclose(ud_actual, ud_expected) assert np.allclose(udd_actual, udd_expected) assert np.allclose(force_actual, force_expected) assert np.allclose(damage_actual, damage_expected) assert np.allclose(nlist_actual, nlist_expected) assert np.allclose(n_neigh_actual, n_neigh_expected) @context_available def test_create_buffers_float(self, velocity_verlet_cl_integrator): """Test initiation of arrays that are dependent on simulation.""" model, integrator = velocity_verlet_cl_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = model.plus_cs u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = None nregimes = 1 nbond_types = 1 integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert(type(integrator.bond_stiffness_d) is np.float64) assert(type(integrator.critical_stretch_d) is np.float64) @context_available def test_create_buffers_array(self, velocity_verlet_cl_integrator): """Test initiation of arrays that are dependent on simulation.""" model, integrator = velocity_verlet_cl_integrator nlist, n_neigh = model.initial_connectivity bond_stiffness = model.bond_stiffness critical_stretch = model.critical_stretch plus_cs = np.zeros((2, 2), dtype=np.float64) u = np.zeros((model.nnodes, 3), dtype=np.float64) ud = np.zeros((model.nnodes, 3), dtype=np.float64) udd = np.zeros((model.nnodes, 3), dtype=np.float64) force = np.zeros((model.nnodes, 3), dtype=np.float64) body_force = np.zeros((model.nnodes, 3), dtype=np.float64) damage = np.zeros((model.nnodes, 3), dtype=np.float64) regimes = np.zeros( (model.nnodes, model.max_neighbours), dtype=np.float64) nregimes = 2 nbond_types = 2 integrator.create_buffers( nlist, n_neigh, bond_stiffness, critical_stretch, plus_cs, u, ud, udd, force, body_force, damage, regimes, nregimes, nbond_types) assert(type(integrator.bond_stiffness_d) is cl._cl.Buffer) assert(type(integrator.critical_stretch_d) is cl._cl.Buffer) @context_available def test_build_exception(self, velocity_verlet_cl_integrator): """Test exception when densities not supplied to VelocityVerletCL.""" model, integrator = velocity_verlet_cl_integrator nnodes = model.nnodes degrees_freedom = model.degrees_freedom max_neighbours = model.max_neighbours coords = model.coords family = model.family volume = model.volume bc_types = model.bc_types bc_values = model.bc_values force_bc_types = model.force_bc_types force_bc_values = model.force_bc_values stiffness_corrections = None bond_types = None densities = None with pytest.raises(ValueError) as exception: integrator.build( nnodes, degrees_freedom, max_neighbours, coords, volume, family, bc_types, bc_values, force_bc_types, force_bc_values, stiffness_corrections, bond_types, densities) assert ( str("densities must be supplied") in exception.value) @context_available def test_create_special_buffers(self, velocity_verlet_cl_integrator): """There are no special buffers so this method does nothing.""" model, integrator = velocity_verlet_cl_integrator value = integrator._create_special_buffers() assert value is None

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null

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1

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1

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null

0

7

19a08639e22b385ded398f9e6eee2efac79fa737

4,187

py

Python

evaluation/examples.py

clamsproject/app-fastpunct

138a79a4d2bdc1e6c2ede036973e417fb9a41a86

[ "Apache-2.0" ]

null

evaluation/examples.py

clamsproject/app-fastpunct

138a79a4d2bdc1e6c2ede036973e417fb9a41a86

[ "Apache-2.0" ]

5

2021-09-20T15:11:30.000Z

2022-01-21T00:39:52.000Z

evaluation/examples.py

clamsproject/app-fastpunct

138a79a4d2bdc1e6c2ede036973e417fb9a41a86

[ "Apache-2.0" ]

null

"""examples.py Some examples for testing and eyeballing parts of the code. """ # This is an example segment where fastpunct inserts repetition into the string segment_with_duplicates_in = """judy woodruff after the news summary the twa bombing is once again our major focus tonight first israeli prime minister peres says who he thinks is to blame then we hear from a reporter who just returned from europe and the mideast finding out how the terrorists operate and from an airline safety expert we next move on to a sampling of what some astronauts had to say at today's shuttle disaster hearing finally a documentary report on what's being done to protect airliners from a killer called wind shear.news summary""" segment_with_duplicates_out = """Judy Woodruff after the news summary: "The TWA bombing is once again our major focus tonight first Israeli Prime Minister Peres says who he thinks is to blame then we hear from a reporter who just returned from Europe and the Mideast finding out how the terrorists operate and from an airline safety expert we next move on to a sampling of what some astronauts had to say at today's shuttle disaster hearing finally a documentary report on what's being done to protect airliners from a killer called Wind Shear.news summary: "After the news summary: The TWA bombing is once again our major focus tonight first Israeli Prime Minister Peters: "First Israeli Prime Minister Peres says who he thinks is to blame then we hear from a reporter who just returned from Europe and the mideast finding out how the terrorists operate and from an airline safety expert we next move on to a sampling of what some astronauts had to say at today's shuttle disaster hearing finally a documentary report on what some astronaut""" # Some cached results from prior invocations of fastpunct so we can run the code # quickly with loading all the libraries and running the slow code. cached_results = { 'been': 'Been.', "evening i'm jim lehrer on the newshour tonight phil ponce likes of the us military reservist call up what it means and who's affected senator attacked and urban debate new post colorado gun control proposals charles krauss tells the story of brazil's economic crisis and rebound and poet laureate robert pinsky reason ben johnson paul all on children and tragedy and all follows a summary that is this tuesday": "Evening I'm Jim Lehrer on the newshour tonight, Phil Ponce, likes of the U.S. military reservist, call up what it means and who's affected senator attacked and urban debate new post Colorado gun control proposals, Charles Krauss tells the story of Brazil's economic crisis and rebound and poet Laurent Pinsky reason Ben Johnson Paul All on Children and Tragicity and All follows a summary that is this Tuesday.", 'keating the world is the biggest challenge of the new century which is widely condemned promote satellite technology to help the american farmer be even more connected': 'Keating the world is the biggest challenge of the new century, which is widely condemned promote satellite technology to help the American farmer be even more connected.', 'the world': 'The world.', "by the corporation for public broadcasting and by the annual financial support from viewers like you president clinton authorized the pentagon today to call up more than thirty thousand reserve and national guard personnel they'll be used in the air campaign over kosovo and the three g i've captured by a bizarre troops were pronounced dead by red cross doctor as bagels bombing of serbia and the flight of ethnic albanian refugees from kosovo continue on beer narrates our update report": "By the Corporation for Public Broadcasting and by the annual financial support from viewers like you, President Clinton authorized the Pentagon today to call up more than thirty thousand Reserve and National Guard personnel they'll be used in the air campaign over Kosovo and the three G I've captured by a bizarre troops were pronounced dead by Red Cross doctor as Bagels bombing of Serbia and the flight of ethnic Albanian refugees from Kosovo continue on beer narrates, our update report." }

116.305556

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1

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1

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1

0

null

0

10

5fd6dffbd1b89e416601b838b06d2693561c2037

19,218

py

Python

piwebasync/api/controllers/eventframes.py

newvicx/piwebasync

fc0d159aa4b99667777f428a090fe7a102481fea

[ "MIT" ]

null

piwebasync/api/controllers/eventframes.py

newvicx/piwebasync

fc0d159aa4b99667777f428a090fe7a102481fea

[ "MIT" ]

2

2022-03-02T17:42:21.000Z

2022-03-29T19:24:01.000Z

piwebasync/api/controllers/eventframes.py

newvicx/piwebasync

fc0d159aa4b99667777f428a090fe7a102481fea

[ "MIT" ]

null

from datetime import datetime from typing import List, Tuple, Union from ...types import APIRequestType, ControllerType, QueryStrType class EventFrames: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe.html """ CONTROLLER = "eventframes" def __init__(self, constructor: ControllerType) -> None: self._constructor = constructor def get( self, webid: str, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/get.html """ action = None return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, selected_fields=selected_fields, web_id_type=web_id_type ) def get_by_path( self, path: str, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getbypath.html """ action = None return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, path=path, selected_fields=selected_fields, web_id_type=web_id_type ) def acknowledge( self, webid: str ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/acknowledge.html """ action = "acknowledge" return self._constructor._build_request( method="PATCH", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid ) def execute_search_by_attribute( self, search_id: str, search_mode: str = None, start_time: datetime = None, end_time: datetime = None, name_filter: QueryStrType = None, referenced_element_name_filter: QueryStrType = None, severity: Union[List[str], Tuple[str]] = None, can_be_acknowledged: str = None, is_acknowleged: str = None, search_full_hierarchy: bool = None, sort_field: str = None, sort_order: str = None, start_index: int = None, max_count: int = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/executesearchbyattribute.html """ action = "searchbyattribute" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, add_path=[search_id], search_mode=search_mode, start_time=start_time, end_time=end_time, name_filter=name_filter, referenced_element_name_filter=referenced_element_name_filter, severity_many=severity, can_be_acknowledged=can_be_acknowledged, is_acknowleged=is_acknowleged, search_full_hierarchy=search_full_hierarchy, sort_field=sort_field, sort_order=sort_order, start_index=start_index, max_count=max_count, selected_fields=selected_fields, web_id_type=web_id_type, ) def find_event_frame_attributes( self, webid: str, search_mode: str = None, start_time: datetime = None, end_time: datetime = None, event_frame_name_filter: QueryStrType = None, event_frame_description_filter: QueryStrType = None, referenced_element_name_filter: QueryStrType = None, event_frame_category: str = None, event_frame_template: str = None, attribute_name_filter: QueryStrType = None, attribute_description_filter: QueryStrType = None, attribute_category: str = None, attribute_type: str = None, search_full_hierarchy: bool = None, sort_field: str = None, sort_order: str = None, start_index: int = None, max_count: int = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, associations: Union[List[str], Tuple[str]] = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/findeventframeattributes.html """ action = "eventframeattributes" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, search_mode=search_mode, start_time=start_time, end_time=end_time, event_frame_name_filter=event_frame_name_filter, event_frame_description_filter=event_frame_description_filter, referenced_element_name_filter=referenced_element_name_filter, event_frame_category=event_frame_category, event_frame_template=event_frame_template, attribute_name_filter=attribute_name_filter, attribute_description_filter=attribute_description_filter, attribute_category=attribute_category, attribute_type=attribute_type, search_full_hierarchy=search_full_hierarchy, sort_field=sort_field, sort_order=sort_order, start_index=start_index, max_count=max_count, selected_fields=selected_fields, web_id_type=web_id_type, associations=associations ) def get_annotation_attachment_media_by_id( self, webid: str, id: str, disposition: str = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/get.html """ action = "annotations" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, add_path=[id, "attachment", "media"], disposition=disposition, selected_fields=selected_fields, web_id_type=web_id_type ) def get_annotation_attachment_media_data_by_id( self, webid: str, id: str, disposition: str = None ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getannotationattachmentmediadatabyid.html """ action = "annotations" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, add_path=[id, "attachment", "media", "mediadata"], disposition=disposition ) def get_annotation_attachment_media_metadata_by_id( self, webid: str, id: str, disposition: str = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getannotationattachmentmediametadatabyid.html """ action = "annotations" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, add_path=[id, "attachment", "media", "metadata"], disposition=disposition, selected_fields=selected_fields, web_id_type=web_id_type ) def get_annotation_by_id( self, webid: str, id: str, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getannotationbyid.html """ action = "annotations" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, add_path=[id], selected_fields=selected_fields, web_id_type=web_id_type ) def get_annotations( self, webid: str, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getannotations.html """ action = "annotations" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, selected_fields=selected_fields, web_id_type=web_id_type ) def get_attributes( self, webid: str, name_filter: QueryStrType = None, category_name: str = None, template_name: str = None, value_type: str = None, search_full_hierarchy: bool = None, sort_field: str = None, sort_order: str = None, start_index: int = None, show_excluded: bool = None, show_hidden: bool = None, max_count: int = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, associations: Union[List[str], Tuple[str]] = None, trait: Union[List[str], Tuple[str]] = None, trait_category: Union[List[str], Tuple[str]] = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getattributes.html """ action = "attributes" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, name_filter=name_filter, category_name=category_name, template_name=template_name, value_type=value_type, search_full_hierarchy=search_full_hierarchy, sort_field=sort_field, sort_order=sort_order, start_index=start_index, show_excluded=show_excluded, show_hidden=show_hidden, max_count=max_count, selected_fields=selected_fields, web_id_type=web_id_type, associations=associations, trait_many=trait, trait_category_many=trait_category ) def get_categories( self, webid: str, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getcategories.html """ action = "categories" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, selected_fields=selected_fields, web_id_type=web_id_type ) def get_event_frames( self, webid: str, search_mode: str = None, start_time: datetime = None, end_time: datetime = None, name_filter: QueryStrType = None, referenced_element_name_filter: QueryStrType = None, category_name: str = None, template_name: str = None, referenced_element_template_name: str = None, severity: Union[List[str], Tuple[str]] = None, can_be_acknowledged: str = None, is_acknowleged: str = None, search_full_hierarchy: bool = None, sort_field: str = None, sort_order: str = None, start_index: int = None, max_count: int = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/geteventframes.html """ action = "eventframes" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, search_mode=search_mode, start_time=start_time, end_time=end_time, name_filter=name_filter, referenced_element_name_filter=referenced_element_name_filter, category_name=category_name, template_name=template_name, referenced_element_template_name=referenced_element_template_name, severity_many=severity, can_be_acknowledged=can_be_acknowledged, is_acknowleged=is_acknowleged, search_full_hierarchy=search_full_hierarchy, sort_field=sort_field, sort_order=sort_order, start_index=start_index, max_count=max_count, selected_fields=selected_fields, web_id_type=web_id_type, ) def get_event_frames_query( self, database_web_id: str = None, query: QueryStrType = None, start_index: int = None, max_count: int = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/geteventframesquery.html """ action = "search" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, database_web_id=database_web_id, query=query, start_index=start_index, max_count=max_count, selected_fields=selected_fields, web_id_type=web_id_type, ) def get_multiple( self, webid: Union[List[str], Tuple[str]] = None, path: Union[List[str], Tuple[str]] = None, include_mode: str = None, as_parallel: bool = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, associations: Union[List[str], Tuple[str]] = None ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getmultiple.html """ assert webid is not None or path is not None action = "multiple" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, web_id=webid, paths=path, include_mode=include_mode, as_parallel=as_parallel, selected_fields=selected_fields, web_id_type=web_id_type, associations=associations ) def get_referenced_elements( self, webid: str, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, associations: Union[List[str], Tuple[str]] = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getreferencedelements.html """ action = "referencedelements" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, selected_fields=selected_fields, web_id_type=web_id_type, associations=associations ) def get_security( self, webid: str, user_identity: Union[List[str], Tuple[str]] = None, force_refresh: bool = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getsecurity.html """ action = "security" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, user_identity_many=user_identity, force_refresh=force_refresh, selected_fields=selected_fields, web_id_type=web_id_type ) def get_security_entries( self, webid: str, name_filter: QueryStrType = None, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getsecurityentries.html """ action = "securityentries" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, name_filter=name_filter, selected_fields=selected_fields, web_id_type=web_id_type, ) def get_security_entry_by_name( self, webid: str, name: str, selected_fields: Union[List[str], Tuple[str]] = None, web_id_type: str = None, ) -> APIRequestType: """ https://docs.osisoft.com/bundle/pi-web-api-reference/page/help/controllers/eventframe/actions/getsecurityentrybyname.html """ action = "securityentries" return self._constructor._build_request( method="GET", protocol="HTTP", controller=self.CONTROLLER, action=action, webid=webid, selected_fields=selected_fields, web_id_type=web_id_type, add_path = [name] )

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0

null

0

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2783e93113013aff83fa33e38dc1ab4de49fb418

1,994

py

Python

tests/test_probes.py

proofdock/chaos-kit

e7f7f8c37075872b503ad5dd95b8341760915b35

[ "Apache-2.0" ]

1

2020-11-29T00:00:13.000Z

tests/test_probes.py

proofdock/chaos-kit

e7f7f8c37075872b503ad5dd95b8341760915b35

[ "Apache-2.0" ]

17

2020-05-21T05:44:53.000Z

2020-10-24T07:03:35.000Z

tests/test_probes.py

proofdock/chaos-kit

e7f7f8c37075872b503ad5dd95b8341760915b35

[ "Apache-2.0" ]

null

from unittest.mock import ANY, patch from tests.fixtures import data from pdchaoskit.alert import probes @patch('pdchaoskit.alert.probes.client_session', spec=True) @patch('pdchaoskit.alert.probes.get_alert_rule', spec=True) @patch('pdchaoskit.alert.probes.get_alerts', spec=True) @patch('pdchaoskit.alert.probes.get_loaded_settings', spec=True) def test_probe_was_alert_fired_no_alerts(get_loaded_settings, get_alerts, get_alert_rule, session): # arrange get_alert_rule.return_value = {"latest_alert": {"status": "resolved"}} get_alerts.return_value = [] get_loaded_settings.return_value = data.provide_settings() # act result = probes.was_alert_fired('rule_1') assert result is False get_alert_rule.assert_called_once_with('rule_1', ANY) get_alerts.assert_called_once_with('rule_1', 'fired', ANY, ANY, ANY) @patch('pdchaoskit.alert.probes.client_session', spec=True) @patch('pdchaoskit.alert.probes.get_alert_rule', spec=True) def test_probe_was_alert_fired_latest_fired(get_alert_rule, session): # arrange get_alert_rule.return_value = {"latest_alert": {"status": "fired"}} # act result = probes.was_alert_fired('rule_1') assert result is True get_alert_rule.assert_called_once_with('rule_1', ANY) @patch('pdchaoskit.alert.probes.client_session', spec=True) @patch('pdchaoskit.alert.probes.get_alert_rule', spec=True) @patch('pdchaoskit.alert.probes.get_alerts', spec=True) @patch('pdchaoskit.alert.probes.get_loaded_settings', spec=True) def test_probe_was_alert_fired_fired_during_experiment(get_loaded_settings, get_alerts, get_alert_rule, session): # arrange get_alert_rule.return_value = {"latest_alert": {"status": "resolved"}} get_alerts.return_value = [{"alert_time": "2020-07-23T19:49:59Z"}] get_loaded_settings.return_value = data.provide_settings() # act result = probes.was_alert_fired('rule_1') assert result is True get_alert_rule.assert_called_once_with('rule_1', ANY)

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null

0

1

0

null

0

7

27cd44aba6863b40e053af69bed026dfa0a2e2b5

54,719

py

Python

pb/quota_pb2.py

zheng-zy/ot_root

920236b48458aeed72968bc7ec8e01a084b15951

[ "Artistic-2.0" ]

1

2016-03-23T07:54:55.000Z

pb/quota_pb2.py

zheng-zy/ot_root

920236b48458aeed72968bc7ec8e01a084b15951

[ "Artistic-2.0" ]

null

pb/quota_pb2.py

zheng-zy/ot_root

920236b48458aeed72968bc7ec8e01a084b15951

[ "Artistic-2.0" ]

1

2020-07-23T18:27:53.000Z

# Generated by the protocol buffer compiler. DO NOT EDIT! # source: quota.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database from google.protobuf import descriptor_pb2 # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() DESCRIPTOR = _descriptor.FileDescriptor( name='quota.proto', package='ly.quota', serialized_pb=_b('\n\x0bquota.proto\x12\x08ly.quota\",\n\nMarketInfo\x12\x0e\n\x06\x65xchid\x18\x01 \x02(\x05\x12\x0e\n\x06market\x18\x02 \x02(\t\"3\n\nMarketList\x12%\n\x07mk_list\x18\x01 \x03(\x0b\x32\x14.ly.quota.MarketInfo\"\x1e\n\x0c\x43odeTableReq\x12\x0e\n\x06\x65xchid\x18\x01 \x02(\x05\"!\n\x0f\x43odeTableChange\x12\x0e\n\x06\x65xchid\x18\x01 \x02(\x05\"R\n\x0cSecurityCode\x12\r\n\x05idnum\x18\x01 \x02(\x05\x12\x0c\n\x04type\x18\x02 \x02(\x05\x12\x15\n\rsecurity_code\x18\x03 \x02(\t\x12\x0e\n\x06symbol\x18\x04 \x02(\t\"\x82\x01\n\x10SecurityCodeResp\x12\x0e\n\x06source\x18\x01 \x02(\x05\x12\x0c\n\x04\x64\x61te\x18\x02 \x02(\x05\x12\r\n\x05\x63ount\x18\x03 \x02(\x05\x12\r\n\x05\x66lags\x18\x04 \x02(\x05\x12\x32\n\x12security_code_list\x18\x05 \x03(\x0b\x32\x16.ly.quota.SecurityCode\":\n\x15MarketDataReqByMdType\x12\x10\n\x08sub_type\x18\x01 \x02(\r\x12\x0f\n\x07mk_type\x18\x02 \x02(\r\"7\n\x14MarketDataReqByIdnum\x12\x10\n\x08sub_type\x18\x01 \x02(\r\x12\r\n\x05idnum\x18\x02 \x03(\x05\"\x9b\x04\n\nMarketData\x12\r\n\x05idnum\x18\x01 \x02(\x05\x12\x0c\n\x04time\x18\x02 \x02(\x05\x12\x0e\n\x06status\x18\x03 \x02(\x05\x12\x11\n\tpre_close\x18\x04 \x02(\r\x12\x0c\n\x04open\x18\x05 \x02(\r\x12\x0c\n\x04high\x18\x06 \x02(\r\x12\x0b\n\x03low\x18\x07 \x02(\r\x12\r\n\x05match\x18\x08 \x02(\r\x12\x15\n\task_price\x18\t \x03(\rB\x02\x10\x01\x12\x13\n\x07\x61sk_vol\x18\n \x03(\rB\x02\x10\x01\x12\x15\n\tbid_price\x18\x0b \x03(\rB\x02\x10\x01\x12\x13\n\x07\x62id_vol\x18\x0c \x03(\rB\x02\x10\x01\x12\x12\n\nnum_trades\x18\r \x02(\r\x12\x0e\n\x06volume\x18\x0e \x02(\x03\x12\x10\n\x08turnover\x18\x0f \x02(\x03\x12\x15\n\rtotal_bid_vol\x18\x10 \x02(\x03\x12\x15\n\rtotal_ask_vol\x18\x11 \x02(\x03\x12\x1e\n\x16weighted_avg_bid_price\x18\x12 \x02(\r\x12\x1e\n\x16weighted_avg_ask_price\x18\x13 \x02(\r\x12\x0c\n\x04iopv\x18\x14 \x02(\x05\x12\x19\n\x11yield_to_maturity\x18\x15 \x02(\x05\x12\x14\n\x0chigh_limited\x18\x16 \x02(\r\x12\x13\n\x0blow_limited\x18\x17 \x02(\r\x12\x0c\n\x04stat\x18\x18 \x02(\x05\x12\x10\n\x08pub_time\x18\x19 \x02(\x05\x12\x12\n\nnow_volume\x18\x1a \x02(\x03\x12\x11\n\tnow_value\x18\x1b \x02(\x03\"\xca\x01\n\tIndexData\x12\r\n\x05idnum\x18\x01 \x02(\x05\x12\x0c\n\x04time\x18\x02 \x02(\x05\x12\x12\n\nopen_index\x18\x03 \x02(\x05\x12\x12\n\nhigh_index\x18\x04 \x02(\x05\x12\x11\n\tlow_index\x18\x05 \x02(\x05\x12\x12\n\nlast_index\x18\x06 \x02(\x05\x12\x14\n\x0ctotal_volume\x18\x07 \x02(\x03\x12\x10\n\x08turnover\x18\x08 \x02(\x03\x12\x17\n\x0fpre_close_index\x18\t \x02(\x05\x12\x10\n\x08pub_time\x18\n \x02(\x05\"\xf0\x03\n\x11MarketDataFutures\x12\r\n\x05idnum\x18\x01 \x02(\x05\x12\x0c\n\x04time\x18\x02 \x02(\x05\x12\x0e\n\x06status\x18\x03 \x02(\x05\x12\x19\n\x11pre_open_interest\x18\x04 \x02(\x03\x12\x11\n\tpre_close\x18\x05 \x02(\r\x12\x18\n\x10pre_settle_price\x18\x06 \x02(\r\x12\x0c\n\x04open\x18\x07 \x02(\r\x12\x0c\n\x04high\x18\x08 \x02(\r\x12\x0b\n\x03low\x18\t \x02(\r\x12\x0c\n\x04last\x18\n \x02(\r\x12\x0e\n\x06volume\x18\x0b \x02(\x03\x12\x10\n\x08turnover\x18\x0c \x02(\x03\x12\x15\n\ropen_interest\x18\r \x02(\x03\x12\r\n\x05\x63lose\x18\x0e \x02(\r\x12\x14\n\x0csettle_price\x18\x0f \x02(\r\x12\x14\n\x0chigh_limited\x18\x10 \x02(\r\x12\x13\n\x0blow_limited\x18\x11 \x02(\r\x12\x11\n\tpre_delta\x18\x12 \x02(\x05\x12\x12\n\ncurr_delta\x18\x13 \x02(\x05\x12\x15\n\task_price\x18\x14 \x03(\rB\x02\x10\x01\x12\x13\n\x07\x61sk_vol\x18\x15 \x03(\rB\x02\x10\x01\x12\x15\n\tbid_price\x18\x16 \x03(\rB\x02\x10\x01\x12\x13\n\x07\x62id_vol\x18\x17 \x03(\rB\x02\x10\x01\x12\x15\n\raverage_price\x18\x18 \x01(\r\x12\x10\n\x08pub_time\x18\x19 \x02(\x05\"|\n\x0bTransaction\x12\r\n\x05idnum\x18\x01 \x02(\x05\x12\x0c\n\x04time\x18\x02 \x02(\x05\x12\r\n\x05index\x18\x03 \x02(\x05\x12\r\n\x05price\x18\x04 \x02(\x05\x12\x0e\n\x06volume\x18\x05 \x02(\x05\x12\x10\n\x08turnover\x18\x06 \x02(\x05\x12\x10\n\x08pub_time\x18\x07 \x02(\x05\"\xc6\x01\n\x11TransactionExItem\x12\x0c\n\x04time\x18\x01 \x01(\x05\x12\x10\n\x08trade_no\x18\x02 \x01(\x05\x12\r\n\x05price\x18\x03 \x01(\x05\x12\x0e\n\x06volume\x18\x04 \x01(\x05\x12\x10\n\x08turnover\x18\x05 \x01(\x05\x12\x0f\n\x07\x62s_flag\x18\x06 \x01(\x05\x12\x12\n\norder_kind\x18\x07 \x01(\x05\x12\x15\n\rfunction_code\x18\x08 \x01(\x05\x12\x11\n\task_order\x18\t \x01(\x05\x12\x11\n\tbid_order\x18\n \x01(\x05\"k\n\rTransactionEx\x12\r\n\x05idnum\x18\x01 \x01(\x05\x12\r\n\x05\x63ount\x18\x02 \x01(\x05\x12\x10\n\x08pub_time\x18\x03 \x01(\x05\x12*\n\x05items\x18\x04 \x03(\x0b\x32\x1b.ly.quota.TransactionExItem\"y\n\nOrderQueue\x12\r\n\x05idnum\x18\x01 \x02(\x05\x12\x0c\n\x04time\x18\x02 \x02(\x05\x12\x0c\n\x04side\x18\x03 \x02(\x05\x12\r\n\x05price\x18\x04 \x02(\x05\x12\x0e\n\x06orders\x18\x05 \x02(\x05\x12\x0f\n\x07volumes\x18\x06 \x03(\x05\x12\x10\n\x08pub_time\x18\x07 \x02(\x05') ) _sym_db.RegisterFileDescriptor(DESCRIPTOR) _MARKETINFO = _descriptor.Descriptor( name='MarketInfo', full_name='ly.quota.MarketInfo', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='exchid', full_name='ly.quota.MarketInfo.exchid', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='market', full_name='ly.quota.MarketInfo.market', index=1, number=2, type=9, cpp_type=9, label=2, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=25, serialized_end=69, ) _MARKETLIST = _descriptor.Descriptor( name='MarketList', full_name='ly.quota.MarketList', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='mk_list', full_name='ly.quota.MarketList.mk_list', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=71, serialized_end=122, ) _CODETABLEREQ = _descriptor.Descriptor( name='CodeTableReq', full_name='ly.quota.CodeTableReq', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='exchid', full_name='ly.quota.CodeTableReq.exchid', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=124, serialized_end=154, ) _CODETABLECHANGE = _descriptor.Descriptor( name='CodeTableChange', full_name='ly.quota.CodeTableChange', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='exchid', full_name='ly.quota.CodeTableChange.exchid', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=156, serialized_end=189, ) _SECURITYCODE = _descriptor.Descriptor( name='SecurityCode', full_name='ly.quota.SecurityCode', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.SecurityCode.idnum', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='type', full_name='ly.quota.SecurityCode.type', index=1, number=2, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='security_code', full_name='ly.quota.SecurityCode.security_code', index=2, number=3, type=9, cpp_type=9, label=2, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='symbol', full_name='ly.quota.SecurityCode.symbol', index=3, number=4, type=9, cpp_type=9, label=2, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=191, serialized_end=273, ) _SECURITYCODERESP = _descriptor.Descriptor( name='SecurityCodeResp', full_name='ly.quota.SecurityCodeResp', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='source', full_name='ly.quota.SecurityCodeResp.source', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='date', full_name='ly.quota.SecurityCodeResp.date', index=1, number=2, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='count', full_name='ly.quota.SecurityCodeResp.count', index=2, number=3, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='flags', full_name='ly.quota.SecurityCodeResp.flags', index=3, number=4, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='security_code_list', full_name='ly.quota.SecurityCodeResp.security_code_list', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=276, serialized_end=406, ) _MARKETDATAREQBYMDTYPE = _descriptor.Descriptor( name='MarketDataReqByMdType', full_name='ly.quota.MarketDataReqByMdType', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='sub_type', full_name='ly.quota.MarketDataReqByMdType.sub_type', index=0, number=1, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='mk_type', full_name='ly.quota.MarketDataReqByMdType.mk_type', index=1, number=2, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=408, serialized_end=466, ) _MARKETDATAREQBYIDNUM = _descriptor.Descriptor( name='MarketDataReqByIdnum', full_name='ly.quota.MarketDataReqByIdnum', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='sub_type', full_name='ly.quota.MarketDataReqByIdnum.sub_type', index=0, number=1, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.MarketDataReqByIdnum.idnum', index=1, number=2, type=5, cpp_type=1, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=468, serialized_end=523, ) _MARKETDATA = _descriptor.Descriptor( name='MarketData', full_name='ly.quota.MarketData', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.MarketData.idnum', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='time', full_name='ly.quota.MarketData.time', index=1, number=2, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='status', full_name='ly.quota.MarketData.status', index=2, number=3, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pre_close', full_name='ly.quota.MarketData.pre_close', index=3, number=4, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='open', full_name='ly.quota.MarketData.open', index=4, number=5, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='high', full_name='ly.quota.MarketData.high', index=5, number=6, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='low', full_name='ly.quota.MarketData.low', index=6, number=7, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='match', full_name='ly.quota.MarketData.match', index=7, number=8, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='ask_price', full_name='ly.quota.MarketData.ask_price', index=8, number=9, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='ask_vol', full_name='ly.quota.MarketData.ask_vol', index=9, number=10, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='bid_price', full_name='ly.quota.MarketData.bid_price', index=10, number=11, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='bid_vol', full_name='ly.quota.MarketData.bid_vol', index=11, number=12, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='num_trades', full_name='ly.quota.MarketData.num_trades', index=12, number=13, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='volume', full_name='ly.quota.MarketData.volume', index=13, number=14, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='turnover', full_name='ly.quota.MarketData.turnover', index=14, number=15, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='total_bid_vol', full_name='ly.quota.MarketData.total_bid_vol', index=15, number=16, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='total_ask_vol', full_name='ly.quota.MarketData.total_ask_vol', index=16, number=17, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='weighted_avg_bid_price', full_name='ly.quota.MarketData.weighted_avg_bid_price', index=17, number=18, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='weighted_avg_ask_price', full_name='ly.quota.MarketData.weighted_avg_ask_price', index=18, number=19, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='iopv', full_name='ly.quota.MarketData.iopv', index=19, number=20, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='yield_to_maturity', full_name='ly.quota.MarketData.yield_to_maturity', index=20, number=21, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='high_limited', full_name='ly.quota.MarketData.high_limited', index=21, number=22, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='low_limited', full_name='ly.quota.MarketData.low_limited', index=22, number=23, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='stat', full_name='ly.quota.MarketData.stat', index=23, number=24, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pub_time', full_name='ly.quota.MarketData.pub_time', index=24, number=25, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='now_volume', full_name='ly.quota.MarketData.now_volume', index=25, number=26, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='now_value', full_name='ly.quota.MarketData.now_value', index=26, number=27, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=526, serialized_end=1065, ) _INDEXDATA = _descriptor.Descriptor( name='IndexData', full_name='ly.quota.IndexData', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.IndexData.idnum', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='time', full_name='ly.quota.IndexData.time', index=1, number=2, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='open_index', full_name='ly.quota.IndexData.open_index', index=2, number=3, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='high_index', full_name='ly.quota.IndexData.high_index', index=3, number=4, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='low_index', full_name='ly.quota.IndexData.low_index', index=4, number=5, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='last_index', full_name='ly.quota.IndexData.last_index', index=5, number=6, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='total_volume', full_name='ly.quota.IndexData.total_volume', index=6, number=7, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='turnover', full_name='ly.quota.IndexData.turnover', index=7, number=8, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pre_close_index', full_name='ly.quota.IndexData.pre_close_index', index=8, number=9, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pub_time', full_name='ly.quota.IndexData.pub_time', index=9, number=10, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=1068, serialized_end=1270, ) _MARKETDATAFUTURES = _descriptor.Descriptor( name='MarketDataFutures', full_name='ly.quota.MarketDataFutures', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.MarketDataFutures.idnum', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='time', full_name='ly.quota.MarketDataFutures.time', index=1, number=2, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='status', full_name='ly.quota.MarketDataFutures.status', index=2, number=3, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pre_open_interest', full_name='ly.quota.MarketDataFutures.pre_open_interest', index=3, number=4, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pre_close', full_name='ly.quota.MarketDataFutures.pre_close', index=4, number=5, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pre_settle_price', full_name='ly.quota.MarketDataFutures.pre_settle_price', index=5, number=6, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='open', full_name='ly.quota.MarketDataFutures.open', index=6, number=7, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='high', full_name='ly.quota.MarketDataFutures.high', index=7, number=8, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='low', full_name='ly.quota.MarketDataFutures.low', index=8, number=9, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='last', full_name='ly.quota.MarketDataFutures.last', index=9, number=10, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='volume', full_name='ly.quota.MarketDataFutures.volume', index=10, number=11, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='turnover', full_name='ly.quota.MarketDataFutures.turnover', index=11, number=12, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='open_interest', full_name='ly.quota.MarketDataFutures.open_interest', index=12, number=13, type=3, cpp_type=2, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='close', full_name='ly.quota.MarketDataFutures.close', index=13, number=14, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='settle_price', full_name='ly.quota.MarketDataFutures.settle_price', index=14, number=15, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='high_limited', full_name='ly.quota.MarketDataFutures.high_limited', index=15, number=16, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='low_limited', full_name='ly.quota.MarketDataFutures.low_limited', index=16, number=17, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pre_delta', full_name='ly.quota.MarketDataFutures.pre_delta', index=17, number=18, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='curr_delta', full_name='ly.quota.MarketDataFutures.curr_delta', index=18, number=19, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='ask_price', full_name='ly.quota.MarketDataFutures.ask_price', index=19, number=20, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='ask_vol', full_name='ly.quota.MarketDataFutures.ask_vol', index=20, number=21, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='bid_price', full_name='ly.quota.MarketDataFutures.bid_price', index=21, number=22, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='bid_vol', full_name='ly.quota.MarketDataFutures.bid_vol', index=22, number=23, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001'))), _descriptor.FieldDescriptor( name='average_price', full_name='ly.quota.MarketDataFutures.average_price', index=23, number=24, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pub_time', full_name='ly.quota.MarketDataFutures.pub_time', index=24, number=25, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=1273, serialized_end=1769, ) _TRANSACTION = _descriptor.Descriptor( name='Transaction', full_name='ly.quota.Transaction', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.Transaction.idnum', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='time', full_name='ly.quota.Transaction.time', index=1, number=2, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='index', full_name='ly.quota.Transaction.index', index=2, number=3, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='price', full_name='ly.quota.Transaction.price', index=3, number=4, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='volume', full_name='ly.quota.Transaction.volume', index=4, number=5, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='turnover', full_name='ly.quota.Transaction.turnover', index=5, number=6, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pub_time', full_name='ly.quota.Transaction.pub_time', index=6, number=7, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=1771, serialized_end=1895, ) _TRANSACTIONEXITEM = _descriptor.Descriptor( name='TransactionExItem', full_name='ly.quota.TransactionExItem', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='time', full_name='ly.quota.TransactionExItem.time', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='trade_no', full_name='ly.quota.TransactionExItem.trade_no', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='price', full_name='ly.quota.TransactionExItem.price', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='volume', full_name='ly.quota.TransactionExItem.volume', index=3, number=4, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='turnover', full_name='ly.quota.TransactionExItem.turnover', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='bs_flag', full_name='ly.quota.TransactionExItem.bs_flag', index=5, number=6, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='order_kind', full_name='ly.quota.TransactionExItem.order_kind', index=6, number=7, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='function_code', full_name='ly.quota.TransactionExItem.function_code', index=7, number=8, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='ask_order', full_name='ly.quota.TransactionExItem.ask_order', index=8, number=9, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='bid_order', full_name='ly.quota.TransactionExItem.bid_order', index=9, number=10, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=1898, serialized_end=2096, ) _TRANSACTIONEX = _descriptor.Descriptor( name='TransactionEx', full_name='ly.quota.TransactionEx', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.TransactionEx.idnum', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='count', full_name='ly.quota.TransactionEx.count', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pub_time', full_name='ly.quota.TransactionEx.pub_time', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='items', full_name='ly.quota.TransactionEx.items', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=2098, serialized_end=2205, ) _ORDERQUEUE = _descriptor.Descriptor( name='OrderQueue', full_name='ly.quota.OrderQueue', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='idnum', full_name='ly.quota.OrderQueue.idnum', index=0, number=1, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='time', full_name='ly.quota.OrderQueue.time', index=1, number=2, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='side', full_name='ly.quota.OrderQueue.side', index=2, number=3, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='price', full_name='ly.quota.OrderQueue.price', index=3, number=4, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='orders', full_name='ly.quota.OrderQueue.orders', index=4, number=5, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='volumes', full_name='ly.quota.OrderQueue.volumes', index=5, number=6, type=5, cpp_type=1, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pub_time', full_name='ly.quota.OrderQueue.pub_time', index=6, number=7, type=5, cpp_type=1, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=2207, serialized_end=2328, ) _MARKETLIST.fields_by_name['mk_list'].message_type = _MARKETINFO _SECURITYCODERESP.fields_by_name['security_code_list'].message_type = _SECURITYCODE _TRANSACTIONEX.fields_by_name['items'].message_type = _TRANSACTIONEXITEM DESCRIPTOR.message_types_by_name['MarketInfo'] = _MARKETINFO DESCRIPTOR.message_types_by_name['MarketList'] = _MARKETLIST DESCRIPTOR.message_types_by_name['CodeTableReq'] = _CODETABLEREQ DESCRIPTOR.message_types_by_name['CodeTableChange'] = _CODETABLECHANGE DESCRIPTOR.message_types_by_name['SecurityCode'] = _SECURITYCODE DESCRIPTOR.message_types_by_name['SecurityCodeResp'] = _SECURITYCODERESP DESCRIPTOR.message_types_by_name['MarketDataReqByMdType'] = _MARKETDATAREQBYMDTYPE DESCRIPTOR.message_types_by_name['MarketDataReqByIdnum'] = _MARKETDATAREQBYIDNUM DESCRIPTOR.message_types_by_name['MarketData'] = _MARKETDATA DESCRIPTOR.message_types_by_name['IndexData'] = _INDEXDATA DESCRIPTOR.message_types_by_name['MarketDataFutures'] = _MARKETDATAFUTURES DESCRIPTOR.message_types_by_name['Transaction'] = _TRANSACTION DESCRIPTOR.message_types_by_name['TransactionExItem'] = _TRANSACTIONEXITEM DESCRIPTOR.message_types_by_name['TransactionEx'] = _TRANSACTIONEX DESCRIPTOR.message_types_by_name['OrderQueue'] = _ORDERQUEUE MarketInfo = _reflection.GeneratedProtocolMessageType('MarketInfo', (_message.Message,), dict( DESCRIPTOR = _MARKETINFO, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.MarketInfo) )) _sym_db.RegisterMessage(MarketInfo) MarketList = _reflection.GeneratedProtocolMessageType('MarketList', (_message.Message,), dict( DESCRIPTOR = _MARKETLIST, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.MarketList) )) _sym_db.RegisterMessage(MarketList) CodeTableReq = _reflection.GeneratedProtocolMessageType('CodeTableReq', (_message.Message,), dict( DESCRIPTOR = _CODETABLEREQ, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.CodeTableReq) )) _sym_db.RegisterMessage(CodeTableReq) CodeTableChange = _reflection.GeneratedProtocolMessageType('CodeTableChange', (_message.Message,), dict( DESCRIPTOR = _CODETABLECHANGE, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.CodeTableChange) )) _sym_db.RegisterMessage(CodeTableChange) SecurityCode = _reflection.GeneratedProtocolMessageType('SecurityCode', (_message.Message,), dict( DESCRIPTOR = _SECURITYCODE, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.SecurityCode) )) _sym_db.RegisterMessage(SecurityCode) SecurityCodeResp = _reflection.GeneratedProtocolMessageType('SecurityCodeResp', (_message.Message,), dict( DESCRIPTOR = _SECURITYCODERESP, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.SecurityCodeResp) )) _sym_db.RegisterMessage(SecurityCodeResp) MarketDataReqByMdType = _reflection.GeneratedProtocolMessageType('MarketDataReqByMdType', (_message.Message,), dict( DESCRIPTOR = _MARKETDATAREQBYMDTYPE, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.MarketDataReqByMdType) )) _sym_db.RegisterMessage(MarketDataReqByMdType) MarketDataReqByIdnum = _reflection.GeneratedProtocolMessageType('MarketDataReqByIdnum', (_message.Message,), dict( DESCRIPTOR = _MARKETDATAREQBYIDNUM, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.MarketDataReqByIdnum) )) _sym_db.RegisterMessage(MarketDataReqByIdnum) MarketData = _reflection.GeneratedProtocolMessageType('MarketData', (_message.Message,), dict( DESCRIPTOR = _MARKETDATA, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.MarketData) )) _sym_db.RegisterMessage(MarketData) IndexData = _reflection.GeneratedProtocolMessageType('IndexData', (_message.Message,), dict( DESCRIPTOR = _INDEXDATA, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.IndexData) )) _sym_db.RegisterMessage(IndexData) MarketDataFutures = _reflection.GeneratedProtocolMessageType('MarketDataFutures', (_message.Message,), dict( DESCRIPTOR = _MARKETDATAFUTURES, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.MarketDataFutures) )) _sym_db.RegisterMessage(MarketDataFutures) Transaction = _reflection.GeneratedProtocolMessageType('Transaction', (_message.Message,), dict( DESCRIPTOR = _TRANSACTION, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.Transaction) )) _sym_db.RegisterMessage(Transaction) TransactionExItem = _reflection.GeneratedProtocolMessageType('TransactionExItem', (_message.Message,), dict( DESCRIPTOR = _TRANSACTIONEXITEM, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.TransactionExItem) )) _sym_db.RegisterMessage(TransactionExItem) TransactionEx = _reflection.GeneratedProtocolMessageType('TransactionEx', (_message.Message,), dict( DESCRIPTOR = _TRANSACTIONEX, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.TransactionEx) )) _sym_db.RegisterMessage(TransactionEx) OrderQueue = _reflection.GeneratedProtocolMessageType('OrderQueue', (_message.Message,), dict( DESCRIPTOR = _ORDERQUEUE, __module__ = 'quota_pb2' # @@protoc_insertion_point(class_scope:ly.quota.OrderQueue) )) _sym_db.RegisterMessage(OrderQueue) _MARKETDATA.fields_by_name['ask_price'].has_options = True _MARKETDATA.fields_by_name['ask_price']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) _MARKETDATA.fields_by_name['ask_vol'].has_options = True _MARKETDATA.fields_by_name['ask_vol']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) _MARKETDATA.fields_by_name['bid_price'].has_options = True _MARKETDATA.fields_by_name['bid_price']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) _MARKETDATA.fields_by_name['bid_vol'].has_options = True _MARKETDATA.fields_by_name['bid_vol']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) _MARKETDATAFUTURES.fields_by_name['ask_price'].has_options = True _MARKETDATAFUTURES.fields_by_name['ask_price']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) _MARKETDATAFUTURES.fields_by_name['ask_vol'].has_options = True _MARKETDATAFUTURES.fields_by_name['ask_vol']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) _MARKETDATAFUTURES.fields_by_name['bid_price'].has_options = True _MARKETDATAFUTURES.fields_by_name['bid_price']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) _MARKETDATAFUTURES.fields_by_name['bid_vol'].has_options = True _MARKETDATAFUTURES.fields_by_name['bid_vol']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\020\001')) # @@protoc_insertion_point(module_scope)

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fdb1e61928e3dc7743483c423fb65c045dbb2ecc

8,552

py

Python

src/tsar_test_add_NN.py

gentry-atkinson/tsar

cb7ae0ef8e2d45169e6cdee7d941a08b694b6292

[ "CC-BY-4.0" ]

null

src/tsar_test_add_NN.py

gentry-atkinson/tsar

cb7ae0ef8e2d45169e6cdee7d941a08b694b6292

[ "CC-BY-4.0" ]

null

src/tsar_test_add_NN.py

gentry-atkinson/tsar

cb7ae0ef8e2d45169e6cdee7d941a08b694b6292

[ "CC-BY-4.0" ]

null

#Author: Gentry Atkinson #Organization: Texas University #Data: 30 December, 2020 #Expand the tsar test to additional models using the features sets from "tsar test" import datetime import numpy as np from tensorflow.keras import Sequential from tensorflow.keras.layers import Input from tensorflow.keras.layers import Dense from sklearn.metrics import accuracy_score from sklearn.model_selection import train_test_split if __name__ == "__main__": unimib_feats_noisy = np.genfromtxt("test/visualizations_for_unimib_sup/UniMiB_sup_feat.csv", delimiter=',') unimib_y_noisy = np.genfromtxt("test/visualizations_for_unimib_sup/UniMiB_shuffeled_labels.csv", delimiter=',', dtype='int32') #unimib_y_noisy = np.argmax(unimib_y_noisy, axis=-1) unimib_bad_guys = np.genfromtxt("test/visualizations_for_unimib_sup/UniMiB_identified_bad.csv", delimiter=',') unimib_feats_clean = np.delete(unimib_feats_noisy, unimib_bad_guys, 0) unimib_y_clean = np.delete(unimib_y_noisy, unimib_bad_guys, 0) print("Unimib noisy features shape: ", unimib_feats_noisy.shape) print("Unimib noisy y shape: ", unimib_y_noisy.shape) print("Unimib clean features shape: ", unimib_feats_clean.shape) print("Unimib clean y shape: ", unimib_y_clean.shape) num_labels = unimib_y_noisy.shape[1] log = open("data_cleaning_experiments_results.txt", 'a+') log.write("{}\n".format(datetime.datetime.now())) log.write("------- UniMiB NN Experiments-----------\n\n") noisy_X_train, noisy_X_test, noisy_y_train, noisy_y_test = train_test_split(unimib_feats_noisy, unimib_y_noisy, test_size=0.2, shuffle=False) clean_X_train, clean_X_test, clean_y_train, clean_y_test = train_test_split(unimib_feats_clean, unimib_y_clean, test_size=0.2, shuffle=False) log.write("3-layer NN results: \n") noisy_model = Sequential([ Input(shape=noisy_X_train[0].shape), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(num_labels, activation='softmax') ]) clean_model = Sequential([ Input(shape=clean_X_train[0].shape), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(num_labels, activation='softmax') ]) noisy_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) noisy_model.summary() clean_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) clean_model.summary() noisy_model.fit(noisy_X_train, noisy_y_train, epochs=20, verbose=1) noisy_y_pred = noisy_model.predict(noisy_X_test) clean_model.fit(clean_X_train, clean_y_train, epochs=20, verbose=1) clean_y_pred = clean_model.predict(clean_X_test) noisy_acc = accuracy_score(np.argmax(noisy_y_test, axis=-1), np.argmax(noisy_y_pred, axis=-1)) clean_acc = accuracy_score(np.argmax(clean_y_test, axis=-1), np.argmax(clean_y_pred, axis=-1)) log.write("Noisy: {}\n".format(noisy_acc)) log.write("Clean: {}\n".format(clean_acc)) log.write("===\n\n".format(clean_acc)) log.write("6-layer NN results: \n") noisy_model = Sequential([ Input(shape=noisy_X_train[0].shape), Dense(128, activation='relu'), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(64, activation='relu'), Dense(32, activation='relu'), Dense(num_labels, activation='softmax') ]) clean_model = Sequential([ Input(shape=clean_X_train[0].shape), Dense(128, activation='relu'), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(64, activation='relu'), Dense(32, activation='relu'), Dense(num_labels, activation='softmax') ]) noisy_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) noisy_model.summary() clean_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) clean_model.summary() noisy_model.fit(noisy_X_train, noisy_y_train, epochs=20, verbose=1) noisy_y_pred = noisy_model.predict(noisy_X_test) clean_model.fit(clean_X_train, clean_y_train, epochs=20, verbose=1) clean_y_pred = clean_model.predict(clean_X_test) noisy_acc = accuracy_score(np.argmax(noisy_y_test, axis=-1), np.argmax(noisy_y_pred, axis=-1)) clean_acc = accuracy_score(np.argmax(clean_y_test, axis=-1), np.argmax(clean_y_pred, axis=-1)) log.write("Noisy: {}\n".format(noisy_acc)) log.write("Clean: {}\n".format(clean_acc)) log.write("===\n\n".format(clean_acc)) log.flush() uci_feats_noisy = np.genfromtxt("test/visualizations_for_uci_sup/UCI_sup_feat.csv", delimiter=',') uci_y_noisy = np.genfromtxt("test/visualizations_for_uci_sup/UCI_shuffeled_labels.csv", delimiter=',', dtype='int32') #uci_y_noisy = np.argmax(uci_y_noisy, axis=-1) uci_bad_guys = np.genfromtxt("test/visualizations_for_uci_sup/UCI_identified_bad.csv", delimiter=',') uci_feats_clean = np.delete(uci_feats_noisy, uci_bad_guys, 0) uci_y_clean = np.delete(uci_y_noisy, uci_bad_guys, 0) print("UCI noisy features shape: ", uci_feats_noisy.shape) print("UCI noisy y shape: ", uci_y_noisy.shape) print("UCI clean features shape: ", uci_feats_clean.shape) print("UCI clean y shape: ", uci_y_clean.shape) num_labels = uci_y_noisy.shape[1] log.write("------- UCI NN Experiments-----------\n\n") noisy_X_train, noisy_X_test, noisy_y_train, noisy_y_test = train_test_split(uci_feats_noisy, uci_y_noisy, test_size=0.2, shuffle=False) clean_X_train, clean_X_test, clean_y_train, clean_y_test = train_test_split(uci_feats_clean, uci_y_clean, test_size=0.2, shuffle=False) log.write("3-layer NN results: \n") noisy_model = Sequential([ Input(shape=noisy_X_train[0].shape), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(num_labels, activation='softmax') ]) clean_model = Sequential([ Input(shape=clean_X_train[0].shape), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(num_labels, activation='softmax') ]) noisy_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) noisy_model.summary() clean_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) clean_model.summary() noisy_model.fit(noisy_X_train, noisy_y_train, epochs=20, verbose=1) noisy_y_pred = noisy_model.predict(noisy_X_test) clean_model.fit(clean_X_train, clean_y_train, epochs=20, verbose=1) clean_y_pred = clean_model.predict(clean_X_test) noisy_acc = accuracy_score(np.argmax(noisy_y_test, axis=-1), np.argmax(noisy_y_pred, axis=-1)) clean_acc = accuracy_score(np.argmax(clean_y_test, axis=-1), np.argmax(clean_y_pred, axis=-1)) log.write("Noisy: {}\n".format(noisy_acc)) log.write("Clean: {}\n".format(clean_acc)) log.write("===\n\n".format(clean_acc)) log.write("6-layer NN results: \n") noisy_model = Sequential([ Input(shape=noisy_X_train[0].shape), Dense(128, activation='relu'), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(64, activation='relu'), Dense(32, activation='relu'), Dense(num_labels, activation='softmax') ]) clean_model = Sequential([ Input(shape=clean_X_train[0].shape), Dense(128, activation='relu'), Dense(128, activation='relu'), Dense(64, activation='relu'), Dense(64, activation='relu'), Dense(32, activation='relu'), Dense(num_labels, activation='softmax') ]) noisy_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) noisy_model.summary() clean_model.compile(optimizer='RMSprop', loss='categorical_crossentropy', metrics=['acc']) clean_model.summary() noisy_model.fit(noisy_X_train, noisy_y_train, epochs=20, verbose=1) noisy_y_pred = noisy_model.predict(noisy_X_test) clean_model.fit(clean_X_train, clean_y_train, epochs=20, verbose=1) clean_y_pred = clean_model.predict(clean_X_test) noisy_acc = accuracy_score(np.argmax(noisy_y_test, axis=-1), np.argmax(noisy_y_pred, axis=-1)) clean_acc = accuracy_score(np.argmax(clean_y_test, axis=-1), np.argmax(clean_y_pred, axis=-1)) log.write("Noisy: {}\n".format(noisy_acc)) log.write("Clean: {}\n".format(clean_acc)) log.write("===\n\n".format(clean_acc)) log.flush() log.close()

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7

e359e4fb6f2c72beba5be6e2a26a31fcda0bcfd4

595

py

Python

HMS/Hospital/apps.py

Arshad360/Hospital-Management-System-Cse327-Projectr

707ab80d021f8a2d10e28b25dd8df5aea512787a

[ "MIT" ]

2

2021-02-10T18:10:30.000Z

2021-04-27T18:07:51.000Z

HMS/Hospital/apps.py

Arshad360/Hospital-Management-System-Cse327-Projectr

707ab80d021f8a2d10e28b25dd8df5aea512787a

[ "MIT" ]

1

2020-09-23T19:00:54.000Z

2020-09-23T19:04:22.000Z

HMS/Hospital/apps.py

Arshad360/Hospital-Management-System-Cse327-Projectr

707ab80d021f8a2d10e28b25dd8df5aea512787a

[ "MIT" ]

1

2021-05-02T17:11:33.000Z

from django.apps import AppConfig class HospitalConfig(AppConfig): name = 'Hospital' class loginConfiq(AppConfig): name = 'Pharmacy' class PharmacyConfiq(AppConfig): name = 'Pharmacy' class Confiq(AppConfig): name = 'Pharmacy' class PharmacyConfiq(AppConfig): name = 'Pharmacy' class PharmacyConfiq(AppConfig): name = 'Pharmacy' class PharmacyConfiq(AppConfig): name = 'Pharmacy' class PharmacyConfiq(AppConfig): name = 'Pharmacy' class PharmacyConfiq(AppConfig): name = 'Pharmacy' class PharmacyConfiq(AppConfig): name = 'Pharmacy' =======

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null

0

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10

8b6c0c8308e1bd22ac4151aed290b7134c88ce41

10,346

py

Python

tests/automation_framework/tests/work_order_tests/test_submit_getresult.py

anjalirx-intel/avalon

5efd20612948a324b8a393bfe22872aeb8527097

[ "Apache-2.0" ]

null

tests/automation_framework/tests/work_order_tests/test_submit_getresult.py

anjalirx-intel/avalon

5efd20612948a324b8a393bfe22872aeb8527097

[ "Apache-2.0" ]

null

tests/automation_framework/tests/work_order_tests/test_submit_getresult.py

anjalirx-intel/avalon

5efd20612948a324b8a393bfe22872aeb8527097

[ "Apache-2.0" ]

null

import pytest import logging import os import env import json from src.libs.avalon_test_wrapper \ import read_json, submit_request from src.libs.test_base import AvalonBase from src.utilities.verification_utils \ import verify_test, check_negative_test_responses from src.utilities.worker_utilities import ResultStatus from src.utilities.worker_utilities import GetResultWaitTime import time logger = logging.getLogger(__name__) class TestClass(): test_obj = AvalonBase() @pytest.mark.workordergetresult @pytest.mark.listener @pytest.mark.sdk @pytest.mark.fabric @pytest.mark.ethereum @pytest.mark.positive def test_workordergetresult_success(self): test_id = '18702' request_file = os.path.join( env.work_order_input_file, "work_order_getresult.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert ( verify_test( submit_response, 0, self.test_obj.build_request_output['pre_test_output'], self.test_obj.build_request_output['action_obj']) is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.sdk @pytest.mark.fabric @pytest.mark.ethereum @pytest.mark.listener @pytest.mark.negative def test_workordergetresult_workorderid_different(self): test_id = '18873' request_file = os.path.join( env.work_order_input_file, "workordergetresult_workorderid_different.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert ( check_negative_test_responses( submit_response, "Invalid work order Id") is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.sdk @pytest.mark.fabric @pytest.mark.ethereum @pytest.mark.listener @pytest.mark.negative def test_workordergetresult_workorderid_specialchar(self): test_id = '18874' request_file = os.path.join( env.work_order_input_file, "workordergetresult_workorderid_specialchar.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert ( check_negative_test_responses( submit_response, "Invalid work order Id") is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.sdk @pytest.mark.fabric @pytest.mark.ethereum @pytest.mark.listener @pytest.mark.negative def test_workordergetresult_workorderid_null(self): test_id = '18875' request_file = os.path.join( env.work_order_input_file, "workordergetresult_workorderid_null.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert ( check_negative_test_responses( submit_response, "Invalid work order Id") is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.sdk @pytest.mark.fabric @pytest.mark.ethereum @pytest.mark.listener @pytest.mark.negative def test_workordergetresult_workorderid_nonhexstring(self): test_id = '18876' request_file = os.path.join( env.work_order_input_file, "workordergetresult_workorderid_nonhexstring.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert ( check_negative_test_responses( submit_response, "Work order Id not found in the database. Hence invalid parameter") is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.sdk @pytest.mark.fabric @pytest.mark.ethereum @pytest.mark.listener @pytest.mark.negative def test_workordergetresult_workorderid_alphabetsonly(self): test_id = '18877' request_file = os.path.join( env.work_order_input_file, "workordergetresult_workorderid_alphabetsonly.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert ( check_negative_test_responses( submit_response, "Invalid work order Id") is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.sdk @pytest.mark.fabric @pytest.mark.ethereum @pytest.mark.listener @pytest.mark.negative def test_workordergetresult_workorderid_withoutquotes(self): test_id = '18878' request_file = os.path.join( env.work_order_input_file, "workordergetresult_workorderid_withoutquotes.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert ( check_negative_test_responses( submit_response, "Invalid params") is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.negative def test_workordergetresult_emptyparameter(self): test_id = '20322' request_file = os.path.join( env.work_order_input_file, "workordergetresult_emptyparameter.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert (validate_response_code(submit_response, 2) is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.negative def test_workordergetresult_unknownparameter(self): test_id = '18879' request_file = os.path.join( env.work_order_input_file, "workordergetresult_unknownparameter.json") err_cd = \ self.test_obj.setup_and_build_request_wo_getresult( read_json(request_file)) submit_response = submit_request( self.test_obj.uri_client, self.test_obj.build_request_output['request_obj'], env.wo_submit_output_json_file_name, read_json(request_file)) logger.info("submit_response: \n%s\n", submit_response) assert (validate_response_code(submit_response, 2) is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n') @pytest.mark.workordergetresult @pytest.mark.listener @pytest.mark.negative def test_workordergetresult_workorderId_empty(self): test_id = '18729' request_file = os.path.join( env.work_order_input_file, "workordergetresult_workorderId_empty.json") msg_response = self.test_obj.post_json_msg(request_file) logger.info("**********Received Response*********\n%s\n", msg_response) assert ( check_negative_test_responses( msg_response, "Invalid work order Id") is ResultStatus.SUCCESS.value) logger.info('\t\t!!! Test completed !!!\n\n')

33.482201

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0.634351

1,163

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5.301806

0.092863

0.079468

0.053519

0.055465

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0

0.007075

0.275952

10,346

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false

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0

null

0

1

0

1

0

null

0

7

47b4a5878e1e64f755a3eee761157c514aaf5678

106

py

Python

couch/models/__init__.py

yssk22/gaecouch

1fc372ca6393c14904a318b04617457d0b5257c2

[ "Apache-2.0" ]

4

2015-03-31T05:48:29.000Z

2018-07-24T01:40:00.000Z

couch/models/__init__.py

yssk22/gaecouch

1fc372ca6393c14904a318b04617457d0b5257c2

[ "Apache-2.0" ]

null

couch/models/__init__.py

yssk22/gaecouch

1fc372ca6393c14904a318b04617457d0b5257c2

[ "Apache-2.0" ]

null

from couch.models.database import * from couch.models.document import * from couch.models.util import *

17.666667

35

0.783019

15

106

5.533333

0.466667

0.325301

0.542169

0.506024

0

0.132075

106

5

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21.2

0.902174

0

1

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true

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1

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1

0

null

0

1

0

1

0

1

0

8

47ccadbf071419b8db62bb5369214a6ee325f7c4

178

py

Python

org_desy_grid_virt_sort_release.py

osynge/grid_version_sort

c8e5d1af8f67034b58d2ec419727ea2aebe13b31

[ "MIT" ]

null

org_desy_grid_virt_sort_release.py

osynge/grid_version_sort

c8e5d1af8f67034b58d2ec419727ea2aebe13b31

[ "MIT" ]

null

org_desy_grid_virt_sort_release.py

osynge/grid_version_sort

c8e5d1af8f67034b58d2ec419727ea2aebe13b31

[ "MIT" ]

null

#!/usr/bin/env python import grid_virt_sort_release.org_desy_grid_virt_sort_release if __name__ == "__main__": grid_virt_sort_release.org_desy_grid_virt_sort_release.main()

29.666667

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178

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0.256

0.384

0.608

0.72

0

0.078652

178

5

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true

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0

null

0

1

0

1

0

12

9a1bf26d6a49f1a0c338b02c9d8f26c8d5d66f8e

3,686

py

Python

tests/test_em_structures.py

stufisher/ispyb-api

c8e488274d565abd8387a485a3b5b80e1b2cedc9

[ "Apache-2.0" ]

3

2019-07-17T22:09:40.000Z

2021-12-08T23:42:26.000Z

tests/test_em_structures.py

stufisher/ispyb-api

c8e488274d565abd8387a485a3b5b80e1b2cedc9

[ "Apache-2.0" ]

137

2017-10-09T09:30:23.000Z

2022-03-31T11:31:12.000Z

tests/test_em_structures.py

stufisher/ispyb-api

c8e488274d565abd8387a485a3b5b80e1b2cedc9

[ "Apache-2.0" ]

9

2016-10-06T14:58:06.000Z

2021-02-18T06:38:37.000Z

def test_insert_movie(testdb): emacquisition = testdb.em_acquisition group_params = emacquisition.get_data_collection_group_params() group_params["parentid"] = 55168 group_id = emacquisition.insert_data_collection_group(list(group_params.values())) collection_params = emacquisition.get_data_collection_params() collection_params["parentid"] = group_id dc_id = emacquisition.insert_data_collection(list(collection_params.values())) params = emacquisition.get_movie_params() params["dataCollectionId"] = dc_id params["movieNumber"] = 1 params["positionX"] = 4.05 params["positionY"] = 8.01 movie_id = emacquisition.insert_movie(list(params.values())) assert movie_id is not None assert movie_id > 0 def test_insert_motion_correction(testdb): emacquisition = testdb.em_acquisition group_params = emacquisition.get_data_collection_group_params() group_params["parentid"] = 55168 group_id = emacquisition.insert_data_collection_group(list(group_params.values())) collection_params = emacquisition.get_data_collection_params() collection_params["parentid"] = group_id dc_id = emacquisition.insert_data_collection(list(collection_params.values())) params = emacquisition.get_movie_params() params["dataCollectionId"] = dc_id params["movieNumber"] = 1 params["positionX"] = 4.05 params["positionY"] = 8.01 movie_id = emacquisition.insert_movie(list(params.values())) motion_cor_id = emacquisition.insert_motion_correction( movie_id=movie_id, dose_per_frame=20 ) assert motion_cor_id def test_insert_ctf(testdb): emacquisition = testdb.em_acquisition group_params = emacquisition.get_data_collection_group_params() group_params["parentid"] = 55168 group_id = emacquisition.insert_data_collection_group(list(group_params.values())) collection_params = emacquisition.get_data_collection_params() collection_params["parentid"] = group_id dc_id = emacquisition.insert_data_collection(list(collection_params.values())) params = emacquisition.get_movie_params() params["dataCollectionId"] = dc_id params["movieNumber"] = 1 params["positionX"] = 4.05 params["positionY"] = 8.01 movie_id = emacquisition.insert_movie(list(params.values())) motion_cor_id = emacquisition.insert_motion_correction( movie_id=movie_id, dose_per_frame=20 ) ctf_id = emacquisition.insert_ctf(motion_correction_id=motion_cor_id) assert ctf_id def test_insert_drift(testdb): emacquisition = testdb.em_acquisition group_params = emacquisition.get_data_collection_group_params() group_params["parentid"] = 55168 group_id = emacquisition.insert_data_collection_group(list(group_params.values())) collection_params = emacquisition.get_data_collection_params() collection_params["parentid"] = group_id dc_id = emacquisition.insert_data_collection(list(collection_params.values())) params = emacquisition.get_movie_params() params["dataCollectionId"] = dc_id params["movieNumber"] = 1 params["positionX"] = 4.05 params["positionY"] = 8.01 movie_id = emacquisition.insert_movie(list(params.values())) motion_cor_id = emacquisition.insert_motion_correction( movie_id=movie_id, dose_per_frame=20 ) drift_params = emacquisition.get_motion_correction_drift_params() drift_params["motionCorrectionId"] = motion_cor_id drift_params["frameNumber"] = 12 drift_params["deltaX"] = 5 drift_params["deltaY"] = 6 drift_id = emacquisition.insert_motion_correction_drift(list(drift_params.values())) assert drift_id is not None

38.8

88

0.754205

445

3,686

5.867416

0.110112

0.097664

0.136729

0.079663

0.843738

0.829567

0

0.018766

0.147043

3,686

94

89

39.212766

0.811705

0

0.753247

0

0.07732

0

0.064935

1

0.051948

false

0

0.051948

0

null

0

1

0

1

0

null

0

7

d006631d58a86f980e920ecaae570ec2e2a76c77

18,278

py

Python

trackme/bin/trackme_rest_handler_maintenance.py

dritanbitincka/trackme

5b2e1eb6b8d46619d2ba053d985647410253e656

[ "Apache-2.0" ]

1

2021-06-06T11:51:36.000Z

trackme/bin/trackme_rest_handler_maintenance.py

duanshuaimin/trackme

78d0ec64e3ae2e40878b282ba2f375f978a28d73

[ "Apache-2.0" ]

null

trackme/bin/trackme_rest_handler_maintenance.py

duanshuaimin/trackme

78d0ec64e3ae2e40878b282ba2f375f978a28d73

[ "Apache-2.0" ]

null

import logging import os, sys import splunk import splunk.entity import splunk.Intersplunk import json logger = logging.getLogger(__name__) splunkhome = os.environ['SPLUNK_HOME'] sys.path.append(os.path.join(splunkhome, 'etc', 'apps', 'trackme', 'lib')) import rest_handler import splunklib.client as client class TrackMeHandlerMaintenance_v1(rest_handler.RESTHandler): def __init__(self, command_line, command_arg): super(TrackMeHandlerMaintenance_v1, self).__init__(command_line, command_arg, logger) # Get the entire data sources collection as a Python array def get_maintenance_status(self, request_info, **kwargs): describe = False # Retrieve from data try: resp_dict = json.loads(str(request_info.raw_args['payload'])) except Exception as e: resp_dict = None if resp_dict is not None: try: describe = resp_dict['describe'] if describe in ("true", "True"): describe = True except Exception as e: describe = False else: # body is not required in this endpoint, if not submitted do not describe the usage describe = False if describe: response = "{\"describe\": \"This endpoint retrieves the current maintenance mode collection returned as a JSON array, it requires a GET call with no data required\"}"\ return { "payload": json.dumps(json.loads(str(response)), indent=1), 'status': 200 # HTTP status code } # Get splunkd port entity = splunk.entity.getEntity('/server', 'settings', namespace='trackme', sessionKey=request_info.session_key, owner='-') splunkd_port = entity['mgmtHostPort'] try: collection_name = "kv_trackme_maintenance_mode" service = client.connect( owner="nobody", app="trackme", port=splunkd_port, token=request_info.session_key ) collection = service.kvstore[collection_name] # Render return { "payload": json.dumps(collection.data.query(), indent=1), 'status': 200 # HTTP status code } except Exception as e: return { 'payload': 'Warn: exception encountered: ' + str(e) # Payload of the request. } # Enable the maintenance mode def post_maintenance_enable(self, request_info, **kwargs): # Declare maintenance_mode_start = None maintenance_mode_end = None maintenance_duration = None maintenance_mode = "enabled" update_comment = "API update" import time describe = False # Retrieve from data try: resp_dict = json.loads(str(request_info.raw_args['payload'])) except Exception as e: resp_dict = None if resp_dict is not None: try: describe = resp_dict['describe'] if describe in ("true", "True"): describe = True except Exception as e: describe = False if not describe: try: resp_dict = json.loads(str(request_info.raw_args['payload'])) except Exception as e: resp_dict = [] # Get start and end maintenance, both are optionals # maintenance_mode_start try: maintenance_mode_start = int(resp_dict['maintenance_mode_start']) except Exception as e: maintenance_mode_start = 0 # maintenance_mode_end try: maintenance_mode_end = int(resp_dict['maintenance_mode_end']) except Exception as e: maintenance_mode_end = 0 # maintenance_duration try: maintenance_duration = int(resp_dict['maintenance_duration']) except Exception as e: maintenance_duration = 0 # Update comment is optional and used for audit changes try: update_comment = resp_dict['update_comment'] except Exception as e: update_comment = "API update" else: # body is not required in this endpoint describe = False if describe: response = "{\"describe\": \"This endpoint enables the maintenance mode, it requires a POST call with the following information:\""\ + ", \"options\" : [ { "\ + "\"maintenance_duration\": \"(integer) OPTIONAL: the duration of the maintenance window in seconds, if unspecified and maintenance_mode_end is not specified either, defaults to now plus 24 hours\", "\ + "\"maintenance_mode_end\": \"(integer) OPTIONAL: the date time in epochtime format for the end of the maintenance window, it is overriden by maintenance_duration if specified, defaults to now plus 24 hours if not specified and maintenance_duration is not specified\", "\ + "\"maintenance_mode_start\": \"(integer) OPTIONAL: the date time in epochtime format for the start of the maintennce window, defaults to now if not specified\", "\ + "\"update_comment\": \"OPTIONAL: a comment for the update, comments are added to the audit record, if unset will be defined to: API update\""\ + " } ] }" return { "payload": json.dumps(json.loads(str(response)), indent=1), 'status': 200 # HTTP status code } # Calculates start and end time_updated = round(time.time()) # if maintenance start is not specified, starts at now if (maintenance_mode_start is None) or (maintenance_mode_start <= 0): maintenance_mode_start = str(round(time_updated)) # if maintenance end is not specified, and maintenance duration is not specified either, defaults to now + 24 hours if (maintenance_mode_end is None) or (maintenance_mode_end <= 0): maintenance_mode_end = str(round(time.time() + 86400)) # if maintenance duration is specified, it overrides the maintenance end whenever it is specified or not if (maintenance_duration is not None) and (maintenance_duration > 0): maintenance_mode_end = str(round(time.time() + maintenance_duration)) # Get splunkd port entity = splunk.entity.getEntity('/server', 'settings', namespace='trackme', sessionKey=request_info.session_key, owner='-') splunkd_port = entity['mgmtHostPort'] try: collection_name = "kv_trackme_maintenance_mode" service = client.connect( owner="nobody", app="trackme", port=splunkd_port, token=request_info.session_key ) collection = service.kvstore[collection_name] # Audit collection collection_name_audit = "kv_trackme_audit_changes" service_audit = client.connect( owner="nobody", app="trackme", port=splunkd_port, token=request_info.session_key ) collection_audit = service_audit.kvstore[collection_name_audit] # Get the current record # Notes: the record is returned as an array, as we search for a specific record, we expect one record only try: record = collection.data.query() key = record[0].get('_key') except Exception as e: key = None # Render result if key is not None and len(key)>2: # Update the record collection.data.update(str(key), json.dumps({"maintenance_mode": str(maintenance_mode), "time_updated": str(time_updated), "maintenance_mode_start": str(maintenance_mode_start), "maintenance_mode_end": str(maintenance_mode_end)})) # Record an audit change current_time = int(round(time.time() * 1000)) user = request_info.user try: # Insert the record collection_audit.data.insert(json.dumps({ "time": str(current_time), "user": str(user), "action": "success", "change_type": "enable maintenance mode", "object": "all", "object_category": "all", "object_attrs": str(json.dumps(collection.data.query_by_id(key), indent=1)), "result": "N/A", "comment": str(update_comment) })) except Exception as e: return { 'payload': 'Warn: exception encountered: ' + str(e) # Payload of the request. } return { "payload": json.dumps(collection.data.query(), indent=1), 'status': 200 # HTTP status code } else: # Insert the record collection.data.insert(json.dumps({"maintenance_mode": str(maintenance_mode), "time_updated": str(time_updated), "maintenance_mode_start": str(maintenance_mode_start), "maintenance_mode_end": str(maintenance_mode_end)})) # Record an audit change current_time = int(round(time.time() * 1000)) user = request_info.user try: # Insert the record collection_audit.data.insert(json.dumps({ "time": str(current_time), "user": str(user), "action": "success", "change_type": "enable maintenance mode", "object": "all", "object_category": "all", "object_attrs": json.dumps({"maintenance_mode": str(maintenance_mode), "time_updated": str(time_updated), "maintenance_mode_start": str(maintenance_mode_start), "maintenance_mode_end": str(maintenance_mode_end)}, index=1), "result": "N/A", "comment": str(update_comment) })) except Exception as e: return { 'payload': 'Warn: exception encountered: ' + str(e) # Payload of the request. } # Render return { "payload": json.dumps(collection.data.query(), indent=1), 'status': 200 # HTTP status code } except Exception as e: return { 'payload': 'Warn: exception encountered: ' + str(e) # Payload of the request. } # Disable the maintenance mode def post_maintenance_disable(self, request_info, **kwargs): import time # Declare maintenance_mode_start = "N/A" maintenance_mode_end = "N/A" maintenance_mode = "disabled" update_comment = "API update" describe = False # Retrieve from data try: resp_dict = json.loads(str(request_info.raw_args['payload'])) except Exception as e: resp_dict = None if resp_dict is not None: try: describe = resp_dict['describe'] if describe in ("true", "True"): describe = True except Exception as e: describe = False if not describe: try: resp_dict = json.loads(str(request_info.raw_args['payload'])) except Exception as e: resp_dict = [] # Update comment is optional and used for audit changes try: update_comment = resp_dict['update_comment'] except Exception as e: update_comment = "API update" else: # body is not required in this endpoint describe = False if describe: response = "{\"describe\": \"This endpoint disables the maintenance mode, it requires a POST call with the following information:\""\ + ", \"options\" : [ { "\ + "\"update_comment\": \"OPTIONAL: a comment for the update, comments are added to the audit record, if unset will be defined to: API update\""\ + " } ] }" return { "payload": json.dumps(json.loads(str(response)), indent=1), 'status': 200 # HTTP status code } # Get splunkd port entity = splunk.entity.getEntity('/server', 'settings', namespace='trackme', sessionKey=request_info.session_key, owner='-') splunkd_port = entity['mgmtHostPort'] try: collection_name = "kv_trackme_maintenance_mode" service = client.connect( owner="nobody", app="trackme", port=splunkd_port, token=request_info.session_key ) collection = service.kvstore[collection_name] # Audit collection collection_name_audit = "kv_trackme_audit_changes" service_audit = client.connect( owner="nobody", app="trackme", port=splunkd_port, token=request_info.session_key ) collection_audit = service_audit.kvstore[collection_name_audit] # Get the current record # Notes: the record is returned as an array, as we search for a specific record, we expect one record only try: record = collection.data.query() key = record[0].get('_key') except Exception as e: key = None # An ack record exists already in the collection, perform an update time_updated = round(time.time()) # Render result if key is not None and len(key)>2: # Update the record collection.data.update(str(key), json.dumps({"maintenance_mode": str(maintenance_mode), "time_updated": str(time_updated), "maintenance_mode_start": str(maintenance_mode_start), "maintenance_mode_end": str(maintenance_mode_end)})) # Record an audit change current_time = int(round(time.time() * 1000)) user = request_info.user try: # Insert the record collection_audit.data.insert(json.dumps({ "time": str(current_time), "user": str(user), "action": "success", "change_type": "disable maintenance mode", "object": "all", "object_category": "all", "object_attrs": str(json.dumps(collection.data.query_by_id(key), indent=1)), "result": "N/A", "comment": str(update_comment) })) except Exception as e: return { 'payload': 'Warn: exception encountered: ' + str(e) # Payload of the request. } return { "payload": json.dumps(collection.data.query(), indent=1), 'status': 200 # HTTP status code } else: # Insert the record collection.data.insert(json.dumps({"maintenance_mode": str(maintenance_mode), "time_updated": str(time_updated), "maintenance_mode_start": str(maintenance_mode_start), "maintenance_mode_end": str(maintenance_mode_end)})) # Record an audit change current_time = int(round(time.time() * 1000)) user = request_info.user try: # Insert the record collection_audit.data.insert(json.dumps({ "time": str(current_time), "user": str(user), "action": "success", "change_type": "disable maintenance mode", "object": "all", "object_category": "all", "object_attrs": json.dumps({"maintenance_mode": str(maintenance_mode), "time_updated": str(time_updated), "maintenance_mode_start": str(maintenance_mode_start), "maintenance_mode_end": str(maintenance_mode_end)}, index=1), "result": "N/A", "comment": str(update_comment) })) except Exception as e: return { 'payload': 'Warn: exception encountered: ' + str(e) # Payload of the request. } # Render return { "payload": json.dumps(collection.data.query(), indent=1), 'status': 200 # HTTP status code } except Exception as e: return { 'payload': 'Warn: exception encountered: ' + str(e) # Payload of the request. }

39.223176

288

0.519477

1,771

18,278

5.191982

0.119706

0.117455

0.046982

0.043067

0.808265

0.788907

0.763893

0.758238

0.730832

0

0.006766

0.393533

18,278

465

289

39.307527

0.822733

0.101652

0

0.806854

0

0.113781

0.017303

0

1

0.012461

false

0

0.031153

0

0.093458

0

null

0

1

0

1

0

null

0

7

d01e89135388afabff283ba2f34fd6515ada9eac

36,187

py

Python

tests/job/previous_api.py

alan-turing-institute/gateway-middleware-old

f09f6099f33f66ec95c4b24c0ae41eebfb68875c

[ "MIT" ]

3

2017-08-03T07:40:08.000Z

2019-07-29T11:39:52.000Z

tests/job/previous_api.py

alan-turing-institute/gateway-middleware-old

f09f6099f33f66ec95c4b24c0ae41eebfb68875c

[ "MIT" ]

58

2017-06-22T15:02:53.000Z

2018-01-08T16:06:01.000Z

tests/job/previous_api.py

alan-turing-institute/gateway-middleware-old

f09f6099f33f66ec95c4b24c0ae41eebfb68875c

[ "MIT" ]

null

import json import pytest import unittest import unittest.mock as mock from werkzeug.exceptions import NotFound from middleware.job.api import JobApi from middleware.job.inmemory_repository import JobRepositoryMemory from middleware.factory import create_app CONFIG_NAME = "test" @pytest.fixture def test_client(job_repository=JobRepositoryMemory()): app = create_app(CONFIG_NAME, job_repository) return app.test_client() def response_to_json(response): data = response.get_data(as_text=True) if not data: return None return json.loads(data) class TestJobApi(unittest.TestCase): def test_abort_if_not_found_throws_notfound_exception(self): jobs = JobRepositoryMemory() api = JobApi(job_repository=jobs) job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" with pytest.raises(NotFound): api.abort_if_not_found(job_id) # === GET tests (READ) === def test_get_for_existing_job_returns_job_with_200_status(self): jobs = JobRepositoryMemory() # Create job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job) client = test_client(jobs) job_response = client.get("/api/job/{}".format(job_id)) assert job_response.status_code == 200 assert response_to_json(job_response) == job def test_get_for_nonexistent_job_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job_response = client.get("/api/job/{}".format(job_id)) error_message = {"message": "Job {} not found".format(job_id)} assert job_response.status_code == 404 assert response_to_json(job_response) == error_message def test_get_with_no_job_id_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_response = client.get("/api/job/") assert job_response.status_code == 404 # No content check as we are expecting the standard 404 error message # TODO: Get the 404 response defined for the app and compare it here # === PUT tests (UPDATE) === def test_put_with_no_job_id_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_response = client.put("/api/job/") assert job_response.status_code == 404 # No content check as we are expecting the standard 404 error message # TODO: Get the 404 response defined for the app and compare it here assert len(jobs._jobs) == 0 def test_put_with_empty_body_returns_error_with_400_status(self): jobs = JobRepositoryMemory() job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job) job = None client = test_client(jobs) job_response = client.put("/api/job/{}".format(job_id), data=json.dumps(job), content_type='application/json') error_message = {"message": "Message body could not be parsed as JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message def test_put_with_nonjson_body_returns_error_with_400_status(self): jobs = JobRepositoryMemory() job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job) invalid_json = "{key-with-no-value}" client = test_client(jobs) # We don't add content_type='application/json' because, if we do the # framework catches invalid JSON before it gets to our response handler job_response = client.put("/api/job/{}".format(job_id), data=invalid_json) error_message = {"message": "Message body could not be parsed as JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message def test_put_with_mismatched_job_id_returns_error_with_409_status(self): jobs = JobRepositoryMemory() # Create job job_id_url = "d769843b-6f37-4939-96c7-c382c3e74b46" job_existing = {"id": job_id_url, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job_existing) job_id_json = "59540b31-0454-4875-a00f-94eb4d81a09c" job_new = {"id": job_id_json, "parameters": {"blue": "high", "green": "low"}} client = test_client(jobs) job_response = client.put("/api/job/{}".format(job_id_url), data=json.dumps(job_new), content_type='application/json') error_message = {"message": "Job ID in URL ({}) does not match job " "ID in message JSON ({}).".format(job_id_url, job_id_json)} assert job_response.status_code == 409 assert response_to_json(job_response) == error_message assert jobs.get_by_id(job_id_url) == job_existing assert jobs.get_by_id(job_id_json) is None def test_put_with_nonexistent_job_id_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job_response = client.put("/api/job/{}".format(job_id)) error_message = {"message": "Job {} not found".format(job_id)} assert job_response.status_code == 404 assert response_to_json(job_response) == error_message def test_put_with_existing_job_id_returns_new_job_with_200_status(self): jobs = JobRepositoryMemory() # Create job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job_original = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job_original) job_new = {"id": job_id, "parameters": {"blue": "high", "green": "low"}} client = test_client(jobs) job_response = client.put("/api/job/{}".format(job_id), data=json.dumps(job_new), content_type='application/json') assert job_response.status_code == 200 assert response_to_json(job_response) == job_new assert jobs.get_by_id(job_id) == job_new def test_put_with_invalid_job_json_returns_error_with_400_status(self): jobs = JobRepositoryMemory() # Create job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job) client = test_client(jobs) invalid_job = {"no-id-field": "valid-json"} job_response = client.put("/api/job/{}".format(job_id), data=json.dumps(invalid_job), content_type='application/json') error_message = {"message": "Message body is not valid Job JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message # === DELETE tests (DELETE) === def test_delete_with_no_job_id_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_response = client.delete("/api/job/") assert job_response.status_code == 404 # No content check as we are expecting the standard 404 error message # TODO: Get the 404 response defined for the app and compare it here def test_delete_with_nonexistent_job_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job_response = client.delete("/api/job/{}".format(job_id)) error_message = {"message": "Job {} not found".format(job_id)} assert job_response.status_code == 404 assert response_to_json(job_response) == error_message def test_delete_with_existing_job_id_returns_new_job_with_204_status(self): jobs = JobRepositoryMemory() # Create job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job) client = test_client(jobs) job_response = client.delete("/api/job/{}".format(job_id)) assert job_response.status_code == 204 assert response_to_json(job_response) is None assert jobs.get_by_id(job_id) is None # === POST tests === def test_post_with_valid_json_correct_id_returns_new_job_success_200(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/job/{}".format(job_id), data=json.dumps(job), content_type='application/json') assert response_to_json(job_response) == job assert job_response.status_code == 200 def test_post_with_valid_json_and_incorrect_id_returns_error_404(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') job = {"id": job_id[::-1], "parameters": {"height": 3}} job_response = client.post("/api/job/{}".format(job_id), data=json.dumps(job), content_type='application/json') error_message = {"message": "Job {} not found".format(job_id[::-1])} assert response_to_json(job_response) == error_message assert job_response.status_code == 404 def test_post_with_missing_json_returns_error_400(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/job/{}".format(job_id), data=None, content_type=None) error_message = {"message": "Message body could not be parsed as JSON"} assert response_to_json(job_response) == error_message assert job_response.status_code == 400 def test_post_with_invalid_json_returns_error_400(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') broken_json = {'test': 5} job_response = client.post("/api/job/{}".format(job_id), data=json.dumps(broken_json), content_type='application/json') error_message = {"message": "Message body is not valid Job JSON"} assert response_to_json(job_response) == error_message assert job_response.status_code == 400 # === PATCH tests (Partial UPDATE) === def test_patch_with_no_job_id_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_response = client.patch("/api/job/") assert job_response.status_code == 404 # No content check as we are expecting the standard 404 error message # TODO: Get the 404 response defined for the app and compare it here assert len(jobs._jobs) == 0 def test_patch_with_empty_body_returns_error_with_400_status(self): jobs = JobRepositoryMemory() job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job) job = None client = test_client(jobs) job_response = client.patch("/api/job/{}".format(job_id), data=json.dumps(job), content_type='application/json-patch+json') error_message = {"message": "Message body could not be parsed as JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message def test_patch_with_nonjson_body_returns_error_with_400_status(self): jobs = JobRepositoryMemory() job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job) invalid_json = "{key-with-no-value}" client = test_client(jobs) # We don't add content_type='application/json' because, if we do the # framework catches invalid JSON before it gets to our response handler job_response = client.patch("/api/job/{}".format(job_id), data=invalid_json) error_message = {"message": "Message body could not be parsed as JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message def test_patch_with_nonexistent_job_id_returns_error_with_404_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job_response = client.patch("/api/job/{}".format(job_id)) error_message = {"message": "Job {} not found".format(job_id)} assert job_response.status_code == 404 assert response_to_json(job_response) == error_message def test_patch_with_mismatched_job_id_returns_error_with_409_status(self): jobs = JobRepositoryMemory() # Create job job_id_url = "d769843b-6f37-4939-96c7-c382c3e74b46" job_existing = {"id": job_id_url, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job_existing) job_id_json = "59540b31-0454-4875-a00f-94eb4d81a09c" job_new = {"id": job_id_json, "parameters": {"height": 7, "green": "low", "depth": None}} client = test_client(jobs) job_response = client.patch( "/api/job/{}".format(job_id_url), data=json.dumps(job_new), content_type='application/merge-patch+json') error_message = {"message": "Job ID in URL ({}) does not match job " "ID in message JSON ({}).".format(job_id_url, job_id_json)} assert job_response.status_code == 409 assert response_to_json(job_response) == error_message assert jobs.get_by_id(job_id_url) == job_existing assert jobs.get_by_id(job_id_json) is None def test_patch_with_existing_job_id_returns_new_job_with_200_status(self): jobs = JobRepositoryMemory() # Create job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job_original = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job_original) job_patch = {"parameters": {"height": 7, "green": "low", "depth": None}} job_new_expected = {"id": job_id, "parameters": {"height": 7, "width": 4, "green": "low"}} client = test_client(jobs) job_response = client.patch( "/api/job/{}".format(job_id), data=json.dumps(job_patch), content_type='application/merge-patch+json') assert job_response.status_code == 200 assert response_to_json(job_response) == job_new_expected assert jobs.get_by_id(job_id) == job_new_expected class TestRunApi(object): @mock.patch('middleware.job_information_manager.job_information_manager.' '_run_remote_script', side_effect=mock_run_remote) @mock.patch('middleware.job_information_manager.job_information_manager.' 'patch_all_templates', side_effect=mock_patch_all) @mock.patch('middleware.job_information_manager.job_information_manager.' 'transfer_all_files', side_effect=mock_transfer_all) def test_run_with_valid_id(self, mock_transfer, mock_patch, mock_run): jobs = JobRepositoryMemory() client = test_client(jobs) # Create full job job = { "id": "d769843b-6f37-4939-96c7-c382c3e74b46", "templates": [ { "source_uri": "./resources/templates/Blue.nml", "destination_path": "project/case/" } ], "scripts": [ {"source_uri": "./resources/scripts/start_job.sh", "destination_path": "project/case/", "action": "RUN"}, {"source_uri": "./resources/scripts/cancel_job.sh", "destination_path": "project/case/", "action": "CANCEL"}, {"source_uri": "./resources/scripts/progress_job.sh", "destination_path": "project/case/", "action": "PROGRESS"}, {"source_uri": "./resources/scripts/setup_job.sh", "destination_path": "project/case/", "action": "SETUP"} ], "parameters": { "viscosity_properties": { "viscosity_phase_1": "42.0" } }, "inputs": [] } job_id = job['id'] client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/run/{}".format(job_id), data=json.dumps(job), content_type='application/json') assert response_to_json(job_response)['stdout'] == 'start_job.sh' assert job_response.status_code == 200 def test_run_with_invalid_id(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') bad_id = "2s3" job_response = client.post("/api/run/{}".format(bad_id), data=json.dumps(job), content_type='application/json') err_message = {'message': ('Job {0} not found. You have requested ' 'this URI [/api/run/{0}] but did' ' you mean /api/run/<string:job_id> ' '?').format(bad_id)} assert response_to_json(job_response) == err_message assert job_response.status_code == 404 def test_run_with_no_json(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/run/{}".format(job_id)) err_message = {'message': ('Message body could not be parsed as JSON')} assert response_to_json(job_response) == err_message assert job_response.status_code == 400 def test_run_with_invalid_json(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') broken_json = {'test': 5} job_response = client.post("/api/run/{}".format(job_id), data=json.dumps(broken_json), content_type='application/json') err_message = {'message': ('Message body is not valid Job JSON')} assert response_to_json(job_response) == err_message assert job_response.status_code == 400 class TestSetupApi(object): @mock.patch('middleware.job_information_manager.job_information_manager.' '_run_remote_script', side_effect=mock_run_remote) @mock.patch('middleware.job_information_manager.job_information_manager.' 'patch_all_templates', side_effect=mock_patch_all) @mock.patch('middleware.job_information_manager.job_information_manager.' 'transfer_all_files', side_effect=mock_transfer_all) def test_setup_with_valid_id(self, mock_transfer, mock_patch, mock_run): jobs = JobRepositoryMemory() client = test_client(jobs) # Create full job job = { "id": "d769843b-6f37-4939-96c7-c382c3e74b46", "templates": [ { "source_uri": "./resources/templates/Blue.nml", "destination_path": "project/case/" } ], "scripts": [ {"source_uri": "./resources/scripts/start_job.sh", "destination_path": "project/case/", "action": "RUN"}, {"source_uri": "./resources/scripts/cancel_job.sh", "destination_path": "project/case/", "action": "CANCEL"}, {"source_uri": "./resources/scripts/progress_job.sh", "destination_path": "project/case/", "action": "PROGRESS"}, {"source_uri": "./resources/scripts/setup_job.sh", "destination_path": "project/case/", "action": "SETUP"} ], "parameters": { "viscosity_properties": { "viscosity_phase_1": "42.0" } }, "inputs": [] } job_id = job['id'] client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/setup/{}".format(job_id), data=json.dumps(job), content_type='application/json') assert response_to_json(job_response)['stdout'] == 'setup_job.sh' assert job_response.status_code == 200 def test_setup_with_invalid_id(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') bad_id = "2s3" job_response = client.post("/api/setup/{}".format(bad_id), data=json.dumps(job), content_type='application/json') err_message = {'message': ('Job {0} not found. You have requested ' 'this URI [/api/setup/{0}] but did ' 'you mean /api/setup/<string:job_id> or ' '/api/run/<string:job_id> ' '?').format(bad_id)} assert response_to_json(job_response) == err_message assert job_response.status_code == 404 def test_setup_with_no_json(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/setup/{}".format(job_id)) err_message = {'message': ('Message body could not be parsed as JSON')} assert response_to_json(job_response) == err_message assert job_response.status_code == 400 def test_setup_with_invalid_json(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') broken_json = {'test': 5} job_response = client.post("/api/setup/{}".format(job_id), data=json.dumps(broken_json), content_type='application/json') err_message = {'message': ('Message body is not valid Job JSON')} assert response_to_json(job_response) == err_message assert job_response.status_code == 400 class TestCancelApi(object): @mock.patch('middleware.job_information_manager.job_information_manager.' '_run_remote_script', side_effect=mock_run_remote) def test_cancel_with_valid_id(self, mock_run): jobs = JobRepositoryMemory() client = test_client(jobs) # Create full job job = { "id": "d769843b-6f37-4939-96c7-c382c3e74b46", "templates": [ { "source_uri": "./resources/templates/Blue.nml", "destination_path": "project/case/" } ], "scripts": [ {"source_uri": "./resources/scripts/start_job.sh", "destination_path": "project/case/", "action": "RUN"}, {"source_uri": "./resources/scripts/cancel_job.sh", "destination_path": "project/case/", "action": "CANCEL"}, {"source_uri": "./resources/scripts/progress_job.sh", "destination_path": "project/case/", "action": "PROGRESS"}, {"source_uri": "./resources/scripts/setup_job.sh", "destination_path": "project/case/", "action": "SETUP"} ], "parameters": { "viscosity_properties": { "viscosity_phase_1": "42.0" } }, "inputs": [] } job_id = job['id'] client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/cancel/{}".format(job_id), data=json.dumps(job), content_type='application/json') assert response_to_json(job_response)['stdout'] == 'cancel_job.sh' assert job_response.status_code == 200 def test_cancel_with_invalid_id(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') bad_id = "2s3" job_response = client.post("/api/cancel/{}".format(bad_id), data=json.dumps(job), content_type='application/json') err_message = {'message': ('Job {0} not found. You have requested ' 'this URI [/api/cancel/{0}] but did ' 'you mean /api/cancel/<string:job_id> ' '?').format(bad_id)} assert response_to_json(job_response) == err_message assert job_response.status_code == 404 class TestProgressApi(object): @mock.patch('middleware.job_information_manager.job_information_manager.' '_run_remote_script', side_effect=mock_run_remote) def test_progress_with_valid_id(self, mock_run): jobs = JobRepositoryMemory() client = test_client(jobs) # Create full job job = { "id": "d769843b-6f37-4939-96c7-c382c3e74b46", "templates": [ { "source_uri": "./resources/templates/Blue.nml", "destination_path": "project/case/" } ], "scripts": [ {"source_uri": "./resources/scripts/start_job.sh", "destination_path": "project/case/", "action": "RUN"}, {"source_uri": "./resources/scripts/cancel_job.sh", "destination_path": "project/case/", "action": "CANCEL"}, {"source_uri": "./resources/scripts/progress_job.sh", "destination_path": "project/case/", "action": "PROGRESS"}, {"source_uri": "./resources/scripts/setup_job.sh", "destination_path": "project/case/", "action": "SETUP"} ], "parameters": { "viscosity_properties": { "viscosity_phase_1": "42.0" } }, "inputs": [] } job_id = job['id'] client.post("/api/job", data=json.dumps(job), content_type='application/json') job_response = client.post("/api/progress/{}".format(job_id), data=json.dumps(job), content_type='application/json') assert response_to_json(job_response)['stdout'] == 'progress_job.sh' assert job_response.status_code == 200 def test_cancel_with_invalid_id(self): jobs = JobRepositoryMemory() client = test_client(jobs) # Create skeleton job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3}} client.post("/api/job", data=json.dumps(job), content_type='application/json') bad_id = "2s3" job_response = client.post("/api/progress/{}".format(bad_id), data=json.dumps(job), content_type='application/json') err_message = {'message': ('Job {0} not found. You have requested ' 'this URI [/api/progress/{0}] but did ' 'you mean /api/progress/' '<string:job_id> ?').format(bad_id)} assert response_to_json(job_response) == err_message assert job_response.status_code == 404 class TestJobsApi(object): # === GET tests (LIST) === def test_get_returns_object_summary_list(self): jobs = JobRepositoryMemory() # Create job job_id_1 = "d769843b-6f37-4939-96c7-c382c3e74b46" job_1 = {"id": job_id_1, "parameters": {"height": 11, "width": 12, "depth": 13}} job_id_2 = "53835db6-87cb-4dd8-a91f-5c98100c0b82" job_2 = {"id": job_id_2, "parameters": {"height": 21, "width": 22, "depth": 23}} job_id_3 = "781692cc-b71c-469e-a8e9-938c2fda89f2" job_3 = {"id": job_id_3, "parameters": {"height": 31, "width": 32, "depth": 33}} jobs.create(job_1) jobs.create(job_2) jobs.create(job_3) client = test_client(jobs) def job_uri(job_id): return "/api/job/{}".format(job_id) expected_response = [{"id": job_id_1, "uri": job_uri(job_id_1)}, {"id": job_id_2, "uri": job_uri(job_id_2)}, {"id": job_id_3, "uri": job_uri(job_id_3)}] job_response = client.get("/api/job") assert job_response.status_code == 200 # Both lists of dictionaries need to have same sort order to # successfully compare assert response_to_json(job_response).sort(key=lambda x: x["id"]) == \ expected_response.sort(key=lambda x: x["id"]) # === POST tests (CREATE) === def test_post_for_nonexistent_job_returns_job_with_200_status(self): jobs = JobRepositoryMemory() # Create job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} client = test_client(jobs) job_response = client.post("/api/job", data=json.dumps(job), content_type='application/json') assert job_response.status_code == 200 assert response_to_json(job_response) == job assert jobs.get_by_id(job_id) == job def test_post_for_existing_job_returns_error_with_409_status(self): jobs = JobRepositoryMemory() # Create job job_id = "d769843b-6f37-4939-96c7-c382c3e74b46" job_existing = {"id": job_id, "parameters": {"height": 3, "width": 4, "depth": 5}} jobs.create(job_existing) job_new = {"id": job_id, "parameters": {"blue": "high", "green": "low"}} client = test_client(jobs) job_response = client.post("/api/job", data=json.dumps(job_new), content_type='application/json') error_message = {"message": "Job with ID {} already " "exists".format(job_id)} assert job_response.status_code == 409 assert response_to_json(job_response) == error_message assert jobs.get_by_id(job_id) == job_existing def test_post_with_none_returns_error_with_400_status(self): jobs = JobRepositoryMemory() client = test_client(jobs) job_response = client.post("/api/job", data=json.dumps(None), content_type='application/json') error_message = {"message": "Message body could not be parsed as JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message assert len(jobs._jobs) == 0 def test_post_with_nonjson_body_returns_error_with_400_status(self): jobs = JobRepositoryMemory() invalid_json = "{key-with-no-value}" client = test_client(jobs) # We don't add content_type='application/json' because, if we do the # framework catches invalid JSON before it gets to our response handler job_response = client.post("/api/job", data=invalid_json) error_message = {"message": "Message body could not be parsed as JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message def test_post_with_invalid_job_json_returns_error_with_400_status(self): jobs = JobRepositoryMemory() invalid_job = {"no-id-field": "valid-json"} client = test_client(jobs) job_response = client.post("/api/job", data=json.dumps(invalid_job), content_type='application/json') error_message = {"message": "Message body is not valid Job JSON"} assert job_response.status_code == 400 assert response_to_json(job_response) == error_message

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d0bc6c892e56244480b67d43b8246335f0520f6e

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Python

ross/tests/test_rubbing.py

hssaabbl/ross

5e548d24c8522c8a9a294479c580c21b4eb3bb65

[ "MIT" ]

69

2018-12-26T19:21:26.000Z

2022-02-10T08:48:03.000Z

ross/tests/test_rubbing.py

hssaabbl/ross

5e548d24c8522c8a9a294479c580c21b4eb3bb65

[ "MIT" ]

639

2018-12-18T16:44:11.000Z

2022-03-27T16:46:41.000Z

ross/tests/test_rubbing.py

hssaabbl/ross

5e548d24c8522c8a9a294479c580c21b4eb3bb65

[ "MIT" ]

136

2019-01-08T12:37:32.000Z

2022-03-30T07:14:35.000Z

import os from pathlib import Path from tempfile import tempdir import numpy as np import pytest from numpy.testing import assert_allclose, assert_almost_equal import ross as rs from ross.defects.misalignment import MisalignmentFlex from ross.units import Q_ steel2 = rs.Material(name="Steel", rho=7850, E=2.17e11, Poisson=0.2992610837438423) # Rotor with 6 DoFs, with internal damping, with 10 shaft elements, 2 disks and 2 bearings. i_d = 0 o_d = 0.019 n = 33 # fmt: off L = np.array( [0 , 25, 64, 104, 124, 143, 175, 207, 239, 271, 303, 335, 345, 355, 380, 408, 436, 466, 496, 526, 556, 586, 614, 647, 657, 667, 702, 737, 772, 807, 842, 862, 881, 914] )/ 1000 # fmt: on L = [L[i] - L[i - 1] for i in range(1, len(L))] shaft_elem = [ rs.ShaftElement6DoF( material=steel2, L=l, idl=i_d, odl=o_d, idr=i_d, odr=o_d, alpha=8.0501, beta=1.0e-5, rotary_inertia=True, shear_effects=True, ) for l in L ] Id = 0.003844540885417 Ip = 0.007513248437500 disk0 = rs.DiskElement6DoF(n=12, m=2.6375, Id=Id, Ip=Ip) disk1 = rs.DiskElement6DoF(n=24, m=2.6375, Id=Id, Ip=Ip) kxx1 = 4.40e5 kyy1 = 4.6114e5 kzz = 0 cxx1 = 27.4 cyy1 = 2.505 czz = 0 kxx2 = 9.50e5 kyy2 = 1.09e8 cxx2 = 50.4 cyy2 = 100.4553 bearing0 = rs.BearingElement6DoF( n=4, kxx=kxx1, kyy=kyy1, cxx=cxx1, cyy=cyy1, kzz=kzz, czz=czz ) bearing1 = rs.BearingElement6DoF( n=31, kxx=kxx2, kyy=kyy2, cxx=cxx2, cyy=cyy2, kzz=kzz, czz=czz ) rotor = rs.Rotor(shaft_elem, [disk0, disk1], [bearing0, bearing1]) @pytest.fixture def rub(): unbalance_magnitudet = np.array([5e-4, 0]) unbalance_phaset = np.array([-np.pi / 2, 0]) rubbing = rotor.run_rubbing( dt=0.001, tI=0, tF=0.5, deltaRUB=7.95e-5, kRUB=1.1e6, cRUB=40, miRUB=0.3, posRUB=12, speed=125.66370614359172, unbalance_magnitude=unbalance_magnitudet, unbalance_phase=unbalance_phaset, print_progress=True, ) return rubbing @pytest.fixture def rub_units(): unbalance_magnitudet = Q_(np.array([0.043398083107259365, 0]), "lb*in") unbalance_phaset = Q_(np.array([-90.0, 0.0]), "degrees") rubbing = rotor.run_rubbing( dt=0.001, tI=0, tF=0.5, deltaRUB=7.95e-5, kRUB=1.1e6, cRUB=40, miRUB=0.3, posRUB=12, speed=Q_(1200, "RPM"), unbalance_magnitude=unbalance_magnitudet, unbalance_phase=unbalance_phaset, print_progress=True, ) return rubbing def test_rub_parameters(rub): assert rub.dt == 0.001 assert rub.tI == 0 assert rub.tF == 0.5 assert rub.deltaRUB == 7.95e-5 assert rub.kRUB == 1.1e6 assert rub.cRUB == 40 assert rub.miRUB == 0.3 assert rub.posRUB == 12 assert rub.speed == 125.66370614359172 def test_rub_parameters_units(rub_units): assert rub_units.dt == 0.001 assert rub_units.tI == 0 assert rub_units.tF == 0.5 assert rub_units.deltaRUB == 7.95e-5 assert rub_units.kRUB == 1.1e6 assert rub_units.cRUB == 40 assert rub_units.miRUB == 0.3 assert rub_units.posRUB == 12 assert rub_units.speed == 125.66370614359172 def test_rub_forces(rub): assert rub.forces_rub[rub.posRUB * 6, :] == pytest.approx( # fmt: off np.array([ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.34106430e+00, 2.38612745e+00, 2.49817920e+00, 1.81347173e+00, 5.98445473e-01, -1.62547004e+00, -4.23917250e+00, -6.00118806e+00, -6.20373067e+00, -4.73612273e+00, -2.73184699e+00, -2.58971885e+00, -6.09874812e+00, -1.19048343e+01, -1.62930120e+01, -1.64120039e+01, -1.22951018e+01, -6.47561269e+00, -1.92419235e+00, 3.53374623e-02, 1.47810258e-01, 6.34772882e-02, 1.83806641e-01, 4.43954908e-01, 5.92533172e-01, 5.51738633e-01, 6.18865825e-01, 1.16291085e+00, 1.99527847e+00, 2.28657481e+00, 1.21810729e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 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0.00000000e+00, 0.00000000e+00, -9.98460245e-01, -5.03924706e+00, -7.75632048e+00, -7.28589841e+00, -4.21050757e+00, -6.78335856e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 4.97669123e-01, 9.43108661e-01, 1.21217301e+00, 1.02059004e+00, 5.88846364e-01, 4.25532247e-01, 7.49102363e-01, 1.21248611e+00, 1.23719949e+00, 5.26714086e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 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0.00000000e+00, 0.00000000e+00, 0.00000000e+00]) # fmt: on ) assert rub.forces_rub[rub.posRUB * 6 + 1, :] == pytest.approx( # fmt: off np.array([ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -2.04165157e+00, -4.37810280e+00, -6.57666995e+00, -8.28694141e+00, -9.37791126e+00, -9.76081035e+00, -9.25783043e+00, -7.68973505e+00, -5.19539491e+00, -2.48084518e+00, -6.09414243e-01, -1.40464287e-01, -2.91868675e-01, 5.94864394e-01, 3.76903307e+00, 7.17867399e+00, 8.50615176e+00, 6.92755001e+00, 3.76919148e+00, 1.38886654e+00, 1.14793265e+00, 2.47476310e+00, 3.69518317e+00, 3.56151341e+00, 2.15845164e+00, 7.22745269e-01, 4.64776971e-01, 1.32361970e+00, 2.08542187e+00, 1.74043906e+00, 3.68327123e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.40526270e+00, 3.91183574e+00, 6.08879987e+00, 6.05701802e+00, 3.35127909e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.33684009e+00, 4.74117308e+00, 5.66393572e+00, 3.75144548e+00, 2.83459537e-01, -1.61445732e+00, -2.61883874e+00, -2.76818696e+00, -2.47679180e+00, -2.29014373e+00, -2.50794047e+00, -3.08754938e+00, -3.77455164e+00, -4.26560645e+00, -4.33448168e+00, -3.93383052e+00, -3.19736872e+00, -2.30738448e+00, -1.36778475e+00, -4.13019001e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -2.30731635e-01, -2.71055349e+00, -3.77777456e+00, -3.19820518e+00, -1.62052825e+00, -1.57786580e-01, 0.00000000e+00, -3.39194075e-01, -1.19486567e+00, -1.40982868e+00, -8.24731765e-01, 1.77245380e-02, 0.00000000e+00, 0.00000000e+00, 1.12393272e+00, 3.42883960e+00, 6.44392419e+00, 7.74026022e+00, 6.02300041e+00, 2.15021680e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.31206244e+00, 2.88224433e+00, 2.70442915e+00, 1.31540273e+00, 6.83579157e-02, -1.44657955e-01, -9.74069771e-04, 2.01609711e-01, 7.58795510e-02, -1.14712672e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.16918168e-01, -9.48748823e-02, -3.74701248e-01, -6.68192840e-01, -7.77720853e-01, -8.15718667e-01, -1.19404470e+00, -2.17926682e+00, -3.40215785e+00, -3.99418641e+00, -3.25449483e+00, -1.22032570e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.72304245e+00, -2.63776333e+00, -2.11110151e+00, -7.22241992e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.37988828e-01, -1.36497601e-01, 1.32278945e-01, 5.15571508e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.42548433e-01, 2.72091640e+00, 3.24542027e+00, 2.03399132e+00, 3.77699186e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.99799699e-01, 5.92260640e-02, -1.02272668e-02, -3.19939917e-01, -7.49813663e-01, -1.06945353e+00, -1.04483902e+00, -5.36963585e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -3.23192576e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.42596962e-01, -1.71901114e-01, -7.45893810e-02, 3.71940362e-01, 6.24286373e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -9.16154067e-02, -8.72890060e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.36067934e-01, 1.13854180e+00, 4.79721529e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00]) # fmt: on ) def test_rub_forces_units(rub_units): assert rub_units.forces_rub[rub_units.posRUB * 6, :] == pytest.approx( # fmt: off np.array([ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.34106430e+00, 2.38612745e+00, 2.49817920e+00, 1.81347173e+00, 5.98445473e-01, -1.62547004e+00, -4.23917250e+00, -6.00118806e+00, -6.20373067e+00, -4.73612273e+00, -2.73184699e+00, -2.58971885e+00, -6.09874812e+00, -1.19048343e+01, -1.62930120e+01, -1.64120039e+01, -1.22951018e+01, -6.47561269e+00, -1.92419235e+00, 3.53374623e-02, 1.47810258e-01, 6.34772882e-02, 1.83806641e-01, 4.43954908e-01, 5.92533172e-01, 5.51738633e-01, 6.18865825e-01, 1.16291085e+00, 1.99527847e+00, 2.28657481e+00, 1.21810729e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.55680614e-01, -1.15087399e+00, -1.31570879e+00, -5.73686616e-01, 1.75075759e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.35857558e+00, 4.63547122e+00, 8.26625410e+00, 1.07680988e+01, 1.13286366e+01, 9.96961037e+00, 7.44128958e+00, 4.81928761e+00, 2.91576005e+00, 1.93968467e+00, 1.61560462e+00, 1.51666598e+00, 1.30530274e+00, 8.25200469e-01, 1.14260074e-01, -1.19244337e+00, -2.29090277e+00, -2.84242534e+00, -2.70568998e+00, -1.71797718e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -3.62954221e-01, -2.15664186e-02, -5.82573814e-01, -1.27145991e+00, -1.38207772e+00, -8.36333007e-01, 0.00000000e+00, -1.52638197e+00, -3.88459875e+00, -5.84147533e+00, -5.55533169e+00, -2.84156510e+00, 0.00000000e+00, 0.00000000e+00, -9.98460245e-01, -5.03924706e+00, -7.75632048e+00, -7.28589841e+00, -4.21050757e+00, -6.78335856e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 4.97669123e-01, 9.43108661e-01, 1.21217301e+00, 1.02059004e+00, 5.88846364e-01, 4.25532247e-01, 7.49102363e-01, 1.21248611e+00, 1.23719949e+00, 5.26714086e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.30579340e-01, 2.26273248e+00, 2.80172735e+00, 2.36060364e+00, 1.47121281e+00, 9.05484679e-01, 1.10607178e+00, 1.80305085e+00, 2.28352354e+00, 2.03304519e+00, 1.10298146e+00, 3.77694650e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -3.22380450e+00, -5.68021237e+00, -5.83462167e+00, -3.25195544e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -9.90196556e-01, -2.90885128e+00, -2.81169132e+00, -8.81117993e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.69024403e-01, 3.11412852e-01, 5.58798236e-01, 6.40371175e-01, 3.49164726e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.36971006e-01, 1.21346945e+00, 2.18249083e+00, 2.84208082e+00, 2.99156571e+00, 2.55421246e+00, 1.59111859e+00, 3.14246711e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -9.16343507e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.16296507e+00, -3.23286551e+00, -4.51354090e+00, -3.98257895e+00, -1.81166144e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.12219345e-01, 2.21171647e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -9.56292801e-01, -1.33271793e+00, -1.03821500e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00]) # fmt: on ) assert rub_units.forces_rub[rub_units.posRUB * 6 + 1, :] == pytest.approx( # fmt: off np.array([ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -2.04165157e+00, -4.37810280e+00, -6.57666995e+00, -8.28694141e+00, -9.37791126e+00, -9.76081035e+00, -9.25783043e+00, -7.68973505e+00, -5.19539491e+00, -2.48084518e+00, -6.09414243e-01, -1.40464287e-01, -2.91868675e-01, 5.94864394e-01, 3.76903307e+00, 7.17867399e+00, 8.50615176e+00, 6.92755001e+00, 3.76919148e+00, 1.38886654e+00, 1.14793265e+00, 2.47476310e+00, 3.69518317e+00, 3.56151341e+00, 2.15845164e+00, 7.22745269e-01, 4.64776971e-01, 1.32361970e+00, 2.08542187e+00, 1.74043906e+00, 3.68327123e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.40526270e+00, 3.91183574e+00, 6.08879987e+00, 6.05701802e+00, 3.35127909e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.33684009e+00, 4.74117308e+00, 5.66393572e+00, 3.75144548e+00, 2.83459537e-01, -1.61445732e+00, -2.61883874e+00, -2.76818696e+00, -2.47679180e+00, -2.29014373e+00, -2.50794047e+00, -3.08754938e+00, -3.77455164e+00, -4.26560645e+00, -4.33448168e+00, -3.93383052e+00, -3.19736872e+00, -2.30738448e+00, -1.36778475e+00, -4.13019001e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -2.30731635e-01, -2.71055349e+00, -3.77777456e+00, -3.19820518e+00, -1.62052825e+00, -1.57786580e-01, 0.00000000e+00, -3.39194075e-01, -1.19486567e+00, -1.40982868e+00, -8.24731765e-01, 1.77245380e-02, 0.00000000e+00, 0.00000000e+00, 1.12393272e+00, 3.42883960e+00, 6.44392419e+00, 7.74026022e+00, 6.02300041e+00, 2.15021680e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.31206244e+00, 2.88224433e+00, 2.70442915e+00, 1.31540273e+00, 6.83579157e-02, -1.44657955e-01, -9.74069771e-04, 2.01609711e-01, 7.58795510e-02, -1.14712672e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.16918168e-01, -9.48748823e-02, -3.74701248e-01, -6.68192840e-01, -7.77720853e-01, -8.15718667e-01, -1.19404470e+00, -2.17926682e+00, -3.40215785e+00, -3.99418641e+00, -3.25449483e+00, -1.22032570e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.72304245e+00, -2.63776333e+00, -2.11110151e+00, -7.22241992e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.37988828e-01, -1.36497601e-01, 1.32278945e-01, 5.15571508e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.42548433e-01, 2.72091640e+00, 3.24542027e+00, 2.03399132e+00, 3.77699186e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -1.99799699e-01, 5.92260640e-02, -1.02272668e-02, -3.19939917e-01, -7.49813663e-01, -1.06945353e+00, -1.04483902e+00, -5.36963585e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -3.23192576e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.42596962e-01, -1.71901114e-01, -7.45893810e-02, 3.71940362e-01, 6.24286373e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -9.16154067e-02, -8.72890060e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.36067934e-01, 1.13854180e+00, 4.79721529e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00]) # fmt: on )

61.668155

92

0.637171

6,597

41,441

3.993027

0.068971

0.567914

0.681497

0.767444

0.947384

0.942753

0.937135

0.934819

0.932807

0

0.67774

0.199537

41,441

671

93

61.76006

0.116363

0.004199

0

0.847134

0

0.000485

0

0.036624

1

0.009554

false

0

0.014331

0

0.02707

0.003185

0

null

1

0

1

0

1

0

1

0

null

0

12

ef70c70213111c3000552a67883e02a0cf97b098

152

py

Python

snip/__main__.py

arminfriedl/snip

b689ba8634ea192c2b19adbc075e70d451a4f4b3

[ "MIT" ]

null

snip/__main__.py

arminfriedl/snip

b689ba8634ea192c2b19adbc075e70d451a4f4b3

[ "MIT" ]

null

snip/__main__.py

arminfriedl/snip

b689ba8634ea192c2b19adbc075e70d451a4f4b3

[ "MIT" ]

null

from . import app from . import snip_config if __name__ == "__main__": app.run(host=snip_config.SNIP_FLASK_HOST, port=snip_config.SNIP_FLASK_PORT)

25.333333

79

0.776316

24

152

4.291667

0.5

0.291262

0.271845

0.368932

0

0.125

152

5

80

30.4

0.774436

0

0.052632

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

ef851f2f7095d06956de6df90e3cfded20236a2d

138

py

Python

test/Backend/NoneBackend.py

DatabaseStratum/py-stratum-cli

e02278386d0c82e08760e2f25c9dadfe94c718b6

[ "MIT" ]

11

2015-01-22T11:06:30.000Z

2018-12-21T08:21:21.000Z

test/Backend/NoneBackend.py

DatabaseStratum/py-stratum-cli

e02278386d0c82e08760e2f25c9dadfe94c718b6

[ "MIT" ]

1

2016-10-19T09:10:40.000Z

test/Backend/NoneBackend.py

DatabaseStratum/py-stratum-cli

e02278386d0c82e08760e2f25c9dadfe94c718b6

[ "MIT" ]

6

2016-02-21T15:19:31.000Z

2020-02-23T11:14:07.000Z

from pystratum_backend.Backend import Backend class NoneBackend(Backend): """ Backend without implementations. """ pass

15.333333

45

0.702899

13

138

7.384615

0.692308

0.291667

0

0.217391

138

8

46

17.25

0.888889

0.231884

0

1

0

true

0.333333

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

efa3200e4c1b4560cab7268c01548cb8b8793342

1,099

py

Python

client/Mahjong-GB/test.py

chriswang2468/mj

918a2414c7e4cde5ad17a33a23c90461aabb87f2

[ "Apache-2.0" ]

null

client/Mahjong-GB/test.py

chriswang2468/mj

918a2414c7e4cde5ad17a33a23c90461aabb87f2

[ "Apache-2.0" ]

null

client/Mahjong-GB/test.py

chriswang2468/mj

918a2414c7e4cde5ad17a33a23c90461aabb87f2

[ "Apache-2.0" ]

null

from MahjongGB import MahjongFanCalculator try: ans=MahjongFanCalculator((),("W1","W1","W1","W2","W2","W2","W3","W3","W3","W4","W4","W4","W5"),"W5",1,True,False,False,True,0,0) except Exception as err: print(err) else: print(ans) try: ans=MahjongFanCalculator((("GANG","W1",2),),("W2","W2","W2","W3","W3","W3","W4","W4","W4","W5"),"W5",1,False,False,False,False,0,0) except Exception as err: print(err) else: print(ans) #错误 try: ans=MahjongFanCalculator((),("W1","W1","W1","W2","W2","W2","W3","W3","W3","W4","W4","W4"),"W5",1,True,False,False,True,0,0) except Exception as err: print(err) else: print(ans) #没和 try: ans=MahjongFanCalculator((("CHI","W1",0),),("W2","W2","W2","W3","W3","W3","W4","W4","W4","W5"),"W7",1,False,False,False,False,0,0) except Exception as err: print(err) else: print(ans) try: ans=MahjongFanCalculator((("PENG","W9",0),("CHI","T7",2), ("CHI", "W7", 1), ("CHI", "W7", 2)),("T9", ),"T9",0,False,False,False,False,0,0) except Exception as err: print(err) else: print(ans)

28.179487

143

0.567789

170

1,099

3.670588

0.182353

0.176282

0.144231

0.136218

0.817308

0

0.083156

0.146497

1,099

38

144

28.921053

0.58209

0.00364

0

0.806452

0

0.127014

0

1

0

false

0

0.032258

0

0.032258

0.322581

0

null

0

1

0

1

0

null

0

7

efd942c84898e89c5e274200a496fc342ea706d3

456

py

Python

tsbenchmark/core/loader.py

DataCanvasIO/TSBenchmark

e8e45cd0cd206723ad59a8cac2a572e48f43a728

[ "Apache-2.0" ]

2

2022-03-28T02:10:09.000Z

2022-03-29T02:56:26.000Z

tsbenchmark/core/loader.py

DataCanvasIO/TSBenchmark

e8e45cd0cd206723ad59a8cac2a572e48f43a728

[ "Apache-2.0" ]

null

tsbenchmark/core/loader.py

DataCanvasIO/TSBenchmark

e8e45cd0cd206723ad59a8cac2a572e48f43a728

[ "Apache-2.0" ]

null

class DataSetLoader: def __init__(self): pass def list(self, data_size, type): pass def exists(self, dataset_id): pass def load_meta(self, dataset_id): pass def load(self, dataset_id): pass class TaskLoader: def __init__(self): pass def list(self, data_size, type): pass def exists(self, dataset_id): pass def load(self, dataset_id): pass

15.2

36

0.572368

57

456

4.298246

0.280702

0.2

0.265306

0.346939

0.84898

0

0.344298

456

29

37

15.724138

0.819398

0

0.85

0

1

0.45

false

0.45

0

0.55

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

12

4bc6a9a095380babfa08d9bb75d70e047c8ef5a3

94

py

Python

carsus/io/output/__init__.py

parikshit14/carsus

3f67e8068829829361d7b1da9020e1fde9dcac2e

[ "BSD-3-Clause" ]

21

2016-06-01T16:12:03.000Z

2022-02-04T09:03:38.000Z

carsus/io/output/__init__.py

parikshit14/carsus

3f67e8068829829361d7b1da9020e1fde9dcac2e

[ "BSD-3-Clause" ]

149

2016-05-03T17:50:42.000Z

2022-03-25T14:48:51.000Z

carsus/io/output/__init__.py

parikshit14/carsus

3f67e8068829829361d7b1da9020e1fde9dcac2e

[ "BSD-3-Clause" ]

34

2016-05-03T16:39:11.000Z

2022-02-03T16:39:49.000Z

from carsus.io.output.tardis_ import AtomData from carsus.io.output.base import TARDISAtomData

47

48

0.861702

14

94

5.714286

0.642857

0.25

0.3

0.45

0

0.074468

94

2

48

47

0.91954

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

ef232963020f3dcb500abc12fb3e5f9deeb905ee

23

py

Python

src/mathlib1/add.py

PartehDev/mathlib1

65047d1d5c4ecddee4c889786552592be1d1ea94

[ "MIT" ]

null

src/mathlib1/add.py

PartehDev/mathlib1

65047d1d5c4ecddee4c889786552592be1d1ea94

[ "MIT" ]

null

src/mathlib1/add.py

PartehDev/mathlib1

65047d1d5c4ecddee4c889786552592be1d1ea94

[ "MIT" ]

null

def add(a,b):return a+b

23

0.695652

7

23

2.285714

0.714286

0.25

0

0.086957

23

1

23

0.761905

0

1

false

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

3291d375be54358c9df1c7bffc404d1ca663bb1c

216

py

Python

tests/test_caller_module.py

brunonicko/basicco

8cd1d66073df47c6b56be3d431f8e6b9ed6d9fa9

[ "MIT" ]

6

2021-11-16T11:26:54.000Z

2022-01-24T05:50:22.000Z

tests/test_caller_module.py

brunonicko/basicco

8cd1d66073df47c6b56be3d431f8e6b9ed6d9fa9

[ "MIT" ]

null

tests/test_caller_module.py

brunonicko/basicco

8cd1d66073df47c6b56be3d431f8e6b9ed6d9fa9

[ "MIT" ]

null

import pytest from basicco import caller_module def test_caller_module(): def func(): return caller_module.caller_module() assert func() == __name__ if __name__ == "__main__": pytest.main()

14.4

44

0.685185

26

216

5.038462

0.538462

0.366412

0.229008

0

0.217593

216

14

45

15.428571

0.775148

0

0.037037

0

0.125

1

0.25

true

0

0.25

0.125

0.625

0

1

0

null

1

0

null

0

1

0

1

0

7

32b941bf04bd246d3c3b4f5ef0b8fc17ee88549c

2,301

py

Python

tests/v2/test_1379-reducers-with-axis-None-and-typetracers.py

douglasdavis/awkward-1.0

f00775803a5568efb0a8e2dae3b1a4f23228fa40

[ "BSD-3-Clause" ]

2

2019-09-12T03:07:23.000Z

2019-09-27T05:32:07.000Z

tests/v2/test_1379-reducers-with-axis-None-and-typetracers.py

douglasdavis/awkward-1.0

f00775803a5568efb0a8e2dae3b1a4f23228fa40

[ "BSD-3-Clause" ]

1

2019-09-26T17:57:45.000Z

tests/v2/test_1379-reducers-with-axis-None-and-typetracers.py

douglasdavis/awkward-1.0

f00775803a5568efb0a8e2dae3b1a4f23228fa40

[ "BSD-3-Clause" ]

null

# BSD 3-Clause License; see https://github.com/scikit-hep/awkward-1.0/blob/main/LICENSE import pytest # noqa: F401 import awkward as ak # noqa: F401 def test(): x = ak._v2.from_iter([[{"x": 1, "y": 1.1}], [], [{"x": 2, "y": 2.2}]]) x_tt = ak._v2.Array(x.layout.typetracer) assert str(ak._v2.count(x_tt, flatten_records=True)) == "unknown-int64" assert str(ak._v2.count_nonzero(x_tt, flatten_records=True)) == "unknown-int64" assert str(ak._v2.any(x_tt, flatten_records=True)) == "unknown-bool" assert str(ak._v2.all(x_tt, flatten_records=True)) == "unknown-bool" assert str(ak._v2.prod(x_tt, flatten_records=True)) == "unknown-float64" assert str(ak._v2.sum(x_tt, flatten_records=True)) == "unknown-float64" assert str(ak._v2.max(x_tt, flatten_records=True)) == "maybe-unknown-float64" assert str(ak._v2.min(x_tt, flatten_records=True)) == "maybe-unknown-float64" assert str(ak._v2.argmax(x_tt, flatten_records=True)) == "maybe-unknown-int64" assert str(ak._v2.argmin(x_tt, flatten_records=True)) == "maybe-unknown-int64" assert str(ak._v2.count(x_tt.x)) == "unknown-int64" assert str(ak._v2.count_nonzero(x_tt.x)) == "unknown-int64" assert str(ak._v2.any(x_tt.x)) == "unknown-bool" assert str(ak._v2.all(x_tt.x)) == "unknown-bool" assert str(ak._v2.prod(x_tt.x, flatten_records=True)) == "unknown-int64" assert str(ak._v2.prod(x_tt.y, flatten_records=True)) == "unknown-float64" assert str(ak._v2.sum(x_tt.x, flatten_records=True)) == "unknown-int64" assert str(ak._v2.sum(x_tt.y, flatten_records=True)) == "unknown-float64" assert str(ak._v2.max(x_tt.x)) == "maybe-unknown-int64" assert str(ak._v2.max(x_tt.y)) == "maybe-unknown-float64" assert str(ak._v2.min(x_tt.x)) == "maybe-unknown-int64" assert str(ak._v2.min(x_tt.y)) == "maybe-unknown-float64" assert str(ak._v2.argmax(x_tt.x)) == "maybe-unknown-int64" assert str(ak._v2.argmax(x_tt.y)) == "maybe-unknown-int64" assert str(ak._v2.argmin(x_tt.x)) == "maybe-unknown-int64" assert str(ak._v2.argmin(x_tt.y)) == "maybe-unknown-int64" assert str(ak._v2.mean(x_tt, flatten_records=True)) == "unknown-float64" assert str(ak._v2.mean(x_tt.x)) == "unknown-float64" assert str(ak._v2.mean(x_tt.y)) == "unknown-float64"

54.785714

87

0.678401

389

2,301

3.809769

0.138817

0.083671

0.21525

0.254386

0.873819

0.84278

0.74359

0

0.047904

0.129074

2,301

41

88

56.121951

0.691617

0.046502

0

0.215068

0.038356

0

0.852941

1

0.029412

false

0

0.058824

0

0.088235

0

null

0

1

0

null

0

1

0

9

32bc841a1ae90cb8aec304523dd80d96f0118d6b

219

py

Python

py_learning_6_30/CheckName.py

Mloser-z/Python_Learning

c0b663faec17349547c8089fc2a918153b675ae9

[ "Apache-2.0" ]

null

py_learning_6_30/CheckName.py

Mloser-z/Python_Learning

c0b663faec17349547c8089fc2a918153b675ae9

[ "Apache-2.0" ]

null

py_learning_6_30/CheckName.py

Mloser-z/Python_Learning

c0b663faec17349547c8089fc2a918153b675ae9

[ "Apache-2.0" ]

null

def get_formatted_name(first, last): return first.title() + ' ' + last.title() def get_name(): first = 'janis' last = 'joplin' full_name = get_formatted_name(first, last) return full_name

21.9

48

0.625571

28

219

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0.392857

0.207692

0.246154

0.323077

0.476923

0

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219

9

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24.333333

0.792683

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false

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0

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null

1

0

1

0

null

0

1

0

1

0

7

32bc89489164310cc376277bbde50adb0ed71718

3,445

py

Python

swmm_calibration/helpers/utils.py

mmmatthew/swmm_calibration

b6bcd1bdb71d25f2095c6863609735de8e3bd6bc

[ "MIT" ]

5

2019-10-22T03:56:21.000Z

2021-05-23T02:39:14.000Z

swmm_calibration/helpers/utils.py

mmmatthew/swmm_calibration

b6bcd1bdb71d25f2095c6863609735de8e3bd6bc

[ "MIT" ]

2

2019-07-12T01:04:09.000Z

2021-06-01T23:29:30.000Z

swmm_calibration/helpers/utils.py

mmmatthew/swmm_calibration

b6bcd1bdb71d25f2095c6863609735de8e3bd6bc

[ "MIT" ]

3

2019-03-12T15:01:33.000Z

2021-12-01T07:35:40.000Z

import pandas as pd from datetime import datetime import csv def format_resample( input_file, # full path to data file to be read output_file, # path to file where data should be saved aggregation_frequency=None, # resampling frequency of data aggregation_type='mean' # aggregation method for data ): # reads CSV data in pandas format and outputs data in SWMM format # resamples the data to 1-second frequency # read data data = pd.read_csv(input_file, parse_dates=[0], index_col=0, infer_datetime_format=True, dayfirst=True, # date_parser=date_parser, sep=';') # aggregate per second, interpolate data = data.resample('S') data = data.mean() data = data.resample('S') data = data.interpolate(method='linear') data['datetime'] = data.index data['date'] = data['datetime'].apply(lambda x: x.strftime('%m/%d/%Y')) data['time'] = data['datetime'].apply(lambda x: x.strftime('%H:%M:%S')) data.to_csv(output_file, sep=' ', columns=['date', 'time', 'value'], # quoting=3, #csv.QUOTE_NONE, index=False, header=False) def resample( input_file, # full path to data file to be read output_file, # path to file where data should be saved aggregation_period='S', # resampling frequency of data aggregation_type='mean' # aggregation method for data ): # converts pandas formatted file to SWMM formatted file # read data data = pd.read_csv(input_file, parse_dates=[0], index_col=0, infer_datetime_format=True, dayfirst=True, # date_parser=date_parser, sep=';') # aggregate per second, interpolate data = data.resample(aggregation_period) data = data.mean() data = data.resample(aggregation_period) data = data.interpolate(method='linear') data['datetime'] = data.index data.to_csv(output_file, sep=';', columns=['datetime', 'value'], # quoting=3, #csv.QUOTE_NONE, index=False, header=True) def format( input_file, # full path to data file to be read output_file, # path to file where data should be saved aggregation_frequency=None, # resampling frequency of data aggregation_type='mean' # aggregation method for data ): # converts pandas formatted file to SWMM formatted file # read data data = pd.read_csv(input_file, parse_dates=[0], index_col=0, infer_datetime_format=True, dayfirst=True, # date_parser=date_parser, sep=';') data['datetime'] = data.index data['date'] = data['datetime'].apply(lambda x: x.strftime('%m/%d/%Y')) data['time'] = data['datetime'].apply(lambda x: x.strftime('%H:%M:%S')) data.to_csv(output_file, sep=' ', columns=['date', 'time', 'value'], # quoting=3, #csv.QUOTE_NONE, index=False, header=False)

34.79798

77

0.542816

387

3,445

4.70801

0.193798

0.048299

0.035126

0.050494

0.902854

0.884193

0.838639

0.816136

0

0.004486

0.352975

3,445

98

78

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0.812921

0.250218

0

0.855072

0

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0

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0.043478

false

0

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0

0.086957

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null

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1

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null

0

7

3ee9f7ca6d29d803d5c1f96c414b73a6c77e5c36

168

py

Python

auth-center/App/api/user_source/__init__.py

Basic-Components/auth-center

bf03922be37161108426712465719f5a3f165834

[ "MIT" ]

1

2021-08-03T09:02:26.000Z

auth-center/App/api/user_source/__init__.py

Basic-Components/auth-center

bf03922be37161108426712465719f5a3f165834

[ "MIT" ]

null

auth-center/App/api/user_source/__init__.py

Basic-Components/auth-center

bf03922be37161108426712465719f5a3f165834

[ "MIT" ]

1

2018-01-15T14:28:46.000Z

from .user_list import UserListSource from .user_roles import UserRoleSource from .user_password import UserPasswordSource from .user_main_email import UserEmailSource

33.6

45

0.880952

21

168

6.809524

0.571429

0.223776

0

0.095238

168

4

46

42

0.940789

0

1

0

true

0.25

1

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1

0

null

1

0

1

0

null

0

1

0

1

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7

41019bacd3247527326f33c61636e81912648266

118

py

Python

train_clf/__init__.py

newTypeGeek/face-recognition

235cf4aaf60ba3504b0e73dbab5f9dc4c7cc3dbd

[ "Apache-2.0" ]

5

2020-02-10T04:38:40.000Z

2021-09-01T18:50:18.000Z

train_clf/__init__.py

newTypeGeek/face-recognition

235cf4aaf60ba3504b0e73dbab5f9dc4c7cc3dbd

[ "Apache-2.0" ]

1

2020-06-11T18:26:38.000Z

train_clf/__init__.py

newTypeGeek/face-recognition

235cf4aaf60ba3504b0e73dbab5f9dc4c7cc3dbd

[ "Apache-2.0" ]

3

2019-06-24T12:30:12.000Z

2020-02-10T04:39:59.000Z

import train_clf.train_svm as train_svm import train_clf.train_knn as train_knn import train_clf.train_rf as train_rf

29.5

39

0.872881

24

118

3.916667

0.291667

0.351064

0.446809

0.606383

0

0.101695

118

3

40

39.333333

0.886792

0

1

0

true

0

1

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1

0

1

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null

1

0

1

0

null

0

1

0

1

0

1

0

8

4106c47b8c30b1131d7b048fc142e9f842193ec4

25,328

py

Python

app/forms.py

stolau/oty_ilmo

61764d3a352c5f0325d4baec983f311ba5037e04

[ "MIT" ]

null

app/forms.py

stolau/oty_ilmo

61764d3a352c5f0325d4baec983f311ba5037e04

[ "MIT" ]

null

app/forms.py

stolau/oty_ilmo

61764d3a352c5f0325d4baec983f311ba5037e04

[ "MIT" ]

null

from flask_wtf import FlaskForm from wtforms import StringField, BooleanField, SubmitField, RadioField, TextAreaField, SelectField from wtforms.validators import DataRequired, Email, Optional, length, Required, InputRequired, Optional class RequiredIf(InputRequired): """Validator which makes a field required if another field is set and has a truthy value. Sources: - http://wtforms.simplecodes.com/docs/1.0.1/validators.html - http://stackoverflow.com/questions/8463209/how-to-make-a-field-conditionally-optional-in-wtforms - https://www.reddit.com/r/flask/comments/7y1k6p/af_wtforms_required_if_validator/ """ field_flags = ('requiredif',) def __init__(self, other_field_name, message=None, *args, **kwargs): self.other_field_name = other_field_name self.message = message def __call__(self, form, field): other_field = form[self.other_field_name] if other_field is None: raise Exception('no field named "%s" in form' % self.other_field_name) if bool(other_field.data): super(RequiredIf, self).__call__(form, field) else: Optional().__call__(form, field) class RequiredIfValue(InputRequired): """Validator which makes a field required if another field is set and has a truthy value. Sources: - http://wtforms.simplecodes.com/docs/1.0.1/validators.html - http://stackoverflow.com/questions/8463209/how-to-make-a-field-conditionally-optional-in-wtforms - https://www.reddit.com/r/flask/comments/7y1k6p/af_wtforms_required_if_validator/ """ field_flags = ('requiredif',) def __init__(self, other_field_name, value, message=None, *args, **kwargs): self.other_field_name = other_field_name self.message = message self.value = value def __call__(self, form, field): other_field = form[self.other_field_name] value = self.value if other_field is None: raise Exception('no field named "%s" in form' % self.other_field_name) if bool(other_field.data == value): super(RequiredIfValue, self).__call__(form, field) else: Optional().__call__(form, field) class pubivisaForm(FlaskForm): teamname = StringField('Joukkueen nimi *', validators=[DataRequired(), length(max=100)]) etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta0 = SelectField('Kilta *', choices=(['OTiT', 'OTiT'], ['SIK', 'SIK'], ['YMP', 'YMP'], ['KONE', 'KONE'], ['PROSE', 'PROSE'], ['OPTIEM', 'OPTIEM'], ['ARK', 'ARK']), validators=[DataRequired()]) etunimi1 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi1 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone1 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email1 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta1 = SelectField('Kilta *', choices=(['OTiT', 'OTiT'], ['SIK', 'SIK'], ['YMP', 'YMP'], ['KONE', 'KONE'], ['PROSE', 'PROSE'], ['OPTIEM', 'OPTIEM'], ['ARK', 'ARK']), validators=[DataRequired()]) etunimi2 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi2 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone2 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email2 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta2 = SelectField('Kilta *', choices=(['OTiT', 'OTiT'], ['SIK', 'SIK'], ['YMP', 'YMP'], ['KONE', 'KONE'], ['PROSE', 'PROSE'], ['OPTIEM', 'OPTIEM'], ['ARK', 'ARK']), validators=[DataRequired()]) etunimi3 = StringField('Etunimi', validators=[length(max=50)]) sukunimi3 = StringField('Sukunimi', validators=[length(max=50)]) phone3 = StringField('Puhelinnumero', validators=[length(max=20)]) email3 = StringField('Sähköposti', validators=[length(max=100)]) kilta3 = SelectField('Kilta', choices=(['OTiT', 'OTiT'], ['SIK', 'SIK'], ['YMP', 'YMP'], ['KONE', 'KONE'], ['PROSE', 'PROSE'], ['OPTIEM', 'OPTIEM'], ['ARK', 'ARK'])) consent0 = BooleanField('Sallin joukkueen nimen julkaisemisen osallistujalistassa') consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) consent2 = BooleanField('Ymmärrän, että ilmoittautuminen on sitova *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class korttijalautapeliiltaForm(FlaskForm): etunimi = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta = SelectField('Kilta *', choices=(['OTiT', 'OTiT'], ['SIK', 'SIK'], ['YMP', 'YMP'], ['KONE', 'KONE'], ['PROSE', 'PROSE'], ['OPTIEM', 'OPTIEM'], ['ARK', 'ARK'])) consent0 = BooleanField('Sallin nimeni julkaisemisen osallistujalistassa') consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojeni käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) consent2 = BooleanField('Ymmärrän, että ilmoittautuminen on sitova *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class fuksilauluiltaForm(FlaskForm): etunimi = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) email = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojeni käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class slumberpartyForm(FlaskForm): etunimi = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta = SelectField('Kilta *', choices=(['OTiT', 'OTiT'], ['SIK', 'SIK'], ['YMP', 'YMP'], ['KONE', 'KONE'], ['PROSE', 'PROSE'], ['OPTIEM', 'OPTIEM'], ['ARK', 'ARK'])) consent0 = BooleanField('Sallin nimeni julkaisemisen osallistujalistassa') consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojeni käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) consent2 = BooleanField('Ymmärrän, että ilmoittautuminen on sitova *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class pakohuoneForm(FlaskForm): aika = RadioField('Aika *', choices=(['18:00', '18:00'], ['19:30', '19:30']), validators=[DataRequired()]) huone1800 = RadioField('Huone (18:00) *', choices=(['Pommi (Uusikatu)', ''], ['Kuolleen miehen saari (Uusikatu)', ''], ['Temppelin kirous (Uusikatu)', ''], ['Velhon perintö (Uusikatu)', ''], ['Murhamysteeri (Kajaaninkatu)', ''], ['Vankilapako (Kajaaninkatu)', ''], ['Professorin arvoitus (Kajaaninkatu)', ''], ['The SAW (Kirkkokatu)', ''], ['Alcatraz (Kirkkokatu)', ''], ['Matka maailman ympäri (Kirkkokatu)', ''], ['', '']), validators=[RequiredIfValue(other_field_name='aika', value='18:00')], default=(['', ''])) huone1930 = RadioField('Huone (19:30) *', choices=(['Pommi (Uusikatu)', ''], ['Kuolleen miehen saari (Uusikatu)', ''], ['Temppelin kirous (Uusikatu)', ''], ['Velhon perintö (Uusikatu)', ''], ['Murhamysteeri (Kajaaninkatu)', ''], ['Vankilapako (Kajaaninkatu)', ''], ['Professorin arvoitus (Kajaaninkatu)', ''], ['The SAW (Kirkkokatu)', ''], ['Alcatraz (Kirkkokatu)', ''], ['Matka maailman ympäri (Kirkkokatu)', ''], ['', '']), validators=[RequiredIfValue(other_field_name='aika', value='19:30')], default=(['', ''])) etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) etunimi1 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi1 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) etunimi2 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi2 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) etunimi3 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi3 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) etunimi4 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi4 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) etunimi5 = StringField('Etunimi', validators=[length(max=50)]) sukunimi5 = StringField('Sukunimi', validators=[length(max=50)]) consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojeni käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class kysely_arvonta_juttuForm(FlaskForm): etunimi = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) email = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojeni käytön *', validators=[DataRequired()]) submit = SubmitField('Submit') class ots2021Form(FlaskForm): etunimi = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) email = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta = SelectField('Kilta', choices=(['ARK', 'Oulun Arkkitehtikilta ry'], ['KONE', 'Oulun Yliopiston Koneinsinöörikilta ry'], ['OLTO', 'Oulun lääketieteen tekniikan opiskelijat ry'], ['OPTIEM', 'OPTIEM - Oulun Tuotantotalousteekkarit ry'], ['OTiT', 'Oulun Tietoteekkarit ry'], ['PROSE', 'Oulun yliopiston Prosessikilta ry'], ['SIK', 'Sähköinsinöörikilta ry'], ['YMP', 'Oulun yliopiston Ympäristörakentajakilta ry'], ['MUU', 'Muu taho'])) consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojeni käytön *', validators=[DataRequired()]) consent1 = BooleanField('Minulle saa lähettää kutsun OTS sitseille myöhemmin', validators=[]) submit = SubmitField('Submit') class fuksisitsitForm(FlaskForm): ''' Created 7.4.2021 ''' membercount = SelectField('Jäsenmäärä', choices=(['1', '1'], ['2', '2'], ['3', '3'], ['4', '4'], ['5', '5'], ['6', '6']), validators=[DataRequired()]) etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta0 = SelectField('Kilta *', choices=(['ARK', 'Oulun Arkkitehtikilta ry'], ['KONE', 'Oulun Yliopiston Koneinsinöörikilta ry'], ['OLTO', 'Oulun lääketieteen tekniikan opiskelijat ry'], ['OPTIEM', 'OPTIEM - Oulun tuotantotalousteekkarit ry'], ['OTiT', 'Oulun Tietoteekkarit ry'], ['PROSE', 'Oulun yliopiston Prosessikilta ry'], ['SIK', 'Sähköinsinöörikilta ry'], ['YRK', 'Oulun yliopiston Ympäristörakentajakilta ry'], ['MUU', 'Muu taho']), validators=[DataRequired()]) vapaavalinta0 = StringField('Muut samalla yhteydellä osallistuvat', validators=[length(max=200)]) consent0 = BooleanField('Sallin nimeni julkaisemisen osallistujalistassa') consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) consent2 = BooleanField('Ymmärrän, että ilmoittautuminen on sitova *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class tupsufuksisitsitForm(FlaskForm): ''' Created 7.4.2021 ''' membercount = SelectField('Jäsenmäärä', choices=(['1', '1'], ['2', '2'], ['3', '3'], ['4', '4'], ['5', '5'], ['6', '6']), validators=[DataRequired()]) etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta0 = SelectField('Kilta *', choices=(['ARK', 'Oulun Arkkitehtikilta ry'], ['KONE', 'Oulun Yliopiston Koneinsinöörikilta ry'], ['OLTO', 'Oulun lääketieteen tekniikan opiskelijat ry'], ['OPTIEM', 'OPTIEM - Oulun tuotantotalousteekkarit ry'], ['OTiT', 'Oulun Tietoteekkarit ry'], ['PROSE', 'Oulun yliopiston Prosessikilta ry'], ['SIK', 'Sähköinsinöörikilta ry'], ['YRK', 'Oulun yliopiston Ympäristörakentajakilta ry'], ['MUU', 'Muu taho']), validators=[DataRequired()]) vapaavalinta0 = StringField('Muut samalla yhteydellä osallistuvat', validators=[length(max=200)]) consent0 = BooleanField('Sallin nimeni julkaisemisen osallistujalistassa') consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) consent2 = BooleanField('Ymmärrän, että ilmoittautuminen on sitova *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class fuksibeerpongForm(FlaskForm): ''' Created 7.4.2021 ''' joukkue = StringField('Joukkueen nimi *', validators=[DataRequired(), length(max=50)]) etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) etunimi1 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi1 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) consent0 = BooleanField('Sallin joukkueen julkaisemisen osallistujalistassa') consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) consent2 = BooleanField('Ymmärrän, että ilmoittautuminen on sitova *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class beerpongForm(FlaskForm): ''' Created 7.4.2021 ''' joukkue = StringField('Joukkueen nimi *', validators=[DataRequired(), length(max=50)]) etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) etunimi1 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi1 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) consent0 = BooleanField('Sallin joukkueen julkaisemisen osallistujalistassa') consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) consent2 = BooleanField('Ymmärrän, että ilmoittautuminen on sitova *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class aitiForm(FlaskForm): ''' Created 7.4.2021 ''' etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) kilta0 = SelectField('Kilta *', choices=(['ARK', 'Oulun Arkkitehtikilta ry'], ['KONE', 'Oulun Yliopiston Koneinsinöörikilta ry'], ['OLTO', 'Oulun lääketieteen tekniikan opiskelijat ry'], ['OPTIEM', 'OPTIEM - Oulun tuotantotalousteekkarit ry'], ['OTiT', 'Oulun Tietoteekkarit ry'], ['PROSE', 'Oulun yliopiston Prosessikilta ry'], ['SIK', 'Sähköinsinöörikilta ry'], ['YRK', 'Oulun yliopiston Ympäristörakentajakilta ry'], ['MUU', 'Muu taho']), validators=[DataRequired()]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class hvsitsituusiForm(FlaskForm): ''' Created 7.4.2021 ''' etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) drink0 = SelectField('Mietojuoma *', choices=(['Olut', 'Olut'], ['Siideri', 'Siideri'], ['Alkoholiton', 'Alkoholiton']), validators=[DataRequired()]) wine0 = SelectField('Viini *', choices=(['Puna', 'Puna'], ['Valko', 'Valko'], ['Alkoholiton', 'Alkoholiton'], ['Ei ollenkaan', 'Ei Ollenkaan']), validators=[DataRequired()]) viina0 = SelectField('Viinakaato *', choices=(['Alkoholi', 'Alkoholi'], ['Alkoholiton', 'Alkoholiton']), validators=[DataRequired()]) other0 = StringField('Ruokavalio/Allergiat ', validators=[length(max=150)]) consent1 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class syysuitotForm(FlaskForm): ''' Created 7.4.2021 ''' etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta0 = SelectField('Kilta *', choices=(['ARK', 'Oulun Arkkitehtikilta ry'], ['KONE', 'Oulun Yliopiston Koneinsinöörikilta ry'], ['OLTO', 'Oulun lääketieteen tekniikan opiskelijat ry'], ['OPTIEM', 'OPTIEM - Oulun tuotantotalousteekkarit ry'], ['OTiT', 'Oulun Tietoteekkarit ry'], ['PROSE', 'Oulun yliopiston Prosessikilta ry'], ['SIK', 'Sähköinsinöörikilta ry'], ['YRK', 'Oulun yliopiston Ympäristörakentajakilta ry'], ['MUU', 'Muu taho']), validators=[DataRequired()]) lakki0 = BooleanField('Haen teekkarilakin uittojen jälkeen ') consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class prositsitForm(FlaskForm): ''' Created 7.4.2021 ''' etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=20)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) kilta0 = SelectField('Kilta *', choices=(['ARK', 'Oulun Arkkitehtikilta ry'], ['KONE', 'Oulun Yliopiston Koneinsinöörikilta ry'], ['OLTO', 'Oulun lääketieteen tekniikan opiskelijat ry'], ['OPTIEM', 'OPTIEM - Oulun tuotantotalousteekkarit ry'], ['OTiT', 'Oulun Tietoteekkarit ry'], ['PROSE', 'Oulun yliopiston Prosessikilta ry'], ['SIK', 'Sähköinsinöörikilta ry'], ['YRK', 'Oulun yliopiston Ympäristörakentajakilta ry'], ['MUU', 'Muu taho']), validators=[DataRequired()]) food0 = SelectField('Ruoka *', choices=(['Sekasyöjä', 'Sekasyöjä'], ['Vegetaristi', 'Vegetaristi'], ['Vegaani', 'Vegaani']), validators=[DataRequired()]) allergies0 = StringField('Allergiat ', validators=[length(max=100)]) drink0 = SelectField('Mieto *', choices=(['Olut', 'Olut'], ['Siideri', 'Siideri'], ['Holiton', 'Holiton']), validators=[DataRequired()]) drink1 = SelectField('Viini *', choices=(['Punaviini', 'Punaviini'], ['Valkoviini', 'Valkoviini'], ['Holiton', 'holiton']), validators=[DataRequired()]) drink2 = SelectField('Snapsi *', choices=(['Holillinen', 'Holillinen'], ['Holiton', 'Holiton']), validators=[DataRequired()]) consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class simailutForm(FlaskForm): ''' Created 7.4.2021 ''' etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) special0 = StringField('Erikoisruokavalio ', validators=[length(max=100)]) allergies0 = StringField('Allergiat ', validators=[length(max=100)]) avec0 = BooleanField('Avec ', render_kw={'onchange': "slideDownLakki()"}) etunimi1 = StringField('Etunimi *', validators=[RequiredIf('avec0'), length(max=50)]) sukunimi1 = StringField('Sukunimi *', validators=[RequiredIf('avec0'), length(max=50)]) email1 = StringField('Sähköposti *', validators=[RequiredIf('avec0'), length(max=50)]) special1 = StringField('Erikoisruokavalio ', validators=[length(max=100)]) allergies1 = StringField('Allergiat ', validators=[length(max=100)]) consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class kotiruokakurssi1Form(FlaskForm): ''' Created 7.4.2021 ''' etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=50)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) food0 = StringField('Ruokavalio ', validators=[length(max=100)]) allergies0 = StringField('Allergiat ', validators=[length(max=100)]) free0 = StringField('Vapaat terveiset ', validators=[length(max=100)]) consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu') class kotiruokakurssi2Form(FlaskForm): ''' Created 7.4.2021 ''' etunimi0 = StringField('Etunimi *', validators=[DataRequired(), length(max=50)]) sukunimi0 = StringField('Sukunimi *', validators=[DataRequired(), length(max=50)]) phone0 = StringField('Puhelinnumero *', validators=[DataRequired(), length(max=50)]) email0 = StringField('Sähköposti *', validators=[DataRequired(), Email(), length(max=100)]) food0 = StringField('Ruokavalio ', validators=[length(max=100)]) allergies0 = StringField('Allergiat ', validators=[length(max=100)]) free0 = StringField('Vapaat terveiset ', validators=[length(max=100)]) consent0 = BooleanField('Olen lukenut tietosuojaselosteen ja hyväksyn tietojen käytön tapahtuman järjestämisessä *', validators=[DataRequired()]) submit = SubmitField('Ilmoittaudu')

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8

411fefadfe092557567e65ccf3b467a42a552033

83

py

Python

models/lists.py

skamansam/python-web-todo

24ce9bd58efdc796c05e52d56b6c5e9befd48393

[ "Unlicense" ]

null

models/lists.py

skamansam/python-web-todo

24ce9bd58efdc796c05e52d56b6c5e9befd48393

[ "Unlicense" ]

null

models/lists.py

skamansam/python-web-todo

24ce9bd58efdc796c05e52d56b6c5e9befd48393

[ "Unlicense" ]

null

# import ormodel from models.ormodel import ORModel class List(ORModel): pass

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4124c3fb69b1ccdacd0ee1cd25b88a9545574ffd

20,877

py

Python

datahub_client/apis/view_api.py

amkimian/mimir_python

994c1542437fa6bd1d0e53b0c0c4c8f692575374

[ "Apache-2.0" ]

null

datahub_client/apis/view_api.py

amkimian/mimir_python

994c1542437fa6bd1d0e53b0c0c4c8f692575374

[ "Apache-2.0" ]

null

datahub_client/apis/view_api.py

amkimian/mimir_python

994c1542437fa6bd1d0e53b0c0c4c8f692575374

[ "Apache-2.0" ]

null

# coding: utf-8 """ DataHub API DataHub API OpenAPI spec version: 0.0.11 Generated by: https://github.com/swagger-api/swagger-codegen.git Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from __future__ import absolute_import import sys import os import re # python 2 and python 3 compatibility library from six import iteritems from ..configuration import Configuration from ..api_client import ApiClient class ViewApi(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient() self.api_client = config.api_client def get_data_set_releases(self, api_key, user_id, dataset, **kwargs): """ Returns releases for a given data set 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_data_set_releases(api_key, user_id, dataset, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param str user_id: The user id that owns the data set (required) :param str dataset: The id of the data set (required) :return: list[DataSetRelease] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_data_set_releases_with_http_info(api_key, user_id, dataset, **kwargs) else: (data) = self.get_data_set_releases_with_http_info(api_key, user_id, dataset, **kwargs) return data def get_data_set_releases_with_http_info(self, api_key, user_id, dataset, **kwargs): """ Returns releases for a given data set 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_data_set_releases_with_http_info(api_key, user_id, dataset, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param str user_id: The user id that owns the data set (required) :param str dataset: The id of the data set (required) :return: list[DataSetRelease] If the method is called asynchronously, returns the request thread. """ all_params = ['api_key', 'user_id', 'dataset'] all_params.append('callback') all_params.append('_return_http_data_only') 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_data_set_releases" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'api_key' is set if ('api_key' not in params) or (params['api_key'] is None): raise ValueError("Missing the required parameter `api_key` when calling `get_data_set_releases`") # verify the required parameter 'user_id' is set if ('user_id' not in params) or (params['user_id'] is None): raise ValueError("Missing the required parameter `user_id` when calling `get_data_set_releases`") # verify the required parameter 'dataset' is set if ('dataset' not in params) or (params['dataset'] is None): raise ValueError("Missing the required parameter `dataset` when calling `get_data_set_releases`") resource_path = '/view/releases/{userId}/{dataset}'.replace('{format}', 'json') path_params = {} if 'user_id' in params: path_params['userId'] = params['user_id'] if 'dataset' in params: path_params['dataset'] = params['dataset'] query_params = {} header_params = {} if 'api_key' in params: header_params['api_key'] = params['api_key'] form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type([]) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[DataSetRelease]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def get_release_elements(self, api_key, user_id, dataset, release, **kwargs): """ Returns the element information for a given release 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_release_elements(api_key, user_id, dataset, release, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param str user_id: (required) :param str dataset: (required) :param str release: (required) :return: list[DataElement] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_release_elements_with_http_info(api_key, user_id, dataset, release, **kwargs) else: (data) = self.get_release_elements_with_http_info(api_key, user_id, dataset, release, **kwargs) return data def get_release_elements_with_http_info(self, api_key, user_id, dataset, release, **kwargs): """ Returns the element information for a given release 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_release_elements_with_http_info(api_key, user_id, dataset, release, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param str user_id: (required) :param str dataset: (required) :param str release: (required) :return: list[DataElement] If the method is called asynchronously, returns the request thread. """ all_params = ['api_key', 'user_id', 'dataset', 'release'] all_params.append('callback') all_params.append('_return_http_data_only') 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_release_elements" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'api_key' is set if ('api_key' not in params) or (params['api_key'] is None): raise ValueError("Missing the required parameter `api_key` when calling `get_release_elements`") # verify the required parameter 'user_id' is set if ('user_id' not in params) or (params['user_id'] is None): raise ValueError("Missing the required parameter `user_id` when calling `get_release_elements`") # verify the required parameter 'dataset' is set if ('dataset' not in params) or (params['dataset'] is None): raise ValueError("Missing the required parameter `dataset` when calling `get_release_elements`") # verify the required parameter 'release' is set if ('release' not in params) or (params['release'] is None): raise ValueError("Missing the required parameter `release` when calling `get_release_elements`") resource_path = '/view/elements/{userId}/{dataset}/{release}'.replace('{format}', 'json') path_params = {} if 'user_id' in params: path_params['userId'] = params['user_id'] if 'dataset' in params: path_params['dataset'] = params['dataset'] if 'release' in params: path_params['release'] = params['release'] query_params = {} header_params = {} if 'api_key' in params: header_params['api_key'] = params['api_key'] form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type([]) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[DataElement]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def get_user_subscriptions(self, api_key, **kwargs): """ 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_user_subscriptions(api_key, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param int page: The page of results to return :return: list[Subscription] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_user_subscriptions_with_http_info(api_key, **kwargs) else: (data) = self.get_user_subscriptions_with_http_info(api_key, **kwargs) return data def get_user_subscriptions_with_http_info(self, api_key, **kwargs): """ 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_user_subscriptions_with_http_info(api_key, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param int page: The page of results to return :return: list[Subscription] If the method is called asynchronously, returns the request thread. """ all_params = ['api_key', 'page'] all_params.append('callback') all_params.append('_return_http_data_only') 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_user_subscriptions" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'api_key' is set if ('api_key' not in params) or (params['api_key'] is None): raise ValueError("Missing the required parameter `api_key` when calling `get_user_subscriptions`") resource_path = '/view/subscriptions'.replace('{format}', 'json') path_params = {} query_params = {} if 'page' in params: query_params['page'] = params['page'] header_params = {} if 'api_key' in params: header_params['api_key'] = params['api_key'] form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type([]) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Subscription]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only')) def get_user_views(self, api_key, **kwargs): """ Returns view information for datasets of a user This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_user_views(api_key, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param int page: The page of results to return :return: list[DataSetView] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.get_user_views_with_http_info(api_key, **kwargs) else: (data) = self.get_user_views_with_http_info(api_key, **kwargs) return data def get_user_views_with_http_info(self, api_key, **kwargs): """ Returns view information for datasets of a user This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_user_views_with_http_info(api_key, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str api_key: The user api key (required) :param int page: The page of results to return :return: list[DataSetView] If the method is called asynchronously, returns the request thread. """ all_params = ['api_key', 'page'] all_params.append('callback') all_params.append('_return_http_data_only') 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_user_views" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'api_key' is set if ('api_key' not in params) or (params['api_key'] is None): raise ValueError("Missing the required parameter `api_key` when calling `get_user_views`") resource_path = '/view/getUserViews'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} if 'api_key' in params: header_params['api_key'] = params['api_key'] if 'page' in params: header_params['page'] = params['page'] form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type([]) # Authentication setting auth_settings = [] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[DataSetView]', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'))

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f5e437550b6e23c4c6c0528e99df5fe7e1d328bb

251

py

Python

ghidra_9.0/Ghidra/Features/Python/ghidra_scripts/external_module_caller.py

ChristopherMorrison/ghidra

e53aa57d1aff79a1df93728f746705c58fe95ab0

[ "Apache-2.0" ]

3

2019-11-14T13:11:35.000Z

2019-12-02T20:51:49.000Z

ghidra_9.0/Ghidra/Features/Python/ghidra_scripts/external_module_caller.py

ChristopherMorrison/ghidra

e53aa57d1aff79a1df93728f746705c58fe95ab0

[ "Apache-2.0" ]

3

2019-07-17T22:51:04.000Z

2019-12-04T05:43:56.000Z

ghidra_9.0/Ghidra/Features/Python/ghidra_scripts/external_module_caller.py

ChristopherMorrison/ghidra

e53aa57d1aff79a1df93728f746705c58fe95ab0

[ "Apache-2.0" ]

3

2019-12-02T13:36:50.000Z

2019-12-04T05:40:12.000Z

# Example of importing an external Ghidra Python module # @category: Examples.Python # Import the external module that wants to access the Ghidra scripting API. # NOTE: see external_module_callee.py for additional tips. import external_module_callee

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7

eb0680d9deaf4e2ae4891235b86761bca171cbef

157

py

Python

default_fs.py

bolaabcd/Polarization2

19d2287f3f73a58a20b96108a069169d75bbd820

[ "MIT" ]

null

default_fs.py

bolaabcd/Polarization2

19d2287f3f73a58a20b96108a069169d75bbd820

[ "MIT" ]

null

default_fs.py

bolaabcd/Polarization2

19d2287f3f73a58a20b96108a069169d75bbd820

[ "MIT" ]

null

from types import FunctionType import numpy as np def same(num_agents : int, f : FunctionType) -> np.ndarray: return np.full((num_agents,num_agents), f)

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null

0

1

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1

0

7

eb1adc145b8f261e3265557093b0dedb90197be5

172

py

Python

windows/debug/__init__.py

IMULMUL/PythonForWindows

61e027a678d5b87aa64fcf8a37a6661a86236589

[ "BSD-3-Clause" ]

479

2016-01-08T00:53:34.000Z

2022-03-22T10:28:19.000Z

windows/debug/__init__.py

IMULMUL/PythonForWindows

61e027a678d5b87aa64fcf8a37a6661a86236589

[ "BSD-3-Clause" ]

38

2017-12-29T17:09:04.000Z

2022-01-31T08:27:47.000Z

windows/debug/__init__.py

IMULMUL/PythonForWindows

61e027a678d5b87aa64fcf8a37a6661a86236589

[ "BSD-3-Clause" ]

103

2016-01-10T01:32:17.000Z

2021-12-24T17:21:06.000Z

from .debugger import Debugger, HXBreakpoint from .symboldbg import SymbolDebugger from .localdbg import LocalDebugger from .breakpoints import * from .breakpoints import *

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7

de3861492bbad87b8ae49e1c2ba0a814242e7975

2,599

py

Python

tests/assert_queries_are_equal_test.py

edharper01/databricks_test

f0560c84bdd0dd3eefa976a1af901927a4f299be

[ "MIT" ]

null

tests/assert_queries_are_equal_test.py

edharper01/databricks_test

f0560c84bdd0dd3eefa976a1af901927a4f299be

[ "MIT" ]

null

tests/assert_queries_are_equal_test.py

edharper01/databricks_test

f0560c84bdd0dd3eefa976a1af901927a4f299be

[ "MIT" ]

1

2020-12-23T20:50:30.000Z

import databricks_test import pytest def test_results_match(): with databricks_test.session() as dbrickstest: query = """ SELECT col1,col2 FROM (VALUES (100,'foo'), (101,'bar'), (102,'baz') ) AS v (col1, col2) """ dbrickstest.assert_queries_are_equal(query, query) def test_results_do_not_match(): with databricks_test.session() as dbrickstest: actual_query = """ SELECT col1,col2 FROM (VALUES (100,'foo'), (101,'bar'), (102,'baz') ) AS v (col1, col2) """ expected_query = """ SELECT col1,col2 FROM (VALUES (100,'foo'), (110,'bar'), (999,'qux') ) AS v (col1, col2) """ with pytest.raises(Exception) as exception_message: dbrickstest.assert_queries_are_equal(actual_query, expected_query) assert str(exception_message.value).startswith("the result sets did not match:") def test_unexpected_result(): with databricks_test.session() as dbrickstest: actual_query = """ SELECT col1,col2 FROM (VALUES (100,'foo'), (101,'bar') ) AS v (col1, col2) """ expected_query = """ SELECT col1,col2 FROM (VALUES (100,'foo') ) AS v (col1, col2) """ expected_message="""the result sets did not match: +---+----+----+ |m |col1|col2| +---+----+----+ |= |100 |foo | |> |101 |bar | +---+----+----+ """ with pytest.raises(Exception) as exception_message: dbrickstest.assert_queries_are_equal(actual_query, expected_query) assert str(exception_message.value)==expected_message def test_missing_result(): with databricks_test.session() as dbrickstest: actual_query = """ SELECT col1,col2 FROM (VALUES (100,'foo') ) AS v (col1, col2) """ expected_query = """ SELECT col1,col2 FROM (VALUES (100,'foo'), (101,'bar') ) AS v (col1, col2) """ expected_message="""the result sets did not match: +---+----+----+ |m |col1|col2| +---+----+----+ |= |100 |foo | |< |101 |bar | +---+----+----+ """ with pytest.raises(Exception) as exception_message: dbrickstest.assert_queries_are_equal(actual_query, expected_query) assert str(exception_message.value)==expected_message

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null

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null

0

7

de3fcbb878c3c9f7aff713761feb6ea84a4a9969

2,880

py

Python

sanicbe/src/helpers/schema/prod_attribute_value.py

fairuztahir/mieagro-be

6b591ecbad7d146f2c252677ba09b9afe2e6e921

[ "MIT" ]

null

sanicbe/src/helpers/schema/prod_attribute_value.py

fairuztahir/mieagro-be

6b591ecbad7d146f2c252677ba09b9afe2e6e921

[ "MIT" ]

null

sanicbe/src/helpers/schema/prod_attribute_value.py

fairuztahir/mieagro-be

6b591ecbad7d146f2c252677ba09b9afe2e6e921

[ "MIT" ]

null

prod_attr_value_post_schema = { 'id': { 'required': True, 'type': 'integer', 'coerce': int, 'min': 1 }, 'name': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 100 }, 'display_name': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 100 }, 'ptav_active': { 'required': True, 'type': 'boolean', 'empty': False }, 'product_attribute_value_id': { 'required': True, 'type': 'list' }, 'attribute_line_id': { 'required': True, 'type': 'list' }, 'price_extra': { 'required': True, 'type': 'float' }, 'exclude_for': { 'required': True, 'type': 'list' }, 'product_tmpl_id': { 'required': True, 'type': 'list' }, 'attribute_id': { 'required': True, 'type': 'list' }, 'ptav_product_variant_ids': { 'required': True, 'type': 'list' }, 'is_custom': { 'required': True, 'type': 'boolean', 'empty': False }, 'display_type': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 100 }, 'create_date': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 20 } } prod_attr_value_upd_schema = { 'id': { 'required': True, 'type': 'integer', 'coerce': int, 'min': 1 }, 'name': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 100 }, 'display_name': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 100 }, 'ptav_active': { 'required': True, 'type': 'boolean', 'empty': False }, 'product_attribute_value_id': { 'required': True, 'type': 'list' }, 'attribute_line_id': { 'required': True, 'type': 'list' }, 'price_extra': { 'required': True, 'type': 'float' }, 'exclude_for': { 'required': True, 'type': 'list' }, 'product_tmpl_id': { 'required': True, 'type': 'list' }, 'attribute_id': { 'required': True, 'type': 'list' }, 'ptav_product_variant_ids': { 'required': True, 'type': 'list' }, 'is_custom': { 'required': True, 'type': 'boolean', 'empty': False }, 'display_type': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 100 }, 'create_date': { 'required': True, 'type': 'string', 'empty': False, 'maxlength': 20 } }

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false

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1

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1

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null

0

10

dee791539dfa8dc18aa2b464da6cefdea026b823

30,163

py

Python

components/image-handler/deleter.py

Kadantte/selfie2anime

0f084d8096bc077d24f2b56385802a74e1529a33

[ "MIT" ]

168

2019-08-17T17:51:34.000Z

2022-03-25T10:00:33.000Z

components/image-handler/deleter.py

Kadantte/selfie2anime

0f084d8096bc077d24f2b56385802a74e1529a33

[ "MIT" ]

1

2021-12-03T04:51:56.000Z

components/image-handler/deleter.py

Kadantte/selfie2anime

0f084d8096bc077d24f2b56385802a74e1529a33

[ "MIT" ]

28

2019-08-18T04:06:23.000Z

2022-01-17T13:48:12.000Z

import boto3 import os from string import Template from time import time from aws_xray_sdk.core import xray_recorder from aws_xray_sdk.core import patch from boto3.dynamodb.conditions import Key libraries = (['boto3']) patch(libraries) dynamo_table = os.environ['DYNAMO_TABLE'] cloudfront_dist = os.environ['CLOUDFRONT_DIST'] def delete(event, context): uuid = event['queryStringParameters']['uuid'] key = event['queryStringParameters']['key'] dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(dynamo_table) resp = table.query( # Add the name of the index you want to use in your query. IndexName="key-index", KeyConditionExpression=Key('key').eq(uuid), ) for item in resp['Items']: if item['token'] == key: s3 = boto3.resource('s3') # Delete outgoing try: s3.Object(item['bucket'], 'outgoing/{}'.format(item['key'])).delete() except Exception as e: print('Failed to delete S3 outgoing: {}'.format(item['key'])) # Delete incoming-cropped try: s3.Object(item['bucket'], 'incoming-cropped/{}'.format(item['key'])).delete() except Exception as e: print('Failed to delete S3 incoming-cropped: {}'.format(item['key'])) # Delete incoming try: s3.Object(item['bucket'], 'incoming/{}'.format(item['key'])).delete() except Exception as e: print('Failed to delete S3 incoming: {}'.format(item['key'])) try: client = boto3.client('cloudfront') response = client.create_invalidation( DistributionId=cloudfront_dist, InvalidationBatch={ 'Paths': { 'Quantity': 1, 'Items': [ '/outgoing/{}'.format(item['key']) ], }, 'CallerReference': str(time()).replace(".", "") } ) except Exception as e: print('Failed to invalidate cache for: {}'.format(item['key'])) html_body = """ <!DOCTYPE html> <html lang="en" xmlns="http://www.w3.org/1999/xhtml" xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta http-equiv="refresh" content="7; url=https://selfie2anime.com/"> <title>Selfie Deleted | Selfie2Anime</title> <link href="https://fonts.googleapis.com/css?family=Merriweather+Sans:400,400i,700,700i" rel="stylesheet"> <style> * { -ms-text-size-adjust: 100%; -webkit-text-size-adjust: 100%; } html, body { margin: 0 auto !important; padding: 0 !important; height: 100% !important; width: 100% !important; background: #f1f1f1; } div[style*="margin: 16px 0"] { margin: 0 !important; } table, td { mso-table-lspace: 0pt !important; mso-table-rspace: 0pt !important; } table { border-spacing: 0 !important; border-collapse: collapse !important; table-layout: fixed !important; margin: 0 auto !important; } img { -ms-interpolation-mode: bicubic; } a { text-decoration: none; } *[x-apple-data-detectors], .unstyle-auto-detected-links *, .aBn { border-bottom: 0 !important; cursor: default !important; color: inherit !important; text-decoration: none !important; font-size: inherit !important; font-family: inherit !important; font-weight: inherit !important; line-height: inherit !important; } .a6S { display: none !important; opacity: 0.01 !important; } .im { color: inherit !important; } img.g-img+div { display: none !important; } @media only screen and (min-device-width: 320px) and (max-device-width: 374px) { u~div .email-container { min-width: 320px !important; } } @media only screen and (min-device-width: 375px) and (max-device-width: 413px) { u~div .email-container { min-width: 375px !important; } } @media only screen and (min-device-width: 414px) { u~div .email-container { min-width: 414px !important; } } </style> <style> .bg_primary { background: #f06292; } .text_primary { color: #f06292; font-weight: bold; } .try_again { font-size: 2em; } .bg_white { background: #fff; } .bg_dark { background: rgba(0, 0, 0, .8); } .email-section { padding: 2.5em; } h1, h2, h3, h4, h5, h6 { font-family: 'Merriweather Sans', sans-serif; color: #000; margin-top: 0; } body { font-family: 'Merriweather Sans', sans-serif; font-weight: 400; font-size: 18px; line-height: 1.8; color: rgba(0, 0, 0, .7); } a { color: #f06292; font-weight: bold; } .logo h1 { margin: 0; } .logo h1 a { color: #000; font-size: 24px; font-weight: 700; text-transform: uppercase; font-family: 'Merriweather Sans', sans-serif; } .navigation { padding: 0; } .navigation li { list-style: none; display: inline-block; ; margin-left: 5px; font-size: 12px; font-weight: 700; text-transform: uppercase; } .navigation li a { color: rgba(0, 0, 0, .6); } .heading-section h2 { color: #000; font-size: 28px; margin-top: 0; line-height: 1.4; font-weight: 700; } .heading-section .subheading { margin-bottom: 20px !important; display: inline-block; font-size: 13px; text-transform: uppercase; letter-spacing: 2px; color: rgba(0, 0, 0, .4); position: relative; } .heading-section .subheading::after { position: absolute; left: 0; right: 0; bottom: -10px; content: ''; width: 100%; height: 2px; background: #f5564e; margin: 0 auto; } .heading-section-white { color: rgba(255, 255, 255, .8); } .heading-section-white h2 { line-height: 1; padding-bottom: 0; } .heading-section-white h2 { color: #fff; } .heading-section-white .subheading { margin-bottom: 0; display: inline-block; font-size: 13px; text-transform: uppercase; letter-spacing: 2px; color: rgba(255, 255, 255, .4); } .call-to-action { padding: 1em 2em; background: #f06292; color: #fff; border-radius: 999px; } </style> </head> <body width="100%" style="margin: 0; padding: 0 !important; mso-line-height-rule: exactly; background-color: #222;"> <center style="width: 100%; background-color: #f1f1f1;"> <div style="display: none; font-size: 1px;max-height: 0px; max-width: 0px; opacity: 0; overflow: hidden; mso-hide: all; font-family: sans-serif;"> &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj;  </div> <div style="max-width: 600px; margin: 0 auto;" class="email-container"> <table align="center" role="presentation" cellspacing="0" cellpadding="0" border="0" width="100%" style="margin: auto;"> <tr> <td valign="top" class="bg_white" style="padding: 1em 2.5em;"> <table role="presentation" border="0" cellpadding="0" cellspacing="0" width="100%"> <tr> <td width="60%" class="logo" style="text-align: left;"> <h1> <a href="https://selfie2anime.com"> Selfie<span class="text_primary">2</span>Anime <span class="text_primary">アニメ</span> </a> </h1> </td> <td width="40%" class="logo" style="text-align: right;"> <a href="https://www.facebook.com/sharer/sharer.php?u=https://selfie2anime.com"> <img width="32" height="32" src="https://selfie2anime.com/email/facebook.png" alt="Share on Facebook"> </a> <a href="https://twitter.com/intent/tweet?url=https://selfie2anime.com&text=What do YOU look like in anime?&hashtags=selfie2anime" target="_blank"> <img width="32" height="32" src="https://selfie2anime.com/email/twitter.png" alt="Share on Twitter"> </a> </td> </tr> </table> </td> </tr> <tr> <td valign="middle" class="bg_white" style="padding: 80px 0;"> <div class="overlay"></div> <table> <tr> <td> <div class="text" style="text-align: center; margin: 0 20px"> Your anime-selfie has been <b>permanently deleted</b>. </div> <div class="text" style="text-align: center; margin: 4em 0"> <a href="https://selfie2anime.com/" class="call-to-action"> GENERATE ANOTHER ONE! </a> </div> <div class="text" style="text-align: center; font-size: 8pt; margin: 0 20px"> You will be automatically redirected to <a href="https://selfie2anime.com/">selfie2anime.com</a>. </div> </td> </tr> </table> </td> </tr> <tr> <td valign="middle" class="bg_primary" style="background-image: url(https://selfie2anime.com/email/wall.jpg); background-size: cover; height: 480px;"> </td> </tr> <tr> <td class="bg_dark email-section" style="text-align:center;"> <div class="heading-section heading-section-white"> <p> Copyright © 2019-2020 by <a href="https://selfie2anime.com">Selfie2Anime.com</a> </p> </div> </td> </tr> </table> </div> </center> </body> </html> """ else: html_body = """ <!DOCTYPE html> <html lang="en" xmlns="http://www.w3.org/1999/xhtml" xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title>Selfie Error | Selfie2Anime</title> <link href="https://fonts.googleapis.com/css?family=Merriweather+Sans:400,400i,700,700i" rel="stylesheet"> <style> * { -ms-text-size-adjust: 100%; -webkit-text-size-adjust: 100%; } html, body { margin: 0 auto !important; padding: 0 !important; height: 100% !important; width: 100% !important; background: #f1f1f1; } div[style*="margin: 16px 0"] { margin: 0 !important; } table, td { mso-table-lspace: 0pt !important; mso-table-rspace: 0pt !important; } table { border-spacing: 0 !important; border-collapse: collapse !important; table-layout: fixed !important; margin: 0 auto !important; } img { -ms-interpolation-mode: bicubic; } a { text-decoration: none; } *[x-apple-data-detectors], .unstyle-auto-detected-links *, .aBn { border-bottom: 0 !important; cursor: default !important; color: inherit !important; text-decoration: none !important; font-size: inherit !important; font-family: inherit !important; font-weight: inherit !important; line-height: inherit !important; } .a6S { display: none !important; opacity: 0.01 !important; } .im { color: inherit !important; } img.g-img+div { display: none !important; } @media only screen and (min-device-width: 320px) and (max-device-width: 374px) { u~div .email-container { min-width: 320px !important; } } @media only screen and (min-device-width: 375px) and (max-device-width: 413px) { u~div .email-container { min-width: 375px !important; } } @media only screen and (min-device-width: 414px) { u~div .email-container { min-width: 414px !important; } } </style> <style> .bg_primary { background: #f06292; } .text_primary { color: #f06292; font-weight: bold; } .try_again { font-size: 2em; } .bg_white { background: #fff; } .bg_dark { background: rgba(0, 0, 0, .8); } .email-section { padding: 2.5em; } h1, h2, h3, h4, h5, h6 { font-family: 'Merriweather Sans', sans-serif; color: #000; margin-top: 0; } body { font-family: 'Merriweather Sans', sans-serif; font-weight: 400; font-size: 18px; line-height: 1.8; color: rgba(0, 0, 0, .7); } a { color: #f06292; font-weight: bold; } .logo h1 { margin: 0; } .logo h1 a { color: #000; font-size: 24px; font-weight: 700; text-transform: uppercase; font-family: 'Merriweather Sans', sans-serif; } .navigation { padding: 0; } .navigation li { list-style: none; display: inline-block; ; margin-left: 5px; font-size: 12px; font-weight: 700; text-transform: uppercase; } .navigation li a { color: rgba(0, 0, 0, .6); } .heading-section h2 { color: #000; font-size: 28px; margin-top: 0; line-height: 1.4; font-weight: 700; } .heading-section .subheading { margin-bottom: 20px !important; display: inline-block; font-size: 13px; text-transform: uppercase; letter-spacing: 2px; color: rgba(0, 0, 0, .4); position: relative; } .heading-section .subheading::after { position: absolute; left: 0; right: 0; bottom: -10px; content: ''; width: 100%; height: 2px; background: #f5564e; margin: 0 auto; } .heading-section-white { color: rgba(255, 255, 255, .8); } .heading-section-white h2 { line-height: 1; padding-bottom: 0; } .heading-section-white h2 { color: #fff; } .heading-section-white .subheading { margin-bottom: 0; display: inline-block; font-size: 13px; text-transform: uppercase; letter-spacing: 2px; color: rgba(255, 255, 255, .4); } .call-to-action { padding: 1em 2em; background: #f06292; color: #fff; border-radius: 999px; } </style> </head> <body width="100%" style="margin: 0; padding: 0 !important; mso-line-height-rule: exactly; background-color: #222;"> <center style="width: 100%; background-color: #f1f1f1;"> <div style="display: none; font-size: 1px;max-height: 0px; max-width: 0px; opacity: 0; overflow: hidden; mso-hide: all; font-family: sans-serif;"> &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj; &zwnj;  </div> <div style="max-width: 600px; margin: 0 auto;" class="email-container"> <table align="center" role="presentation" cellspacing="0" cellpadding="0" border="0" width="100%" style="margin: auto;"> <tr> <td valign="top" class="bg_white" style="padding: 1em 2.5em;"> <table role="presentation" border="0" cellpadding="0" cellspacing="0" width="100%"> <tr> <td width="60%" class="logo" style="text-align: left;"> <h1> <a href="https://selfie2anime.com"> Selfie<span class="text_primary">2</span>Anime <span class="text_primary">アニメ</span> </a> </h1> </td> <td width="40%" class="logo" style="text-align: right;"> <a href="https://www.facebook.com/sharer/sharer.php?u=https://selfie2anime.com"> <img width="32" height="32" src="https://selfie2anime.com/email/facebook.png" alt="Share on Facebook"> </a> <a href="https://twitter.com/intent/tweet?url=https://selfie2anime.com&text=What do YOU look like in anime?&hashtags=selfie2anime" target="_blank"> <img width="32" height="32" src="https://selfie2anime.com/email/twitter.png" alt="Share on Twitter"> </a> </td> </tr> </table> </td> </tr> <tr> <td valign="middle" class="bg_white" style="padding: 80px 0;"> <div class="overlay"></div> <table> <tr> <td> <div class="text" style="text-align: center; margin: 0 20px"> Your verification token was invalid. </div> <div class="text" style="font-size: 10px; text-align: center; margin: 0 50px"> Make sure you clicked the delete image button from the email you received. If that doesn't work, contact us at <a href="mailto:legal@selfie2anime.com">legal@selfie2anime.com</a> to have your data removed another way.</div> </div> <div class="text" style="text-align: center; margin: 4em 0"> <a href="https://selfie2anime.com/" class="call-to-action"> GENERATE ANOTHER ONE! </a> </div> </td> </tr> </table> </td> </tr> <tr> <td valign="middle" class="bg_primary" style="background-image: url(https://selfie2anime.com/email/wall.jpg); background-size: cover; height: 480px;"> </td> </tr> <tr> <td class="bg_dark email-section" style="text-align:center;"> <div class="heading-section heading-section-white"> <p> Copyright © 2019-2020 by <a href="https://selfie2anime.com">Selfie2Anime.com</a> </p> </div> </td> </tr> </table> </div> </center> </body> </html> """ response = { "statusCode": 200, "body": html_body, "headers": { 'Content-Type': 'text/html', } } return response

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Python

cloudmersive_convert_api_client/api/edit_html_api.py

Cloudmersive/Cloudmersive.APIClient.Python.Convert

dba2fe7257229ebdacd266531b3724552c651009

[ "Apache-2.0" ]

3

2018-07-25T23:04:34.000Z

2021-08-10T16:43:10.000Z

cloudmersive_convert_api_client/api/edit_html_api.py

Cloudmersive/Cloudmersive.APIClient.Python.Convert

dba2fe7257229ebdacd266531b3724552c651009

[ "Apache-2.0" ]

3

2020-11-23T10:46:48.000Z

2021-12-30T14:09:34.000Z

cloudmersive_convert_api_client/api/edit_html_api.py

Cloudmersive/Cloudmersive.APIClient.Python.Convert

dba2fe7257229ebdacd266531b3724552c651009

[ "Apache-2.0" ]

2

2020-01-07T09:48:01.000Z

2020-11-23T10:47:00.000Z

# coding: utf-8 """ convertapi Convert API lets you effortlessly convert file formats and types. # noqa: E501 OpenAPI spec version: v1 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 cloudmersive_convert_api_client.api_client import ApiClient class EditHtmlApi(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 edit_html_html_append_header_tag(self, html_tag, **kwargs): # noqa: E501 """Append an HTML tag to the HEAD section of an HTML Document # noqa: E501 Appends an HTML tag to the HEAD section of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_header_tag(html_tag, async_req=True) >>> result = thread.get() :param async_req bool :param str html_tag: The HTML tag to append. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_append_header_tag_with_http_info(html_tag, **kwargs) # noqa: E501 else: (data) = self.edit_html_html_append_header_tag_with_http_info(html_tag, **kwargs) # noqa: E501 return data def edit_html_html_append_header_tag_with_http_info(self, html_tag, **kwargs): # noqa: E501 """Append an HTML tag to the HEAD section of an HTML Document # noqa: E501 Appends an HTML tag to the HEAD section of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_header_tag_with_http_info(html_tag, async_req=True) >>> result = thread.get() :param async_req bool :param str html_tag: The HTML tag to append. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['html_tag', 'input_file', 'input_file_url'] # 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 edit_html_html_append_header_tag" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'html_tag' is set if ('html_tag' not in params or params['html_tag'] is None): raise ValueError("Missing the required parameter `html_tag` when calling `edit_html_html_append_header_tag`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'html_tag' in params: header_params['htmlTag'] = params['html_tag'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/head/append/tag', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_append_heading(self, heading_text, **kwargs): # noqa: E501 """Append a Heading to an HTML Document # noqa: E501 Appends a heading to the end of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_heading(heading_text, async_req=True) >>> result = thread.get() :param async_req bool :param str heading_text: The text content to be used in the header. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param int heading_size: Optional: The heading size number. Default is 1. Accepts values between 1 and 6. :param str css_style: Optional: The CSS style for the heading. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_append_heading_with_http_info(heading_text, **kwargs) # noqa: E501 else: (data) = self.edit_html_html_append_heading_with_http_info(heading_text, **kwargs) # noqa: E501 return data def edit_html_html_append_heading_with_http_info(self, heading_text, **kwargs): # noqa: E501 """Append a Heading to an HTML Document # noqa: E501 Appends a heading to the end of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_heading_with_http_info(heading_text, async_req=True) >>> result = thread.get() :param async_req bool :param str heading_text: The text content to be used in the header. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param int heading_size: Optional: The heading size number. Default is 1. Accepts values between 1 and 6. :param str css_style: Optional: The CSS style for the heading. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['heading_text', 'input_file', 'input_file_url', 'heading_size', 'css_style'] # 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 edit_html_html_append_heading" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'heading_text' is set if ('heading_text' not in params or params['heading_text'] is None): raise ValueError("Missing the required parameter `heading_text` when calling `edit_html_html_append_heading`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'heading_text' in params: header_params['headingText'] = params['heading_text'] # noqa: E501 if 'heading_size' in params: header_params['headingSize'] = params['heading_size'] # noqa: E501 if 'css_style' in params: header_params['cssStyle'] = params['css_style'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/append/heading', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_append_image_from_url(self, image_url, **kwargs): # noqa: E501 """Append an Image to an HTML Document from a URL # noqa: E501 Appends an image to the end of an HTML document using a URL. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_image_from_url(image_url, async_req=True) >>> result = thread.get() :param async_req bool :param str image_url: The URL for the image. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param str css_style: Optional: CSS style for the image. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_append_image_from_url_with_http_info(image_url, **kwargs) # noqa: E501 else: (data) = self.edit_html_html_append_image_from_url_with_http_info(image_url, **kwargs) # noqa: E501 return data def edit_html_html_append_image_from_url_with_http_info(self, image_url, **kwargs): # noqa: E501 """Append an Image to an HTML Document from a URL # noqa: E501 Appends an image to the end of an HTML document using a URL. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_image_from_url_with_http_info(image_url, async_req=True) >>> result = thread.get() :param async_req bool :param str image_url: The URL for the image. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param str css_style: Optional: CSS style for the image. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['image_url', 'input_file', 'input_file_url', 'css_style'] # 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 edit_html_html_append_image_from_url" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'image_url' is set if ('image_url' not in params or params['image_url'] is None): raise ValueError("Missing the required parameter `image_url` when calling `edit_html_html_append_image_from_url`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'image_url' in params: header_params['imageUrl'] = params['image_url'] # noqa: E501 if 'css_style' in params: header_params['cssStyle'] = params['css_style'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/append/image/from-url', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_append_image_inline(self, **kwargs): # noqa: E501 """Append a Base64 Inline Image to an HTML Document # noqa: E501 Appends a base64 inline image to the end of an HTML document from an input file or URL. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_image_inline(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param file image_file: Optional: Image file to be appended as base64 inline image. :param str image_url: Optional: Image URL to be appended as base64 inline image. :param str css_style: Optional: CSS style for the image. :param str image_extension: Optional: The extension (JPG, PNG, GIF, etc.) of the image file. Recommended if uploading an imageFile directly, instead of using imageUrl. If no extension can be determined, will default to JPG. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_append_image_inline_with_http_info(**kwargs) # noqa: E501 else: (data) = self.edit_html_html_append_image_inline_with_http_info(**kwargs) # noqa: E501 return data def edit_html_html_append_image_inline_with_http_info(self, **kwargs): # noqa: E501 """Append a Base64 Inline Image to an HTML Document # noqa: E501 Appends a base64 inline image to the end of an HTML document from an input file or URL. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_image_inline_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param file image_file: Optional: Image file to be appended as base64 inline image. :param str image_url: Optional: Image URL to be appended as base64 inline image. :param str css_style: Optional: CSS style for the image. :param str image_extension: Optional: The extension (JPG, PNG, GIF, etc.) of the image file. Recommended if uploading an imageFile directly, instead of using imageUrl. If no extension can be determined, will default to JPG. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['input_file', 'input_file_url', 'image_file', 'image_url', 'css_style', 'image_extension'] # 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 edit_html_html_append_image_inline" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'image_url' in params: header_params['imageUrl'] = params['image_url'] # noqa: E501 if 'css_style' in params: header_params['cssStyle'] = params['css_style'] # noqa: E501 if 'image_extension' in params: header_params['imageExtension'] = params['image_extension'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 if 'image_file' in params: local_var_files['imageFile'] = params['image_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['multipart/form-data']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/append/image/inline', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_append_paragraph(self, paragraph_text, **kwargs): # noqa: E501 """Append a Paragraph to an HTML Document # noqa: E501 Appends a paragraph to the end of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_paragraph(paragraph_text, async_req=True) >>> result = thread.get() :param async_req bool :param str paragraph_text: The text content to be used in the paragraph. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param str css_style: Optional: The CSS style for the paragraph. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_append_paragraph_with_http_info(paragraph_text, **kwargs) # noqa: E501 else: (data) = self.edit_html_html_append_paragraph_with_http_info(paragraph_text, **kwargs) # noqa: E501 return data def edit_html_html_append_paragraph_with_http_info(self, paragraph_text, **kwargs): # noqa: E501 """Append a Paragraph to an HTML Document # noqa: E501 Appends a paragraph to the end of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_append_paragraph_with_http_info(paragraph_text, async_req=True) >>> result = thread.get() :param async_req bool :param str paragraph_text: The text content to be used in the paragraph. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param str css_style: Optional: The CSS style for the paragraph. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['paragraph_text', 'input_file', 'input_file_url', 'css_style'] # 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 edit_html_html_append_paragraph" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'paragraph_text' is set if ('paragraph_text' not in params or params['paragraph_text'] is None): raise ValueError("Missing the required parameter `paragraph_text` when calling `edit_html_html_append_paragraph`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'paragraph_text' in params: header_params['paragraphText'] = params['paragraph_text'] # noqa: E501 if 'css_style' in params: header_params['cssStyle'] = params['css_style'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/append/paragraph', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_create_blank_document(self, **kwargs): # noqa: E501 """Create a Blank HTML Document # noqa: E501 Returns a blank HTML Document format file. The file is blank, with no contents by default. Use the optional input parameters to add various starting elements. Use additional editing commands such as Append Header, Append Paragraph or Append Image from URL to populate the document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_create_blank_document(async_req=True) >>> result = thread.get() :param async_req bool :param str title: Optional: The title of the HTML document :param str css_url: Optional: A CSS style URL to be added to the document. :param str css_inline: Optional: An inline CSS style to be added to the document. :param str javascript_url: Optional: Javascript URL to be added to the document. :param str javascript_inline: Optional: Inline Javascript to be added to the document. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_create_blank_document_with_http_info(**kwargs) # noqa: E501 else: (data) = self.edit_html_html_create_blank_document_with_http_info(**kwargs) # noqa: E501 return data def edit_html_html_create_blank_document_with_http_info(self, **kwargs): # noqa: E501 """Create a Blank HTML Document # noqa: E501 Returns a blank HTML Document format file. The file is blank, with no contents by default. Use the optional input parameters to add various starting elements. Use additional editing commands such as Append Header, Append Paragraph or Append Image from URL to populate the document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_create_blank_document_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str title: Optional: The title of the HTML document :param str css_url: Optional: A CSS style URL to be added to the document. :param str css_inline: Optional: An inline CSS style to be added to the document. :param str javascript_url: Optional: Javascript URL to be added to the document. :param str javascript_inline: Optional: Inline Javascript to be added to the document. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['title', 'css_url', 'css_inline', 'javascript_url', 'javascript_inline'] # 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 edit_html_html_create_blank_document" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'title' in params: header_params['title'] = params['title'] # noqa: E501 if 'css_url' in params: header_params['cssUrl'] = params['css_url'] # noqa: E501 if 'css_inline' in params: header_params['cssInline'] = params['css_inline'] # noqa: E501 if 'javascript_url' in params: header_params['javascriptUrl'] = params['javascript_url'] # noqa: E501 if 'javascript_inline' in params: header_params['javascriptInline'] = params['javascript_inline'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/create/blank', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_get_language(self, **kwargs): # noqa: E501 """Gets the language for the HTML document # noqa: E501 Retrieves the language code (e.g. \"en\" or \"de\") of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_language(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: HtmlGetLanguageResult If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_get_language_with_http_info(**kwargs) # noqa: E501 else: (data) = self.edit_html_html_get_language_with_http_info(**kwargs) # noqa: E501 return data def edit_html_html_get_language_with_http_info(self, **kwargs): # noqa: E501 """Gets the language for the HTML document # noqa: E501 Retrieves the language code (e.g. \"en\" or \"de\") of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_language_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: HtmlGetLanguageResult If the method is called asynchronously, returns the request thread. """ all_params = ['input_file', 'input_file_url'] # 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 edit_html_html_get_language" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/head/get/language', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='HtmlGetLanguageResult', # 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 edit_html_html_get_links(self, **kwargs): # noqa: E501 """Extract resolved link URLs from HTML File # noqa: E501 Extracts the resolved link URLs, fully-qualified if possible, from an input HTML file. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_links(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param str base_url: Optional: Base URL of the page, such as https://mydomain.com :return: HtmlGetLinksResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_get_links_with_http_info(**kwargs) # noqa: E501 else: (data) = self.edit_html_html_get_links_with_http_info(**kwargs) # noqa: E501 return data def edit_html_html_get_links_with_http_info(self, **kwargs): # noqa: E501 """Extract resolved link URLs from HTML File # noqa: E501 Extracts the resolved link URLs, fully-qualified if possible, from an input HTML file. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_links_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :param str base_url: Optional: Base URL of the page, such as https://mydomain.com :return: HtmlGetLinksResponse If the method is called asynchronously, returns the request thread. """ all_params = ['input_file', 'input_file_url', 'base_url'] # 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 edit_html_html_get_links" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'base_url' in params: header_params['baseUrl'] = params['base_url'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/extract/links', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='HtmlGetLinksResponse', # 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 edit_html_html_get_rel_canonical(self, **kwargs): # noqa: E501 """Gets the rel canonical URL for the HTML document # noqa: E501 Gets the rel canonical URL of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_rel_canonical(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: HtmlGetRelCanonicalUrlResult If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_get_rel_canonical_with_http_info(**kwargs) # noqa: E501 else: (data) = self.edit_html_html_get_rel_canonical_with_http_info(**kwargs) # noqa: E501 return data def edit_html_html_get_rel_canonical_with_http_info(self, **kwargs): # noqa: E501 """Gets the rel canonical URL for the HTML document # noqa: E501 Gets the rel canonical URL of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_rel_canonical_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: HtmlGetRelCanonicalUrlResult If the method is called asynchronously, returns the request thread. """ all_params = ['input_file', 'input_file_url'] # 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 edit_html_html_get_rel_canonical" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/head/get/rel-canonical-url', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='HtmlGetRelCanonicalUrlResult', # 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 edit_html_html_get_sitemap(self, **kwargs): # noqa: E501 """Gets the sitemap URL for the HTML document # noqa: E501 Gets the sitemap link URL of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_sitemap(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: HtmlGetSitemapUrlResult If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_get_sitemap_with_http_info(**kwargs) # noqa: E501 else: (data) = self.edit_html_html_get_sitemap_with_http_info(**kwargs) # noqa: E501 return data def edit_html_html_get_sitemap_with_http_info(self, **kwargs): # noqa: E501 """Gets the sitemap URL for the HTML document # noqa: E501 Gets the sitemap link URL of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_get_sitemap_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: HtmlGetSitemapUrlResult If the method is called asynchronously, returns the request thread. """ all_params = ['input_file', 'input_file_url'] # 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 edit_html_html_get_sitemap" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/head/get/sitemap-url', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='HtmlGetSitemapUrlResult', # 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 edit_html_html_set_language(self, language_code, **kwargs): # noqa: E501 """Sets the language for the HTML document # noqa: E501 Sets the language code of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_set_language(language_code, async_req=True) >>> result = thread.get() :param async_req bool :param str language_code: The HTML langauge code to set. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_set_language_with_http_info(language_code, **kwargs) # noqa: E501 else: (data) = self.edit_html_html_set_language_with_http_info(language_code, **kwargs) # noqa: E501 return data def edit_html_html_set_language_with_http_info(self, language_code, **kwargs): # noqa: E501 """Sets the language for the HTML document # noqa: E501 Sets the language code of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_set_language_with_http_info(language_code, async_req=True) >>> result = thread.get() :param async_req bool :param str language_code: The HTML langauge code to set. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['language_code', 'input_file', 'input_file_url'] # 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 edit_html_html_set_language" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'language_code' is set if ('language_code' not in params or params['language_code'] is None): raise ValueError("Missing the required parameter `language_code` when calling `edit_html_html_set_language`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'language_code' in params: header_params['languageCode'] = params['language_code'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/head/set/language', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_set_rel_canonical(self, canonical_url, **kwargs): # noqa: E501 """Sets the rel canonical URL for the HTML document # noqa: E501 Sets the rel canonical URL of an HTML document. This is useful for telling search engines and other indexers which pages are duplicates of eachother; any pages with the rel=canonical tag will be treated as duplicates of the canonical URL. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_set_rel_canonical(canonical_url, async_req=True) >>> result = thread.get() :param async_req bool :param str canonical_url: The HTML canonical URL to set. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_set_rel_canonical_with_http_info(canonical_url, **kwargs) # noqa: E501 else: (data) = self.edit_html_html_set_rel_canonical_with_http_info(canonical_url, **kwargs) # noqa: E501 return data def edit_html_html_set_rel_canonical_with_http_info(self, canonical_url, **kwargs): # noqa: E501 """Sets the rel canonical URL for the HTML document # noqa: E501 Sets the rel canonical URL of an HTML document. This is useful for telling search engines and other indexers which pages are duplicates of eachother; any pages with the rel=canonical tag will be treated as duplicates of the canonical URL. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_set_rel_canonical_with_http_info(canonical_url, async_req=True) >>> result = thread.get() :param async_req bool :param str canonical_url: The HTML canonical URL to set. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['canonical_url', 'input_file', 'input_file_url'] # 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 edit_html_html_set_rel_canonical" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'canonical_url' is set if ('canonical_url' not in params or params['canonical_url'] is None): raise ValueError("Missing the required parameter `canonical_url` when calling `edit_html_html_set_rel_canonical`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'canonical_url' in params: header_params['canonicalUrl'] = params['canonical_url'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/head/set/rel-canonical-url', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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 edit_html_html_set_sitemap_url(self, sitemap_url, **kwargs): # noqa: E501 """Sets the sitemap URL for the HTML document # noqa: E501 Sets the sitemap URL of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_set_sitemap_url(sitemap_url, async_req=True) >>> result = thread.get() :param async_req bool :param str sitemap_url: The HTML sitemap URL to set. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_html_html_set_sitemap_url_with_http_info(sitemap_url, **kwargs) # noqa: E501 else: (data) = self.edit_html_html_set_sitemap_url_with_http_info(sitemap_url, **kwargs) # noqa: E501 return data def edit_html_html_set_sitemap_url_with_http_info(self, sitemap_url, **kwargs): # noqa: E501 """Sets the sitemap URL for the HTML document # noqa: E501 Sets the sitemap URL of an HTML document. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_html_html_set_sitemap_url_with_http_info(sitemap_url, async_req=True) >>> result = thread.get() :param async_req bool :param str sitemap_url: The HTML sitemap URL to set. (required) :param file input_file: Optional: Input file to perform the operation on. :param str input_file_url: Optional: URL of a file to operate on as input. :return: str If the method is called asynchronously, returns the request thread. """ all_params = ['sitemap_url', 'input_file', 'input_file_url'] # 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 edit_html_html_set_sitemap_url" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'sitemap_url' is set if ('sitemap_url' not in params or params['sitemap_url'] is None): raise ValueError("Missing the required parameter `sitemap_url` when calling `edit_html_html_set_sitemap_url`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'input_file_url' in params: header_params['inputFileUrl'] = params['input_file_url'] # noqa: E501 if 'sitemap_url' in params: header_params['sitemapUrl'] = params['sitemap_url'] # noqa: E501 form_params = [] local_var_files = {} if 'input_file' in params: local_var_files['inputFile'] = params['input_file'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/json', 'application/xml', 'text/xml']) # noqa: E501 # Authentication setting auth_settings = ['Apikey'] # noqa: E501 return self.api_client.call_api( '/convert/edit/html/head/set/sitemap-url', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', # noqa: E501 auth_settings=auth_settings, async_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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61,555

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44.702251

0.821637

0.382

0

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0

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false

0

0.005457

0

0.096862

0

null

0

1

0

1

0

null

0

8

a0fcb9c661abce26b7869dfa7de6b88f032eff9d

127

py

Python

ravegen/generateAp.py

mytab0r/RaveGen-Telegram-bot-generator

4b42ae622554c4b2442b35b1181f8f09886215d2

[ "MIT" ]

1

2020-06-13T17:16:57.000Z

ravegen/generateAp.py

NICK-FTW/RaveGen-Telegram-bot-generator

269b36333a31cadb697f3c1250c6bf118cdc7fcc

[ "MIT" ]

5

2019-04-03T19:10:54.000Z

2019-06-14T17:21:14.000Z

ravegen/generateAp.py

NICK-FTW/RaveGen-Telegram-bot-generator

269b36333a31cadb697f3c1250c6bf118cdc7fcc

[ "MIT" ]

2

2019-03-19T19:45:05.000Z

2021-02-07T18:04:33.000Z

import ConsoleEngine.generateAutoCompletition as generateAutoCompletition generateAutoCompletition.generateAutoCompletition()

31.75

73

0.92126

7

127

16.714286

0.571429

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0.047244

127

3

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1

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true

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1

0

null

0

1

0

1

0

7

9d0648ef5855f2000c98a0fb0edac445c5e5a2a2

104,677

py

Python

models/H_Net.py

zxg3017/H-Net

30c3c08292f4fccf76a63341392488b8baee3d3d

[ "MIT" ]

null

models/H_Net.py

zxg3017/H-Net

30c3c08292f4fccf76a63341392488b8baee3d3d

[ "MIT" ]

null

models/H_Net.py

zxg3017/H-Net

30c3c08292f4fccf76a63341392488b8baee3d3d

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F from torchvision import models from torch.autograd import Variable from functools import partial from segmentation_models_pytorch import create_model import segmentation_models_pytorch as smp nonlinearity = partial(F.relu, inplace=True) BN_EPS = 1e-4 #1e-4 #1e-5 class H_Net_V1(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(H_Net_V1, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(3, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(3, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # ce_net encoder part filters = [64, 128, 256, 512] resnet = models.resnet34(pretrained=True) self.firstconv = resnet.conv1 self.firstbn = resnet.bn1 self.firstrelu = resnet.relu self.firstmaxpool = resnet.maxpool self.encoder1 = resnet.layer1 self.encoder2 = resnet.layer2 self.encoder3 = resnet.layer3 self.encoder4 = resnet.layer4 # the center of M_Net self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the center of ce_Net self.dblock = DACblock(512) # 空洞卷积 self.spp = SPPblock(512) # 池化后再上采样 # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_up0 = nn.ConvTranspose2d(512, 512, 2, stride=2) self.e4_up = nn.ConvTranspose2d(516, 256, 2, stride=2) self.e2_up = nn.ConvTranspose2d(128, 128, 2, stride=2) self.rc_up1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_up2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_up3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_up4 = nn.ConvTranspose2d(128, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_Ce = CACblock_with_inception(512) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(64, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(32, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.d3_conv = nn.Conv2d(384, 128, kernel_size=1, padding=0, stride=1, bias=True) self.d2_conv = nn.Conv2d(192, 64, kernel_size=1, padding=0, stride=1, bias=True) self.d1_conv = nn.Conv2d(96, 64, kernel_size=1, padding=0, stride=1, bias=True) # the decoder of ce_net self.decoder4 = DecoderBlock(516, filters[2]) self.decoder3 = DecoderBlock(filters[2], filters[1]) self.decoder2 = DecoderBlock(filters[1], filters[0]) self.decoder1 = DecoderBlock(filters[0], filters[0]) # 解码部分 self.finaldeconv1 = nn.ConvTranspose2d(filters[0], 32, 4, 2, 1) # 逆卷积 self.finalrelu1 = nonlinearity self.finalconv2 = nn.Conv2d(32, 32, 3, padding=1) self.finalrelu2 = nonlinearity self.finalconv3 = nn.Conv2d(32, out_ch, 3, padding=1) def forward(self, x): # M_Net Encoder Part l_x = x _, _, img_shape, _ = l_x.size() x_2 = F.upsample(l_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(l_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(l_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out1 = self.down1(l_x) # conv1 [32,512,512] out1 = torch.cat([self.conv2(x_2), out1], dim=1) conv2, out2 = self.down2(out1) # conv2 [64,256,256] out2 = torch.cat([self.conv3(x_3), out2], dim=1) conv3, out3 = self.down3(out2) # conv3 [128,128,128] out3 = torch.cat([self.conv4(x_4), out3], dim=1) conv4, out4 = self.down4(out3) # conv4 [256,64,64] # cet_out = self.center(out) # CAC_out = self.CAC(out4) # CE_Net Encoder part rx = x e0 = self.firstconv(rx) #[64,256,256] e0 = self.firstbn(e0) #[64,256,256] e0 = self.firstrelu(e0) #[64,256,256] pe0 = self.firstmaxpool(e0) #[64,128,128] e1 = self.encoder1(pe0) #[64,128,128] e2 = self.encoder2(e1) #[128,64,64] e3 = self.encoder3(e2) #[256,32,32] e4 = self.encoder4(e3) #[512,16,16] # Center of CE_Net # e4 = self.CAC_Ce(e4) e4 = self.dblock(e4) e4 = self.spp(e4) # the center part e4_up = self.e4_up(e4) CAC_out = self.CAC(out4) CAC_out = e4_up + CAC_out cet_out = self.CAC_conv4(CAC_out) r1_cat = torch.cat([e3, cet_out], dim=1) up_out = self.rc_up1(r1_cat) up5 = self.up5(up_out) r2_cat = torch.cat([e2, up5], dim=1) up_out1 = self.rc_up2(r2_cat) up6 = self.up6(up_out1) r3_cat = torch.cat([e1, up6], dim=1) up_out2 = self.rc_up3(r3_cat) up7 = self.up7(up_out2) r4_cat = torch.cat([e0, up7], dim=1) up_out3 = self.rc_up4(r4_cat) up8 = self.up8(up_out3) M_Net_out = self.side_8(up8) # e4 = self.spp(e4) # Encoder of CE_Net d4 = self.decoder4(e4) + out4 # [256,32,32] d3 = self.decoder3(d4) + self.d3_conv(out3) # [128,64,64] d2 = self.decoder2(d3) + self.d2_conv(out2) # [64,128,128] d1 = self.decoder1(d2) + self.d1_conv(out1) # [64,256,256] out = self.finaldeconv1(d1) out = self.finalrelu1(out) out = self.finalconv2(out) out = self.finalrelu2(out) cet_out = self.finalconv3(out) ave_out = (cet_out + M_Net_out) /2 return F.sigmoid(cet_out),F.sigmoid(M_Net_out),F.sigmoid(ave_out),cet_out,M_Net_out,ave_out class H_Net_V2(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(H_Net_V2, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(3, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(3, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # ce_net encoder part filters = [64, 128, 256, 512] resnet = models.resnet34(pretrained=True) self.firstconv = resnet.conv1 self.firstbn = resnet.bn1 self.firstrelu = resnet.relu self.firstmaxpool = resnet.maxpool self.encoder1 = resnet.layer1 self.encoder2 = resnet.layer2 self.encoder3 = resnet.layer3 self.encoder4 = resnet.layer4 # the center of M_Net self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the center of ce_Net self.dblock = DACblock(512) # 空洞卷积 self.spp = SPPblock(512) # 池化后再上采样 # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_up0 = nn.ConvTranspose2d(512, 512, 2, stride=2) self.e4_up = nn.ConvTranspose2d(516, 256, 2, stride=2) self.e2_up = nn.ConvTranspose2d(128, 128, 2, stride=2) self.rc_up1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_up2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_up3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_up4 = nn.ConvTranspose2d(128, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_Ce = CACblock_with_inception(512) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(64, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(32, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.d3_conv = nn.Conv2d(384, 128, kernel_size=1, padding=0, stride=1, bias=True) self.d2_conv = nn.Conv2d(192, 64, kernel_size=1, padding=0, stride=1, bias=True) self.d1_conv = nn.Conv2d(96, 64, kernel_size=1, padding=0, stride=1, bias=True) # the decoder of ce_net self.decoder4 = DecoderBlock(516, filters[2]) self.decoder3 = DecoderBlock(filters[2], filters[1]) self.decoder2 = DecoderBlock(filters[1], filters[0]) self.decoder1 = DecoderBlock(filters[0], filters[0]) # 解码部分 self.finaldeconv1 = nn.ConvTranspose2d(filters[0], 32, 4, 2, 1) # 逆卷积 self.finalrelu1 = nonlinearity self.finalconv2 = nn.Conv2d(32, 32, 3, padding=1) self.finalrelu2 = nonlinearity self.finalconv3 = nn.Conv2d(32, out_ch, 3, padding=1) def forward(self, x): # M_Net Encoder Part l_x = x _, _, img_shape, _ = l_x.size() x_2 = F.upsample(l_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(l_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(l_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out1 = self.down1(l_x) # conv1 [32,512,512] out1 = torch.cat([self.conv2(x_2), out1], dim=1) conv2, out2 = self.down2(out1) # conv2 [64,256,256] out2 = torch.cat([self.conv3(x_3), out2], dim=1) conv3, out3 = self.down3(out2) # conv3 [128,128,128] out3 = torch.cat([self.conv4(x_4), out3], dim=1) conv4, out4 = self.down4(out3) # conv4 [256,64,64] # cet_out = self.center(out) # CAC_out = self.CAC(out4) # CE_Net Encoder part rx = x e0 = self.firstconv(rx) #[64,256,256] e0 = self.firstbn(e0) #[64,256,256] e0 = self.firstrelu(e0) #[64,256,256] pe0 = self.firstmaxpool(e0) #[64,128,128] e1 = self.encoder1(pe0) #[64,128,128] e2 = self.encoder2(e1) #[128,64,64] e3 = self.encoder3(e2) #[256,32,32] e4 = self.encoder4(e3) #[512,16,16] # Center of CE_Net e4 = self.CAC_Ce(e4) # e4 = self.dblock(e4) e4 = self.spp(e4) # the center part e4_up = self.e4_up(e4) CAC_out = self.CAC(out4) CAC_out = e4_up + CAC_out cet_out = self.CAC_conv4(CAC_out) r1_cat = torch.cat([e3, cet_out], dim=1) up_out = self.rc_up1(r1_cat) up5 = self.up5(up_out) r2_cat = torch.cat([e2, up5], dim=1) up_out1 = self.rc_up2(r2_cat) up6 = self.up6(up_out1) r3_cat = torch.cat([e1, up6], dim=1) up_out2 = self.rc_up3(r3_cat) up7 = self.up7(up_out2) r4_cat = torch.cat([e0, up7], dim=1) up_out3 = self.rc_up4(r4_cat) up8 = self.up8(up_out3) M_Net_out = self.side_8(up8) # e4 = self.spp(e4) # Encoder of CE_Net d4 = self.decoder4(e4) + out4 # [256,32,32] d3 = self.decoder3(d4) + self.d3_conv(out3) # [128,64,64] d2 = self.decoder2(d3) + self.d2_conv(out2) # [64,128,128] d1 = self.decoder1(d2) + self.d1_conv(out1) # [64,256,256] out = self.finaldeconv1(d1) out = self.finalrelu1(out) out = self.finalconv2(out) out = self.finalrelu2(out) cet_out = self.finalconv3(out) ave_out = (cet_out + M_Net_out) /2 return F.sigmoid(cet_out),F.sigmoid(M_Net_out),F.sigmoid(ave_out),cet_out,M_Net_out,ave_out class H_Net_134(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(H_Net_134, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(3, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(3, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # ce_net encoder part filters = [64, 128, 256, 512] resnet = models.resnet34(pretrained=True) self.firstconv = resnet.conv1 self.firstbn = resnet.bn1 self.firstrelu = resnet.relu self.firstmaxpool = resnet.maxpool self.encoder1 = resnet.layer1 self.encoder2 = resnet.layer2 self.encoder3 = resnet.layer3 self.encoder4 = resnet.layer4 # the center of M_Net self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the center of ce_Net self.dblock = DACblock134(512) # 空洞卷积 self.spp = SPPblock(512) # 池化后再上采样 # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_up0 = nn.ConvTranspose2d(512, 512, 2, stride=2) self.e4_up = nn.ConvTranspose2d(516, 256, 2, stride=2) self.e2_up = nn.ConvTranspose2d(128, 128, 2, stride=2) self.rc_up1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_up2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_up3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_up4 = nn.ConvTranspose2d(128, 32, 2, stride=2) # the CAC block self.CAC = DACblock134(256) self.CAC_Ce = DACblock134(512) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(64, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(32, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.d3_conv = nn.Conv2d(384, 128, kernel_size=1, padding=0, stride=1, bias=True) self.d2_conv = nn.Conv2d(192, 64, kernel_size=1, padding=0, stride=1, bias=True) self.d1_conv = nn.Conv2d(96, 64, kernel_size=1, padding=0, stride=1, bias=True) # the decoder of ce_net self.decoder4 = DecoderBlock(516, filters[2]) self.decoder3 = DecoderBlock(filters[2], filters[1]) self.decoder2 = DecoderBlock(filters[1], filters[0]) self.decoder1 = DecoderBlock(filters[0], filters[0]) # 解码部分 self.finaldeconv1 = nn.ConvTranspose2d(filters[0], 32, 4, 2, 1) # 逆卷积 self.finalrelu1 = nonlinearity self.finalconv2 = nn.Conv2d(32, 32, 3, padding=1) self.finalrelu2 = nonlinearity self.finalconv3 = nn.Conv2d(32, out_ch, 3, padding=1) def forward(self, x): # M_Net Encoder Part l_x = x _, _, img_shape, _ = l_x.size() x_2 = F.upsample(l_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(l_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(l_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out1 = self.down1(l_x) # conv1 [32,512,512] out1 = torch.cat([self.conv2(x_2), out1], dim=1) conv2, out2 = self.down2(out1) # conv2 [64,256,256] out2 = torch.cat([self.conv3(x_3), out2], dim=1) conv3, out3 = self.down3(out2) # conv3 [128,128,128] out3 = torch.cat([self.conv4(x_4), out3], dim=1) conv4, out4 = self.down4(out3) # conv4 [256,64,64] # cet_out = self.center(out) # CAC_out = self.CAC(out4) # CE_Net Encoder part rx = x e0 = self.firstconv(rx) #[64,256,256] e0 = self.firstbn(e0) #[64,256,256] e0 = self.firstrelu(e0) #[64,256,256] pe0 = self.firstmaxpool(e0) #[64,128,128] e1 = self.encoder1(pe0) #[64,128,128] e2 = self.encoder2(e1) #[128,64,64] e3 = self.encoder3(e2) #[256,32,32] e4 = self.encoder4(e3) #[512,16,16] # Center of CE_Net e4 = self.CAC_Ce(e4) # e4 = self.dblock(e4) e4 = self.spp(e4) # the center part e4_up = self.e4_up(e4) CAC_out = self.CAC(out4) CAC_out = e4_up + CAC_out cet_out = self.CAC_conv4(CAC_out) r1_cat = torch.cat([e3, cet_out], dim=1) up_out = self.rc_up1(r1_cat) up5 = self.up5(up_out) r2_cat = torch.cat([e2, up5], dim=1) up_out1 = self.rc_up2(r2_cat) up6 = self.up6(up_out1) r3_cat = torch.cat([e1, up6], dim=1) up_out2 = self.rc_up3(r3_cat) up7 = self.up7(up_out2) r4_cat = torch.cat([e0, up7], dim=1) up_out3 = self.rc_up4(r4_cat) up8 = self.up8(up_out3) M_Net_out = self.side_8(up8) # e4 = self.spp(e4) # Encoder of CE_Net d4 = self.decoder4(e4) + out4 # [256,32,32] d3 = self.decoder3(d4) + self.d3_conv(out3) # [128,64,64] d2 = self.decoder2(d3) + self.d2_conv(out2) # [64,128,128] d1 = self.decoder1(d2) + self.d1_conv(out1) # [64,256,256] out = self.finaldeconv1(d1) out = self.finalrelu1(out) out = self.finalconv2(out) out = self.finalrelu2(out) cet_out = self.finalconv3(out) ave_out = (cet_out + M_Net_out) /2 return F.sigmoid(cet_out),F.sigmoid(M_Net_out),F.sigmoid(ave_out),cet_out,M_Net_out,ave_out class H_Net_137(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(H_Net_137, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(3, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(3, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # ce_net encoder part filters = [64, 128, 256, 512] resnet = models.resnet34(pretrained=True) self.firstconv = resnet.conv1 self.firstbn = resnet.bn1 self.firstrelu = resnet.relu self.firstmaxpool = resnet.maxpool self.encoder1 = resnet.layer1 self.encoder2 = resnet.layer2 self.encoder3 = resnet.layer3 self.encoder4 = resnet.layer4 # the center of M_Net self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the center of ce_Net self.dblock = DACblock137(512) # 空洞卷积 self.spp = SPPblock(512) # 池化后再上采样 # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_up0 = nn.ConvTranspose2d(512, 512, 2, stride=2) self.e4_up = nn.ConvTranspose2d(516, 256, 2, stride=2) self.e2_up = nn.ConvTranspose2d(128, 128, 2, stride=2) self.rc_up1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_up2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_up3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_up4 = nn.ConvTranspose2d(128, 32, 2, stride=2) # the CAC block self.CAC = DACblock137(256) self.CAC_Ce = DACblock137(512) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(64, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(32, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.d3_conv = nn.Conv2d(384, 128, kernel_size=1, padding=0, stride=1, bias=True) self.d2_conv = nn.Conv2d(192, 64, kernel_size=1, padding=0, stride=1, bias=True) self.d1_conv = nn.Conv2d(96, 64, kernel_size=1, padding=0, stride=1, bias=True) # the decoder of ce_net self.decoder4 = DecoderBlock(516, filters[2]) self.decoder3 = DecoderBlock(filters[2], filters[1]) self.decoder2 = DecoderBlock(filters[1], filters[0]) self.decoder1 = DecoderBlock(filters[0], filters[0]) # 解码部分 self.finaldeconv1 = nn.ConvTranspose2d(filters[0], 32, 4, 2, 1) # 逆卷积 self.finalrelu1 = nonlinearity self.finalconv2 = nn.Conv2d(32, 32, 3, padding=1) self.finalrelu2 = nonlinearity self.finalconv3 = nn.Conv2d(32, out_ch, 3, padding=1) def forward(self, x): # M_Net Encoder Part l_x = x _, _, img_shape, _ = l_x.size() x_2 = F.upsample(l_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(l_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(l_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out1 = self.down1(l_x) # conv1 [32,512,512] out1 = torch.cat([self.conv2(x_2), out1], dim=1) conv2, out2 = self.down2(out1) # conv2 [64,256,256] out2 = torch.cat([self.conv3(x_3), out2], dim=1) conv3, out3 = self.down3(out2) # conv3 [128,128,128] out3 = torch.cat([self.conv4(x_4), out3], dim=1) conv4, out4 = self.down4(out3) # conv4 [256,64,64] # cet_out = self.center(out) # CAC_out = self.CAC(out4) # CE_Net Encoder part rx = x e0 = self.firstconv(rx) #[64,256,256] e0 = self.firstbn(e0) #[64,256,256] e0 = self.firstrelu(e0) #[64,256,256] pe0 = self.firstmaxpool(e0) #[64,128,128] e1 = self.encoder1(pe0) #[64,128,128] e2 = self.encoder2(e1) #[128,64,64] e3 = self.encoder3(e2) #[256,32,32] e4 = self.encoder4(e3) #[512,16,16] # Center of CE_Net e4 = self.CAC_Ce(e4) # e4 = self.dblock(e4) e4 = self.spp(e4) # the center part e4_up = self.e4_up(e4) CAC_out = self.CAC(out4) CAC_out = e4_up + CAC_out cet_out = self.CAC_conv4(CAC_out) r1_cat = torch.cat([e3, cet_out], dim=1) up_out = self.rc_up1(r1_cat) up5 = self.up5(up_out) r2_cat = torch.cat([e2, up5], dim=1) up_out1 = self.rc_up2(r2_cat) up6 = self.up6(up_out1) r3_cat = torch.cat([e1, up6], dim=1) up_out2 = self.rc_up3(r3_cat) up7 = self.up7(up_out2) r4_cat = torch.cat([e0, up7], dim=1) up_out3 = self.rc_up4(r4_cat) up8 = self.up8(up_out3) M_Net_out = self.side_8(up8) # e4 = self.spp(e4) # Encoder of CE_Net d4 = self.decoder4(e4) + out4 # [256,32,32] d3 = self.decoder3(d4) + self.d3_conv(out3) # [128,64,64] d2 = self.decoder2(d3) + self.d2_conv(out2) # [64,128,128] d1 = self.decoder1(d2) + self.d1_conv(out1) # [64,256,256] out = self.finaldeconv1(d1) out = self.finalrelu1(out) out = self.finalconv2(out) out = self.finalrelu2(out) cet_out = self.finalconv3(out) ave_out = (cet_out + M_Net_out) /2 return F.sigmoid(cet_out),F.sigmoid(M_Net_out),F.sigmoid(ave_out),cet_out,M_Net_out,ave_out class H_Net_139(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(H_Net_139, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(3, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(3, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # ce_net encoder part filters = [64, 128, 256, 512] resnet = models.resnet34(pretrained=True) self.firstconv = resnet.conv1 self.firstbn = resnet.bn1 self.firstrelu = resnet.relu self.firstmaxpool = resnet.maxpool self.encoder1 = resnet.layer1 self.encoder2 = resnet.layer2 self.encoder3 = resnet.layer3 self.encoder4 = resnet.layer4 # the center of M_Net self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the center of ce_Net self.dblock = DACblock139(512) # 空洞卷积 self.spp = SPPblock(512) # 池化后再上采样 # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_up0 = nn.ConvTranspose2d(512, 512, 2, stride=2) self.e4_up = nn.ConvTranspose2d(516, 256, 2, stride=2) self.e2_up = nn.ConvTranspose2d(128, 128, 2, stride=2) self.rc_up1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_up2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_up3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_up4 = nn.ConvTranspose2d(128, 32, 2, stride=2) # the CAC block self.CAC = DACblock139(256) self.CAC_Ce = DACblock139(512) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(64, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(32, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.d3_conv = nn.Conv2d(384, 128, kernel_size=1, padding=0, stride=1, bias=True) self.d2_conv = nn.Conv2d(192, 64, kernel_size=1, padding=0, stride=1, bias=True) self.d1_conv = nn.Conv2d(96, 64, kernel_size=1, padding=0, stride=1, bias=True) # the decoder of ce_net self.decoder4 = DecoderBlock(516, filters[2]) self.decoder3 = DecoderBlock(filters[2], filters[1]) self.decoder2 = DecoderBlock(filters[1], filters[0]) self.decoder1 = DecoderBlock(filters[0], filters[0]) # 解码部分 self.finaldeconv1 = nn.ConvTranspose2d(filters[0], 32, 4, 2, 1) # 逆卷积 self.finalrelu1 = nonlinearity self.finalconv2 = nn.Conv2d(32, 32, 3, padding=1) self.finalrelu2 = nonlinearity self.finalconv3 = nn.Conv2d(32, out_ch, 3, padding=1) def forward(self, x): # M_Net Encoder Part l_x = x _, _, img_shape, _ = l_x.size() x_2 = F.upsample(l_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(l_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(l_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out1 = self.down1(l_x) # conv1 [32,512,512] out1 = torch.cat([self.conv2(x_2), out1], dim=1) conv2, out2 = self.down2(out1) # conv2 [64,256,256] out2 = torch.cat([self.conv3(x_3), out2], dim=1) conv3, out3 = self.down3(out2) # conv3 [128,128,128] out3 = torch.cat([self.conv4(x_4), out3], dim=1) conv4, out4 = self.down4(out3) # conv4 [256,64,64] # cet_out = self.center(out) # CAC_out = self.CAC(out4) # CE_Net Encoder part rx = x e0 = self.firstconv(rx) #[64,256,256] e0 = self.firstbn(e0) #[64,256,256] e0 = self.firstrelu(e0) #[64,256,256] pe0 = self.firstmaxpool(e0) #[64,128,128] e1 = self.encoder1(pe0) #[64,128,128] e2 = self.encoder2(e1) #[128,64,64] e3 = self.encoder3(e2) #[256,32,32] e4 = self.encoder4(e3) #[512,16,16] # Center of CE_Net e4 = self.CAC_Ce(e4) # e4 = self.dblock(e4) e4 = self.spp(e4) # the center part e4_up = self.e4_up(e4) CAC_out = self.CAC(out4) CAC_out = e4_up + CAC_out cet_out = self.CAC_conv4(CAC_out) r1_cat = torch.cat([e3, cet_out], dim=1) up_out = self.rc_up1(r1_cat) up5 = self.up5(up_out) r2_cat = torch.cat([e2, up5], dim=1) up_out1 = self.rc_up2(r2_cat) up6 = self.up6(up_out1) r3_cat = torch.cat([e1, up6], dim=1) up_out2 = self.rc_up3(r3_cat) up7 = self.up7(up_out2) r4_cat = torch.cat([e0, up7], dim=1) up_out3 = self.rc_up4(r4_cat) up8 = self.up8(up_out3) M_Net_out = self.side_8(up8) # e4 = self.spp(e4) # Encoder of CE_Net d4 = self.decoder4(e4) + out4 # [256,32,32] d3 = self.decoder3(d4) + self.d3_conv(out3) # [128,64,64] d2 = self.decoder2(d3) + self.d2_conv(out2) # [64,128,128] d1 = self.decoder1(d2) + self.d1_conv(out1) # [64,256,256] out = self.finaldeconv1(d1) out = self.finalrelu1(out) out = self.finalconv2(out) out = self.finalrelu2(out) cet_out = self.finalconv3(out) ave_out = (cet_out + M_Net_out) /2 return F.sigmoid(cet_out),F.sigmoid(M_Net_out),F.sigmoid(ave_out),cet_out,M_Net_out,ave_out class H_Net(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(H_Net, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(3, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(3, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # ce_net encoder part filters = [64, 128, 256, 512] resnet = models.resnet34(pretrained=True) self.firstconv = resnet.conv1 self.firstbn = resnet.bn1 self.firstrelu = resnet.relu self.firstmaxpool = resnet.maxpool self.encoder1 = resnet.layer1 self.encoder2 = resnet.layer2 self.encoder3 = resnet.layer3 self.encoder4 = resnet.layer4 # the center of M_Net self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the center of ce_Net self.dblock = DACblock(512) # 空洞卷积 self.spp = SPPblock(512) # 池化后再上采样 # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_up0 = nn.ConvTranspose2d(512, 512, 2, stride=2) self.e4_up = nn.ConvTranspose2d(512, 256, 2, stride=2) self.e2_up = nn.ConvTranspose2d(128, 128, 2, stride=2) self.rc_up1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_up2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_up3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_up4 = nn.ConvTranspose2d(128, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_Ce = CACblock_with_inception(512) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(64, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(32, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.d3_conv = nn.Conv2d(384, 128, kernel_size=1, padding=0, stride=1, bias=True) self.d2_conv = nn.Conv2d(192, 64, kernel_size=1, padding=0, stride=1, bias=True) self.d1_conv = nn.Conv2d(96, 64, kernel_size=1, padding=0, stride=1, bias=True) # the decoder of ce_net self.decoder4 = DecoderBlock(512, filters[2]) self.decoder3 = DecoderBlock(filters[2], filters[1]) self.decoder2 = DecoderBlock(filters[1], filters[0]) self.decoder1 = DecoderBlock(filters[0], filters[0]) # 解码部分 self.finaldeconv1 = nn.ConvTranspose2d(filters[0], 32, 4, 2, 1) # 逆卷积 self.finalrelu1 = nonlinearity self.finalconv2 = nn.Conv2d(32, 32, 3, padding=1) self.finalrelu2 = nonlinearity self.finalconv3 = nn.Conv2d(32, out_ch, 3, padding=1) def forward(self, x): # M_Net Encoder Part l_x = x _, _, img_shape, _ = l_x.size() x_2 = F.upsample(l_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(l_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(l_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out1 = self.down1(l_x) # conv1 [32,512,512] out1 = torch.cat([self.conv2(x_2), out1], dim=1) conv2, out2 = self.down2(out1) # conv2 [64,256,256] out2 = torch.cat([self.conv3(x_3), out2], dim=1) conv3, out3 = self.down3(out2) # conv3 [128,128,128] out3 = torch.cat([self.conv4(x_4), out3], dim=1) conv4, out4 = self.down4(out3) # conv4 [256,64,64] # cet_out = self.center(out) # CE_Net Encoder part rx = x e0 = self.firstconv(rx) #[64,256,256] e0 = self.firstbn(e0) #[64,256,256] e0 = self.firstrelu(e0) #[64,256,256] pe0 = self.firstmaxpool(e0) #[64,128,128] e1 = self.encoder1(pe0) #[64,128,128] e2 = self.encoder2(e1) #[128,64,64] e3 = self.encoder3(e2) #[256,32,32] e4 = self.encoder4(e3) #[512,16,16] # Center of CE_Net e4 = self.CAC_Ce(e4) # the center part e4_up = self.e4_up(e4) CAC_out = self.CAC(out4) CAC_out = e4_up + CAC_out cet_out = self.CAC_conv4(CAC_out) r1_cat = torch.cat([e3, cet_out], dim=1) up_out = self.rc_up1(r1_cat) up5 = self.up5(up_out) r2_cat = torch.cat([e2, up5], dim=1) up_out1 = self.rc_up2(r2_cat) up6 = self.up6(up_out1) r3_cat = torch.cat([e1, up6], dim=1) up_out2 = self.rc_up3(r3_cat) up7 = self.up7(up_out2) r4_cat = torch.cat([e0, up7], dim=1) up_out3 = self.rc_up4(r4_cat) up8 = self.up8(up_out3) M_Net_out = self.side_8(up8) # e4 = self.spp(e4) # Encoder of CE_Net d4 = self.decoder4(e4) + out4 # [256,32,32] d3 = self.decoder3(d4) + self.d3_conv(out3) # [128,64,64] d2 = self.decoder2(d3) + self.d2_conv(out2) # [64,128,128] d1 = self.decoder1(d2) + self.d1_conv(out1) # [64,256,256] out = self.finaldeconv1(d1) out = self.finalrelu1(out) out = self.finalconv2(out) out = self.finalrelu2(out) cet_out = self.finalconv3(out) ave_out = (cet_out + M_Net_out) /2 return F.sigmoid(cet_out),F.sigmoid(M_Net_out),F.sigmoid(ave_out),cet_out,M_Net_out,ave_out class H_Net_ori(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(H_Net_ori, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(3, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(3, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # ce_net encoder part filters = [64, 128, 256, 512] resnet = models.resnet34(pretrained=True) self.firstconv = resnet.conv1 self.firstbn = resnet.bn1 self.firstrelu = resnet.relu self.firstmaxpool = resnet.maxpool self.encoder1 = resnet.layer1 self.encoder2 = resnet.layer2 self.encoder3 = resnet.layer3 self.encoder4 = resnet.layer4 # the center of M_Net self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the center of ce_Net self.dblock = DACblock(512) # 空洞卷积 self.spp = SPPblock(512) # 池化后再上采样 # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_up0 = nn.ConvTranspose2d(512, 512, 2, stride=2) self.e3_up = nn.ConvTranspose2d(256, 256, 2, stride=2) self.e2_up = nn.ConvTranspose2d(128, 128, 2, stride=2) self.rc_up1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_up2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_up3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_up4 = nn.ConvTranspose2d(128, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(64, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(32, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.d3_conv = nn.Conv2d(384, 128, kernel_size=1, padding=0, stride=1, bias=True) self.d2_conv = nn.Conv2d(192, 64, kernel_size=1, padding=0, stride=1, bias=True) self.d1_conv = nn.Conv2d(96, 64, kernel_size=1, padding=0, stride=1, bias=True) # the decoder of ce_net self.decoder4 = DecoderBlock(512, filters[2]) self.decoder3 = DecoderBlock(filters[2], filters[1]) self.decoder2 = DecoderBlock(filters[1], filters[0]) self.decoder1 = DecoderBlock(filters[0], filters[0]) # 解码部分 self.finaldeconv1 = nn.ConvTranspose2d(filters[0], 32, 4, 2, 1) # 逆卷积 self.finalrelu1 = nonlinearity self.finalconv2 = nn.Conv2d(32, 32, 3, padding=1) self.finalrelu2 = nonlinearity self.finalconv3 = nn.Conv2d(32, out_ch, 3, padding=1) def forward(self, x): # M_Net Encoder Part l_x = x _, _, img_shape, _ = l_x.size() x_2 = F.upsample(l_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(l_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(l_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out1 = self.down1(l_x) # conv1 [32,512,512] out1 = torch.cat([self.conv2(x_2), out1], dim=1) conv2, out2 = self.down2(out1) # conv2 [64,256,256] out2 = torch.cat([self.conv3(x_3), out2], dim=1) conv3, out3 = self.down3(out2) # conv3 [128,128,128] out3 = torch.cat([self.conv4(x_4), out3], dim=1) conv4, out4 = self.down4(out3) # conv4 [256,64,64] # cet_out = self.center(out) # CE_Net Encoder part rx = x e0 = self.firstconv(rx) #[64,256,256] e0 = self.firstbn(e0) #[64,256,256] e0 = self.firstrelu(e0) #[64,256,256] pe0 = self.firstmaxpool(e0) #[64,128,128] e1 = self.encoder1(pe0) #[64,128,128] e2 = self.encoder2(e1) #[128,64,64] e3 = self.encoder3(e2) #[256,32,32] e4 = self.encoder4(e3) #[512,16,16] # the center part CAC_out = self.CAC(out4) cet_out = self.CAC_conv4(CAC_out) r1_cat = torch.cat([e3, cet_out], dim=1) up_out = self.rc_up1(r1_cat) up5 = self.up5(up_out) r2_cat = torch.cat([e2, up5], dim=1) up_out1 = self.rc_up2(r2_cat) up6 = self.up6(up_out1) r3_cat = torch.cat([e1, up6], dim=1) up_out2 = self.rc_up3(r3_cat) up7 = self.up7(up_out2) r4_cat = torch.cat([e0, up7], dim=1) up_out3 = self.rc_up4(r4_cat) up8 = self.up8(up_out3) M_Net_out = self.side_8(up8) # center of CE_Net e4 = self.dblock(e4) e4 = self.spp(e4) # Encoder of CE_Net d4 = self.decoder4(e4) + out4 # [256,32,32] d3 = self.decoder3(d4) + self.d3_conv(out3) # [128,64,64] d2 = self.decoder2(d3) + self.d2_conv(out2) # [64,128,128] d1 = self.decoder1(d2) + self.d1_conv(out1) # [64,256,256] out = self.finaldeconv1(d1) out = self.finalrelu1(out) out = self.finalconv2(out) out = self.finalrelu2(out) cet_out = self.finalconv3(out) ave_out = (cet_out + M_Net_out)/2 return F.sigmoid(ave_out) class DecoderBlock(nn.Module): def __init__(self, in_channels, n_filters): super(DecoderBlock, self).__init__() self.conv1 = nn.Conv2d(in_channels, in_channels // 4, 1) self.norm1 = nn.BatchNorm2d(in_channels // 4) self.relu1 = nonlinearity self.deconv2 = nn.ConvTranspose2d(in_channels // 4, in_channels // 4, 3, stride=2, padding=1, output_padding=1) self.norm2 = nn.BatchNorm2d(in_channels // 4) self.relu2 = nonlinearity self.conv3 = nn.Conv2d(in_channels // 4, n_filters, 1) self.norm3 = nn.BatchNorm2d(n_filters) self.relu3 = nonlinearity def forward(self, x): x = self.conv1(x) x = self.norm1(x) x = self.relu1(x) x = self.deconv2(x) x = self.norm2(x) x = self.relu2(x) x = self.conv3(x) x = self.norm3(x) x = self.relu3(x) return x class SPPblock(nn.Module): def __init__(self, in_channels): super(SPPblock, self).__init__() self.pool1 = nn.MaxPool2d(kernel_size=[2, 2], stride=2) self.pool2 = nn.MaxPool2d(kernel_size=[3, 3], stride=3) self.pool3 = nn.MaxPool2d(kernel_size=[5, 5], stride=5) self.pool4 = nn.MaxPool2d(kernel_size=[6, 6], stride=6) self.conv = nn.Conv2d(in_channels=in_channels, out_channels=1, kernel_size=1, padding=0) def forward(self, x): self.in_channels, h, w = x.size(1), x.size(2), x.size(3) self.layer1 = F.upsample(self.conv(self.pool1(x)), size=(h, w), mode='bilinear') self.layer2 = F.upsample(self.conv(self.pool2(x)), size=(h, w), mode='bilinear') self.layer3 = F.upsample(self.conv(self.pool3(x)), size=(h, w), mode='bilinear') self.layer4 = F.upsample(self.conv(self.pool4(x)), size=(h, w), mode='bilinear') out = torch.cat([self.layer1, self.layer2, self.layer3, self.layer4, x], 1) return out class DACblock(nn.Module): def __init__(self, channel): super(DACblock, self).__init__() self.dilate1 = nn.Conv2d(channel, channel, kernel_size=3, dilation=1, padding=1) self.dilate2 = nn.Conv2d(channel, channel, kernel_size=3, dilation=3, padding=3) self.dilate3 = nn.Conv2d(channel, channel, kernel_size=3, dilation=5, padding=5) self.conv1x1 = nn.Conv2d(channel, channel, kernel_size=1, dilation=1, padding=0) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): if m.bias is not None: m.bias.data.zero_() def forward(self, x): dilate1_out = nonlinearity(self.dilate1(x)) dilate2_out = nonlinearity(self.conv1x1(self.dilate2(x))) dilate3_out = nonlinearity(self.conv1x1(self.dilate2(self.dilate1(x)))) dilate4_out = nonlinearity(self.conv1x1(self.dilate3(self.dilate2(self.dilate1(x))))) out = x + dilate1_out + dilate2_out + dilate3_out + dilate4_out return out class DACblock134(nn.Module): def __init__(self, channel): super(DACblock134, self).__init__() self.dilate1 = nn.Conv2d(channel, channel, kernel_size=3, dilation=1, padding=1) self.dilate2 = nn.Conv2d(channel, channel, kernel_size=3, dilation=3, padding=3) self.dilate3 = nn.Conv2d(channel, channel, kernel_size=3, dilation=4, padding=4) self.conv1x1 = nn.Conv2d(channel, channel, kernel_size=1, dilation=1, padding=0) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): if m.bias is not None: m.bias.data.zero_() def forward(self, x): dilate1_out = nonlinearity(self.dilate1(x)) dilate2_out = nonlinearity(self.conv1x1(self.dilate2(x))) dilate3_out = nonlinearity(self.conv1x1(self.dilate2(self.dilate1(x)))) dilate4_out = nonlinearity(self.conv1x1(self.dilate3(self.dilate2(self.dilate1(x))))) out = x + dilate1_out + dilate2_out + dilate3_out + dilate4_out return out class DACblock137(nn.Module): def __init__(self, channel): super(DACblock137, self).__init__() self.dilate1 = nn.Conv2d(channel, channel, kernel_size=3, dilation=1, padding=1) self.dilate2 = nn.Conv2d(channel, channel, kernel_size=3, dilation=3, padding=3) self.dilate3 = nn.Conv2d(channel, channel, kernel_size=3, dilation=7, padding=7) self.conv1x1 = nn.Conv2d(channel, channel, kernel_size=1, dilation=1, padding=0) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): if m.bias is not None: m.bias.data.zero_() def forward(self, x): dilate1_out = nonlinearity(self.dilate1(x)) dilate2_out = nonlinearity(self.conv1x1(self.dilate2(x))) dilate3_out = nonlinearity(self.conv1x1(self.dilate2(self.dilate1(x)))) dilate4_out = nonlinearity(self.conv1x1(self.dilate3(self.dilate2(self.dilate1(x))))) out = x + dilate1_out + dilate2_out + dilate3_out + dilate4_out return out class DACblock139(nn.Module): def __init__(self, channel): super(DACblock139, self).__init__() self.dilate1 = nn.Conv2d(channel, channel, kernel_size=3, dilation=1, padding=1) self.dilate2 = nn.Conv2d(channel, channel, kernel_size=3, dilation=3, padding=3) self.dilate3 = nn.Conv2d(channel, channel, kernel_size=3, dilation=9, padding=9) self.conv1x1 = nn.Conv2d(channel, channel, kernel_size=1, dilation=1, padding=0) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): if m.bias is not None: m.bias.data.zero_() def forward(self, x): dilate1_out = nonlinearity(self.dilate1(x)) dilate2_out = nonlinearity(self.conv1x1(self.dilate2(x))) dilate3_out = nonlinearity(self.conv1x1(self.dilate2(self.dilate1(x)))) dilate4_out = nonlinearity(self.conv1x1(self.dilate3(self.dilate2(self.dilate1(x))))) out = x + dilate1_out + dilate2_out + dilate3_out + dilate4_out return out class M_Net(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(M_Net, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(in_ch, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(in_ch, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(in_ch, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_down1 = nn.ConvTranspose2d(512, 256, 2, stride=2) self.rc_down2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_down3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_down4 = nn.ConvTranspose2d(64, 32, 2, stride=2) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.gf = FastGuidedFilter_attention(r=2, eps=1e-2) # # # attention blocks # self.attentionblock5 = GridAttentionBlock(in_channels=512) # self.attentionblock6 = GridAttentionBlock(in_channels=256) # self.attentionblock7 = GridAttentionBlock(in_channels=128) # self.attentionblock8 = GridAttentionBlock(in_channels=64) def forward(self, x): _, _, img_shape, _ = x.size() x_2 = F.upsample(x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) cet_out = self.center(out) up_out = self.rc_down1(cet_out) r1_cat = torch.cat([conv4, up_out], dim=1) up5 = self.up5(r1_cat) up_out = self.rc_down2(up5) r2_cat = torch.cat([conv3,up_out],dim = 1) up6 = self.up6(r2_cat) up_out = self.rc_down3(up6) r3_cat = torch.cat([conv2,up_out],dim = 1) up7 = self.up7(r3_cat) up_out = self.rc_down4(up7) r4_cat = torch.cat([conv1,up_out],dim = 1) up8 = self.up8(r4_cat) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class M_Net_CAC_with_CAM(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(M_Net_CAC_with_CAM, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(in_ch, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(in_ch, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(in_ch, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_down1 = nn.ConvTranspose2d(256, 256, 2, stride=2) self.rc_down2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_down3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_down4 = nn.ConvTranspose2d(64, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_conv4 = M_Conv(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the CAM block self.p_CAM = nn.MaxPool2d(16) # self.CAM_conv = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.CAM_conv = M_Conv(1, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) def forward(self, x,cam_x): _, _, img_shape, _ = x.size() x_2 = F.upsample(x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) # cet_out = self.center(out) CAC_out = self.CAC(out) # the CAC block concat with our CAM cam = self.p_CAM(cam_x) cam_conv = self.CAM_conv(cam) cam_cac = torch.cat([CAC_out,cam_conv],dim=1) cet_out = self.CAC_conv4(cam_cac) up_out = self.rc_down1(cet_out) r1_cat = torch.cat([conv4, up_out], dim=1) up5 = self.up5(r1_cat) up_out = self.rc_down2(up5) r2_cat = torch.cat([conv3,up_out],dim = 1) up6 = self.up6(r2_cat) up_out = self.rc_down3(up6) r3_cat = torch.cat([conv2,up_out],dim = 1) up7 = self.up7(r3_cat) up_out = self.rc_down4(up7) r4_cat = torch.cat([conv1,up_out],dim = 1) up8 = self.up8(r4_cat) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class M_Net_CAC_with_CAM_Slide(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(M_Net_CAC_with_CAM_Slide, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(1, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(1, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(1, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_down1 = nn.ConvTranspose2d(256, 256, 2, stride=2) self.rc_down2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_down3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_down4 = nn.ConvTranspose2d(64, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_conv4 = M_Conv(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the CAM block self.p_CAM = nn.MaxPool2d(16) # self.CAM_conv = M_Conv(3, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.CAM_conv = M_Conv(1, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) def forward(self, x,cam_x): _, _, img_shape, _ = x.size() x_2 = F.upsample(cam_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(cam_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(cam_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) # cet_out = self.center(out) CAC_out = self.CAC(out) # the CAC block concat with our CAM cam = self.p_CAM(cam_x) cam_conv = self.CAM_conv(cam) cam_cac = torch.cat([CAC_out,cam_conv],dim=1) cet_out = self.CAC_conv4(cam_cac) up_out = self.rc_down1(cet_out) r1_cat = torch.cat([conv4, up_out], dim=1) up5 = self.up5(r1_cat) up_out = self.rc_down2(up5) r2_cat = torch.cat([conv3,up_out],dim = 1) up6 = self.up6(r2_cat) up_out = self.rc_down3(up6) r3_cat = torch.cat([conv2,up_out],dim = 1) up7 = self.up7(r3_cat) up_out = self.rc_down4(up7) r4_cat = torch.cat([conv1,up_out],dim = 1) up8 = self.up8(r4_cat) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class M_Net_CAC_slide(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(M_Net_CAC_slide, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(1, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(1, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(1, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_down1 = nn.ConvTranspose2d(256, 256, 2, stride=2) self.rc_down2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_down3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_down4 = nn.ConvTranspose2d(64, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.gf = FastGuidedFilter_attention(r=2, eps=1e-2) # # # attention blocks # self.attentionblock5 = GridAttentionBlock(in_channels=512) # self.attentionblock6 = GridAttentionBlock(in_channels=256) # self.attentionblock7 = GridAttentionBlock(in_channels=128) # self.attentionblock8 = GridAttentionBlock(in_channels=64) def forward(self, x,cam_x): _, _, img_shape, _ = x.size() x_2 = F.upsample(cam_x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(cam_x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(cam_x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) # cet_out = self.center(out) CAC_out = self.CAC(out) cet_out = self.CAC_conv4(CAC_out) up_out = self.rc_down1(cet_out) r1_cat = torch.cat([conv4, up_out], dim=1) up5 = self.up5(r1_cat) up_out = self.rc_down2(up5) r2_cat = torch.cat([conv3,up_out],dim = 1) up6 = self.up6(r2_cat) up_out = self.rc_down3(up6) r3_cat = torch.cat([conv2,up_out],dim = 1) up7 = self.up7(r3_cat) up_out = self.rc_down4(up7) r4_cat = torch.cat([conv1,up_out],dim = 1) up8 = self.up8(r4_cat) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class M_Net_CAC(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(M_Net_CAC, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(in_ch, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(in_ch, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(in_ch, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_down1 = nn.ConvTranspose2d(256, 256, 2, stride=2) self.rc_down2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_down3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_down4 = nn.ConvTranspose2d(64, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception(256) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.gf = FastGuidedFilter_attention(r=2, eps=1e-2) # # # attention blocks # self.attentionblock5 = GridAttentionBlock(in_channels=512) # self.attentionblock6 = GridAttentionBlock(in_channels=256) # self.attentionblock7 = GridAttentionBlock(in_channels=128) # self.attentionblock8 = GridAttentionBlock(in_channels=64) def forward(self, x): _, _, img_shape, _ = x.size() x_2 = F.upsample(x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) # cet_out = self.center(out) CAC_out = self.CAC(out) cet_out = self.CAC_conv4(CAC_out) up_out = self.rc_down1(cet_out) r1_cat = torch.cat([conv4, up_out], dim=1) up5 = self.up5(r1_cat) up_out = self.rc_down2(up5) r2_cat = torch.cat([conv3,up_out],dim = 1) up6 = self.up6(r2_cat) up_out = self.rc_down3(up6) r3_cat = torch.cat([conv2,up_out],dim = 1) up7 = self.up7(r3_cat) up_out = self.rc_down4(up7) r4_cat = torch.cat([conv1,up_out],dim = 1) up8 = self.up8(r4_cat) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class M_Net_CAC_with_Coarse(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(M_Net_CAC_with_Coarse, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(in_ch, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(in_ch, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(in_ch, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # self.rw_up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True) self.rc_down1 = nn.ConvTranspose2d(256, 256, 2, stride=2) self.rc_down2 = nn.ConvTranspose2d(256, 128, 2, stride=2) self.rc_down3 = nn.ConvTranspose2d(128, 64, 2, stride=2) self.rc_down4 = nn.ConvTranspose2d(64, 32, 2, stride=2) # the CAC block self.CAC = CACblock_with_inception_blocks(256) self.CAC_conv4 = M_Conv(256, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) # self.gf = FastGuidedFilter_attention(r=2, eps=1e-2) # # # attention blocks # self.attentionblock5 = GridAttentionBlock(in_channels=512) # self.attentionblock6 = GridAttentionBlock(in_channels=256) # self.attentionblock7 = GridAttentionBlock(in_channels=128) # self.attentionblock8 = GridAttentionBlock(in_channels=64) def forward(self, x,cam): _, _, img_shape, _ = x.size() x_2 = F.upsample(x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) # cet_out = self.center(out) CAC_out = self.CAC(out) cet_out = self.CAC_conv4(CAC_out) up_out = self.rc_down1(cet_out) r1_cat = torch.cat([conv4, up_out], dim=1) up5 = self.up5(r1_cat) up_out = self.rc_down2(up5) r2_cat = torch.cat([conv3,up_out],dim = 1) up6 = self.up6(r2_cat) up_out = self.rc_down3(up6) r3_cat = torch.cat([conv2,up_out],dim = 1) up7 = self.up7(r3_cat) up_out = self.rc_down4(up7) r4_cat = torch.cat([conv1,up_out],dim = 1) up8 = self.up8(r4_cat) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class AG_Net_EASPP(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(AG_Net_EASPP, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(in_ch, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(in_ch, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(in_ch, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the CAC block # self.CAC = CACblock_with_inception_blocks(512) self.CAC = CACblock_with_inception(512) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.gf = FastGuidedFilter_attention(r=2, eps=1e-2) # attention blocks self.attentionblock5 = GridAttentionBlock(in_channels=512) self.attentionblock6 = GridAttentionBlock(in_channels=256) self.attentionblock7 = GridAttentionBlock(in_channels=128) self.attentionblock8 = GridAttentionBlock(in_channels=64) def forward(self, x): _, _, img_shape, _ = x.size() x_2 = F.upsample(x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) out = self.center(out) CAC_out = self.CAC(out) FG = torch.cat([self.conv4(x_4), conv4], dim=1) N, C, H, W= FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, CAC_out, FG,self.attentionblock5(FG_small,out)) up5 = self.up5(out) FG = torch.cat([self.conv3(x_3), conv3], dim=1) N, C, H, W = FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, up5, FG,self.attentionblock6(FG_small,up5)) up6 = self.up6(out) FG = torch.cat([self.conv2(x_2), conv2], dim=1) N, C, H, W = FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, up6, FG,self.attentionblock7(FG_small,up6)) up7 = self.up7(out) FG = torch.cat([conv1, conv1], dim=1) N, C, H, W = FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, up7, FG,self.attentionblock8(FG_small,up7)) up8 = self.up8(out) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class AG_Net(nn.Module): def __init__(self, in_ch, out_ch, bn=True, BatchNorm=False): super(AG_Net, self).__init__() # mutli-scale simple convolution self.conv2 = M_Conv(in_ch, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv3 = M_Conv(in_ch, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.conv4 = M_Conv(in_ch, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the down convolution contain concat operation self.down1 = M_Encoder(in_ch, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 512 self.down2 = M_Encoder(64 + 32, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 256 self.down3 = M_Encoder(128 + 64, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 128 self.down4 = M_Encoder(256 + 128, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # 64 # the center self.center = M_Encoder(256, 512, kernel_size=3, pooling=False) # the up convolution contain concat operation self.up5 = M_Decoder_my_10(512, 256, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up6 = M_Decoder_my_10(256, 128, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up7 = M_Decoder_my_10(128, 64, kernel_size=3, bn=bn, BatchNorm=BatchNorm) self.up8 = M_Decoder_my_10(64, 32, kernel_size=3, bn=bn, BatchNorm=BatchNorm) # the sideoutput self.side_5 = nn.Conv2d(256, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_6 = nn.Conv2d(128, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_7 = nn.Conv2d(64, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.side_8 = nn.Conv2d(32, out_ch, kernel_size=1, padding=0, stride=1, bias=True) self.gf = FastGuidedFilter_attention(r=2, eps=1e-2) # attention blocks self.attentionblock5 = GridAttentionBlock(in_channels=512) self.attentionblock6 = GridAttentionBlock(in_channels=256) self.attentionblock7 = GridAttentionBlock(in_channels=128) self.attentionblock8 = GridAttentionBlock(in_channels=64) def forward(self, x): _, _, img_shape, _ = x.size() x_2 = F.upsample(x, size=(int(img_shape / 2), int(img_shape / 2)), mode='bilinear') x_3 = F.upsample(x, size=(int(img_shape / 4), int(img_shape / 4)), mode='bilinear') x_4 = F.upsample(x, size=(int(img_shape / 8), int(img_shape / 8)), mode='bilinear') conv1, out = self.down1(x) out = torch.cat([self.conv2(x_2), out], dim=1) conv2, out = self.down2(out) out = torch.cat([self.conv3(x_3), out], dim=1) conv3, out = self.down3(out) out = torch.cat([self.conv4(x_4), out], dim=1) conv4, out = self.down4(out) out = self.center(out) FG = torch.cat([self.conv4(x_4), conv4], dim=1) N, C, H, W= FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, out, FG,self.attentionblock5(FG_small,out)) up5 = self.up5(out) FG = torch.cat([self.conv3(x_3), conv3], dim=1) N, C, H, W = FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, up5, FG,self.attentionblock6(FG_small,up5)) up6 = self.up6(out) FG = torch.cat([self.conv2(x_2), conv2], dim=1) N, C, H, W = FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, up6, FG,self.attentionblock7(FG_small,up6)) up7 = self.up7(out) FG = torch.cat([conv1, conv1], dim=1) N, C, H, W = FG.size() FG_small = F.upsample(FG, size=(int(H/2), int(W/2)), mode='bilinear') out = self.gf(FG_small, up7, FG,self.attentionblock8(FG_small,up7)) up8 = self.up8(out) side_5 = F.upsample(up5, size=(img_shape, img_shape), mode='bilinear') side_6 = F.upsample(up6, size=(img_shape, img_shape), mode='bilinear') side_7 = F.upsample(up7, size=(img_shape, img_shape), mode='bilinear') side_8 = F.upsample(up8, size=(img_shape, img_shape), mode='bilinear') side_5 = self.side_5(side_5) side_6 = self.side_6(side_6) side_7 = self.side_7(side_7) side_8 = self.side_8(side_8) ave_out = (side_5+side_6+side_7+side_8)/4 return [ave_out, side_5, side_6, side_7, side_8] class CACblock_with_inception_blocks(nn.Module): def __init__(self, channel): super(CACblock_with_inception_blocks, self).__init__() self.conv1x1 = nn.Conv2d(channel, channel, kernel_size=1, dilation=1, padding=0) self.conv3x3 = nn.Conv2d(channel, channel, kernel_size=3, dilation=1, padding=1) self.conv5x5 = nn.Conv2d(channel, channel, kernel_size=5, dilation=1, padding=2) self.conv7x7 = nn.Conv2d(channel, channel, kernel_size=7, dilation=1, padding=3) self.pooling = nn.MaxPool2d(kernel_size=3, stride=1, padding=1) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): if m.bias is not None: m.bias.data.zero_() def forward(self, x): dilate1_out = nonlinearity(self.conv1x1(x)) dilate2_out = nonlinearity(self.conv3x3(self.conv1x1(x))) dilate3_out = nonlinearity(self.conv5x5(self.conv1x1(x))) dilate4_out = nonlinearity(self.conv7x7(self.conv1x1(x))) dilate5_out = self.pooling(x) out = dilate1_out + dilate2_out + dilate3_out + dilate4_out + dilate5_out return out class CACblock_with_inception(nn.Module): # 1X1,3X3,5X5 def __init__(self, channel): super(CACblock_with_inception, self).__init__() self.conv1x1 = nn.Conv2d(channel, channel, kernel_size=1, dilation=1, padding=0) self.conv3x3 = nn.Conv2d(channel, channel, kernel_size=3, dilation=1, padding=1) self.conv5x5 = nn.Conv2d(channel, channel, kernel_size=5, dilation=1, padding=2) # self.conv7x7 = nn.Conv2d(channel, channel, kernel_size=7, dilation=1, padding=3) self.pooling = nn.MaxPool2d(kernel_size=3, stride=1, padding=1) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): if m.bias is not None: m.bias.data.zero_() def forward(self, x): dilate1_out = nonlinearity(self.conv1x1(x)) dilate2_out = nonlinearity(self.conv3x3(self.conv1x1(x))) dilate3_out = nonlinearity(self.conv5x5(self.conv1x1(x))) # dilate4_out = nonlinearity(self.conv7x7(self.conv1x1(x))) dilate4_out = self.pooling(x) out = dilate1_out + dilate2_out + dilate3_out + dilate4_out return out class ConvBnRelu2d(nn.Module): def __init__(self, in_channels, out_channels, kernel_size=3, padding=1, dilation=1, stride=1, groups=1, is_bn=False, BatchNorm=False, is_relu=True, num_groups=32): super(ConvBnRelu2d, self).__init__() self.conv = nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, padding=padding, stride=stride, dilation=dilation, groups=groups, bias=False) if BatchNorm: self.bn = nn.BatchNorm2d(out_channels, eps=BN_EPS) self.relu = nn.ReLU(inplace=True) if is_bn: if out_channels//num_groups==0: num_groups=1 self.gn =nn.GroupNorm(num_groups, out_channels, eps=BN_EPS) self.is_bn = is_bn self.is_BatchNorm=BatchNorm if is_relu is False: self.relu=None def forward(self,x): x = self.conv(x) if self.is_BatchNorm: x = self.bn(x) if self.is_bn: x = self.gn(x) if self.relu is not None: x = self.relu(x) return x class StackEncoder (nn.Module): def __init__(self, x_channels, y_channels, kernel_size=3, dilation=1, bn=False, BatchNorm=False, num_groups=32): super(StackEncoder, self).__init__() padding=(dilation*kernel_size-1)//2 self.encode = nn.Sequential( ConvBnRelu2d(x_channels, y_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(y_channels, y_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ) def forward(self,x): y = self.encode(x) y_small = F.max_pool2d(y, kernel_size=2, stride=2) return y, y_small class StackDecoder (nn.Module): def __init__(self, x_big_channels, x_channels, y_channels, kernel_size=3, dilation=1, bn=False, BatchNorm=False, num_groups=32): super(StackDecoder, self).__init__() padding=(dilation*kernel_size-1)//2 self.decode = nn.Sequential( ConvBnRelu2d(x_big_channels+x_channels, y_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(y_channels, y_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(y_channels, y_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ) def forward(self, x_big, x): N,C,H,W = x_big.size() y = F.upsample(x, size=(H,W),mode='bilinear') #y = F.upsample(x, scale_factor=2,mode='bilinear') y = torch.cat([y,x_big],1) y = self.decode(y) return y class M_Encoder(nn.Module): def __init__(self, input_channels, output_channels, kernel_size=3, dilation=1, pooling=True, bn=False, BatchNorm=False, num_groups=32): super(M_Encoder, self).__init__() padding =(dilation*kernel_size-1)//2 self.encode = nn.Sequential( ConvBnRelu2d(input_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ) self.pooling = pooling def forward(self, x): conv = self.encode(x) if self.pooling: pool = F.max_pool2d(conv, kernel_size=2, stride=2) return conv,pool else: return conv class M_Conv(nn.Module): def __init__(self, input_channels, output_channels, kernel_size=3, dilation=1, pooling=True, bn=False, BatchNorm=False, num_groups=32): super(M_Conv, self).__init__() padding =(dilation*kernel_size-1)//2 self.encode = nn.Sequential( nn.Conv2d(input_channels, output_channels,kernel_size=kernel_size, padding=1, stride=1), nn.ReLU(inplace=True), ) def forward(self, x): conv = self.encode(x) return conv class M_Decoder(nn.Module): def __init__(self, input_channels, output_channels, kernel_size=3, dilation=1, deconv = False, bn=False, BatchNorm=False, num_groups=32): super(M_Decoder, self).__init__() padding =(dilation*kernel_size-1)//2 if deconv: self.deconv = nn.Sequential( nn.ConvTranspose2d(input_channels, output_channels, kernel_size, stride=1, padding=1), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1,is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ) else: self.deconv = False self.decode = nn.Sequential( ConvBnRelu2d(input_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ) def forward(self, x_big, x): N,C,H,W = x_big.size() out = F.upsample(x, size=(H,W),mode='bilinear') out = torch.cat([x_big,out], dim=1) if self.deconv: out = self.deconv(out) else: out = self.decode(out) return out class M_Decoder_my_10(nn.Module): def __init__(self, input_channels, output_channels, kernel_size=3, dilation=1, deconv = False, bn=False, BatchNorm=False, num_groups=32): super(M_Decoder_my_10, self).__init__() padding =(dilation*kernel_size-1)//2 if deconv: self.deconv = nn.Sequential( nn.ConvTranspose2d(input_channels, output_channels, kernel_size, stride=1, padding=1), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1,is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ) else: self.deconv = False self.decode = nn.Sequential( ConvBnRelu2d(input_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ConvBnRelu2d(output_channels, output_channels, kernel_size=kernel_size, padding=padding, dilation=dilation, stride=1, groups=1, is_bn=bn,BatchNorm=BatchNorm, num_groups=num_groups), ) def forward(self,x): x = self.decode(x) return x class GridAttentionBlock(nn.Module): def __init__(self, in_channels): super(GridAttentionBlock, self).__init__() self.inter_channels = in_channels self.in_channels = in_channels self.gating_channels = in_channels self.theta = nn.Conv2d(in_channels=self.in_channels, out_channels=self.inter_channels, kernel_size=1) self.phi = nn.Conv2d(in_channels=self.gating_channels, out_channels=self.inter_channels, kernel_size=1, stride=1, padding=0, bias=True) self.psi = nn.Conv2d(in_channels=self.inter_channels, out_channels=1, kernel_size=1, stride=1, padding=0, bias=True) self.softmax = nn.Softmax(dim=-1) def forward(self, x, g): input_size = x.size() batch_size = input_size[0] assert batch_size == g.size(0) theta_x = self.theta(x) theta_x_size = theta_x.size() phi_g = F.upsample(self.phi(g), size=theta_x_size[2:], mode='bilinear') f = F.relu(theta_x + phi_g, inplace=True) sigm_psi_f = F.sigmoid(self.psi(f)) return sigm_psi_f class FastGuidedFilter_attention(nn.Module): def __init__(self, r, eps=1e-8): super(FastGuidedFilter_attention, self).__init__() self.r = r self.eps = eps self.boxfilter = BoxFilter(r) self.epss = 1e-12 def forward(self, lr_x, lr_y, hr_x, l_a): n_lrx, c_lrx, h_lrx, w_lrx = lr_x.size() n_lry, c_lry, h_lry, w_lry = lr_y.size() n_hrx, c_hrx, h_hrx, w_hrx = hr_x.size() lr_x = lr_x.double() lr_y = lr_y.double() hr_x = hr_x.double() l_a = l_a.double() assert n_lrx == n_lry and n_lry == n_hrx assert c_lrx == c_hrx and (c_lrx == 1 or c_lrx == c_lry) assert h_lrx == h_lry and w_lrx == w_lry assert h_lrx > 2*self.r+1 and w_lrx > 2*self.r+1 ## N N = self.boxfilter(Variable(lr_x.data.new().resize_((1, 1, h_lrx, w_lrx)).fill_(1.0))) # l_a = torch.abs(l_a) l_a = torch.abs(l_a) + self.epss t_all = torch.sum(l_a) l_t = l_a / t_all ## mean_attention mean_a = self.boxfilter(l_a) / N ## mean_a^2xy mean_a2xy = self.boxfilter(l_a * l_a * lr_x * lr_y) / N ## mean_tax mean_tax = self.boxfilter(l_t * l_a * lr_x) / N ## mean_ay mean_ay = self.boxfilter(l_a * lr_y) / N ## mean_a^2x^2 mean_a2x2 = self.boxfilter(l_a * l_a * lr_x * lr_x) / N ## mean_ax mean_ax = self.boxfilter(l_a * lr_x) / N ## A temp = torch.abs(mean_a2x2 - N * mean_tax * mean_ax) A = (mean_a2xy - N * mean_tax * mean_ay) / (temp + self.eps) ## b b = (mean_ay - A * mean_ax) / (mean_a) # -------------------------------- # Mean # -------------------------------- A = self.boxfilter(A) / N b = self.boxfilter(b) / N ## mean_A; mean_b mean_A = F.upsample(A, (h_hrx, w_hrx), mode='bilinear') mean_b = F.upsample(b, (h_hrx, w_hrx), mode='bilinear') return (mean_A*hr_x+mean_b).float() def diff_x(input, r): assert input.dim() == 4 left = input[:, :, r:2 * r + 1] middle = input[:, :, 2 * r + 1: ] - input[:, :, :-2 * r - 1] right = input[:, :, -1: ] - input[:, :, -2 * r - 1: -r - 1] output = torch.cat([left, middle, right], dim=2) return output def diff_y(input, r): assert input.dim() == 4 left = input[:, :, :, r:2 * r + 1] middle = input[:, :, :, 2 * r + 1: ] - input[:, :, :, :-2 * r - 1] right = input[:, :, :, -1: ] - input[:, :, :, -2 * r - 1: -r - 1] output = torch.cat([left, middle, right], dim=3) return output class BoxFilter(nn.Module): def __init__(self, r): super(BoxFilter, self).__init__() self.r = r def forward(self, x): assert x.dim() == 4 return diff_y(diff_x(x.cumsum(dim=2), self.r).cumsum(dim=3), self.r) if __name__ == '__main__': from torchstat import stat # model = H_Net(3,2,bn=True, BatchNorm=False) model = create_model(arch='DeepLabV3Plus', encoder_name="efficientnet-b0", encoder_weights= "imagenet", in_channels = 3, classes = 2) eff = smp.encoders.get_encoder(name='efficientnet-b0', in_channels=3, depth=4, weights=None) a = torch.rand((2, 3, 512, 512)) print(model.encoder._blocks)

46.961418

199

0.612073

15,640

104,677

3.904859

0.021356

0.059929

0.039625

0.071326

0.939776

0.931802

0.92404

0.918277

0.913528

0.907503

0

0.088067

0.25466

104,677

2,229

200

46.961418

0.694706

0.086781

0

0.841418

0

0.00873

0

0.004975

1

0.042289

false

0

0.005597

0

0.090796

0.000622

0

null

0

1

0

1

0

null

0

7

c20e96a238407a3228f47417673dd8aa9b253900

545

py

Python

src/adapt/project-id.py

CaioSR/deps-ahoy

730a1ed16f5d48f654e5a85c2366f3e56aebc9d9

[ "MIT" ]

null

src/adapt/project-id.py

CaioSR/deps-ahoy

730a1ed16f5d48f654e5a85c2366f3e56aebc9d9

[ "MIT" ]

null

src/adapt/project-id.py

CaioSR/deps-ahoy

730a1ed16f5d48f654e5a85c2366f3e56aebc9d9

[ "MIT" ]

null

import csv with open('spring/aNodes.csv', 'r') as rF, open('spring/aNodes_new.csv', 'w', newline='') as wF: reader = csv.reader(rF) for node in reader: node.append([1]) writer = csv.writer(wF) writer.writerow(node) rF.close() wF.close() with open('shiro/aNodes.csv', 'r') as rF, open('shiro/aNodes_new.csv', 'w', newline='') as wF: reader = csv.reader(rF) for node in reader: node.append([2]) writer = csv.writer(wF) writer.writerow(node) rF.close() wF.close()

24.772727

96

0.581651

80

545

3.9375

0.3

0.050794

0.101587

0.07619

0.844444

0.730159

0

0.004866

0.245872

545

21

97

25.952381

0.761557

0

0.705882

0

0.143119

0.038532

0

1

0

false

0

0.058824

0

0.058824

0

null

0

1

0

1

0

null

0

7

df9fb662a3a7ad6e1fac83b218e03ec76f821c84

13,108

py

Python

bvai.py

Shahin3010/Shahinvai

6128c4e9883d5da35f1b43ace6e68d972034b6cd

[ "MIT" ]

null

bvai.py

Shahin3010/Shahinvai

6128c4e9883d5da35f1b43ace6e68d972034b6cd

[ "MIT" ]

null

bvai.py

Shahin3010/Shahinvai

6128c4e9883d5da35f1b43ace6e68d972034b6cd

[ "MIT" ]

null

# bvai v1.0 # Contact Me On Facebook For Using This Tool # Coded By Shahin Islam # If You Wanna Take Credits For This Code, Please Look Yourself Again... # Reserved2020 # Powered by Shahin islam import base64 exec(base64.b32decode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Python

test/api/test_consent_type.py

ryomahan/read-tracardi-api

d0a012fb097ca81daf046b314000301eb54bfad8

[ "MIT" ]

3

2021-11-27T18:03:31.000Z

2022-02-06T21:47:59.000Z

test/api/test_consent_type.py

ryomahan/read-tracardi-api

d0a012fb097ca81daf046b314000301eb54bfad8

[ "MIT" ]

13

2021-11-03T18:15:06.000Z

2022-03-27T22:28:38.000Z

test/api/test_consent_type.py

ryomahan/read-tracardi-api

d0a012fb097ca81daf046b314000301eb54bfad8

[ "MIT" ]

8

2021-11-16T04:07:41.000Z

2022-03-14T14:51:34.000Z

from ..utils import Endpoint from fastapi import HTTPException endpoint = Endpoint() def test_post_consent_type(): data = { "name": "test-name", "description": "test-description", "revokable": True, "default_value": "grant", "enabled": True, "tags": ["tag1", "tag2", "tag3"], "required": True, "auto_revoke": "15m" } result = endpoint.post("/consent/type", data) result = result.json() assert not result["errors"] assert result["saved"] == 1 assert result["ids"] == ["test-name"] data = { "name": "test-name", "description": "test-description", "revokable": False, "default_value": "deny", "enabled": False, "tags": ["tag1", "tag2", "tag3"], "required": False, "auto_revoke": "15m" } result = endpoint.post("/consent/type", data) result = result.json() assert not result["errors"] assert result["saved"] == 1 assert result["ids"] == ["test-name"] data = { "name": "test-name", "description": "test-description", "revokable": False, "default_value": "incorrect_data", "enabled": False, "tags": ["tag1", "tag2", "tag3"], "required": False, "auto_revoke": "incorrect_data" } result = endpoint.post("/consent/type", data) result = result.json() assert "detail" in result assert result["detail"][0]["loc"][1] == "default_value" assert result["detail"][1]["loc"][1] == "auto_revoke" endpoint.delete("/consent/type/test-name") def test_get_consent_type_id(): data = { "name": "test-name", "description": "test-description", "revokable": True, "default_value": "grant", "enabled": True, "tags": ["tag1", "tag2", "tag3"], "required": True, "auto_revoke": "15m" } result = endpoint.post("/consent/type", data) result = result.json() assert not result["errors"] assert result["saved"] == 1 assert result["ids"] == ["test-name"] result = endpoint.get("/consent/type/test-name") result = result.json() assert "id" in result and result["id"] == "test-name" endpoint.delete("/consent/type/test-name") def test_delete_consent_type_id(): try: data = { "name": "test-name", "description": "test-description", "revokable": True, "default_value": "grant", "enabled": True, "tags": ["tag1", "tag2", "tag3"], "required": True, "auto_revoke": "15m" } result = endpoint.post("/consent/type", data) result = result.json() assert not result["errors"] assert result["saved"] == 1 assert result["ids"] == ["test-name"] result = endpoint.delete("/consent/type/test-name") result = result.json() assert result == {"deleted": 1} result = endpoint.delete("/consent/type/test-name") result = result.json() assert result == {"deleted": 0} finally: endpoint.delete("/consent/type/test-name") def test_get_consents_type(): result = endpoint.get("/consents/type") def test_get_consents_type_enabled(): try: data = { "name": "test-name", "description": "test-description", "revokable": True, "default_value": "grant", "enabled": True, "tags": ["tag1", "tag2", "tag3"], "required": True, "auto_revoke": "15m" } result = endpoint.post("/consent/type", data) result = result.json() assert not result["errors"] assert result["saved"] == 1 assert result["ids"] == ["test-name"] result = endpoint.get("/consents/type/enabled") result = result.json() assert {consent["enabled"] for consent in result["result"]} == {True} finally: endpoint.delete("/consent/type/test-name") def test_put_consents_type_refresh(): result = endpoint.put("/consents/type/refresh") def test_get_consents_type_by_tag(): result = endpoint.get("/consents/type/by_tag")

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Python

flasky2/venv/Lib/site-packages/weka/flow/sink.py

akshat0109/kisan_backend

b26fb382fa5377010be60e6edd5e57b3e6c5b3fe

[ "MIT" ]

null

flasky2/venv/Lib/site-packages/weka/flow/sink.py

akshat0109/kisan_backend

b26fb382fa5377010be60e6edd5e57b3e6c5b3fe

[ "MIT" ]

null

flasky2/venv/Lib/site-packages/weka/flow/sink.py

akshat0109/kisan_backend

b26fb382fa5377010be60e6edd5e57b3e6c5b3fe

[ "MIT" ]

null

# This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # sink.py # Copyright (C) 2015 Fracpete (pythonwekawrapper at gmail dot com) import traceback import weka.core.serialization as serialization from weka.core.dataset import Instances, Instance from weka.flow.base import InputConsumer from weka.flow.container import ModelContainer from weka.classifiers import Evaluation import weka.plot.classifiers as pltclassifier import weka.plot.clusterers as pltclusterer import weka.plot.dataset as pltdataset class Sink(InputConsumer): """ The ancestor for all sinks. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(Sink, self).__init__(name=name, config=config) super(InputConsumer, self).__init__(name=name, config=config) def post_execute(self): """ Gets executed after the actual execution. :return: None if successful, otherwise error message :rtype: str """ result = super(Sink, self).post_execute() if result is None: self._input = None return result class Null(Sink): """ Sink that just gobbles up all the data. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(Null, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Sink that just gobbles up all the data." def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ return None class Console(Sink): """ Sink that outputs the payloads of the data on stdout. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(Console, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Sink that outputs the payloads of the data on stdout." @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return "prefix: '" + str(self.config["prefix"]) + "'" def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(Console, self).fix_config(options) opt = "prefix" if opt not in options: options[opt] = "" if opt not in self.help: self.help[opt] = "The prefix for the output (string)." return options def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ print(self.resolve_option("prefix") + str(self.input.payload)) return None class FileOutputSink(Sink): """ Ancestor for sinks that output data to a file. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(FileOutputSink, self).__init__(name=name, config=config) @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return "output: '" + str(self.config["output"]) + "'" def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(FileOutputSink, self).fix_config(options) opt = "output" if opt not in options: options[opt] = "." if opt not in self.help: self.help[opt] = "The file to write to (string)." return options class DumpFile(FileOutputSink): """ Sink that outputs the payloads of the data to a file. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(DumpFile, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Sink that outputs the payloads of the data to a file." @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return super(DumpFile, self).quickinfo + ", append: " + str(self.config["append"]) def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(DumpFile, self).fix_config(options) opt = "append" if opt not in options: options[opt] = False if opt not in self.help: self.help[opt] = "Whether to append to the file or overwrite (bool)." return options def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None f = None try: if bool(self.resolve_option("append")): f = open(str(self.resolve_option("output")), "a") else: f = open(str(self.resolve_option("output")), "w") f.write(str(self.input.payload)) f.write("\n") except Exception, e: result = self.full_name + "\n" + traceback.format_exc() finally: if f is not None: f.close() return result class ModelWriter(FileOutputSink): """ Writes a model to disk. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(ModelWriter, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Writes a model to disk." def check_input(self, token): """ Performs checks on the input token. Raises an exception if unsupported. :param token: the token to check :type token: Token """ if not isinstance(token.payload, ModelContainer): raise Exception(self.full_name + ": Input token is not a ModelContainer!") def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None cont = self.input.payload serialization.write_all( str(self.resolve_option("output")), [cont.get("Model").jobject, cont.get("Header").jobject]) return result class MatrixPlot(Sink): """ Displays the Instances object as matrix plot. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(MatrixPlot, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Displays the Instances object as matrix plot." def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(MatrixPlot, self).fix_config(options) opt = "percent" if opt not in options: options[opt] = 100.0 if opt not in self.help: self.help[opt] = "The percentage of the data to display (0-100, float)." opt = "seed" if opt not in options: options[opt] = 1 if opt not in self.help: self.help[opt] = "The seed value for randomizing the plot when viewing a subset (int)." opt = "size" if opt not in options: options[opt] = 10 if opt not in self.help: self.help[opt] = "The size of the circles in the plot (int)." opt = "title" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The title for the plot (str)." opt = "outfile" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The file to store the plot in (str)." opt = "wait" if opt not in options: options[opt] = True if opt not in self.help: self.help[opt] = "Whether to wait for user to close the plot window (bool)." return options @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return "percent: " + str(self.config["percent"]) \ + ", title: " + str(self.config["title"]) \ + ", outfile: " + str(self.config["outfile"]) \ + ", wait: " + str(self.config["wait"]) def check_input(self, token): """ Performs checks on the input token. Raises an exception if unsupported. :param token: the token to check :type token: Token """ if not isinstance(token.payload, Instances): raise Exception(self.full_name + ": Input token is not an Instances object!") def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None data = self.input.payload pltdataset.matrix_plot( data, percent=float(self.resolve_option("percent")), seed=int(self.resolve_option("seed")), size=int(self.resolve_option("size")), title=self.resolve_option("title"), outfile=self.resolve_option("outfile"), wait=bool(self.resolve_option("wait"))) return result class LinePlot(Sink): """ Displays the Instances object as line plot using the internal format, one line per Instance. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(LinePlot, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Displays the Instances object as line plot using the internal format, one line per Instance." def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(LinePlot, self).fix_config(options) opt = "attributes" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The list of 0-based attribute indices to print; None for all (int)." opt = "percent" if opt not in options: options[opt] = 100.0 if opt not in self.help: self.help[opt] = "The percentage of the data to display (0-100, float)." opt = "seed" if opt not in options: options[opt] = 1 if opt not in self.help: self.help[opt] = "The seed value for randomizing the plot when viewing a subset (int)." opt = "title" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The title for the plot (str)." opt = "outfile" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The file to store the plot in (str)." opt = "wait" if opt not in options: options[opt] = True if opt not in self.help: self.help[opt] = "Whether to wait for user to close the plot window (bool)." return options @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return "percent: " + str(self.config["percent"]) \ + ", title: " + str(self.config["title"]) \ + ", outfile: " + str(self.config["outfile"]) \ + ", wait: " + str(self.config["wait"]) def check_input(self, token): """ Performs checks on the input token. Raises an exception if unsupported. :param token: the token to check :type token: Token """ if not isinstance(token.payload, Instances): raise Exception(self.full_name + ": Input token is not an Instances object!") def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None data = self.input.payload pltdataset.line_plot( data, atts=self.resolve_option("attributes"), percent=float(self.resolve_option("percent")), seed=int(self.resolve_option("seed")), title=self.resolve_option("title"), outfile=self.resolve_option("outfile"), wait=bool(self.resolve_option("wait"))) return result class ClassifierErrors(Sink): """ Displays the errors obtained through a classifier evaluation. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(ClassifierErrors, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Displays the errors obtained through a classifier evaluation." def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(ClassifierErrors, self).fix_config(options) opt = "absolute" if opt not in options: options[opt] = True if opt not in self.help: self.help[opt] = "Whether to use absolute errors as size or relative ones (bool)." opt = "max_relative_size" if opt not in options: options[opt] = 50 if opt not in self.help: self.help[opt] = "The maximum size in point in case of relative mode (int)." opt = "absolute_size" if opt not in options: options[opt] = 50 if opt not in self.help: self.help[opt] = "The size in point in case of absolute mode (int)." opt = "title" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The title for the plot (str)." opt = "outfile" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The file to store the plot in (str)." opt = "wait" if opt not in options: options[opt] = True if opt not in self.help: self.help[opt] = "Whether to wait for user to close the plot window (bool)." return options @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return "absolute: " + str(self.config["absolute"]) \ + ", title: " + str(self.config["title"]) \ + ", outfile: " + str(self.config["outfile"]) \ + ", wait: " + str(self.config["wait"]) def check_input(self, token): """ Performs checks on the input token. Raises an exception if unsupported. :param token: the token to check :type token: Token """ if not isinstance(token.payload, Evaluation): raise Exception(self.full_name + ": Input token is not an Evaluation object!") def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None evl = self.input.payload pltclassifier.plot_classifier_errors( evl.predictions, absolute=bool(self.resolve_option("absolute")), max_relative_size=int(self.resolve_option("max_relative_size")), absolute_size=int(self.resolve_option("absolute_size")), title=self.resolve_option("title"), outfile=self.resolve_option("outfile"), wait=bool(self.resolve_option("wait"))) return result class ROC(Sink): """ Displays the ROC curve obtained from a classifier evaluation. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(ROC, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Displays the ROC curve obtained from a classifier evaluation." def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(ROC, self).fix_config(options) opt = "class_index" if opt not in options: options[opt] = [0] if opt not in self.help: self.help[opt] = "The list of 0-based class-label indices to display (list)." opt = "key_loc" if opt not in options: options[opt] = "lower right" if opt not in self.help: self.help[opt] = "The location of the key in the plot (str)." opt = "title" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The title for the plot (str)." opt = "outfile" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The file to store the plot in (str)." opt = "wait" if opt not in options: options[opt] = True if opt not in self.help: self.help[opt] = "Whether to wait for user to close the plot window (bool)." return options @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return "classes: " + str(self.config["class_index"]) \ + ", title: " + str(self.config["title"]) \ + ", outfile: " + str(self.config["outfile"]) \ + ", wait: " + str(self.config["wait"]) def check_input(self, token): """ Performs checks on the input token. Raises an exception if unsupported. :param token: the token to check :type token: Token """ if not isinstance(token.payload, Evaluation): raise Exception(self.full_name + ": Input token is not an Evaluation object!") def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None evl = self.input.payload pltclassifier.plot_roc( evl, class_index=self.resolve_option("class_index"), title=self.resolve_option("title"), key_loc=self.resolve_option("key_loc"), outfile=self.resolve_option("outfile"), wait=bool(self.resolve_option("wait"))) return result class PRC(Sink): """ Displays the PRC curve obtained from a classifier evaluation. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(PRC, self).__init__(name=name, config=config) def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Displays the PRC curve obtained from a classifier evaluation." def fix_config(self, options): """ Fixes the options, if necessary. I.e., it adds all required elements to the dictionary. :param options: the options to fix :type options: dict :return: the (potentially) fixed options :rtype: dict """ options = super(PRC, self).fix_config(options) opt = "class_index" if opt not in options: options[opt] = [0] if opt not in self.help: self.help[opt] = "The list of 0-based class-label indices to display (list)." opt = "key_loc" if opt not in options: options[opt] = "lower center" if opt not in self.help: self.help[opt] = "The location of the key in the plot (str)." opt = "title" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The title for the plot (str)." opt = "outfile" if opt not in options: options[opt] = None if opt not in self.help: self.help[opt] = "The file to store the plot in (str)." opt = "wait" if opt not in options: options[opt] = True if opt not in self.help: self.help[opt] = "Whether to wait for user to close the plot window (bool)." return options @property def quickinfo(self): """ Returns a short string describing some of the options of the actor. :return: the info, None if not available :rtype: str """ return "classes: " + str(self.config["class_index"]) \ + ", title: " + str(self.config["title"]) \ + ", outfile: " + str(self.config["outfile"]) \ + ", wait: " + str(self.config["wait"]) def check_input(self, token): """ Performs checks on the input token. Raises an exception if unsupported. :param token: the token to check :type token: Token """ if not isinstance(token.payload, Evaluation): raise Exception(self.full_name + ": Input token is not an Evaluation object!") def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None evl = self.input.payload pltclassifier.plot_prc( evl, class_index=self.resolve_option("class_index"), title=self.resolve_option("title"), key_loc=self.resolve_option("key_loc"), outfile=self.resolve_option("outfile"), wait=bool(self.resolve_option("wait"))) return result class InstanceDumper(FileOutputSink): """ Sink that dumps the incoming Instance/Instances into a file. """ def __init__(self, name=None, config=None): """ Initializes the sink. :param name: the name of the sink :type name: str :param config: the dictionary with the options (str -> object). :type config: dict """ super(InstanceDumper, self).__init__(name=name, config=config) self._header = None def description(self): """ Returns a description of the actor. :return: the description :rtype: str """ return "Sink that dumps the incoming Instance/Instances objects in a file." def check_input(self, token): """ Performs checks on the input token. Raises an exception if unsupported. :param token: the token to check :type token: Token """ if isinstance(token.payload, Instance): return if isinstance(token.payload, Instances): return raise Exception(self.full_name + ": Input token is neither an Instance nor Instances object!") def do_execute(self): """ The actual execution of the actor. :return: None if successful, otherwise error message :rtype: str """ result = None data = self.input.payload if isinstance(self._input.payload, Instance): inst = self.input.payload data = inst.dataset elif isinstance(self.input.payload, Instances): data = self.input.payload inst = None append = True if self._header is None or (self._header.equal_headers(data) is not None): self._header = Instances.template_instances(data, 0) outstr = str(data) append = False elif inst is not None: outstr = str(inst) else: outstr = str(data) f = None try: if append: f = open(str(self.resolve_option("output")), "a") else: f = open(str(self.resolve_option("output")), "w") f.write(outstr) f.write("\n") except Exception, e: result = self.full_name + "\n" + traceback.format_exc() finally: if f is not None: f.close() return result

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0.080825

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0.029663

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0.813707

0.805813

0.798816

0.789965

0

0.00176

0.330877

29,715

983

110

30.228891

0.839209

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null

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1

0

1

0

null

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1

0

8

a0882244036a99359abc60506107aa145ee78134

26,815

py

Python

com/vmware/nsx/app_discovery/sessions_client.py

vishal-12/vsphere-automation-sdk-python

9cf363971db77ea5a12928eecd5cf5170a7fcd8a

[ "MIT" ]

null

com/vmware/nsx/app_discovery/sessions_client.py

vishal-12/vsphere-automation-sdk-python

9cf363971db77ea5a12928eecd5cf5170a7fcd8a

[ "MIT" ]

null

com/vmware/nsx/app_discovery/sessions_client.py

vishal-12/vsphere-automation-sdk-python

9cf363971db77ea5a12928eecd5cf5170a7fcd8a

[ "MIT" ]

null

# -*- coding: utf-8 -*- #--------------------------------------------------------------------------- # Copyright 2019 VMware, Inc. All rights reserved. # AUTO GENERATED FILE -- DO NOT MODIFY! # # vAPI stub file for package com.vmware.nsx.app_discovery.sessions. #--------------------------------------------------------------------------- """ """ __author__ = 'VMware, Inc.' __docformat__ = 'restructuredtext en' import sys from vmware.vapi.bindings import type from vmware.vapi.bindings.converter import TypeConverter from vmware.vapi.bindings.enum import Enum from vmware.vapi.bindings.error import VapiError from vmware.vapi.bindings.struct import VapiStruct from vmware.vapi.bindings.stub import ( ApiInterfaceStub, StubFactoryBase, VapiInterface) from vmware.vapi.bindings.common import raise_core_exception from vmware.vapi.data.validator import (UnionValidator, HasFieldsOfValidator) from vmware.vapi.exception import CoreException from vmware.vapi.lib.constants import TaskType from vmware.vapi.lib.rest import OperationRestMetadata class AppProfiles(VapiInterface): """ """ _VAPI_SERVICE_ID = 'com.vmware.nsx.app_discovery.sessions.app_profiles' """ Identifier of the service in canonical form. """ def __init__(self, config): """ :type config: :class:`vmware.vapi.bindings.stub.StubConfiguration` :param config: Configuration to be used for creating the stub. """ VapiInterface.__init__(self, config, _AppProfilesStub) def list(self, session_id, cursor=None, included_fields=None, page_size=None, sort_ascending=None, sort_by=None, ): """ Returns the application profiles that was part of the application discovery session | while it was started. :type session_id: :class:`str` :param session_id: (required) :type cursor: :class:`str` or ``None`` :param cursor: Opaque cursor to be used for getting next page of records (supplied by current result page) (optional) :type included_fields: :class:`str` or ``None`` :param included_fields: Comma separated list of fields that should be included in query result (optional) :type page_size: :class:`long` or ``None`` :param page_size: Maximum number of results to return in this page (server may return fewer) (optional, default to 1000) :type sort_ascending: :class:`bool` or ``None`` :param sort_ascending: (optional) :type sort_by: :class:`str` or ``None`` :param sort_by: Field by which records are sorted (optional) :rtype: :class:`com.vmware.nsx.model_client.AppProfileListResult` :return: com.vmware.nsx.model.AppProfileListResult :raise: :class:`com.vmware.vapi.std.errors_client.ServiceUnavailable` Service Unavailable :raise: :class:`com.vmware.vapi.std.errors_client.InvalidRequest` Bad Request, Precondition Failed :raise: :class:`com.vmware.vapi.std.errors_client.InternalServerError` Internal Server Error :raise: :class:`com.vmware.vapi.std.errors_client.Unauthorized` Forbidden :raise: :class:`com.vmware.vapi.std.errors_client.NotFound` Not Found """ return self._invoke('list', { 'session_id': session_id, 'cursor': cursor, 'included_fields': included_fields, 'page_size': page_size, 'sort_ascending': sort_ascending, 'sort_by': sort_by, }) class InstalledApps(VapiInterface): """ """ _VAPI_SERVICE_ID = 'com.vmware.nsx.app_discovery.sessions.installed_apps' """ Identifier of the service in canonical form. """ def __init__(self, config): """ :type config: :class:`vmware.vapi.bindings.stub.StubConfiguration` :param config: Configuration to be used for creating the stub. """ VapiInterface.__init__(self, config, _InstalledAppsStub) def list(self, session_id, app_profile_id=None, cursor=None, included_fields=None, page_size=None, sort_ascending=None, sort_by=None, vm_id=None, ): """ Returns the details of the installed apps for the app profile ID in that session :type session_id: :class:`str` :param session_id: (required) :type app_profile_id: :class:`str` or ``None`` :param app_profile_id: (optional) :type cursor: :class:`str` or ``None`` :param cursor: Opaque cursor to be used for getting next page of records (supplied by current result page) (optional) :type included_fields: :class:`str` or ``None`` :param included_fields: Comma separated list of fields that should be included in query result (optional) :type page_size: :class:`long` or ``None`` :param page_size: Maximum number of results to return in this page (server may return fewer) (optional, default to 1000) :type sort_ascending: :class:`bool` or ``None`` :param sort_ascending: (optional) :type sort_by: :class:`str` or ``None`` :param sort_by: Field by which records are sorted (optional) :type vm_id: :class:`str` or ``None`` :param vm_id: (optional) :rtype: :class:`com.vmware.nsx.model_client.AppInfoListResult` :return: com.vmware.nsx.model.AppInfoListResult :raise: :class:`com.vmware.vapi.std.errors_client.ServiceUnavailable` Service Unavailable :raise: :class:`com.vmware.vapi.std.errors_client.InvalidRequest` Bad Request, Precondition Failed :raise: :class:`com.vmware.vapi.std.errors_client.InternalServerError` Internal Server Error :raise: :class:`com.vmware.vapi.std.errors_client.Unauthorized` Forbidden :raise: :class:`com.vmware.vapi.std.errors_client.NotFound` Not Found """ return self._invoke('list', { 'session_id': session_id, 'app_profile_id': app_profile_id, 'cursor': cursor, 'included_fields': included_fields, 'page_size': page_size, 'sort_ascending': sort_ascending, 'sort_by': sort_by, 'vm_id': vm_id, }) class NsGroups(VapiInterface): """ """ _VAPI_SERVICE_ID = 'com.vmware.nsx.app_discovery.sessions.ns_groups' """ Identifier of the service in canonical form. """ def __init__(self, config): """ :type config: :class:`vmware.vapi.bindings.stub.StubConfiguration` :param config: Configuration to be used for creating the stub. """ VapiInterface.__init__(self, config, _NsGroupsStub) def list(self, session_id, cursor=None, included_fields=None, page_size=None, sort_ascending=None, sort_by=None, ): """ Returns the ns groups that was part of the application discovery session | while it was started :type session_id: :class:`str` :param session_id: (required) :type cursor: :class:`str` or ``None`` :param cursor: Opaque cursor to be used for getting next page of records (supplied by current result page) (optional) :type included_fields: :class:`str` or ``None`` :param included_fields: Comma separated list of fields that should be included in query result (optional) :type page_size: :class:`long` or ``None`` :param page_size: Maximum number of results to return in this page (server may return fewer) (optional, default to 1000) :type sort_ascending: :class:`bool` or ``None`` :param sort_ascending: (optional) :type sort_by: :class:`str` or ``None`` :param sort_by: Field by which records are sorted (optional) :rtype: :class:`com.vmware.nsx.model_client.NSGroupMetaInfoListResult` :return: com.vmware.nsx.model.NSGroupMetaInfoListResult :raise: :class:`com.vmware.vapi.std.errors_client.ServiceUnavailable` Service Unavailable :raise: :class:`com.vmware.vapi.std.errors_client.InvalidRequest` Bad Request, Precondition Failed :raise: :class:`com.vmware.vapi.std.errors_client.InternalServerError` Internal Server Error :raise: :class:`com.vmware.vapi.std.errors_client.Unauthorized` Forbidden :raise: :class:`com.vmware.vapi.std.errors_client.NotFound` Not Found """ return self._invoke('list', { 'session_id': session_id, 'cursor': cursor, 'included_fields': included_fields, 'page_size': page_size, 'sort_ascending': sort_ascending, 'sort_by': sort_by, }) class ReClassify(VapiInterface): """ """ _VAPI_SERVICE_ID = 'com.vmware.nsx.app_discovery.sessions.re_classify' """ Identifier of the service in canonical form. """ def __init__(self, config): """ :type config: :class:`vmware.vapi.bindings.stub.StubConfiguration` :param config: Configuration to be used for creating the stub. """ VapiInterface.__init__(self, config, _ReClassifyStub) def create(self, session_id, session_reclassification_parameter, ): """ Re-classify completed application discovery session against input AppProfiles. If no AppProfiles are specified then we use the previous AppProfiles of that session. :type session_id: :class:`str` :param session_id: (required) :type session_reclassification_parameter: :class:`com.vmware.nsx.model_client.SessionReclassificationParameter` :param session_reclassification_parameter: (required) :rtype: :class:`com.vmware.nsx.model_client.AppDiscoverySessionResultSummary` :return: com.vmware.nsx.model.AppDiscoverySessionResultSummary :raise: :class:`com.vmware.vapi.std.errors_client.ServiceUnavailable` Service Unavailable :raise: :class:`com.vmware.vapi.std.errors_client.InvalidRequest` Bad Request, Precondition Failed :raise: :class:`com.vmware.vapi.std.errors_client.InternalServerError` Internal Server Error :raise: :class:`com.vmware.vapi.std.errors_client.Unauthorized` Forbidden :raise: :class:`com.vmware.vapi.std.errors_client.NotFound` Not Found """ return self._invoke('create', { 'session_id': session_id, 'session_reclassification_parameter': session_reclassification_parameter, }) class Summary(VapiInterface): """ """ _VAPI_SERVICE_ID = 'com.vmware.nsx.app_discovery.sessions.summary' """ Identifier of the service in canonical form. """ def __init__(self, config): """ :type config: :class:`vmware.vapi.bindings.stub.StubConfiguration` :param config: Configuration to be used for creating the stub. """ VapiInterface.__init__(self, config, _SummaryStub) def get(self, session_id, ): """ Returns the summary of the application discovery session :type session_id: :class:`str` :param session_id: (required) :rtype: :class:`com.vmware.nsx.model_client.AppDiscoverySessionResultSummary` :return: com.vmware.nsx.model.AppDiscoverySessionResultSummary :raise: :class:`com.vmware.vapi.std.errors_client.ServiceUnavailable` Service Unavailable :raise: :class:`com.vmware.vapi.std.errors_client.InvalidRequest` Bad Request, Precondition Failed :raise: :class:`com.vmware.vapi.std.errors_client.InternalServerError` Internal Server Error :raise: :class:`com.vmware.vapi.std.errors_client.Unauthorized` Forbidden :raise: :class:`com.vmware.vapi.std.errors_client.NotFound` Not Found """ return self._invoke('get', { 'session_id': session_id, }) class _AppProfilesStub(ApiInterfaceStub): def __init__(self, config): # properties for list operation list_input_type = type.StructType('operation-input', { 'session_id': type.StringType(), 'cursor': type.OptionalType(type.StringType()), 'included_fields': type.OptionalType(type.StringType()), 'page_size': type.OptionalType(type.IntegerType()), 'sort_ascending': type.OptionalType(type.BooleanType()), 'sort_by': type.OptionalType(type.StringType()), }) list_error_dict = { 'com.vmware.vapi.std.errors.service_unavailable': type.ReferenceType('com.vmware.vapi.std.errors_client', 'ServiceUnavailable'), 'com.vmware.vapi.std.errors.invalid_request': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InvalidRequest'), 'com.vmware.vapi.std.errors.internal_server_error': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InternalServerError'), 'com.vmware.vapi.std.errors.unauthorized': type.ReferenceType('com.vmware.vapi.std.errors_client', 'Unauthorized'), 'com.vmware.vapi.std.errors.not_found': type.ReferenceType('com.vmware.vapi.std.errors_client', 'NotFound'), } list_input_value_validator_list = [ ] list_output_validator_list = [ ] list_rest_metadata = OperationRestMetadata( http_method='GET', url_template='/api/v1/app-discovery/sessions/{session-id}/app-profiles', path_variables={ 'session_id': 'session-id', }, query_parameters={ 'cursor': 'cursor', 'included_fields': 'included_fields', 'page_size': 'page_size', 'sort_ascending': 'sort_ascending', 'sort_by': 'sort_by', }, content_type='application/json' ) operations = { 'list': { 'input_type': list_input_type, 'output_type': type.ReferenceType('com.vmware.nsx.model_client', 'AppProfileListResult'), 'errors': list_error_dict, 'input_value_validator_list': list_input_value_validator_list, 'output_validator_list': list_output_validator_list, 'task_type': TaskType.NONE, }, } rest_metadata = { 'list': list_rest_metadata, } ApiInterfaceStub.__init__( self, iface_name='com.vmware.nsx.app_discovery.sessions.app_profiles', config=config, operations=operations, rest_metadata=rest_metadata, is_vapi_rest=False) class _InstalledAppsStub(ApiInterfaceStub): def __init__(self, config): # properties for list operation list_input_type = type.StructType('operation-input', { 'session_id': type.StringType(), 'app_profile_id': type.OptionalType(type.StringType()), 'cursor': type.OptionalType(type.StringType()), 'included_fields': type.OptionalType(type.StringType()), 'page_size': type.OptionalType(type.IntegerType()), 'sort_ascending': type.OptionalType(type.BooleanType()), 'sort_by': type.OptionalType(type.StringType()), 'vm_id': type.OptionalType(type.StringType()), }) list_error_dict = { 'com.vmware.vapi.std.errors.service_unavailable': type.ReferenceType('com.vmware.vapi.std.errors_client', 'ServiceUnavailable'), 'com.vmware.vapi.std.errors.invalid_request': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InvalidRequest'), 'com.vmware.vapi.std.errors.internal_server_error': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InternalServerError'), 'com.vmware.vapi.std.errors.unauthorized': type.ReferenceType('com.vmware.vapi.std.errors_client', 'Unauthorized'), 'com.vmware.vapi.std.errors.not_found': type.ReferenceType('com.vmware.vapi.std.errors_client', 'NotFound'), } list_input_value_validator_list = [ ] list_output_validator_list = [ ] list_rest_metadata = OperationRestMetadata( http_method='GET', url_template='/api/v1/app-discovery/sessions/{session-id}/installed-apps', path_variables={ 'session_id': 'session-id', }, query_parameters={ 'app_profile_id': 'app_profile_id', 'cursor': 'cursor', 'included_fields': 'included_fields', 'page_size': 'page_size', 'sort_ascending': 'sort_ascending', 'sort_by': 'sort_by', 'vm_id': 'vm_id', }, content_type='application/json' ) operations = { 'list': { 'input_type': list_input_type, 'output_type': type.ReferenceType('com.vmware.nsx.model_client', 'AppInfoListResult'), 'errors': list_error_dict, 'input_value_validator_list': list_input_value_validator_list, 'output_validator_list': list_output_validator_list, 'task_type': TaskType.NONE, }, } rest_metadata = { 'list': list_rest_metadata, } ApiInterfaceStub.__init__( self, iface_name='com.vmware.nsx.app_discovery.sessions.installed_apps', config=config, operations=operations, rest_metadata=rest_metadata, is_vapi_rest=False) class _NsGroupsStub(ApiInterfaceStub): def __init__(self, config): # properties for list operation list_input_type = type.StructType('operation-input', { 'session_id': type.StringType(), 'cursor': type.OptionalType(type.StringType()), 'included_fields': type.OptionalType(type.StringType()), 'page_size': type.OptionalType(type.IntegerType()), 'sort_ascending': type.OptionalType(type.BooleanType()), 'sort_by': type.OptionalType(type.StringType()), }) list_error_dict = { 'com.vmware.vapi.std.errors.service_unavailable': type.ReferenceType('com.vmware.vapi.std.errors_client', 'ServiceUnavailable'), 'com.vmware.vapi.std.errors.invalid_request': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InvalidRequest'), 'com.vmware.vapi.std.errors.internal_server_error': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InternalServerError'), 'com.vmware.vapi.std.errors.unauthorized': type.ReferenceType('com.vmware.vapi.std.errors_client', 'Unauthorized'), 'com.vmware.vapi.std.errors.not_found': type.ReferenceType('com.vmware.vapi.std.errors_client', 'NotFound'), } list_input_value_validator_list = [ ] list_output_validator_list = [ ] list_rest_metadata = OperationRestMetadata( http_method='GET', url_template='/api/v1/app-discovery/sessions/{session-id}/ns-groups', path_variables={ 'session_id': 'session-id', }, query_parameters={ 'cursor': 'cursor', 'included_fields': 'included_fields', 'page_size': 'page_size', 'sort_ascending': 'sort_ascending', 'sort_by': 'sort_by', }, content_type='application/json' ) operations = { 'list': { 'input_type': list_input_type, 'output_type': type.ReferenceType('com.vmware.nsx.model_client', 'NSGroupMetaInfoListResult'), 'errors': list_error_dict, 'input_value_validator_list': list_input_value_validator_list, 'output_validator_list': list_output_validator_list, 'task_type': TaskType.NONE, }, } rest_metadata = { 'list': list_rest_metadata, } ApiInterfaceStub.__init__( self, iface_name='com.vmware.nsx.app_discovery.sessions.ns_groups', config=config, operations=operations, rest_metadata=rest_metadata, is_vapi_rest=False) class _ReClassifyStub(ApiInterfaceStub): def __init__(self, config): # properties for create operation create_input_type = type.StructType('operation-input', { 'session_id': type.StringType(), 'session_reclassification_parameter': type.ReferenceType('com.vmware.nsx.model_client', 'SessionReclassificationParameter'), }) create_error_dict = { 'com.vmware.vapi.std.errors.service_unavailable': type.ReferenceType('com.vmware.vapi.std.errors_client', 'ServiceUnavailable'), 'com.vmware.vapi.std.errors.invalid_request': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InvalidRequest'), 'com.vmware.vapi.std.errors.internal_server_error': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InternalServerError'), 'com.vmware.vapi.std.errors.unauthorized': type.ReferenceType('com.vmware.vapi.std.errors_client', 'Unauthorized'), 'com.vmware.vapi.std.errors.not_found': type.ReferenceType('com.vmware.vapi.std.errors_client', 'NotFound'), } create_input_value_validator_list = [ ] create_output_validator_list = [ ] create_rest_metadata = OperationRestMetadata( http_method='POST', url_template='/api/v1/app-discovery/sessions/{session-id}/re-classify', request_body_parameter='session_reclassification_parameter', path_variables={ 'session_id': 'session-id', }, query_parameters={ }, content_type='application/json' ) operations = { 'create': { 'input_type': create_input_type, 'output_type': type.ReferenceType('com.vmware.nsx.model_client', 'AppDiscoverySessionResultSummary'), 'errors': create_error_dict, 'input_value_validator_list': create_input_value_validator_list, 'output_validator_list': create_output_validator_list, 'task_type': TaskType.NONE, }, } rest_metadata = { 'create': create_rest_metadata, } ApiInterfaceStub.__init__( self, iface_name='com.vmware.nsx.app_discovery.sessions.re_classify', config=config, operations=operations, rest_metadata=rest_metadata, is_vapi_rest=False) class _SummaryStub(ApiInterfaceStub): def __init__(self, config): # properties for get operation get_input_type = type.StructType('operation-input', { 'session_id': type.StringType(), }) get_error_dict = { 'com.vmware.vapi.std.errors.service_unavailable': type.ReferenceType('com.vmware.vapi.std.errors_client', 'ServiceUnavailable'), 'com.vmware.vapi.std.errors.invalid_request': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InvalidRequest'), 'com.vmware.vapi.std.errors.internal_server_error': type.ReferenceType('com.vmware.vapi.std.errors_client', 'InternalServerError'), 'com.vmware.vapi.std.errors.unauthorized': type.ReferenceType('com.vmware.vapi.std.errors_client', 'Unauthorized'), 'com.vmware.vapi.std.errors.not_found': type.ReferenceType('com.vmware.vapi.std.errors_client', 'NotFound'), } get_input_value_validator_list = [ ] get_output_validator_list = [ ] get_rest_metadata = OperationRestMetadata( http_method='GET', url_template='/api/v1/app-discovery/sessions/{session-id}/summary', path_variables={ 'session_id': 'session-id', }, query_parameters={ }, content_type='application/json' ) operations = { 'get': { 'input_type': get_input_type, 'output_type': type.ReferenceType('com.vmware.nsx.model_client', 'AppDiscoverySessionResultSummary'), 'errors': get_error_dict, 'input_value_validator_list': get_input_value_validator_list, 'output_validator_list': get_output_validator_list, 'task_type': TaskType.NONE, }, } rest_metadata = { 'get': get_rest_metadata, } ApiInterfaceStub.__init__( self, iface_name='com.vmware.nsx.app_discovery.sessions.summary', config=config, operations=operations, rest_metadata=rest_metadata, is_vapi_rest=False) class StubFactory(StubFactoryBase): _attrs = { 'AppProfiles': AppProfiles, 'InstalledApps': InstalledApps, 'NsGroups': NsGroups, 'ReClassify': ReClassify, 'Summary': Summary, 'ns_groups': 'com.vmware.nsx.app_discovery.sessions.ns_groups_client.StubFactory', }

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a0b967ba667456e32e7ff4e43e7fa76889a809a7

36,728

py

Python

pybind/nos/v7_1_0/monitor/session/span_command/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/nos/v7_1_0/monitor/session/span_command/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/nos/v7_1_0/monitor/session/span_command/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

1

2021-11-05T22:15:42.000Z

from operator import attrgetter import pyangbind.lib.xpathhelper as xpathhelper from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType from pyangbind.lib.base import PybindBase from decimal import Decimal from bitarray import bitarray import __builtin__ class span_command(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module brocade-span - based on the path /monitor/session/span-command. Each member element of the container is represented as a class variable - with a specific YANG type. """ __slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__source','__src_tengigabitethernet','__src_tengigabitethernet_val','__destination','__dest_tengigabitethernet','__dest_tengigabitethernet_val','__dest_vlan_val','__direction',) _yang_name = 'span-command' _rest_name = '' _pybind_generated_by = 'container' def __init__(self, *args, **kwargs): path_helper_ = kwargs.pop("path_helper", None) if path_helper_ is False: self._path_helper = False elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper): self._path_helper = path_helper_ elif hasattr(self, "_parent"): path_helper_ = getattr(self._parent, "_path_helper", False) self._path_helper = path_helper_ else: self._path_helper = False extmethods = kwargs.pop("extmethods", None) if extmethods is False: self._extmethods = False elif extmethods is not None and isinstance(extmethods, dict): self._extmethods = extmethods elif hasattr(self, "_parent"): extmethods = getattr(self._parent, "_extmethods", None) self._extmethods = extmethods else: self._extmethods = False self.__direction = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'both': {'value': 2}, u'rx': {'value': 1}, u'tx': {'value': 0}},), is_leaf=True, yang_name="direction", rest_name="direction", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Mirror Direction:Ingress or Egress or Both', u'cli-optional-in-sequence': None, u'display-when': u"(((../dest-tengigabitethernet = 'gigabitethernet') or\n(../dest-tengigabitethernet = 'tengigabitethernet') or\n(../dest-tengigabitethernet = 'fortygigabitethernet') or\n(../dest-tengigabitethernet = 'rspan-vlan') or \n (../dest-tengigabitethernet = 'hundredgigabitethernet')) and \n(../source))"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) self.__dest_tengigabitethernet_val = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="dest-tengigabitethernet-val", rest_name="dest-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'gigabitethernet' or\n../dest-tengigabitethernet = 'tengigabitethernet' or\n../dest-tengigabitethernet = 'fortygigabitethernet' or\n../dest-tengigabitethernet = 'hundredgigabitethernet'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True) self.__dest_vlan_val = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..8191']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(1), is_leaf=True, yang_name="dest-vlan-val", rest_name="dest-vlan-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'rspan-vlan'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='interface:vlan-type', is_config=True) self.__destination = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'destination': {'value': 0}},), is_leaf=True, yang_name="destination", rest_name="destination", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) self.__src_tengigabitethernet = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="src-tengigabitethernet", rest_name="src-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) self.__source = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'source': {'value': 0}},), is_leaf=True, yang_name="source", rest_name="source", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None, u'cli-optional-in-sequence': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) self.__dest_tengigabitethernet = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'rspan-vlan': {'value': 4}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="dest-tengigabitethernet", rest_name="dest-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) self.__src_tengigabitethernet_val = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="src-tengigabitethernet-val", rest_name="src-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True) load = kwargs.pop("load", None) if args: if len(args) > 1: raise TypeError("cannot create a YANG container with >1 argument") all_attr = True for e in self._pyangbind_elements: if not hasattr(args[0], e): all_attr = False break if not all_attr: raise ValueError("Supplied object did not have the correct attributes") for e in self._pyangbind_elements: nobj = getattr(args[0], e) if nobj._changed() is False: continue setmethod = getattr(self, "_set_%s" % e) if load is None: setmethod(getattr(args[0], e)) else: setmethod(getattr(args[0], e), load=load) def _path(self): if hasattr(self, "_parent"): return self._parent._path()+[self._yang_name] else: return [u'monitor', u'session', u'span-command'] def _rest_path(self): if hasattr(self, "_parent"): if self._rest_name: return self._parent._rest_path()+[self._rest_name] else: return self._parent._rest_path() else: return [u'monitor', u'session'] def _get_source(self): """ Getter method for source, mapped from YANG variable /monitor/session/span_command/source (enumeration) """ return self.__source def _set_source(self, v, load=False): """ Setter method for source, mapped from YANG variable /monitor/session/span_command/source (enumeration) If this variable is read-only (config: false) in the source YANG file, then _set_source is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_source() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'source': {'value': 0}},), is_leaf=True, yang_name="source", rest_name="source", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None, u'cli-optional-in-sequence': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """source must be of a type compatible with enumeration""", 'defined-type': "brocade-span:enumeration", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'source': {'value': 0}},), is_leaf=True, yang_name="source", rest_name="source", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None, u'cli-optional-in-sequence': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True)""", }) self.__source = t if hasattr(self, '_set'): self._set() def _unset_source(self): self.__source = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'source': {'value': 0}},), is_leaf=True, yang_name="source", rest_name="source", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None, u'cli-optional-in-sequence': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) def _get_src_tengigabitethernet(self): """ Getter method for src_tengigabitethernet, mapped from YANG variable /monitor/session/span_command/src_tengigabitethernet (enumeration) """ return self.__src_tengigabitethernet def _set_src_tengigabitethernet(self, v, load=False): """ Setter method for src_tengigabitethernet, mapped from YANG variable /monitor/session/span_command/src_tengigabitethernet (enumeration) If this variable is read-only (config: false) in the source YANG file, then _set_src_tengigabitethernet is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_src_tengigabitethernet() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="src-tengigabitethernet", rest_name="src-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """src_tengigabitethernet must be of a type compatible with enumeration""", 'defined-type': "brocade-span:enumeration", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="src-tengigabitethernet", rest_name="src-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True)""", }) self.__src_tengigabitethernet = t if hasattr(self, '_set'): self._set() def _unset_src_tengigabitethernet(self): self.__src_tengigabitethernet = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="src-tengigabitethernet", rest_name="src-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) def _get_src_tengigabitethernet_val(self): """ Getter method for src_tengigabitethernet_val, mapped from YANG variable /monitor/session/span_command/src_tengigabitethernet_val (span-if-type) """ return self.__src_tengigabitethernet_val def _set_src_tengigabitethernet_val(self, v, load=False): """ Setter method for src_tengigabitethernet_val, mapped from YANG variable /monitor/session/span_command/src_tengigabitethernet_val (span-if-type) If this variable is read-only (config: false) in the source YANG file, then _set_src_tengigabitethernet_val is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_src_tengigabitethernet_val() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="src-tengigabitethernet-val", rest_name="src-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """src_tengigabitethernet_val must be of a type compatible with span-if-type""", 'defined-type': "brocade-span:span-if-type", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="src-tengigabitethernet-val", rest_name="src-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True)""", }) self.__src_tengigabitethernet_val = t if hasattr(self, '_set'): self._set() def _unset_src_tengigabitethernet_val(self): self.__src_tengigabitethernet_val = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="src-tengigabitethernet-val", rest_name="src-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u'(../source)', u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True) def _get_destination(self): """ Getter method for destination, mapped from YANG variable /monitor/session/span_command/destination (enumeration) """ return self.__destination def _set_destination(self, v, load=False): """ Setter method for destination, mapped from YANG variable /monitor/session/span_command/destination (enumeration) If this variable is read-only (config: false) in the source YANG file, then _set_destination is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_destination() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'destination': {'value': 0}},), is_leaf=True, yang_name="destination", rest_name="destination", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """destination must be of a type compatible with enumeration""", 'defined-type': "brocade-span:enumeration", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'destination': {'value': 0}},), is_leaf=True, yang_name="destination", rest_name="destination", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True)""", }) self.__destination = t if hasattr(self, '_set'): self._set() def _unset_destination(self): self.__destination = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'destination': {'value': 0}},), is_leaf=True, yang_name="destination", rest_name="destination", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) def _get_dest_tengigabitethernet(self): """ Getter method for dest_tengigabitethernet, mapped from YANG variable /monitor/session/span_command/dest_tengigabitethernet (enumeration) """ return self.__dest_tengigabitethernet def _set_dest_tengigabitethernet(self, v, load=False): """ Setter method for dest_tengigabitethernet, mapped from YANG variable /monitor/session/span_command/dest_tengigabitethernet (enumeration) If this variable is read-only (config: false) in the source YANG file, then _set_dest_tengigabitethernet is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_dest_tengigabitethernet() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'rspan-vlan': {'value': 4}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="dest-tengigabitethernet", rest_name="dest-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """dest_tengigabitethernet must be of a type compatible with enumeration""", 'defined-type': "brocade-span:enumeration", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'rspan-vlan': {'value': 4}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="dest-tengigabitethernet", rest_name="dest-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True)""", }) self.__dest_tengigabitethernet = t if hasattr(self, '_set'): self._set() def _unset_dest_tengigabitethernet(self): self.__dest_tengigabitethernet = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'fortygigabitethernet': {'value': 2}, u'rspan-vlan': {'value': 4}, u'gigabitethernet': {'value': 0}, u'tengigabitethernet': {'value': 1}, u'hundredgigabitethernet': {'value': 3}},), is_leaf=True, yang_name="dest-tengigabitethernet", rest_name="dest-tengigabitethernet", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) def _get_dest_tengigabitethernet_val(self): """ Getter method for dest_tengigabitethernet_val, mapped from YANG variable /monitor/session/span_command/dest_tengigabitethernet_val (span-if-type) """ return self.__dest_tengigabitethernet_val def _set_dest_tengigabitethernet_val(self, v, load=False): """ Setter method for dest_tengigabitethernet_val, mapped from YANG variable /monitor/session/span_command/dest_tengigabitethernet_val (span-if-type) If this variable is read-only (config: false) in the source YANG file, then _set_dest_tengigabitethernet_val is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_dest_tengigabitethernet_val() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="dest-tengigabitethernet-val", rest_name="dest-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'gigabitethernet' or\n../dest-tengigabitethernet = 'tengigabitethernet' or\n../dest-tengigabitethernet = 'fortygigabitethernet' or\n../dest-tengigabitethernet = 'hundredgigabitethernet'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """dest_tengigabitethernet_val must be of a type compatible with span-if-type""", 'defined-type': "brocade-span:span-if-type", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="dest-tengigabitethernet-val", rest_name="dest-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'gigabitethernet' or\n../dest-tengigabitethernet = 'tengigabitethernet' or\n../dest-tengigabitethernet = 'fortygigabitethernet' or\n../dest-tengigabitethernet = 'hundredgigabitethernet'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True)""", }) self.__dest_tengigabitethernet_val = t if hasattr(self, '_set'): self._set() def _unset_dest_tengigabitethernet_val(self): self.__dest_tengigabitethernet_val = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'3..16']}), is_leaf=True, yang_name="dest-tengigabitethernet-val", rest_name="dest-tengigabitethernet-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'gigabitethernet' or\n../dest-tengigabitethernet = 'tengigabitethernet' or\n../dest-tengigabitethernet = 'fortygigabitethernet' or\n../dest-tengigabitethernet = 'hundredgigabitethernet'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='span-if-type', is_config=True) def _get_dest_vlan_val(self): """ Getter method for dest_vlan_val, mapped from YANG variable /monitor/session/span_command/dest_vlan_val (interface:vlan-type) """ return self.__dest_vlan_val def _set_dest_vlan_val(self, v, load=False): """ Setter method for dest_vlan_val, mapped from YANG variable /monitor/session/span_command/dest_vlan_val (interface:vlan-type) If this variable is read-only (config: false) in the source YANG file, then _set_dest_vlan_val is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_dest_vlan_val() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..8191']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(1), is_leaf=True, yang_name="dest-vlan-val", rest_name="dest-vlan-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'rspan-vlan'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='interface:vlan-type', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """dest_vlan_val must be of a type compatible with interface:vlan-type""", 'defined-type': "interface:vlan-type", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..8191']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(1), is_leaf=True, yang_name="dest-vlan-val", rest_name="dest-vlan-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'rspan-vlan'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='interface:vlan-type', is_config=True)""", }) self.__dest_vlan_val = t if hasattr(self, '_set'): self._set() def _unset_dest_vlan_val(self): self.__dest_vlan_val = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..8191']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(1), is_leaf=True, yang_name="dest-vlan-val", rest_name="dest-vlan-val", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'display-when': u"../dest-tengigabitethernet = 'rspan-vlan'"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='interface:vlan-type', is_config=True) def _get_direction(self): """ Getter method for direction, mapped from YANG variable /monitor/session/span_command/direction (enumeration) """ return self.__direction def _set_direction(self, v, load=False): """ Setter method for direction, mapped from YANG variable /monitor/session/span_command/direction (enumeration) If this variable is read-only (config: false) in the source YANG file, then _set_direction is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_direction() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'both': {'value': 2}, u'rx': {'value': 1}, u'tx': {'value': 0}},), is_leaf=True, yang_name="direction", rest_name="direction", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Mirror Direction:Ingress or Egress or Both', u'cli-optional-in-sequence': None, u'display-when': u"(((../dest-tengigabitethernet = 'gigabitethernet') or\n(../dest-tengigabitethernet = 'tengigabitethernet') or\n(../dest-tengigabitethernet = 'fortygigabitethernet') or\n(../dest-tengigabitethernet = 'rspan-vlan') or \n (../dest-tengigabitethernet = 'hundredgigabitethernet')) and \n(../source))"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """direction must be of a type compatible with enumeration""", 'defined-type': "brocade-span:enumeration", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'both': {'value': 2}, u'rx': {'value': 1}, u'tx': {'value': 0}},), is_leaf=True, yang_name="direction", rest_name="direction", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Mirror Direction:Ingress or Egress or Both', u'cli-optional-in-sequence': None, u'display-when': u"(((../dest-tengigabitethernet = 'gigabitethernet') or\n(../dest-tengigabitethernet = 'tengigabitethernet') or\n(../dest-tengigabitethernet = 'fortygigabitethernet') or\n(../dest-tengigabitethernet = 'rspan-vlan') or \n (../dest-tengigabitethernet = 'hundredgigabitethernet')) and \n(../source))"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True)""", }) self.__direction = t if hasattr(self, '_set'): self._set() def _unset_direction(self): self.__direction = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'both': {'value': 2}, u'rx': {'value': 1}, u'tx': {'value': 0}},), is_leaf=True, yang_name="direction", rest_name="direction", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Mirror Direction:Ingress or Egress or Both', u'cli-optional-in-sequence': None, u'display-when': u"(((../dest-tengigabitethernet = 'gigabitethernet') or\n(../dest-tengigabitethernet = 'tengigabitethernet') or\n(../dest-tengigabitethernet = 'fortygigabitethernet') or\n(../dest-tengigabitethernet = 'rspan-vlan') or \n (../dest-tengigabitethernet = 'hundredgigabitethernet')) and \n(../source))"}}, namespace='urn:brocade.com:mgmt:brocade-span', defining_module='brocade-span', yang_type='enumeration', is_config=True) source = __builtin__.property(_get_source, _set_source) src_tengigabitethernet = __builtin__.property(_get_src_tengigabitethernet, _set_src_tengigabitethernet) src_tengigabitethernet_val = __builtin__.property(_get_src_tengigabitethernet_val, _set_src_tengigabitethernet_val) destination = __builtin__.property(_get_destination, _set_destination) dest_tengigabitethernet = __builtin__.property(_get_dest_tengigabitethernet, _set_dest_tengigabitethernet) dest_tengigabitethernet_val = __builtin__.property(_get_dest_tengigabitethernet_val, _set_dest_tengigabitethernet_val) dest_vlan_val = __builtin__.property(_get_dest_vlan_val, _set_dest_vlan_val) direction = __builtin__.property(_get_direction, _set_direction) _pyangbind_elements = {'source': source, 'src_tengigabitethernet': src_tengigabitethernet, 'src_tengigabitethernet_val': src_tengigabitethernet_val, 'destination': destination, 'dest_tengigabitethernet': dest_tengigabitethernet, 'dest_tengigabitethernet_val': dest_tengigabitethernet_val, 'dest_vlan_val': dest_vlan_val, 'direction': direction, }

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100.076294

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0

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264eb499c72e7bcbba58cd6e3b0dcfe130eb67ce

116,246

py

Python

chars.py

idootop/qz_killer

ae05da9cec9aab1bfcd6a86f527442ee38f0b40a

[ "MIT" ]

4

2019-12-23T07:13:33.000Z

2021-02-21T08:44:40.000Z

chars.py

idootop/qz_killer

ae05da9cec9aab1bfcd6a86f527442ee38f0b40a

[ "MIT" ]

null

chars.py

idootop/qz_killer

ae05da9cec9aab1bfcd6a86f527442ee38f0b40a

[ "MIT" ]

null

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cd143c21716d1b02c861cacac4877aa6df7731e2

810

py

Python

Python/M01_ProgrammingBasics/L03_ConditionalStatementsAdvanced/Exercises/Solutions/P06_OperationsBetweenNumbers.py

todorkrastev/softuni-software-engineering

cfc0b5eaeb82951ff4d4668332ec3a31c59a5f84

[ "MIT" ]

null

Python/M01_ProgrammingBasics/L03_ConditionalStatementsAdvanced/Exercises/Solutions/P06_OperationsBetweenNumbers.py

todorkrastev/softuni-software-engineering

cfc0b5eaeb82951ff4d4668332ec3a31c59a5f84

[ "MIT" ]

null

Python/M01_ProgrammingBasics/L03_ConditionalStatementsAdvanced/Exercises/Solutions/P06_OperationsBetweenNumbers.py

todorkrastev/softuni-software-engineering

cfc0b5eaeb82951ff4d4668332ec3a31c59a5f84

[ "MIT" ]

1

2022-02-23T13:03:14.000Z

N1 = int(input()) N2 = int(input()) operator = input() if operator == "+" and (N1 + N2) % 2 == 0: print(f'{N1} + {N2} = {N1 + N2} - even') elif operator == "+" and (N1 + N2) % 2 != 0: print(f'{N1} + {N2} = {N1 + N2} - odd') elif operator == "-" and (N1 - N2) % 2 == 0: print(f'{N1} - {N2} = {N1 - N2} - even') elif operator == "-" and (N1 - N2) % 2 != 0: print(f'{N1} - {N2} = {N1 - N2} - odd') elif operator == "*" and (N1 * N2) % 2 == 0: print(f'{N1} * {N2} = {N1 * N2} - even') elif operator == "*" and (N1 * N2) % 2 != 0: print(f'{N1} * {N2} = {N1 * N2} - odd') elif (operator == "/" or operator == "%") and N2 == 0: print(f'Cannot divide {N1} by zero') elif operator == "/": print(f'{N1} / {N2} = {N1 / N2:.2f}') elif operator == "%": print(f'{N1} % {N2} = {N1 % N2}')

36.818182

54

0.45679

123

810

3.00813

0.162602

0.237838

0.172973

0.216216

0.786486

0.645946

0

0.103333

0.259259

810

22

55

36.818182

0.513333

0

0.324291

0

1

0

false

0

0.428571

0

null

1

0

1

0

1

0

1

0

null

0

1

0

7

26ad56b7d11869adeaf2b4463b22dd898dd0c475

35

py

Python

lib/python3.4/site-packages/flask/testsuite/test_apps/flaskext/oldext_package/submodule.py

LChristakis/chalice-hunter

6bffea4620e23ce9ff12ac30526ebafcb9c10058

[ "MIT" ]

21,684

2015-01-01T03:42:20.000Z

2022-03-30T13:32:44.000Z

lib/python3.4/site-packages/flask/testsuite/test_apps/flaskext/oldext_package/submodule.py

LChristakis/chalice-hunter

6bffea4620e23ce9ff12ac30526ebafcb9c10058

[ "MIT" ]

4,067

2015-01-01T00:04:51.000Z

2022-03-30T13:42:56.000Z

lib/python3.4/site-packages/flask/testsuite/test_apps/flaskext/oldext_package/submodule.py

LChristakis/chalice-hunter

6bffea4620e23ce9ff12ac30526ebafcb9c10058

[ "MIT" ]

1,901

2015-01-01T21:05:59.000Z

2022-03-21T08:14:25.000Z

def test_function(): return 42

11.666667

20

0.685714

5

35

4.6

1

0

0.074074

0.228571

35

2

21

17.5

0.777778

0

1

0.5

true

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

7

e47da2d93ac65b12a253a6a652446fefced808ed

57

py

Python

app/stocks/config.py

Monxun/DjangoMLDocker

f34ddbc2f504054ed32ed1fb66a0a77c461350dd

[ "MIT" ]

null

app/stocks/config.py

Monxun/DjangoMLDocker

f34ddbc2f504054ed32ed1fb66a0a77c461350dd

[ "MIT" ]

null

app/stocks/config.py

Monxun/DjangoMLDocker

f34ddbc2f504054ed32ed1fb66a0a77c461350dd

[ "MIT" ]

null

tiingo_token = '7805c033e3cd1d7e1b3aa071522e811893a28676'

57

0.912281

3

57

17

1

0

0.527273

0.035088

57

1

57

0.4

0

0.689655

0

1

0

false

0

1

0

1

null

0

1

0

1

0

1

0

1

null

0

7

e4a56c8f65d045b5b2f1c7c30f44299ba89dcbd1

25,123

py

Python

etl/sql_scripts.py

ClinicalTrialsTeam/CTFrontier

d7e2558f314f6bbd9964667e12ee5655bc64215b

[ "Apache-2.0" ]

4

2021-03-07T02:16:22.000Z

2022-03-13T03:22:42.000Z

etl/sql_scripts.py

ClinicalTrialsTeam/CTFrontier

d7e2558f314f6bbd9964667e12ee5655bc64215b

[ "Apache-2.0" ]

8

2021-03-14T22:14:07.000Z

2021-04-26T17:20:56.000Z

etl/sql_scripts.py

ClinicalTrialsTeam/CTFrontier

d7e2558f314f6bbd9964667e12ee5655bc64215b

[ "Apache-2.0" ]

1

2021-03-07T02:16:39.000Z

class SqlScripts: last_run_date = """ SELECT last_run_date FROM ctgov.etl """ update_count_from_ctti = """ SELECT COUNT(*) FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s | UPDATE ctgov.etl SET update_max_rows = %s """ insert_count_from_ctti = """ SELECT COUNT(*) FROM ctgov.studies WHERE study_first_submitted_date >= %s | UPDATE ctgov.etl SET insert_max_rows = %s """ get_etl_metadata = """ SELECT last_run_date, insert_current_offset, insert_max_rows, update_current_offset, update_max_rows FROM ctgov.etl """ insert_studies = """ SELECT nct_id, nlm_download_date_description, study_first_submitted_date, results_first_submitted_date, disposition_first_submitted_date, last_update_submitted_date, study_first_submitted_qc_date, study_first_posted_date, study_first_posted_date_type, results_first_submitted_qc_date, results_first_posted_date, results_first_posted_date_type, disposition_first_submitted_qc_date, disposition_first_posted_date, disposition_first_posted_date_type, last_update_submitted_qc_date, last_update_posted_date, last_update_posted_date_type, start_month_year, start_date_type, start_date, verification_month_year, verification_date, completion_month_year, completion_date_type, completion_date, primary_completion_month_year, primary_completion_date_type, primary_completion_date, target_duration, study_type, acronym, baseline_population, brief_title, official_title, overall_status, last_known_status, phase, enrollment, enrollment_type, source, limitations_and_caveats, number_of_arms, number_of_groups, why_stopped, has_expanded_access, expanded_access_type_individual, expanded_access_type_intermediate, expanded_access_type_treatment, has_dmc, is_fda_regulated_drug, is_fda_regulated_device, is_unapproved_device, is_ppsd, is_us_export, biospec_retention, biospec_description, ipd_time_frame, ipd_access_criteria, ipd_url, plan_to_share_ipd, plan_to_share_ipd_description, created_at, updated_at FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s | INSERT INTO ctgov.studies(nct_id, nlm_download_date_description, study_first_submitted_date, results_first_submitted_date, disposition_first_submitted_date, last_update_submitted_date, study_first_submitted_qc_date, study_first_posted_date, study_first_posted_date_type, results_first_submitted_qc_date, results_first_posted_date, results_first_posted_date_type, disposition_first_submitted_qc_date, disposition_first_posted_date, disposition_first_posted_date_type, last_update_submitted_qc_date, last_update_posted_date, last_update_posted_date_type, start_month_year, start_date_type, start_date, verification_month_year, verification_date, completion_month_year, completion_date_type, completion_date, primary_completion_month_year, primary_completion_date_type, primary_completion_date, target_duration, study_type, acronym, baseline_population, brief_title, official_title, overall_status, last_known_status, phase, enrollment, enrollment_type, source, limitations_and_caveats, number_of_arms, number_of_groups, why_stopped, has_expanded_access, expanded_access_type_individual, expanded_access_type_intermediate, expanded_access_type_treatment, has_dmc, is_fda_regulated_drug, is_fda_regulated_device, is_unapproved_device, is_ppsd, is_us_export, biospec_retention, biospec_description, ipd_time_frame, ipd_access_criteria, ipd_url, plan_to_share_ipd, plan_to_share_ipd_description, created_at, updated_at) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s); """ update_studies = """ SELECT nlm_download_date_description, study_first_submitted_date, results_first_submitted_date, disposition_first_submitted_date, last_update_submitted_date, study_first_submitted_qc_date, study_first_posted_date, study_first_posted_date_type, results_first_submitted_qc_date, results_first_posted_date, results_first_posted_date_type, disposition_first_submitted_qc_date, disposition_first_posted_date, disposition_first_posted_date_type, last_update_submitted_qc_date, last_update_posted_date, last_update_posted_date_type, start_month_year, start_date_type, start_date, verification_month_year, verification_date, completion_month_year, completion_date_type, completion_date, primary_completion_month_year, primary_completion_date_type, primary_completion_date, target_duration, study_type, acronym, baseline_population, brief_title, official_title, overall_status, last_known_status, phase, enrollment, enrollment_type, source, limitations_and_caveats, number_of_arms, number_of_groups, why_stopped, has_expanded_access, expanded_access_type_individual, expanded_access_type_intermediate, expanded_access_type_treatment, has_dmc, is_fda_regulated_drug, is_fda_regulated_device, is_unapproved_device, is_ppsd, is_us_export, biospec_retention, biospec_description, ipd_time_frame, ipd_access_criteria, ipd_url, plan_to_share_ipd, plan_to_share_ipd_description, created_at, updated_at, nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s | UPDATE ctgov.studies SET nlm_download_date_description=%s, study_first_submitted_date=%s, results_first_submitted_date=%s, disposition_first_submitted_date=%s, last_update_submitted_date=%s, study_first_submitted_qc_date=%s, study_first_posted_date=%s, study_first_posted_date_type=%s, results_first_submitted_qc_date=%s, results_first_posted_date=%s, results_first_posted_date_type=%s, disposition_first_submitted_qc_date=%s, disposition_first_posted_date=%s, disposition_first_posted_date_type=%s, last_update_submitted_qc_date=%s, last_update_posted_date=%s, last_update_posted_date_type=%s, start_month_year=%s, start_date_type=%s, start_date=%s, verification_month_year=%s, verification_date=%s, completion_month_year=%s, completion_date_type=%s, completion_date=%s, primary_completion_month_year=%s, primary_completion_date_type=%s, primary_completion_date=%s, target_duration=%s, study_type=%s, acronym=%s, baseline_population=%s, brief_title=%s, official_title=%s, overall_status=%s, last_known_status=%s, phase=%s, enrollment=%s, enrollment_type=%s, source=%s, limitations_and_caveats=%s, number_of_arms=%s, number_of_groups=%s, why_stopped=%s, has_expanded_access=%s, expanded_access_type_individual=%s, expanded_access_type_intermediate=%s, expanded_access_type_treatment=%s, has_dmc=%s, is_fda_regulated_drug=%s, is_fda_regulated_device=%s, is_unapproved_device=%s, is_ppsd=%s, is_us_export=%s, biospec_retention=%s, biospec_description=%s, ipd_time_frame=%s, ipd_access_criteria=%s, ipd_url=%s, plan_to_share_ipd=%s, plan_to_share_ipd_description=%s, created_at=%s, updated_at=%s WHERE nct_id = %s; """ insert_conditions = """ SELECT id, nct_id, name, downcase_name FROM ctgov.conditions WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.conditions(id, nct_id, name, downcase_name) VALUES (%s, %s, %s, %s); """ update_conditions = """ SELECT name, downcase_name, id FROM ctgov.conditions WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.conditions SET name=%s, downcase_name=%s WHERE id = %s """ insert_detailed_descriptions = """ SELECT id, nct_id, description FROM ctgov.detailed_descriptions WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.detailed_descriptions(id, nct_id, description) VALUES (%s, %s, %s) """ update_detailed_descriptions = """ SELECT description, id FROM ctgov.detailed_descriptions WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.detailed_descriptions SET description= %s WHERE id = %s """ insert_countries = """ SELECT id, nct_id, name, removed FROM ctgov.countries WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.countries(id, nct_id, name, removed) VALUES (%s, %s, %s, %s); """ update_countries = """ SELECT name, removed, id FROM ctgov.countries WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.countries SET name= %s, removed= %s WHERE id = %s; """ insert_interventions = """ SELECT id, nct_id, intervention_type, name, description FROM ctgov.interventions WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.interventions (id, nct_id, intervention_type, name, description) VALUES (%s, %s, %s, %s, %s); """ update_interventions = """ SELECT intervention_type, name, description, id FROM ctgov.interventions WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.interventions SET intervention_type=%s, name=%s, description=%s WHERE id = %s; """ insert_keywords = """ SELECT id, nct_id, name, downcase_name FROM ctgov.keywords WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.keywords(id, nct_id, name, downcase_name) VALUES (%s, %s, %s, %s); """ update_keywords = """ SELECT name, downcase_name, id FROM ctgov.keywords WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.keywords SET name=%s, downcase_name=%s WHERE id = %s; """ insert_eligibilities = """ SELECT id, nct_id, sampling_method, gender, minimum_age, maximum_age, healthy_volunteers, population, criteria, gender_description, gender_based FROM ctgov.eligibilities WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.eligibilities(id, nct_id, sampling_method, gender, minimum_age, maximum_age, healthy_volunteers, population, criteria, gender_description, gender_based) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s); """ update_eligibilities = """ SELECT sampling_method, gender, minimum_age, maximum_age, healthy_volunteers, population, criteria, gender_description, gender_based, id FROM ctgov.eligibilities WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.eligibilities SET sampling_method=%s, gender=%s, minimum_age=%s, maximum_age=%s, healthy_volunteers=%s, population=%s, criteria=%s, gender_description=%s, gender_based=%s WHERE id = %s; """ insert_facilities = """ SELECT id, nct_id, status, name, city, state, zip, country FROM ctgov.facilities WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.facilities( id, nct_id, status, name, city, state, zip, country) VALUES (%s, %s, %s, %s, %s, %s, %s, %s); """ update_facilities = """ SELECT status, name, city, state, zip, country, id FROM ctgov.facilities WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.facilities SET status=%s, name=%s, city=%s, state=%s, zip=%s, country=%s WHERE id = %s; """ insert_brief_summaries = """ SELECT id, nct_id, description FROM ctgov.brief_summaries WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.brief_summaries(id, nct_id, description) VALUES (%s, %s, %s); """ update_brief_summaries = """ SELECT description, id FROM ctgov.brief_summaries WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.brief_summaries SET description=%s WHERE id = %s; """ insert_sponsors = """ SELECT id, nct_id, agency_class, lead_or_collaborator, name FROM ctgov.sponsors WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.sponsors( id, nct_id, agency_class, lead_or_collaborator, name) VALUES (%s, %s, %s, %s, %s); """ update_sponsors = """ SELECT agency_class, lead_or_collaborator, name, id FROM ctgov.sponsors WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.sponsors SET agency_class=%s, lead_or_collaborator=%s, name=%s WHERE id = %s; """ # Handle Deletes insert_outcomes = """ SELECT id, nct_id, outcome_type, title, description, time_frame, population, anticipated_posting_date, anticipated_posting_month_year, units, units_analyzed, dispersion_type, param_type FROM ctgov.outcomes WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.outcomes( id, nct_id, outcome_type, title, description, time_frame, population, anticipated_posting_date, anticipated_posting_month_year, units, units_analyzed, dispersion_type, param_type) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s); """ update_outcomes = """ SELECT outcome_type, title, description, time_frame, population, anticipated_posting_date, anticipated_posting_month_year, units, units_analyzed, dispersion_type, param_type, id FROM ctgov.outcomes WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.outcomes SET outcome_type=%s, title=%s, description=%s, time_frame=%s, population=%s, anticipated_posting_date=%s, anticipated_posting_month_year=%s, units=%s, units_analyzed=%s, dispersion_type=%s, param_type=%s WHERE id = %s; """ insert_results_groups = """ SELECT id, nct_id, ctgov_group_code, result_type, title, description FROM ctgov.result_groups WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.result_groups( id, nct_id, ctgov_group_code, result_type, title, description) VALUES (%s, %s, %s, %s, %s, %s); """ update_results_groups = """ SELECT ctgov_group_code, result_type, title, description, id FROM ctgov.result_groups WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.result_groups SET ctgov_group_code=%s, result_type=%s, title=%s, description=%s WHERE id = %s; """ insert_outcome_measures = """ SELECT id, nct_id, outcome_id, result_group_id, ctgov_group_code, classification, category, title, description, units, param_type, param_value, param_value_num, dispersion_type, dispersion_value, dispersion_value_num, dispersion_lower_limit, dispersion_upper_limit, explanation_of_na FROM ctgov.outcome_measurements WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.outcome_measurements( id, nct_id, outcome_id, result_group_id, ctgov_group_code, classification, category, title, description, units, param_type, param_value, param_value_num, dispersion_type, dispersion_value, dispersion_value_num, dispersion_lower_limit, dispersion_upper_limit, explanation_of_na) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s); """ update_outcome_measures = """ SELECT outcome_id, result_group_id, ctgov_group_code, classification, category, title, description, units, param_type, param_value, param_value_num, dispersion_type, dispersion_value, dispersion_value_num, dispersion_lower_limit, dispersion_upper_limit, explanation_of_na, id FROM ctgov.outcome_measurements WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.outcome_measurements SET outcome_id=%s, result_group_id=%s, ctgov_group_code=%s, classification=%s, category=%s, title=%s, description=%s, units=%s, param_type=%s, param_value=%s, param_value_num=%s, dispersion_type=%s, dispersion_value=%s, dispersion_value_num=%s, dispersion_lower_limit=%s, dispersion_upper_limit=%s, explanation_of_na=%s WHERE id = %s; """ insert_id_information = """ SELECT id, nct_id, id_type, id_value FROM ctgov.id_information WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.id_information(id, nct_id, id_type, id_value) VALUES (%s, %s, %s, %s); """ update_id_information = """ SELECT id_type, id_value, id FROM ctgov.id_information WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.id_information SET id_type=%s, id_value=%s WHERE id = %s; """ insert_documents = """ SELECT id, nct_id, document_id, document_type, url, comment FROM ctgov.documents WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE study_first_submitted_date >= %s ORDER BY created_at LIMIT %s OFFSET %s) | INSERT INTO ctgov.documents( id, nct_id, document_id, document_type, url, comment) VALUES (%s, %s, %s, %s, %s, %s); """ update_documents = """ SELECT document_id, document_type, url, comment, id FROM ctgov.documents WHERE nct_id IN (SELECT nct_id FROM ctgov.studies WHERE last_update_submitted_date >= %s AND study_first_submitted_date < %s ORDER BY created_at LIMIT %s OFFSET %s) | UPDATE ctgov.documents SET document_id=%s, document_type=%s, url=%s, comment=%s WHERE id = %s; """ update_last_run_date = """ UPDATE ctgov.etl SET last_run_date = %s """ rebuild_search_studies = """ REFRESH MATERIALIZED VIEW ctgov.search_studies """ rebuild_all_sponsors_type = """ REFRESH MATERIALIZED VIEW ctgov.all_sponsors_type """ rebuild_all_documents = """ REFRESH MATERIALIZED VIEW ctgov.all_documents """

41.801997

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0.599968

2,956

25,123

4.728349

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0.027903

0.032911

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0.745367

0.716892

0.714316

0.678472

0

0.325479

25,123

600

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41.871667

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null

0

1

0

1

0

null

0

7

e4f37bf7eeedb679f1866cb93d39b9dc1c1aaa19

639

py

Python

tools/accuracy_checker/__init__.py

shinh/dldt

693ab4e79a428e0801f17f4511b129a3fa8f4a62

[ "Apache-2.0" ]

1

2021-02-20T21:48:36.000Z

tools/accuracy_checker/__init__.py

erinpark33/dldt

edd86d090592f7779f4dbb2681546e1f4e81284f

[ "Apache-2.0" ]

null

tools/accuracy_checker/__init__.py

erinpark33/dldt

edd86d090592f7779f4dbb2681546e1f4e81284f

[ "Apache-2.0" ]

1

2021-02-19T01:06:12.000Z

from .accuracy_checker import ( annotation_converters, adapters, config, data_readers, launcher, metrics, postprocessor, preprocessor, representation, dataset, dependency, logging, main, model_evaluator, presenters, progress_reporters, utils ) __all__ = [ 'annotation_converters', 'adapters', 'config', 'data_readers', 'launcher', 'metrics', 'postprocessor', 'preprocessor', 'representation', 'dataset', 'dependency', 'logging', 'main', 'model_evaluator', 'presenters', 'progress_reporters', 'utils' ]

15.975

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639

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0.149733

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0.026316

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null

0

1

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null

0

7

902948b991c801ef769b540922a6d6536cafe4fc

1,401

py

Python

test/TestDasTime.py

Septaris/das2py

ee657afe706f4aec6e016b17b63a093ed271f7f6

[ "MIT" ]

null

test/TestDasTime.py

Septaris/das2py

ee657afe706f4aec6e016b17b63a093ed271f7f6

[ "MIT" ]

null

test/TestDasTime.py

Septaris/das2py

ee657afe706f4aec6e016b17b63a093ed271f7f6

[ "MIT" ]

null

import das2 import unittest class TestDasTime(unittest.TestCase): def test_floor(self): dt1 = das2.DasTime('2014-01-01T12:57:34.445') dt2 = das2.DasTime('2014-01-01T12:57') dt1.floor(60) self.assertEqual(dt1, dt2) dt1 = das2.DasTime('2014-01-01T12:57:34.445') dt2 = das2.DasTime('2014-01-01T12:57:30') dt1.floor(25) self.assertEqual(dt1, dt2) dt1 = das2.DasTime('2014-01-01T12:57:34.445') dt2 = das2.DasTime('2014-01-01T12:50') dt1.floor(600) self.assertEqual(dt1, dt2) dt1 = das2.DasTime('2014-01-01T12:57:34.445') dt2 = das2.DasTime('2014-01-01T12:40') dt1.floor(1200) self.assertEqual(dt1, dt2) dt1 = das2.DasTime('2014-01-01T12:57:34.445') dt2 = das2.DasTime('2014-01-01T12:00') dt1.floor(3600) self.assertEqual(dt1, dt2) def test_ceil(self): dt1 = das2.DasTime('2014-01-01T12:07:34.445') dt2 = das2.DasTime('2014-01-01T12:08') dt1.ceil(60) self.assertEqual(dt1, dt2) dt1 = das2.DasTime('2014-01-01T12:07:34.445') dt2 = das2.DasTime('2014-01-01T12:10') dt1.ceil(600) self.assertEqual(dt1, dt2) dt1 = das2.DasTime('2014-01-01T12:07:34.445') dt2 = das2.DasTime('2014-01-01T12:20') dt1.ceil(1200) self.assertEqual(dt1, dt2) dt1 = das2.DasTime('2014-01-01T12:07:34.445') dt2 = das2.DasTime('2014-01-01T13:00') dt1.ceil(3600) self.assertEqual(dt1, dt2) if __name__ == '__main__': unittest.main()

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0.668808

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0.79288

0.738943

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0.144183

1,401

57

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1

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1

0

1

0

null

0

10

903e3441c05cc7bda0f6a746497f38127133ab56

165

py

Python

config/__init__.py

AbhishekRana23/TeleTor

864d528b3afbb12ac03d371e866475801ee5e0ab

[ "Apache-2.0" ]

69

2018-11-30T11:22:50.000Z

2021-12-05T20:30:53.000Z

config/__init__.py

AbhishekRana23/TeleTor

864d528b3afbb12ac03d371e866475801ee5e0ab

[ "Apache-2.0" ]

2

2019-02-24T09:33:25.000Z

2020-03-23T12:52:17.000Z

config/__init__.py

AbhishekRana23/TeleTor

864d528b3afbb12ac03d371e866475801ee5e0ab

[ "Apache-2.0" ]

28

2019-03-28T16:32:00.000Z

2022-02-07T13:14:24.000Z

from .settings import telegram_bot, LOG_LEVEL, auth_cfg, torrents_cfg, favourites __all__ = ['telegram_bot', 'LOG_LEVEL', 'auth_cfg', 'torrents_cfg', 'favourites']

41.25

81

0.769697

22

165

5.227273

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0.191304

0.243478

0.330435

0.817391

0

0.09697

165

3

82

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false

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0.5

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1

0

1

0

null

0

1

0

10

5f3faf1058464a7354fde6f57ee8e62eb344bd30

10,161

py

Python

app/tests/routers/test_stars.py

NewShadesDAO/api

1e66336f0ea526f245918ecdc328c9a66280be91

[ "CC0-1.0" ]

1

2022-03-21T07:37:02.000Z

app/tests/routers/test_stars.py

NewShadesDAO/api

1e66336f0ea526f245918ecdc328c9a66280be91

[ "CC0-1.0" ]

25

2022-01-16T13:18:21.000Z

2022-03-29T13:08:19.000Z

app/tests/routers/test_stars.py

NewShadesDAO/api

1e66336f0ea526f245918ecdc328c9a66280be91

[ "CC0-1.0" ]

1

2022-01-15T21:42:00.000Z

from typing import Callable import pytest from fastapi import FastAPI from httpx import AsyncClient from pymongo.database import Database from app.models.channel import Channel from app.models.message import Message from app.models.server import Server from app.models.user import User class TestStarsRoutes: @pytest.mark.asyncio async def test_create_star_channel_message( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, channel_message: Message ): data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 json_response = response.json() assert json_response["type"] == "message" assert json_response["message"] == str(channel_message.id) @pytest.mark.asyncio async def test_create_star_dm( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, direct_message: Message ): data = {"message": str(direct_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 json_response = response.json() assert json_response["type"] == "message" assert json_response["message"] == str(direct_message.id) @pytest.mark.asyncio async def test_create_star_server_channel( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, server_channel: Channel ): data = {"channel": str(server_channel.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 json_response = response.json() assert json_response["type"] == "channel" assert json_response["channel"] == str(server_channel.id) @pytest.mark.asyncio async def test_create_star_dm_channel( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, dm_channel: Channel ): data = {"channel": str(dm_channel.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 json_response = response.json() assert json_response["type"] == "channel" assert json_response["channel"] == str(dm_channel.id) @pytest.mark.asyncio async def test_create_star_server( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, server: Server ): data = {"server": str(server.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 json_response = response.json() assert json_response["type"] == "server" assert json_response["server"] == str(server.id) @pytest.mark.asyncio async def test_create_star_random( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient ): data = {"random": "whatevz"} response = await authorized_client.post("/stars", json=data) assert response.status_code == 400 @pytest.mark.asyncio async def test_create_star_multiple_times( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, channel_message: Message ): data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 1 response = await authorized_client.post("/stars", json=data) assert response.status_code == 400 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 1 @pytest.mark.asyncio async def test_create_same_star_multiple_users( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, guest_user: User, get_authorized_client: Callable, channel_message: Message, ): data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 1 guest_client = await get_authorized_client(guest_user) response = await guest_client.post("/stars", json=data) assert response.status_code == 201 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 1 guest_stars = (await guest_client.get("/stars")).json() assert len(guest_stars) == 1 @pytest.mark.asyncio async def test_list_stars( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, channel_message: Message ): stars = (await authorized_client.get("/stars")).json() assert len(stars) == 0 data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 1 assert stars[0]["type"] == "message" assert stars[0]["message"] == str(channel_message.id) @pytest.mark.asyncio async def test_delete_star( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, channel_message: Message ): data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 star_id = response.json()["id"] response = await authorized_client.delete(f"/stars/{star_id}") assert response.status_code == 204 @pytest.mark.asyncio async def test_delete_star_multiple_times( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, channel_message: Message ): data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 star_id = response.json()["id"] stars = (await authorized_client.get("/stars")).json() assert len(stars) == 1 response = await authorized_client.delete(f"/stars/{star_id}") assert response.status_code == 204 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 0 response = await authorized_client.delete(f"/stars/{star_id}") assert response.status_code == 204 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 0 response = await authorized_client.delete(f"/stars/{star_id}") assert response.status_code == 204 stars = (await authorized_client.get("/stars")).json() assert len(stars) == 0 @pytest.mark.asyncio async def test_delete_other_user_star( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, guest_user: User, get_authorized_client: Callable, channel_message: Message, ): data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 star_id = response.json()["id"] stars = (await authorized_client.get("/stars")).json() assert len(stars) == 1 guest_client = await get_authorized_client(guest_user) response = await guest_client.delete(f"/stars/{star_id}") assert response.status_code == 403 @pytest.mark.asyncio async def test_get_message_stars( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, channel_message: Message ): data = {"message": str(channel_message.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 assert (await authorized_client.get("/stars?type=channel")).json() == [] assert (await authorized_client.get("/stars?type=server")).json() == [] response = await authorized_client.get("/stars?type=message") assert response.status_code == 200 stars = response.json() assert len(stars) == 1 assert stars[0]["type"] == "message" assert stars[0]["message"] == data["message"] @pytest.mark.asyncio async def test_get_channel_stars( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, server_channel: Channel ): data = {"channel": str(server_channel.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 assert (await authorized_client.get("/stars?type=message")).json() == [] assert (await authorized_client.get("/stars?type=server")).json() == [] response = await authorized_client.get("/stars?type=channel") assert response.status_code == 200 stars = response.json() assert len(stars) == 1 assert stars[0]["type"] == "channel" assert stars[0]["channel"] == data["channel"] @pytest.mark.asyncio async def test_get_server_stars( self, app: FastAPI, db: Database, current_user: User, authorized_client: AsyncClient, server: Server ): data = {"server": str(server.id)} response = await authorized_client.post("/stars", json=data) assert response.status_code == 201 assert (await authorized_client.get("/stars?type=channel")).json() == [] assert (await authorized_client.get("/stars?type=message")).json() == [] response = await authorized_client.get("/stars?type=server") assert response.status_code == 200 stars = response.json() assert len(stars) == 1 assert stars[0]["type"] == "server" assert stars[0]["server"] == data["server"]

38.782443

118

0.651708

1,190

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5.382353

0.053782

0.147385

0.131148

0.093677

0.920999

0.908821

0.904606

0.880094

0.845746

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0

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0.226553

10,161

261

119

38.931034

0.802519

0

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0

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false

0

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0

0.046948

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null

0

1

0

1

0

null

0

7

5f64bdeca4e52eeec1da5baf3b66171ccecb9b9f

6,617

py

Python

atv/mailer.py

sebastianlees/answer.tv

f9827c1168f5488e043ab99dc1e4439373d99f31

[ "MIT" ]

null

atv/mailer.py

sebastianlees/answer.tv

f9827c1168f5488e043ab99dc1e4439373d99f31

[ "MIT" ]

61

2018-07-09T17:33:15.000Z

2020-01-06T18:46:53.000Z

atv/mailer.py

sebs-code/answer-tv

f9827c1168f5488e043ab99dc1e4439373d99f31

[ "MIT" ]

2

2018-08-06T03:39:46.000Z

2019-10-02T17:48:34.000Z

import os import smtplib from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText #Email server settings smtp_server = 'email-smtp.eu-west-1.amazonaws.com' smtp_username = 'AKIAID2MYX7XYWL7TKSA' smtp_password = 'Alv3cd3HeejmJqItsKe9JGPx150YJswnmz9xjc42Wz/U' smtp_port = '25' smtp_do_tls = True # /Contact contact form mailer def contactForm(sender, email, message): toaddrs = 'sebastian@incerto.net' msg = "From: team@answer.tv " + message #Change according to your settings server.set_debuglevel(10) server.tls() server.login(smtp_username, smtp_password) server.sendmail(sender, toaddrs, msg) server.quit() #Signup email def signUp(email, verify): msg = MIMEMultipart('alternative') msg['Subject'] = "Answer.tv registration" msg['From'] = 'registration@answer.tv' # Your from name and email address msg['To'] = email text = '''Thank you for signing up to answer.tv! To complete your registration, simply click on the link below to activate your account. If you cannot click on the link please copy and paste into your web browser. Please note that this link will expire within 24 hours.\n http://www.answer.tv/verify/''' + verify + '''\nIf you believe you have received this email in error, please contact us at answer.tv/contact.\n Regards \n The answer.tv team\n''' part1 = MIMEText(text, 'plain') html = '''<p>Thank you for signing up to answer.tv! To complete your registration, simply click on the link below to activate your account. If you cannot click on the link please copy and paste into your web browser. Please note that this link will expire within 24 hours.</p>''' + "<p><a href='http://www.answer.tv/verify/" + verify\ + "'>http://www.answer.tv/verify/" + verify + "</a></p>" + """<p>If you believe that you have received this email in error, please <a href="http://answer.tv/conatact">contact us</a>.</p><p>Regards</p><p>The answer.tv team</p>""" part2 = MIMEText(html, 'html') username = 'USR' password = 'PASSWORD' msg.attach(part1) msg.attach(part2) #Change according to your settings server = smtplib.SMTP(host=smtp_server, port=smtp_port, timeout=10) server.set_debuglevel(10) server.starttls() server.ehlo() server.login(smtp_username, smtp_password) server.sendmail(msg['From'], msg['To'], msg.as_string()) server.quit() #Reset password email def resetPassword(email, resetcode): msg = MIMEMultipart('alternative') msg['Subject'] = "Answer.tv reset password request" msg['From'] = 'registration@answer.tv' # Your from name and email address msg['To'] = email text = '''You have requested to reset your answer.tv password. Click on the link below to reset your password. If you cannot click on the link, please copy and paste the address into your web browser. Please note that this link will expire within 24 hours.\n http://www.answer.tv/ reset/''' + resetcode + """\nIf you believe you have received this email in error, or you have not requested a password reset, please contact us at answer.tv/contact.\n Regards \n The answer.tv team\n""" part1 = MIMEText(text, 'plain') html = '''<p>You have requested to reset your answer.tv password. Click on the link below to reset your password. If you cannot click on the link, please copy and paste the address into your web browser. Please note that this link will expire within 24 hours.</p>''' + """ <p><a href='http://www.answer.tv/reset/""" + resetcode + """'> http://www.answer.tv/reset/""" + resetcode + "</a></p>" + """<p>If you believe that you have received this email in error, or you have not requested a password reset, please <a href="http://answer.tv/conatact">contact us</a>. </p><p>Regards</p><p>The answer.tv team</p>""" part2 = MIMEText(html, 'html') username = 'USR' password = 'PASSWORD' msg.attach(part1) msg.attach(part2) #Change according to your settings server = smtplib.SMTP(host=smtp_server, port=smtp_port, timeout=10) server.set_debuglevel(10) server.starttls() server.ehlo() server.login(smtp_username, smtp_password) server.sendmail(msg['From'], msg['To'], msg.as_string()) server.quit() #Reset email password def resetEmail(email, resetcode): msg = MIMEMultipart('alternative') msg['Subject'] = "Answer.tv email change request" msg['From'] = 'registration@answer.tv' # Your from name and email address msg['To'] = email text = '''You have requested to change your answer.tv email address. Click on the link below to reset your email address. If you cannot click on the link, please copy and paste the address into your web browser. Please note that this link will expire within 24 hours.\n http://www.answer.tv/ereset/''' + resetcode + """\nIf you believe you have received this email in error, or you have not requested an email change please contact us at answer.tv/contact.\n Regards \n The answer.tv team\n""" part1 = MIMEText(text, 'plain') html = '''<p>You have requested to change your answer.tv email address. Click on the link below to reset your email address. If you cannot click on the link, please copy and paste the address into your web browser. Please note that this link will expire within 24 hours.</p> ''' + "<p><a href='http://www.answer.tv/ereset/" + resetcode + """'> http://www.answer.tv/ereset/""" + resetcode + "</a></p>" + """<p>If you believe that you have received this email in error, or you have not requested a email change, <a href="http://answer.tv/conatact">contact us</a>. </p><p>Regards</p><p>The answer.tv team</p>""" part2 = MIMEText(html, 'html') username = 'USR' password = 'PASSWORD' msg.attach(part1) msg.attach(part2) #Change according to your settings server = smtplib.SMTP(host=smtp_server, port=smtp_port, timeout=10) server.set_debuglevel(10) server.starttls() server.ehlo() server.login(smtp_username, smtp_password) server.sendmail(msg['From'], msg['To'], msg.as_string()) server.quit()

40.845679

101

0.644854

916

6,617

4.628821

0.14083

0.064151

0.028302

0.039623

0.871934

0.866981

0.827594

0.816981

0.805425

0.777594

0

0.010518

0.238477

6,617

161

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Python

src/steputils/express/expressListener.py

w0rm/steputils

f49c0b282dad8087fd4d5ac153412c6a5bdfef29

[ "MIT" ]

16

2020-06-30T09:28:46.000Z

2022-02-18T02:55:44.000Z

src/steputils/express/expressListener.py

w0rm/steputils

f49c0b282dad8087fd4d5ac153412c6a5bdfef29

[ "MIT" ]

3

2020-07-14T15:49:14.000Z

2022-03-29T03:20:33.000Z

src/steputils/express/expressListener.py

w0rm/steputils

f49c0b282dad8087fd4d5ac153412c6a5bdfef29

[ "MIT" ]

5

2020-07-21T16:21:06.000Z

2022-03-28T12:03:30.000Z

# Generated from D:/Source/steputils/data/formal\express.g4 by ANTLR 4.7.2 from antlr4 import * if __name__ is not None and "." in __name__: from .expressParser import expressParser else: from expressParser import expressParser # This class defines a complete listener for a parse tree produced by expressParser. class expressListener(ParseTreeListener): # Enter a parse tree produced by expressParser#attribute_ref. def enterAttribute_ref(self, ctx:expressParser.Attribute_refContext): pass # Exit a parse tree produced by expressParser#attribute_ref. def exitAttribute_ref(self, ctx:expressParser.Attribute_refContext): pass # Enter a parse tree produced by expressParser#constant_ref. def enterConstant_ref(self, ctx:expressParser.Constant_refContext): pass # Exit a parse tree produced by expressParser#constant_ref. def exitConstant_ref(self, ctx:expressParser.Constant_refContext): pass # Enter a parse tree produced by expressParser#entity_ref. def enterEntity_ref(self, ctx:expressParser.Entity_refContext): pass # Exit a parse tree produced by expressParser#entity_ref. def exitEntity_ref(self, ctx:expressParser.Entity_refContext): pass # Enter a parse tree produced by expressParser#enumeration_ref. def enterEnumeration_ref(self, ctx:expressParser.Enumeration_refContext): pass # Exit a parse tree produced by expressParser#enumeration_ref. def exitEnumeration_ref(self, ctx:expressParser.Enumeration_refContext): pass # Enter a parse tree produced by expressParser#function_ref. def enterFunction_ref(self, ctx:expressParser.Function_refContext): pass # Exit a parse tree produced by expressParser#function_ref. def exitFunction_ref(self, ctx:expressParser.Function_refContext): pass # Enter a parse tree produced by expressParser#parameter_ref. def enterParameter_ref(self, ctx:expressParser.Parameter_refContext): pass # Exit a parse tree produced by expressParser#parameter_ref. def exitParameter_ref(self, ctx:expressParser.Parameter_refContext): pass # Enter a parse tree produced by expressParser#procedure_ref. def enterProcedure_ref(self, ctx:expressParser.Procedure_refContext): pass # Exit a parse tree produced by expressParser#procedure_ref. def exitProcedure_ref(self, ctx:expressParser.Procedure_refContext): pass # Enter a parse tree produced by expressParser#rule_label_ref. def enterRule_label_ref(self, ctx:expressParser.Rule_label_refContext): pass # Exit a parse tree produced by expressParser#rule_label_ref. def exitRule_label_ref(self, ctx:expressParser.Rule_label_refContext): pass # Enter a parse tree produced by expressParser#rule_ref. def enterRule_ref(self, ctx:expressParser.Rule_refContext): pass # Exit a parse tree produced by expressParser#rule_ref. def exitRule_ref(self, ctx:expressParser.Rule_refContext): pass # Enter a parse tree produced by expressParser#schema_ref. def enterSchema_ref(self, ctx:expressParser.Schema_refContext): pass # Exit a parse tree produced by expressParser#schema_ref. def exitSchema_ref(self, ctx:expressParser.Schema_refContext): pass # Enter a parse tree produced by expressParser#subtype_constraint_ref. def enterSubtype_constraint_ref(self, ctx:expressParser.Subtype_constraint_refContext): pass # Exit a parse tree produced by expressParser#subtype_constraint_ref. def exitSubtype_constraint_ref(self, ctx:expressParser.Subtype_constraint_refContext): pass # Enter a parse tree produced by expressParser#type_label_ref. def enterType_label_ref(self, ctx:expressParser.Type_label_refContext): pass # Exit a parse tree produced by expressParser#type_label_ref. def exitType_label_ref(self, ctx:expressParser.Type_label_refContext): pass # Enter a parse tree produced by expressParser#type_ref. def enterType_ref(self, ctx:expressParser.Type_refContext): pass # Exit a parse tree produced by expressParser#type_ref. def exitType_ref(self, ctx:expressParser.Type_refContext): pass # Enter a parse tree produced by expressParser#variable_ref. def enterVariable_ref(self, ctx:expressParser.Variable_refContext): pass # Exit a parse tree produced by expressParser#variable_ref. def exitVariable_ref(self, ctx:expressParser.Variable_refContext): pass # Enter a parse tree produced by expressParser#abstract_entity_declaration. def enterAbstract_entity_declaration(self, ctx:expressParser.Abstract_entity_declarationContext): pass # Exit a parse tree produced by expressParser#abstract_entity_declaration. def exitAbstract_entity_declaration(self, ctx:expressParser.Abstract_entity_declarationContext): pass # Enter a parse tree produced by expressParser#abstract_supertype. def enterAbstract_supertype(self, ctx:expressParser.Abstract_supertypeContext): pass # Exit a parse tree produced by expressParser#abstract_supertype. def exitAbstract_supertype(self, ctx:expressParser.Abstract_supertypeContext): pass # Enter a parse tree produced by expressParser#abstract_supertype_declaration. def enterAbstract_supertype_declaration(self, ctx:expressParser.Abstract_supertype_declarationContext): pass # Exit a parse tree produced by expressParser#abstract_supertype_declaration. def exitAbstract_supertype_declaration(self, ctx:expressParser.Abstract_supertype_declarationContext): pass # Enter a parse tree produced by expressParser#actual_parameter_list. def enterActual_parameter_list(self, ctx:expressParser.Actual_parameter_listContext): pass # Exit a parse tree produced by expressParser#actual_parameter_list. def exitActual_parameter_list(self, ctx:expressParser.Actual_parameter_listContext): pass # Enter a parse tree produced by expressParser#add_like_op. def enterAdd_like_op(self, ctx:expressParser.Add_like_opContext): pass # Exit a parse tree produced by expressParser#add_like_op. def exitAdd_like_op(self, ctx:expressParser.Add_like_opContext): pass # Enter a parse tree produced by expressParser#aggregate_initializer. def enterAggregate_initializer(self, ctx:expressParser.Aggregate_initializerContext): pass # Exit a parse tree produced by expressParser#aggregate_initializer. def exitAggregate_initializer(self, ctx:expressParser.Aggregate_initializerContext): pass # Enter a parse tree produced by expressParser#aggregate_source. def enterAggregate_source(self, ctx:expressParser.Aggregate_sourceContext): pass # Exit a parse tree produced by expressParser#aggregate_source. def exitAggregate_source(self, ctx:expressParser.Aggregate_sourceContext): pass # Enter a parse tree produced by expressParser#aggregate_type. def enterAggregate_type(self, ctx:expressParser.Aggregate_typeContext): pass # Exit a parse tree produced by expressParser#aggregate_type. def exitAggregate_type(self, ctx:expressParser.Aggregate_typeContext): pass # Enter a parse tree produced by expressParser#aggregation_types. def enterAggregation_types(self, ctx:expressParser.Aggregation_typesContext): pass # Exit a parse tree produced by expressParser#aggregation_types. def exitAggregation_types(self, ctx:expressParser.Aggregation_typesContext): pass # Enter a parse tree produced by expressParser#algorithm_head. def enterAlgorithm_head(self, ctx:expressParser.Algorithm_headContext): pass # Exit a parse tree produced by expressParser#algorithm_head. def exitAlgorithm_head(self, ctx:expressParser.Algorithm_headContext): pass # Enter a parse tree produced by expressParser#alias_stmt. def enterAlias_stmt(self, ctx:expressParser.Alias_stmtContext): pass # Exit a parse tree produced by expressParser#alias_stmt. def exitAlias_stmt(self, ctx:expressParser.Alias_stmtContext): pass # Enter a parse tree produced by expressParser#array_type. def enterArray_type(self, ctx:expressParser.Array_typeContext): pass # Exit a parse tree produced by expressParser#array_type. def exitArray_type(self, ctx:expressParser.Array_typeContext): pass # Enter a parse tree produced by expressParser#assignment_stmt. def enterAssignment_stmt(self, ctx:expressParser.Assignment_stmtContext): pass # Exit a parse tree produced by expressParser#assignment_stmt. def exitAssignment_stmt(self, ctx:expressParser.Assignment_stmtContext): pass # Enter a parse tree produced by expressParser#attribute_decl. def enterAttribute_decl(self, ctx:expressParser.Attribute_declContext): pass # Exit a parse tree produced by expressParser#attribute_decl. def exitAttribute_decl(self, ctx:expressParser.Attribute_declContext): pass # Enter a parse tree produced by expressParser#attribute_id. def enterAttribute_id(self, ctx:expressParser.Attribute_idContext): pass # Exit a parse tree produced by expressParser#attribute_id. def exitAttribute_id(self, ctx:expressParser.Attribute_idContext): pass # Enter a parse tree produced by expressParser#attribute_qualifier. def enterAttribute_qualifier(self, ctx:expressParser.Attribute_qualifierContext): pass # Exit a parse tree produced by expressParser#attribute_qualifier. def exitAttribute_qualifier(self, ctx:expressParser.Attribute_qualifierContext): pass # Enter a parse tree produced by expressParser#bag_type. def enterBag_type(self, ctx:expressParser.Bag_typeContext): pass # Exit a parse tree produced by expressParser#bag_type. def exitBag_type(self, ctx:expressParser.Bag_typeContext): pass # Enter a parse tree produced by expressParser#binary_type. def enterBinary_type(self, ctx:expressParser.Binary_typeContext): pass # Exit a parse tree produced by expressParser#binary_type. def exitBinary_type(self, ctx:expressParser.Binary_typeContext): pass # Enter a parse tree produced by expressParser#boolean_type. def enterBoolean_type(self, ctx:expressParser.Boolean_typeContext): pass # Exit a parse tree produced by expressParser#boolean_type. def exitBoolean_type(self, ctx:expressParser.Boolean_typeContext): pass # Enter a parse tree produced by expressParser#bound_1. def enterBound_1(self, ctx:expressParser.Bound_1Context): pass # Exit a parse tree produced by expressParser#bound_1. def exitBound_1(self, ctx:expressParser.Bound_1Context): pass # Enter a parse tree produced by expressParser#bound_2. def enterBound_2(self, ctx:expressParser.Bound_2Context): pass # Exit a parse tree produced by expressParser#bound_2. def exitBound_2(self, ctx:expressParser.Bound_2Context): pass # Enter a parse tree produced by expressParser#bound_spec. def enterBound_spec(self, ctx:expressParser.Bound_specContext): pass # Exit a parse tree produced by expressParser#bound_spec. def exitBound_spec(self, ctx:expressParser.Bound_specContext): pass # Enter a parse tree produced by expressParser#built_in_constant. def enterBuilt_in_constant(self, ctx:expressParser.Built_in_constantContext): pass # Exit a parse tree produced by expressParser#built_in_constant. def exitBuilt_in_constant(self, ctx:expressParser.Built_in_constantContext): pass # Enter a parse tree produced by expressParser#built_in_function. def enterBuilt_in_function(self, ctx:expressParser.Built_in_functionContext): pass # Exit a parse tree produced by expressParser#built_in_function. def exitBuilt_in_function(self, ctx:expressParser.Built_in_functionContext): pass # Enter a parse tree produced by expressParser#built_in_procedure. def enterBuilt_in_procedure(self, ctx:expressParser.Built_in_procedureContext): pass # Exit a parse tree produced by expressParser#built_in_procedure. def exitBuilt_in_procedure(self, ctx:expressParser.Built_in_procedureContext): pass # Enter a parse tree produced by expressParser#case_action. def enterCase_action(self, ctx:expressParser.Case_actionContext): pass # Exit a parse tree produced by expressParser#case_action. def exitCase_action(self, ctx:expressParser.Case_actionContext): pass # Enter a parse tree produced by expressParser#case_label. def enterCase_label(self, ctx:expressParser.Case_labelContext): pass # Exit a parse tree produced by expressParser#case_label. def exitCase_label(self, ctx:expressParser.Case_labelContext): pass # Enter a parse tree produced by expressParser#case_stmt. def enterCase_stmt(self, ctx:expressParser.Case_stmtContext): pass # Exit a parse tree produced by expressParser#case_stmt. def exitCase_stmt(self, ctx:expressParser.Case_stmtContext): pass # Enter a parse tree produced by expressParser#compound_stmt. def enterCompound_stmt(self, ctx:expressParser.Compound_stmtContext): pass # Exit a parse tree produced by expressParser#compound_stmt. def exitCompound_stmt(self, ctx:expressParser.Compound_stmtContext): pass # Enter a parse tree produced by expressParser#concrete_types. def enterConcrete_types(self, ctx:expressParser.Concrete_typesContext): pass # Exit a parse tree produced by expressParser#concrete_types. def exitConcrete_types(self, ctx:expressParser.Concrete_typesContext): pass # Enter a parse tree produced by expressParser#constant_body. def enterConstant_body(self, ctx:expressParser.Constant_bodyContext): pass # Exit a parse tree produced by expressParser#constant_body. def exitConstant_body(self, ctx:expressParser.Constant_bodyContext): pass # Enter a parse tree produced by expressParser#constant_decl. def enterConstant_decl(self, ctx:expressParser.Constant_declContext): pass # Exit a parse tree produced by expressParser#constant_decl. def exitConstant_decl(self, ctx:expressParser.Constant_declContext): pass # Enter a parse tree produced by expressParser#constant_factor. def enterConstant_factor(self, ctx:expressParser.Constant_factorContext): pass # Exit a parse tree produced by expressParser#constant_factor. def exitConstant_factor(self, ctx:expressParser.Constant_factorContext): pass # Enter a parse tree produced by expressParser#constant_id. def enterConstant_id(self, ctx:expressParser.Constant_idContext): pass # Exit a parse tree produced by expressParser#constant_id. def exitConstant_id(self, ctx:expressParser.Constant_idContext): pass # Enter a parse tree produced by expressParser#constructed_types. def enterConstructed_types(self, ctx:expressParser.Constructed_typesContext): pass # Exit a parse tree produced by expressParser#constructed_types. def exitConstructed_types(self, ctx:expressParser.Constructed_typesContext): pass # Enter a parse tree produced by expressParser#declaration. def enterDeclaration(self, ctx:expressParser.DeclarationContext): pass # Exit a parse tree produced by expressParser#declaration. def exitDeclaration(self, ctx:expressParser.DeclarationContext): pass # Enter a parse tree produced by expressParser#derived_attr. def enterDerived_attr(self, ctx:expressParser.Derived_attrContext): pass # Exit a parse tree produced by expressParser#derived_attr. def exitDerived_attr(self, ctx:expressParser.Derived_attrContext): pass # Enter a parse tree produced by expressParser#derive_clause. def enterDerive_clause(self, ctx:expressParser.Derive_clauseContext): pass # Exit a parse tree produced by expressParser#derive_clause. def exitDerive_clause(self, ctx:expressParser.Derive_clauseContext): pass # Enter a parse tree produced by expressParser#domain_rule. def enterDomain_rule(self, ctx:expressParser.Domain_ruleContext): pass # Exit a parse tree produced by expressParser#domain_rule. def exitDomain_rule(self, ctx:expressParser.Domain_ruleContext): pass # Enter a parse tree produced by expressParser#element. def enterElement(self, ctx:expressParser.ElementContext): pass # Exit a parse tree produced by expressParser#element. def exitElement(self, ctx:expressParser.ElementContext): pass # Enter a parse tree produced by expressParser#entity_body. def enterEntity_body(self, ctx:expressParser.Entity_bodyContext): pass # Exit a parse tree produced by expressParser#entity_body. def exitEntity_body(self, ctx:expressParser.Entity_bodyContext): pass # Enter a parse tree produced by expressParser#entity_constructor. def enterEntity_constructor(self, ctx:expressParser.Entity_constructorContext): pass # Exit a parse tree produced by expressParser#entity_constructor. def exitEntity_constructor(self, ctx:expressParser.Entity_constructorContext): pass # Enter a parse tree produced by expressParser#entity_decl. def enterEntity_decl(self, ctx:expressParser.Entity_declContext): pass # Exit a parse tree produced by expressParser#entity_decl. def exitEntity_decl(self, ctx:expressParser.Entity_declContext): pass # Enter a parse tree produced by expressParser#entity_head. def enterEntity_head(self, ctx:expressParser.Entity_headContext): pass # Exit a parse tree produced by expressParser#entity_head. def exitEntity_head(self, ctx:expressParser.Entity_headContext): pass # Enter a parse tree produced by expressParser#entity_id. def enterEntity_id(self, ctx:expressParser.Entity_idContext): pass # Exit a parse tree produced by expressParser#entity_id. def exitEntity_id(self, ctx:expressParser.Entity_idContext): pass # Enter a parse tree produced by expressParser#enumeration_extension. def enterEnumeration_extension(self, ctx:expressParser.Enumeration_extensionContext): pass # Exit a parse tree produced by expressParser#enumeration_extension. def exitEnumeration_extension(self, ctx:expressParser.Enumeration_extensionContext): pass # Enter a parse tree produced by expressParser#enumeration_id. def enterEnumeration_id(self, ctx:expressParser.Enumeration_idContext): pass # Exit a parse tree produced by expressParser#enumeration_id. def exitEnumeration_id(self, ctx:expressParser.Enumeration_idContext): pass # Enter a parse tree produced by expressParser#enumeration_items. def enterEnumeration_items(self, ctx:expressParser.Enumeration_itemsContext): pass # Exit a parse tree produced by expressParser#enumeration_items. def exitEnumeration_items(self, ctx:expressParser.Enumeration_itemsContext): pass # Enter a parse tree produced by expressParser#enumeration_reference. def enterEnumeration_reference(self, ctx:expressParser.Enumeration_referenceContext): pass # Exit a parse tree produced by expressParser#enumeration_reference. def exitEnumeration_reference(self, ctx:expressParser.Enumeration_referenceContext): pass # Enter a parse tree produced by expressParser#enumeration_type. def enterEnumeration_type(self, ctx:expressParser.Enumeration_typeContext): pass # Exit a parse tree produced by expressParser#enumeration_type. def exitEnumeration_type(self, ctx:expressParser.Enumeration_typeContext): pass # Enter a parse tree produced by expressParser#escape_stmt. def enterEscape_stmt(self, ctx:expressParser.Escape_stmtContext): pass # Exit a parse tree produced by expressParser#escape_stmt. def exitEscape_stmt(self, ctx:expressParser.Escape_stmtContext): pass # Enter a parse tree produced by expressParser#explicit_attr. def enterExplicit_attr(self, ctx:expressParser.Explicit_attrContext): pass # Exit a parse tree produced by expressParser#explicit_attr. def exitExplicit_attr(self, ctx:expressParser.Explicit_attrContext): pass # Enter a parse tree produced by expressParser#expression. def enterExpression(self, ctx:expressParser.ExpressionContext): pass # Exit a parse tree produced by expressParser#expression. def exitExpression(self, ctx:expressParser.ExpressionContext): pass # Enter a parse tree produced by expressParser#factor. def enterFactor(self, ctx:expressParser.FactorContext): pass # Exit a parse tree produced by expressParser#factor. def exitFactor(self, ctx:expressParser.FactorContext): pass # Enter a parse tree produced by expressParser#formal_parameter. def enterFormal_parameter(self, ctx:expressParser.Formal_parameterContext): pass # Exit a parse tree produced by expressParser#formal_parameter. def exitFormal_parameter(self, ctx:expressParser.Formal_parameterContext): pass # Enter a parse tree produced by expressParser#function_call. def enterFunction_call(self, ctx:expressParser.Function_callContext): pass # Exit a parse tree produced by expressParser#function_call. def exitFunction_call(self, ctx:expressParser.Function_callContext): pass # Enter a parse tree produced by expressParser#function_decl. def enterFunction_decl(self, ctx:expressParser.Function_declContext): pass # Exit a parse tree produced by expressParser#function_decl. def exitFunction_decl(self, ctx:expressParser.Function_declContext): pass # Enter a parse tree produced by expressParser#function_head. def enterFunction_head(self, ctx:expressParser.Function_headContext): pass # Exit a parse tree produced by expressParser#function_head. def exitFunction_head(self, ctx:expressParser.Function_headContext): pass # Enter a parse tree produced by expressParser#function_id. def enterFunction_id(self, ctx:expressParser.Function_idContext): pass # Exit a parse tree produced by expressParser#function_id. def exitFunction_id(self, ctx:expressParser.Function_idContext): pass # Enter a parse tree produced by expressParser#generalized_types. def enterGeneralized_types(self, ctx:expressParser.Generalized_typesContext): pass # Exit a parse tree produced by expressParser#generalized_types. def exitGeneralized_types(self, ctx:expressParser.Generalized_typesContext): pass # Enter a parse tree produced by expressParser#general_aggregation_types. def enterGeneral_aggregation_types(self, ctx:expressParser.General_aggregation_typesContext): pass # Exit a parse tree produced by expressParser#general_aggregation_types. def exitGeneral_aggregation_types(self, ctx:expressParser.General_aggregation_typesContext): pass # Enter a parse tree produced by expressParser#general_array_type. def enterGeneral_array_type(self, ctx:expressParser.General_array_typeContext): pass # Exit a parse tree produced by expressParser#general_array_type. def exitGeneral_array_type(self, ctx:expressParser.General_array_typeContext): pass # Enter a parse tree produced by expressParser#general_bag_type. def enterGeneral_bag_type(self, ctx:expressParser.General_bag_typeContext): pass # Exit a parse tree produced by expressParser#general_bag_type. def exitGeneral_bag_type(self, ctx:expressParser.General_bag_typeContext): pass # Enter a parse tree produced by expressParser#general_list_type. def enterGeneral_list_type(self, ctx:expressParser.General_list_typeContext): pass # Exit a parse tree produced by expressParser#general_list_type. def exitGeneral_list_type(self, ctx:expressParser.General_list_typeContext): pass # Enter a parse tree produced by expressParser#general_ref. def enterGeneral_ref(self, ctx:expressParser.General_refContext): pass # Exit a parse tree produced by expressParser#general_ref. def exitGeneral_ref(self, ctx:expressParser.General_refContext): pass # Enter a parse tree produced by expressParser#general_set_type. def enterGeneral_set_type(self, ctx:expressParser.General_set_typeContext): pass # Exit a parse tree produced by expressParser#general_set_type. def exitGeneral_set_type(self, ctx:expressParser.General_set_typeContext): pass # Enter a parse tree produced by expressParser#generic_entity_type. def enterGeneric_entity_type(self, ctx:expressParser.Generic_entity_typeContext): pass # Exit a parse tree produced by expressParser#generic_entity_type. def exitGeneric_entity_type(self, ctx:expressParser.Generic_entity_typeContext): pass # Enter a parse tree produced by expressParser#generic_type. def enterGeneric_type(self, ctx:expressParser.Generic_typeContext): pass # Exit a parse tree produced by expressParser#generic_type. def exitGeneric_type(self, ctx:expressParser.Generic_typeContext): pass # Enter a parse tree produced by expressParser#group_qualifier. def enterGroup_qualifier(self, ctx:expressParser.Group_qualifierContext): pass # Exit a parse tree produced by expressParser#group_qualifier. def exitGroup_qualifier(self, ctx:expressParser.Group_qualifierContext): pass # Enter a parse tree produced by expressParser#if_stmt. def enterIf_stmt(self, ctx:expressParser.If_stmtContext): pass # Exit a parse tree produced by expressParser#if_stmt. def exitIf_stmt(self, ctx:expressParser.If_stmtContext): pass # Enter a parse tree produced by expressParser#increment. def enterIncrement(self, ctx:expressParser.IncrementContext): pass # Exit a parse tree produced by expressParser#increment. def exitIncrement(self, ctx:expressParser.IncrementContext): pass # Enter a parse tree produced by expressParser#increment_control. def enterIncrement_control(self, ctx:expressParser.Increment_controlContext): pass # Exit a parse tree produced by expressParser#increment_control. def exitIncrement_control(self, ctx:expressParser.Increment_controlContext): pass # Enter a parse tree produced by expressParser#index. def enterIndex(self, ctx:expressParser.IndexContext): pass # Exit a parse tree produced by expressParser#index. def exitIndex(self, ctx:expressParser.IndexContext): pass # Enter a parse tree produced by expressParser#index_1. def enterIndex_1(self, ctx:expressParser.Index_1Context): pass # Exit a parse tree produced by expressParser#index_1. def exitIndex_1(self, ctx:expressParser.Index_1Context): pass # Enter a parse tree produced by expressParser#index_2. def enterIndex_2(self, ctx:expressParser.Index_2Context): pass # Exit a parse tree produced by expressParser#index_2. def exitIndex_2(self, ctx:expressParser.Index_2Context): pass # Enter a parse tree produced by expressParser#index_qualifier. def enterIndex_qualifier(self, ctx:expressParser.Index_qualifierContext): pass # Exit a parse tree produced by expressParser#index_qualifier. def exitIndex_qualifier(self, ctx:expressParser.Index_qualifierContext): pass # Enter a parse tree produced by expressParser#instantiable_type. def enterInstantiable_type(self, ctx:expressParser.Instantiable_typeContext): pass # Exit a parse tree produced by expressParser#instantiable_type. def exitInstantiable_type(self, ctx:expressParser.Instantiable_typeContext): pass # Enter a parse tree produced by expressParser#integer_type. def enterInteger_type(self, ctx:expressParser.Integer_typeContext): pass # Exit a parse tree produced by expressParser#integer_type. def exitInteger_type(self, ctx:expressParser.Integer_typeContext): pass # Enter a parse tree produced by expressParser#interface_specification. def enterInterface_specification(self, ctx:expressParser.Interface_specificationContext): pass # Exit a parse tree produced by expressParser#interface_specification. def exitInterface_specification(self, ctx:expressParser.Interface_specificationContext): pass # Enter a parse tree produced by expressParser#interval. def enterInterval(self, ctx:expressParser.IntervalContext): pass # Exit a parse tree produced by expressParser#interval. def exitInterval(self, ctx:expressParser.IntervalContext): pass # Enter a parse tree produced by expressParser#interval_high. def enterInterval_high(self, ctx:expressParser.Interval_highContext): pass # Exit a parse tree produced by expressParser#interval_high. def exitInterval_high(self, ctx:expressParser.Interval_highContext): pass # Enter a parse tree produced by expressParser#interval_item. def enterInterval_item(self, ctx:expressParser.Interval_itemContext): pass # Exit a parse tree produced by expressParser#interval_item. def exitInterval_item(self, ctx:expressParser.Interval_itemContext): pass # Enter a parse tree produced by expressParser#interval_low. def enterInterval_low(self, ctx:expressParser.Interval_lowContext): pass # Exit a parse tree produced by expressParser#interval_low. def exitInterval_low(self, ctx:expressParser.Interval_lowContext): pass # Enter a parse tree produced by expressParser#interval_op. def enterInterval_op(self, ctx:expressParser.Interval_opContext): pass # Exit a parse tree produced by expressParser#interval_op. def exitInterval_op(self, ctx:expressParser.Interval_opContext): pass # Enter a parse tree produced by expressParser#inverse_attr. def enterInverse_attr(self, ctx:expressParser.Inverse_attrContext): pass # Exit a parse tree produced by expressParser#inverse_attr. def exitInverse_attr(self, ctx:expressParser.Inverse_attrContext): pass # Enter a parse tree produced by expressParser#inverse_clause. def enterInverse_clause(self, ctx:expressParser.Inverse_clauseContext): pass # Exit a parse tree produced by expressParser#inverse_clause. def exitInverse_clause(self, ctx:expressParser.Inverse_clauseContext): pass # Enter a parse tree produced by expressParser#list_type. def enterList_type(self, ctx:expressParser.List_typeContext): pass # Exit a parse tree produced by expressParser#list_type. def exitList_type(self, ctx:expressParser.List_typeContext): pass # Enter a parse tree produced by expressParser#literal. def enterLiteral(self, ctx:expressParser.LiteralContext): pass # Exit a parse tree produced by expressParser#literal. def exitLiteral(self, ctx:expressParser.LiteralContext): pass # Enter a parse tree produced by expressParser#local_decl. def enterLocal_decl(self, ctx:expressParser.Local_declContext): pass # Exit a parse tree produced by expressParser#local_decl. def exitLocal_decl(self, ctx:expressParser.Local_declContext): pass # Enter a parse tree produced by expressParser#local_variable. def enterLocal_variable(self, ctx:expressParser.Local_variableContext): pass # Exit a parse tree produced by expressParser#local_variable. def exitLocal_variable(self, ctx:expressParser.Local_variableContext): pass # Enter a parse tree produced by expressParser#logical_expression. def enterLogical_expression(self, ctx:expressParser.Logical_expressionContext): pass # Exit a parse tree produced by expressParser#logical_expression. def exitLogical_expression(self, ctx:expressParser.Logical_expressionContext): pass # Enter a parse tree produced by expressParser#logical_literal. def enterLogical_literal(self, ctx:expressParser.Logical_literalContext): pass # Exit a parse tree produced by expressParser#logical_literal. def exitLogical_literal(self, ctx:expressParser.Logical_literalContext): pass # Enter a parse tree produced by expressParser#logical_type. def enterLogical_type(self, ctx:expressParser.Logical_typeContext): pass # Exit a parse tree produced by expressParser#logical_type. def exitLogical_type(self, ctx:expressParser.Logical_typeContext): pass # Enter a parse tree produced by expressParser#multiplication_like_op. def enterMultiplication_like_op(self, ctx:expressParser.Multiplication_like_opContext): pass # Exit a parse tree produced by expressParser#multiplication_like_op. def exitMultiplication_like_op(self, ctx:expressParser.Multiplication_like_opContext): pass # Enter a parse tree produced by expressParser#named_types. def enterNamed_types(self, ctx:expressParser.Named_typesContext): pass # Exit a parse tree produced by expressParser#named_types. def exitNamed_types(self, ctx:expressParser.Named_typesContext): pass # Enter a parse tree produced by expressParser#named_type_or_rename. def enterNamed_type_or_rename(self, ctx:expressParser.Named_type_or_renameContext): pass # Exit a parse tree produced by expressParser#named_type_or_rename. def exitNamed_type_or_rename(self, ctx:expressParser.Named_type_or_renameContext): pass # Enter a parse tree produced by expressParser#null_stmt. def enterNull_stmt(self, ctx:expressParser.Null_stmtContext): pass # Exit a parse tree produced by expressParser#null_stmt. def exitNull_stmt(self, ctx:expressParser.Null_stmtContext): pass # Enter a parse tree produced by expressParser#number_type. def enterNumber_type(self, ctx:expressParser.Number_typeContext): pass # Exit a parse tree produced by expressParser#number_type. def exitNumber_type(self, ctx:expressParser.Number_typeContext): pass # Enter a parse tree produced by expressParser#numeric_expression. def enterNumeric_expression(self, ctx:expressParser.Numeric_expressionContext): pass # Exit a parse tree produced by expressParser#numeric_expression. def exitNumeric_expression(self, ctx:expressParser.Numeric_expressionContext): pass # Enter a parse tree produced by expressParser#one_of. def enterOne_of(self, ctx:expressParser.One_ofContext): pass # Exit a parse tree produced by expressParser#one_of. def exitOne_of(self, ctx:expressParser.One_ofContext): pass # Enter a parse tree produced by expressParser#parameter. def enterParameter(self, ctx:expressParser.ParameterContext): pass # Exit a parse tree produced by expressParser#parameter. def exitParameter(self, ctx:expressParser.ParameterContext): pass # Enter a parse tree produced by expressParser#parameter_id. def enterParameter_id(self, ctx:expressParser.Parameter_idContext): pass # Exit a parse tree produced by expressParser#parameter_id. def exitParameter_id(self, ctx:expressParser.Parameter_idContext): pass # Enter a parse tree produced by expressParser#parameter_type. def enterParameter_type(self, ctx:expressParser.Parameter_typeContext): pass # Exit a parse tree produced by expressParser#parameter_type. def exitParameter_type(self, ctx:expressParser.Parameter_typeContext): pass # Enter a parse tree produced by expressParser#population. def enterPopulation(self, ctx:expressParser.PopulationContext): pass # Exit a parse tree produced by expressParser#population. def exitPopulation(self, ctx:expressParser.PopulationContext): pass # Enter a parse tree produced by expressParser#precision_spec. def enterPrecision_spec(self, ctx:expressParser.Precision_specContext): pass # Exit a parse tree produced by expressParser#precision_spec. def exitPrecision_spec(self, ctx:expressParser.Precision_specContext): pass # Enter a parse tree produced by expressParser#primary. def enterPrimary(self, ctx:expressParser.PrimaryContext): pass # Exit a parse tree produced by expressParser#primary. def exitPrimary(self, ctx:expressParser.PrimaryContext): pass # Enter a parse tree produced by expressParser#procedure_call_stmt. def enterProcedure_call_stmt(self, ctx:expressParser.Procedure_call_stmtContext): pass # Exit a parse tree produced by expressParser#procedure_call_stmt. def exitProcedure_call_stmt(self, ctx:expressParser.Procedure_call_stmtContext): pass # Enter a parse tree produced by expressParser#procedure_decl. def enterProcedure_decl(self, ctx:expressParser.Procedure_declContext): pass # Exit a parse tree produced by expressParser#procedure_decl. def exitProcedure_decl(self, ctx:expressParser.Procedure_declContext): pass # Enter a parse tree produced by expressParser#procedure_head. def enterProcedure_head(self, ctx:expressParser.Procedure_headContext): pass # Exit a parse tree produced by expressParser#procedure_head. def exitProcedure_head(self, ctx:expressParser.Procedure_headContext): pass # Enter a parse tree produced by expressParser#procedure_id. def enterProcedure_id(self, ctx:expressParser.Procedure_idContext): pass # Exit a parse tree produced by expressParser#procedure_id. def exitProcedure_id(self, ctx:expressParser.Procedure_idContext): pass # Enter a parse tree produced by expressParser#qualifiable_factor. def enterQualifiable_factor(self, ctx:expressParser.Qualifiable_factorContext): pass # Exit a parse tree produced by expressParser#qualifiable_factor. def exitQualifiable_factor(self, ctx:expressParser.Qualifiable_factorContext): pass # Enter a parse tree produced by expressParser#qualified_attribute. def enterQualified_attribute(self, ctx:expressParser.Qualified_attributeContext): pass # Exit a parse tree produced by expressParser#qualified_attribute. def exitQualified_attribute(self, ctx:expressParser.Qualified_attributeContext): pass # Enter a parse tree produced by expressParser#qualifier. def enterQualifier(self, ctx:expressParser.QualifierContext): pass # Exit a parse tree produced by expressParser#qualifier. def exitQualifier(self, ctx:expressParser.QualifierContext): pass # Enter a parse tree produced by expressParser#query_expression. def enterQuery_expression(self, ctx:expressParser.Query_expressionContext): pass # Exit a parse tree produced by expressParser#query_expression. def exitQuery_expression(self, ctx:expressParser.Query_expressionContext): pass # Enter a parse tree produced by expressParser#real_type. def enterReal_type(self, ctx:expressParser.Real_typeContext): pass # Exit a parse tree produced by expressParser#real_type. def exitReal_type(self, ctx:expressParser.Real_typeContext): pass # Enter a parse tree produced by expressParser#redeclared_attribute. def enterRedeclared_attribute(self, ctx:expressParser.Redeclared_attributeContext): pass # Exit a parse tree produced by expressParser#redeclared_attribute. def exitRedeclared_attribute(self, ctx:expressParser.Redeclared_attributeContext): pass # Enter a parse tree produced by expressParser#referenced_attribute. def enterReferenced_attribute(self, ctx:expressParser.Referenced_attributeContext): pass # Exit a parse tree produced by expressParser#referenced_attribute. def exitReferenced_attribute(self, ctx:expressParser.Referenced_attributeContext): pass # Enter a parse tree produced by expressParser#reference_clause. def enterReference_clause(self, ctx:expressParser.Reference_clauseContext): pass # Exit a parse tree produced by expressParser#reference_clause. def exitReference_clause(self, ctx:expressParser.Reference_clauseContext): pass # Enter a parse tree produced by expressParser#rel_op. def enterRel_op(self, ctx:expressParser.Rel_opContext): pass # Exit a parse tree produced by expressParser#rel_op. def exitRel_op(self, ctx:expressParser.Rel_opContext): pass # Enter a parse tree produced by expressParser#rel_op_extended. def enterRel_op_extended(self, ctx:expressParser.Rel_op_extendedContext): pass # Exit a parse tree produced by expressParser#rel_op_extended. def exitRel_op_extended(self, ctx:expressParser.Rel_op_extendedContext): pass # Enter a parse tree produced by expressParser#rename_id. def enterRename_id(self, ctx:expressParser.Rename_idContext): pass # Exit a parse tree produced by expressParser#rename_id. def exitRename_id(self, ctx:expressParser.Rename_idContext): pass # Enter a parse tree produced by expressParser#repeat_control. def enterRepeat_control(self, ctx:expressParser.Repeat_controlContext): pass # Exit a parse tree produced by expressParser#repeat_control. def exitRepeat_control(self, ctx:expressParser.Repeat_controlContext): pass # Enter a parse tree produced by expressParser#repeat_stmt. def enterRepeat_stmt(self, ctx:expressParser.Repeat_stmtContext): pass # Exit a parse tree produced by expressParser#repeat_stmt. def exitRepeat_stmt(self, ctx:expressParser.Repeat_stmtContext): pass # Enter a parse tree produced by expressParser#repetition. def enterRepetition(self, ctx:expressParser.RepetitionContext): pass # Exit a parse tree produced by expressParser#repetition. def exitRepetition(self, ctx:expressParser.RepetitionContext): pass # Enter a parse tree produced by expressParser#resource_or_rename. def enterResource_or_rename(self, ctx:expressParser.Resource_or_renameContext): pass # Exit a parse tree produced by expressParser#resource_or_rename. def exitResource_or_rename(self, ctx:expressParser.Resource_or_renameContext): pass # Enter a parse tree produced by expressParser#resource_ref. def enterResource_ref(self, ctx:expressParser.Resource_refContext): pass # Exit a parse tree produced by expressParser#resource_ref. def exitResource_ref(self, ctx:expressParser.Resource_refContext): pass # Enter a parse tree produced by expressParser#return_stmt. def enterReturn_stmt(self, ctx:expressParser.Return_stmtContext): pass # Exit a parse tree produced by expressParser#return_stmt. def exitReturn_stmt(self, ctx:expressParser.Return_stmtContext): pass # Enter a parse tree produced by expressParser#rule_decl. def enterRule_decl(self, ctx:expressParser.Rule_declContext): pass # Exit a parse tree produced by expressParser#rule_decl. def exitRule_decl(self, ctx:expressParser.Rule_declContext): pass # Enter a parse tree produced by expressParser#rule_head. def enterRule_head(self, ctx:expressParser.Rule_headContext): pass # Exit a parse tree produced by expressParser#rule_head. def exitRule_head(self, ctx:expressParser.Rule_headContext): pass # Enter a parse tree produced by expressParser#rule_id. def enterRule_id(self, ctx:expressParser.Rule_idContext): pass # Exit a parse tree produced by expressParser#rule_id. def exitRule_id(self, ctx:expressParser.Rule_idContext): pass # Enter a parse tree produced by expressParser#rule_label_id. def enterRule_label_id(self, ctx:expressParser.Rule_label_idContext): pass # Exit a parse tree produced by expressParser#rule_label_id. def exitRule_label_id(self, ctx:expressParser.Rule_label_idContext): pass # Enter a parse tree produced by expressParser#schema_body. def enterSchema_body(self, ctx:expressParser.Schema_bodyContext): pass # Exit a parse tree produced by expressParser#schema_body. def exitSchema_body(self, ctx:expressParser.Schema_bodyContext): pass # Enter a parse tree produced by expressParser#schema_decl. def enterSchema_decl(self, ctx:expressParser.Schema_declContext): pass # Exit a parse tree produced by expressParser#schema_decl. def exitSchema_decl(self, ctx:expressParser.Schema_declContext): pass # Enter a parse tree produced by expressParser#schema_id. def enterSchema_id(self, ctx:expressParser.Schema_idContext): pass # Exit a parse tree produced by expressParser#schema_id. def exitSchema_id(self, ctx:expressParser.Schema_idContext): pass # Enter a parse tree produced by expressParser#schema_version_id. def enterSchema_version_id(self, ctx:expressParser.Schema_version_idContext): pass # Exit a parse tree produced by expressParser#schema_version_id. def exitSchema_version_id(self, ctx:expressParser.Schema_version_idContext): pass # Enter a parse tree produced by expressParser#selector. def enterSelector(self, ctx:expressParser.SelectorContext): pass # Exit a parse tree produced by expressParser#selector. def exitSelector(self, ctx:expressParser.SelectorContext): pass # Enter a parse tree produced by expressParser#select_extension. def enterSelect_extension(self, ctx:expressParser.Select_extensionContext): pass # Exit a parse tree produced by expressParser#select_extension. def exitSelect_extension(self, ctx:expressParser.Select_extensionContext): pass # Enter a parse tree produced by expressParser#select_list. def enterSelect_list(self, ctx:expressParser.Select_listContext): pass # Exit a parse tree produced by expressParser#select_list. def exitSelect_list(self, ctx:expressParser.Select_listContext): pass # Enter a parse tree produced by expressParser#select_type. def enterSelect_type(self, ctx:expressParser.Select_typeContext): pass # Exit a parse tree produced by expressParser#select_type. def exitSelect_type(self, ctx:expressParser.Select_typeContext): pass # Enter a parse tree produced by expressParser#set_type. def enterSet_type(self, ctx:expressParser.Set_typeContext): pass # Exit a parse tree produced by expressParser#set_type. def exitSet_type(self, ctx:expressParser.Set_typeContext): pass # Enter a parse tree produced by expressParser#simple_expression. def enterSimple_expression(self, ctx:expressParser.Simple_expressionContext): pass # Exit a parse tree produced by expressParser#simple_expression. def exitSimple_expression(self, ctx:expressParser.Simple_expressionContext): pass # Enter a parse tree produced by expressParser#simple_factor. def enterSimple_factor(self, ctx:expressParser.Simple_factorContext): pass # Exit a parse tree produced by expressParser#simple_factor. def exitSimple_factor(self, ctx:expressParser.Simple_factorContext): pass # Enter a parse tree produced by expressParser#simple_types. def enterSimple_types(self, ctx:expressParser.Simple_typesContext): pass # Exit a parse tree produced by expressParser#simple_types. def exitSimple_types(self, ctx:expressParser.Simple_typesContext): pass # Enter a parse tree produced by expressParser#skip_stmt. def enterSkip_stmt(self, ctx:expressParser.Skip_stmtContext): pass # Exit a parse tree produced by expressParser#skip_stmt. def exitSkip_stmt(self, ctx:expressParser.Skip_stmtContext): pass # Enter a parse tree produced by expressParser#stmt. def enterStmt(self, ctx:expressParser.StmtContext): pass # Exit a parse tree produced by expressParser#stmt. def exitStmt(self, ctx:expressParser.StmtContext): pass # Enter a parse tree produced by expressParser#string_literal. def enterString_literal(self, ctx:expressParser.String_literalContext): pass # Exit a parse tree produced by expressParser#string_literal. def exitString_literal(self, ctx:expressParser.String_literalContext): pass # Enter a parse tree produced by expressParser#string_type. def enterString_type(self, ctx:expressParser.String_typeContext): pass # Exit a parse tree produced by expressParser#string_type. def exitString_type(self, ctx:expressParser.String_typeContext): pass # Enter a parse tree produced by expressParser#subsuper. def enterSubsuper(self, ctx:expressParser.SubsuperContext): pass # Exit a parse tree produced by expressParser#subsuper. def exitSubsuper(self, ctx:expressParser.SubsuperContext): pass # Enter a parse tree produced by expressParser#subtype_constraint. def enterSubtype_constraint(self, ctx:expressParser.Subtype_constraintContext): pass # Exit a parse tree produced by expressParser#subtype_constraint. def exitSubtype_constraint(self, ctx:expressParser.Subtype_constraintContext): pass # Enter a parse tree produced by expressParser#subtype_constraint_body. def enterSubtype_constraint_body(self, ctx:expressParser.Subtype_constraint_bodyContext): pass # Exit a parse tree produced by expressParser#subtype_constraint_body. def exitSubtype_constraint_body(self, ctx:expressParser.Subtype_constraint_bodyContext): pass # Enter a parse tree produced by expressParser#subtype_constraint_decl. def enterSubtype_constraint_decl(self, ctx:expressParser.Subtype_constraint_declContext): pass # Exit a parse tree produced by expressParser#subtype_constraint_decl. def exitSubtype_constraint_decl(self, ctx:expressParser.Subtype_constraint_declContext): pass # Enter a parse tree produced by expressParser#subtype_constraint_head. def enterSubtype_constraint_head(self, ctx:expressParser.Subtype_constraint_headContext): pass # Exit a parse tree produced by expressParser#subtype_constraint_head. def exitSubtype_constraint_head(self, ctx:expressParser.Subtype_constraint_headContext): pass # Enter a parse tree produced by expressParser#subtype_constraint_id. def enterSubtype_constraint_id(self, ctx:expressParser.Subtype_constraint_idContext): pass # Exit a parse tree produced by expressParser#subtype_constraint_id. def exitSubtype_constraint_id(self, ctx:expressParser.Subtype_constraint_idContext): pass # Enter a parse tree produced by expressParser#subtype_declaration. def enterSubtype_declaration(self, ctx:expressParser.Subtype_declarationContext): pass # Exit a parse tree produced by expressParser#subtype_declaration. def exitSubtype_declaration(self, ctx:expressParser.Subtype_declarationContext): pass # Enter a parse tree produced by expressParser#supertype_constraint. def enterSupertype_constraint(self, ctx:expressParser.Supertype_constraintContext): pass # Exit a parse tree produced by expressParser#supertype_constraint. def exitSupertype_constraint(self, ctx:expressParser.Supertype_constraintContext): pass # Enter a parse tree produced by expressParser#supertype_expression. def enterSupertype_expression(self, ctx:expressParser.Supertype_expressionContext): pass # Exit a parse tree produced by expressParser#supertype_expression. def exitSupertype_expression(self, ctx:expressParser.Supertype_expressionContext): pass # Enter a parse tree produced by expressParser#supertype_factor. def enterSupertype_factor(self, ctx:expressParser.Supertype_factorContext): pass # Exit a parse tree produced by expressParser#supertype_factor. def exitSupertype_factor(self, ctx:expressParser.Supertype_factorContext): pass # Enter a parse tree produced by expressParser#supertype_rule. def enterSupertype_rule(self, ctx:expressParser.Supertype_ruleContext): pass # Exit a parse tree produced by expressParser#supertype_rule. def exitSupertype_rule(self, ctx:expressParser.Supertype_ruleContext): pass # Enter a parse tree produced by expressParser#supertype_term. def enterSupertype_term(self, ctx:expressParser.Supertype_termContext): pass # Exit a parse tree produced by expressParser#supertype_term. def exitSupertype_term(self, ctx:expressParser.Supertype_termContext): pass # Enter a parse tree produced by expressParser#syntax. def enterSyntax(self, ctx:expressParser.SyntaxContext): pass # Exit a parse tree produced by expressParser#syntax. def exitSyntax(self, ctx:expressParser.SyntaxContext): pass # Enter a parse tree produced by expressParser#term. def enterTerm(self, ctx:expressParser.TermContext): pass # Exit a parse tree produced by expressParser#term. def exitTerm(self, ctx:expressParser.TermContext): pass # Enter a parse tree produced by expressParser#total_over. def enterTotal_over(self, ctx:expressParser.Total_overContext): pass # Exit a parse tree produced by expressParser#total_over. def exitTotal_over(self, ctx:expressParser.Total_overContext): pass # Enter a parse tree produced by expressParser#type_decl. def enterType_decl(self, ctx:expressParser.Type_declContext): pass # Exit a parse tree produced by expressParser#type_decl. def exitType_decl(self, ctx:expressParser.Type_declContext): pass # Enter a parse tree produced by expressParser#type_id. def enterType_id(self, ctx:expressParser.Type_idContext): pass # Exit a parse tree produced by expressParser#type_id. def exitType_id(self, ctx:expressParser.Type_idContext): pass # Enter a parse tree produced by expressParser#type_label. def enterType_label(self, ctx:expressParser.Type_labelContext): pass # Exit a parse tree produced by expressParser#type_label. def exitType_label(self, ctx:expressParser.Type_labelContext): pass # Enter a parse tree produced by expressParser#type_label_id. def enterType_label_id(self, ctx:expressParser.Type_label_idContext): pass # Exit a parse tree produced by expressParser#type_label_id. def exitType_label_id(self, ctx:expressParser.Type_label_idContext): pass # Enter a parse tree produced by expressParser#unary_op. def enterUnary_op(self, ctx:expressParser.Unary_opContext): pass # Exit a parse tree produced by expressParser#unary_op. def exitUnary_op(self, ctx:expressParser.Unary_opContext): pass # Enter a parse tree produced by expressParser#underlying_type. def enterUnderlying_type(self, ctx:expressParser.Underlying_typeContext): pass # Exit a parse tree produced by expressParser#underlying_type. def exitUnderlying_type(self, ctx:expressParser.Underlying_typeContext): pass # Enter a parse tree produced by expressParser#unique_clause. def enterUnique_clause(self, ctx:expressParser.Unique_clauseContext): pass # Exit a parse tree produced by expressParser#unique_clause. def exitUnique_clause(self, ctx:expressParser.Unique_clauseContext): pass # Enter a parse tree produced by expressParser#unique_rule. def enterUnique_rule(self, ctx:expressParser.Unique_ruleContext): pass # Exit a parse tree produced by expressParser#unique_rule. def exitUnique_rule(self, ctx:expressParser.Unique_ruleContext): pass # Enter a parse tree produced by expressParser#until_control. def enterUntil_control(self, ctx:expressParser.Until_controlContext): pass # Exit a parse tree produced by expressParser#until_control. def exitUntil_control(self, ctx:expressParser.Until_controlContext): pass # Enter a parse tree produced by expressParser#use_clause. def enterUse_clause(self, ctx:expressParser.Use_clauseContext): pass # Exit a parse tree produced by expressParser#use_clause. def exitUse_clause(self, ctx:expressParser.Use_clauseContext): pass # Enter a parse tree produced by expressParser#variable_id. def enterVariable_id(self, ctx:expressParser.Variable_idContext): pass # Exit a parse tree produced by expressParser#variable_id. def exitVariable_id(self, ctx:expressParser.Variable_idContext): pass # Enter a parse tree produced by expressParser#where_clause. def enterWhere_clause(self, ctx:expressParser.Where_clauseContext): pass # Exit a parse tree produced by expressParser#where_clause. def exitWhere_clause(self, ctx:expressParser.Where_clauseContext): pass # Enter a parse tree produced by expressParser#while_control. def enterWhile_control(self, ctx:expressParser.While_controlContext): pass # Exit a parse tree produced by expressParser#while_control. def exitWhile_control(self, ctx:expressParser.While_controlContext): pass # Enter a parse tree produced by expressParser#width. def enterWidth(self, ctx:expressParser.WidthContext): pass # Exit a parse tree produced by expressParser#width. def exitWidth(self, ctx:expressParser.WidthContext): pass # Enter a parse tree produced by expressParser#width_spec. def enterWidth_spec(self, ctx:expressParser.Width_specContext): pass # Exit a parse tree produced by expressParser#width_spec. def exitWidth_spec(self, ctx:expressParser.Width_specContext): pass

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0.647048

0.63084

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1,729

108

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5f8fb83da3e5a0e37a03fc684620033443eee284

13,085

py

Python

examples/modeling/modeling_bert.py

bcmi220/ggdp

ccd1d25a951c4f3549de5f4701b56746cb3495a2

[ "Apache-2.0" ]

9

2019-12-03T16:47:20.000Z

2021-07-08T08:58:58.000Z

examples/modeling/modeling_bert.py

bcmi220/ggdp

ccd1d25a951c4f3549de5f4701b56746cb3495a2

[ "Apache-2.0" ]

4

2021-02-22T16:43:41.000Z

2021-04-13T13:39:47.000Z

examples/modeling/modeling_bert.py

bcmi220/ggdp

ccd1d25a951c4f3549de5f4701b56746cb3495a2

[ "Apache-2.0" ]

5

2021-02-22T12:14:16.000Z

2021-07-08T08:58:59.000Z

import logging import math import os import sys import torch from torch import nn import torch.nn.functional as F from torch.nn import CrossEntropyLoss from transformers import (BertPreTrainedModel, BertModel) from .utils_modeling import (BiAAttention, BiLinear) logger = logging.getLogger(__name__) class BertForDependencyParsing(BertPreTrainedModel): def __init__(self, config): super(BertForDependencyParsing, self).__init__(config) self.use_postag = config.use_postag if self.use_postag: # 采用加的方式整合postag embedding # 使用0作为pad的postag位置 self.postag_embeddings = nn.Embedding(config.num_postags, config.hidden_size, padding_idx=0) self.num_labels = config.num_labels self.bert = BertModel(config) self.dropout = nn.Dropout(config.hidden_dropout_prob) self.arc_h = nn.Linear(config.hidden_size, config.arc_space) self.arc_c = nn.Linear(config.hidden_size, config.arc_space) self.attention = BiAAttention(config.arc_space, config.arc_space, 1, biaffine=True) self.label_h = nn.Linear(config.hidden_size, config.label_space) self.label_c = nn.Linear(config.hidden_size, config.label_space) self.bilinear = BiLinear(config.label_space, config.label_space, self.num_labels) self.init_weights() def forward(self, input_ids=None, attention_mask=None, token_type_ids=None, position_ids=None, head_mask=None, inputs_embeds=None, postag_ids=None, head_ids=None, label_ids=None): # 1. 编码 outputs = self.bert(input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, position_ids=position_ids, head_mask=head_mask, inputs_embeds=inputs_embeds) sequence_output = outputs[0] sequence_output = self.dropout(sequence_output) # output size [batch, length, arc_space] arc_h = F.elu(self.arc_h(sequence_output)) arc_c = F.elu(self.arc_c(sequence_output)) # output size [batch, length, label_space] label_h = F.elu(self.label_h(sequence_output)) label_c = F.elu(self.label_c(sequence_output)) # apply dropout # [batch, length, dim] --> [batch, 2 * length, dim] arcs = torch.cat([arc_h, arc_c], dim=1) labels = torch.cat([label_h, label_c], dim=1) arcs = self.dropout(arcs) arc_h, arc_c = arcs.chunk(2, 1) labels = self.dropout(labels) label_h, label_c = labels.chunk(2, 1) label_h = label_h.contiguous() label_c = label_c.contiguous() # [batch, length, length] out_arc = self.attention(arc_h, arc_c, mask_d=attention_mask, mask_e=attention_mask).squeeze(dim=1) batch, max_len, label_space = label_h.size() if head_ids is not None and label_ids is not None: # create batch index [batch] batch_index = torch.arange(0, batch).type_as(out_arc).long() # get vector for head_ids [batch, length, label_space], label_h = label_h[batch_index, head_ids.t()].transpose(0, 1).contiguous() # compute output for type [batch, length, num_labels] out_label = self.bilinear(label_h, label_c) # mask invalid position to -inf for log_softmax if attention_mask is not None: minus_inf = -1e8 minus_mask = (1 - attention_mask) * minus_inf out_arc = out_arc + minus_mask.unsqueeze(2) + minus_mask.unsqueeze(1) # loss_arc shape [batch, length, length] loss_arc = F.log_softmax(out_arc, dim=1) # loss_label shape [batch, length, num_labels] loss_label = F.log_softmax(out_label, dim=2) # mask invalid position to 0 for sum loss if attention_mask is not None: loss_arc = loss_arc * attention_mask.unsqueeze(2) * attention_mask.unsqueeze(1) loss_label = loss_label * attention_mask.unsqueeze(2) # number of valid positions which contribute to loss (remove the symbolic head for each sentence. num = attention_mask.sum() - batch else: # number of valid positions which contribute to loss (remove the symbolic head for each sentence. num = float(max_len - 1) * batch # first create index matrix [length, batch] child_index = torch.arange(0, max_len).view(max_len, 1).expand(max_len, batch) child_index = child_index.type_as(out_arc).long() # [length-1, batch] loss_arc = loss_arc[batch_index, head_ids.t(), child_index][1:] loss_label = loss_label[batch_index, child_index, label_ids.t()][1:] total_loss = (-loss_arc.sum() / num) + (-loss_label.sum() / num) outputs = (total_loss, ) else: label_h = label_h.unsqueeze(2).expand(batch, max_len, max_len, label_space).contiguous() label_c = label_c.unsqueeze(1).expand(batch, max_len, max_len, label_space).contiguous() # compute output for label [batch, length, length, num_labels] out_label = self.bilinear(label_h, label_c) # mask invalid position to -inf for log_softmax if attention_mask is not None: minus_inf = -1e8 minus_mask = (1 - attention_mask) * minus_inf out_arc = out_arc + minus_mask.unsqueeze(2) + minus_mask.unsqueeze(1) # logits_arc shape [batch, length, length] logits_arc = F.log_softmax(out_arc, dim=1) # logits_label shape [batch, num_labels, length, length] logits_label = F.log_softmax(out_label, dim=3).permute(0, 3, 1, 2) # [batch, num_labels, length, length] energy = torch.exp(logits_arc.unsqueeze(1) + logits_label) outputs = (energy, logits_arc, logits_label, ) return outputs class BertForDependencyParsingWithOrder(BertPreTrainedModel): def __init__(self, config): super(BertForDependencyParsingWithOrder, self).__init__(config) self.use_postag = config.use_postag if self.use_postag: # 采用加的方式整合postag embedding # 使用0作为pad的postag位置 self.postag_embeddings = nn.Embedding(config.num_postags, config.hidden_size, padding_idx=0) self.num_labels = config.num_labels self.bert = BertModel(config) self.dropout = nn.Dropout(config.hidden_dropout_prob) self.arc_h = nn.Linear(config.hidden_size, config.arc_space) self.arc_c = nn.Linear(config.hidden_size, config.arc_space) self.attention = BiAAttention(config.arc_space, config.arc_space, 1, biaffine=True) self.label_h = nn.Linear(config.hidden_size, config.label_space) self.label_c = nn.Linear(config.hidden_size, config.label_space) self.bilinear = BiLinear(config.label_space, config.label_space, self.num_labels) self.max_parsing_order = config.max_parsing_order self.order_hidden = nn.Linear(config.hidden_size, config.order_space) self.order_classifier = nn.Linear(config.order_space, self.max_parsing_order) self.init_weights() def forward(self, input_ids=None, attention_mask=None, token_type_ids=None, position_ids=None, head_mask=None, inputs_embeds=None, postag_ids=None, order_ids=None, head_ids=None, label_ids=None): # 1. 编码 outputs = self.bert(input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, position_ids=position_ids, head_mask=head_mask, inputs_embeds=inputs_embeds) sequence_output = outputs[0] sequence_output = self.dropout(sequence_output) # output size [batch, length, arc_space] arc_h = F.elu(self.arc_h(sequence_output)) arc_c = F.elu(self.arc_c(sequence_output)) # output size [batch, length, label_space] label_h = F.elu(self.label_h(sequence_output)) label_c = F.elu(self.label_c(sequence_output)) # output size [batch, length, order_space] order_h = F.elu(self.order_hidden(sequence_output)) # apply dropout # [batch, length, dim] --> [batch, 2 * length, dim] arcs = torch.cat([arc_h, arc_c], dim=1) labels = torch.cat([label_h, label_c], dim=1) arcs = self.dropout(arcs) arc_h, arc_c = arcs.chunk(2, 1) labels = self.dropout(labels) label_h, label_c = labels.chunk(2, 1) label_h = label_h.contiguous() label_c = label_c.contiguous() order_h = self.dropout(order_h) # [batch, length, length] out_arc = self.attention(arc_h, arc_c, mask_d=attention_mask, mask_e=attention_mask).squeeze(dim=1) # [batch, length, max_parsing_order] logits_order = self.order_classifier(order_h) batch, max_len, label_space = label_h.size() if order_ids is not None and head_ids is not None and label_ids is not None: # create batch index [batch] batch_index = torch.arange(0, batch).type_as(out_arc).long() # get vector for head_ids [batch, length, label_space], label_h = label_h[batch_index, head_ids.t()].transpose(0, 1).contiguous() # compute output for type [batch, length, num_labels] out_label = self.bilinear(label_h, label_c) # mask invalid position to -inf for log_softmax if attention_mask is not None: minus_inf = -1e8 minus_mask = (1 - attention_mask) * minus_inf out_arc = out_arc + minus_mask.unsqueeze(2) + minus_mask.unsqueeze(1) # loss_arc shape [batch, length, length] loss_arc = F.log_softmax(out_arc, dim=1) # loss_label shape [batch, length, num_labels] loss_label = F.log_softmax(out_label, dim=2) # mask invalid position to 0 for sum loss if attention_mask is not None: loss_arc = loss_arc * attention_mask.unsqueeze(2) * attention_mask.unsqueeze(1) loss_label = loss_label * attention_mask.unsqueeze(2) # number of valid positions which contribute to loss (remove the symbolic head for each sentence. num = attention_mask.sum() - batch else: # number of valid positions which contribute to loss (remove the symbolic head for each sentence. num = float(max_len - 1) * batch # first create index matrix [length, batch] child_index = torch.arange(0, max_len).view(max_len, 1).expand(max_len, batch) child_index = child_index.type_as(out_arc).long() # [length-1, batch] loss_arc = loss_arc[batch_index, head_ids.t(), child_index][1:] loss_label = loss_label[batch_index, child_index, label_ids.t()][1:] # loss_fct = CrossEntropyLoss(reduction="sum") # Only keep active parts of the loss if attention_mask is not None: active_loss = attention_mask.view(-1) == 1 active_logits_order = logits_order.view(-1, self.max_parsing_order)[active_loss] active_order_ids = order_ids.view(-1)[active_loss] loss_order = loss_fct(active_logits_order, active_order_ids) else: loss_order = loss_fct(logits_order.view(-1, self.max_parsing_order), order_ids.view(-1)) total_loss = (-loss_arc.sum() / num) + (-loss_label.sum() / num) + (loss_order / num) outputs = (total_loss, ) else: label_h = label_h.unsqueeze(2).expand(batch, max_len, max_len, label_space).contiguous() label_c = label_c.unsqueeze(1).expand(batch, max_len, max_len, label_space).contiguous() # compute output for label [batch, length, length, num_labels] out_label = self.bilinear(label_h, label_c) # mask invalid position to -inf for log_softmax if attention_mask is not None: minus_inf = -1e8 minus_mask = (1 - attention_mask) * minus_inf out_arc = out_arc + minus_mask.unsqueeze(2) + minus_mask.unsqueeze(1) # logits_arc shape [batch, length, length] logits_arc = F.log_softmax(out_arc, dim=1) # logits_label shape [batch, num_labels, length, length] logits_label = F.log_softmax(out_label, dim=3).permute(0, 3, 1, 2) # [batch, num_labels, length, length] energy = torch.exp(logits_arc.unsqueeze(1) + logits_label) outputs = (energy, logits_arc, logits_label, logits_order) return outputs

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Python

axisafe/elements.py

michalkalkowski/axisym-safe-python

7456d32b1a5ac7ca3881ade9b597bfef18acdc3e

[ "MIT" ]

4

2019-07-03T07:31:18.000Z

2021-08-30T17:13:06.000Z

axisafe/elements.py

michalkalkowski/axisym-safe-python

7456d32b1a5ac7ca3881ade9b597bfef18acdc3e

[ "MIT" ]

null

axisafe/elements.py

michalkalkowski/axisym-safe-python

7456d32b1a5ac7ca3881ade9b597bfef18acdc3e

[ "MIT" ]

2

2019-09-23T09:10:22.000Z

2022-01-05T01:12:30.000Z

""" ============================================================================== Copyright (C) 2016--2017 Michal Kalkowski (MIT License) kalkowski.m@gmail.com This is a part of the axisafe package developed for simulating elastic wave propagation in buried/submerged fluid-filled waveguides. The package is based on the publication: Kalkowski MK et al. Axisymmetric semi-analytical finite elements for modelling waves in buried/submerged fluid-filled waveguides. Comput Struct (2017), https://doi.org/10.1016/j.compstruc.2017.10.004 This file contains element definitions. ============================================================================== """ from __future__ import print_function import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import splrep, splev from . import shape_functions as shape_fun def gamma_PML(x, gamma, PML_start, PML_thk): """ Polynomial stretching profile for a perfectly matched layer. Parameters: x : physical coordinate gamma : average value of the profile PML_start : where the PML starts PML_thk : thickness of the PML Returns: the value of the profile function at x """ return 1 + 3*(gamma - 1)*((abs(x - PML_start))/PML_thk)**2 def gamma_PML_exp(x, gamma, PML_start, PML_thk): """ Polynomial stretching profile for a perfectly matched layer. Parameters: x : physical coordinate gamma : profile parameters in the form a + 1j*b PML_start : where the PML starts PML_thk : thickness of the PML Returns: the value of the profile function at x """ local_x = (x - PML_start)/PML_thk return np.exp(gamma.real*local_x) - 1j*(np.exp(gamma.imag*local_x)- 1) class SLAX6(object): """ Class for an axisymmetric 1D line element with nodes wrt GLL quadrature and higher order Lagrange interpolating polynomials u = [ur utheta uz] strain directions = [rr tt zz tz rz rt] n is the circumferential order number Here six matrices are assembled and the circumferential order is applied at a later stage """ def __init__(self, nodes_at, n): """ Initialise the element with node locations. Parameters: nodes_at : node locations """ self.n = n self.nodes_at = nodes_at self.nodes_per_el = len(nodes_at) self.no_of_dofs = sum([3]*self.nodes_per_el) # define basic properties of the element (no of nodes, etc.) self.dofs_per_node = [3]*self.nodes_per_el self.dofs_domain = [['s']*3]*self.nodes_per_el self.dofs_per_el = sum(self.dofs_per_node) # define T transormation component self.T_components = [[1, 1j, 1j]]*self.nodes_per_el self.C = None self.loss_factor = None self.rho = None # Pre-allocate the arrays self.K_Fz = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_Ft = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F1 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F2 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F3 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_1 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_2 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_3 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_4 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_5 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_6 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.M = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex64') self.Hs0 = None self.Hs1 = None def add_properties(self, list_of_props): """Assign mechanical properties and the circumferential order. Parameters: list_of_props : [lame_1, lame_2, denisty, loss_factor] n : circumferential order """ # assign the properties self.loss_factor = list_of_props[3] lame_1 = list_of_props[0] lame_2 = list_of_props[1] self.C = (1 + self.loss_factor*1.0j)*\ np.array([(lame_1 + 2*lame_2, lame_1, lame_1, 0, 0, 0), (lame_1, lame_1 + 2*lame_2, lame_1, 0, 0, 0), (lame_1, lame_1, lame_1 + 2*lame_2, 0, 0, 0), (0, 0, 0, lame_2, 0, 0), (0, 0, 0, 0, lame_2, 0), (0, 0, 0, 0, 0, lame_2)]) self.rho = list_of_props[2] def inspect_shape_fun(self): """ This function computes and plots shape functions in the natural coordinates together with their derivatives. (not updated for long) """ ksi, _ = shape_fun.build_GLL_quadrature(len(self.nodes_at)) xi_dense = np.linspace(-1, 1, 100) N, dN = shape_fun.lagrange_poly(xi_dense, len(ksi)) _, (ax1, ax2) = plt.subplots(2, 1, sharex=True) ax1_limits = 1.2*np.min(N), 1.2*np.max(N) ax2_limits = 1.2*np.min(dN), 1.2*np.max(dN) ax2.set_xlabel(r'$\xi$') ax1.set_xlabel(r'shape functions') ax2.set_xlabel(r'shape functions derivatives') for this_xi in ksi: ax1.plot(2*[this_xi], list(ax1_limits), '--', c='red') ax2.plot(2*[this_xi], list(ax2_limits), '--', c='red') ax1.plot(xi_dense, N.T) ax2.plot(xi_dense, dN.T) ax1.set_title(r'Spectral element of order ' + \ str(len(self.nodes_at) - 1) + ' with ' +\ str(len(self.nodes_at)) + ' nodes.') def calculate_matrices(self): """Calculates the shape function and B matrices including Jacobian*Gauss Weight* det(Jacobian) at all Gauss quadrature points""" # get the nodal locations weights and shape functions for a given GLL quadrature ksis, weights, NN, NN_r, JJ = \ shape_fun.line_spectral_GLL_lagrange(self.nodes_at) # extract the matrices and sum at each integration point for i in range(len(ksis)): # shape funcion values at current location are NN[:, i] # generate the shape function matrix in standard form diagonals = [[funct]*3 for funct in NN[:, i]] N = np.column_stack([np.diag(diagonal) for diagonal in diagonals]) diagonals_r = [[funct]*3 for funct in NN_r[:, i]] N_r = np.column_stack([np.diag(diagonal) for diagonal in diagonals_r]) # local radius in physical coordinates r_i = self.nodes_at.dot(NN[:, i]) # differential operator matrices L_z = np.zeros([6, 3]) L_theta = np.zeros([6, 3]) L_r = np.zeros([6, 3]) L = np.zeros([6, 3]) L_z[2, 2], L_z[3, 1], L_z[4, 0] = 1, 1, 1 L_r[0, 0], L_r[4, 2], L_r[5, 1] = 1, 1, 1 L[1, 0], L[5, 1] = 1.0, -1.0 L_theta[1, 1], L_theta[3, 2], L_theta[5, 0] = 1, 1, 1 B_1 = L.dot(N)/r_i + L_r.dot(N_r) B_2 = L_theta.dot(N)/r_i B_3 = L_z.dot(N) K_F1 = B_1.T.dot(self.C).dot(B_3) K_F2 = B_1.T.dot(self.C).dot(B_2) K_F3 = B_2.T.dot(self.C).dot(B_3) K_1 = B_1.T.dot(self.C).dot(B_1) K_2 = K_F2.T - K_F2 K_3 = K_F1.T - K_F1 K_4 = K_F3.T + K_F3 K_5 = B_2.T.dot(self.C).dot(B_2) K_6 = B_3.T.dot(self.C).dot(B_3) K_F = K_F1.T K_Ft = K_F3.T K_Fz = K_6 M = self.rho*N.T.dot(N) # perform the integration self.K_F += 2*np.pi*weights[i]*K_F*JJ[i]*r_i self.K_Ft += 2*np.pi*weights[i]*K_Ft*JJ[i]*r_i self.K_Fz += 2*np.pi*weights[i]*K_Fz*JJ[i]*r_i self.K_F1 += 2*np.pi*weights[i]*K_F1*JJ[i]*r_i self.K_F2 += 2*np.pi*weights[i]*K_F2*JJ[i]*r_i self.K_F3 += 2*np.pi*weights[i]*K_F3*JJ[i]*r_i self.K_1 += 2*np.pi*weights[i]*K_1*JJ[i]*r_i self.K_2 += 2*np.pi*weights[i]*K_2*JJ[i]*r_i self.K_3 += 2*np.pi*weights[i]*K_3*JJ[i]*r_i self.K_4 += 2*np.pi*weights[i]*K_4*JJ[i]*r_i self.K_5 += 2*np.pi*weights[i]*K_5*JJ[i]*r_i self.K_6 += 2*np.pi*weights[i]*K_6*JJ[i]*r_i self.M += 2*np.pi*weights[i]*M*JJ[i]*r_i # if the element is coupled to fluid elements - create the ingredients # of the coupling matrices normal = np.array([1, 0, 0]).reshape(-1, 1) diagonals = [[funct]*3 for funct in NN[:, 0]] N_u = np.column_stack([np.diag(diagonal) for diagonal in diagonals]) self.Hs0 = 2*np.pi*N_u.T.dot(normal) diagonals = [[funct]*3 for funct in NN[:, -1]] N_u = np.column_stack([np.diag(diagonal) for diagonal in diagonals]) self.Hs1 = 2*np.pi*N_u.T.dot(normal)*self.nodes_at[-1] class ALAX6(object): """ Class for an acoustic axisymmetric 1D line element with nodes wrt GLL quadrature and higher order Lagrange interpolating polynomials Each node has one degree of freedom- velocity potential n is the circumferential order number""" def __init__(self, nodes_at, n): """ Initialise the element with node locations. Parameters: nodes_at : node locations """ self.nodes_at = nodes_at self.nodes_per_el = len(nodes_at) self.no_of_dofs = self.nodes_per_el # define basic properties of the element self.dofs_per_node = [1]*self.nodes_per_el self.dofs_domain = [['f']]*self.nodes_per_el self.dofs_per_el = sum(self.dofs_per_node) # define T-transformation components self.T_components = [[1]]*self.nodes_per_el self.c_p = None self.rho = None self.n = n # Pre-allocate the arrays self.K_Fz = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_Ft = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_1 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dz*dz self.K_2 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta*dz self.K_3 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dz self.K_4 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta*dtheta self.K_5 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta self.K_6 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # - self.M = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='float64') self.Hf0 = None self.Hf1 = None def add_properties(self, list_of_props): """Assign mechanical properties. Parameters: list_of_props : [bulk modulus, density] """ # assign properties self.c_p = (list_of_props[0]/list_of_props[1])**0.5 self.rho = list_of_props[1] def calculate_matrices(self): """Calculates the shape function and b matrices including Jacobian*Gauss Weight* det(Jacobian) at all Gauss quadrature points""" # get the nodal locations weights and shape functions for a given GLL quadrature ksis, weights, NN, NN_r, JJ = \ shape_fun.line_spectral_GLL_lagrange(self.nodes_at) # extract the matrices and sum at each integration point for i in range(len(ksis)): # shape funcion values at current location are NN[:, i] # generate the shape function matrix in standard form N = NN[:, i].reshape(1, -1) N_r = NN_r[:, i].reshape(1, -1) # local radius in physical coordinates r_i = self.nodes_at.dot(NN[:, i]) K_1 = N_r.T.dot(N_r) K_5 = 1/r_i**2*N.T.dot(N) K_6 = N.T.dot(N) M = N.T.dot(N)/self.c_p**2 # perform the integration self.K_6 += -self.rho*2*np.pi*weights[i]*K_6*JJ[i]*r_i self.K_1 += -self.rho*2*np.pi*weights[i]*K_1*JJ[i]*r_i self.K_5 += -self.rho*2*np.pi*weights[i]*K_5*JJ[i]*r_i self.K_Fz += -self.rho*2*np.pi*weights[i]*K_6*JJ[i]*r_i self.K_Ft += -self.rho*2*np.pi*weights[i]*K_5*JJ[i]*r_i self.M += -self.rho*2*np.pi*weights[i]*M*JJ[i]*r_i # if the element is coupled to solid elements - create the ingredients # of the coupling matrices N_phi = NN[:, 0].reshape(-1, 1) self.Hf0 = self.rho*N_phi N_phi = NN[:, -1].reshape(-1, 1) self.Hf1 = self.rho*N_phi*self.nodes_at[-1] class SLAX6_core(object): """ Class for an axisymmetric core (with a node at the axis of symmetry) 1D line element with nodes wrt GLJ quadrature and higher order Lagrange interpolating polynomials u = [ur utheta uz] strain directions = [rr tt zz tz rz rt] n is the circumferential order number Here six matrices are assembled and the circumferential order is applied at a later stage""" def __init__(self, nodes_at, n): """ Initialise the element with node locations. Parameters: nodes_at : node locations """ self.nodes_at = nodes_at self.nodes_per_el = len(nodes_at) # double-check if there is a node at the axis of symmetry # specify basic element characteristics given the circumferential order if 0 in self.nodes_at: if n == 0: self.dofs_per_node = [1] + [3]*(self.nodes_per_el - 1) self.dofs_domain = [['s']*1] + [['s']*3]*(self.nodes_per_el - 1) self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[1j]] + [[1, 1j, 1j]]*(self.nodes_per_el - 1) elif n == 1: self.dofs_per_node = [2] + [3]*(self.nodes_per_el - 1) self.dofs_domain = [['s']*2] + [['s']*3]*(self.nodes_per_el - 1) self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[1, 1j]] + [[1, 1j, 1j]]*(self.nodes_per_el - 1) elif n > 1: self.dofs_per_node = [0] + [3]*(self.nodes_per_el - 1) self.dofs_domain = [[]] + [['s']*3]*(self.nodes_per_el - 1) self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[]] + [[1, 1j, 1j]]*(self.nodes_per_el - 1) else: self.dofs_per_node = [3]*self.nodes_per_el self.dofs_domain = [['s']*3]*self.nodes_per_el self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[1, 1j, 1j]]*self.nodes_per_el self.n = n self.C = None self.loss_factor = None self.rho = None # preallocate the arrays # use full size - respective dofs will be rmoved at a later stage no_of_dofs = sum([3]*self.nodes_per_el) # keep the attribute no of dofs not set self.no_of_dofs = None self.K_Fz = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_Ft = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_F = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_F1 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_F2 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_F3 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_1 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_2 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_3 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_4 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_5 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.K_6 = np.zeros([no_of_dofs, no_of_dofs], dtype='complex') self.M = np.zeros([no_of_dofs, no_of_dofs], dtype='complex64') self. Hs1 = None def add_properties(self, list_of_props): """Assign mechanical properties and the circumferential order. Parameters: list_of_props : [lame_1, lame_2, denisty, loss_factor] n : circumferential order """ # assign the properties self.loss_factor = list_of_props[3] lame_1 = list_of_props[0] lame_2 = list_of_props[1] self.C = (1 + self.loss_factor*1.0j)*\ np.array([(lame_1 + 2*lame_2, lame_1, lame_1, 0, 0, 0), (lame_1, lame_1 + 2*lame_2, lame_1, 0, 0, 0), (lame_1, lame_1, lame_1 + 2*lame_2, 0, 0, 0), (0, 0, 0, lame_2, 0, 0), (0, 0, 0, 0, lame_2, 0), (0, 0, 0, 0, 0, lame_2)]) self.rho = list_of_props[2] def inspect_shape_fun(self): """ This function computes and plots shape functions in the natural coordinates together with their derivatives. (not updated for long) """ ksi, _ = shape_fun.build_GLJ_quadrature(len(self.nodes_at)) xi_dense = np.linspace(-1, 1, 100) N, _ = shape_fun.lagrange_GLJ(xi_dense, len(ksi)) dN = np.column_stack([splev(xi_dense, splrep(xi_dense, N[:, i]), der=1) \ for i in range(N.shape[1])]) _, (ax1, ax2) = plt.subplots(2, 1, sharex=True) ax1_limits = 1.2*np.min(N), 1.2*np.max(N) ax2_limits = 1.2*np.min(dN), 1.2*np.max(dN) ax2.set_xlabel(r'$\xi$') ax1.set_xlabel(r'shape functions') ax2.set_xlabel(r'shape functions derivatives') for this_xi in ksi: ax1.plot(2*[this_xi], list(ax1_limits), '--', c='red') ax2.plot(2*[this_xi], list(ax2_limits), '--', c='red') ax1.plot(xi_dense, N) ax2.plot(xi_dense, dN) ax1.set_title(r'Spectral element of order ' + \ str(len(self.nodes_at) - 1) + ' with ' +\ str(len(self.nodes_at)) + ' nodes.') def calculate_matrices(self): """Calculates the shape function and B matrices including Jacobian*Gauss Weight* det(Jacobian) at all Gauss quadrature points""" # get the nodal locations weights and shape functions for a given GLJ quadrature ksis, weights, NN, NN_r, JJ = \ shape_fun.line_spectral_GLJ_lagrange(self.nodes_at) # extract the matrices and sum at each integration point for i, ksi in enumerate(list(ksis)): # shape funcion values at current location are NN[:, i] # generate the shape function matrix in standard form diagonals = [[funct]*3 for funct in NN[:, i]] N = np.column_stack([np.diag(diagonal) for diagonal in diagonals]) diagonals_r = [[funct]*3 for funct in NN_r[:, i]] N_r = np.column_stack([np.diag(diagonal) for diagonal in diagonals_r]) # local r in physical coordinates r_i = self.nodes_at[i] # scale the radius according to the de'l'Hospital's rule for the axis # singularity w = 1 + ksi if np.round(r_i, 7) == 0: rat = JJ[i] else: rat = r_i/w # differential operator matrices L_z = np.zeros([6, 3]) L_theta = np.zeros([6, 3]) L_r = np.zeros([6, 3]) L = np.zeros([6, 3]) L_z[2, 2], L_z[3, 1], L_z[4, 0] = 1, 1, 1 L_r[0, 0], L_r[4, 2], L_r[5, 1] = 1, 1, 1 L[1, 0], L[5, 1] = 1.0, -1.0 L_theta[1, 1], L_theta[3, 2], L_theta[5, 0] = 1, 1, 1 # use different forms for the axis of symmetry and the rest of the domain if np.round(r_i, 7) == 0: B_1 = L.dot(N_r) + L_r.dot(N_r) B_2 = L_theta.dot(N_r) B_3 = L_z.dot(N) else: B_1 = L.dot(N)/r_i + L_r.dot(N_r) B_2 = L_theta.dot(N)/r_i B_3 = L_z.dot(N) K_F1 = B_1.T.dot(self.C).dot(B_3) K_F2 = B_1.T.dot(self.C).dot(B_2) K_F3 = B_2.T.dot(self.C).dot(B_3) K_1 = B_1.T.dot(self.C).dot(B_1) K_2 = K_F2.T - K_F2 K_3 = K_F1.T - K_F1 K_4 = K_F3.T + K_F3 K_5 = B_2.T.dot(self.C).dot(B_2) K_6 = B_3.T.dot(self.C).dot(B_3) K_F = K_F1.T K_Ft = K_F3.T K_Fz = K_6 M = self.rho*N.T.dot(N) # GLJ integration self.K_F += 2*np.pi*weights[i]*K_F*JJ[i]*rat self.K_Ft += 2*np.pi*weights[i]*K_Ft*JJ[i]*rat self.K_Fz += 2*np.pi*weights[i]*K_Fz*JJ[i]*rat self.K_F1 += 2*np.pi*weights[i]*K_F1*JJ[i]*rat self.K_F2 += 2*np.pi*weights[i]*K_F2*JJ[i]*rat self.K_F3 += 2*np.pi*weights[i]*K_F3*JJ[i]*rat self.K_1 += 2*np.pi*weights[i]*K_1*JJ[i]*rat self.K_2 += 2*np.pi*weights[i]*K_2*JJ[i]*rat self.K_3 += 2*np.pi*weights[i]*K_3*JJ[i]*rat self.K_4 += 2*np.pi*weights[i]*K_4*JJ[i]*rat self.K_5 += 2*np.pi*weights[i]*K_5*JJ[i]*rat self.K_6 += 2*np.pi*weights[i]*K_6*JJ[i]*rat self.M += 2*np.pi*weights[i]*M*JJ[i]*rat # if the element is coupled to fluid elements - create the ingredients # of the coupling matrices normal = np.array([1, 0, 0]).reshape(-1, 1) diagonals = [[funct]*3 for funct in NN[:, -1]] N_u = np.column_stack([np.diag(diagonal) for diagonal in diagonals]) self.Hs1 = 2*np.pi*N_u.T.dot(normal)*self.nodes_at[-1] # apply the boundary conditions at the axis of symmetry if 0 in self.nodes_at: if self.n == 0: self.K_1 = np.delete(np.delete(self.K_1, [0, 1], 0), [0, 1], 1) self.K_2 = np.delete(np.delete(self.K_2, [0, 1], 0), [0, 1], 1) self.K_3 = np.delete(np.delete(self.K_3, [0, 1], 0), [0, 1], 1) self.K_4 = np.delete(np.delete(self.K_4, [0, 1], 0), [0, 1], 1) self.K_5 = np.delete(np.delete(self.K_5, [0, 1], 0), [0, 1], 1) self.K_6 = np.delete(np.delete(self.K_6, [0, 1], 0), [0, 1], 1) self.M = np.delete(np.delete(self.M, [0, 1], 0), [0, 1], 1) self.K_F = np.delete(np.delete(self.K_F, [0, 1], 0), [0, 1], 1) self.K_Ft = np.delete(np.delete(self.K_Ft, [0, 1], 0), [0, 1], 1) self.K_Fz = np.delete(np.delete(self.K_Fz, [0, 1], 0), [0, 1], 1) self.Hs1 = 2*np.pi*N_u[:, 2:].T.dot(normal)*self.nodes_at[-1] elif self.n == 1: self.K_1 = np.delete(np.delete(self.K_1, [2], 0), [2], 1) self.K_2 = np.delete(np.delete(self.K_2, [2], 0), [2], 1) self.K_3 = np.delete(np.delete(self.K_3, [2], 0), [2], 1) self.K_4 = np.delete(np.delete(self.K_4, [2], 0), [2], 1) self.K_5 = np.delete(np.delete(self.K_5, [2], 0), [2], 1) self.K_6 = np.delete(np.delete(self.K_6, [2], 0), [2], 1) self.M = np.delete(np.delete(self.M, [2], 0), [2], 1) self.K_F = np.delete(np.delete(self.K_F, [2], 0), [2], 1) self.K_Ft = np.delete(np.delete(self.K_Ft, [2], 0), [2], 1) self.K_Fz = np.delete(np.delete(self.K_Fz, [2], 0), [2], 1) self.Hs1 = 2*np.pi*np.delete(N_u, [2], 1).T.dot(normal)*self.nodes_at[-1] elif self.n > 1: self.K_1 = np.delete(np.delete(self.K_1, [0, 1, 2], 0), [0, 1, 2], 1) self.K_2 = np.delete(np.delete(self.K_2, [0, 1, 2], 0), [0, 1, 2], 1) self.K_3 = np.delete(np.delete(self.K_3, [0, 1, 2], 0), [0, 1, 2], 1) self.K_4 = np.delete(np.delete(self.K_4, [0, 1, 2], 0), [0, 1, 2], 1) self.K_5 = np.delete(np.delete(self.K_5, [0, 1, 2], 0), [0, 1, 2], 1) self.K_6 = np.delete(np.delete(self.K_6, [0, 1, 2], 0), [0, 1, 2], 1) self.M = np.delete(np.delete(self.M, [0, 1, 2], 0), [0, 1, 2], 1) self.K_F = np.delete(np.delete(self.K_F, [0, 1, 2], 0), [0, 1, 2], 1) self.K_Ft = np.delete(np.delete(self.K_Ft, [0, 1, 2], 0), [0, 1, 2], 1) self.K_Fz = np.delete(np.delete(self.K_Fz, [0, 1, 2], 0), [0, 1, 2], 1) self.Hs1 = 2*np.pi*N_u[:, 3:].T.dot(normal)*self.nodes_at[-1] self.no_of_dofs = self.K_1.shape[0] class ALAX6_core(object): """ Class for an acoustic axisymmetric 1D line core element (with a node at the axis of symmetry) with nodes wrt GLJ quadrature and higher order Lagrange interpolating polynomials. Each node has one degree of freedom- velocity potential n is the circumferential order number""" def __init__(self, nodes_at, n): """ Initialise the element with node locations. Parameters: nodes_at : node locations """ self.nodes_at = nodes_at self.nodes_per_el = len(nodes_at) self.no_of_dofs = self.nodes_per_el self.n = n # doulbe-check if there is a node at the axis of symmetry # define basic properties of the element and T-transformation if 0 in self.nodes_at and n != 0: self.dofs_per_node = [0] + [1]*(self.nodes_per_el - 1) self.dofs_domain = [[]] + [['f']]*(self.nodes_per_el - 1) self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[]] + [[1]]*(self.nodes_per_el - 1) else: self.dofs_per_node = [1]*self.nodes_per_el self.dofs_domain = [['f']]*self.nodes_per_el self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[1]]*self.nodes_per_el self.c_p = None self.rho = None # preallocate the arrays self.K_Fz = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_Ft = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_1 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dz*dz self.K_2 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta*dz self.K_3 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dz self.K_4 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta*dtheta self.K_5 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta self.K_6 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # - self.M = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='float64') self.Hf1 = None def add_properties(self, list_of_props): """Assign mechanical properties. Parameters: list_of_props : [bulk modulus, density] """ # assign properties self.c_p = (list_of_props[0]/list_of_props[1])**0.5 self.rho = list_of_props[1] def inspect_shape_fun(self): """ This function computes and plots shape functions in the natural coordinates together with their derivatives (not updated for long) """ ksi, _ = shape_fun.build_GLJ_quadrature(len(self.nodes_at)) xi_dense = np.linspace(-1, 1, 100) N, _ = shape_fun.lagrange_GLJ(xi_dense, len(ksi)) dN = np.column_stack([splev(xi_dense, splrep(xi_dense, N[:, i]), der=1) \ for i in range(N.shape[1])]) _, (ax1, ax2) = plt.subplots(2, 1, sharex=True) ax1_limits = 1.2*np.min(N), 1.2*np.max(N) ax2_limits = 1.2*np.min(dN), 1.2*np.max(dN) ax2.set_xlabel(r'$\xi$') ax1.set_xlabel(r'shape functions') ax2.set_xlabel(r'shape functions derivatives') for this_xi in ksi: ax1.plot(2*[this_xi], list(ax1_limits), '--', c='red') ax2.plot(2*[this_xi], list(ax2_limits), '--', c='red') ax1.plot(xi_dense, N) ax2.plot(xi_dense, dN) ax1.set_title(r'Spectral element of order ' + \ str(len(self.nodes_at) - 1) + ' with ' +\ str(len(self.nodes_at)) + ' nodes.') def calculate_matrices(self): """Calculates the shape function and b matrices including Jacobian*Gauss Weight* det(Jacobian) at all Gauss quadrature points""" # get the nodal locations weights and shape functions for a given GLJ quadrature ksis, weights, NN, NN_r, JJ = \ shape_fun.line_spectral_GLJ_lagrange(self.nodes_at) # extract the matrices and sum at each integration point for i, ksi in enumerate(list(ksis)): # shape funcion values at current location are NN[:, i] # generate the shape function matrix in standard form N = NN[:, i].reshape(1, -1) N_r = NN_r[:, i].reshape(1, -1) # local r in physcial coordinates r_i = self.nodes_at.dot(NN[:, i]) # scale the radius according to the de'l'Hospital's rule for the axis # singularity w = 1 + ksi if np.round(r_i, 7) == 0: rat = JJ[i] else: rat = r_i/w # use different forms for the axis of symmetri and the rest of the domain if np.round(r_i, 7) == 0: K_5 = N_r.T.dot(N_r) else: K_5 = 1/r_i**2*N.T.dot(N) K_1 = N_r.T.dot(N_r) K_6 = N.T.dot(N) M = N.T.dot(N)/self.c_p**2 # GLJ integration self.K_1 += -self.rho*2*np.pi*weights[i]*K_1*JJ[i]*rat self.K_5 += -self.rho*2*np.pi*weights[i]*K_5*JJ[i]*rat self.K_6 += -self.rho*2*np.pi*weights[i]*K_6*JJ[i]*rat self.K_Fz += -self.rho*2*np.pi*weights[i]*K_6*JJ[i]*rat self.K_Ft += -self.rho*2*np.pi*weights[i]*K_5*JJ[i]*rat self.M += -self.rho*2*np.pi*weights[i]*M*JJ[i]*rat # if the element is coupled to solid elements - create the ingredients # of the coupling matrices N_phi = NN[:, -1].reshape(-1, 1) self.Hf1 = self.rho*N_phi*self.nodes_at[-1] # apply the boundary conditions at the axis of symmetry if (0 in self.nodes_at) & (self.n != 0): self.K_1 = np.delete(np.delete(self.K_1, [0], 0), [0], 1) self.K_5 = np.delete(np.delete(self.K_5, [0], 0), [0], 1) self.K_6 = np.delete(np.delete(self.K_6, [0], 0), [0], 1) self.M = np.delete(np.delete(self.M, [0], 0), [0], 1) self.K_F = np.delete(np.delete(self.K_F, [0], 0), [0], 1) self.K_Ft = np.delete(np.delete(self.K_Ft, [0], 0), [0], 1) self.K_Fz = np.delete(np.delete(self.K_Fz, [0], 0), [0], 1) class SLAX6_PML(object): """ Class for an axisymmetric PML 1D line element with nodes wrt GLL quadrature and higher order Lagrange interpolating polynomials u = [ur utheta uz] strain directions = [rr tt zz tz rz rt] n is the circumferential order number""" def __init__(self, nodes_at, n, PML_params, PML_function=gamma_PML_exp): """ Initialise the element with node locations and PML parameters Parameters: nodes_at : node locations PML_params : parameters of the PML as a list [start, thickness, a + 1j*b] PML_function : function defining the PML profile (exponential by default) """ self.nodes_at = nodes_at self.nodes_per_el = len(nodes_at) self.no_of_dofs = 3*self.nodes_per_el # specify basic element characteristics and T-transformation self.dofs_per_node = [3]*self.nodes_per_el self.dofs_domain = [['s']*3]*self.nodes_per_el self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[1, 1j, 1j]]*self.nodes_per_el self.n = n self.C = None self.loss_factor = None self.rho = None # preallocate the arrays self.K_Fz = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_Ft = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_1 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_2 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_3 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_4 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_5 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_6 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.M = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.Hs0 = None self.PML_start = PML_params[0] self.PML_thk = PML_params[1] self.gamma = PML_params[2] self.PML_function = PML_function def add_properties(self, list_of_props): """Assign mechanical properties and the circumferential order. Parameters: list_of_props : [lame_1, lame_2, denisty, loss_factor] n : circumferential order """ # assign the properties self.loss_factor = list_of_props[3] lame_1 = list_of_props[0] lame_2 = list_of_props[1] self.C = (1 + self.loss_factor*1.0j)*\ np.array([(lame_1 + 2*lame_2, lame_1, lame_1, 0, 0, 0), (lame_1, lame_1 + 2*lame_2, lame_1, 0, 0, 0), (lame_1, lame_1, lame_1 + 2*lame_2, 0, 0, 0), (0, 0, 0, lame_2, 0, 0), (0, 0, 0, 0, lame_2, 0), (0, 0, 0, 0, 0, lame_2)]) self.rho = list_of_props[2] def calculate_matrices(self): """Calculates the shape function and b matrices including Jacobian*Gauss Weight* det(Jacobian) at all Gauss quadrature points""" # get the nodal locations weights and shape functions for a given GLJ quadrature ksis, weights, NN, NN_r, JJ = \ shape_fun.line_spectral_GLL_lagrange(self.nodes_at) # extract the matrices and sum at each integration point for i in range(len(ksis)): # shape funcion values at current location are NN[:, i] # generate the shape function matrix in standard form diagonals = [[funct]*3 for funct in NN[:, i]] N = np.column_stack([np.diag(diagonal) for diagonal in diagonals]) diagonals_r = [[funct]*3 for funct in NN_r[:, i]] N_r = np.column_stack([np.diag(diagonal) for diagonal in diagonals_r]) # local r in physical coordinates r_i = self.nodes_at.dot(NN[:, i]) # calculate the stretched r if self.PML_function is gamma_PML: r_tilde = -(self.gamma - 1)*(self.PML_start - r_i)**3/self.PML_thk**2 + r_i elif self.PML_function is gamma_PML_exp: local_r = (r_i - self.PML_start)/self.PML_thk r_tilde = self.PML_start + self.PML_thk/self.gamma.real*( np.exp(self.gamma.real*local_r) - 1) - \ 1j*self.PML_thk/self.gamma.imag*( np.exp(self.gamma.imag*local_r) - 1) + 1j*local_r*self.PML_thk else: print('Error. No such PML function defined') # calculate the value of the PML profile at current integration point current_gamma = self.PML_function(r_i, self.gamma, \ self.PML_start, self.PML_thk) # differential operator matrices L_z = np.zeros([6, 3]) L_theta = np.zeros([6, 3]) L_r = np.zeros([6, 3]) L = np.zeros([6, 3]) L_z[2, 2], L_z[3, 1], L_z[4, 0] = 1, 1, 1 L_r[0, 0], L_r[4, 2], L_r[5, 1] = 1, 1, 1 L[1, 0], L[5, 1] = 1.0, -1.0 L_theta[1, 1], L_theta[3, 2], L_theta[5, 0] = 1, 1, 1 B_1 = L.dot(N)/r_tilde + 1/current_gamma*L_r.dot(N_r) B_2 = L_theta.dot(N)/r_tilde B_3 = L_z.dot(N) K_F1 = B_1.T.dot(self.C).dot(B_3) K_F2 = B_1.T.dot(self.C).dot(B_2) K_F3 = B_2.T.dot(self.C).dot(B_3) K_1 = B_1.T.dot(self.C).dot(B_1) K_2 = K_F2.T - K_F2 K_3 = K_F1.T - K_F1 K_4 = K_F3.T + K_F3 K_5 = B_2.T.dot(self.C).dot(B_2) K_6 = B_3.T.dot(self.C).dot(B_3) K_F = K_F1.T K_Ft = K_F3.T K_Fz = K_6 M = self.rho*N.T.dot(N) # GLL integration self.K_F += 2*np.pi*weights[i]*K_F*JJ[i]*r_tilde*current_gamma self.K_Ft += 2*np.pi*weights[i]*K_Ft*JJ[i]*r_tilde*current_gamma self.K_Fz += 2*np.pi*weights[i]*K_Fz*JJ[i]*r_tilde*current_gamma self.K_1 += 2*np.pi*weights[i]*K_1*JJ[i]*r_tilde*current_gamma self.K_2 += 2*np.pi*weights[i]*K_2*JJ[i]*r_tilde*current_gamma self.K_3 += 2*np.pi*weights[i]*K_3*JJ[i]*r_tilde*current_gamma self.K_4 += 2*np.pi*weights[i]*K_4*JJ[i]*r_tilde*current_gamma self.K_5 += 2*np.pi*weights[i]*K_5*JJ[i]*r_tilde*current_gamma self.K_6 += 2*np.pi*weights[i]*K_6*JJ[i]*r_tilde*current_gamma self.M += 2*np.pi*weights[i]*M*JJ[i]*r_tilde*current_gamma # if the element is coupled to fluid elements - create the ingredients # of the coupling matrices normal = np.array([1, 0, 0]) diagonals = [[funct]*3 for funct in NN[:, 0]] N_u = np.column_stack([np.diag(diagonal) for diagonal in diagonals]) self.Hs0 = 2*np.pi*N_u.T.dot(normal.reshape(-1, 1)) class ALAX6_PML(object): """ Class for an acoustic axisymmetric 1D line element with nodes wrt GLL quadrature and higher order Lagrange interpolating polynomials belonging to a PML each node has one degree of freedom - velocity potential n is the circumferential order number""" def __init__(self, nodes_at, n, PML_params, PML_function=gamma_PML_exp): """ Initialise the element with node locations and PML parameters Parameters: nodes_at : node locations PML_params : parameters of the PML as a list [start, thickness, a + 1j*b] PML_function : function defining the PML profile (exponential by default) """ self.nodes_at = nodes_at self.nodes_per_el = len(nodes_at) self.no_of_dofs = self.nodes_per_el # define basic properties of the element and T-transformation self.dofs_per_node = [1]*self.nodes_per_el self.dofs_domain = [['f']]*self.nodes_per_el self.dofs_per_el = sum(self.dofs_per_node) self.T_components = [[1]]*self.nodes_per_el self.n = n self.c_p = None self.rho = None # preallocate the arrays self.K_Fz = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_Ft = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_F = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.K_1 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dz*dz self.K_2 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta*dz self.K_3 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dz self.K_4 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta*dtheta self.K_5 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # dtheta self.K_6 = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') # - self.M = np.zeros([self.no_of_dofs, self.no_of_dofs], dtype='complex') self.Hf0 = None self.PML_start = PML_params[0] self.PML_thk = PML_params[1] self.gamma = PML_params[2] self.PML_function = PML_function def add_properties(self, list_of_props): """Assign mechanical properties. Parameters: list_of_props : [bulk modulus, density] """ # assign properties self.c_p = (list_of_props[0]/list_of_props[1])**0.5 self.rho = list_of_props[1] def calculate_matrices(self): """Calculates the shape function and b matrices including Jacobian*Gauss Weight* det(Jacobian) at all Gauss quadrature points""" # get the nodal locations weights and shape functions for a given GLL quadrature ksis, weights, NN, NN_r, JJ = \ shape_fun.line_spectral_GLL_lagrange(self.nodes_at) # extract the matrices and sum at each integration point for i in range(len(ksis)): # shape funcion values at current location are NN[:, i] # generate the shape function matrix in standard form N = NN[:, i].reshape(1, -1) N_r = NN_r[:, i].reshape(1, -1) # local r in physical coordinates r_i = self.nodes_at.dot(NN[:, i]) # calculate the stretched r according to the chosen PML profile if self.PML_function is gamma_PML: r_tilde = -(self.gamma - 1)*(self.PML_start - r_i)**3/self.PML_thk**2 + r_i elif self.PML_function is gamma_PML_exp: local_r = (r_i - self.PML_start)/self.PML_thk r_tilde = self.PML_start + self.PML_thk/self.gamma.real*( np.exp(self.gamma.real*local_r) - 1) - \ 1j*self.PML_thk/self.gamma.imag*( np.exp(self.gamma.imag*local_r) - 1) + 1j*local_r*self.PML_thk else: print('Error. No such PML function defined') # calculate the value of the PML profile at the current location current_gamma = self.PML_function(r_i, self.gamma, \ self.PML_start, self.PML_thk) K_1 = 1/current_gamma**2*N_r.T.dot(N_r) K_5 = 1/r_tilde**2*N.T.dot(N) K_6 = N.T.dot(N) M = N.T.dot(N)/self.c_p**2 # GLL integration self.K_6 += -self.rho*2*np.pi*weights[i]*K_6*JJ[i]*r_tilde*current_gamma self.K_1 += -self.rho*2*np.pi*weights[i]*K_1*JJ[i]*r_tilde*current_gamma self.K_5 += -self.rho*2*np.pi*weights[i]*K_5*JJ[i]*r_tilde*current_gamma self.K_Fz += -self.rho*2*np.pi*weights[i]*K_6*JJ[i]*r_tilde*current_gamma self.K_Ft += -self.rho*2*np.pi*weights[i]*K_5*JJ[i]*r_tilde*current_gamma self.M += -self.rho*2*np.pi*weights[i]*M*JJ[i]*r_tilde*current_gamma # if the element is coupled to solid elements - create the ingredients # of the coupling matrices N_phi = NN[:, 0].reshape(-1, 1) self.Hf0 = self.rho*N_phi

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7

5fc2bf4beb1a7c9a9aabde70d8cec59e39de63d8

85

py

Python

proxypay/references/__init__.py

AgeuMatheus/django-proxypay

90736875e434013abe3ea1be5f9ff3100c9005db

[ "MIT" ]

12

2020-05-06T17:07:26.000Z

2020-10-19T15:41:56.000Z

proxypay/references/__init__.py

txiocoder/django-proxypay

90736875e434013abe3ea1be5f9ff3100c9005db

[ "MIT" ]

1

2020-05-22T14:24:29.000Z

2020-06-07T10:38:10.000Z

proxypay/references/__init__.py

txiocoder/django-proxypay

90736875e434013abe3ea1be5f9ff3100c9005db

[ "MIT" ]

null

from proxypay.references.create import create from proxypay.references.get import get

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7

399c2e0f44bdf00501d9eb64e3613018f618b64b

1,207

py

Python

src/test/test_sample.py

andrew-oxenburgh/python-bowling

9f8ee6aa885a23c6d91f67a65b754defef5c86a4

[ "MIT" ]

null

src/test/test_sample.py

andrew-oxenburgh/python-bowling

9f8ee6aa885a23c6d91f67a65b754defef5c86a4

[ "MIT" ]

null

src/test/test_sample.py

andrew-oxenburgh/python-bowling

9f8ee6aa885a23c6d91f67a65b754defef5c86a4

[ "MIT" ]

null

from src import bottles_of_beer RES_0_BOTTLE = ''' no more bottles of beer on the wall, no more bottles of beer. go to the store and buy some more, 0 bottles of beer on the wall. ''' def test_0_bottle(): actual = bottles_of_beer.how_many_bottles(0) expected = RES_0_BOTTLE assert actual == expected RES_1_BOTTLE = ''' 1 more bottle beer on the wall, 1 more bottle of beer. drink it down pass it around, 1 more bottle of beer no more bottles of beer on the wall, no more bottles of beer. go to the store and buy some more, 1 bottles of beer on the wall. ''' def test_1_bottle(): actual = bottles_of_beer.how_many_bottles(1) expected = RES_1_BOTTLE assert actual == expected RES_2_BOTTLES = ''' 2 more bottles of beer on the wall, 2 more bottles of beer. drink it down pass it around, 2 more bottles of beer 1 more bottle beer on the wall, 1 more bottle of beer. drink it down pass it around, 1 more bottle of beer no more bottles of beer on the wall, no more bottles of beer. go to the store and buy some more, 2 bottles of beer on the wall. ''' def test_2_bottle(): actual = bottles_of_beer.how_many_bottles(2) expected = RES_2_BOTTLES assert actual == expected

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7

39b44c165af377c6704b1b11480222b4943c7937

7,430

py

Python

tests/argguard_test.py

gcascio/yaml-attributes

43478cf8f49d5f4c22d9ae229dc3ec8fc9a360d7

[ "MIT" ]

null

tests/argguard_test.py

gcascio/yaml-attributes

43478cf8f49d5f4c22d9ae229dc3ec8fc9a360d7

[ "MIT" ]

2

2021-09-29T22:48:43.000Z

2021-09-29T22:54:41.000Z

tests/argguard_test.py

gcascio/yaml-attributes

43478cf8f49d5f4c22d9ae229dc3ec8fc9a360d7

[ "MIT" ]

null

from typing import Optional import pytest from yamlattributes import YamlAttributes def test_config_loads_successfully_in_sync_mode(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act TestConfig.init() # Assert assert ( TestConfig.test_attribute_a == 'config_test_value_a' and TestConfig.test_attribute_b == 'config_test_value_b' and TestConfig.test_attribute_c == 42 ), 'Config values are not correctly assigned to config class' def test_config_fails_with_incomplete_yaml_in_sync_mode(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/incomplete_test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act # Assert with pytest.raises( AssertionError, match=r".*\"sync\" mode.*", ): TestConfig.init() def test_config_fails_with_overloaded_yaml_in_sync_mode(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/overloaded_test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act # Assert with pytest.raises( AssertionError, match=r".*\"sync\" mode.*", ): TestConfig.init() def test_config_loads_successfully_in_soft_config_mode(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act TestConfig.init(mode='soft_config') # Assert assert ( TestConfig.test_attribute_a == 'config_test_value_a' and TestConfig.test_attribute_b == 'config_test_value_b' and TestConfig.test_attribute_c == 42 ), 'Config values are not correctly assigned to config class' def test_config_loads_successfully_overloaded_config_in_soft_config_mode(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/overloaded_test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act TestConfig.init(mode='soft_config') # Assert assert ( TestConfig.test_attribute_a == 'config_test_value_a' and TestConfig.test_attribute_b == 'config_test_value_b' and TestConfig.test_attribute_c == 42 and not hasattr(TestConfig, 'test_attribute_d') ), 'Config values are not correctly assigned to config class' def test_config_fails_with_incomplete_yaml_in_soft_config_mode(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/incomplete_test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act # Assert with pytest.raises( AssertionError, match=r".*\"soft_config\" mode.*", ): TestConfig.init(mode='soft_config') def test_config_fails_with_type_mismatch(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/test_config.yaml' # create type mismatch between config class and YAML file # by changing str to int test_attribute_a: int test_attribute_b = 'test_value_b' test_attribute_c: int # Act # Assert with pytest.raises( AssertionError, match=r".*missmatch.*\"test_attribute_a\" attribute.*", ): TestConfig.init() def test_config_loads_successfully_with_union_type(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int optional_attribute: Optional[int] # Act TestConfig.init() # Assert assert ( TestConfig.test_attribute_a == 'config_test_value_a' and TestConfig.test_attribute_b == 'config_test_value_b' and TestConfig.test_attribute_c == 42 and hasattr(TestConfig, 'optional_attribute') and not TestConfig.optional_attribute ), 'Config values are not correctly assigned to config class' def test_config_successfully_assighns_optional_values(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: Optional[int] # Act TestConfig.init() # Assert assert ( TestConfig.test_attribute_a == 'config_test_value_a' and TestConfig.test_attribute_b == 'config_test_value_b' and TestConfig.test_attribute_c == 42 ), 'Config values are not correctly assigned to config class' def test_config_successfully_converts_to_dict(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int test_config_dict = { 'yaml_file_path': './tests/test_config.yaml', 'test_attribute_a': 'config_test_value_a', 'test_attribute_b': 'config_test_value_b', 'test_attribute_c': 42, } # print(TestConfig.to_dict()) # Act TestConfig.init() # Assert assert ( test_config_dict == TestConfig.to_dict() ), 'Config class was not correctly converted to a dict' def test_config_loads_successfully_when_config_path_is_passed_to_init(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act TestConfig.init(yaml_file_path='./tests/test_config.yaml') # Assert assert ( TestConfig.test_attribute_a == 'config_test_value_a' and TestConfig.test_attribute_b == 'config_test_value_b' and TestConfig.test_attribute_c == 42 ), 'Config values are not correctly assigned to config class' def test_config_loads_successfully_when_config_section_is_passed_to_init(): YamlAttributes.__abstractmethods__ = set() # Arrange class TestConfig(YamlAttributes): yaml_file_path = './tests/test_config.yaml' test_attribute_a: str test_attribute_b = 'test_value_b' test_attribute_c: int # Act TestConfig.init(yaml_section='another_config') # Assert assert ( TestConfig.test_attribute_a == 'another_config_test_value_a' and TestConfig.test_attribute_b == 'another_config_test_value_b' and TestConfig.test_attribute_c == 7 ), 'Config values are not correctly assigned to config class'

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0

null

0

1

0

1

0

null

0

7

39b94a64c7b098faa32d96f42d7c525f54f052e8

2,096

py

Python

qa/tasks/tests/test_devstack.py

rpratap-bot/ceph

9834961a66927ae856935591f2fd51082e2ee484

[ "MIT" ]

4

2020-04-08T03:42:02.000Z

2020-10-01T20:34:48.000Z

qa/tasks/tests/test_devstack.py

rpratap-bot/ceph

9834961a66927ae856935591f2fd51082e2ee484

[ "MIT" ]

93

2020-03-26T14:29:14.000Z

2020-11-12T05:54:55.000Z

qa/tasks/tests/test_devstack.py

rpratap-bot/ceph

9834961a66927ae856935591f2fd51082e2ee484

[ "MIT" ]

23

2020-03-24T10:28:44.000Z

2020-09-24T09:42:19.000Z

from textwrap import dedent from tasks import devstack class TestDevstack(object): def test_parse_os_table(self): table_str = dedent(""" +---------------------+--------------------------------------+ | Property | Value | +---------------------+--------------------------------------+ | attachments | [] | | availability_zone | nova | | bootable | false | | created_at | 2014-02-21T17:14:47.548361 | | display_description | None | | display_name | NAME | | id | ffdbd1bb-60dc-4d95-acfe-88774c09ad3e | | metadata | {} | | size | 1 | | snapshot_id | None | | source_volid | None | | status | creating | | volume_type | None | +---------------------+--------------------------------------+ """).strip() expected = { 'Property': 'Value', 'attachments': '[]', 'availability_zone': 'nova', 'bootable': 'false', 'created_at': '2014-02-21T17:14:47.548361', 'display_description': 'None', 'display_name': 'NAME', 'id': 'ffdbd1bb-60dc-4d95-acfe-88774c09ad3e', 'metadata': '{}', 'size': '1', 'snapshot_id': 'None', 'source_volid': 'None', 'status': 'creating', 'volume_type': 'None'} vol_info = devstack.parse_os_table(table_str) assert vol_info == expected

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118

2,096

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0.037975

0.113924

0.721519

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0

1

0

1

0

null

0

7

39c180ff82a0772db8834b418bec31a2766cdb59

2,124

py

Python

AutoEncoder.py

Batman9698/AutoEncoder

96e5a3f805ed9884227ef14739dd626900ec24a6

[ "MIT" ]

null

AutoEncoder.py

Batman9698/AutoEncoder

96e5a3f805ed9884227ef14739dd626900ec24a6

[ "MIT" ]

null

AutoEncoder.py

Batman9698/AutoEncoder

96e5a3f805ed9884227ef14739dd626900ec24a6

[ "MIT" ]

null

import torch.nn as nn #AE_v4 class AutoEncoder_v4(nn.Module): def __init__(self, encoding_dim): super(AutoEncoder_v4, self).__init__() self.encoder = nn.Sequential(nn.Linear(784, encoding_dim), nn.Tanh()) self.decoder = nn.Sequential(nn.Linear(encoding_dim, 784), nn.Sigmoid()) def forward(self, x): x = self.encoder(x) x = self.decoder(x) return x def encode(self, x): return self.encoder(x) def decode(self, x): return self.decoder(x) # AE_v3 class AutoEncoder_v3(nn.Module): def __init__(self, encoding_dim): super(AutoEncoder_v3, self).__init__() self.encoder = nn.Sequential(nn.Linear(784, 512), nn.ReLU(), nn.Linear(512,256), nn.ReLU(), nn.Linear(256, encoding_dim)) self.decoder = nn.Sequential(nn.Linear(encoding_dim, 256), nn.ReLU(), nn.Linear(256, 512), nn.ReLU(), nn.Linear(512, 784), nn.Sigmoid()) def forward(self, x): x = self.encoder(x) x = self.decoder(x) return x def encode(self, x): return self.encoder(x) def decode(self, x): return self.decoder(x) # AE_v2 class AutoEncoder_v2(nn.Module): def __init__(self, encoding_dim): super(AutoEncoder_v2, self).__init__() self.encoder = nn.Sequential(nn.Linear(784, encoding_dim), nn.ReLU()) self.decoder = nn.Sequential(nn.Linear(encoding_dim, 784), nn.Sigmoid()) def forward(self, x): x = self.encoder(x) x = self.decoder(x) return x def encode(self, x): return self.encoder(x) def decode(self, x): return self.decoder(x)

33.1875

66

0.479284

234

2,124

4.17094

0.136752

0.081967

0.086066

0.122951

0.893443

0.811475

0.768443

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0

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0.410546

2,124

64

67

33.1875

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null

0

1

0

1

0

8

39e32cadc9efd78ea28df489a31d74fa9ba6e8f2

37,102

py

Python

lux_ai/models.py

limash/lux-ai

c9f0ccd659e03919b0b80d84b770a9ba506b041a

[ "Apache-2.0" ]

null

lux_ai/models.py

limash/lux-ai

c9f0ccd659e03919b0b80d84b770a9ba506b041a

[ "Apache-2.0" ]

null

lux_ai/models.py

limash/lux-ai

c9f0ccd659e03919b0b80d84b770a9ba506b041a

[ "Apache-2.0" ]

null

# move all imports inside functions to use ray.remote multitasking def actor_critic_residual_six_actions(actions_shape): import tensorflow as tf import tensorflow.keras as keras class ResidualUnit(keras.layers.Layer): def __init__(self, filters, initializer, activation, **kwargs): super().__init__(**kwargs) self._filters = filters self._activation = activation self._conv = keras.layers.Conv2D(filters, 3, kernel_initializer=initializer, padding="same", use_bias=False) self._norm = keras.layers.BatchNormalization() def call(self, inputs, training=False, **kwargs): x = self._conv(inputs) x = self._norm(x, training=training) return self._activation(inputs + x) def compute_output_shape(self, batch_input_shape): batch, x, y, _ = batch_input_shape return [batch, x, y, self._filters] class ResidualModel(keras.Model): def __init__(self, actions_number, **kwargs): super().__init__(**kwargs) filters = 200 layers = 10 initializer = keras.initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='truncated_normal') initializer_random = keras.initializers.random_uniform(minval=-0.03, maxval=0.03) activation = keras.activations.relu self._conv = keras.layers.Conv2D(filters, 3, padding="same", kernel_initializer=initializer, use_bias=False) self._norm = keras.layers.BatchNormalization() self._activation = keras.layers.ReLU() self._residual_block = [ResidualUnit(filters, initializer, activation) for _ in range(layers)] # self._depthwise = keras.layers.DepthwiseConv2D(32) self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() # self._city_tiles_probs0 = keras.layers.Dense(128, activation=activation, kernel_initializer=initializer) # self._city_tiles_probs1 = keras.layers.Dense(4, activation="softmax", # kernel_initializer=initializer_random) self._workers_probs0 = keras.layers.Dense(128, activation=activation, kernel_initializer=initializer) self._workers_probs1 = keras.layers.Dense(actions_number, activation="softmax", kernel_initializer=initializer_random) # self._carts_probs0 = keras.layers.Dense(128, activation=activation, kernel_initializer=initializer) # self._carts_probs1 = keras.layers.Dense(17, activation="softmax", kernel_initializer=initializer_random) self._baseline = keras.layers.Dense(1, kernel_initializer=initializer_random, activation=keras.activations.tanh) def call(self, inputs, training=False, mask=None): features = inputs x = features x = self._conv(x) x = self._norm(x, training=training) x = self._activation(x) for layer in self._residual_block: x = layer(x, training=training) shape_x = tf.shape(x) y = tf.reshape(x, (shape_x[0], -1, shape_x[-1])) y = tf.reduce_mean(y, axis=1) z1 = (x * features[:, :, :, :1]) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([z1, z2], axis=1) # t = self._city_tiles_probs0(z) # t = self._city_tiles_probs1(t) w = self._workers_probs0(z) w = self._workers_probs1(w) # c = self._carts_probs0(z) # c = self._carts_probs1(c) # probs = tf.concat([t, w, c], axis=1) # probs = probs * actions_mask probs = w baseline = self._baseline(tf.concat([y, z], axis=1)) return probs, baseline def get_config(self): pass model = ResidualModel(actions_shape) return model def actor_critic_sep_residual_six_actions(actions_shape): import tensorflow as tf import tensorflow.keras as keras class ResidualUnit(keras.layers.Layer): def __init__(self, filters, initializer, activation, **kwargs): super().__init__(**kwargs) self._filters = filters self._activation = activation self._conv = keras.layers.Conv2D(filters, 3, kernel_initializer=initializer, padding="same", use_bias=False) self._norm = keras.layers.BatchNormalization() def call(self, inputs, training=False, **kwargs): x = self._conv(inputs) x = self._norm(x, training=training) return self._activation(inputs + x) def compute_output_shape(self, batch_input_shape): batch, x, y, _ = batch_input_shape return [batch, x, y, self._filters] class CriticBranch(keras.layers.Layer): def __init__(self, filters, initializer, activation, layers, **kwargs): super().__init__(**kwargs) self._residual_block = [ResidualUnit(filters, initializer, activation) for _ in range(layers)] self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._fc_128 = keras.layers.Dense(128, activation=activation, kernel_initializer=initializer) def call(self, inputs, training=False, **kwargs): x, center = inputs for layer in self._residual_block: x = layer(x, training=training) shape_x = tf.shape(x) y = tf.reshape(x, (shape_x[0], -1, shape_x[-1])) y = tf.reduce_mean(y, axis=1) z1 = (x * center) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([y, z1, z2], axis=1) z = self._fc_128(z) return z class ActorBranch(keras.layers.Layer): def __init__(self, filters, initializer, activation, layers, **kwargs): super().__init__(**kwargs) self._residual_block = [ResidualUnit(filters, initializer, activation) for _ in range(layers)] self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._fc_128 = keras.layers.Dense(128, activation=activation, kernel_initializer=initializer) def call(self, inputs, training=False, **kwargs): x, center = inputs for layer in self._residual_block: x = layer(x, training=training) z1 = (x * center) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([z1, z2], axis=1) z = self._fc_128(z) return z class ResidualModel(keras.Model): def __init__(self, actions_number, **kwargs): super().__init__(**kwargs) initializer = keras.initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='truncated_normal') initializer_random = keras.initializers.random_uniform(minval=-0.03, maxval=0.03) activation = keras.activations.relu self._root = keras.layers.Conv2D(200, 3, padding="same", kernel_initializer=initializer, use_bias=False) self._root_norm = keras.layers.BatchNormalization() self._root_activation = keras.layers.ReLU() # actor actor_filters = 200 actor_layers = 10 self._actor_branch = ActorBranch(actor_filters, initializer, activation, actor_layers) self._action_type = keras.layers.Dense(actions_number, activation="softmax", kernel_initializer=initializer_random) # critic critic_filters = 200 critic_layers = 10 self._critic_branch = CriticBranch(critic_filters, initializer, activation, critic_layers) self._baseline = keras.layers.Dense(1, kernel_initializer=initializer_random, activation=keras.activations.tanh) def call(self, inputs, training=False, mask=None): features = inputs x = features x = self._root(x) x = self._root_norm(x, training=training) x = self._root_activation(x) center = features[:, :, :, :1] z = (x, center) w1 = self._actor_branch(z, training=training) action_probs = self._action_type(w1) w2 = self._critic_branch(z, training=training) baseline = self._baseline(w2) return action_probs, baseline def get_config(self): pass model = ResidualModel(actions_shape) return model def actor_critic_residual_with_transfer(): import tensorflow as tf import tensorflow.keras as keras class ResidualUnit(keras.layers.Layer): def __init__(self, filters, initializer, activation, **kwargs): super().__init__(**kwargs) self._filters = filters self._activation = activation self._conv = keras.layers.Conv2D(filters, 3, kernel_initializer=initializer, padding="same", use_bias=False) self._norm = keras.layers.BatchNormalization() def call(self, inputs, training=False, **kwargs): x = self._conv(inputs) x = self._norm(x, training=training) return self._activation(inputs + x) def compute_output_shape(self, batch_input_shape): batch, x, y, _ = batch_input_shape return [batch, x, y, self._filters] class ActorBranch(keras.layers.Layer): def __init__(self, filters, initializer, activation, layers, **kwargs): super().__init__(**kwargs) self._residual_block = [ResidualUnit(filters, initializer, activation) for _ in range(layers)] self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._fc_200 = keras.layers.Dense(200, activation=activation, kernel_initializer=initializer) def call(self, inputs, training=False, **kwargs): x, center = inputs for layer in self._residual_block: x = layer(x, training=training) z1 = (x * center) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([z1, z2], axis=1) z = self._fc_200(z) return z class ResidualModel(keras.Model): def __init__(self, **kwargs): super().__init__(**kwargs) filters = 200 stem_layers = 10 branch_layers = 1 initializer = keras.initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='truncated_normal') initializer_random = keras.initializers.random_uniform(minval=-0.03, maxval=0.03) activation = keras.activations.relu self._root = keras.layers.Conv2D(filters, 3, padding="same", kernel_initializer=initializer, use_bias=False) self._root_norm = keras.layers.BatchNormalization() self._root_activation = keras.layers.ReLU() self._stem = [ResidualUnit(filters, initializer, activation) for _ in range(stem_layers)] # action type: north, east, south, west, idle, build, transfer self._action_type_branch = ActorBranch(filters, initializer, activation, branch_layers) self._action_type = keras.layers.Dense(7, activation="softmax", kernel_initializer=initializer_random) # transfer direction: north, east, south, west self._transfer_direction_branch = ActorBranch(filters, initializer, activation, branch_layers) self._transfer_direction = keras.layers.Dense(4, activation="softmax", kernel_initializer=initializer_random) # resource to transfer: wood, coal, uranium self._transfer_resource_branch = ActorBranch(filters, initializer, activation, branch_layers) self._transfer_resource = keras.layers.Dense(3, activation="softmax", kernel_initializer=initializer_random) self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._baseline = keras.layers.Dense(1, kernel_initializer=initializer_random, activation=keras.activations.tanh) def call(self, inputs, training=False, mask=None): features = inputs x = features x = self._root(x) x = self._root_norm(x, training=training) x = self._root_activation(x) for layer in self._stem: x = layer(x, training=training) center = features[:, :, :, :1] z = (x, center) w1 = self._action_type_branch(z, training=training) action_type_probs = self._action_type(w1) w3 = self._transfer_direction_branch(z, training=training) transfer_direction_probs = self._transfer_direction(w3) w4 = self._transfer_resource_branch(z, training=training) transfer_resource_probs = self._transfer_resource(w4) shape_x = tf.shape(x) y = tf.reshape(x, (shape_x[0], -1, shape_x[-1])) y = tf.reduce_mean(y, axis=1) o1 = (x * center) shape_o1 = tf.shape(o1) o1 = tf.reshape(o1, (shape_o1[0], -1, shape_o1[-1])) o1 = tf.reduce_sum(o1, axis=1) o2 = self._depthwise(x) o2 = self._flatten(o2) o = tf.concat([o1, o2], axis=1) baseline = self._baseline(tf.concat([y, o], axis=1)) return action_type_probs, transfer_direction_probs, transfer_resource_probs, baseline def get_config(self): pass model = ResidualModel() return model def actor_critic_residual_shrub(): import tensorflow as tf import tensorflow.keras as keras class ResidualUnit(keras.layers.Layer): def __init__(self, filters, initializer, activation, **kwargs): super().__init__(**kwargs) self._filters = filters self._activation = activation self._conv = keras.layers.Conv2D(filters, 3, kernel_initializer=initializer, kernel_regularizer=keras.regularizers.l2(l2=1.e-5), padding="same", use_bias=False) self._norm = keras.layers.BatchNormalization() def call(self, inputs, training=False, **kwargs): x = self._conv(inputs) x = self._norm(x, training=training) return self._activation(inputs + x) def compute_output_shape(self, batch_input_shape): batch, x, y, _ = batch_input_shape return [batch, x, y, self._filters] class ActorBranch(keras.layers.Layer): def __init__(self, filters, initializer, activation, layers, **kwargs): super().__init__(**kwargs) self._residual_block = [ResidualUnit(filters, initializer, activation) for _ in range(layers)] self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._fc = keras.layers.Dense(filters, activation=activation, kernel_initializer=initializer) def call(self, inputs, training=False, **kwargs): x, center = inputs for layer in self._residual_block: x = layer(x, training=training) z1 = (x * center) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([z1, z2], axis=1) z = self._fc(z) return z class ResidualModel(keras.Model): def __init__(self, **kwargs): super().__init__(**kwargs) initializer = keras.initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='truncated_normal') initializer_random = keras.initializers.random_uniform(minval=-0.03, maxval=0.03) activation = keras.activations.relu # movements branch self._root1 = keras.layers.Conv2D(256, 3, padding="same", kernel_initializer=initializer, kernel_regularizer=keras.regularizers.l2(l2=1.e-5), use_bias=False) self._root_norm1 = keras.layers.BatchNormalization() self._root_activation1 = keras.layers.ReLU() # movement direction self._movement_direction_branch = ActorBranch(256, initializer, activation, layers=11) self._movement_direction = keras.layers.Dense(4, activation="softmax", kernel_initializer=initializer_random) # move idle bcity self._root2 = keras.layers.Conv2D(128, 3, padding="same", kernel_initializer=initializer, kernel_regularizer=keras.regularizers.l2(l2=1.e-5), use_bias=False) self._root_norm2 = keras.layers.BatchNormalization() self._root_activation2 = keras.layers.ReLU() self._move_build_idle_branch = ActorBranch(128, initializer, activation, layers=11) self._mbi = keras.layers.Dense(3, activation="softmax", kernel_initializer=initializer_random) def call(self, inputs, training=False, mask=None): x1 = inputs center = inputs[:, :, :, :1] x1 = self._root1(x1) x1 = self._root_norm1(x1, training=training) x1 = self._root_activation1(x1) z1 = (x1, center) w1 = self._movement_direction_branch(z1, training=training) movement_direction_probs = self._movement_direction(w1) x2 = inputs x2 = self._root2(x2) x2 = self._root_norm2(x2, training=training) x2 = self._root_activation2(x2) z2 = (x2, center) w2 = self._move_build_idle_branch(z2, training=training) mbi_probs = self._mbi(w2) return movement_direction_probs, mbi_probs def get_config(self): pass model = ResidualModel() return model def actor_critic_residual_switch_shrub(): import tensorflow as tf import tensorflow.keras as keras class ResidualUnit(keras.layers.Layer): def __init__(self, filters, initializer, activation, **kwargs): super().__init__(**kwargs) self._filters = filters self._activation = activation self._conv = keras.layers.Conv2D(filters, 3, kernel_initializer=initializer, kernel_regularizer=keras.regularizers.l2(l2=1.e-5), padding="same", use_bias=False) self._norm = keras.layers.BatchNormalization() def call(self, inputs, training=False, **kwargs): x = self._conv(inputs) x = self._norm(x, training=training) return self._activation(inputs + x) def compute_output_shape(self, batch_input_shape): batch, x, y, _ = batch_input_shape return [batch, x, y, self._filters] class ActorBranch(keras.layers.Layer): def __init__(self, filters, initializer, activation, layers, **kwargs): super().__init__(**kwargs) self._residual_block = [ResidualUnit(filters, initializer, activation) for _ in range(layers)] self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._fc = keras.layers.Dense(filters, activation=activation, kernel_initializer=initializer) def call(self, inputs, training=False, **kwargs): x, center = inputs for layer in self._residual_block: x = layer(x, training=training) z1 = (x * center) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([z1, z2], axis=1) z = self._fc(z) return z class ResidualModel(keras.Model): def __init__(self, **kwargs): super().__init__(**kwargs) filters = 200 stem_layers1 = 4 branch_layers1 = 6 stem_layers2 = 6 branch_layers2 = 4 initializer = keras.initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='truncated_normal') initializer_random = keras.initializers.random_uniform(minval=-0.03, maxval=0.03) activation = keras.activations.relu self._root = keras.layers.Conv2D(filters, 3, padding="same", kernel_initializer=initializer, kernel_regularizer=keras.regularizers.l2(l2=1.e-5), use_bias=False) self._root_norm = keras.layers.BatchNormalization() self._root_activation = keras.layers.ReLU() # stem1 self._stem1 = [ResidualUnit(filters, initializer, activation) for _ in range(stem_layers1)] # movement directions self._north_branch = ActorBranch(filters, initializer, activation, branch_layers1) self._north = keras.layers.Dense(2, activation="softmax", kernel_initializer=initializer_random) self._east_branch = ActorBranch(filters, initializer, activation, branch_layers1) self._east = keras.layers.Dense(2, activation="softmax", kernel_initializer=initializer_random) self._south_branch = ActorBranch(filters, initializer, activation, branch_layers1) self._south = keras.layers.Dense(2, activation="softmax", kernel_initializer=initializer_random) self._west_branch = ActorBranch(filters, initializer, activation, branch_layers1) self._west = keras.layers.Dense(2, activation="softmax", kernel_initializer=initializer_random) # build self._build_branch = ActorBranch(filters, initializer, activation, branch_layers1) self._build = keras.layers.Dense(2, activation="softmax", kernel_initializer=initializer_random) # idle self._idle_branch = ActorBranch(filters, initializer, activation, branch_layers1) self._idle = keras.layers.Dense(2, activation="softmax", kernel_initializer=initializer_random) # stem2 self._stem2 = [ResidualUnit(filters, initializer, activation) for _ in range(stem_layers2)] # transfer self._transfer_branch = ActorBranch(filters, initializer, activation, branch_layers2) self._transfer = keras.layers.Dense(2, activation="softmax", kernel_initializer=initializer_random) # transfer direction self._transfer_direction_branch = ActorBranch(filters, initializer, activation, branch_layers2) self._transfer_direction = keras.layers.Dense(4, activation="softmax", kernel_initializer=initializer_random) # resource to transfer self._transfer_resource_branch = ActorBranch(filters, initializer, activation, branch_layers2) self._transfer_resource = keras.layers.Dense(3, activation="softmax", kernel_initializer=initializer_random) def call(self, inputs, training=False, mask=None): features = inputs x = features center = features[:, :, :, :1] x = self._root(x) x = self._root_norm(x, training=training) x = self._root_activation(x) x1 = x for layer in self._stem1: x1 = layer(x1, training=training) z1 = (x1, center) wn = self._north_branch(z1, training=training) north_switch = self._north(wn) we = self._east_branch(z1, training=training) east_switch = self._east(we) ws = self._south_branch(z1, training=training) south_switch = self._south(ws) ww = self._west_branch(z1, training=training) west_switch = self._west(ww) wb = self._build_branch(z1, training=training) build_switch = self._build(wb) wi = self._idle_branch(z1, training=training) idle_switch = self._idle(wi) x2 = x for layer in self._stem2: x2 = layer(x2, training=training) z2 = (x2, center) wt = self._transfer_branch(z2, training=training) transfer_switch = self._transfer(wt) w_td = self._transfer_direction_branch(z2, training=training) transfer_direction_probs = self._transfer_direction(w_td) w_tr = self._transfer_resource_branch(z2, training=training) transfer_resource_probs = self._transfer_resource(w_tr) return north_switch, east_switch, south_switch, west_switch, build_switch, idle_switch, \ transfer_switch, transfer_direction_probs, transfer_resource_probs def get_config(self): pass model = ResidualModel() return model def actor_critic_efficient_six_actions(actions_shape): import copy import itertools import tensorflow as tf import tensorflow.keras as keras # import lux_ai.effnetv2_model as eff_model import lux_ai.hparams as hparams import lux_ai.effnetv2_configs as effnetv2_configs import lux_ai.utils as utils from lux_ai.effnetv2_model import round_filters, round_repeats, Stem, MBConvBlock, FusedMBConvBlock class EfficientModel(keras.Model): def __init__(self, actions_n, **kwargs): model_name = 'efficientnetv2-s' super().__init__(name=model_name, **kwargs) cfg = copy.deepcopy(hparams.base_config) if model_name: cfg.override(effnetv2_configs.get_model_config(model_name)) self.cfg = cfg self._mconfig = cfg.model self._stem = Stem(self._mconfig, self._mconfig.blocks_args[0].input_filters) self._blocks = [] block_id = itertools.count(0) block_name = lambda: 'blocks_%d' % next(block_id) for block_args in self._mconfig.blocks_args: assert block_args.num_repeat > 0 # Update block input and output filters based on depth multiplier. input_filters = round_filters(block_args.input_filters, self._mconfig) output_filters = round_filters(block_args.output_filters, self._mconfig) repeats = round_repeats(block_args.num_repeat, self._mconfig.depth_coefficient) block_args.update( dict( input_filters=input_filters, output_filters=output_filters, num_repeat=repeats)) # The first block needs to take care of stride and filter size increase. conv_block = {0: MBConvBlock, 1: FusedMBConvBlock}[block_args.conv_type] self._blocks.append( conv_block(block_args, self._mconfig, name=block_name())) if block_args.num_repeat > 1: # rest of blocks with the same block_arg # pylint: disable=protected-access block_args.input_filters = block_args.output_filters block_args.strides = 1 # pylint: enable=protected-access for _ in range(block_args.num_repeat - 1): self._blocks.append( conv_block(block_args, self._mconfig, name=block_name())) initializer = keras.initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='truncated_normal') initializer_random = keras.initializers.random_uniform(minval=-0.03, maxval=0.03) activation = utils.get_act_fn(self._mconfig.act_fn) self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._workers_probs0 = keras.layers.Dense(128, activation=activation, kernel_initializer=initializer) self._workers_probs1 = keras.layers.Dense(actions_n, activation="softmax", kernel_initializer=initializer_random) self._baseline = keras.layers.Dense(1, kernel_initializer=initializer_random, activation=keras.activations.tanh) def call(self, inputs, training=False, mask=None): outputs = self._stem(inputs, training) for idx, block in enumerate(self._blocks): survival_prob = self._mconfig.survival_prob if survival_prob: drop_rate = 1.0 - survival_prob survival_prob = 1.0 - drop_rate * float(idx) / len(self._blocks) # survival_prob = 1.0 outputs = block(outputs, training=training, survival_prob=survival_prob) x = outputs shape_x = tf.shape(x) y = tf.reshape(x, (shape_x[0], -1, shape_x[-1])) y = tf.reduce_mean(y, axis=1) z1 = (x * inputs[:, :, :, :1]) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([z1, z2], axis=1) w = self._workers_probs0(z) w = self._workers_probs1(w) probs = w baseline = self._baseline(tf.concat([y, z], axis=1)) return probs, baseline def get_config(self): pass model = EfficientModel(actions_shape) return model def actor_critic_efficient_shrub(actions_shape): import copy import itertools import tensorflow as tf import tensorflow.keras as keras # import lux_ai.effnetv2_model as eff_model import lux_ai.hparams as hparams import lux_ai.effnetv2_configs as effnetv2_configs import lux_ai.utils as utils from lux_ai.effnetv2_model import round_filters, round_repeats, Stem, MBConvBlock, FusedMBConvBlock class EfficientModel(keras.Model): def __init__(self, actions_number, **kwargs): model_name = 'efficientnetv2-s' super().__init__(name=model_name, **kwargs) cfg = copy.deepcopy(hparams.base_config) if model_name: cfg.override(effnetv2_configs.get_model_config(model_name)) self.cfg = cfg self._mconfig = cfg.model self._stem = Stem(self._mconfig, self._mconfig.blocks_args[0].input_filters) self._blocks = [] block_id = itertools.count(0) block_name = lambda: 'blocks_%d' % next(block_id) for block_args in self._mconfig.blocks_args: assert block_args.num_repeat > 0 # Update block input and output filters based on depth multiplier. input_filters = round_filters(block_args.input_filters, self._mconfig) output_filters = round_filters(block_args.output_filters, self._mconfig) repeats = round_repeats(block_args.num_repeat, self._mconfig.depth_coefficient) block_args.update( dict( input_filters=input_filters, output_filters=output_filters, num_repeat=repeats)) # The first block needs to take care of stride and filter size increase. conv_block = {0: MBConvBlock, 1: FusedMBConvBlock}[block_args.conv_type] self._blocks.append( conv_block(block_args, self._mconfig, name=block_name())) if block_args.num_repeat > 1: # rest of blocks with the same block_arg # pylint: disable=protected-access block_args.input_filters = block_args.output_filters block_args.strides = 1 # pylint: enable=protected-access for _ in range(block_args.num_repeat - 1): self._blocks.append( conv_block(block_args, self._mconfig, name=block_name())) initializer = keras.initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='truncated_normal') initializer_random = keras.initializers.random_uniform(minval=-0.03, maxval=0.03) activation = utils.get_act_fn(self._mconfig.act_fn) self._depthwise = keras.layers.DepthwiseConv2D(13) self._flatten = keras.layers.Flatten() self._workers_probs0 = keras.layers.Dense(128, activation=activation, kernel_initializer=initializer) # action type self._workers_probs1_0 = keras.layers.Dense(actions_number[0][0], activation="softmax", kernel_initializer=initializer_random) # movement direction self._workers_probs1_1 = keras.layers.Dense(actions_number[1][0], activation="softmax", kernel_initializer=initializer_random) # transfer direction self._workers_probs1_2 = keras.layers.Dense(actions_number[1][0], activation="softmax", kernel_initializer=initializer_random) # resource to transfer self._workers_probs1_3 = keras.layers.Dense(actions_number[2][0], activation="softmax", kernel_initializer=initializer_random) self._baseline = keras.layers.Dense(1, kernel_initializer=initializer_random, activation=keras.activations.tanh) def call(self, inputs, training=False, mask=None): outputs = self._stem(inputs, training) for idx, block in enumerate(self._blocks): # survival_prob = self._mconfig.survival_prob # if survival_prob: # drop_rate = 1.0 - survival_prob # survival_prob = 1.0 - drop_rate * float(idx) / len(self._blocks) survival_prob = 1.0 outputs = block(outputs, training=training, survival_prob=survival_prob) x = outputs shape_x = tf.shape(x) y = tf.reshape(x, (shape_x[0], -1, shape_x[-1])) y = tf.reduce_mean(y, axis=1) z1 = (x * inputs[:, :, :, :1]) shape_z = tf.shape(z1) z1 = tf.reshape(z1, (shape_z[0], -1, shape_z[-1])) z1 = tf.reduce_sum(z1, axis=1) z2 = self._depthwise(x) z2 = self._flatten(z2) z = tf.concat([z1, z2], axis=1) w = self._workers_probs0(z) probs0 = self._workers_probs1_0(w) probs1 = self._workers_probs1_1(w) probs2 = self._workers_probs1_2(w) probs3 = self._workers_probs1_3(w) baseline = self._baseline(tf.concat([y, z], axis=1)) return probs0, probs1, probs2, probs3, baseline def get_config(self): pass model = EfficientModel(actions_shape) # model = eff_model.get_model("efficientnetv2-s", weights=None) return model

43.907692

120

0.593849

4,043

37,102

5.186743

0.064556

0.049833

0.065427

0.045398

0.875203

0.851264

0.841869

0.835575

0.788269

0.767811

0

0.023234

0.309768

37,102

844

121

43.959716

0.795619

0.052504

0

0.766234

0

0.011253

0

0.003247

1

0.086039

false

0.011364

0.042208

0

0.202922

0

null

0

1

0

1

0

null

0

7

f2fe1e8d5a3a54c3c011686c3d2c1d97c948541d

12,002

py

Python

2018/day_15/python/day15.py

josephroquedev/advent-of-code

bb217deb7a5f5ed5c8c04cb726ddadb5b042ee4d

[ "MIT" ]

null

2018/day_15/python/day15.py

josephroquedev/advent-of-code

bb217deb7a5f5ed5c8c04cb726ddadb5b042ee4d

[ "MIT" ]

2

2021-06-02T00:41:38.000Z

2021-11-30T10:05:29.000Z

2018/day_15/python/day15.py

autoreleasefool/advent-of-code

bb217deb7a5f5ed5c8c04cb726ddadb5b042ee4d

[ "MIT" ]

null

from aoc import AOC import queue aoc = AOC(year=2018, day=15) data = aoc.load() walls = set() caverns = set() goblins = {} elves = {} beings = {} total_elves = 0 total_goblins = 0 max_width = 0 max_height = 0 for y, line in enumerate(data.lines()): line = line.strip() for x, c in enumerate(line): parsed_cell = (x, y) if c == "#": walls.add(parsed_cell) elif c == ".": caverns.add(parsed_cell) elif c == "G": gob_id = "G{}".format(total_goblins) goblins[gob_id] = {"id": gob_id, "attack": 3, "hp": 200, "x": x, "y": y} beings[parsed_cell] = gob_id total_goblins += 1 caverns.add(parsed_cell) elif c == "E": elf_id = "E{}".format(total_elves) elves[elf_id] = {"id": elf_id, "attack": 3, "hp": 200, "x": x, "y": y} beings[parsed_cell] = elf_id total_elves += 1 caverns.add(parsed_cell) if y == 0: max_width += 1 max_height += 1 def reading_order(c1, c2): if c1[1] < c2[1]: return c1 if c2[1] < c1[1]: return c2 return c1 if c1[0] < c2[0] else c2 def neighbors(n): ns = [] if n[1] > 0: pot = (n[0], n[1] - 1) if pot not in walls: ns.append(pot) if n[0] > 0: pot = (n[0] - 1, n[1]) if pot not in walls: ns.append(pot) if n[0] < max_width - 1: pot = (n[0] + 1, n[1]) if pot not in walls: ns.append(pot) if n[1] < max_height - 1: pot = (n[0], n[1] + 1) if pot not in walls: ns.append(pot) return ns def bfs(cell, targets): targets = set(targets) q = queue.PriorityQueue() dist = {cell: 0} prev = {} q.put((0, 0, 0, cell)) def build_path(cell): path = [cell] p = prev[cell] while p is not None: path.append(p) p = prev[p] if p in prev else None path.reverse() return path while not q.empty(): n = q.get()[3] for ne in neighbors(n): if ne in prev: continue if ne in caverns and ne not in beings: alt = dist[n] + 1 if ne not in dist or alt < dist[ne]: dist[ne] = alt prev[ne] = n if ne in targets: return build_path(ne)[1] q.put((alt, ne[1], ne[0], ne)) return None def remove(removed): if removed["id"][0] == "G": del goblins[removed["id"]] else: del elves[removed["id"]] del beings[(removed["x"], removed["y"])] def get_target(cell, friendly_type): enemies = [] for n in neighbors(cell): if friendly_type == "E" and n in beings and beings[n][0] == "G": enemies.append((goblins[beings[n]], n)) elif friendly_type == "G" and n in beings and beings[n][0] == "E": enemies.append((elves[beings[n]], n)) target = None for e in enemies: if target is None: target = e elif e[0]["hp"] < target[0]["hp"]: target = e else: target_order = reading_order(target[1], e[1]) if target_order != target[1]: target = e return target[0] if target else None def get_target_spaces(enemies): spaces = [] for enemy_id in enemies: enemy = enemies[enemy_id] enemy_cell = (enemy["x"], enemy["y"]) adjacent = neighbors(enemy_cell) spaces.extend(adjacent) return spaces fighting = True current_round = 0 # print_status() while fighting: order = sorted(list(beings.keys()), key=lambda x: (x[1], x[0])) for being_position in order: if being_position not in beings: continue being_id = beings[being_position] being_type = being_id[0] if (being_type == "E" and not goblins) or (being_type == "G" and not elves): fighting = False break being = elves[being_id] if being_type == "E" else goblins[being_id] # pylint: disable=unsupported-assignment-operation, unsubscriptable-object current_target = get_target(being_position, being_type) if current_target is not None: current_target["hp"] -= being["attack"] if current_target["hp"] <= 0: remove(current_target) else: open_spaces = get_target_spaces(elves if being_type == "G" else goblins) if open_spaces: next_space = bfs(being_position, open_spaces) if next_space: del beings[being_position] beings[next_space] = being_id if being_type == "E": elves[being_id]["x"] = next_space[0] elves[being_id]["y"] = next_space[1] else: goblins[being_id]["x"] = next_space[0] goblins[being_id]["y"] = next_space[1] if next_space: current_target = get_target(next_space, being_type) if current_target: current_target["hp"] -= being["attack"] if current_target["hp"] <= 0: remove(current_target) current_round += 1 survivors = elves if elves else goblins total_health = sum(survivors[s]["hp"] for s in survivors) aoc.p1((current_round - 1) * total_health) ## Part 2 def run_sim(starting_attack): walls = set() caverns = set() goblins = {} elves = {} beings = {} total_elves = 0 total_goblins = 0 max_width = 0 max_height = 0 for y, line in enumerate(data.lines()): line = line.strip() for x, c in enumerate(line): cell = (x, y) if c == "#": walls.add(cell) elif c == ".": caverns.add(cell) elif c == "G": gob_id = "G{}".format(total_goblins) goblins[gob_id] = {"id": gob_id, "attack": 3, "hp": 200, "x": x, "y": y} beings[cell] = gob_id total_goblins += 1 caverns.add(cell) elif c == "E": elf_id = "E{}".format(total_elves) elves[elf_id] = { "id": elf_id, "attack": starting_attack, "hp": 200, "x": x, "y": y, } beings[cell] = elf_id total_elves += 1 caverns.add(cell) if y == 0: max_width += 1 max_height += 1 def reading_order(c1, c2): if c1[1] < c2[1]: return c1 if c2[1] < c1[1]: return c2 return c1 if c1[0] < c2[0] else c2 def neighbors(n): ns = [] if n[1] > 0: pot = (n[0], n[1] - 1) if pot not in walls: ns.append(pot) if n[0] > 0: pot = (n[0] - 1, n[1]) if pot not in walls: ns.append(pot) if n[0] < max_width - 1: pot = (n[0] + 1, n[1]) if pot not in walls: ns.append(pot) if n[1] < max_height - 1: pot = (n[0], n[1] + 1) if pot not in walls: ns.append(pot) return ns def bfs(cell, targets): targets = set(targets) q = queue.PriorityQueue() dist = {cell: 0} prev = {} q.put((0, 0, 0, cell)) def build_path(cell): path = [cell] p = prev[cell] while p is not None: path.append(p) p = prev[p] if p in prev else None path.reverse() return path while not q.empty(): n = q.get()[3] for ne in neighbors(n): if ne in prev: continue if ne in caverns and ne not in beings: alt = dist[n] + 1 if ne not in dist or alt < dist[ne]: dist[ne] = alt prev[ne] = n if ne in targets: return build_path(ne)[1] q.put((alt, ne[1], ne[0], ne)) return None def remove(being): if being["id"][0] == "G": del goblins[being["id"]] else: del elves[being["id"]] del beings[(being["x"], being["y"])] def get_target(cell, being_type): enemies = [] for n in neighbors(cell): if being_type == "E" and n in beings and beings[n][0] == "G": enemies.append((goblins[beings[n]], n)) elif being_type == "G" and n in beings and beings[n][0] == "E": enemies.append((elves[beings[n]], n)) target = None for e in enemies: if target is None: target = e elif e[0]["hp"] < target[0]["hp"]: target = e else: target_order = reading_order(target[1], e[1]) if target_order != target[1]: target = e return target[0] if target else None def get_target_spaces(enemies): spaces = [] for enemy_id in enemies: enemy = enemies[enemy_id] enemy_cell = (enemy["x"], enemy["y"]) adjacent = neighbors(enemy_cell) spaces.extend(adjacent) return spaces fighting = True current_round = 0 while fighting: order = sorted(list(beings.keys()), key=lambda x: (x[1], x[0])) for being_position in order: if being_position not in beings: continue being_id = beings[being_position] being_type = being_id[0] if (being_type == "E" and not goblins) or (being_type == "G" and not elves): fighting = False break being = elves[being_id] if being_type == "E" else goblins[being_id] # pylint: disable=unsupported-assignment-operation, unsubscriptable-object target = get_target(being_position, being_type) if target is not None: target["hp"] -= being["attack"] if target["hp"] <= 0: if target["id"][0] == "E": return False remove(target) else: open_spaces = get_target_spaces(elves if being_type == "G" else goblins) if open_spaces: next_space = bfs(being_position, open_spaces) if next_space: del beings[being_position] beings[next_space] = being_id if being_type == "E": elves[being_id]["x"] = next_space[0] elves[being_id]["y"] = next_space[1] else: goblins[being_id]["x"] = next_space[0] goblins[being_id]["y"] = next_space[1] if next_space: target = get_target(next_space, being_type) if target: target["hp"] -= being["attack"] if target["hp"] <= 0: if target["id"][0] == "E": return False remove(target) current_round += 1 survivors = elves if elves else goblins total_health = sum(survivors[s]["hp"] for s in survivors) return True elf_died = True attack = 4 while elf_died: elf_died = not run_sim(attack) if not elf_died: aoc.p2(attack) break attack += 1

29.781638

88

0.469588

1,495

12,002

3.646823

0.086288

0.026963

0.018158

0.013206

0.917828

0.893434

0.889398

0.883162

0.820249

0

0.025637

0.411765

12,002

402

89

29.855721

0.746601

0.013914

0

0.840708

0

0.01471

0

1

0.044248

false

0

0.0059

0

0.112094

0

null

0

1

0

1

0

null

0

7

8418d9c2f67bb04f7a5ed5a79b6630a6b2a14d40

340

py

Python

solutions/drop_columns.py

SdgJlbl/ml-workshop

f9bf4c23d5d02dde16e4fdf80e728447adf71b1f

[ "MIT" ]

5

2018-03-27T13:30:48.000Z

2018-03-29T21:42:27.000Z

solutions/drop_columns.py

SdgJlbl/ml-workshop

f9bf4c23d5d02dde16e4fdf80e728447adf71b1f

[ "MIT" ]

null

solutions/drop_columns.py

SdgJlbl/ml-workshop

f9bf4c23d5d02dde16e4fdf80e728447adf71b1f

[ "MIT" ]

2

2018-03-27T13:31:26.000Z

2018-10-08T13:08:59.000Z

df_ml = df.drop(['First_pokemon', 'Second_pokemon', 'Winner', 'Name', 'Name_opponent', 'Generation', 'Generation_opponent'], axis=1) # df_ml = df.drop(columns=['First_pokemon', 'Second_pokemon', 'Winner', # 'Name', 'Name_opponent', # 'Generation', 'Generation_opponent'])

48.571429

71

0.564706

33

340

5.515152

0.393939

0.043956

0.065934

0.10989

0.824176

0

0.004

0.264706

340

6

72

56.666667

0.724

0.485294

0

0.461988

0

1

0

false

0

null

0

1

0

1

0

null

0

7

ffcc47585775975ffce42d7b1ff2e5dfac6f312a

540

py

Python

test/test_function.py

AICyberTeam/retrievalSystem

3a6b4a3f38ed179b529d3ac0cf0aad9aa6b98903

[ "MIT" ]

51

2021-11-07T03:14:12.000Z

2022-03-31T11:47:56.000Z

test/test_function.py

AICyberTeam/retrievalSystem

3a6b4a3f38ed179b529d3ac0cf0aad9aa6b98903

[ "MIT" ]

null

test/test_function.py

AICyberTeam/retrievalSystem

3a6b4a3f38ed179b529d3ac0cf0aad9aa6b98903

[ "MIT" ]

13

2021-11-07T03:14:14.000Z

2022-03-20T11:14:03.000Z

import numpy as np data = [ { "image_id": 11, "image_path": "../data/test_data/images/00013.jpg", "user_id": 1, "privilege": 1 }, { "image_id": 33, "image_path": "../data/test_data/images/00013.jpg", "user_id": 1, "privilege": 1 }, { "image_id": 32, "image_path": "../data/test_data/images/00013.jpg", "user_id": 2, "privilege": 1 } ] print(data)

22.5

63

0.412963

55

540

3.836364

0.363636

0.099526

0.184834

0.241706

0.753555

0

0.087662

0.42963

540

24

64

22.5

0.597403

0

0.363636

0

0.377079

0.18854

0

1

0

false

0

0.045455

0

0.045455

0

null

0

1

0

1

0

null

0

7

08385bf23f12ac0d08559de32f6ec5af4d0c2485

10,308

py

Python

src/genie/libs/parser/iosxe/tests/ShowClnsInterface/cli/equal/golden_output_2_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

204

2018-06-27T00:55:27.000Z

2022-03-06T21:12:18.000Z

src/genie/libs/parser/iosxe/tests/ShowClnsInterface/cli/equal/golden_output_2_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

468

2018-06-19T00:33:18.000Z

2022-03-31T23:23:35.000Z

src/genie/libs/parser/iosxe/tests/ShowClnsInterface/cli/equal/golden_output_2_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

309

2019-01-16T20:21:07.000Z

2022-03-30T12:56:41.000Z

expected_output = { "interfaces": { "GigabitEthernet1": { "line_protocol": "up", "status": "up", "clns_protocol_processing": False, }, "GigabitEthernet2": { "line_protocol": "up", "status": "up", "checksum_enabled": True, "mtu": 1497, "encapsulation": "SAP", "erpdus_enabled": True, "min_interval_msec": 10, "clns_fast_switching": True, "clns_sse_switching": False, "dec_compatibility_mode": "OFF", "next_esh_ish_in": 55, "routing_protocol": { "IS-IS": { "process_id": { "test": { "level_type": "level-1-2", "interface_number": "0x1", "local_circuit_id": "0x1", "neighbor_extended_local_circuit_id": "0x0", "level-1": { "metric": 10, "circuit_id": "R2.01", "dr_id": "R2.01", "ipv6_metric": 10, }, "priority": { "level-1": {"priority": 64}, "level-2": {"priority": 64}, }, "adjacencies": { "level-1": {"number_of_active_adjancies": 1}, "level-2": {"number_of_active_adjancies": 0}, }, "level-2": { "metric": 10, "circuit_id": "R2.01", "dr_id": "0000.0000.0000.00", "ipv6_metric": 10, }, "hello_interval": { "level-1": {"next_is_is_lan_hello_in_ms": 432}, "level-2": {"next_is_is_lan_hello_in": 4}, }, } } } }, }, "GigabitEthernet3": { "line_protocol": "up", "status": "up", "checksum_enabled": True, "mtu": 1497, "encapsulation": "SAP", "erpdus_enabled": True, "min_interval_msec": 10, "clns_fast_switching": True, "clns_sse_switching": False, "dec_compatibility_mode": "OFF", "next_esh_ish_in": 15, "routing_protocol": { "IS-IS": { "process_id": { "test": { "level_type": "level-1-2", "interface_number": "0x2", "local_circuit_id": "0x2", "neighbor_extended_local_circuit_id": "0x0", "level-1": { "metric": 10, "circuit_id": "R2.02", "dr_id": "0000.0000.0000.00", "ipv6_metric": 10, }, "priority": { "level-1": {"priority": 64}, "level-2": {"priority": 64}, }, "adjacencies": { "level-1": {"number_of_active_adjancies": 0}, "level-2": {"number_of_active_adjancies": 0}, }, "level-2": { "metric": 10, "circuit_id": "R2.02", "dr_id": "0000.0000.0000.00", "ipv6_metric": 10, }, "hello_interval": { "level-1": {"next_is_is_lan_hello_in": 5}, "level-2": {"next_is_is_lan_hello_in": 6}, }, } } } }, }, "GigabitEthernet4": { "line_protocol": "up", "status": "up", "checksum_enabled": True, "mtu": 1497, "encapsulation": "SAP", "erpdus_enabled": True, "min_interval_msec": 10, "clns_fast_switching": True, "clns_sse_switching": False, "dec_compatibility_mode": "OFF", "next_esh_ish_in": 32, "routing_protocol": { "IS-IS": { "process_id": { "VRF1": { "level_type": "level-1-2", "interface_number": "0x1", "local_circuit_id": "0x1", "neighbor_extended_local_circuit_id": "0x0", "level-1": { "metric": 10, "circuit_id": "R2.01", "dr_id": "0000.0000.0000.00", "ipv6_metric": 10, }, "priority": { "level-1": {"priority": 64}, "level-2": {"priority": 64}, }, "adjacencies": { "level-1": {"number_of_active_adjancies": 0}, "level-2": {"number_of_active_adjancies": 0}, }, "level-2": { "metric": 10, "circuit_id": "R2.01", "dr_id": "0000.0000.0000.00", "ipv6_metric": 10, }, "hello_interval": { "level-1": {"next_is_is_lan_hello_in": 2}, "level-2": {"next_is_is_lan_hello_in": 7}, }, } } } }, }, "Loopback0": { "line_protocol": "up", "status": "up", "checksum_enabled": True, "mtu": 1514, "encapsulation": "LOOPBACK", "erpdus_enabled": True, "min_interval_msec": 10, "clns_fast_switching": False, "clns_sse_switching": False, "dec_compatibility_mode": "OFF", "next_esh_ish_in": 36, "routing_protocol": { "IS-IS": { "process_id": { "test": { "level_type": "level-1-2", "interface_number": "0x0", "local_circuit_id": "0x7", "neighbor_extended_local_circuit_id": "0x0", "level-1": { "metric": 10, "circuit_id": "R2.07", "ipv6_metric": 10, }, "priority": { "level-1": {"priority": 64}, "level-2": {"priority": 64}, }, "adjacencies": { "level-1": {"number_of_active_adjancies": 0}, "level-2": {"number_of_active_adjancies": 0}, }, "level-2": { "metric": 10, "circuit_id": "R2.07", "ipv6_metric": 10, }, "hello_interval": {"next_is_is_hello_in": 0}, "if_state": "Down", } } } }, }, "Loopback1": { "line_protocol": "up", "status": "up", "checksum_enabled": True, "mtu": 1514, "encapsulation": "LOOPBACK", "erpdus_enabled": True, "min_interval_msec": 10, "clns_fast_switching": False, "clns_sse_switching": False, "dec_compatibility_mode": "OFF", "next_esh_ish_in": 49, "routing_protocol": { "IS-IS": { "process_id": { "VRF1": { "level_type": "level-1-2", "interface_number": "0x0", "local_circuit_id": "0x8", "neighbor_extended_local_circuit_id": "0x0", "level-1": { "metric": 10, "circuit_id": "R2.08", "ipv6_metric": 10, }, "priority": { "level-1": {"priority": 64}, "level-2": {"priority": 64}, }, "adjacencies": { "level-1": {"number_of_active_adjancies": 0}, "level-2": {"number_of_active_adjancies": 0}, }, "level-2": { "metric": 10, "circuit_id": "R2.08", "ipv6_metric": 10, }, "hello_interval": {"next_is_is_hello_in": 0}, "if_state": "Down", } } } }, }, } }

41.732794

79

0.307916

670

10,308

4.4

0.141791

0.046811

0.04749

0.057666

0.937585

0.930122

0.905699

0.902985

0

0.072474

0.575669

10,308

246

80

41.902439

0.601509

0

0.686992

0

0.293364

0.068393

0

0.004366

0

1

0

false

0

null

0

1

0

1

0

null

0

7

f23fc4ebd66e9eeaf982e3b50daff2102106af32

5,880

py

Python

stencils/mpi125pt.py

OscarAntepara/bricklib

344ae3088fe8f40b80254e9ecd90391349a06255

[ "MIT" ]

3

2020-10-31T00:39:25.000Z

2021-03-02T14:34:17.000Z

stencils/mpi125pt.py

OscarAntepara/bricklib

344ae3088fe8f40b80254e9ecd90391349a06255

[ "MIT" ]

1

2021-09-07T14:05:26.000Z

2021-09-10T20:11:42.000Z

stencils/mpi125pt.py

OscarAntepara/bricklib

344ae3088fe8f40b80254e9ecd90391349a06255

[ "MIT" ]

3

2020-10-31T02:46:58.000Z

2022-03-03T21:44:47.000Z

from st.expr import Index, ConstRef from st.grid import Grid # Declare indices i = Index(0) j = Index(1) k = Index(2) # Declare grid input = Grid("in", 3) output = Grid("out", 3) # Symmetries of 125pt stencil imply 10 constants, permuted +/- # 0 0 0 - 1 of these a0 = ConstRef("MPI_C0") # 0 0 1 - 6 of these a1 = ConstRef("MPI_C1") # 0 0 2 - 6 of these a2 = ConstRef("MPI_C2") # 0 1 1 - 12 of these a3 = ConstRef("MPI_C3") # 0 1 2 - 24 of these a4 = ConstRef("MPI_C4") # 0 2 2 - 12 of these a5 = ConstRef("MPI_C5") # 1 1 1 - 8 of these a6 = ConstRef("MPI_C6") # 1 1 2 - 24 of these a7 = ConstRef("MPI_C7") # 1 2 2 - 24 of these a8 = ConstRef("MPI_C8") # 2 2 2 - 8 of these a9 = ConstRef("MPI_C9") # Express computation # output[i, j, k] is assumed calc = \ a0 * input(i, j, k) + \ a1 * input(i + 1, j, k) + \ a1 * input(i - 1, j, k) + \ a1 * input(i, j + 1, k) + \ a1 * input(i, j - 1, k) + \ a1 * input(i, j, k + 1) + \ a1 * input(i, j, k - 1) + \ a2 * input(i + 2, j, k) + \ a2 * input(i - 2, j, k) + \ a2 * input(i, j + 2, k) + \ a2 * input(i, j - 2, k) + \ a2 * input(i, j, k + 2) + \ a2 * input(i, j, k - 2) + \ a3 * input(i + 1, j + 1, k) + \ a3 * input(i - 1, j + 1, k) + \ a3 * input(i + 1, j - 1, k) + \ a3 * input(i - 1, j - 1, k) + \ a3 * input(i + 1, j, k + 1) + \ a3 * input(i - 1, j, k + 1) + \ a3 * input(i + 1, j, k - 1) + \ a3 * input(i - 1, j, k - 1) + \ a3 * input(i, j + 1, k + 1) + \ a3 * input(i, j - 1, k + 1) + \ a3 * input(i, j + 1, k - 1) + \ a3 * input(i, j - 1, k - 1) + \ a4 * input(i + 1, j + 2, k) + \ a4 * input(i - 1, j + 2, k) + \ a4 * input(i + 1, j - 2, k) + \ a4 * input(i - 1, j - 2, k) + \ a4 * input(i + 1, j, k + 2) + \ a4 * input(i - 1, j, k + 2) + \ a4 * input(i + 1, j, k - 2) + \ a4 * input(i - 1, j, k - 2) + \ a4 * input(i, j + 1, k + 2) + \ a4 * input(i, j - 1, k + 2) + \ a4 * input(i, j + 1, k - 2) + \ a4 * input(i, j - 1, k - 2) + \ a4 * input(i + 2, j + 1, k) + \ a4 * input(i - 2, j + 1, k) + \ a4 * input(i + 2, j - 1, k) + \ a4 * input(i - 2, j - 1, k) + \ a4 * input(i + 2, j, k + 1) + \ a4 * input(i - 2, j, k + 1) + \ a4 * input(i + 2, j, k - 1) + \ a4 * input(i - 2, j, k - 1) + \ a4 * input(i, j + 2, k + 1) + \ a4 * input(i, j - 2, k + 1) + \ a4 * input(i, j + 2, k - 1) + \ a4 * input(i, j - 2, k - 1) + \ a5 * input(i + 2, j + 2, k) + \ a5 * input(i - 2, j + 2, k) + \ a5 * input(i + 2, j - 2, k) + \ a5 * input(i - 2, j - 2, k) + \ a5 * input(i + 2, j, k + 2) + \ a5 * input(i - 2, j, k + 2) + \ a5 * input(i + 2, j, k - 2) + \ a5 * input(i - 2, j, k - 2) + \ a5 * input(i, j + 2, k + 2) + \ a5 * input(i, j - 2, k + 2) + \ a5 * input(i, j + 2, k - 2) + \ a5 * input(i, j - 2, k - 2) + \ a6 * input(i + 1, j + 1, k + 1) + \ a6 * input(i - 1, j + 1, k + 1) + \ a6 * input(i + 1, j - 1, k + 1) + \ a6 * input(i - 1, j - 1, k + 1) + \ a6 * input(i + 1, j + 1, k - 1) + \ a6 * input(i - 1, j + 1, k - 1) + \ a6 * input(i + 1, j - 1, k - 1) + \ a6 * input(i - 1, j - 1, k - 1) + \ a7 * input(i + 1, j + 1, k + 2) + \ a7 * input(i - 1, j + 1, k + 2) + \ a7 * input(i + 1, j - 1, k + 2) + \ a7 * input(i - 1, j - 1, k + 2) + \ a7 * input(i + 1, j + 1, k - 2) + \ a7 * input(i - 1, j + 1, k - 2) + \ a7 * input(i + 1, j - 1, k - 2) + \ a7 * input(i - 1, j - 1, k - 2) + \ a7 * input(i + 1, j + 2, k + 1) + \ a7 * input(i - 1, j + 2, k + 1) + \ a7 * input(i + 1, j - 2, k + 1) + \ a7 * input(i - 1, j - 2, k + 1) + \ a7 * input(i + 1, j + 2, k - 1) + \ a7 * input(i - 1, j + 2, k - 1) + \ a7 * input(i + 1, j - 2, k - 1) + \ a7 * input(i - 1, j - 2, k - 1) + \ a7 * input(i + 2, j + 1, k + 1) + \ a7 * input(i - 2, j + 1, k + 1) + \ a7 * input(i + 2, j - 1, k + 1) + \ a7 * input(i - 2, j - 1, k + 1) + \ a7 * input(i + 2, j + 1, k - 1) + \ a7 * input(i - 2, j + 1, k - 1) + \ a7 * input(i + 2, j - 1, k - 1) + \ a7 * input(i - 2, j - 1, k - 1) + \ a8 * input(i + 2, j + 2, k + 1) + \ a8 * input(i - 2, j + 2, k + 1) + \ a8 * input(i + 2, j - 2, k + 1) + \ a8 * input(i - 2, j - 2, k + 1) + \ a8 * input(i + 2, j + 2, k - 1) + \ a8 * input(i - 2, j + 2, k - 1) + \ a8 * input(i + 2, j - 2, k - 1) + \ a8 * input(i - 2, j - 2, k - 1) + \ a8 * input(i + 2, j + 1, k + 2) + \ a8 * input(i - 2, j + 1, k + 2) + \ a8 * input(i + 2, j - 1, k + 2) + \ a8 * input(i - 2, j - 1, k + 2) + \ a8 * input(i + 2, j + 1, k - 2) + \ a8 * input(i - 2, j + 1, k - 2) + \ a8 * input(i + 2, j - 1, k - 2) + \ a8 * input(i - 2, j - 1, k - 2) + \ a8 * input(i + 1, j + 2, k + 2) + \ a8 * input(i - 1, j + 2, k + 2) + \ a8 * input(i + 1, j - 2, k + 2) + \ a8 * input(i - 1, j - 2, k + 2) + \ a8 * input(i + 1, j + 2, k - 2) + \ a8 * input(i - 1, j + 2, k - 2) + \ a8 * input(i + 1, j - 2, k - 2) + \ a8 * input(i - 1, j - 2, k - 2) + \ a9 * input(i + 2, j + 2, k + 2) + \ a9 * input(i - 2, j + 2, k + 2) + \ a9 * input(i + 2, j - 2, k + 2) + \ a9 * input(i - 2, j - 2, k + 2) + \ a9 * input(i + 2, j + 2, k - 2) + \ a9 * input(i - 2, j + 2, k - 2) + \ a9 * input(i + 2, j - 2, k - 2) + \ a9 * input(i - 2, j - 2, k - 2) output(i, j, k).assign(calc) STENCIL = [output]

35.636364

62

0.351361

1,082

5,880

1.900185

0.055453

0.364786

0.170233

0.194553

0.7607

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0.737354

0.72714

0

0.148898

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5,880

164

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35.853659

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0.056293

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1

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1

0

null

0

9

4b472aed6ceda241eb38580b1a0b490f1aebb390

6,482

py

Python

urls.py

margasiewicz/FootballTeam-Bots

5b639ac33eb41fe0ebf27ab21644f3bfaf162052

[ "Unlicense" ]

null

urls.py

margasiewicz/FootballTeam-Bots

5b639ac33eb41fe0ebf27ab21644f3bfaf162052

[ "Unlicense" ]

null

urls.py

margasiewicz/FootballTeam-Bots

5b639ac33eb41fe0ebf27ab21644f3bfaf162052

[ "Unlicense" ]

null

skill_hover = { "ofensywa": '//*[@id="container"]/div/div[2]/div[1]/div[2]/div/div[2]/div[2]', "defensywa": '//*[@id="container"]/div/div[2]/div[1]/div[3]/div/div[2]/div[2]', "rozgrywanie:": '//*[@id="container"]/div/div[2]/div[1]/div[4]/div/div[2]/div[2]', "kondycja": '//*[@id="container"]/div/div[2]/div[1]/div[5]/div/div[2]/div[2]', "czytanie": '//*[@id="container"]/div/div[2]/div[1]/div[6]/div/div[2]/div[2]', "pressing": '//*[@id="container"]/div/div[2]/div[1]/div[7]/div/div[2]/div[2]', "stale_fragmenty": '//*[@id="container"]/div/div[2]/div[1]/div[8]/div/div[2]/div[2]', "skutecznosc": '//*[@id="container"]/div/div[2]/div[1]/div[9]/div/div[2]/div[2]' } skill_btns = { "ofensywa": '//*[@id="container"]/div/div[2]/div[1]/div[2]/div/div[2]/button', "defensywa": '//*[@id="container"]/div/div[2]/div[1]/div[3]/div/div[2]/button', "rozgrywanie:": '//*[@id="container"]/div/div[2]/div[1]/div[4]/div/div[2]/button', "kondycja": '//*[@id="container"]/div/div[2]/div[1]/div[5]/div/div[2]/button', "czytanie": '//*[@id="container"]/div/div[2]/div[1]/div[6]/div/div[2]/button', "pressing": '//*[@id="container"]/div/div[2]/div[1]/div[7]/div/div[2]/button', "stale_fragmenty": '//*[@id="container"]/div/div[2]/div[1]/div[8]/div/div[2]/button', "skutecznosc": '//*[@id="container"]/div/div[2]/div[1]/div[9]/div/div[2]/button', } spec_urls = { "ofensywa": "https://game.footballteam.pl/training/specialization/offensive", "defensywa": "https://game.footballteam.pl/training/specialization/defensive", "rozgrywanie": "https://game.footballteam.pl/training/specialization/playmaking", "kondycja": "https://game.footballteam.pl/training/specialization/condition", "czytanie": "https://game.footballteam.pl/training/specialization/reading", "pressing": "https://game.footballteam.pl/training/specialization/pressing", "stale_fragmenty": "https://game.footballteam.pl/training/specialization/freekicks", "skutecznosc": "https://game.footballteam.pl/training/specialization/efficacy" } spec_hover = { "jeden": '//*[@id="container"]/div/div[2]/div/div[2]/div[2]/div[2]', "dwa": '//*[@id="container"]/div/div[2]/div/div[3]/div[2]/div[2]', "trzy": '//*[@id="container"]/div/div[2]/div/div[4]/div[2]/div[2]', "cztery": '//*[@id="container"]/div/div[2]/div/div[5]/div[2]/div[2]' } spec_btns = { "jeden": '//*[@id="container"]/div/div[2]/div/div[2]/div[2]/button', "dwa": '//*[@id="container"]/div/div[2]/div/div[3]/div[2]/button', "trzy": '//*[@id="container"]/div/div[2]/div/div[4]/div[2]/button', "cztery": '//*[@id="container"]/div/div[2]/div/div[5]/div[2]/button' } other_btns = { "first_login_btn": '//*[@id="buttons"]/div/button[1]', "login_screen": '//*[@id="modal-login-tab"]/h5', "put_login": '//*[@id="login-form"]/div[1]/input', "put_pass": '//*[@id="login-form"]/div[2]/input', "login_btn": '//*[@id="btn-login"]' } work_hover = { 1:'//*[@id="container"]/div/div/div/div[1]/div[2]', 2:'//*[@id="container"]/div/div/div/div[2]/div[2]', 3:'//*[@id="container"]/div/div/div/div[3]/div[2]', 4:'//*[@id="container"]/div/div/div/div[4]/div[2]', 5:'//*[@id="container"]/div/div/div/div[5]/div[2]', 6:'//*[@id="container"]/div/div/div/div[6]/div[2]', 7:'//*[@id="container"]/div/div/div/div[7]/div[2]', 8:'//*[@id="container"]/div/div/div/div[8]/div[2]', 9:'//*[@id="container"]/div/div/div/div[9]/div[2]' } work_click={ 1:'//*[@id="container"]/div/div/div/div[1]/div[2]/div[3]/button', 2:'//*[@id="container"]/div/div/div/div[2]/div[2]/div[3]/button', 3:'//*[@id="container"]/div/div/div/div[3]/div[2]/div[3]/button', 4:'//*[@id="container"]/div/div/div/div[4]/div[2]/div[3]/button', 5:'//*[@id="container"]/div/div/div/div[5]/div[2]/div[3]/button', 6:'//*[@id="container"]/div/div/div/div[6]/div[2]/div[3]/button', 7:'//*[@id="container"]/div/div/div/div[7]/div[2]/div[3]/button', 8:'//*[@id="container"]/div/div/div/div[8]/div[2]/div[3]/button', 9:'//*[@id="container"]/div/div/div/div[9]/div[2]/div[3]/button' } work_sleep_time={ 1:30, 2:150, 3:360, 4:300, 5:1800, 6:5400, 7:600, 8:7200, 9:21600 } food_hover = { 1:'//*[@id="container"]/div/div/div[1]/div[1]/div[2]', 2:'//*[@id="container"]/div/div/div[1]/div[2]/div[2]', 3:'//*[@id="container"]/div/div/div[1]/div[3]/div[2]', 4:'//*[@id="container"]/div/div/div[1]/div[4]/div[2]', 5:'//*[@id="container"]/div/div/div[1]/div[5]/div[2]', 6:'//*[@id="container"]/div/div/div[1]/div[6]/div[2]', } food_click = { 1:'//*[@id="container"]/div/div/div[1]/div[1]/div[2]/div[3]/button', 2:'//*[@id="container"]/div/div/div[1]/div[2]/div[2]/div[3]/button', 3:'//*[@id="container"]/div/div/div[1]/div[3]/div[2]/div[3]/button', 4:'//*[@id="container"]/div/div/div[1]/div[4]/div[2]/div[3]/button', 5:'//*[@id="container"]/div/div/div[1]/div[5]/div[2]/div[3]/button', 6:'//*[@id="container"]/div/div/div[1]/div[6]/div[2]/div[3]/button', } food_sleep_time = { 1:360, 2:1800, 3:7200, 4:14400, 5:21600, 6:43200, } market_btns = { 'toggle_item_color':'//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[1]/div/div/div[2]/div/img', 'gold':'//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[1]/div/div/div[2]/div/div/div[2]/div[3]/div', 'red': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[1]/div/div/div[2]/div/div/div[2]/div[4]', 'green': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[1]/div/div/div[2]/div/div/div[2]/div[5]/div', 'blue': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[1]/div/div/div[2]/div/div/div[2]/div[6]/div', 'grey': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[1]/div/div/div[2]/div/div/div[2]/div[7]/div', 'any': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[1]/div/div/div[2]/div/div/div[2]/div[1]/div', 'min-max': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[2]/div[1]/div/div[1]/div[4]/i[2]', 'max-min': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[2]/div[1]/div/div[1]/div[4]/i[1]', 'first_item': '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[2]/div[1]/div/div[2]/div[4]/b', "buy": '//*[@id="container"]/div/div[2]/div[3]/div[2]/div/div[2]/div[1]/div/div[2]/div[5]/button', "confirm": '//*[@id="container"]/div/div[2]/div[1]/div/div/div[3]/button[2]' }

53.570248

113

0.568035

1,117

6,482

3.272158

0.080573

0.297127

0.193434

0.183311

0.827086

0.809302

0.705335

0.692476

0.685636

0

0.063368

0.089479

6,482

121

114

53.570248

0.555913

0

0.475

0.799938

0.659263

0

1

0

false

0.008333

0

null

1

0

1

0

1

null

0

10

4b5a40319a139cb5307b19ea0b42c51275d71c68

151

py

Python

digsby/src/plugins/fbchat/fbchat_gui.py

ifwe/digsby

f5fe00244744aa131e07f09348d10563f3d8fa99

[ "Python-2.0" ]

35

2015-08-15T14:32:38.000Z

2021-12-09T16:21:26.000Z

digsby/src/plugins/fbchat/fbchat_gui.py

niterain/digsby

16a62c7df1018a49eaa8151c0f8b881c7e252949

[ "Python-2.0" ]

4

2015-09-12T10:42:57.000Z

2017-02-27T04:05:51.000Z

digsby/src/plugins/fbchat/fbchat_gui.py

niterain/digsby

16a62c7df1018a49eaa8151c0f8b881c7e252949

[ "Python-2.0" ]

15

2015-07-10T23:58:07.000Z

2022-01-23T22:16:33.000Z

def construct_advanced_subpanel_im(panel, SP, MSP, MSC): return True def extract_advanced_subpanel_im(panel, info, SP, MSP, MSC): return True

25.166667

60

0.754967

23

151

4.695652

0.565217

0.296296

0.333333

0.425926

0.333333

0

0.15894

151

5

61

30.2

0.850394

0

0.5

0

1

0.5

false

0

0.5

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

8

4b67d36563903a6fffdf1be44cb597271f295cd4

8,643

py

Python

tests/vm/test_machine_actions.py

proofdock/chaos-azure

85302f8be18153862656c587988eafb5dd37ddf7

[ "Apache-2.0" ]

1

2021-04-24T20:01:54.000Z

tests/vm/test_machine_actions.py

proofdock/chaos-azure

85302f8be18153862656c587988eafb5dd37ddf7

[ "Apache-2.0" ]

23

2020-05-22T06:43:14.000Z

2021-02-25T21:02:28.000Z

tests/vm/test_machine_actions.py

proofdock/chaos-azure

85302f8be18153862656c587988eafb5dd37ddf7

[ "Apache-2.0" ]

null

from unittest.mock import ANY, MagicMock, patch from azure.mgmt.compute import ComputeManagementClient import pdchaosazure from pdchaosazure.vm.actions import (burn_io, delete, fill_disk, network_latency, restart, stop, stress_cpu) from tests.data import config_provider, machine_provider, secrets_provider MACHINE_ALPHA = { 'name': 'VirtualMachineAlpha', 'resourceGroup': 'group'} MACHINE_BETA = { 'name': 'VirtualMachineBeta', 'resourceGroup': 'group'} class AnyStringWith(str): def __eq__(self, other): return self in other @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) def test_delete_one_machine(init, fetch): client = MagicMock() init.return_value = client fetch.return_value = [MACHINE_ALPHA] configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() f = "where resourceGroup=='myresourcegroup'" delete(f, configuration, secrets) fetch.assert_called_with(f, configuration, secrets) assert client.virtual_machines.begin_delete.call_count == 1 @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) def test_delete_two_machines(init, fetch): client = MagicMock() init.return_value = client fetch.return_value = [MACHINE_ALPHA, MACHINE_BETA] configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() f = "where resourceGroup=='myresourcegroup' | sample 2" delete(f, configuration, secrets) fetch.assert_called_with(f, configuration, secrets) assert client.virtual_machines.begin_delete.call_count == 2 @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) def test_stop_one_machine(init, fetch): client = MagicMock() init.return_value = client machines = [MACHINE_ALPHA] fetch.return_value = machines configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() f = "where resourceGroup=='myresourcegroup'" stop(f, configuration, secrets) fetch.assert_called_with(f, configuration, secrets) assert client.virtual_machines.begin_power_off.call_count == 1 @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) def test_stop_two_machines(init, fetch): client = MagicMock() init.return_value = client fetch.return_value = [MACHINE_ALPHA, MACHINE_BETA] configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() f = "where resourceGroup=='myresourcegroup' | sample 2" stop(f, configuration, secrets) fetch.assert_called_with(f, configuration, secrets) assert client.virtual_machines.begin_power_off.call_count == 2 @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) def test_restart_one_machine(init, fetch): client = MagicMock() init.return_value = client fetch.return_value = [MACHINE_ALPHA] configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() f = "where resourceGroup=='myresourcegroup'" restart(f, configuration, secrets) fetch.assert_called_with(f, configuration, secrets) assert client.virtual_machines.begin_restart.call_count == 1 @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) def test_restart_two_machines(init, fetch): client = MagicMock() init.return_value = client fetch.return_value = [MACHINE_ALPHA, MACHINE_BETA] configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() f = "where resourceGroup=='myresourcegroup' | sample 2" restart(f, configuration, secrets) fetch.assert_called_with(f, configuration, secrets) assert client.virtual_machines.begin_restart.call_count == 2 @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) @patch.object(pdchaosazure.common.compute.command, 'run', autospec=True) def test_stress_cpu(mocked_command_run, mocked_init_client, fetch): # arrange mocks machine = machine_provider.default() fetch.return_value = [machine] mocked_client = MagicMock(spec=ComputeManagementClient) mocked_init_client.return_value = mocked_client configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() duration = 60 # act stress_cpu( filter="where name=='some_linux_machine'", duration=duration, configuration=configuration, secrets=secrets) # assert fetch.assert_called_with("where name=='some_linux_machine'", configuration, secrets) mocked_command_run.assert_called_with(machine['resourceGroup'], machine, parameters=ANY, client=mocked_client) @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) @patch.object(pdchaosazure.common.compute.command, 'prepare_path', autospec=True) @patch.object(pdchaosazure.common.compute.command, 'run', autospec=True) def test_fill_disk(mocked_command_run, mocked_command_prepare_path, mocked_init_client, fetch): # arrange mocks mocked_command_prepare_path.return_value = '/root/burn/hard' machine = machine_provider.default() fetch.return_value = [machine] mocked_client = MagicMock(spec=ComputeManagementClient) mocked_init_client.return_value = mocked_client configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() duration = 60 # act fill_disk(filter="where name=='some_linux_machine'", duration=duration, size=1000, path='/root/burn/hard', configuration=configuration, secrets=secrets) # assert fetch.assert_called_with("where name=='some_linux_machine'", configuration, secrets) mocked_command_run.assert_called_with(machine['resourceGroup'], machine, parameters=ANY, client=mocked_client) @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) @patch.object(pdchaosazure.common.compute.command, 'run', autospec=True) def test_network_latency(mocked_command_run, mocked_init_client, fetch): # arrange mocks machine = machine_provider.default() machines = [machine] fetch.return_value = machines mocked_client = MagicMock(spec=ComputeManagementClient) mocked_init_client.return_value = mocked_client configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() duration = 60 # act network_latency( filter="where name=='some_linux_machine'", duration=duration, delay=200, jitter=50, configuration=configuration, secrets=secrets) # assert fetch.assert_called_with("where name=='some_linux_machine'", configuration, secrets) mocked_command_run.assert_called_with(machine['resourceGroup'], machine, parameters=ANY, client=mocked_client) @patch('pdchaosazure.vm.actions.fetch_machines', autospec=True) @patch('pdchaosazure.vm.actions.client.init', autospec=True) @patch.object(pdchaosazure.common.compute.command, 'run', autospec=True) def test_burn_io(mocked_command_run, mocked_init_client, fetch): # arrange mocks machine = machine_provider.default() machines = [machine] fetch.return_value = machines configuration = config_provider.provide_default_config() secrets = secrets_provider.provide_secrets_via_service_principal() mocked_client = MagicMock(spec=ComputeManagementClient) mocked_init_client.return_value = mocked_client duration = 60 # act burn_io(filter="where name=='some_linux_machine'", duration=duration, configuration=configuration, secrets=secrets) # assert fetch.assert_called_with("where name=='some_linux_machine'", configuration, secrets) mocked_command_run.assert_called_with(machine['resourceGroup'], machine, parameters=ANY, client=mocked_client)

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null

0

1

0

1

0

null

0

7

2995c3648f7190ada0c724bc9a40968641b32f3f

207

py

Python

officialWebsite/misc/admin.py

rdotjain/officialWebsite

d5f37cf840c303ecbc47aa12bd76781bb725422d

[ "MIT" ]

1

2021-11-21T04:34:13.000Z

officialWebsite/misc/admin.py

raghavTinker/officialWebsite

bf02249894b7d26b8b3f8062f2fc75556a52ae1e

[ "MIT" ]

null

officialWebsite/misc/admin.py

raghavTinker/officialWebsite

bf02249894b7d26b8b3f8062f2fc75556a52ae1e

[ "MIT" ]

null

from django.contrib import admin from . import models admin.site.register(models.Achievement) admin.site.register(models.FAQ) admin.site.register(models.ContactRequest) admin.site.register(models.Sponsor)

23

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null

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1

0

7

29dc1d23848492ae3acbecb27666c2f7540270bc

2,245

py

Python

curation_projects/kannada_audio/dvg_jnaapaka/__main__.py

sanskrit-coders/audio_curation

363cfdab94cac0bc72096efa4649d0e075f55f51

[ "MIT" ]

null

curation_projects/kannada_audio/dvg_jnaapaka/__main__.py

sanskrit-coders/audio_curation

363cfdab94cac0bc72096efa4649d0e075f55f51

[ "MIT" ]

1

2018-10-06T20:36:13.000Z

curation_projects/kannada_audio/dvg_jnaapaka/__main__.py

sanskrit-coders/audio_curation

363cfdab94cac0bc72096efa4649d0e075f55f51

[ "MIT" ]

null

from curation_projects.kannada_audio import dvg_jnaapaka # dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಹಲವಾರು-ಸಾರ್ವಜನಿಕರು jnApaka-chitra-shAle halavAru-sArvajanikaru", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-halavaru-sArvajanikaru"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಹೃದಯಸಮ್ಪನ್ನರು dvg-jnapaka-chitra-shaale-hRdaya-sampannaru", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-hRdaya-sampannaru"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಕಲೋಪಾಸಕರು dvg-jnapaka-chitra-shaale-kalopAsakaru", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-kalopAsakaru"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಮೈಸೂರಿನ ದಿವಾನರು dvg-jnapaka-chitra-shaale-maisUrina-dIvAnaru", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-maisUrina-dIvAnaru"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಸಾಹಿತಿ-ಸಜ್ಜನ-ಸಾರ್ವಜನಿಕರು dvg-jnapaka-chitra-shaale-sAhiti-sajjana-sArvajanikaru", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-sAhiti-sajjana-sArvajanikaru"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಸಾಹಿತ್ಯೋಪಾಸಕರು dvg-jnapaka-chitra-shaale-sAhityopAsakaru", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-sAhityopAsakaru"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಸಂಕೀರ್ಣ ಸ್ಮೃತಿ ಸಮ್ಪುಟ dvg-jnapaka-chitra-shaale-sankIrNa-smRti-sampuTa", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-sankIrNa-smRti-sampuTa"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ವೈದಿಕ-ಧರ್ಮ-ಸಮ್ಪ್ರದಾಯಸ್ಥರು dvg-jnapaka-chitra-shaale-vaidika-dharma-sampradAyastharu", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "dvg-jnapaka-chitra-shaale-vaidika-dharma-sampradAyastharu"], dry_run=False) dvg_jnaapaka.upload_volume(title = "ಜ್ಞಾಪಕಚಿತ್ರಶಾಲೆ ಬ್ರಹ್ಮಪುರಿಯ ಭಿಕ್ಷುಕ dvg-gaNesh-brahmapuriya-bhixuka", repo_paths=["/home/vvasuki/kannada-audio/dvg-jnApaka/" + "brahmapuriya-bhixuka"], dry_run=False, description = "ರಾ ಗಣೇಶ R Ganesh")

140.3125

271

0.766147

491

2,245

3.651731

0.193483

0.133854

0.184049

0.854992

0.824317

0.759621

0.653653

0.617959

0.585611

0

0.045434

2,245

15

272

149.666667

0.784414

0.10735

0

0.888889

0.656172

0.524738

0.888889

0

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0

1

0

1

0

1

null

0

1

0

9

4b1b471b666a471f6af57df1472da56413021991

1,124

py

Python

tests/test_16.py

sungho-joo/leetcode2github

ce7730ef40f6051df23681dd3c0e1e657abba620

[ "MIT" ]

null

tests/test_16.py

sungho-joo/leetcode2github

ce7730ef40f6051df23681dd3c0e1e657abba620

[ "MIT" ]

null

tests/test_16.py

sungho-joo/leetcode2github

ce7730ef40f6051df23681dd3c0e1e657abba620

[ "MIT" ]

null

#!/usr/bin/env python import pytest """ Test 16. 3Sum Closest """ @pytest.fixture(scope="session") def init_variables_16(): from src.leetcode_16_3sum_closest import Solution solution = Solution() def _init_variables_16(): return solution yield _init_variables_16 class TestClass16: def test_solution_0(self, init_variables_16): assert init_variables_16().threeSumClosest([-1, 2, 1, -4], 1) == 2 def test_solution_1(self, init_variables_16): assert init_variables_16().threeSumClosest([0, 0, 0], 1) == 0 #!/usr/bin/env python import pytest """ Test 16. 3Sum Closest """ @pytest.fixture(scope="session") def init_variables_16(): from src.leetcode_16_3sum_closest import Solution solution = Solution() def _init_variables_16(): return solution yield _init_variables_16 class TestClass16: def test_solution_0(self, init_variables_16): assert init_variables_16().threeSumClosest([-1, 2, 1, -4], 1) == 2 def test_solution_1(self, init_variables_16): assert init_variables_16().threeSumClosest([0, 0, 0], 1) == 0

19.719298

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154

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4.753247

0.201299

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0.286885

0.098361

1

0

0.077093

0.192171

1,124

56

75

20.071429

0.729075

0.035587

0

1

0

0.013672

0

0.153846

1

0.307692

false

0

0.153846

0.076923

0.615385

0

null

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0

1

0

1

0

null

0

1

0

1

0

11

4b1c309c79cea422cb42796d5ed450a4c2a749c5

79

py

Python

IA/Python/1/1.1/2.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

1

2022-02-23T12:47:00.000Z

IA/Python/1/1.1/2.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

null

IA/Python/1/1.1/2.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

null

a=2 b=3 print(a==b) print(a!=b) print(a>b) print(a<b) print(a>=b) print(a<=b)

8.777778

12

0.582278

22

79

2.090909

0.227273

0.782609

0.913043

1.304348

0.913043

0

0.028571

0.113924

79

8

13

9.875

0.628571

0

1

0

false

0

0.75

1

0

null

1

0

1

0

null

0

1

0

12

d9b0ce5ee4f0d710978e4eb051209e148c2c1c89

85,318

py

Python

pandadoc_client/api/documents_api.py

PandaDoc/pandadoc-api-python-client

a707c540e788eee485cc338f29ca363acca4973e

[ "MIT" ]

27

2021-11-16T11:30:13.000Z

2022-03-17T08:56:18.000Z

pandadoc_client/api/documents_api.py

PandaDoc/pandadoc-api-python-client

a707c540e788eee485cc338f29ca363acca4973e

[ "MIT" ]

null

pandadoc_client/api/documents_api.py

PandaDoc/pandadoc-api-python-client

a707c540e788eee485cc338f29ca363acca4973e

[ "MIT" ]

2

2021-12-16T13:38:15.000Z

2022-01-09T00:38:00.000Z

""" PandaDoc Public API PandaDoc Public API documentation # noqa: E501 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from pandadoc_client.api_client import ApiClient, Endpoint as _Endpoint from pandadoc_client.model_utils import ( # noqa: F401 check_allowed_values, check_validations, date, datetime, file_type, none_type, validate_and_convert_types ) from pandadoc_client.model.document_create_link_request import DocumentCreateLinkRequest from pandadoc_client.model.document_create_link_response import DocumentCreateLinkResponse from pandadoc_client.model.document_create_request import DocumentCreateRequest from pandadoc_client.model.document_create_response import DocumentCreateResponse from pandadoc_client.model.document_details_response import DocumentDetailsResponse from pandadoc_client.model.document_list_response import DocumentListResponse from pandadoc_client.model.document_ordering_fields_enum import DocumentOrderingFieldsEnum from pandadoc_client.model.document_send_request import DocumentSendRequest from pandadoc_client.model.document_send_response import DocumentSendResponse from pandadoc_client.model.document_status_change_request import DocumentStatusChangeRequest from pandadoc_client.model.document_status_request_enum import DocumentStatusRequestEnum from pandadoc_client.model.document_status_response import DocumentStatusResponse from pandadoc_client.model.document_transfer_all_ownership_request import DocumentTransferAllOwnershipRequest from pandadoc_client.model.document_transfer_ownership_request import DocumentTransferOwnershipRequest from pandadoc_client.model.linked_object_create_request import LinkedObjectCreateRequest from pandadoc_client.model.linked_object_create_response import LinkedObjectCreateResponse from pandadoc_client.model.linked_object_list_response import LinkedObjectListResponse class DocumentsApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client self.change_document_status_endpoint = _Endpoint( settings={ 'response_type': None, 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/status', 'operation_id': 'change_document_status', 'http_method': 'PATCH', 'servers': None, }, params_map={ 'all': [ 'id', 'document_status_change_request', ], 'required': [ 'id', 'document_status_change_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'document_status_change_request': (DocumentStatusChangeRequest,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', 'document_status_change_request': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json', 'multipart/form-data' ] }, api_client=api_client ) self.create_document_endpoint = _Endpoint( settings={ 'response_type': (DocumentCreateResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents', 'operation_id': 'create_document', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'document_create_request', 'editor_ver', ], 'required': [ 'document_create_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'document_create_request': (DocumentCreateRequest,), 'editor_ver': (str,), }, 'attribute_map': { 'editor_ver': 'editor_ver', }, 'location_map': { 'document_create_request': 'body', 'editor_ver': 'query', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json', 'multipart/form-data' ] }, api_client=api_client ) self.create_document_link_endpoint = _Endpoint( settings={ 'response_type': (DocumentCreateLinkResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/session', 'operation_id': 'create_document_link', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'id', 'document_create_link_request', ], 'required': [ 'id', 'document_create_link_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'document_create_link_request': (DocumentCreateLinkRequest,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', 'document_create_link_request': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) self.create_linked_object_endpoint = _Endpoint( settings={ 'response_type': (LinkedObjectCreateResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/linked-objects', 'operation_id': 'create_linked_object', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'id', 'linked_object_create_request', ], 'required': [ 'id', 'linked_object_create_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'linked_object_create_request': (LinkedObjectCreateRequest,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', 'linked_object_create_request': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) self.delete_document_endpoint = _Endpoint( settings={ 'response_type': None, 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}', 'operation_id': 'delete_document', 'http_method': 'DELETE', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.delete_linked_object_endpoint = _Endpoint( settings={ 'response_type': None, 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/linked-objects/{linked_object_id}', 'operation_id': 'delete_linked_object', 'http_method': 'DELETE', 'servers': None, }, params_map={ 'all': [ 'id', 'linked_object_id', ], 'required': [ 'id', 'linked_object_id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'linked_object_id': (str,), }, 'attribute_map': { 'id': 'id', 'linked_object_id': 'linked_object_id', }, 'location_map': { 'id': 'path', 'linked_object_id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.details_document_endpoint = _Endpoint( settings={ 'response_type': (DocumentDetailsResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/details', 'operation_id': 'details_document', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.download_document_endpoint = _Endpoint( settings={ 'response_type': (file_type,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/download', 'operation_id': 'download_document', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'id', 'watermark_color', 'watermark_font_size', 'watermark_opacity', 'watermark_text', 'separate_files', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'watermark_color': (str,), 'watermark_font_size': (int,), 'watermark_opacity': (float,), 'watermark_text': (str,), 'separate_files': (bool,), }, 'attribute_map': { 'id': 'id', 'watermark_color': 'watermark_color', 'watermark_font_size': 'watermark_font_size', 'watermark_opacity': 'watermark_opacity', 'watermark_text': 'watermark_text', 'separate_files': 'separate_files', }, 'location_map': { 'id': 'path', 'watermark_color': 'query', 'watermark_font_size': 'query', 'watermark_opacity': 'query', 'watermark_text': 'query', 'separate_files': 'query', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/pdf', 'application/json' ], 'content_type': [], }, api_client=api_client ) self.download_protected_document_endpoint = _Endpoint( settings={ 'response_type': (file_type,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/download-protected', 'operation_id': 'download_protected_document', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'id', 'separate_files', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'separate_files': (bool,), }, 'attribute_map': { 'id': 'id', 'separate_files': 'separate_files', }, 'location_map': { 'id': 'path', 'separate_files': 'query', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/pdf', 'application/json' ], 'content_type': [], }, api_client=api_client ) self.list_documents_endpoint = _Endpoint( settings={ 'response_type': (DocumentListResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents', 'operation_id': 'list_documents', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'completed_from', 'completed_to', 'contact_id', 'count', 'created_from', 'created_to', 'deleted', 'id', 'folder_uuid', 'form_id', 'membership_id', 'metadata', 'modified_from', 'modified_to', 'order_by', 'page', 'q', 'status', 'status__ne', 'tag', 'template_id', ], 'required': [], 'nullable': [ ], 'enum': [ ], 'validation': [ 'page', ] }, root_map={ 'validations': { ('page',): { 'inclusive_minimum': 1, }, }, 'allowed_values': { }, 'openapi_types': { 'completed_from': (str,), 'completed_to': (str,), 'contact_id': (str,), 'count': (int,), 'created_from': (str,), 'created_to': (str,), 'deleted': (bool,), 'id': (str,), 'folder_uuid': (str,), 'form_id': (str,), 'membership_id': (str,), 'metadata': ([str],), 'modified_from': (str,), 'modified_to': (str,), 'order_by': (DocumentOrderingFieldsEnum,), 'page': (int,), 'q': (str,), 'status': (DocumentStatusRequestEnum,), 'status__ne': (DocumentStatusRequestEnum,), 'tag': (str,), 'template_id': (str,), }, 'attribute_map': { 'completed_from': 'completed_from', 'completed_to': 'completed_to', 'contact_id': 'contact_id', 'count': 'count', 'created_from': 'created_from', 'created_to': 'created_to', 'deleted': 'deleted', 'id': 'id', 'folder_uuid': 'folder_uuid', 'form_id': 'form_id', 'membership_id': 'membership_id', 'metadata': 'metadata', 'modified_from': 'modified_from', 'modified_to': 'modified_to', 'order_by': 'order_by', 'page': 'page', 'q': 'q', 'status': 'status', 'status__ne': 'status__ne', 'tag': 'tag', 'template_id': 'template_id', }, 'location_map': { 'completed_from': 'query', 'completed_to': 'query', 'contact_id': 'query', 'count': 'query', 'created_from': 'query', 'created_to': 'query', 'deleted': 'query', 'id': 'query', 'folder_uuid': 'query', 'form_id': 'query', 'membership_id': 'query', 'metadata': 'query', 'modified_from': 'query', 'modified_to': 'query', 'order_by': 'query', 'page': 'query', 'q': 'query', 'status': 'query', 'status__ne': 'query', 'tag': 'query', 'template_id': 'query', }, 'collection_format_map': { 'metadata': 'multi', } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.list_linked_objects_endpoint = _Endpoint( settings={ 'response_type': (LinkedObjectListResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/linked-objects', 'operation_id': 'list_linked_objects', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.send_document_endpoint = _Endpoint( settings={ 'response_type': (DocumentSendResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/send', 'operation_id': 'send_document', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'id', 'document_send_request', ], 'required': [ 'id', 'document_send_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'document_send_request': (DocumentSendRequest,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', 'document_send_request': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) self.status_document_endpoint = _Endpoint( settings={ 'response_type': (DocumentStatusResponse,), 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}', 'operation_id': 'status_document', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.transfer_all_documents_ownership_endpoint = _Endpoint( settings={ 'response_type': None, 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/ownership', 'operation_id': 'transfer_all_documents_ownership', 'http_method': 'PATCH', 'servers': None, }, params_map={ 'all': [ 'document_transfer_all_ownership_request', ], 'required': [ 'document_transfer_all_ownership_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'document_transfer_all_ownership_request': (DocumentTransferAllOwnershipRequest,), }, 'attribute_map': { }, 'location_map': { 'document_transfer_all_ownership_request': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) self.transfer_document_ownership_endpoint = _Endpoint( settings={ 'response_type': None, 'auth': [ 'apiKey', 'oauth2' ], 'endpoint_path': '/public/v1/documents/{id}/ownership', 'operation_id': 'transfer_document_ownership', 'http_method': 'PATCH', 'servers': None, }, params_map={ 'all': [ 'id', 'document_transfer_ownership_request', ], 'required': [ 'id', 'document_transfer_ownership_request', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'document_transfer_ownership_request': (DocumentTransferOwnershipRequest,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', 'document_transfer_ownership_request': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) def change_document_status( self, id, document_status_change_request, **kwargs ): """Document status change # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.change_document_status(id, document_status_change_request, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. document_status_change_request (DocumentStatusChangeRequest): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: None If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id kwargs['document_status_change_request'] = \ document_status_change_request return self.change_document_status_endpoint.call_with_http_info(**kwargs) def create_document( self, document_create_request, **kwargs ): """Create document # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_document(document_create_request, async_req=True) >>> result = thread.get() Args: document_create_request (DocumentCreateRequest): Use a PandaDoc template or an existing PDF to create a document. See the creation request examples [by template](/schemas/DocumentCreateByTemplateRequest) and [by pdf](/schemas/DocumentCreateByPdfRequest) Keyword Args: editor_ver (str): Set this parameter as `ev1` if you want to create a document from PDF with Classic Editor when both editors are enabled for the workspace.. [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: DocumentCreateResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['document_create_request'] = \ document_create_request return self.create_document_endpoint.call_with_http_info(**kwargs) def create_document_link( self, id, document_create_link_request, **kwargs ): """Create a Document Link # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_document_link(id, document_create_link_request, async_req=True) >>> result = thread.get() Args: id (str): Document ID document_create_link_request (DocumentCreateLinkRequest): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: DocumentCreateLinkResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id kwargs['document_create_link_request'] = \ document_create_link_request return self.create_document_link_endpoint.call_with_http_info(**kwargs) def create_linked_object( self, id, linked_object_create_request, **kwargs ): """Create Linked Object # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_linked_object(id, linked_object_create_request, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. linked_object_create_request (LinkedObjectCreateRequest): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: LinkedObjectCreateResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id kwargs['linked_object_create_request'] = \ linked_object_create_request return self.create_linked_object_endpoint.call_with_http_info(**kwargs) def delete_document( self, id, **kwargs ): """Delete document by id # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_document(id, async_req=True) >>> result = thread.get() Args: id (str): Document ID Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: None If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.delete_document_endpoint.call_with_http_info(**kwargs) def delete_linked_object( self, id, linked_object_id, **kwargs ): """Delete Linked Object # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_linked_object(id, linked_object_id, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. linked_object_id (str): Specify linked object ID. Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: None If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id kwargs['linked_object_id'] = \ linked_object_id return self.delete_linked_object_endpoint.call_with_http_info(**kwargs) def details_document( self, id, **kwargs ): """Document details # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.details_document(id, async_req=True) >>> result = thread.get() Args: id (str): Document ID Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: DocumentDetailsResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.details_document_endpoint.call_with_http_info(**kwargs) def download_document( self, id, **kwargs ): """Document download # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.download_document(id, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. Keyword Args: watermark_color (str): HEX code (for example `#FF5733`).. [optional] watermark_font_size (int): Font size of the watermark.. [optional] watermark_opacity (float): In range 0.0-1.0. [optional] watermark_text (str): Specify watermark text.. [optional] separate_files (bool): Set as `true` if you want to receive a zip file with all documents in separate when document transaction contains more than 1.. [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: file_type If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.download_document_endpoint.call_with_http_info(**kwargs) def download_protected_document( self, id, **kwargs ): """Download document protected # noqa: E501 Download a signed PDF of a completed document # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.download_protected_document(id, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. Keyword Args: separate_files (bool): Set as `true` if you want to receive a zip file with all documents in separate when document transaction contains more than 1.. [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: file_type If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.download_protected_document_endpoint.call_with_http_info(**kwargs) def list_documents( self, **kwargs ): """List documents # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_documents(async_req=True) >>> result = thread.get() Keyword Args: completed_from (str): Return results where the `date_completed` field (ISO 8601) is greater than or equal to this value.. [optional] completed_to (str): Return results where the `date_completed` field (ISO 8601) is less than or equal to this value.. [optional] contact_id (str): Returns results where 'contact_id' is present in document as recipient or approver. [optional] count (int): Specify how many document results to return. Default is 50 documents, maximum is 100 documents.. [optional] created_from (str): Return results where the `date_created` field (ISO 8601) is greater than or equal to this value.. [optional] created_to (str): Return results where the `date_created` field (ISO 8601) is less than this value.. [optional] deleted (bool): Returns only the deleted documents.. [optional] id (str): [optional] folder_uuid (str): The UUID of the folder where the documents are stored.. [optional] form_id (str): Specify the form used for documents creation. This parameter can't be used with template_id.. [optional] membership_id (str): Returns results where 'membership_id' is present in document as owner (should be member uuid). [optional] metadata ([str]): Specify metadata to filter by in the format of `metadata_{metadata-key}={metadata-value}` such as `metadata_opportunity_id=2181432`. The `metadata_` prefix is always required.. [optional] modified_from (str): Return results where the `date_modified` field (iso-8601) is greater than or equal to this value.. [optional] modified_to (str): Return results where the `date_modified` field (iso-8601) is less than this value.. [optional] order_by (DocumentOrderingFieldsEnum): Specify the order of documents to return. Use `value` (for example, `date_created`) for ASC and `-value` (for example, `-date_created`) for DESC.. [optional] page (int): Specify which page of the dataset to return.. [optional] q (str): Search query. Filter by document reference number (this token is stored on the template level) or name.. [optional] status (DocumentStatusRequestEnum): Specify the status of documents to return. * 0: document.draft * 1: document.sent * 2: document.completed * 3: document.uploaded * 4: document.error * 5: document.viewed * 6: document.waiting_approval * 7: document.approved * 8: document.rejected * 9: document.waiting_pay * 10: document.paid * 11: document.voided * 12: document.declined * 13: document.external_review . [optional] status__ne (DocumentStatusRequestEnum): Specify the status of documents to return (exclude). * 0: document.draft * 1: document.sent * 2: document.completed * 3: document.uploaded * 4: document.error * 5: document.viewed * 6: document.waiting_approval * 7: document.approved * 8: document.rejected * 9: document.waiting_pay * 10: document.paid * 11: document.voided * 12: document.declined * 13: document.external_review . [optional] tag (str): Search tag. Filter by document tag.. [optional] template_id (str): Specify the template used for documents creation. Parameter can't be used with form_id.. [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: DocumentListResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') return self.list_documents_endpoint.call_with_http_info(**kwargs) def list_linked_objects( self, id, **kwargs ): """List Linked Objects # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_linked_objects(id, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: LinkedObjectListResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.list_linked_objects_endpoint.call_with_http_info(**kwargs) def send_document( self, id, document_send_request, **kwargs ): """Send Document # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.send_document(id, document_send_request, async_req=True) >>> result = thread.get() Args: id (str): Document ID document_send_request (DocumentSendRequest): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: DocumentSendResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id kwargs['document_send_request'] = \ document_send_request return self.send_document_endpoint.call_with_http_info(**kwargs) def status_document( self, id, **kwargs ): """Document status # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.status_document(id, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: DocumentStatusResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.status_document_endpoint.call_with_http_info(**kwargs) def transfer_all_documents_ownership( self, document_transfer_all_ownership_request, **kwargs ): """Transfer all documents ownership # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.transfer_all_documents_ownership(document_transfer_all_ownership_request, async_req=True) >>> result = thread.get() Args: document_transfer_all_ownership_request (DocumentTransferAllOwnershipRequest): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: None If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['document_transfer_all_ownership_request'] = \ document_transfer_all_ownership_request return self.transfer_all_documents_ownership_endpoint.call_with_http_info(**kwargs) def transfer_document_ownership( self, id, document_transfer_ownership_request, **kwargs ): """Update document ownership # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.transfer_document_ownership(id, document_transfer_ownership_request, async_req=True) >>> result = thread.get() Args: id (str): Specify document ID. document_transfer_ownership_request (DocumentTransferOwnershipRequest): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _content_type (str/None): force body content-type. Default is None and content-type will be predicted by allowed content-types and body. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: None If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_spec_property_naming'] = kwargs.get( '_spec_property_naming', False ) kwargs['_content_type'] = kwargs.get( '_content_type') kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id kwargs['document_transfer_ownership_request'] = \ document_transfer_ownership_request return self.transfer_document_ownership_endpoint.call_with_http_info(**kwargs)

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Python/Tests/TestShuntingYard.py

JonathanScala/Algorithms-and-Data-Structures

6d5ffe3d21607d59dc940aafc18c335a5b628ff5

[ "MIT" ]

null

Python/Tests/TestShuntingYard.py

JonathanScala/Algorithms-and-Data-Structures

6d5ffe3d21607d59dc940aafc18c335a5b628ff5

[ "MIT" ]

null

Python/Tests/TestShuntingYard.py

JonathanScala/Algorithms-and-Data-Structures

6d5ffe3d21607d59dc940aafc18c335a5b628ff5

[ "MIT" ]

null

import unittest import sys import os class TestConvertMethod(unittest.TestCase): def test_basic_addition(self): result = PostFix.convert('x+y') self.assertEqual(result, 'xy+', "Cannot add two variables") def test_basic_subtraction(self): result = PostFix.convert('x-y') self.assertEqual(result, 'xy-', "Cannot subtract two variables") def test_basic_multiplication(self): result = PostFix.convert('x*y') self.assertEqual(result, 'xy*', "Cannot Multiply two variables") def test_basic_multiplication(self): result = PostFix.convert('x/y') self.assertEqual(result, 'xy/', "Cannot Multiply two variables") def test_division_and_subtraction(self): result = PostFix.convert('(x)/(y-z)') self.assertEqual(result, 'xyz-/', "Cannot Divide and Subtract Simultaneously") def test_division_and_Multiplication(self): result = PostFix.convert('(x)/(y*z)') self.assertEqual(result, 'xyz*/', "Cannot Divide and Multiply Simultaneously") def test_division_and_Addition(self): result = PostFix.convert('(x)/(y+z)') self.assertEqual(result, 'xyz+/', "Cannot Divide and Add Simultaneously") def test_Multiplication_and_Subtraction(self): result = PostFix.convert('x*(y-z)') self.assertEqual(result, 'xyz-*', "Cannot Multiply and Subtract Simultaneously") def test_Multiplication_and_Addition(self): result = PostFix.convert('x*(y+z)') self.assertEqual(result, 'xyz+*', "Cannot Multiply and Add Simultaneously") def test_Addition_and_Subtraction(self): result = PostFix.convert('x+(y-z)') self.assertEqual(result, 'xyz-+', "Cannot Add and Subtract Simultaneously") def test_all_operators(self): result = PostFix.convert('((q+x)*(y-z))/r') self.assertEqual(result, 'qx+yz-*r/', "Cannot Multiply and Add Simultaneously") class TestEvaluateMethod(unittest.TestCase): def test_basic_addition(self): result = PostFix.evaluate('1 2 +') self.assertEqual(result, 3.0, 'Cannot Add two Integers') def test_basic_subtraction(self): result = PostFix.evaluate('2 4 -') self.assertEqual(result, -2.0, "Cannot subtract two Integers") def test_basic_multiplication(self): result = PostFix.evaluate('3 4 *') self.assertEqual(result, 12.0, "Cannot Multiply two Integers") def test_basic_multiplication(self): result = PostFix.evaluate('4 2 /') self.assertEqual(result, 2.0, "Cannot Multiply two Integers") def test_division_and_subtraction(self): result = PostFix.evaluate('1 2 1 - /') self.assertEqual(result, 1.0, "Cannot Divide and Subtract Simultaneously") def test_division_and_Multiplication(self): result = PostFix.evaluate('2 2 2 * /') self.assertEqual(result, 0.5, "Cannot Divide and Multiply Simultaneously") def test_division_and_Addition(self): result = PostFix.evaluate('1 2 1 + /') self.assertEqual(result, float(1/3), "Cannot Divide and Add Simultaneously") def test_Multiplication_and_Subtraction(self): result = PostFix.evaluate('1 - 2 6 - *') self.assertEqual(result, 4.0, "Cannot Multiply and Subtract Simultaneously") def test_Multiplication_and_Addition(self): result = PostFix.evaluate('5 4 1 + *') self.assertEqual(result, 25.0, "Cannot Multiply and Add Simultaneously") def test_Addition_and_Subtraction(self): result = PostFix.evaluate('1 - 4 3 - +') self.assertEqual(result, 0.0, "Cannot Add and Subtract Simultaneously") def test_all_operators(self): result = PostFix.evaluate('1 2 + 4 3 - * 2 /') self.assertEqual(result, 1.5, "Cannot Compute with all Operators Simultaneously") if(__name__ == "__main__"): sys.path.append(os.path.abspath('../Algorithms')) from shuntingYard import PostFix unittest.main(exit=False)

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0.13347

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0.142857

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0

1

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null

0

1

0

7

d9fbd70edde2969b0b86a3b1cba8a3b23b031178

2,345

py

Python

NN_models/old.py

ThomasMrY/ActivationFunctionDemo

1f75c7964e354e7593e1fe54932877feb2961488

[ "MIT" ]

12

2018-10-29T02:07:43.000Z

2022-03-18T09:56:34.000Z

NN_models/old.py

ThomasMrY/Activation_function_demo

1f75c7964e354e7593e1fe54932877feb2961488

[ "MIT" ]

null

NN_models/old.py

ThomasMrY/Activation_function_demo

1f75c7964e354e7593e1fe54932877feb2961488

[ "MIT" ]

6

2019-05-31T08:54:39.000Z

2021-08-15T03:09:33.000Z

import pickle import torch import numpy as np def tanh_apx(input_d,file_name): file = open('./process_data\\'+file_name+'.pkl','rb') x_linspace = pickle.load(file) values = pickle.load(file) num = len(values) output = torch.zeros_like(input_d) temp_1 = x_linspace[-1] output_1 = torch.where(torch.lt(input_d, temp_1), torch.zeros_like(input_d), torch.ones_like(input_d)) alpha = 10 * output_1 input_d = torch.add(input_d, alpha) output = torch.add(output, output_1) temp_1 = x_linspace[0] output_1 = torch.where(torch.lt(input_d, temp_1), torch.ones_like(input_d), torch.zeros_like(input_d)) alpha = 10 * output_1 input_d = torch.add(input_d, alpha) output = torch.add(output, -1 * output_1) for t in range(1, num-1): temp_1 = x_linspace[t] temp_2 = values[t-1] output_1 = torch.where(torch.lt(input_d, temp_1), torch.ones_like(input_d), torch.zeros_like(input_d)) alpha = 10 * output_1 input_d = torch.add(input_d, alpha) output = torch.add(temp_2 * output_1, output) return output def selu_apx(input_d,file_name): def selu(x,name = "selu"): scale = 1.0507009873554804934193349852946 alpha = 1.6732632423543772848170429916717 return scale * tf.where(x > 0.0, x, alpha * tf.exp(x) - alpha) file = open('./process_data\\'+file_name+'.pkl','rb') x_linspace = pickle.load(file) values = pickle.load(file) num = len(values) output = torch.zeros_like(input_d) temp_1 = x_linspace[-1] output_1 = torch.where(torch.lt(input_d, temp_1), torch.zeros_like(input_d), input_d) output_temp = torch.where(torch.lt(input_d, temp_1), torch.zeros_like(input_d), torch.ones_like(input_d)) alpha = 10 * output_temp input_d = torch.add(input_d, alpha) output = torch.add(output, output_1) temp_1 = x_linspace[0] output_1 = torch.where(torch.lt(input_d, temp_1), torch.ones_like(input_d), torch.zeros_like(input_d)) alpha = 10 * output_1 input_d = torch.add(input_d, alpha) output = torch.add(output, -1.6733 * output_1) for t in range(1,num-1): temp_1 = x_linspace[t] temp_2 = values[t-1] output_1 = torch.where(torch.lt(input_d, temp_1), torch.ones_like(input_d), torch.zeros_like(input_d)) alpha = 10 * output_1 input_d = torch.add(input_d, alpha) output = torch.add(temp_2 * output_1, output) return output

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103

0.698934

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2,345

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0.867101

0.844951

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0.163753

2,345

62

104

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0.717491

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0

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0

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0.152542

0

null

0

1

0

1

0

null

0

7

8a055946ef49ebfa9352f08b7d3890ca5f838a46

2,653

py

Python

tests/config/test_config.py

craftslab/langcrawler

33490841411b290debc71960e0bd8e71bee653c1

[ "Apache-2.0" ]

null

tests/config/test_config.py

craftslab/langcrawler

33490841411b290debc71960e0bd8e71bee653c1

[ "Apache-2.0" ]

null

tests/config/test_config.py

craftslab/langcrawler

33490841411b290debc71960e0bd8e71bee653c1

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from langcrawler.config.config import Config, ConfigException def test_config(): config = Config() try: config.pg_host = "" except ConfigException as _: assert True else: assert False try: config.pg_host = "127.0.0.1" except ConfigException as _: assert False else: assert True try: config.pg_port = 0 except ConfigException as _: assert True else: assert False try: config.pg_port = 5432 except ConfigException as _: assert False else: assert True try: config.pg_user = "" except ConfigException as _: assert True else: assert False try: config.pg_user = "postgres" except ConfigException as _: assert False else: assert True try: config.pg_pass = "" except ConfigException as _: assert True else: assert False try: config.pg_pass = "postgres" except ConfigException as _: assert False else: assert True try: config.redis_host = "" except ConfigException as _: assert True else: assert False try: config.redis_host = "127.0.0.1" except ConfigException as _: assert False else: assert True try: config.redis_port = 0 except ConfigException as _: assert True else: assert False try: config.redis_port = 6379 except ConfigException as _: assert False else: assert True try: config.redis_pass = "" except ConfigException as _: assert True else: assert False try: config.redis_pass = "redis" except ConfigException as _: assert False else: assert True try: config.repo_count = 0 except ConfigException as _: assert True else: assert False try: config.repo_count = 1 except ConfigException as _: assert False else: assert True try: config.repo_host = [] except ConfigException as _: assert True else: assert False try: config.repo_host = ["gerrit"] except ConfigException as _: assert False else: assert True try: config.repo_lang = [] except ConfigException as _: assert True else: assert False try: config.repo_lang = ["go"] except ConfigException as _: assert False else: assert True

17.925676

61

0.555974

274

2,653

5.233577

0.124088

0.125523

0.320781

0.404463

0.883543

0.85007

0

0.015328

0.385224

2,653

147

62

18.047619

0.863887

0.007916

0

0.813008

0

0.017871

0

0.325203

1

0.00813

false

0.03252

0.00813

0

0.01626

0

null

0

1

0

1

0

null

0

9

8a0f21cf3be7bebe7ba46cbb20a7b8a97a859e51

2,422

py

Python

connapi/api/agify.py

YellowFoxH4XOR/connapi

f7663c048856f3c402cc3e2c1a22751bae703a81

[ "MIT" ]

null

connapi/api/agify.py

YellowFoxH4XOR/connapi

f7663c048856f3c402cc3e2c1a22751bae703a81

[ "MIT" ]

null

connapi/api/agify.py

YellowFoxH4XOR/connapi

f7663c048856f3c402cc3e2c1a22751bae703a81

[ "MIT" ]

null

import requests import json from connapi.data import Linker class Agify(): def get_age(datadict,country_code=None,api_key=None): size = len(datadict) if(size == 1): url = Linker.url_agify + "name=" + str(datadict[0]) else: temp_url = "" for i in range(0,size): if(i<(size-1)): temp_url += "name[]=" + str(datadict[i]) + "&" else: temp_url += "name[]=" + str(datadict[i]) url = Linker.url_agify + temp_url if(country_code is not None): url += "&country_id=" + country_code if(api_key is not None): url += "&apikey=" + api_key resp = requests.get(url) if(resp.status_code == 200): return json.loads(resp.text) else: return "Error Fetching data" def get_gender(datadict,country_code=None,api_key=None): size = len(datadict) if(size == 1): url = Linker.url_genderize + "name=" + str(datadict[0]) else: temp_url = "" for i in range(0,size): if(i<(size-1)): temp_url += "name[]=" + str(datadict[i]) + "&" else: temp_url += "name[]=" + str(datadict[i]) url = Linker.url_genderize + temp_url if(country_code is not None): url += "&country_id=" + country_code if(api_key is not None): url += "&apikey=" + api_key resp = requests.get(url) if(resp.status_code == 200): return json.loads(resp.text) else: return "Error Fetching data" def get_nationality(datadict,api_key=None): size = len(datadict) if(size == 1): url = Linker.url_nationalize + "name=" + str(datadict[0]) else: temp_url = "" for i in range(0,size): if(i<(size-1)): temp_url += "name[]=" + str(datadict[i]) + "&" else: temp_url += "name[]=" + str(datadict[i]) url = Linker.url_nationalize + temp_url if(api_key is not None): url += "&apikey=" + api_key resp = requests.get(url) if(resp.status_code == 200): return json.loads(resp.text) else: return "Error Fetching data"

34.112676

69

0.488439

285

2,422

4.007018

0.168421

0.073555

0.118214

0.073555

0.8669

0

0.013953

0.378613

2,422

70

34.6

0.744851

0

0.8

0

0.068126

0

1

0.046154

false

0

0.046154

0

0.2

0

null

0

1

0

1

0

null

0

7

8a4e0657ecd54582c7cbd42a4a8aaaa43dbf531b

69,806

py

Python

gym_novel_gridworlds/novelty_wrappers.py

dirkmcpherson/gym-novel-gridworlds

5cd04fdf65e20cee51a9a6ed8eead662aad39259

[ "MIT" ]

2

2021-08-06T08:41:34.000Z

2021-11-02T14:17:15.000Z

gym_novel_gridworlds/novelty_wrappers.py

dirkmcpherson/gym-novel-gridworlds

5cd04fdf65e20cee51a9a6ed8eead662aad39259

[ "MIT" ]

3

2020-08-24T11:19:31.000Z

2021-08-23T10:12:04.000Z

gym_novel_gridworlds/novelty_wrappers.py

dirkmcpherson/gym-novel-gridworlds

5cd04fdf65e20cee51a9a6ed8eead662aad39259

[ "MIT" ]

6

2020-07-28T12:52:44.000Z

2022-02-18T14:41:52.000Z

import copy import numpy as np import gym from gym import error, spaces, utils class AxeEasy(gym.core.Wrapper): """ Novelty wrapper to add a new item (axe) in the inventory Using axe reduces the step_cost when Break action is used With optional arg breakincrease, the agent will get 2 items in inventory after break action instead of 1 """ def __init__(self, env, axe_material, breakincrease='false'): super().__init__(env) self.axe_name = axe_material + '_axe' # wooden_axe, iron_axe self.env.items.add(self.axe_name) self.env.items_id.setdefault(self.axe_name, len(self.items_id)) self.env.inventory_items_quantity.update({self.axe_name: 1}) self.env.entities.add(self.axe_name) self.env.select_actions_id.update({'Select_' + self.axe_name: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) self.breakincrease = breakincrease def reset(self): obs = self.env.reset() self.env.inventory_items_quantity.update({self.axe_name: 1}) return obs def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Break' in self.limited_actions_id, "Cannot use breakincrease novelty_arg2 because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Break']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.env.block_in_front_str not in self.env.unbreakable_items: if self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'wooden_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 if self.breakincrease == 'true': self.env.inventory_items_quantity[self.env.block_in_front_str] += 2 else: self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.5 # 1800.0 elif self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'iron_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 if self.breakincrease == 'true': self.env.inventory_items_quantity[self.env.block_in_front_str] += 2 else: self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.25 # 900.0 else: block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class AxeMedium(gym.core.Wrapper): """ Novelty wrapper to add a new item (axe) in the map When the agent goes near axe, axe gets into the inventory Using axe reduces the step_cost when Break action is used With optional arg breakincrease, the agent will get 2 items in inventory after break action instead of 1 """ def __init__(self, env, axe_material, breakincrease='false'): super().__init__(env) self.axe_name = axe_material + '_axe' # wooden_axe, iron_axe self.env.add_new_items({self.axe_name: 1}) self.env.entities.add(self.axe_name) self.env.select_actions_id.update({'Select_' + self.axe_name: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) self.breakincrease = breakincrease def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Break' in self.limited_actions_id, "Cannot use breakincrease novelty_arg2 because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Break']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.env.block_in_front_str not in self.env.unbreakable_items: if self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'wooden_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 if self.breakincrease == 'true': self.env.inventory_items_quantity[self.env.block_in_front_str] += 2 else: self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.5 # 1800.0 elif self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'iron_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 if self.breakincrease == 'true': self.env.inventory_items_quantity[self.env.block_in_front_str] += 2 else: self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.25 # 900.0 else: block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class AxeHard(gym.core.Wrapper): """ Novelty wrapper to add a new recipe and action to craft axe The ingredients of axe are placed in the map When the agent crafts axe, it goes in the inventory Using axe reduces the step_cost to when Break action is used With optional arg breakincrease, the agent will get 2 items in inventory after break action instead of 1 """ def __init__(self, env, axe_material, breakincrease='false'): super().__init__(env) self.axe_material = axe_material self.axe_name = self.axe_material + '_axe' # wooden_axe, iron_axe self.env.items.add(self.axe_name) self.env.items_id.setdefault(self.axe_name, len(self.items_id)) self.env.inventory_items_quantity.update({self.axe_name: 0}) self.env.entities.add(self.axe_name) # Action Space if self.axe_material == 'wooden': axe_recipe = {'stick': 2, 'plank': 3} elif self.axe_material == 'iron': axe_recipe = {'stick': 2, 'iron': 3} # adding axe's ingredients to map for item in axe_recipe: if item in self.env.items: if item in self.items_quantity: item_quantity = self.items_quantity[item] self.env.items_quantity.update({item: item_quantity + axe_recipe[item]}) else: self.env.items_quantity.update({item: axe_recipe[item]}) else: self.env.add_new_items({item: axe_recipe[item]}) self.env.recipes.update({self.axe_name: {'input': axe_recipe, 'output': {self.axe_name: 1}}}) self.env.craft_actions_id.update({'Craft_' + self.axe_name: len(self.env.actions_id)}) self.env.actions_id.update({'Craft_' + self.axe_name: len(self.env.actions_id)}) self.env.select_actions_id.update({'Select_' + self.axe_name: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) self.env.action_space = spaces.Discrete(len(self.env.actions_id)) self.breakincrease = breakincrease def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Craft_' + self.axe_name in self.limited_actions_id,\ "Cannot use AxeHard novelty because you do not have " + "Craft_" + self.axe_name + " in LimitActions" assert 'Break' in self.limited_actions_id, "Cannot use breakincrease novelty_arg2 because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Craft_' + self.axe_name]: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward, result, step_cost, message = self.craft(self.axe_name) # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) elif action_id == actions_id['Break']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.env.block_in_front_str not in self.env.unbreakable_items: if self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'wooden_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 if self.breakincrease == 'true': self.env.inventory_items_quantity[self.env.block_in_front_str] += 2 else: self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.5 # 1800.0 elif self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'iron_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 if self.breakincrease == 'true': self.env.inventory_items_quantity[self.env.block_in_front_str] += 2 else: self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.25 # 900.0 else: block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info def craft(self, item_to_craft): reward = -1 # default reward to craft in a wrong way result = True step_cost = 0 # default step_cost message = '' # Check if there are enough ingredients in the inventory have_all_ingredients = {} for item in self.env.recipes[item_to_craft]['input']: if item in self.env.inventory_items_quantity and self.env.inventory_items_quantity[item] >= \ self.env.recipes[item_to_craft]['input'][item]: have_all_ingredients[item] = True else: have_all_ingredients[item] = False # If there are not enough ingredients in the inventory if False in have_all_ingredients.values(): result = False message = "Missing items: " if item_to_craft == 'tree_tap': step_cost = 360.0 elif item_to_craft == 'pogo_stick': step_cost = 480.0 for item in have_all_ingredients: if not have_all_ingredients[item]: message += str(self.env.recipes[item_to_craft]['input'][item]) + ' ' + item + ', ' return reward, result, step_cost, message[:-2] # Craft else: # If more than 1 ingredient needed, agent needs to be in front of crafting_table if len(self.env.recipes[item_to_craft]['input']) > 1: self.env.update_block_in_front() if not self.env.block_in_front_str == 'crafting_table': if item_to_craft == 'tree_tap': step_cost = 720.0 elif item_to_craft == 'pogo_stick': step_cost = 840.0 elif item_to_craft == self.axe_name: step_cost = 600.0 result = False message = 'Need to be in front of crafting_table' return reward, result, step_cost, message reward = self.reward_intermediate # default reward to craft in a good way # Reduce ingredients from the inventory for item in self.env.recipes[item_to_craft]['input']: self.env.inventory_items_quantity[item] -= self.env.recipes[item_to_craft]['input'][item] # Add item_to_craft in the inventory self.env.inventory_items_quantity[item_to_craft] += self.env.recipes[item_to_craft]['output'][item_to_craft] if item_to_craft == 'plank': step_cost = 1200.0 elif item_to_craft == 'stick': step_cost = 2400.0 elif item_to_craft == 'tree_tap': step_cost = 7200.0 elif item_to_craft == 'pogo_stick': step_cost = 8400.0 elif item_to_craft == self.axe_name: step_cost = 6000.0 message = 'Crafted ' + item_to_craft return reward, result, step_cost, message class AxetoBreakEasy(gym.core.Wrapper): """ Novelty wrapper to add a new item (axe) in the inventory and requiring axe to break items Using axe reduces the step_cost when Break action is used """ def __init__(self, env, axe_material): super().__init__(env) self.axe_name = axe_material + '_axe' # wooden_axe, iron_axe self.env.items.add(self.axe_name) self.env.items_id.setdefault(self.axe_name, len(self.items_id)) self.env.inventory_items_quantity.update({self.axe_name: 1}) self.env.entities.add(self.axe_name) self.env.select_actions_id.update({'Select_' + self.axe_name: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) def reset(self): obs = self.env.reset() self.env.inventory_items_quantity.update({self.axe_name: 1}) return obs def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Break' in self.limited_actions_id, "Cannot use axetobreak novelty because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Break']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.env.block_in_front_str not in self.env.unbreakable_items: if self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'wooden_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.5 # 1800.0 elif self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'iron_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.25 # 900.0 else: result = False message = "Cannot break without " + self.axe_name + " selected" else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class AxetoBreakMedium(gym.core.Wrapper): """ Novelty wrapper to add a new item (axe) in the map When the agent goes near axe, axe gets into the inventory Axe is required to break items Using axe reduces the step_cost when Break action is used """ def __init__(self, env, axe_material): super().__init__(env) self.axe_name = axe_material + '_axe' # wooden_axe, iron_axe self.env.add_new_items({self.axe_name: 1}) self.env.entities.add(self.axe_name) self.env.select_actions_id.update({'Select_' + self.axe_name: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Break' in self.limited_actions_id, "Cannot use axetobreak novelty because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Break']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.env.block_in_front_str not in self.env.unbreakable_items: if self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'wooden_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.5 # 1800.0 elif self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'iron_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.25 # 900.0 else: result = False message = "Cannot break without " + self.axe_name + " selected" else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class AxetoBreakHard(gym.core.Wrapper): """ Novelty wrapper to add a new recipe and action to craft axe Agent starts with ingredients to craft an axe in the inventory When the agent crafts axe, it goes in the inventory Axe is required to break items Using axe reduces the step_cost when Break action is used """ def __init__(self, env, axe_material): super().__init__(env) self.axe_material = axe_material self.axe_name = self.axe_material + '_axe' # wooden_axe, iron_axe self.env.items.add(self.axe_name) self.env.items_id.setdefault(self.axe_name, len(self.items_id)) self.env.inventory_items_quantity.update({self.axe_name: 0}) self.env.entities.add(self.axe_name) # Action Space if self.axe_material == 'wooden': axe_recipe = {'stick': 2, 'plank': 3} elif self.axe_material == 'iron': axe_recipe = {'stick': 2, 'iron': 3} for item in axe_recipe: if item not in self.env.items: self.env.items.add(item) self.env.items_id.setdefault(item, len(self.items_id)) self.env.inventory_items_quantity.update(axe_recipe) self.env.recipes.update({self.axe_name: {'input': axe_recipe, 'output': {self.axe_name: 1}}}) # self.action_craft_str.update({'Craft_' + self.axe_name: len(self.action_str)}) self.env.actions_id.update({'Craft_' + self.axe_name: len(self.env.actions_id)}) self.env.select_actions_id.update({'Select_' + self.axe_name: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) self.env.action_space = spaces.Discrete(len(self.env.actions_id)) def reset(self): obs = self.env.reset() if self.axe_material == 'wooden': self.env.inventory_items_quantity.update({'wooden_axe': 0, 'stick': 2, 'plank': 3}) elif self.axe_material == 'iron': self.env.inventory_items_quantity.update({'iron_axe': 0, 'stick': 2, 'iron': 3}) return obs def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Craft_' + self.axe_name in self.limited_actions_id,\ "Cannot use AxetoBreakHard novelty because you do not have " + "Craft_" + self.axe_name + " in LimitActions" assert 'Break' in self.limited_actions_id, "Cannot use axetobreak novelty because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Craft_' + self.axe_name]: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward, result, step_cost, message = self.craft(self.axe_name) # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) elif action_id == actions_id['Break']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.env.block_in_front_str not in self.env.unbreakable_items: if self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'wooden_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.5 # 1800.0 elif self.env.inventory_items_quantity[self.axe_name] >= 1 and self.env.selected_item == 'iron_axe': block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate step_cost = step_cost * 0.25 # 900.0 else: result = False message = "Cannot break without " + self.axe_name + " selected" else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info def craft(self, item_to_craft): reward = -1 # default reward to craft in a wrong way result = True step_cost = 0 # default step_cost message = '' # Check if there are enough ingredients in the inventory have_all_ingredients = {} for item in self.env.recipes[item_to_craft]['input']: if item in self.env.inventory_items_quantity and self.env.inventory_items_quantity[item] >= \ self.env.recipes[item_to_craft]['input'][item]: have_all_ingredients[item] = True else: have_all_ingredients[item] = False # If there are not enough ingredients in the inventory if False in have_all_ingredients.values(): result = False message = "Missing items: " if item_to_craft == 'tree_tap': step_cost = 360.0 elif item_to_craft == 'pogo_stick': step_cost = 480.0 for item in have_all_ingredients: if not have_all_ingredients[item]: message += str(self.env.recipes[item_to_craft]['input'][item]) + ' ' + item + ', ' return reward, result, step_cost, message[:-2] # Craft else: # If more than 1 ingredient needed, agent needs to be in front of crafting_table if len(self.env.recipes[item_to_craft]['input']) > 1: self.env.update_block_in_front() if not self.env.block_in_front_str == 'crafting_table': if item_to_craft == 'tree_tap': step_cost = 720.0 elif item_to_craft == 'pogo_stick': step_cost = 840.0 elif item_to_craft == self.axe_name: step_cost = 600.0 result = False message = 'Need to be in front of crafting_table' return reward, result, step_cost, message reward = self.reward_intermediate # default reward to craft in a good way # Reduce ingredients from the inventory for item in self.env.recipes[item_to_craft]['input']: self.env.inventory_items_quantity[item] -= self.env.recipes[item_to_craft]['input'][item] # Add item_to_craft in the inventory self.env.inventory_items_quantity[item_to_craft] += self.env.recipes[item_to_craft]['output'][item_to_craft] if item_to_craft == 'plank': step_cost = 1200.0 elif item_to_craft == 'stick': step_cost = 2400.0 elif item_to_craft == 'tree_tap': step_cost = 7200.0 elif item_to_craft == 'pogo_stick': step_cost = 8400.0 elif item_to_craft == self.axe_name: step_cost = 6000.0 message = 'Crafted ' + item_to_craft return reward, result, step_cost, message class Fence(gym.core.Wrapper): """ Novelty wrapper to add fence around items in the map """ def __init__(self, env, difficulty, fence_material): super().__init__(env) self.fence_name = fence_material + '_fence' # oak_fence, jungle_fence self.env.items.add(self.fence_name) self.env.items_id.setdefault(self.fence_name, len(self.items_id)) self.env.select_actions_id.update({'Select_' + self.fence_name: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) if difficulty == 'easy': self.fence_percent_range = (20, 50) elif difficulty == 'medium': self.fence_percent_range = (50, 90) else: self.fence_percent_range = (90, 100) def reset(self): self.env.reset() result = np.array(np.where((self.env.map != 0) & (self.env.map != self.env.items_id['wall']))) # Shuffling locations in result indices = np.arange(len(result[0])) np.random.shuffle(indices) result[0] = result[0][indices] result[1] = result[1][indices] fence_percent = np.random.randint(low=self.fence_percent_range[0], high=self.fence_percent_range[1], size=1)[0] for i in range(int(np.ceil(len(result[0]) * (fence_percent / 100)))): r, c = result[0][i], result[1][i] self.env.add_fence_around((r, c), self.fence_name) # Update after each reset obs = self.get_observation() self.update_block_in_front() return obs class FenceRestriction(gym.core.Wrapper): """ Novelty wrapper to restrict breaking an item around fence until fence(s) are broken. All fences are always breakable. """ def __init__(self, env, difficulty, fence_material): super().__init__(env) self.difficulty = difficulty self.env2 = Fence(env, 'medium', fence_material=fence_material) def reset(self): obs = self.env2.reset() return obs def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Break' in self.limited_actions_id, "Cannot use fencerestriction novelty because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Break'] and self.difficulty != 'easy': self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() if self.env.block_in_front_str not in self.env.unbreakable_items: if self.env.block_in_front_str == self.env2.fence_name: # Fence is always breakable obs, reward, done, info = self.env.step(action_id) else: fence_restriction = False if self.difficulty == 'medium': # In medium, one side of the item to break must not have fence and agent must be on that side r, c = self.agent_location if self.agent_facing_str == 'NORTH' or self.agent_facing_str == 'SOUTH': if self.map[r][c - 1] == self.items_id[self.env2.fence_name] or self.map[r][c + 1] == self.items_id[self.env2.fence_name]: fence_restriction = True elif self.agent_facing_str == 'WEST' or self.agent_facing_str == 'EAST': if self.map[r - 1][c] == self.items_id[self.env2.fence_name] or self.map[r + 1][c] == self.items_id[self.env2.fence_name]: fence_restriction = True else: # In hard, all the sides of the item to break must not have fence r, c = self.block_in_front_location for r_item in [r - 1, r, r + 1]: for c_item in [c - 1, c, c + 1]: if self.map[r_item][c_item] == self.items_id[self.env2.fence_name]: fence_restriction = True break if not fence_restriction: obs, reward, done, info = self.env.step(action_id) else: result = False message = "Cannot break due to fence restriction" else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class AddItem(gym.core.Wrapper): """ Novelty wrapper to add a new item in the map """ def __init__(self, env, difficulty, item_to_add): super().__init__(env) self.item_to_add = item_to_add self.env.items.add(self.item_to_add) self.env.items_id.setdefault(self.item_to_add, len(self.items_id)) # self.env.entities.add(self.item_to_add) self.env.select_actions_id.update({'Select_' + self.item_to_add: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) if difficulty == 'easy': self.item_percent_range = (1, 10) elif difficulty == 'medium': self.item_percent_range = (10, 20) else: self.item_percent_range = (20, 30) def reset(self): self.env.reset() result = np.array(np.where(self.env.map == 0)) # Shuffling locations in result indices = np.arange(len(result[0])) np.random.shuffle(indices) result[0] = result[0][indices] result[1] = result[1][indices] item_percent = np.random.randint(low=self.item_percent_range[0], high=self.item_percent_range[1], size=1)[0] for i in range(int(np.ceil(len(result[0]) * (item_percent / 100)))): r, c = result[0][i], result[1][i] if (r, c) != self.env.agent_location: self.env.map[r][c] = self.items_id[self.item_to_add] # Update after each reset obs = self.get_observation() self.update_block_in_front() return obs class Crate(gym.core.Wrapper): """ Novelty wrapper to add crate(s) in the map. When the crate is broken, some ingredients of the goal_item_to_craft gets in the inventory """ def __init__(self, env, difficulty): super().__init__(env) self.env2 = AddItem(env, 'easy', item_to_add='crate') if difficulty == 'easy': item_percent_range = (99, 100) elif difficulty == 'medium': item_percent_range = (50, 90) else: item_percent_range = (10, 50) item_percent = np.random.randint(low=item_percent_range[0], high=item_percent_range[1], size=1)[0] total_ingredients = 0 ingredients = [] for item in self.recipes[self.goal_item_to_craft]['input']: total_ingredients += self.recipes[self.goal_item_to_craft]['input'][item] ingredients.append(item) crate_ingredients_num = int(np.ceil((item_percent / 100) * total_ingredients)) self.crate_ingredients = [] while crate_ingredients_num: item = np.random.choice(ingredients, size=1)[0] if self.crate_ingredients.count(item) < self.recipes[self.goal_item_to_craft]['input'][item]: self.crate_ingredients.append(item) crate_ingredients_num -= 1 def reset(self): obs = self.env2.reset() return obs def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Break' in self.limited_actions_id, "Cannot use crate novelty because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Break'] and self.env.block_in_front_str == 'crate': for item in self.crate_ingredients: self.env.inventory_items_quantity[item] += 1 obs, reward, done, info = self.env.step(action_id) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class ReplaceItem(gym.core.Wrapper): """ Novelty wrapper to replace an item with another """ def __init__(self, env, difficulty, item_to_replace='wall', item_to_replace_with='brick'): super().__init__(env) self.item_to_replace = item_to_replace self.item_to_replace_with = item_to_replace_with assert self.item_to_replace in self.env.items_id, "Item to replace (" + self.item_to_replace + \ ") is not in the original map" assert self.item_to_replace_with not in self.env.items_id, "Item to replace with (" + self.item_to_replace_with \ + ") should be a new item" self.env.items.add(self.item_to_replace_with) self.env.items_id.setdefault(self.item_to_replace_with, len(self.items_id)) # self.env.entities.add(self.item_to_replace_with) self.env.select_actions_id.update({'Select_' + self.item_to_replace_with: len(self.env.actions_id)}) self.env.actions_id.update(self.env.select_actions_id) if self.item_to_replace == 'wall': self.env.unbreakable_items.add(self.item_to_replace_with) if difficulty == 'easy': self.item_percent_range = (5, 20) elif difficulty == 'medium': self.item_percent_range = (40, 90) else: self.item_percent_range = (99, 100) def reset(self): self.env.reset() result = np.array(np.where(self.env.map == self.env.items_id[self.item_to_replace])) # Shuffling locations in result indices = np.arange(len(result[0])) np.random.shuffle(indices) result[0] = result[0][indices] result[1] = result[1][indices] item_percent = np.random.randint(low=self.item_percent_range[0], high=self.item_percent_range[1], size=1)[0] for i in range(int(np.ceil(len(result[0]) * (item_percent / 100)))): r, c = result[0][i], result[1][i] if (r, c) != self.env.agent_location: self.env.map[r][c] = self.items_id[self.item_to_replace_with] # Update after each reset obs = self.env.get_observation() self.update_block_in_front() return obs class FireWall(gym.core.Wrapper): """ Novelty wrapper to add fire_wall, agent dies when it's next to fire_wall """ def __init__(self, env, difficulty='hard'): super().__init__(env) self.env2 = ReplaceItem(env, difficulty, item_to_replace='wall', item_to_replace_with='fire_wall') def reset(self): obs = self.env2.reset() return obs def step(self, action_id): obs, reward, done, info = self.env.step(action_id) r, c = self.agent_location close_to_fire_wall = False # NORTH if (0 <= (r - 1) <= self.map_size - 1) and self.map[r - 1][c] == self.env.items_id['fire_wall']: close_to_fire_wall = True # SOUTH elif (0 <= (r + 1) <= self.map_size - 1) and self.map[r + 1][c] == self.env.items_id['fire_wall']: close_to_fire_wall = True # WEST elif (0 <= (c - 1) <= self.map_size - 1) and self.map[r][c - 1] == self.env.items_id['fire_wall']: close_to_fire_wall = True # EAST elif (0 <= (c + 1) <= self.map_size - 1) and self.map[r][c + 1] == self.env.items_id['fire_wall']: close_to_fire_wall = True if close_to_fire_wall: reward = -self.reward_done // 2 done = True info['message'] = 'You died due to fire_wall' # Update after each step self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) return obs, reward, done, info def remap_action_difficulty(env, difficulty='hard'): """ Remap actions randomly If LimitActions wrapper is used only limited_actions will be remapped regardless of any difficulty """ if hasattr(env, 'limited_actions_id'): env.set_limited_actions_id(env.remap_action(env.limited_actions_id, 0)) else: if difficulty == 'easy': env.manipulation_actions_id = env.remap_action(env.manipulation_actions_id, 0) env.actions_id.update(env.manipulation_actions_id) elif difficulty == 'medium': env.manipulation_actions_id = env.remap_action(env.manipulation_actions_id, 0) env.craft_actions_id = env.remap_action(env.craft_actions_id, len(env.manipulation_actions_id)) env.actions_id.update(env.manipulation_actions_id) env.actions_id.update(env.craft_actions_id) else: env.actions_id = env.remap_action(env.actions_id, 0) env.craft_actions_id = {action: env.actions_id[action] for action in env.actions_id if action.startswith('Craft')} env.select_actions_id = {action: env.actions_id[action] for action in env.actions_id if action.startswith('Select')} return env # Novelty without difficulty types: class BlockItem(gym.core.Wrapper): """ Novelty wrapper to block crafting_table from tree_log when rubber is extracted """ def __init__(self, env): super().__init__(env) self.items_to_block = 'crafting_table' self.item_to_block_from = 'tree_log' self.env.items.add('fence') self.env.items_id.setdefault('fence', len(self.items_id)) def step(self, action_id): old_rubber_quantity = copy.deepcopy(self.env.inventory_items_quantity['rubber']) obs, reward, done, info = self.env.step(action_id) # Extract_rubber if action_id == self.actions_id['Extract_rubber']: if old_rubber_quantity < self.env.inventory_items_quantity['rubber']: # Block by self.item_to_block_from # self.env.block_items(item_to_block=self.items_to_block, item_to_block_from=self.item_to_block_from) # Block by fence result = np.where(self.env.map == self.env.items_id[self.items_to_block]) for i in range(len(result[0])): r, c = result[0][i], result[1][i] self.env.add_fence_around((r, c)) return obs, reward, done, info class AddChopAction(gym.core.Wrapper): """ Novelty wrapper to add chop action It's like break action, but instead of 1 item, agent will get 2 items, but step_cost will be higher (1.2 times) """ def __init__(self, env): super().__init__(env) self.env.manipulation_actions_id['Chop'] = len(self.actions_id) self.env.actions_id.update(self.manipulation_actions_id) self.action_space = spaces.Discrete(len(self.actions_id)) def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Chop' in self.limited_actions_id, "Cannot use addchop novelty because you do not have Chop in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Chop']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 * 1.2 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.block_in_front_str not in self.unbreakable_items: block_r, block_c = self.block_in_front_location self.map[block_r][block_c] = 0 self.inventory_items_quantity[self.block_in_front_str] += 1 * 2 reward = self.reward_intermediate else: result = False message = "Cannot chop " + self.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class AddJumpAction(gym.core.Wrapper): """ Novelty wrapper to add jump action, when it's executed, the agent jumps 2 blocks forward """ def __init__(self, env): super().__init__(env) self.env.manipulation_actions_id['Jump'] = len(self.actions_id) self.env.actions_id.update(self.manipulation_actions_id) self.action_space = spaces.Discrete(len(self.actions_id)) def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Jump' in self.limited_actions_id, "Cannot use addjump novelty because you do not have Jump in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Jump']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] r, c = self.agent_location reward = -1 # default reward result = True step_cost = 0 # default step_cost message = '' if self.agent_facing_str == 'NORTH' and (0 <= (r - 2) <= self.map_size - 1) and self.map[r - 2][c] == 0: self.set_agent_location(r - 2, c) elif self.agent_facing_str == 'SOUTH' and (0 <= (r + 2) <= self.map_size - 1) and self.map[r + 2][c] == 0: self.set_agent_location(r + 2, c) elif self.agent_facing_str == 'WEST' and (0 <= (c - 2) <= self.map_size - 1) and self.map[r][c - 2] == 0: self.set_agent_location(r, c - 2) elif self.agent_facing_str == 'EAST' and (0 <= (c + 2) <= self.map_size - 1) and self.map[r][c + 2] == 0: self.set_agent_location(r, c + 2) else: result = False message = 'Block in path' step_cost = 27.906975 * 2 # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class BreakIncrease(gym.core.Wrapper): """ Novelty wrapper to get 2 items in inventory when the agent break that item instead of 1 itemtobreakmore: apply this to only itemtobreakmore or if itemtobreakmore == '', then to all items """ def __init__(self, env, itemtobreakmore=''): super().__init__(env) self.itemtobreakmore = itemtobreakmore def step(self, action_id): if hasattr(self, 'limited_actions_id'): assert 'Break' in self.limited_actions_id, "Cannot use breakincrease novelty because you do not have Break in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id if action_id == actions_id['Break']: self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] reward = -1 # default reward result = True step_cost = 3600.0 message = '' self.env.update_block_in_front() # If block in front is not air and wall, place the block in front in inventory if self.env.block_in_front_str not in self.env.unbreakable_items: block_r, block_c = self.env.block_in_front_location self.env.map[block_r][block_c] = 0 if self.itemtobreakmore == self.env.block_in_front_str: self.env.inventory_items_quantity[self.itemtobreakmore] += 2 elif self.itemtobreakmore == '': self.env.inventory_items_quantity[self.block_in_front_str] += 2 else: self.env.inventory_items_quantity[self.env.block_in_front_str] += 1 reward = self.reward_intermediate else: result = False message = "Cannot break " + self.env.block_in_front_str # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info class ExtractIncDec(gym.core.Wrapper): """ Novelty wrapper to increase/decrease string when Extract_string action is executed incdec: 'increase' to increase, 'decrease' to decrease """ def __init__(self, env, incdec='decrease'): super().__init__(env) self.incdec = incdec def step(self, action_id): if hasattr(self, 'limited_actions_id'): has_extract = False for action in self.limited_actions_id: if action.startswith('Extract'): has_extract = True break assert has_extract, "Cannot use extractincdec novelty because you do not have Extract action in LimitActions" actions_id = self.limited_actions_id else: actions_id = self.actions_id self.env.last_action = list(actions_id.keys())[list(actions_id.values()).index(action_id)] if self.env.last_action.startswith('Extract'): reward = -1 # default reward result = True step_cost = 120.0 # default step_cost message = '' if self.env_id.startswith('NovelGridworld-Bow'): if self.block_in_front_str == 'wool': if self.incdec == 'increase': self.inventory_items_quantity['string'] += 4 * 2 # Extract_string else: self.inventory_items_quantity['string'] += 4 // 2 # Extract_string block_r, block_c = self.block_in_front_location self.map[block_r][block_c] = 0 reward = self.reward_intermediate step_cost = 5000 else: result = False message = "No wool found" elif self.env_id.startswith('NovelGridworld-Pogostick'): # Make sure that block_in_front_location is next to a tree block_in_front_next_to_tree = self.is_block_in_front_next_to('tree_log') if self.block_in_front_str == 'tree_tap': if block_in_front_next_to_tree: if self.incdec == 'increase': self.inventory_items_quantity['rubber'] += 1 * 2 # Extract_rubber reward = self.reward_intermediate step_cost = 50000 else: result = False message = "No tree_log near tree_tap" else: result = False message = "No tree_tap found" # Update after each step self.env.grab_entities() if hasattr(self, 'observation'): obs = self.observation() else: obs = self.env.get_observation() self.env.update_block_in_front() done = False if self.env.inventory_items_quantity[self.goal_item_to_craft] >= 1: reward = self.reward_done done = True info = {'result': result, 'step_cost': step_cost, 'message': message} # Update after each step self.env.step_count += 1 self.env.last_step_cost = step_cost self.env.last_reward = reward self.env.last_done = done lasts = {'last_action': self.env.last_action, 'step_count': self.env.step_count, 'last_step_cost': self.env.last_step_cost, 'last_reward': self.env.last_reward, 'last_done': self.env.last_done} self.set_lasts(lasts) else: obs, reward, done, info = self.env.step(action_id) return obs, reward, done, info #################### Novelty Helper #################### def inject_novelty(env, novelty_name, difficulty='hard', novelty_arg1='', novelty_arg2=''): novelty_names = ['addchop', 'additem', 'addjump', 'axe', 'axetobreak', 'breakincrease', 'crate', 'extractincdec', 'fence', 'fencerestriction', 'firewall', 'remapaction', 'replaceitem'] assert novelty_name in novelty_names, "novelty_name must be one of " + str(novelty_names) if novelty_name in ['additem', 'axe', 'axetobreak', 'crate', 'fence', 'fencerestriction', 'firewall', 'remapaction', 'replaceitem']: assert difficulty in ['easy', 'medium', 'hard'], "difficulty must be one of 'easy', 'medium', 'hard'" if novelty_name == 'addchop': env = AddChopAction(env) elif novelty_name == 'additem': assert novelty_arg1, "For additem novelty, novelty_arg1 (name of the item to add) is needed" env = AddItem(env, difficulty, novelty_arg1) elif novelty_name == 'addjump': env = AddJumpAction(env) elif novelty_name == 'axe': assert novelty_arg1 in ['wooden', 'iron'], \ "For axe novelty, novelty_arg1 (attribute of axe, e.g. wooden, iron) is needed" if novelty_arg2: assert novelty_arg2 in ['true', 'false'], "For axe novelty, novelty_arg2 (breakincrease) must be 'true' or 'false'" if difficulty == 'easy': env = AxeEasy(env, novelty_arg1, novelty_arg2) elif difficulty == 'medium': env = AxeMedium(env, novelty_arg1, novelty_arg2) elif difficulty == 'hard': env = AxeHard(env, novelty_arg1, novelty_arg2) else: if difficulty == 'easy': env = AxeEasy(env, novelty_arg1) elif difficulty == 'medium': env = AxeMedium(env, novelty_arg1) elif difficulty == 'hard': env = AxeHard(env, novelty_arg1) elif novelty_name == 'axetobreak': assert novelty_arg1 in ['wooden', 'iron'], \ "For axe novelty, novelty_arg1 (attribute of axe, e.g. wooden, iron) is needed" if difficulty == 'easy': env = AxetoBreakEasy(env, novelty_arg1) elif difficulty == 'medium': env = AxetoBreakMedium(env, novelty_arg1) elif difficulty == 'hard': env = AxetoBreakHard(env, novelty_arg1) elif novelty_name == 'breakincrease': if novelty_arg1: assert novelty_arg1 in env.items, env.itemtobreakmore + " is not in " + env.env_id env = BreakIncrease(env, novelty_arg1) else: env = BreakIncrease(env) elif novelty_name == 'crate': env = Crate(env, difficulty) elif novelty_name == 'extractincdec': assert novelty_arg1 in ['increase', 'decrease'], \ "For extractincdec novelty, novelty_arg1 ('increase', 'decrease') is needed" assert env.env_id != 'NovelGridworld-Bow-v0', "There is nothing to extract in NovelGridworld-Bow-v0" if env.env_id == 'NovelGridworld-Bow-v1': assert novelty_arg1 == 'decrease', "In NovelGridworld-Bow-v1, increasing string extraction will not benefit " \ "as only 3 string are needed" assert not env.env_id.startswith('NovelGridworld-Pogostick'), "In NovelGridworld-Pogostick, you should not use " \ "extractincdec novelty because rubber extraction cannot be decreased, and increasing rubber extraction will" \ " not benefit as only 1 rubber is needed" env = ExtractIncDec(env, novelty_arg1) elif novelty_name == 'fence': assert novelty_arg1, "For fence novelty, novelty_arg1 (attribute of fence, e.g. oak, jungle) is needed" env = Fence(env, difficulty, novelty_arg1) elif novelty_name == 'fencerestriction': assert novelty_arg1, "For fencerestriction novelty, novelty_arg1 (attribute of fence, e.g. oak, jungle) is needed" env = FenceRestriction(env, difficulty, novelty_arg1) elif novelty_name == 'firewall': env = FireWall(env, difficulty) elif novelty_name == 'remapaction': env = remap_action_difficulty(env, difficulty) elif novelty_name == 'replaceitem': assert novelty_arg1 and novelty_arg2, "For replaceitem novelty, novelty_arg1 (Item to replace) and novelty_arg2" \ "(Item to replace with) are needed" env = ReplaceItem(env, difficulty, novelty_arg1, novelty_arg2) return env

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8aba7cf6bbae988523fe116fa67e1795059a1673

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py

Python

A2/Versions/assign2v4.py

ShamsuddohaShameem17/coms3200

211df3ea954c33f64cc833772e07e90356baa853

[ "MIT" ]

null

A2/Versions/assign2v4.py

ShamsuddohaShameem17/coms3200

211df3ea954c33f64cc833772e07e90356baa853

[ "MIT" ]

null

A2/Versions/assign2v4.py

ShamsuddohaShameem17/coms3200

211df3ea954c33f64cc833772e07e90356baa853

[ "MIT" ]

1

2021-05-13T21:09:21.000Z

# REF: https://pymotw.com/2/struct/ #Creating a RUSH packet sender import sys import socket from collections import namedtuple from struct import pack, unpack LOCALHOST = "127.0.0.1" LOCAL_ADDR_INFO =(LOCALHOST,0) PACKET_SIZE = 1472 PAYLOAD_SIZE = 1466 PAYLOAD_SIZE_BITS = PAYLOAD_SIZE * 8 SEND_SIZE = 1500 #Max size of RUSH packet RECV_SIZE = 1500 #Max size of RUSH packet # Creating RUSH packets rushFields = ("seq_num","ack_num","ack_flag","nak_flag","get_flag","dat_flag","fin_flag","reserved","data") defaultFieldValues = [0,0,0,0,0,0,0,0] Packet = namedtuple('RUSH', rushFields, defaults = defaultFieldValues) # Find free ports by PC def free_port(): dummy = socket.socket() dummy.bind(LOCAL_ADDR_INFO) # Bind to a free port provided by the host computer. (port 0) freePort = dummy.getsockname()[1] dummy.close() return freePort # Return the port number assigned. # Convert string to integer (byte representation) def str_to_int(string, pad=PAYLOAD_SIZE): b_str = string.encode("UTF-8") if pad is not None: for i in range(len(string), pad): b_str += b'\0' return int.from_bytes(b_str, byteorder='big') # Convert byte (represented as integer) to string (data) def int_to_str(integer, size=PAYLOAD_SIZE): return integer.to_bytes(size, byteorder='big').rstrip(b'\x00').decode("UTF-8") # Convert the packet into bytes array def raw(packet): # Packet Identifier seq_num = packet.seq_num ack_num = packet.ack_num packet_id_bytes = pack('!hh',seq_num,ack_num) # Flags ack_flag = packet.ack_flag nak_flag = packet.nak_flag get_flag = packet.get_flag dat_flag = packet.dat_flag fin_flag = packet.fin_flag flag_list = [ack_flag,nak_flag,get_flag,dat_flag,fin_flag] flag_str = "".join(map(str,flag_list))+"000" flag_byte = pack("!B",int(flag_str,base=2)) # Reserved Byte reserved = b'\x00' #Data #data_byte = str_to_int(packet.data) # data_byte =bytes(str(str_to_int(packet.data)).encode()) # print(data_byte) # print(bytes(str(data_byte).encode())) # raw_byte =b"".join([packet_id_bytes,flag_byte,reserved, data_byte]) ##Take 2 # data_length = len(str(packet.data)) # padding_size = PAYLOAD_SIZE-data_length # print(packet.data) # print(">>>",data_length,padding_size) # data_byte = packet.data.encode("UTF-8") # for i in range(len(packet.data), PAYLOAD_SIZE): # data_byte += b'\0' # print(data_byte) ##Take 3 data_byte = str_to_int(packet.data).to_bytes(PAYLOAD_SIZE, byteorder='big') raw_byte =b"".join([packet_id_bytes,flag_byte,reserved, data_byte]) return raw_byte # Convert raw packet information into packet (repr) def raw_packet_decode(rawByte): # First 6 Bytes are RUSH HEADER without payload unpacked_data = unpack('!hhBx', rawByte[0:6]) #gives (1, 0, 8192) seq_num, ack_num, flag_byte= unpacked_data flagStr = bin(int(str(flag_byte),base=10))[2:7] #first 5 bits print("Binary string of byte:",flagStr) flags = [int(c) for c in flagStr] data_info = rawByte[6:].rstrip(b'\x00').decode("UTF-8") packet_val_list = [seq_num,ack_num] packet_val_list.extend(flags) return Packet(*packet_val_list,data = data_info) def print_packet(packet): print(repr(packet)) ######################################################################################################### class Connection: def __init__(self, my_ip, my_port): self._my_info = (my_ip, my_port) self._socket = None self._seq_num = 1 def _print(self, pkt, port, mode): output = "{} port {}:\n (seq_num={}, ack_num={}, flags={}{}{}{}{})".format(mode, port, pkt.seq_num, pkt.ack_num, pkt.ack_flag, pkt.nak_flag, pkt.get_flag, pkt.dat_flag, pkt.fin_flag) output += "\n Data: {}".format(repr(int_to_str(pkt.data))) print(output + "\n") def _find_freeport(self): return free_port() def connect(self): try: self._socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) self._socket.bind(self._my_info) return True except socket.error as err: print("Error encountered when opening socket:\n", err) return False def close(self): self._socket.close() def send_request(self, resource): pkt = RUSH(seq_num=self._seq_num, get_flag=1, data=str_to_int(resource)) self._socket.sendto(raw(pkt), self._serv_info) self._seq_num += 1 self._print(pkt, self._serv_info[1], SEND_MODE) def recv_pkt(self): raw_data, info = self._socket.recvfrom(RECV_SIZE) assert len(raw_data) <= PACKET_SIZE, "Received overlong packet: " + repr(raw_data) try: #OLD: return RUSH(raw_data), info ########## except: assert False, "Could not decode packet: " + repr(raw_data) def run(self): while True: pkt, info = self.recv_pkt() self._print(pkt, info[1], RECV_MODE) if pkt.fin_flag == 1 and all(i == 0 for i in (pkt.ack_flag, pkt.nak_flag, pkt.dat_flag, pkt.get_flag)): cli_fin_ack = RUSH(seq_num=self._seq_num, ack_num=pkt.seq_num, fin_flag=1, ack_flag=1) self._socket.sendto(raw(cli_fin_ack), self._serv_info) self._seq_num += 1 self._print(cli_fin_ack, self._serv_info[1], SEND_MODE) while True: serv_fin_ack, info = self.recv_pkt() self._print(serv_fin_ack, info[1], RECV_MODE) if serv_fin_ack.fin_flag == 1 and serv_fin_ack.ack_flag == 1 and \ all(i == 0 for i in (serv_fin_ack.nak_flag, serv_fin_ack.dat_flag, serv_fin_ack.get_flag)): return # end of connection elif pkt.dat_flag == 1: ack = RUSH(seq_num=self._seq_num, ack_num=pkt.seq_num, dat_flag=1, ack_flag=1) self._socket.sendto(raw(ack), self._serv_info) self._seq_num += 1 self._print(ack, self._serv_info[1], SEND_MODE) ############################################################################################# def main(argv): if len(argv) >= 2: print("Usage: python3 assign2.py") return my_port = free_port() serv_port = free_port() print("my port:",my_port,"serv port:",serv_port) LOCAL_ADDR_INFO = (LOCALHOST,my_port) # sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) # sock.bind(LOCAL_ADDR_INFO) # #Recieve data # totalData = [] # while True: # # Data are in bytes # data = sock.recv(RECV_SIZE) # if not data: break # totalData.append(data) # print(b''.join(totalData)) #========================================================================# # conn = Connection(LOCALHOST, my_port, LOCALHOST, serv_port, debug_level) # if not conn.connect(): # return # try: # conn.send_request(FILE_NAME) # conn.run() # except AssertionError as e: # print(e.args[0]) #conn.close() #========================================================================# #sock.close() raw_in = 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print(raw_packet_decode(raw_in)) tst = Packet(seq_num=1,ack_flag=1,data='file.txt') raw_val = raw(tst) print(raw_val) print("Decoding",raw_packet_decode(raw_val)) pass if __name__ == "__main__": main(sys.argv)

64.711538

5,904

0.667088

2,534

13,460

3.433702

0.080505

1.010918

1.515343

2.019078

0.630157

0.607057

0.593265

0.566257

0.557292

0.541892

0

0.259171

0.129123

13,460

208

5,905

64.711538

0.483109

0.1263

0

0.070866

0

0.007874

0.546048

0.512535

0

1

0

0.015748

1

0.11811

false

0.007874

0.031496

0.015748

0.244094

0.125984

0

null

1

0

1

0

1

0

1

0

1

null

1

0

8

76f5a0b102fd0e16dd9343e88d07aa7fa886b5c7

92

py

Python

parameters_8080.py

wasuaje/web2py5

02f310b9526f92c4ec62ab5b0271069a1c101e9f

[ "BSD-3-Clause" ]

null

parameters_8080.py

wasuaje/web2py5

02f310b9526f92c4ec62ab5b0271069a1c101e9f

[ "BSD-3-Clause" ]

null

parameters_8080.py

wasuaje/web2py5

02f310b9526f92c4ec62ab5b0271069a1c101e9f

[ "BSD-3-Clause" ]

null

password="pbkdf2(1000,20,sha512)$bb52f3e9876e0730$0bb37c618f43b658beefac05844b4795d0311e45"

46

91

0.891304

7

92

11.714286

1

0

0.516484

0.01087

92

1

92

0.384615

0

0.869565

0

1

0

false

1

0

1

0

1

null

0

1

0

1

0

1

0

1

null

0

1

0

8

6a689443e7a572d063847663310c8b58021ec566

35,353

py

Python

COMET/resources/svg_resources_rc.py

dallaval5u/COMET

8c5793faafe2797dd4100507aa0fe1e71cf9f6c0

[ "MIT" ]

null

COMET/resources/svg_resources_rc.py

dallaval5u/COMET

8c5793faafe2797dd4100507aa0fe1e71cf9f6c0

[ "MIT" ]

null

COMET/resources/svg_resources_rc.py

dallaval5u/COMET

8c5793faafe2797dd4100507aa0fe1e71cf9f6c0

[ "MIT" ]

null

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\x00\x00\x00\x3a\x00\x02\x00\x00\x00\x01\x00\x00\x00\x05\ \x00\x00\x00\x54\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\ \x00\x00\x00\xa4\x00\x00\x00\x00\x00\x01\x00\x00\x17\x98\ \x00\x00\x00\x76\x00\x00\x00\x00\x00\x01\x00\x00\x06\xf9\ \x00\x00\x00\x8c\x00\x00\x00\x00\x00\x01\x00\x00\x0f\x43\ " qt_resource_struct_v2 = b"\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x04\x00\x00\x00\x01\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x1e\x00\x02\x00\x00\x00\x01\x00\x00\x00\x08\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x2c\x00\x02\x00\x00\x00\x01\x00\x00\x00\x07\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x06\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x3a\x00\x02\x00\x00\x00\x01\x00\x00\x00\x05\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x54\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\ \x00\x00\x01\x69\xc9\x81\x48\xec\ \x00\x00\x00\xa4\x00\x00\x00\x00\x00\x01\x00\x00\x17\x98\ \x00\x00\x01\x69\xc8\xe3\xb6\x92\ \x00\x00\x00\x76\x00\x00\x00\x00\x00\x01\x00\x00\x06\xf9\ \x00\x00\x01\x69\xc4\x3a\xfd\xd0\ \x00\x00\x00\x8c\x00\x00\x00\x00\x00\x01\x00\x00\x0f\x43\ \x00\x00\x01\x69\xc4\x3a\xfd\xcb\ " qt_version = QtCore.qVersion().split(".") if qt_version < ["5", "8", "0"]: rcc_version = 1 qt_resource_struct = qt_resource_struct_v1 else: rcc_version = 2 qt_resource_struct = qt_resource_struct_v2 def qInitResources(): QtCore.qRegisterResourceData( rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data ) def qCleanupResources(): QtCore.qUnregisterResourceData( rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data ) qInitResources()

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13

6a7e50a53d1f785658e81e7ea1992e28ac663a2c

13,859

py

Python

internetradio/src/InternetRadioOledDisplay.py

Mariusz1970/enigma2-plugins-1

126d31d075c156f32b09d4321ebe1a17f93a5bd6

[ "OLDAP-2.3" ]

1

2020-01-27T22:53:56.000Z

internetradio/src/InternetRadioOledDisplay.py

Mariusz1970/enigma2-plugins-1

126d31d075c156f32b09d4321ebe1a17f93a5bd6

[ "OLDAP-2.3" ]

null

internetradio/src/InternetRadioOledDisplay.py

Mariusz1970/enigma2-plugins-1

126d31d075c156f32b09d4321ebe1a17f93a5bd6

[ "OLDAP-2.3" ]

11

2015-02-26T20:59:14.000Z

2021-09-20T08:23:03.000Z

# # InternetRadio E2 # # Coded by Dr.Best (c) 2012 # Support: www.dreambox-tools.info # E-Mail: dr.best@dreambox-tools.info # # This plugin is open source but it is NOT free software. # # This plugin may only be distributed to and executed on hardware which # is licensed by Dream Multimedia GmbH. # In other words: # It's NOT allowed to distribute any parts of this plugin or its source code in ANY way # to hardware which is NOT licensed by Dream Multimedia GmbH. # It's NOT allowed to execute this plugin and its source code or even parts of it in ANY way # on hardware which is NOT licensed by Dream Multimedia GmbH. # # If you want to use or modify the code or parts of it, # you have to keep MY license and inform me about the modifications by mail. # from Screens.Screen import Screen from Components.ProgressBar import ProgressBar from Components.Pixmap import Pixmap from Components.Label import Label from InternetRadioVisualization import InternetRadioVisualization class InternetRadioOledDisplay(Screen, InternetRadioVisualization): # helper for skinning # skincontent = "" # skincontent2 = "" # count = 16 # x = 0 # posx = 1 # skinid = 0 # while True: # skincontent += "<widget name=\"progress_%d\" zPosition=\"3\" position=\"%d,5\" size=\"5,50\" transparent=\"1\" orientation=\"orBottomToTop\" pixmap=\"/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png\" />\n" % (x,posx) # skincontent2 += "<widget name=\"top_%d\" position=\"%d,5\" zPosition=\"6\" size=\"5,2\" transparent=\"1\" pixmap=\"/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png\" />\n" % (x,posx) # posx += 6 # x += 1 # if x == count: # break skin = (""" <screen name="InternetRadioOledDisplay" position="0,0" size="96,64" id="2"> <widget name="text1" position="4,0" size="96,14" font="Regular;12" halign="center" valign="center"/> <widget name="text2" position="4,14" size="96,49" font="Regular;10" halign="center" valign="center"/> <widget name="progress_0" zPosition="3" position="1,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_1" zPosition="3" position="7,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_2" zPosition="3" position="13,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_3" zPosition="3" position="19,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_4" zPosition="3" position="25,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_5" zPosition="3" position="31,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_6" zPosition="3" position="37,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_7" zPosition="3" position="43,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_8" zPosition="3" position="49,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_9" zPosition="3" position="55,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_10" zPosition="3" position="61,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_11" zPosition="3" position="67,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_12" zPosition="3" position="73,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_13" zPosition="3" position="79,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_14" zPosition="3" position="85,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="progress_15" zPosition="3" position="91,5" size="5,50" transparent="1" orientation="orBottomToTop" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled-fs8.png" /> <widget name="top_0" position="1,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_1" position="7,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_2" position="13,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_3" position="19,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_4" position="25,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_5" position="31,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_6" position="37,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_7" position="43,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_8" position="49,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_9" position="55,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_10" position="61,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_11" position="67,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_12" position="73,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_13" position="79,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_14" position="85,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> <widget name="top_15" position="91,5" zPosition="6" size="5,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/bar_oled_top-fs8.png" /> </screen>""",""" <screen name="InternetRadioOledDisplay" position="0,0" size="132,64" id="1"> <widget name="text1" position="4,0" size="132,14" font="Regular;12" halign="center" valign="center"/> <widget name="text2" position="4,14" size="132,49" font="Regular;10" halign="center" valign="center"/> <widget name="progress_0" zPosition="3" position="2,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_1" zPosition="3" position="10,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_2" zPosition="3" position="18,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_3" zPosition="3" position="26,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_4" zPosition="3" position="34,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_5" zPosition="3" position="42,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_6" zPosition="3" position="50,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_7" zPosition="3" position="58,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_8" zPosition="3" position="66,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_9" zPosition="3" position="74,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_10" zPosition="3" position="82,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_11" zPosition="3" position="90,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_12" zPosition="3" position="98,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_13" zPosition="3" position="106,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_14" zPosition="3" position="114,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="progress_15" zPosition="3" position="122,5" size="7,50" transparent="1" orientation="orBottomToTop" /> <widget name="top_0" position="2,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_1" position="10,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_2" position="18,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_3" position="26,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_4" position="34,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_5" position="42,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_6" position="50,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_7" position="58,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_8" position="66,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_9" position="74,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_10" position="82,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_11" position="90,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_12" position="98,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_13" position="106,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_14" position="114,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> <widget name="top_15" position="122,5" zPosition="6" size="7,2" transparent="1" pixmap="/usr/lib/enigma2/python/Plugins/Extensions/InternetRadio/images/topvalue-lcd-fs8.png" /> </screen>""") def __init__(self, session, parent): Screen.__init__(self, session) InternetRadioVisualization.__init__(self) self["text1"] = Label(_("Internet Radio")) self["text2"] = Label("") self.onLayoutFinish.append(self.startRun) def startRun(self): self.setProperties() self.hideControls() self["text1"].hide() self["text2"].hide() def setText(self, text): self["text2"].setText(text) def setLabelVisibility(self,value): if value: self["text1"].show() self["text2"].show() self.hideControls() else: self["text1"].hide() self["text2"].hide()

94.278912

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6af074d2754f1959922f4345aca7f4b8b10b165a

356

py

Python

evalutils/__init__.py

coendevente/evalutils

eb22da85ab27819a6da1249fe5111c7e36185369

[ "MIT" ]

null

evalutils/__init__.py

coendevente/evalutils

eb22da85ab27819a6da1249fe5111c7e36185369

[ "MIT" ]

null

evalutils/__init__.py

coendevente/evalutils

eb22da85ab27819a6da1249fe5111c7e36185369

[ "MIT" ]

null

from .evalutils import ( ClassificationAlgorithm, ClassificationEvaluation, DetectionAlgorithm, DetectionEvaluation, Evaluation, SegmentationAlgorithm, ) __all__ = [ "ClassificationAlgorithm", "ClassificationEvaluation", "DetectionAlgorithm", "DetectionEvaluation", "Evaluation", "SegmentationAlgorithm", ]

19.777778

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null

1

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null

0

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0aab525284d67792ecdf98ec041e5ccbbaceb15b

24,495

py

Python

tests/test_dhis.py

rileyhazard/smartva-dhis2

04a6326bbffb4050c3af33a66b2c183af33c7069

[ "MIT" ]

3

2018-06-14T03:30:12.000Z

2018-07-23T06:39:20.000Z

tests/test_dhis.py

rileyhazard/smartva-dhis2

04a6326bbffb4050c3af33a66b2c183af33c7069

[ "MIT" ]

17

2018-04-23T12:48:32.000Z

2018-12-10T18:14:09.000Z

tests/test_dhis.py

rileyhazard/smartva-dhis2

04a6326bbffb4050c3af33a66b2c183af33c7069

[ "MIT" ]

6

2018-05-09T03:51:20.000Z

2020-11-10T08:24:53.000Z

import pytest from smartvadhis2.core.dhis import RaiseImportFailure, raise_if_duplicate, Dhis from smartvadhis2.core.exceptions.errors import * from smartvadhis2.core.exceptions.base import DhisApiException def test_import_orgunit_invalid(): response = { "httpStatus": "Conflict", "httpStatusCode": 409, "status": "ERROR", "message": "An error occurred, please check import summary.", "response": { "responseType": "ImportSummaries", "status": "ERROR", "imported": 0, "updated": 0, "deleted": 0, "ignored": 1, "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "importSummaries": [ { "responseType": "ImportSummary", "status": "ERROR", "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "description": "Event.orgUnit does not point to a valid organisation unit: tbd", "importCount": { "imported": 0, "updated": 0, "ignored": 1, "deleted": 0 } } ] } } with pytest.raises(OrgunitNotValidImportError): RaiseImportFailure(response) def test_import_program_invalid(): response = { "httpStatus": "Conflict", "httpStatusCode": 409, "status": "ERROR", "message": "An error occurred, please check import summary.", "response": { "responseType": "ImportSummaries", "status": "ERROR", "imported": 0, "updated": 0, "deleted": 0, "ignored": 1, "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "importSummaries": [ { "responseType": "ImportSummary", "status": "ERROR", "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "description": "Event.program does not point to a valid program: abc", "importCount": { "imported": 0, "updated": 0, "ignored": 1, "deleted": 0 } } ] } } with pytest.raises(ProgramNotValidError): RaiseImportFailure(response) def test_import_success(): response = { "httpStatus": "OK", "httpStatusCode": 200, "status": "OK", "message": "Import was successful.", "response": { "responseType": "ImportSummaries", "status": "SUCCESS", "imported": 2, "updated": 4, "deleted": 0, "ignored": 0, "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "importSummaries": [ { "responseType": "ImportSummary", "status": "SUCCESS", "importCount": { "imported": 2, "updated": 0, "ignored": 0, "deleted": 0 }, "reference": "IgEemKlf33z", "href": "https://play.dhis2.org/2.28/api/events/IgEemKlf33z" }, { "responseType": "ImportSummary", "status": "SUCCESS", "importCount": { "imported": 0, "updated": 2, "ignored": 0, "deleted": 0 }, "reference": "onXW2DQHRGS", "href": "https://play.dhis2.org/2.28/api/events/onXW2DQHRGS" }, { "responseType": "ImportSummary", "status": "SUCCESS", "importCount": { "imported": 0, "updated": 2, "ignored": 0, "deleted": 0 }, "reference": "A7vnB73x5Xw", "href": "https://play.dhis2.org/2.28/api/events/A7vnB73x5Xw" } ] } } import_status = RaiseImportFailure(response) assert import_status.status_code == 200 assert import_status.imported == 2 assert import_status.deleted == 0 assert import_status.updated == 4 assert import_status.ignored == 0 assert import_status.deleted == 0 def test_import_conflict_dataelement_invalid(): response = { "httpStatus": "Conflict", "httpStatusCode": 409, "status": "WARNING", "message": "One more conflicts encountered, please check import summary.", "response": { "responseType": "ImportSummaries", "status": "WARNING", "imported": 2, "updated": 3, "deleted": 0, "ignored": 1, "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "importSummaries": [ { "responseType": "ImportSummary", "status": "SUCCESS", "importCount": { "imported": 2, "updated": 0, "ignored": 0, "deleted": 0 }, "reference": "iG9fBAyM71U", "href": "https://play.dhis2.org/2.28/api/events/iG9fBAyM71U" }, { "responseType": "ImportSummary", "status": "WARNING", "importCount": { "imported": 0, "updated": 1, "ignored": 1, "deleted": 0 }, "conflicts": [ { "object": "dataElement", "value": "sWoqcoByYmE is not a valid data element" } ], "reference": "onXW2DQHRGS", "href": "https://play.dhis2.org/2.28/api/events/onXW2DQHRGS" }, { "responseType": "ImportSummary", "status": "SUCCESS", "importCount": { "imported": 0, "updated": 2, "ignored": 0, "deleted": 0 }, "reference": "A7vnB73x5Xw", "href": "https://play.dhis2.org/2.28/api/events/A7vnB73x5Xw" } ] } } with pytest.raises(GenericImportError): RaiseImportFailure(response) def test_empty_post_throws(): response = { "httpStatus": "OK", "httpStatusCode": 200, "status": "OK", "message": "Import was successful.", "response": { "responseType": "ImportSummaries", "status": "SUCCESS", "imported": 0, "updated": 0, "deleted": 0, "ignored": 0, "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False } } } with pytest.raises(GenericImportError): RaiseImportFailure(response) def test_event_duplicate_found(): sid = "VA_12345678912345" response = { "headers": [ { "name": "event", "column": "event", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "created", "column": "created", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "lastUpdated", "column": "lastUpdated", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "storedBy", "column": "storedBy", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "completedBy", "column": "completedBy", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "completedDate", "column": "completedDate", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "eventDate", "column": "eventDate", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "dueDate", "column": "dueDate", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "orgUnit", "column": "orgUnit", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "orgUnitName", "column": "orgUnitName", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "status", "column": "status", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "longitude", "column": "longitude", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "latitude", "column": "latitude", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "programStage", "column": "programStage", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "program", "column": "program", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "attributeOptionCombo", "column": "attributeOptionCombo", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "deleted", "column": "deleted", "type": "java.lang.String", "hidden": False, "meta": False } ], "rows": [ [ "zLPwmHJVr09", "2018-04-19 07:43:30.068", "2018-04-19 07:43:30.078", "smartvadhis2_v0.0.1", "bao-admin", "2018-04-19 00:00:00.0", "2018-03-26 00:00:00.0", "2018-04-19 07:43:30.068", "MJ0S8In5PIQ", "Gournadi Upazila", "COMPLETED", "", "", "pQ8gaWKD3pi", "HPrJOsYuM1K", "HllvX50cXC0", "False" ] ], "width": 17, "height": 1 } with pytest.raises(DuplicateEventImportError): raise_if_duplicate(response, sid) def test_event_no_duplicate(): sid = "VA_12345678912345" response = { "headers": [ { "name": "event", "column": "event", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "created", "column": "created", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "lastUpdated", "column": "lastUpdated", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "storedBy", "column": "storedBy", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "completedBy", "column": "completedBy", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "completedDate", "column": "completedDate", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "eventDate", "column": "eventDate", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "dueDate", "column": "dueDate", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "orgUnit", "column": "orgUnit", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "orgUnitName", "column": "orgUnitName", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "status", "column": "status", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "longitude", "column": "longitude", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "latitude", "column": "latitude", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "programStage", "column": "programStage", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "program", "column": "program", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "attributeOptionCombo", "column": "attributeOptionCombo", "type": "java.lang.String", "hidden": False, "meta": False }, { "name": "deleted", "column": "deleted", "type": "java.lang.String", "hidden": False, "meta": False } ], "rows": [], "width": 17, "height": 0 } raise_if_duplicate(response, sid) def test_orgunit_not_assigned(): response = { "httpStatus": "Conflict", "httpStatusCode": 409, "status": "ERROR", "message": "An error occurred, please check import summary.", "response": { "responseType": "ImportSummaries", "status": "ERROR", "imported": 0, "updated": 0, "deleted": 0, "ignored": 1, "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "importSummaries": [ { "responseType": "ImportSummary", "status": "ERROR", "importOptions": { "idSchemes": {}, "dryRun": False, "async": False, "importStrategy": "CREATE", "mergeMode": "REPLACE", "reportMode": "FULL", "skipExistingCheck": False, "sharing": False, "skipNotifications": False, "datasetAllowsPeriods": False, "strictPeriods": False, "strictCategoryOptionCombos": False, "strictAttributeOptionCombos": False, "strictOrganisationUnits": False, "requireCategoryOptionCombo": False, "requireAttributeOptionCombo": False }, "description": "Program is not assigned to this organisation unit: MJ0S8In5PIQ", "importCount": { "imported": 0, "updated": 0, "ignored": 1, "deleted": 0 } } ] } } with pytest.raises(OrgUnitNotAssignedError): RaiseImportFailure(response) def test_generic_import_error(): response = { "Unknown response" } with pytest.raises(GenericImportError): RaiseImportFailure(response) def test_get_root_orgunit(): response = { "organisationUnits": [ { "id": "ImspTQPwCqd" } ] } assert 'ImspTQPwCqd' == Dhis._get_root_id(response) def test_get_root_orgunit_multiple(): response = { "organisationUnits": [ { "id": "ImspTQPwCqd" }, { "id": "lc3eMKXaEfw" } ] } with pytest.raises(DhisApiException): Dhis._get_root_id(response) def test_get_root_orgunit_none(): response = { "pager": { "page": 1, "pageCount": 1, "total": 1, "pageSize": 50 }, "organisationUnits": [] } with pytest.raises(DhisApiException): Dhis._get_root_id(response)

32.747326

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0

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null

0

7

7c8fe0d63bbfb4e593b911dbf63d3e421d2ae5cd

7,397

py

Python

tests/regressiontests/utils/termcolors.py

Smarsh/django

ffb738e0f56027e16564a79b709cbf44596c2335

[ "BSD-3-Clause" ]

19

2015-05-01T19:59:03.000Z

2021-12-09T08:03:16.000Z

tests/regressiontests/utils/termcolors.py

aprefontaine/TMScheduler

298a332532b9df1d3f6a80b1334630bc106d3b78

[ "BSD-3-Clause" ]

1

2018-01-03T15:26:49.000Z

tests/regressiontests/utils/termcolors.py

aprefontaine/TMScheduler

298a332532b9df1d3f6a80b1334630bc106d3b78

[ "BSD-3-Clause" ]

30

2015-03-25T19:40:07.000Z

2021-05-28T22:59:26.000Z

from unittest import TestCase from django.utils.termcolors import parse_color_setting, PALETTES, DEFAULT_PALETTE, LIGHT_PALETTE, DARK_PALETTE, NOCOLOR_PALETTE class TermColorTests(TestCase): def test_empty_string(self): self.assertEquals(parse_color_setting(''), PALETTES[DEFAULT_PALETTE]) def test_simple_palette(self): self.assertEquals(parse_color_setting('light'), PALETTES[LIGHT_PALETTE]) self.assertEquals(parse_color_setting('dark'), PALETTES[DARK_PALETTE]) self.assertEquals(parse_color_setting('nocolor'), None) def test_fg(self): self.assertEquals(parse_color_setting('error=green'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) def test_fg_bg(self): self.assertEquals(parse_color_setting('error=green/blue'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'bg':'blue'})) def test_fg_opts(self): self.assertEquals(parse_color_setting('error=green,blink'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'opts': ('blink',)})) self.assertEquals(parse_color_setting('error=green,bold,blink'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'opts': ('blink','bold')})) def test_fg_bg_opts(self): self.assertEquals(parse_color_setting('error=green/blue,blink'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'bg':'blue', 'opts': ('blink',)})) self.assertEquals(parse_color_setting('error=green/blue,bold,blink'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'bg':'blue', 'opts': ('blink','bold')})) def test_override_palette(self): self.assertEquals(parse_color_setting('light;error=green'), dict(PALETTES[LIGHT_PALETTE], ERROR={'fg':'green'})) def test_override_nocolor(self): self.assertEquals(parse_color_setting('nocolor;error=green'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg': 'green'})) def test_reverse_override(self): self.assertEquals(parse_color_setting('error=green;light'), PALETTES[LIGHT_PALETTE]) def test_multiple_roles(self): self.assertEquals(parse_color_setting('error=green;sql_field=blue'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'}, SQL_FIELD={'fg':'blue'})) def test_override_with_multiple_roles(self): self.assertEquals(parse_color_setting('light;error=green;sql_field=blue'), dict(PALETTES[LIGHT_PALETTE], ERROR={'fg':'green'}, SQL_FIELD={'fg':'blue'})) def test_empty_definition(self): self.assertEquals(parse_color_setting(';'), None) self.assertEquals(parse_color_setting('light;'), PALETTES[LIGHT_PALETTE]) self.assertEquals(parse_color_setting(';;;'), None) def test_empty_options(self): self.assertEquals(parse_color_setting('error=green,'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) self.assertEquals(parse_color_setting('error=green,,,'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) self.assertEquals(parse_color_setting('error=green,,blink,,'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'opts': ('blink',)})) def test_bad_palette(self): self.assertEquals(parse_color_setting('unknown'), None) def test_bad_role(self): self.assertEquals(parse_color_setting('unknown='), None) self.assertEquals(parse_color_setting('unknown=green'), None) self.assertEquals(parse_color_setting('unknown=green;sql_field=blue'), dict(PALETTES[NOCOLOR_PALETTE], SQL_FIELD={'fg':'blue'})) def test_bad_color(self): self.assertEquals(parse_color_setting('error='), None) self.assertEquals(parse_color_setting('error=;sql_field=blue'), dict(PALETTES[NOCOLOR_PALETTE], SQL_FIELD={'fg':'blue'})) self.assertEquals(parse_color_setting('error=unknown'), None) self.assertEquals(parse_color_setting('error=unknown;sql_field=blue'), dict(PALETTES[NOCOLOR_PALETTE], SQL_FIELD={'fg':'blue'})) self.assertEquals(parse_color_setting('error=green/unknown'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) self.assertEquals(parse_color_setting('error=green/blue/something'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'bg': 'blue'})) self.assertEquals(parse_color_setting('error=green/blue/something,blink'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'bg': 'blue', 'opts': ('blink',)})) def test_bad_option(self): self.assertEquals(parse_color_setting('error=green,unknown'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) self.assertEquals(parse_color_setting('error=green,unknown,blink'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'opts': ('blink',)})) def test_role_case(self): self.assertEquals(parse_color_setting('ERROR=green'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) self.assertEquals(parse_color_setting('eRrOr=green'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) def test_color_case(self): self.assertEquals(parse_color_setting('error=GREEN'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) self.assertEquals(parse_color_setting('error=GREEN/BLUE'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'bg':'blue'})) self.assertEquals(parse_color_setting('error=gReEn'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green'})) self.assertEquals(parse_color_setting('error=gReEn/bLuE'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'bg':'blue'})) def test_opts_case(self): self.assertEquals(parse_color_setting('error=green,BLINK'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'opts': ('blink',)})) self.assertEquals(parse_color_setting('error=green,bLiNk'), dict(PALETTES[NOCOLOR_PALETTE], ERROR={'fg':'green', 'opts': ('blink',)}))

49.313333

128

0.556442

719

7,397

5.479833

0.069541

0.109137

0.185533

0.277157

0.911675

0.902792

0.839848

0.786041

0.691117

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7,397

149

129

49.644295

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0

null

0

1

0

1

0

null

0

7

7ce8471d3cad31b7187d410f4921260f284256a7

26,948

py

Python

integration/core/test_api.py

amy/catalog-service

31c601fc4c036a4da27fc4f7437d8503a08f415a

[ "Apache-2.0" ]

null

integration/core/test_api.py

amy/catalog-service

31c601fc4c036a4da27fc4f7437d8503a08f415a

[ "Apache-2.0" ]

null

integration/core/test_api.py

amy/catalog-service

31c601fc4c036a4da27fc4f7437d8503a08f415a

[ "Apache-2.0" ]

1

2019-10-16T13:00:41.000Z

import pytest import cattle import requests import json from wait_for import wait_for def headers(environment_id): return { 'Accept': 'application/json', 'x-api-project-id': environment_id } DEFAULT_ENV = 'e1' DEFAULT_HEADERS = headers(DEFAULT_ENV) BASE_URL = 'http://localhost:8088/v1-catalog/' def create_catalog(name, url, branch=None, headers=DEFAULT_HEADERS): schemas_url = 'http://localhost:8088/v1-catalog/schemas' client = cattle.from_env(url=schemas_url, headers=headers) original_catalogs = client.list_catalog() assert len(original_catalogs) > 0 original_templates = client.list_template() assert len(original_templates) > 0 data = { 'name': name, 'url': url, } if branch: data['branch'] = branch api_url = 'http://localhost:8088/v1-catalog/catalogs' response = requests.post(api_url, data=json.dumps(data), headers=headers) assert response.status_code == 200 resp = response.json() assert resp['name'] == name assert resp['url'] == url if branch: assert resp['branch'] == branch api_url = 'http://localhost:8088/v1-catalog/templates?action=refresh' response = requests.post(api_url, headers=headers) assert response.status_code == 204 templates = client.list_template() catalogs = client.list_catalog() assert len(catalogs) == len(original_catalogs) + 1 assert len(templates) > len(original_templates) return resp def create_duplicate_catalog(name, url, branch=None, headers=DEFAULT_HEADERS): schemas_url = 'http://localhost:8088/v1-catalog/schemas' client = cattle.from_env(url=schemas_url, headers=headers) original_catalogs = client.list_catalog() assert len(original_catalogs) > 0 original_templates = client.list_template() assert len(original_templates) > 0 data = { 'name': name, 'url': url, } if branch: data['branch'] = branch api_url = 'http://localhost:8088/v1-catalog/catalogs' response = requests.post(api_url, data=json.dumps(data), headers=headers) assert response.status_code == 422 def delete_catalog(name, headers=DEFAULT_HEADERS): schemas_url = 'http://localhost:8088/v1-catalog/schemas' client = cattle.from_env(url=schemas_url, headers=headers) original_catalogs = client.list_catalog() assert len(original_catalogs) > 0 original_templates = client.list_template() assert len(original_templates) > 0 url = 'http://localhost:8088/v1-catalog/catalogs/' + name response = requests.delete(url, headers=headers) assert response.status_code == 204 templates = client.list_template() catalogs = client.list_catalog() assert len(catalogs) == len(original_catalogs) - 1 assert len(templates) < len(original_templates) @pytest.fixture def client(): url = 'http://localhost:8088/v1-catalog/schemas' catalogs = cattle.from_env(url=url, headers=DEFAULT_HEADERS).list_catalog() wait_for( lambda: len(catalogs) > 0 ) return cattle.from_env(url=url, headers=DEFAULT_HEADERS) def test_catalog_list(client): catalogs = client.list_catalog() assert len(catalogs) == 2 for catalog in catalogs: if catalog.name == 'orig': assert catalog.url == 'https://github.com/rancher/test-catalog' elif catalog.name == 'updated': assert catalog.url == '/tmp/test-catalog' else: assert False def test_get_catalogs(client): url = 'http://localhost:8088/v1-catalog/catalogs' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json()['data'][0] assert resp['name'] == 'orig' assert resp['url'] == 'https://github.com/rancher/test-catalog' assert resp['links']['self'] == 'http://localhost:8088/' + \ 'v1-catalog/catalogs/orig?projectId=' + DEFAULT_ENV def test_get_catalog(client): url = 'http://localhost:8088/v1-catalog/catalogs/orig' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['name'] == 'orig' assert resp['url'] == 'https://github.com/rancher/test-catalog' assert resp['links']['self'] == 'http://localhost:8088/' + \ 'v1-catalog/catalogs/orig?projectId=' + DEFAULT_ENV def test_get_catalog_404(client): url = 'http://localhost:8088/v1-catalog/catalogs/not-real' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 404 def test_catalog_commit(client): latest_commit = '4ec17d4c057be16e01fecb599af16b2b9dda9065' url = 'http://localhost:8088/v1-catalog/catalogs/orig' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['commit'] == latest_commit url = 'http://localhost:8088/v1-catalog/catalogs/updated' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['commit'] != latest_commit def test_create_and_delete_catalog(client): url = 'https://github.com/rancher/community-catalog' create_catalog('created', url) delete_catalog('created') def test_catalog_branch(client): url = 'https://github.com/rancher/test-catalog' create_catalog('branch', url, "test-branch") delete_catalog('branch') def test_catalog_duplicate_env_name(client): url = 'https://github.com/rancher/test-catalog' create_catalog('test', url) create_duplicate_catalog('test', url) delete_catalog('test') def test_catalog_duplicate_global_name(client): # orig is the name of a global catalog that already exists url = 'https://github.com/rancher/test-catalog' create_duplicate_catalog('orig', url) def test_catalog_edit(client): url = 'https://github.com/rancher/community-catalog' create_resp = create_catalog('edit', url) url = 'https://github.com/rancher/rancher-catalog' different_name = 'different_name' data = { 'url': url, 'name': different_name, } api_url = create_resp['links']['self'] response = requests.put(api_url, data=json.dumps(data), headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() response = requests.get(resp['links']['self'], headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['url'] == url assert resp['name'] == different_name delete_catalog(different_name) def test_catalog_different_environment(client): original_catalogs = client.list_catalog() assert len(original_catalogs) > 0 original_templates = client.list_template() assert len(original_templates) > 0 url = 'https://github.com/rancher/community-catalog' create_catalog('env', url, headers=headers('e2')) templates = client.list_template() catalogs = client.list_catalog() assert len(catalogs) == len(original_catalogs) assert len(templates) == len(original_templates) delete_catalog('env', headers=headers('e2')) def test_template_list(client): templates = client.list_template() assert len(templates) > 0 def test_get_template(client): url = 'http://localhost:8088/v1-catalog/templates/orig:k8s' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['catalogId'] == 'orig' assert resp['folderName'] == 'k8s' assert resp['defaultVersion'] == 'v1.3.0-rancher4' assert len(resp['categories']) == 1 assert resp['categories'][0] == 'System' def test_get_template_template_version(client): url = 'http://localhost:8088/v1-catalog/templates' + \ '/orig:k8s-template-version' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['catalogId'] == 'orig' assert resp['folderName'] == 'k8s-template-version' assert resp['defaultVersion'] == 'v1.3.0-rancher4' assert len(resp['categories']) == 1 assert resp['categories'][0] == 'System' def test_get_template_with_version_folders(client): url = 'http://localhost:8088/v1-catalog/templates/orig:version-folders' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['catalogId'] == 'orig' assert resp['folderName'] == 'version-folders' versionLinks = resp['versionLinks'] assert len(versionLinks) == 3 assert 'v0.0.1' in versionLinks assert 'v0.0.1-rancher1.2' in versionLinks assert 'v0.0.3' in versionLinks for version in ('v0.0.1', 'v0.0.1-rancher1.2', 'v0.0.3'): version_id = 'orig:version-folders:' + version assert version_id in versionLinks.values()[0] or \ version_id in versionLinks.values()[1] or \ version_id in versionLinks.values()[2] def test_get_template_404(client): url = 'http://localhost:8088/v1-catalog/templates/orig:not-real' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 404 def test_template_category(client): url = 'http://localhost:8088/v1-catalog/templates/orig:nfs-server' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert len(resp['categories']) == 1 assert resp['categories'][0] == 'Test' def test_template_categories(client): url = 'http://localhost:8088/v1-catalog/templates/orig:categories' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert len(resp['categories']) == 2 assert resp['categories'][0] == 'category1' assert resp['categories'][1] == 'category2' def test_preserve_category_case(client): url = BASE_URL + 'templates/orig:upper-case-categories' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert len(resp['categories']) == 3 assert resp['categories'][0] == 'CATEGORY1' assert resp['categories'][1] == 'CATEGORY2' assert resp['categories'][2] == 'CATEGORY3' def test_category_filter(client): base_url = 'http://localhost:8088/v1-catalog/templates?category=' for category in ('category1', 'category2', 'category3', 'System'): response = requests.get(base_url + category, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['data'] is not None for template in resp['data']: categories = [c.lower() for c in template['categories']] assert category.lower() in categories def test_category_ne_filter(client): base_url = 'http://localhost:8088/v1-catalog/templates?category_ne=' for category in ('category1', 'category2', 'System'): response = requests.get(base_url + category, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['data'] is not None for template in resp['data']: categories = template['categories'] if categories: assert category not in template['categories'] def test_template_without_categories(client): base_url = 'http://localhost:8088/v1-catalog/templates' for category in ('category1', 'category2', 'System'): url = base_url + '?catalog_ne=' + category response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() templates = resp['data'] no_categories_template_found = False for template in templates: if template['folderName'] == 'no-categories': no_categories_template_found = True break assert no_categories_template_found def test_machine_template(client): url = 'http://localhost:8088/v1-catalog/templates/orig:machine*vultr' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['templateBase'] == 'machine' url = 'http://localhost:8088/v1-catalog/templates/orig:machine*vultr:0' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert len(resp['files']) == 2 assert 'rancher-compose.yml' in resp['files'] assert 'url' in resp['files'] def test_template_labels(client): url = 'http://localhost:8088/v1-catalog/templates/orig:labels' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['labels'] is not None assert resp['labels']['key1'] == 'value1' assert resp['labels']['key2'] == 'value2' def test_template_version_links(client): url = 'http://localhost:8088/v1-catalog/templates/orig:many-versions' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert len(resp['versionLinks']) == 14 url = 'http://localhost:8088/v1-catalog/templates/orig:many-versions' + \ '?rancherVersion=v1.0.1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert len(resp['versionLinks']) == 9 def test_rancher_version_filter(client): templates = client.list_template() assert len(templates) > 0 min_rancher_template_found = False max_rancher_template_found = False for template in templates: if template.folderName == 'min-rancher-version': min_rancher_template_found = True if template.folderName == 'max-rancher-version': max_rancher_template_found = True assert min_rancher_template_found assert max_rancher_template_found url = 'http://localhost:8088/v1-catalog/templates?rancherVersion=v1.2.0' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['data'] is not None for template in resp['data']: assert template['folderName'] != 'min-rancher-version' url = 'http://localhost:8088/v1-catalog/templates?rancherVersion=v1.5.0' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['data'] is not None for template in resp['data']: assert template['folderName'] != 'max-rancher-version' def test_upgrade_links(client): url = 'http://localhost:8088/v1-catalog/templates/' + \ 'orig:test-upgrade-links:1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() upgradeLinks = resp['upgradeVersionLinks'] assert upgradeLinks is not None assert len(upgradeLinks) == 10 url = 'http://localhost:8088/v1-catalog/templates/orig:many-versions:2' + \ '?rancherVersion=v1.0.1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() upgradeLinks = resp['upgradeVersionLinks'] assert upgradeLinks is not None assert len(upgradeLinks) == 7 def test_template_icon(client): url = 'http://localhost:8088/v1-catalog/templates/orig:nfs-server' + \ '?image&projectId=%s' % (DEFAULT_ENV) response = requests.get(url, headers=headers('')) assert response.status_code == 200 assert len(response.content) == 1139 def test_get_template_version_by_revision(client): url = 'http://localhost:8088/v1-catalog/templates/orig:k8s:0' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == 'v0.1.0-rancher1' url = 'http://localhost:8088/v1-catalog/templates/orig:k8s:1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == 'v1.2.4-rancher6' def test_get_template_version_by_revision_template_version(client): url = 'http://localhost:8088/v1-catalog/templates' + \ '/orig:k8s-template-version:0' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == 'v0.1.0-rancher1' url = 'http://localhost:8088/v1-catalog/templates' + \ '/orig:k8s-template-version:1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == 'v1.2.4-rancher6' def test_get_template_version_by_version(client): url = BASE_URL+'templates/orig:version-folders:v0.0.1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == 'v0.0.1' url = BASE_URL+'templates/orig:version-folders:v0.0.1-rancher1.2' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == 'v0.0.1-rancher1.2' url = BASE_URL+'templates/orig:version-folders:v0.0.3' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == 'v0.0.3' url = BASE_URL+'templates/orig:version-folders:v0.0.2' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 404 def test_get_template_version_404(client): url = 'http://localhost:8088/v1-catalog/templates/orig:k8s:1000' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 404 def test_get_template_version_404_template_version(client): url = 'http://localhost:8088/v1-catalog/templates' + \ '/orig:k8s-template-version:1000' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 404 def test_get_template_version_labels(client): url = 'http://localhost:8088/v1-catalog/templates/orig:version-labels:0' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['labels'] is not None assert resp['labels']['key1'] == 'value1' assert resp['labels']['key2'] == 'value2' def test_template_version_questions(client): url = 'http://localhost:8088/v1-catalog/templates/' + \ 'orig:all-question-types:1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() questions = resp['questions'] assert questions is not None assert len(questions) == 11 assert questions[0]['variable'] == 'TEST_STRING' assert questions[0]['label'] == 'String' assert not questions[0]['required'] assert questions[0]['default'] == 'hello' assert questions[0]['type'] == 'string' assert questions[1]['variable'] == 'TEST_MULTILINE' assert questions[1]['label'] == 'Multi-Line' assert not questions[1]['required'] assert questions[1]['default'] == 'Hello\nWorld\n' assert questions[1]['type'] == 'multiline' assert questions[2]['variable'] == 'TEST_PASSWORD' assert questions[2]['label'] == 'Password' assert not questions[2]['required'] assert questions[2]['default'] == "not-so-secret stuff" assert questions[2]['type'] == 'password' assert questions[3]['variable'] == 'TEST_ENUM' assert questions[3]['label'] == 'Enum' assert not questions[3]['required'] assert questions[3]['options'] == ['purple', 'monkey', 'dishwasher'] assert questions[3]['default'] == 'monkey' assert questions[3]['type'] == 'enum' assert questions[4]['variable'] == 'TEST_DATE' assert questions[4]['label'] == 'Date' assert not questions[4]['required'] assert questions[4]['default'] == '2015-07-25T19:55:00Z' assert questions[4]['type'] == 'date' assert questions[5]['variable'] == 'TEST_INT' assert questions[5]['label'] == 'Integer' assert not questions[5]['required'] assert questions[5]['default'] == '42' assert questions[5]['type'] == 'int' assert questions[6]['variable'] == 'TEST_FLOAT' assert questions[6]['label'] == 'Float' assert not questions[6]['required'] assert questions[6]['default'] == '4.2' assert questions[6]['type'] == 'float' assert questions[7]['variable'] == 'TEST_BOOLEAN' assert questions[7]['label'] == 'Boolean' assert not questions[7]['required'] assert questions[7]['default'] == 'true' assert questions[7]['type'] == 'boolean' assert questions[8]['variable'] == 'TEST_SERVICE' assert questions[8]['label'] == 'Service' assert not questions[8]['required'] assert questions[8]['default'] == 'kopf' assert questions[8]['type'] == 'service' assert questions[9]['variable'] == 'TEST_CERTIFICATE' assert questions[9]['label'] == 'Certificate' assert not questions[9]['required'] assert questions[9]['default'] == 'rancher.rocks' assert questions[9]['type'] == 'certificate' assert questions[10]['variable'] == 'TEST_UNKNOWN' assert questions[10]['label'] == 'Unknown' assert not questions[10]['required'] assert questions[10]['default'] == 'wha?' assert questions[10]['type'] == 'unknown' def test_template_version_questions_template_version(client): url = 'http://localhost:8088/v1-catalog/templates/' + \ 'orig:all-question-types-template-version:1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() questions = resp['questions'] assert questions is not None assert len(questions) == 11 assert questions[0]['variable'] == 'TEST_STRING' assert questions[0]['label'] == 'String' assert not questions[0]['required'] assert questions[0]['default'] == 'hello' assert questions[0]['type'] == 'string' assert questions[1]['variable'] == 'TEST_MULTILINE' assert questions[1]['label'] == 'Multi-Line' assert not questions[1]['required'] assert questions[1]['default'] == 'Hello\nWorld\n' assert questions[1]['type'] == 'multiline' assert questions[2]['variable'] == 'TEST_PASSWORD' assert questions[2]['label'] == 'Password' assert not questions[2]['required'] assert questions[2]['default'] == "not-so-secret stuff" assert questions[2]['type'] == 'password' assert questions[3]['variable'] == 'TEST_ENUM' assert questions[3]['label'] == 'Enum' assert not questions[3]['required'] assert questions[3]['options'] == ['purple', 'monkey', 'dishwasher'] assert questions[3]['default'] == 'monkey' assert questions[3]['type'] == 'enum' assert questions[4]['variable'] == 'TEST_DATE' assert questions[4]['label'] == 'Date' assert not questions[4]['required'] assert questions[4]['default'] == '2015-07-25T19:55:00Z' assert questions[4]['type'] == 'date' assert questions[5]['variable'] == 'TEST_INT' assert questions[5]['label'] == 'Integer' assert not questions[5]['required'] assert questions[5]['default'] == '42' assert questions[5]['type'] == 'int' assert questions[6]['variable'] == 'TEST_FLOAT' assert questions[6]['label'] == 'Float' assert not questions[6]['required'] assert questions[6]['default'] == '4.2' assert questions[6]['type'] == 'float' assert questions[7]['variable'] == 'TEST_BOOLEAN' assert questions[7]['label'] == 'Boolean' assert not questions[7]['required'] assert questions[7]['default'] == 'true' assert questions[7]['type'] == 'boolean' assert questions[8]['variable'] == 'TEST_SERVICE' assert questions[8]['label'] == 'Service' assert not questions[8]['required'] assert questions[8]['default'] == 'kopf' assert questions[8]['type'] == 'service' assert questions[9]['variable'] == 'TEST_CERTIFICATE' assert questions[9]['label'] == 'Certificate' assert not questions[9]['required'] assert questions[9]['default'] == 'rancher.rocks' assert questions[9]['type'] == 'certificate' assert questions[10]['variable'] == 'TEST_UNKNOWN' assert questions[10]['label'] == 'Unknown' assert not questions[10]['required'] assert questions[10]['default'] == 'wha?' assert questions[10]['type'] == 'unknown' def test_refresh(client): url = 'http://localhost:8088/v1-catalog/templates/updated:many-versions:14' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['version'] == '1.0.14' def test_refresh_no_changes(client): original_catalogs = client.list_catalog() assert len(original_catalogs) > 0 original_templates = client.list_template() assert len(original_templates) > 0 url = 'http://localhost:8088/v1-catalog/templates?action=refresh' response = requests.post(url, headers=DEFAULT_HEADERS) assert response.status_code == 204 catalogs = client.list_catalog() templates = client.list_template() assert len(catalogs) == len(original_catalogs) assert len(templates) == len(original_templates) def test_v2_syntax(client): for revision in [0, 1, 2, 3]: url = 'http://localhost:8088/v1-catalog/templates/orig:v2:' + \ str(revision) response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 def test_alternative_config_fields_1(client): url = 'http://localhost:8088/v1-catalog/templates' + \ '/orig:alternative-config-fields-1' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['defaultVersion'] == '3.0.0' assert resp['links']['project'] == 'www.test.com' def test_alternative_config_fields_2(client): url = 'http://localhost:8088/v1-catalog/templates' + \ '/orig:alternative-config-fields-2' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['defaultVersion'] == '3.0.0' assert resp['links']['project'] == 'www.test.com' def test_alternative_config_fields_3(client): url = 'http://localhost:8088/v1-catalog/templates' + \ '/orig:alternative-config-fields-3' response = requests.get(url, headers=DEFAULT_HEADERS) assert response.status_code == 200 resp = response.json() assert resp['defaultVersion'] == '3.0.0'

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6b07290d6c051a24df18267c0fd4bdaee1b0c2e2

16,109

py

Python

tests/benchmarks/pybench/Lookups.py

Mortal/Nuitka

5150eeff7ff845ed4993c773449cd81b7f127c6b

[ "Apache-2.0" ]

null

tests/benchmarks/pybench/Lookups.py

Mortal/Nuitka

5150eeff7ff845ed4993c773449cd81b7f127c6b

[ "Apache-2.0" ]

null

tests/benchmarks/pybench/Lookups.py

Mortal/Nuitka

5150eeff7ff845ed4993c773449cd81b7f127c6b

[ "Apache-2.0" ]

1

2018-12-16T23:51:18.000Z

# Copyright 2018, Kay Hayen, mailto:kay.hayen@gmail.com # # Python test originally created or extracted from other peoples work. The # parts from me are licensed as below. It is at least Free Software where # it's copied from other people. In these cases, that will normally be # indicated. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from pybench import Test class SpecialClassAttribute(Test): version = 2.0 operations = 5*(12 + 12) rounds = 100000 def test(self): class c: pass for i in xrange(self.rounds): c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 c.__a = 2 c.__b = 3 c.__c = 4 x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c x = c.__a x = c.__b x = c.__c def calibrate(self): class c: pass for i in xrange(self.rounds): pass class NormalClassAttribute(Test): version = 2.0 operations = 5*(12 + 12) rounds = 100000 def test(self): class c: pass for i in xrange(self.rounds): c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 c.a = 2 c.b = 3 c.c = 4 x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c x = c.a x = c.b x = c.c def calibrate(self): class c: pass for i in xrange(self.rounds): pass class SpecialInstanceAttribute(Test): version = 2.0 operations = 5*(12 + 12) rounds = 100000 def test(self): class c: pass o = c() for i in xrange(self.rounds): o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 o.__a__ = 2 o.__b__ = 3 o.__c__ = 4 x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ x = o.__a__ x = o.__b__ x = o.__c__ def calibrate(self): class c: pass o = c() for i in xrange(self.rounds): pass class NormalInstanceAttribute(Test): version = 2.0 operations = 5*(12 + 12) rounds = 100000 def test(self): class c: pass o = c() for i in xrange(self.rounds): o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 o.a = 2 o.b = 3 o.c = 4 x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c x = o.a x = o.b x = o.c def calibrate(self): class c: pass o = c() for i in xrange(self.rounds): pass class BuiltinMethodLookup(Test): version = 2.0 operations = 5*(3*5 + 3*5) rounds = 70000 def test(self): l = [] d = {} for i in xrange(self.rounds): l.append l.append l.append l.append l.append l.insert l.insert l.insert l.insert l.insert l.sort l.sort l.sort l.sort l.sort d.has_key d.has_key d.has_key d.has_key d.has_key d.items d.items d.items d.items d.items d.get d.get d.get d.get d.get l.append l.append l.append l.append l.append l.insert l.insert l.insert l.insert l.insert l.sort l.sort l.sort l.sort l.sort d.has_key d.has_key d.has_key d.has_key d.has_key d.items d.items d.items d.items d.items d.get d.get d.get d.get d.get l.append l.append l.append l.append l.append l.insert l.insert l.insert l.insert l.insert l.sort l.sort l.sort l.sort l.sort d.has_key d.has_key d.has_key d.has_key d.has_key d.items d.items d.items d.items d.items d.get d.get d.get d.get d.get l.append l.append l.append l.append l.append l.insert l.insert l.insert l.insert l.insert l.sort l.sort l.sort l.sort l.sort d.has_key d.has_key d.has_key d.has_key d.has_key d.items d.items d.items d.items d.items d.get d.get d.get d.get d.get l.append l.append l.append l.append l.append l.insert l.insert l.insert l.insert l.insert l.sort l.sort l.sort l.sort l.sort d.has_key d.has_key d.has_key d.has_key d.has_key d.items d.items d.items d.items d.items d.get d.get d.get d.get d.get def calibrate(self): l = [] d = {} for i in xrange(self.rounds): pass

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ext/ANTsPyNet/antspynet/architectures/create_deep_back_projection_network_model.py

tsmonteiro/fmri_proc

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ext/ANTsPyNet/antspynet/architectures/create_deep_back_projection_network_model.py

tsmonteiro/fmri_proc

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ext/ANTsPyNet/antspynet/architectures/create_deep_back_projection_network_model.py

tsmonteiro/fmri_proc

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from keras.models import Model from keras.layers import (Input, Add, Subtract, PReLU, Concatenate, Conv2D, Conv2DTranspose, Conv3D, Conv3DTranspose) def create_deep_back_projection_network_model_2d(input_image_size, number_of_outputs=1, number_of_base_filters=64, number_of_feature_filters=256, number_of_back_projection_stages=7, convolution_kernel_size=(12, 12), strides=(8, 8), last_convolution=(3, 3), number_of_loss_functions=1 ): """ 2-D implementation of the deep back-projection network. Creates a keras model of the deep back-project network for image super resolution. More information is provided at the authors' website: https://www.toyota-ti.ac.jp/Lab/Denshi/iim/members/muhammad.haris/projects/DBPN.html with the paper available here: https://arxiv.org/abs/1803.02735 This particular implementation was influenced by the following keras (python) implementation: https://github.com/rajatkb/DBPN-Keras with help from the original author's Caffe and Pytorch implementations: https://github.com/alterzero/DBPN-caffe https://github.com/alterzero/DBPN-Pytorch Arguments --------- input_image_size : tuple of length 3 Used for specifying the input tensor shape. The shape (or dimension) of that tensor is the image dimensions followed by the number of channels (e.g., red, green, and blue). number_of_outputs : integer Number of outputs (e.g., 3 for RGB images). number_of_feature_filters : integer Number of feature filters. number_of_base_filters : integer Number of base filters. number_of_back_projection_stages : integer Number of up-down-projection stages. This number includes the final up block. convolution_kernel_size : tuple of length 2 Kernel size for certain convolutional layers. The strides are dependent on the scale factor discussed in original paper. Factors used in the original implementation are as follows: 2x --> convolution_kernel_size=(6, 6), 4x --> convolution_kernel_size=(8, 8), 8x --> convolution_kernel_size=(12, 12). We default to 8x parameters. strides : tuple of length 2 Strides for certain convolutional layers. This and the convolution_kernel_size are dependent on the scale factor discussed in original paper. Factors used in the original implementation are as follows: 2x --> strides = (2, 2), 4x --> strides = (4, 4), 8x --> strides = (8, 8). We default to 8x parameters. last_convolution: tuple of length 2 The kernel size for the last convolutional layer. number_of_loss_functions : integer The number of data targets, e.g. 2 for 2 targets Returns ------- Keras model A 2-D Keras model defining the network. Example ------- >>> model = create_deep_back_projection_network_model_2d((128, 128, 1)) >>> model.summary() """ def up_block_2d(L, number_of_filters=64, kernel_size=(12, 12), strides=(8, 8), include_dense_convolution_layer=True): if include_dense_convolution_layer == True: L = Conv2D(filters = number_of_filters, use_bias=True, kernel_size=(1, 1), strides=(1, 1), padding='same')(L) L = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(L) # Scale up H0 = Conv2DTranspose(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(L) H0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(H0) # Scale down L0 = Conv2D(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(H0) L0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(L0) # Residual E = Subtract()([L0, L]) # Scale residual up H1 = Conv2DTranspose(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(E) H1 = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(H1) # Output feature map up_block = Add()([H0, H1]) return(up_block) def down_block_2d(H, number_of_filters=64, kernel_size=(12, 12), strides=(8, 8), include_dense_convolution_layer=True): if include_dense_convolution_layer == True: H = Conv2D(filters = number_of_filters, use_bias=True, kernel_size=(1, 1), strides=(1, 1), padding='same')(H) H = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(H) # Scale down L0 = Conv2D(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(H) L0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(L0) # Scale up H0 = Conv2DTranspose(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(L0) H0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(H0) # Residual E = Subtract()([H0, H]) # Scale residual down L1 = Conv2D(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(E) L1 = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(L1) # Output feature map down_block = Add()([L0, L1]) return(down_block) inputs = Input(shape=input_image_size) # Initial feature extraction model = Conv2D(filters=number_of_feature_filters, kernel_size=(3, 3), strides=(1, 1), padding='same', kernel_initializer='glorot_uniform')(inputs) model = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(model) # Feature smashing model = Conv2D(filters=number_of_base_filters, kernel_size=(1, 1), strides=(1, 1), padding='same', kernel_initializer='glorot_uniform')(model) model = PReLU(alpha_initializer='zero', shared_axes=[1, 2])(model) # Back projection up_projection_blocks = [] down_projection_blocks = [] model = up_block_2d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides) up_projection_blocks.append(model) for i in range(number_of_back_projection_stages): if i == 0: model = down_block_2d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides) down_projection_blocks.append(model) model = up_block_2d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides) up_projection_blocks.append(model) model = Concatenate()(up_projection_blocks) else: model = down_block_2d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides, include_dense_convolution_layer=True) down_projection_blocks.append(model) model = Concatenate()(down_projection_blocks) model = up_block_2d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides, include_dense_convolution_layer=True) up_projection_blocks.append(model) model = Concatenate()(up_projection_blocks) # Final convolution layer outputs = Conv2D(filters=number_of_outputs, kernel_size=last_convolution, strides=(1, 1), padding = 'same', kernel_initializer = "glorot_uniform")(model) if number_of_loss_functions == 1: deep_back_projection_network_model = Model(inputs=inputs, outputs=outputs) else: outputList=[] for k in range(number_of_loss_functions): outputList.append(outputs) deep_back_projection_network_model = Model(inputs=inputs, outputs=outputList) return(deep_back_projection_network_model) def create_deep_back_projection_network_model_3d(input_image_size, number_of_outputs=1, number_of_base_filters=64, number_of_feature_filters=256, number_of_back_projection_stages=7, convolution_kernel_size=(12, 12, 12), strides=(8, 8, 8), last_convolution=(3, 3, 3), number_of_loss_functions=1 ): """ 3-D implementation of the deep back-projection network. Creates a keras model of the deep back-project network for image super resolution. More information is provided at the authors' website: https://www.toyota-ti.ac.jp/Lab/Denshi/iim/members/muhammad.haris/projects/DBPN.html with the paper available here: https://arxiv.org/abs/1803.02735 This particular implementation was influenced by the following keras (python) implementation: https://github.com/rajatkb/DBPN-Keras with help from the original author's Caffe and Pytorch implementations: https://github.com/alterzero/DBPN-caffe https://github.com/alterzero/DBPN-Pytorch Arguments --------- input_image_size : tuple of length 4 Used for specifying the input tensor shape. The shape (or dimension) of that tensor is the image dimensions followed by the number of channels (e.g., red, green, and blue). number_of_outputs : integer Number of outputs (e.g., 3 for RGB images). number_of_feature_filters : integer Number of feature filters. number_of_base_filters : integer Number of base filters. number_of_back_projection_stages : integer Number of up-down-projection stages. This number includes the final up block. convolution_kernel_size : tuple of length 3 Kernel size for certain convolutional layers. The strides are dependent on the scale factor discussed in original paper. Factors used in the original implementation are as follows: 2x --> convolution_kernel_size=(6, 6, 6), 4x --> convolution_kernel_size=(8, 8, 8), 8x --> convolution_kernel_size=(12, 12, 12). We default to 8x parameters. strides : tuple of length 3 Strides for certain convolutional layers. This and the convolution_kernel_size are dependent on the scale factor discussed in original paper. Factors used in the original implementation are as follows: 2x --> strides = (2, 2, 2), 4x --> strides = (4, 4, 4), 8x --> strides = (8, 8, 8). We default to 8x parameters. last_convolution: tuple of length 3 The kernel size for the last convolutional layer. number_of_loss_functions : integer The number of data targets, e.g. 2 for 2 targets Returns ------- Keras model A 3-D Keras model defining the network. Example ------- >>> model = create_deep_back_projection_network_model_3d((128, 128, 128, 1)) >>> model.summary() """ def up_block_3d(L, number_of_filters=64, kernel_size=(12, 12, 12), strides=(8, 8, 8), include_dense_convolution_layer=True): if include_dense_convolution_layer == True: L = Conv3D(filters = number_of_filters, use_bias=True, kernel_size=(1, 1, 1), strides=(1, 1, 1), padding='same')(L) L = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(L) # Scale up H0 = Conv3DTranspose(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(L) H0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(H0) # Scale down L0 = Conv3D(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(H0) L0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(L0) # Residual E = Subtract()([L0, L]) # Scale residual up H1 = Conv3DTranspose(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(E) H1 = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(H1) # Output feature map up_block = Add()([H0, H1]) return(up_block) def down_block_3d(H, number_of_filters=64, kernel_size=(12, 12, 12), strides=(8, 8, 8), include_dense_convolution_layer=True): if include_dense_convolution_layer == True: H = Conv3D(filters = number_of_filters, use_bias=True, kernel_size=(1, 1, 1), strides=(1, 1, 1), padding='same')(H) H = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(H) # Scale down L0 = Conv3D(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(H) L0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(L0) # Scale up H0 = Conv3DTranspose(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(L0) H0 = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(H0) # Residual E = Subtract()([H0, H]) # Scale residual down L1 = Conv3D(filters=number_of_filters, kernel_size=kernel_size, strides=strides, kernel_initializer='glorot_uniform', padding='same')(E) L1 = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(L1) # Output feature map down_block = Add()([L0, L1]) return(down_block) inputs = Input(shape=input_image_size) # Initial feature extraction model = Conv3D(filters=number_of_feature_filters, kernel_size=(3, 3, 3), strides=(1, 1, 1), padding='same', kernel_initializer='glorot_uniform')(inputs) model = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(model) # Feature smashing model = Conv3D(filters=number_of_base_filters, kernel_size=(1, 1, 1), strides=(1, 1, 1), padding='same', kernel_initializer='glorot_uniform')(model) model = PReLU(alpha_initializer='zero', shared_axes=[1, 2, 3])(model) # Back projection up_projection_blocks = [] down_projection_blocks = [] model = up_block_3d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides) up_projection_blocks.append(model) for i in range(number_of_back_projection_stages): if i == 0: model = down_block_3d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides) down_projection_blocks.append(model) model = up_block_3d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides) up_projection_blocks.append(model) model = Concatenate()(up_projection_blocks) else: model = down_block_3d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides, include_dense_convolution_layer=True) down_projection_blocks.append(model) model = Concatenate()(down_projection_blocks) model = up_block_3d(model, number_of_filters=number_of_base_filters, kernel_size=convolution_kernel_size, strides=strides, include_dense_convolution_layer=True) up_projection_blocks.append(model) model = Concatenate()(up_projection_blocks) # Final convolution layer outputs = Conv3D(filters=number_of_outputs, kernel_size=last_convolution, strides=(1, 1, 1), padding = 'same', kernel_initializer = "glorot_uniform")(model) if number_of_loss_functions == 1: deep_back_projection_network_model = Model(inputs=inputs, outputs=outputs) else: outputList=[] for k in range(number_of_loss_functions): outputList.append(outputs) deep_back_projection_network_model = Model(inputs=inputs, outputs=outputList) return(deep_back_projection_network_model)

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