xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

54689a8f70204ed3ce3be420eefa51d103851d6f

21,932

py

Python

pynab/openapi/api/payee_locations_api.py

idwagner/pynab

26e0f2d2adc86374ff5caf5a614778fafa1c19d6

[ "Apache-2.0" ]

null

pynab/openapi/api/payee_locations_api.py

idwagner/pynab

26e0f2d2adc86374ff5caf5a614778fafa1c19d6

[ "Apache-2.0" ]

null

pynab/openapi/api/payee_locations_api.py

idwagner/pynab

26e0f2d2adc86374ff5caf5a614778fafa1c19d6

[ "Apache-2.0" ]

1

2020-11-05T22:28:13.000Z

# coding: utf-8 """ YNAB API Endpoints Our API uses a REST based design, leverages the JSON data format, and relies upon HTTPS for transport. We respond with meaningful HTTP response codes and if an error occurs, we include error details in the response body. API Documentation is at https://api.youneedabudget.com # noqa: E501 The version of the OpenAPI document: 1.0.0 Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from pynab.openapi.api_client import ApiClient from pynab.openapi.exceptions import ( # noqa: F401 ApiTypeError, ApiValueError ) class PayeeLocationsApi(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 def get_payee_location_by_id(self, budget_id, payee_location_id, **kwargs): # noqa: E501 """Single payee location # noqa: E501 Returns a single payee location # 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_payee_location_by_id(budget_id, payee_location_id, async_req=True) >>> result = thread.get() :param budget_id: The id of the budget. \"last-used\" can be used to specify the last used budget and \"default\" can be used if default budget selection is enabled (see: https://api.youneedabudget.com/#oauth-default-budget). (required) :type budget_id: str :param payee_location_id: id of payee location (required) :type payee_location_id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: 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. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: PayeeLocationResponse """ kwargs['_return_http_data_only'] = True return self.get_payee_location_by_id_with_http_info(budget_id, payee_location_id, **kwargs) # noqa: E501 def get_payee_location_by_id_with_http_info(self, budget_id, payee_location_id, **kwargs): # noqa: E501 """Single payee location # noqa: E501 Returns a single payee location # 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_payee_location_by_id_with_http_info(budget_id, payee_location_id, async_req=True) >>> result = thread.get() :param budget_id: The id of the budget. \"last-used\" can be used to specify the last used budget and \"default\" can be used if default budget selection is enabled (see: https://api.youneedabudget.com/#oauth-default-budget). (required) :type budget_id: str :param payee_location_id: id of payee location (required) :type payee_location_id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: 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. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(PayeeLocationResponse, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'budget_id', 'payee_location_id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_payee_location_by_id" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'budget_id' is set if self.api_client.client_side_validation and ('budget_id' not in local_var_params or # noqa: E501 local_var_params['budget_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `budget_id` when calling `get_payee_location_by_id`") # noqa: E501 # verify the required parameter 'payee_location_id' is set if self.api_client.client_side_validation and ('payee_location_id' not in local_var_params or # noqa: E501 local_var_params['payee_location_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `payee_location_id` when calling `get_payee_location_by_id`") # noqa: E501 collection_formats = {} path_params = {} if 'budget_id' in local_var_params: path_params['budget_id'] = local_var_params['budget_id'] # noqa: E501 if 'payee_location_id' in local_var_params: path_params['payee_location_id'] = local_var_params['payee_location_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['bearer'] # noqa: E501 response_types_map = { 200: "PayeeLocationResponse", 404: "ErrorResponse", } return self.api_client.call_api( '/budgets/{budget_id}/payee_locations/{payee_location_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def get_payee_locations(self, budget_id, **kwargs): # noqa: E501 """List payee locations # noqa: E501 Returns all payee locations # 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_payee_locations(budget_id, async_req=True) >>> result = thread.get() :param budget_id: The id of the budget. \"last-used\" can be used to specify the last used budget and \"default\" can be used if default budget selection is enabled (see: https://api.youneedabudget.com/#oauth-default-budget). (required) :type budget_id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: 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. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: PayeeLocationsResponse """ kwargs['_return_http_data_only'] = True return self.get_payee_locations_with_http_info(budget_id, **kwargs) # noqa: E501 def get_payee_locations_with_http_info(self, budget_id, **kwargs): # noqa: E501 """List payee locations # noqa: E501 Returns all payee locations # 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_payee_locations_with_http_info(budget_id, async_req=True) >>> result = thread.get() :param budget_id: The id of the budget. \"last-used\" can be used to specify the last used budget and \"default\" can be used if default budget selection is enabled (see: https://api.youneedabudget.com/#oauth-default-budget). (required) :type budget_id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: 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. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(PayeeLocationsResponse, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'budget_id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_payee_locations" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'budget_id' is set if self.api_client.client_side_validation and ('budget_id' not in local_var_params or # noqa: E501 local_var_params['budget_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `budget_id` when calling `get_payee_locations`") # noqa: E501 collection_formats = {} path_params = {} if 'budget_id' in local_var_params: path_params['budget_id'] = local_var_params['budget_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['bearer'] # noqa: E501 response_types_map = { 200: "PayeeLocationsResponse", 404: "ErrorResponse", } return self.api_client.call_api( '/budgets/{budget_id}/payee_locations', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def get_payee_locations_by_payee(self, budget_id, payee_id, **kwargs): # noqa: E501 """List locations for a payee # noqa: E501 Returns all payee locations for a specified payee # 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_payee_locations_by_payee(budget_id, payee_id, async_req=True) >>> result = thread.get() :param budget_id: The id of the budget. \"last-used\" can be used to specify the last used budget and \"default\" can be used if default budget selection is enabled (see: https://api.youneedabudget.com/#oauth-default-budget). (required) :type budget_id: str :param payee_id: id of payee (required) :type payee_id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: 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. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: PayeeLocationsResponse """ kwargs['_return_http_data_only'] = True return self.get_payee_locations_by_payee_with_http_info(budget_id, payee_id, **kwargs) # noqa: E501 def get_payee_locations_by_payee_with_http_info(self, budget_id, payee_id, **kwargs): # noqa: E501 """List locations for a payee # noqa: E501 Returns all payee locations for a specified payee # 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_payee_locations_by_payee_with_http_info(budget_id, payee_id, async_req=True) >>> result = thread.get() :param budget_id: The id of the budget. \"last-used\" can be used to specify the last used budget and \"default\" can be used if default budget selection is enabled (see: https://api.youneedabudget.com/#oauth-default-budget). (required) :type budget_id: str :param payee_id: id of payee (required) :type payee_id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: 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. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(PayeeLocationsResponse, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'budget_id', 'payee_id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_payee_locations_by_payee" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'budget_id' is set if self.api_client.client_side_validation and ('budget_id' not in local_var_params or # noqa: E501 local_var_params['budget_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `budget_id` when calling `get_payee_locations_by_payee`") # noqa: E501 # verify the required parameter 'payee_id' is set if self.api_client.client_side_validation and ('payee_id' not in local_var_params or # noqa: E501 local_var_params['payee_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `payee_id` when calling `get_payee_locations_by_payee`") # noqa: E501 collection_formats = {} path_params = {} if 'budget_id' in local_var_params: path_params['budget_id'] = local_var_params['budget_id'] # noqa: E501 if 'payee_id' in local_var_params: path_params['payee_id'] = local_var_params['payee_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['bearer'] # noqa: E501 response_types_map = { 200: "PayeeLocationsResponse", 404: "ErrorResponse", } return self.api_client.call_api( '/budgets/{budget_id}/payees/{payee_id}/payee_locations', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth'))

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null

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548390e9bec27ab9cd5d973da63a866ca6137155

4,463

py

Python

bench/rand.py

pskopnik/htc-cache-simulator

ee502db3f1c2b99ffe05ee609a18069b583798da

[ "MIT" ]

1

2020-12-15T16:09:31.000Z

bench/rand.py

pskopnik/htc-cache-system-simulator

ee502db3f1c2b99ffe05ee609a18069b583798da

[ "MIT" ]

null

bench/rand.py

pskopnik/htc-cache-system-simulator

ee502db3f1c2b99ffe05ee609a18069b583798da

[ "MIT" ]

null

import itertools import timeit import random from .utils import StringSource from typing import Callable, Deque, List, Set, Tuple """Benchmark for data structures + operations for the RAND cache eviction algorithm. The operations performed for each replacement are: 1. Choose a random file from the list (algorithm state) and remove it (also evict from storage). 2. Append the file to be placed to the list (algorithm state). """ base_length = 10000 def time_list_choice() -> Tuple[int, float]: col: List[str] = [] s = StringSource() col.extend(s.take(base_length)) def do() -> None: el = random.choice(col) col.remove(el) col.append(next(s)) timer = timeit.Timer(do) return timer.autorange() def time_list_ind_del() -> Tuple[int, float]: col: List[str] = [] s = StringSource() col.extend(s.take(base_length)) def do() -> None: ind = random.randrange(len(col)) del col[ind] col.append(next(s)) timer = timeit.Timer(do) return timer.autorange() def time_list_ind_del_check() -> Tuple[int, float]: col: List[str] = [] s = StringSource() col.extend(s.take(base_length)) def do() -> None: ind = random.randrange(len(col)) del col[ind] el = next(s) if el not in col: col.append(el) timer = timeit.Timer(do) return timer.autorange() def time_list_ind_pop() -> Tuple[int, float]: col: List[str] = [] s = StringSource() col = [] col.extend(s.take(base_length)) def do() -> None: ind = random.randrange(len(col)) col[ind] = col[-1] col.pop() col.append(next(s)) timer = timeit.Timer(do) return timer.autorange() def time_list_ind_pop_check() -> Tuple[int, float]: col: List[str] = [] s = StringSource() col.extend(s.take(base_length)) def do() -> None: ind = random.randrange(len(col)) col[ind] = col[-1] col.pop() el = next(s) if el not in col: col.append(el) timer = timeit.Timer(do) return timer.autorange() def time_list_set_del() -> Tuple[int, float]: col: List[str] = [] col_set: Set[str] = set() s = StringSource() for el in s.take(base_length): col.append(el) col_set.add(el) def do() -> None: ind = random.randrange(len(col)) el = col[ind] del col[ind] col_set.remove(el) el = next(s) if el not in col_set: col.append(el) col_set.add(el) timer = timeit.Timer(do) return timer.autorange() def time_list_set_pop() -> Tuple[int, float]: col: List[str] = [] col_set: Set[str] = set() s = StringSource() for el in s.take(base_length): col.append(el) col_set.add(el) def do() -> None: ind = random.randrange(len(col)) el = col[ind] col[ind] = col[-1] col.pop() col_set.remove(el) el = next(s) if el not in col_set: col.append(el) col_set.add(el) timer = timeit.Timer(do) return timer.autorange() def time_deque() -> Tuple[int, float]: col: Deque[str] = Deque() s = StringSource() col.extend(s.take(base_length)) def do() -> None: el = random.choice(col) col.remove(el) col.append(next(s)) timer = timeit.Timer(do) return timer.autorange() def time_deque_range() -> Tuple[int, float]: col: Deque[str] = Deque() s = StringSource() col.extend(s.take(base_length)) def do() -> None: ind = random.randrange(len(col)) el = col[ind] del col[ind] col.append(next(s)) timer = timeit.Timer(do) return timer.autorange() def time_deque_ind_check() -> Tuple[int, float]: col: Deque[str] = Deque() s = StringSource() col.extend(s.take(base_length)) def do() -> None: ind = random.randrange(len(col)) el = col[ind] del col[ind] el = next(s) if el not in col: col.append(el) timer = timeit.Timer(do) return timer.autorange() def time_set_iter() -> Tuple[int, float]: col: Set[str] = set() s = StringSource() col.update(s.take(base_length)) def do() -> None: ind = random.randrange(len(col)) el_to_remove = list(itertools.islice(col, ind, ind + 1))[0] col.remove(el_to_remove) col.add(next(s)) timer = timeit.Timer(do) return timer.autorange() BenchmarkFunction = Callable[[], Tuple[int, float]] benchmark_functions: List[BenchmarkFunction] = [ time_list_choice, time_list_ind_del, time_list_ind_del_check, time_list_ind_pop, time_list_ind_pop_check, time_list_set_del, time_list_set_pop, time_deque, time_deque_range, time_deque_ind_check, time_set_iter, ] def main() -> None: for f in benchmark_functions: rep, dur = f() print(f.__name__, (dur / rep, rep, dur)) if __name__ == '__main__': main()

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49d2ed6066cc56a87632114b0bc00af34fbe2877

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py

Python

tools/deepke/name_entity_re/standard/__init__.py

dfface/DoctorKG

6bd6ebec8244a9ce0a2c8c278a704f02b9afaaf8

[ "MIT" ]

1

2022-03-26T16:08:08.000Z

tools/deepke/name_entity_re/standard/__init__.py

dfface/DoctorKG

6bd6ebec8244a9ce0a2c8c278a704f02b9afaaf8

[ "MIT" ]

null

tools/deepke/name_entity_re/standard/__init__.py

dfface/DoctorKG

6bd6ebec8244a9ce0a2c8c278a704f02b9afaaf8

[ "MIT" ]

null

from .models import * from .tools import *

21.5

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b718f24e7816394140c4c96868d0e31c144b52dc

145

py

Python

my_functions.py

Hejinzefinance/Learn_git

83903bd1da8493d6855c959dddec6793ff29d89e

[ "MIT" ]

null

my_functions.py

Hejinzefinance/Learn_git

83903bd1da8493d6855c959dddec6793ff29d89e

[ "MIT" ]

null

my_functions.py

Hejinzefinance/Learn_git

83903bd1da8493d6855c959dddec6793ff29d89e

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Mon Mar 15 21:21:17 2021 @author: Hejizne """ def add(x,y): return x+y def minus(x,y): return x-y

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b7371c852221804191c75e6e40e06d13acff645e

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py

Python

umysqldb/constants.py

byaka/umysqldb_portable

0485cd9c623d169280de0c0d595858b04b03d080

[ "BSD-3-Clause" ]

null

umysqldb/constants.py

byaka/umysqldb_portable

0485cd9c623d169280de0c0d595858b04b03d080

[ "BSD-3-Clause" ]

1

2017-02-22T16:31:24.000Z

umysqldb/constants.py

byaka/umysqldb_portable

0485cd9c623d169280de0c0d595858b04b03d080

[ "BSD-3-Clause" ]

null

from pymysql_portable.constants import *

20.5

40

0.853659

5

41

6.8

1

0

0.097561

41

1

41

0.918919

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

3f91d023ed9da6d3e6745fa9158ac328f7b2fb1b

155

py

Python

gehomesdk/exception/ge_needs_reauthentication_error.py

willhayslett/gehome

7e407a1d31cede1453656eaef948332e808484ea

[ "MIT" ]

17

2021-05-18T01:58:06.000Z

2022-03-22T20:49:32.000Z

gehomesdk/exception/ge_needs_reauthentication_error.py

willhayslett/gehome

7e407a1d31cede1453656eaef948332e808484ea

[ "MIT" ]

29

2021-05-17T21:43:16.000Z

2022-02-28T22:50:48.000Z

gehomesdk/exception/ge_needs_reauthentication_error.py

willhayslett/gehome

7e407a1d31cede1453656eaef948332e808484ea

[ "MIT" ]

9

2021-05-17T04:40:58.000Z

2022-02-02T17:26:13.000Z

from .ge_exception import GeException class GeNeedsReauthenticationError(GeException): """Error raised when the reauthentication is needed""" pass

31

58

0.793548

16

155

7.625

0.9375

0

0.141935

155

5

59

31

0.917293

0.309677

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

3f957aae7d3424f49398ea82640d72d107428ded

33

py

Python

root/main.py

smysnk/led-controller

9f74d644ba4b5841806483ed245f075f61a4f719

[ "MIT" ]

null

root/main.py

smysnk/led-controller

9f74d644ba4b5841806483ed245f075f61a4f719

[ "MIT" ]

null

root/main.py

smysnk/led-controller

9f74d644ba4b5841806483ed245f075f61a4f719

[ "MIT" ]

null

import src.main src.main.start()

11

16

0.757576

6

33

4.166667

0.666667

0.56

0

0.090909

33

2

17

16.5

0.833333

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

b7477a1d5b995b4b193cd54073cdd5bf7bd04da1

91,724

py

Python

datasets/col_loc_scale_dataset.py

tim-henry/experiment-framework

ff54b315e5c584269f473c5eb8959fb40926a59c

[ "MIT" ]

1

2021-01-25T11:40:19.000Z

datasets/col_loc_scale_dataset.py

tim-henry/experiment-framework

ff54b315e5c584269f473c5eb8959fb40926a59c

[ "MIT" ]

null

datasets/col_loc_scale_dataset.py

tim-henry/experiment-framework

ff54b315e5c584269f473c5eb8959fb40926a59c

[ "MIT" ]

2

2020-04-12T02:44:01.000Z

2021-12-27T02:13:38.000Z

import numpy as np from PIL import Image import random import torch import matplotlib.pyplot as plt from torchvision import datasets, transforms class ColLocScaleMNIST(datasets.MNIST): # Color classes color_name_map = ["red", "green", "blue", "yellow", "magenta", "cyan", "purple", "lime", "orange", "white"] color_map = [np.array([1, 0.1, 0.1]), np.array([0.1, 1, 0.1]), np.array([0.1, 0.1, 1]), np.array([1, 1, 0.1]), np.array([1, 0.1, 1]), np.array([0.1, 1, 1]), np.array([0.57, 0.12, 0.71]), np.array([0.72, 0.96, 0.24]), np.array([0.96, 0.51, 0.19]), np.array([1, 1, 1])] # Gaussian noise arguments mu = 0 sigma = 50 # pct_to_keep: percentage of possible combinations to keep between 0 and 1, rounded down to nearest multiple of 1/9 def __init__(self, root, train=True, transform=None, target_transform=None, download=False, pct_to_keep=1, color_indices=np.arange(9)): super().__init__(root, train, transform, target_transform, download) pct = pct_to_keep self.max_left_dist = int(pct / 2) self.max_right_dist = int(pct / 2) if pct % 2 == 0 else int(pct / 2) + 1 self.held_out = [(0, 4), (1, 5), (2, 6), (3, 7), (4, 8), (5, 0), (6, 1), (7, 2), (8, 3)] self.control = [(0, 0), (1, 1), (2, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7), (8, 8)] self.combination_space_shape = (9, 9) self.class_names = ("shape", "color", "location", "scale") self.name = "col_loc_scale_mnist" np.random.seed(17) self.color_indices = np.arange(9) self.loc_indices = np.arange(9) self.scale_indices = np.arange(9) np.random.shuffle(self.color_indices) np.random.shuffle(self.loc_indices) np.random.shuffle(self.scale_indices) self.pct_to_combs = [[(0, 0, 0, 0),(1, 1, 0, 0),(2, 2, 0, 0),(3, 3, 0, 0),(4, 4, 0, 0),(5, 5, 0, 0),(6, 6, 0, 0),(7, 7, 0, 0),(8, 8, 0, 0),(1, 0, 1, 0),(2, 1, 1, 0),(3, 2, 1, 0),(4, 3, 1, 0),(5, 4, 1, 0),(6, 5, 1, 0),(7, 6, 1, 0),(8, 7, 1, 0),(0, 8, 1, 0),(2, 0, 2, 0),(3, 1, 2, 0),(4, 2, 2, 0),(5, 3, 2, 0),(6, 4, 2, 0),(7, 5, 2, 0),(8, 6, 2, 0),(0, 7, 2, 0),(1, 8, 2, 0),(3, 0, 3, 0),(4, 1, 3, 0),(5, 2, 3, 0),(6, 3, 3, 0),(7, 4, 3, 0),(8, 5, 3, 0),(0, 6, 3, 0),(1, 7, 3, 0),(2, 8, 3, 0),(4, 0, 4, 0),(5, 1, 4, 0),(6, 2, 4, 0),(7, 3, 4, 0),(8, 4, 4, 0),(0, 5, 4, 0),(1, 6, 4, 0),(2, 7, 4, 0),(3, 8, 4, 0),(5, 0, 5, 0),(6, 1, 5, 0),(7, 2, 5, 0),(8, 3, 5, 0),(0, 4, 5, 0),(1, 5, 5, 0),(2, 6, 5, 0),(3, 7, 5, 0),(4, 8, 5, 0),(6, 0, 6, 0),(7, 1, 6, 0),(8, 2, 6, 0),(0, 3, 6, 0),(1, 4, 6, 0),(2, 5, 6, 0),(3, 6, 6, 0),(4, 7, 6, 0),(5, 8, 6, 0),(7, 0, 7, 0),(8, 1, 7, 0),(0, 2, 7, 0),(1, 3, 7, 0),(2, 4, 7, 0),(3, 5, 7, 0),(4, 6, 7, 0),(5, 7, 7, 0),(6, 8, 7, 0),(8, 0, 8, 0),(0, 1, 8, 0),(1, 2, 8, 0),(2, 3, 8, 0),(3, 4, 8, 0),(4, 5, 8, 0),(5, 6, 8, 0),(6, 7, 8, 0),(7, 8, 8, 0),(1, 0, 0, 1),(2, 1, 0, 1),(3, 2, 0, 1),(4, 3, 0, 1),(5, 4, 0, 1),(6, 5, 0, 1),(7, 6, 0, 1),(8, 7, 0, 1),(0, 8, 0, 1),(2, 0, 1, 1),(3, 1, 1, 1),(4, 2, 1, 1),(5, 3, 1, 1),(6, 4, 1, 1),(7, 5, 1, 1),(8, 6, 1, 1),(0, 7, 1, 1),(1, 8, 1, 1),(3, 0, 2, 1),(4, 1, 2, 1),(5, 2, 2, 1),(6, 3, 2, 1),(7, 4, 2, 1),(8, 5, 2, 1),(0, 6, 2, 1),(1, 7, 2, 1),(2, 8, 2, 1),(4, 0, 3, 1),(5, 1, 3, 1),(6, 2, 3, 1),(7, 3, 3, 1),(8, 4, 3, 1),(0, 5, 3, 1),(1, 6, 3, 1),(2, 7, 3, 1),(3, 8, 3, 1),(5, 0, 4, 1),(6, 1, 4, 1),(7, 2, 4, 1),(8, 3, 4, 1),(0, 4, 4, 1),(1, 5, 4, 1),(2, 6, 4, 1),(3, 7, 4, 1),(4, 8, 4, 1),(6, 0, 5, 1),(7, 1, 5, 1),(8, 2, 5, 1),(0, 3, 5, 1),(1, 4, 5, 1),(2, 5, 5, 1),(3, 6, 5, 1),(4, 7, 5, 1),(5, 8, 5, 1),(7, 0, 6, 1),(8, 1, 6, 1),(0, 2, 6, 1),(1, 3, 6, 1),(2, 4, 6, 1),(3, 5, 6, 1),(4, 6, 6, 1),(5, 7, 6, 1),(6, 8, 6, 1),(8, 0, 7, 1),(0, 1, 7, 1),(1, 2, 7, 1),(2, 3, 7, 1),(3, 4, 7, 1),(4, 5, 7, 1),(5, 6, 7, 1),(6, 7, 7, 1),(7, 8, 7, 1),(0, 0, 8, 1),(1, 1, 8, 1),(2, 2, 8, 1),(3, 3, 8, 1),(4, 4, 8, 1),(5, 5, 8, 1),(6, 6, 8, 1),(7, 7, 8, 1),(8, 8, 8, 1),(2, 0, 0, 2),(3, 1, 0, 2),(4, 2, 0, 2),(5, 3, 0, 2),(6, 4, 0, 2),(7, 5, 0, 2),(8, 6, 0, 2),(0, 7, 0, 2),(1, 8, 0, 2),(3, 0, 1, 2),(4, 1, 1, 2),(5, 2, 1, 2),(6, 3, 1, 2),(7, 4, 1, 2),(8, 5, 1, 2),(0, 6, 1, 2),(1, 7, 1, 2),(2, 8, 1, 2),(4, 0, 2, 2),(5, 1, 2, 2),(6, 2, 2, 2),(7, 3, 2, 2),(8, 4, 2, 2),(0, 5, 2, 2),(1, 6, 2, 2),(2, 7, 2, 2),(3, 8, 2, 2),(5, 0, 3, 2),(6, 1, 3, 2),(7, 2, 3, 2),(8, 3, 3, 2),(0, 4, 3, 2),(1, 5, 3, 2),(2, 6, 3, 2),(3, 7, 3, 2),(4, 8, 3, 2),(6, 0, 4, 2),(7, 1, 4, 2),(8, 2, 4, 2),(0, 3, 4, 2),(1, 4, 4, 2),(2, 5, 4, 2),(3, 6, 4, 2),(4, 7, 4, 2),(5, 8, 4, 2),(7, 0, 5, 2),(8, 1, 5, 2),(0, 2, 5, 2),(1, 3, 5, 2),(2, 4, 5, 2),(3, 5, 5, 2),(4, 6, 5, 2),(5, 7, 5, 2),(6, 8, 5, 2),(8, 0, 6, 2),(0, 1, 6, 2),(1, 2, 6, 2),(2, 3, 6, 2),(3, 4, 6, 2),(4, 5, 6, 2),(5, 6, 6, 2),(6, 7, 6, 2),(7, 8, 6, 2),(0, 0, 7, 2),(1, 1, 7, 2),(2, 2, 7, 2),(3, 3, 7, 2),(4, 4, 7, 2),(5, 5, 7, 2),(6, 6, 7, 2),(7, 7, 7, 2),(8, 8, 7, 2),(1, 0, 8, 2),(2, 1, 8, 2),(3, 2, 8, 2),(4, 3, 8, 2),(5, 4, 8, 2),(6, 5, 8, 2),(7, 6, 8, 2),(8, 7, 8, 2),(0, 8, 8, 2),(3, 0, 0, 3),(4, 1, 0, 3),(5, 2, 0, 3),(6, 3, 0, 3),(7, 4, 0, 3),(8, 5, 0, 3),(0, 6, 0, 3),(1, 7, 0, 3),(2, 8, 0, 3),(4, 0, 1, 3),(5, 1, 1, 3),(6, 2, 1, 3),(7, 3, 1, 3),(8, 4, 1, 3),(0, 5, 1, 3),(1, 6, 1, 3),(2, 7, 1, 3),(3, 8, 1, 3),(5, 0, 2, 3),(6, 1, 2, 3),(7, 2, 2, 3),(8, 3, 2, 3),(0, 4, 2, 3),(1, 5, 2, 3),(2, 6, 2, 3),(3, 7, 2, 3),(4, 8, 2, 3),(6, 0, 3, 3),(7, 1, 3, 3),(8, 2, 3, 3),(0, 3, 3, 3),(1, 4, 3, 3),(2, 5, 3, 3),(3, 6, 3, 3),(4, 7, 3, 3),(5, 8, 3, 3),(7, 0, 4, 3),(8, 1, 4, 3),(0, 2, 4, 3),(1, 3, 4, 3),(2, 4, 4, 3),(3, 5, 4, 3),(4, 6, 4, 3),(5, 7, 4, 3),(6, 8, 4, 3),(8, 0, 5, 3),(0, 1, 5, 3),(1, 2, 5, 3),(2, 3, 5, 3),(3, 4, 5, 3),(4, 5, 5, 3),(5, 6, 5, 3),(6, 7, 5, 3),(7, 8, 5, 3),(0, 0, 6, 3),(1, 1, 6, 3),(2, 2, 6, 3),(3, 3, 6, 3),(4, 4, 6, 3),(5, 5, 6, 3),(6, 6, 6, 3),(7, 7, 6, 3),(8, 8, 6, 3),(1, 0, 7, 3),(2, 1, 7, 3),(3, 2, 7, 3),(4, 3, 7, 3),(5, 4, 7, 3),(6, 5, 7, 3),(7, 6, 7, 3),(8, 7, 7, 3),(0, 8, 7, 3),(2, 0, 8, 3),(3, 1, 8, 3),(4, 2, 8, 3),(5, 3, 8, 3),(6, 4, 8, 3),(7, 5, 8, 3),(8, 6, 8, 3),(0, 7, 8, 3),(1, 8, 8, 3),(4, 0, 0, 4),(5, 1, 0, 4),(6, 2, 0, 4),(7, 3, 0, 4),(8, 4, 0, 4),(0, 5, 0, 4),(1, 6, 0, 4),(2, 7, 0, 4),(3, 8, 0, 4),(5, 0, 1, 4),(6, 1, 1, 4),(7, 2, 1, 4),(8, 3, 1, 4),(0, 4, 1, 4),(1, 5, 1, 4),(2, 6, 1, 4),(3, 7, 1, 4),(4, 8, 1, 4),(6, 0, 2, 4),(7, 1, 2, 4),(8, 2, 2, 4),(0, 3, 2, 4),(1, 4, 2, 4),(2, 5, 2, 4),(3, 6, 2, 4),(4, 7, 2, 4),(5, 8, 2, 4),(7, 0, 3, 4),(8, 1, 3, 4),(0, 2, 3, 4),(1, 3, 3, 4),(2, 4, 3, 4),(3, 5, 3, 4),(4, 6, 3, 4),(5, 7, 3, 4),(6, 8, 3, 4),(8, 0, 4, 4),(0, 1, 4, 4),(1, 2, 4, 4),(2, 3, 4, 4),(3, 4, 4, 4),(4, 5, 4, 4),(5, 6, 4, 4),(6, 7, 4, 4),(7, 8, 4, 4),(0, 0, 5, 4),(1, 1, 5, 4),(2, 2, 5, 4),(3, 3, 5, 4),(4, 4, 5, 4),(5, 5, 5, 4),(6, 6, 5, 4),(7, 7, 5, 4),(8, 8, 5, 4),(1, 0, 6, 4),(2, 1, 6, 4),(3, 2, 6, 4),(4, 3, 6, 4),(5, 4, 6, 4),(6, 5, 6, 4),(7, 6, 6, 4),(8, 7, 6, 4),(0, 8, 6, 4),(2, 0, 7, 4),(3, 1, 7, 4),(4, 2, 7, 4),(5, 3, 7, 4),(6, 4, 7, 4),(7, 5, 7, 4),(8, 6, 7, 4),(0, 7, 7, 4),(1, 8, 7, 4),(3, 0, 8, 4),(4, 1, 8, 4),(5, 2, 8, 4),(6, 3, 8, 4),(7, 4, 8, 4),(8, 5, 8, 4),(0, 6, 8, 4),(1, 7, 8, 4),(2, 8, 8, 4),(5, 0, 0, 5),(6, 1, 0, 5),(7, 2, 0, 5),(8, 3, 0, 5),(0, 4, 0, 5),(1, 5, 0, 5),(2, 6, 0, 5),(3, 7, 0, 5),(4, 8, 0, 5),(6, 0, 1, 5),(7, 1, 1, 5),(8, 2, 1, 5),(0, 3, 1, 5),(1, 4, 1, 5),(2, 5, 1, 5),(3, 6, 1, 5),(4, 7, 1, 5),(5, 8, 1, 5),(7, 0, 2, 5),(8, 1, 2, 5),(0, 2, 2, 5),(1, 3, 2, 5),(2, 4, 2, 5),(3, 5, 2, 5),(4, 6, 2, 5),(5, 7, 2, 5),(6, 8, 2, 5),(8, 0, 3, 5),(0, 1, 3, 5),(1, 2, 3, 5),(2, 3, 3, 5),(3, 4, 3, 5),(4, 5, 3, 5),(5, 6, 3, 5),(6, 7, 3, 5),(7, 8, 3, 5),(0, 0, 4, 5),(1, 1, 4, 5),(2, 2, 4, 5),(3, 3, 4, 5),(4, 4, 4, 5),(5, 5, 4, 5),(6, 6, 4, 5),(7, 7, 4, 5),(8, 8, 4, 5),(1, 0, 5, 5),(2, 1, 5, 5),(3, 2, 5, 5),(4, 3, 5, 5),(5, 4, 5, 5),(6, 5, 5, 5),(7, 6, 5, 5),(8, 7, 5, 5),(0, 8, 5, 5),(2, 0, 6, 5),(3, 1, 6, 5),(4, 2, 6, 5),(5, 3, 6, 5),(6, 4, 6, 5),(7, 5, 6, 5),(8, 6, 6, 5),(0, 7, 6, 5),(1, 8, 6, 5),(3, 0, 7, 5),(4, 1, 7, 5),(5, 2, 7, 5),(6, 3, 7, 5),(7, 4, 7, 5),(8, 5, 7, 5),(0, 6, 7, 5),(1, 7, 7, 5),(2, 8, 7, 5),(4, 0, 8, 5),(5, 1, 8, 5),(6, 2, 8, 5),(7, 3, 8, 5),(8, 4, 8, 5),(0, 5, 8, 5),(1, 6, 8, 5),(2, 7, 8, 5),(3, 8, 8, 5),(6, 0, 0, 6),(7, 1, 0, 6),(8, 2, 0, 6),(0, 3, 0, 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4, 1, 8),(4, 5, 1, 8),(5, 6, 1, 8),(6, 7, 1, 8),(7, 8, 1, 8),(0, 0, 2, 8),(1, 1, 2, 8),(2, 2, 2, 8),(3, 3, 2, 8),(4, 4, 2, 8),(5, 5, 2, 8),(6, 6, 2, 8),(7, 7, 2, 8),(8, 8, 2, 8),(1, 0, 3, 8),(2, 1, 3, 8),(3, 2, 3, 8),(4, 3, 3, 8),(5, 4, 3, 8),(6, 5, 3, 8),(7, 6, 3, 8),(8, 7, 3, 8),(0, 8, 3, 8),(2, 0, 4, 8),(3, 1, 4, 8),(4, 2, 4, 8),(5, 3, 4, 8),(6, 4, 4, 8),(7, 5, 4, 8),(8, 6, 4, 8),(0, 7, 4, 8),(1, 8, 4, 8),(3, 0, 5, 8),(4, 1, 5, 8),(5, 2, 5, 8),(6, 3, 5, 8),(7, 4, 5, 8),(8, 5, 5, 8),(0, 6, 5, 8),(1, 7, 5, 8),(2, 8, 5, 8),(4, 0, 6, 8),(5, 1, 6, 8),(6, 2, 6, 8),(7, 3, 6, 8),(8, 4, 6, 8),(0, 5, 6, 8),(1, 6, 6, 8),(2, 7, 6, 8),(3, 8, 6, 8),(5, 0, 7, 8),(6, 1, 7, 8),(7, 2, 7, 8),(8, 3, 7, 8),(0, 4, 7, 8),(1, 5, 7, 8),(2, 6, 7, 8),(3, 7, 7, 8),(4, 8, 7, 8),(6, 0, 8, 8),(7, 1, 8, 8),(8, 2, 8, 8),(0, 3, 8, 8),(1, 4, 8, 8),(2, 5, 8, 8),(3, 6, 8, 8),(4, 7, 8, 8),(5, 8, 8, 8)]] self.valid_combs = {} print(pct) for keep_pct in range(pct): for shape, color, loc, scale in self.pct_to_combs[keep_pct]: if shape not in self.valid_combs: self.valid_combs[shape] = {} if color not in self.valid_combs[shape]: self.valid_combs[shape][color] = {} if loc not in self.valid_combs[shape][color]: self.valid_combs[shape][color][loc] = [] self.valid_combs[shape][color][loc].append(scale) self.synth_ct = {} for keep_pct in range(pct): for shape, color, loc, scale in self.pct_to_combs[keep_pct]: if shape not in self.synth_ct: self.synth_ct[shape] = {} if color not in self.synth_ct[shape]: self.synth_ct[shape][color] = {} if loc not in self.synth_ct[shape][color]: self.synth_ct[shape][color][loc] = {} self.synth_ct[shape][color][loc][scale] = 0 def __getitem__(self, index): """ Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class. """ if self.train: img, target = self.train_data[index], self.train_labels[index] else: img, target = self.test_data[index], self.test_labels[index] assert target.item() < 9 # Sample labels shape_class = target.item() color_class = random.choice(list(self.valid_combs[shape_class].keys())) loc_class = random.choice(list(self.valid_combs[shape_class][color_class].keys())) scale_class = random.choice(list(self.valid_combs[shape_class][color_class][loc_class])) while self.synth_ct[shape_class][color_class][loc_class][scale_class] < \ max(self.synth_ct[shape_class][color_class][loc_class].values()): color_class = random.choice(list(self.valid_combs[shape_class].keys())) loc_class = random.choice(list(self.valid_combs[shape_class][color_class].keys())) scale_class = random.choice(list(self.valid_combs[shape_class][color_class][loc_class])) self.synth_ct[shape_class][color_class][loc_class][scale_class] += 1 # Put grayscale image in RGB space img_array = np.stack((img[0] * 255,) * 3, axis=-1).astype(np.uint8) # Determine image size img_size = 28 box_size = 32 total_size = 32 * 3 size = range(12, 29, 2)[self.scale_indices[scale_class]] img = Image.fromarray(img_array, 'RGB') img.thumbnail((size, size)) local_vert_offset = int((img_size - size) / 2) local_horiz_offset = int((img_size - size) / 2) # Determine image location loc_idx = self.loc_indices[loc_class] vert_loc_class = int(loc_idx / 3) horiz_loc_class = loc_idx % 3 global_vert_offset = vert_loc_class * box_size global_horiz_offset = horiz_loc_class * box_size vert_offset = local_vert_offset + global_vert_offset horiz_offset = local_horiz_offset + global_horiz_offset # Render img_array = np.zeros((total_size, total_size, 3)) img_array[vert_offset:(vert_offset + size), horiz_offset:(horiz_offset + size), :] = np.array(img) img_array = np.clip(img_array, 0, 254) img_array = img_array.astype(dtype=np.uint8) # Color image img_array = img_array * self.color_map[self.color_indices[color_class]] # Add Gaussian noise noise = np.reshape(np.random.normal(self.mu, self.sigma, img_array.size), img_array.shape) mask = (img_array != 0).astype("uint8") img_array = img_array + np.multiply(mask, noise) img_array = np.clip(img_array, 0, 255) img_array = img_array.astype("uint8") img = Image.fromarray(img_array) # Perform additional transformations if self.transform is not None: img = self.transform(img) if self.target_transform is not None: target = self.target_transform(target) return transforms.ToTensor()(img), torch.tensor([target.item(), color_class, loc_class, scale_class])

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1

0

1

0

null

0

6

b7568ca217d1e1cf743150556abb235d178156c5

325

py

Python

start.py

moenova/Human-Memory-Manager

02b2d8ffd78a3ddcd693f0d991bd4c5d0ef54c80

[ "MIT" ]

6

2019-09-20T01:15:05.000Z

2020-05-20T20:14:39.000Z

start.py

moenova/Memory-Helper

02b2d8ffd78a3ddcd693f0d991bd4c5d0ef54c80

[ "MIT" ]

null

start.py

moenova/Memory-Helper

02b2d8ffd78a3ddcd693f0d991bd4c5d0ef54c80

[ "MIT" ]

null

from src.memory import startTable,startNode #startTable("genki test","res/","eng","hiragana",lesson=13) #startTable("genki test","res/","eng","hiragana") #startNode("test","res/","第一章节") #startTable("genki 2 volcab","res/","eng","hiragana",lesson=13) startTable("genki 2 kanji","res/","hiragana","kanji",lesson=13)

36.111111

64

0.68

42

325

5.261905

0.404762

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0.190045

0.199095

0.502262

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0

0.026667

0.076923

325

8

65

40.625

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null

0

1

0

1

0

6

b75f8069a886743e26f1ac9cfdb82b1ea13e45ff

38

py

Python

tests/test_project.py

buuren/project

e115a85cd5bf2c6d797ab10a61462837b1adb35e

[ "MIT" ]

null

tests/test_project.py

buuren/project

e115a85cd5bf2c6d797ab10a61462837b1adb35e

[ "MIT" ]

1

2021-06-01T21:54:28.000Z

tests/test_project.py

buuren/project

e115a85cd5bf2c6d797ab10a61462837b1adb35e

[ "MIT" ]

null

def test_project(): assert 0 == 0

12.666667

19

0.605263

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3.666667

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0.071429

0.263158

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true

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null

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null

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1

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6

b782012597a99e32099d7094fab85f68e6d862fe

33

py

Python

stko/utilities/__init__.py

SFin94/stko

7a913c7f0c4b616ddc52fef7eeb44c539176c351

[ "MIT" ]

21

2018-04-12T16:25:24.000Z

2022-02-14T23:05:43.000Z

stko/utilities/__init__.py

SFin94/stko

7a913c7f0c4b616ddc52fef7eeb44c539176c351

[ "MIT" ]

60

2020-05-22T13:38:54.000Z

2022-03-25T09:34:22.000Z

stko/utilities/__init__.py

SFin94/stko

7a913c7f0c4b616ddc52fef7eeb44c539176c351

[ "MIT" ]

5

2018-08-07T13:00:16.000Z

2021-11-01T00:55:10.000Z

from .utilities import * # noqa

16.5

32

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0.884615

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6

b7b778adb80cc53c8973743429065b7cf0cd1ca9

175

py

Python

filey/__init__.py

kendfss/filey

890126f197cee060b3df2bf8660f9401dab629dc

[ "MIT" ]

null

filey/__init__.py

kendfss/filey

890126f197cee060b3df2bf8660f9401dab629dc

[ "MIT" ]

null

filey/__init__.py

kendfss/filey

890126f197cee060b3df2bf8660f9401dab629dc

[ "MIT" ]

null

from .handles import * from .shell import * from .walking import * from .persistence import * from .shortcuts import * if __name__ == "__main__": pass

12.5

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5.421053

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null

1

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null

0

1

0

1

0

6

4d4417123d0ca0c9a30b103f83b57c04ec4a12fa

2,613

py

Python

tests/test_reprs.py

amangoel185/hist

040872b978ecfd98e9836ad0a7e5c27d8dd44d09

[ "BSD-3-Clause" ]

84

2020-02-12T02:02:58.000Z

2022-03-23T10:50:03.000Z

tests/test_reprs.py

amangoel185/hist

040872b978ecfd98e9836ad0a7e5c27d8dd44d09

[ "BSD-3-Clause" ]

213

2020-03-09T02:38:25.000Z

2022-03-16T19:22:31.000Z

tests/test_reprs.py

amangoel185/hist

040872b978ecfd98e9836ad0a7e5c27d8dd44d09

[ "BSD-3-Clause" ]

15

2020-03-14T12:05:18.000Z

2021-11-12T14:25:07.000Z

from __future__ import annotations from hist import Hist, Stack, axis def test_1D_empty_repr(named_hist): h = named_hist.new.Reg(10, -1, 1, name="x", label="y").Double() html = h._repr_html_() assert html assert "name='x'" in repr(h) assert "label='y'" in repr(h) def test_1D_var_empty_repr(named_hist): h = named_hist.new.Var(range(10), name="x", label="y").Double() html = h._repr_html_() assert html assert "name='x'" in repr(h) assert "label='y'" in repr(h) def test_1D_int_empty_repr(named_hist): h = named_hist.new.Int(-9, 9, name="x", label="y").Double() html = h._repr_html_() assert html assert "name='x'" in repr(h) assert "label='y'" in repr(h) def test_1D_intcat_empty_repr(named_hist): h = named_hist.new.IntCat([1, 3, 5], name="x", label="y").Double() html = h._repr_html_() assert html assert "name='x'" in repr(h) assert "label='y'" in repr(h) def test_1D_strcat_empty_repr(named_hist): h = named_hist.new.StrCat(["1", "3", "5"], name="x", label="y").Double() html = h._repr_html_() assert html assert "name='x'" in repr(h) assert "label='y'" in repr(h) def test_2D_empty_repr(named_hist): h = ( named_hist.new.Reg(10, -1, 1, name="x", label="y") .Int(0, 15, name="p", label="q") .Double() ) html = h._repr_html_() assert html assert "name='x'" in repr(h) assert "name='p'" in repr(h) assert "label='y'" in repr(h) assert "label='q'" in repr(h) def test_1D_circ_empty_repr(named_hist): h = named_hist.new.Reg(10, -1, 1, circular=True, name="R", label="r").Double() html = h._repr_html_() assert html assert "name='R'" in repr(h) assert "label='r'" in repr(h) def test_ND_empty_repr(named_hist): h = ( named_hist.new.Reg(10, -1, 1, name="x", label="y") .Reg(12, -3, 3, name="p", label="q") .Reg(15, -2, 4, name="a", label="b") .Double() ) html = h._repr_html_() assert html assert "name='x'" in repr(h) assert "name='p'" in repr(h) assert "name='a'" in repr(h) assert "label='y'" in repr(h) assert "label='q'" in repr(h) assert "label='b'" in repr(h) def test_stack_repr(named_hist): a1 = axis.Regular( 50, -5, 5, name="A", label="a [unit]", underflow=False, overflow=False ) a2 = axis.Regular( 50, -5, 5, name="A", label="a [unit]", underflow=False, overflow=False ) assert "name='A'" in repr(Stack(Hist(a1), Hist(a2))) assert "label='a [unit]'" in repr(Stack(Hist(a1), Hist(a2)))

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1

0

1

0

null

0

1

0

6

4d7f0f7c79183b1551ac547e2d97917b1d1b3d26

124

py

Python

blog/admin.py

shivansh1698/Blog_yourself

de797a4c01484fb006fddb3e213b75fad517e74b

[ "BSD-3-Clause" ]

null

blog/admin.py

shivansh1698/Blog_yourself

de797a4c01484fb006fddb3e213b75fad517e74b

[ "BSD-3-Clause" ]

5

2020-02-11T21:31:42.000Z

2021-06-10T22:45:00.000Z

blog/admin.py

shivansh1698/Blog_yourself

de797a4c01484fb006fddb3e213b75fad517e74b

[ "BSD-3-Clause" ]

null

from django.contrib import admin from . import models admin.site.register(models.Post) admin.site.register(models.Comment)

20.666667

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18

124

5.611111

0.555556

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0

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5

36

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true

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null

0

1

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1

0

6

4db79b5311b693731e27206c61e61819471b1c8b

89

py

Python

app/moment/__init__.py

MultyXu/Islandr

5f965638d0cda68e76f63b0625b2411029e90c2d

[ "MIT" ]

2

2019-06-05T01:36:53.000Z

2019-06-05T01:37:12.000Z

app/moment/__init__.py

dingding0606/Islandr

dd2277a8a7ceb002af3b28045133797fa9ffed9d

[ "MIT" ]

null

app/moment/__init__.py

dingding0606/Islandr

dd2277a8a7ceb002af3b28045133797fa9ffed9d

[ "MIT" ]

1

2019-08-28T20:49:22.000Z

from flask import Blueprint moment = Blueprint('moment', __name__) from . import views

14.833333

38

0.764045

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89

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0.157303

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null

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1

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1

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6

4de9c106d4d0f208b0c30b9db9b1737ca7387795

22

py

Python

__init__.py

keenJMS/JMS_OIM

6f4bc1c114d007c108d6989c05fb0847aee78a1c

[ "Apache-2.0" ]

null

__init__.py

keenJMS/JMS_OIM

6f4bc1c114d007c108d6989c05fb0847aee78a1c

[ "Apache-2.0" ]

null

__init__.py

keenJMS/JMS_OIM

6f4bc1c114d007c108d6989c05fb0847aee78a1c

[ "Apache-2.0" ]

null

from modeling import *

22

0.818182

3

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null

0

1

0

1

0

1

0

6

1283c9db0b2ab37c874f836d2104cd5f7207a579

8,779

py

Python

tests/components/intellifire/test_config_flow.py

MrDelik/core

93a66cc357b226389967668441000498a10453bb

[ "Apache-2.0" ]

3

2021-11-22T22:37:43.000Z

2022-03-17T00:55:28.000Z

tests/components/intellifire/test_config_flow.py

MrDelik/core

93a66cc357b226389967668441000498a10453bb

[ "Apache-2.0" ]

14

2022-01-13T04:27:21.000Z

2022-03-06T20:30:43.000Z

tests/components/intellifire/test_config_flow.py

MrDelik/core

93a66cc357b226389967668441000498a10453bb

[ "Apache-2.0" ]

3

2022-01-02T18:49:54.000Z

2022-01-25T02:03:54.000Z

"""Test the IntelliFire config flow.""" from unittest.mock import AsyncMock, MagicMock, patch from homeassistant import config_entries from homeassistant.components import dhcp from homeassistant.components.intellifire.config_flow import MANUAL_ENTRY_STRING from homeassistant.components.intellifire.const import DOMAIN from homeassistant.const import CONF_HOST from homeassistant.core import HomeAssistant from homeassistant.data_entry_flow import RESULT_TYPE_CREATE_ENTRY, RESULT_TYPE_FORM from tests.common import MockConfigEntry async def test_no_discovery( hass: HomeAssistant, mock_setup_entry: AsyncMock, mock_intellifire_config_flow: MagicMock, ) -> None: """Test we should get the manual discovery form - because no discovered fireplaces.""" with patch( "homeassistant.components.intellifire.config_flow.AsyncUDPFireplaceFinder.search_fireplace", return_value=[], ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == RESULT_TYPE_FORM assert result["errors"] == {} assert result["step_id"] == "manual_device_entry" result2 = await hass.config_entries.flow.async_configure( result["flow_id"], { CONF_HOST: "1.1.1.1", }, ) await hass.async_block_till_done() assert result2["type"] == RESULT_TYPE_CREATE_ENTRY assert result2["title"] == "Fireplace 12345" assert result2["data"] == {CONF_HOST: "1.1.1.1"} assert len(mock_setup_entry.mock_calls) == 1 async def test_single_discovery( hass: HomeAssistant, mock_setup_entry: AsyncMock, mock_intellifire_config_flow: MagicMock, ) -> None: """Test single fireplace UDP discovery.""" with patch( "homeassistant.components.intellifire.config_flow.AsyncUDPFireplaceFinder.search_fireplace", return_value=["192.168.1.69"], ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) result2 = await hass.config_entries.flow.async_configure( result["flow_id"], {CONF_HOST: "192.168.1.69"} ) await hass.async_block_till_done() print("Result:", result) assert result2["type"] == RESULT_TYPE_CREATE_ENTRY assert result2["title"] == "Fireplace 12345" assert result2["data"] == {CONF_HOST: "192.168.1.69"} assert len(mock_setup_entry.mock_calls) == 1 async def test_manual_entry( hass: HomeAssistant, mock_setup_entry: AsyncMock, mock_intellifire_config_flow: MagicMock, ) -> None: """Test for multiple firepalce discovery - involing a pick_device step.""" with patch( "homeassistant.components.intellifire.config_flow.AsyncUDPFireplaceFinder.search_fireplace", return_value=["192.168.1.69", "192.168.1.33", "192.168.169"], ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["step_id"] == "pick_device" result2 = await hass.config_entries.flow.async_configure( result["flow_id"], user_input={CONF_HOST: MANUAL_ENTRY_STRING} ) await hass.async_block_till_done() assert result2["step_id"] == "manual_device_entry" async def test_multi_discovery( hass: HomeAssistant, mock_setup_entry: AsyncMock, mock_intellifire_config_flow: MagicMock, ) -> None: """Test for multiple fireplace discovery - involving a pick_device step.""" with patch( "homeassistant.components.intellifire.config_flow.AsyncUDPFireplaceFinder.search_fireplace", return_value=["192.168.1.69", "192.168.1.33", "192.168.169"], ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["step_id"] == "pick_device" result2 = await hass.config_entries.flow.async_configure( result["flow_id"], user_input={CONF_HOST: "192.168.1.33"} ) await hass.async_block_till_done() assert result["step_id"] == "pick_device" assert result2["type"] == RESULT_TYPE_CREATE_ENTRY async def test_multi_discovery_cannot_connect( hass: HomeAssistant, mock_setup_entry: AsyncMock, mock_intellifire_config_flow: MagicMock, ) -> None: """Test for multiple fireplace discovery - involving a pick_device step.""" with patch( "homeassistant.components.intellifire.config_flow.AsyncUDPFireplaceFinder.search_fireplace", return_value=["192.168.1.69", "192.168.1.33", "192.168.169"], ): mock_intellifire_config_flow.poll.side_effect = ConnectionError result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == RESULT_TYPE_FORM assert result["step_id"] == "pick_device" result2 = await hass.config_entries.flow.async_configure( result["flow_id"], user_input={CONF_HOST: "192.168.1.33"} ) await hass.async_block_till_done() assert result2["type"] == RESULT_TYPE_FORM assert result2["errors"] == {"base": "cannot_connect"} async def test_form_cannot_connect_manual_entry( hass: HomeAssistant, mock_intellifire_config_flow: MagicMock, mock_fireplace_finder_single: AsyncMock, ) -> None: """Test we handle cannot connect error.""" mock_intellifire_config_flow.poll.side_effect = ConnectionError result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == RESULT_TYPE_FORM assert result["step_id"] == "manual_device_entry" result2 = await hass.config_entries.flow.async_configure( result["flow_id"], { CONF_HOST: "1.1.1.1", }, ) assert result2["type"] == RESULT_TYPE_FORM assert result2["errors"] == {"base": "cannot_connect"} async def test_picker_already_discovered( hass: HomeAssistant, mock_setup_entry: AsyncMock, mock_intellifire_config_flow: MagicMock, ) -> None: """Test single fireplace UDP discovery.""" entry = MockConfigEntry( domain=DOMAIN, data={ "host": "192.168.1.3", }, title="Fireplace", unique_id=44444, ) entry.add_to_hass(hass) with patch( "homeassistant.components.intellifire.config_flow.AsyncUDPFireplaceFinder.search_fireplace", return_value=["192.168.1.3"], ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) await hass.async_block_till_done() result2 = await hass.config_entries.flow.async_configure( result["flow_id"], { CONF_HOST: "192.168.1.4", }, ) assert result2["type"] == RESULT_TYPE_CREATE_ENTRY assert result2["title"] == "Fireplace 12345" assert result2["data"] == {CONF_HOST: "192.168.1.4"} assert len(mock_setup_entry.mock_calls) == 2 async def test_dhcp_discovery_intellifire_device( hass: HomeAssistant, mock_setup_entry: AsyncMock, mock_intellifire_config_flow: MagicMock, ) -> None: """Test successful DHCP Discovery.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_DHCP}, data=dhcp.DhcpServiceInfo( ip="1.1.1.1", macaddress="AA:BB:CC:DD:EE:FF", hostname="zentrios-Test", ), ) assert result["type"] == RESULT_TYPE_FORM assert result["step_id"] == "dhcp_confirm" result2 = await hass.config_entries.flow.async_configure(result["flow_id"]) assert result2["type"] == RESULT_TYPE_FORM assert result2["step_id"] == "dhcp_confirm" result3 = await hass.config_entries.flow.async_configure( result2["flow_id"], user_input={} ) assert result3["title"] == "Fireplace 12345" assert result3["data"] == {"host": "1.1.1.1"} async def test_dhcp_discovery_non_intellifire_device( hass: HomeAssistant, mock_intellifire_config_flow: MagicMock, mock_setup_entry: AsyncMock, ) -> None: """Test failed DHCP Discovery.""" mock_intellifire_config_flow.poll.side_effect = ConnectionError result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_DHCP}, data=dhcp.DhcpServiceInfo( ip="1.1.1.1", macaddress="AA:BB:CC:DD:EE:FF", hostname="zentrios-Evil", ), ) assert result["type"] == "abort" assert result["reason"] == "not_intellifire_device"

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100

0.681399

1,045

8,779

5.456459

0.121531

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0.073658

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0.821817

0.790951

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0.714135

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0

null

0

1

0

null

0

6

129ad3d48081ec0e1b77ba778d2fde2371b7fd16

13,653

py

Python

public_interface/forms.py

danmcelroy/VoSeq

e22bd5d971154170bf3f4f24b684b95a12418637

[ "BSD-3-Clause" ]

2

2019-08-20T04:16:12.000Z

2020-08-25T02:05:12.000Z

public_interface/forms.py

danmcelroy/VoSeq

e22bd5d971154170bf3f4f24b684b95a12418637

[ "BSD-3-Clause" ]

65

2016-09-27T23:14:51.000Z

2022-03-19T14:17:58.000Z

public_interface/forms.py

danmcelroy/VoSeq

e22bd5d971154170bf3f4f24b684b95a12418637

[ "BSD-3-Clause" ]

4

2018-07-02T16:57:44.000Z

2021-03-23T02:12:15.000Z

import datetime from functools import partial from typing import Dict, Tuple from django import forms from haystack.forms import ModelSearchForm from haystack.query import SearchQuerySet from Bio.Alphabet import IUPAC from public_interface.models import Genes, Vouchers, Sequences DateInput = partial(forms.DateInput, {'class': 'datepicker form-control', 'placeholder': 'Type or pick a date'}) class SequencesAdminForm(forms.ModelForm): def clean_sequences(self) -> str: valid_letters = set(IUPAC.ambiguous_dna.letters.upper() + 'N?-') sequence = str(self.cleaned_data['sequences']) for nucleotide in sequence: if nucleotide == ' ': self.add_error('sequences', "White spaces are not valid. " "Cannot save this sequence") elif not valid_letters.issuperset(nucleotide.upper()): self.add_error('sequences', "The character {} is not valid. " "Cannot save this sequence".format(nucleotide)) return sequence class AdvancedSearchForm(ModelSearchForm): NULL = 'Select' MALE = 'male' FEMALE = 'female' LARVA = 'larva' WORKER = 'worker' QUEEN = 'queen' UNKNOWN = 'unknown' SEX_CHOICES = ( (NULL, 'Select'), (MALE, 'male'), (FEMALE, 'female'), (LARVA, 'larva'), (WORKER, 'worker'), (QUEEN, 'queen'), (UNKNOWN, 'unknown'), ) NULL = 'Select' DONT_KNOW = 'unknown' YES = 'yes' NO = 'not' TYPE_SPECIES_CHOICES = ( (NULL, 'Select'), (DONT_KNOW, 'unknown'), (YES, 'yes'), (NO, 'not'), ) NULL = 'Select' SPREAD = 'spread' ENVELOPE = 'in envelope' PHOTO = 'only photo' NONE = 'no voucher' DESTROYED = 'destroyed' LOST = 'lost' VOUCHER_CHOICES = ( (NULL, 'Select'), (SPREAD, 'spread'), (ENVELOPE, 'in envelope'), (PHOTO, 'only photo'), (NONE, 'no voucher'), (DESTROYED, 'destroyed'), (LOST, 'lost'), (UNKNOWN, 'unknown'), ) code = forms.CharField(label="Code in voseq", max_length=100, required=False) orden = forms.CharField(label="Order", max_length=100, required=False) superfamily = forms.CharField(label="Superfamily", max_length=100, required=False) family = forms.CharField(label="Family", max_length=100, required=False) subfamily = forms.CharField(label="Subfamily", max_length=100, required=False) tribe = forms.CharField(label="Tribe", max_length=100, required=False) subtribe = forms.CharField(label="Subtribe", max_length=100, required=False) genus = forms.CharField(label="Genus", max_length=100, required=False) species = forms.CharField(label="Species", max_length=100, required=False) subspecies = forms.CharField(label="Subspecies", max_length=100, required=False) country = forms.CharField(label="Country", max_length=100, required=False) specific_locality = forms.CharField( label="Specific Locality", max_length=250, required=False) type_species = forms.ChoiceField( label="Type species", choices=TYPE_SPECIES_CHOICES, widget=forms.Select(attrs={'class': 'form-control'}), required=False) latitude = forms.FloatField(label="Latitude", required=False) longitude = forms.FloatField(label="Longitude", required=False) max_altitude = forms.IntegerField(label="Maximum altitude", required=False) min_altitude = forms.IntegerField(label="Minimum altitude", required=False) collector = forms.CharField(label="Collector", max_length=100, required=False) date_collection = forms.DateField( label="Date of collection start", required=False, widget=DateInput(), error_messages={'invalid': 'Enter valid date: YYYY-mm-dd'}, ) date_collection_end = forms.DateField( label="Date of collection end", required=False, widget=DateInput(), error_messages={'invalid': 'Enter valid date: YYYY-mm-dd'}, ) extraction = forms.CharField( label="Extraction", max_length=50, help_text="Number of extraction event.", required=False) extraction_tube = forms.CharField( label="Extraction tube", max_length=50, help_text="Tube containing DNA extract.", required=False) date_extraction = forms.DateField( label="Date of extraction", required=False, widget=DateInput(), error_messages={'invalid': 'Enter valid date: YYYY-mm-dd'}) extractor = forms.CharField(label="Extractor", max_length=100, required=False) voucher_locality = forms.CharField( label="Voucher locality", max_length=200, required=False) published_in = forms.CharField(label="Published in", required=False) notes = forms.CharField(label="Notes", required=False) latest_editor = forms.CharField(label="Latest editor", required=False) hostorg = forms.CharField( label="Host organism", max_length=200, help_text="Hostplant or other host.", required=False) sex = forms.ChoiceField(label="Sex", choices=SEX_CHOICES, required=False, widget=forms.Select(attrs={'class': 'form-control'})) voucher = forms.ChoiceField( label="Voucher", choices=VOUCHER_CHOICES, required=False, widget=forms.Select(attrs={'class': 'form-control'})) voucher_code = forms.CharField( label="Alternative voucher code", max_length=100, help_text="Original code of voucher specimen.", required=False) code_bold = forms.CharField( label="Code in BOLD database", max_length=100, help_text="Optional code for specimens kept in the BOLD database.", required=False) determined_by = forms.CharField( label="Determined by", max_length=100, help_text="Person that identified the taxon for this specimen.", required=False) author = forms.CharField( label="Author", max_length=100, help_text="Person that described this taxon.", required=False) # Sequences model YES = 'y' NO = 'n' GENBANK_CHOICES = ( (YES, 'Yes'), (NO, 'No'), ) gene_code = forms.ModelChoiceField( Genes.objects.all().order_by('gene_code'), required=False, widget=forms.Select(attrs={'class': 'form-control'}), empty_label='Select', ) genbank = forms.ChoiceField( widget=forms.RadioSelect, choices=GENBANK_CHOICES, required=False) accession = forms.CharField(max_length=100, required=False) lab_person = forms.CharField(max_length=100, required=False) def no_query_found(self): sqs = SearchQuerySet.none return sqs def search(self): keywords, sequence_keywords = self.clean_search_keywords() sqs = '' if keywords and not sequence_keywords: sqs = Vouchers.objects.filter(**keywords).distinct("code") elif sequence_keywords and not keywords: sqs = Sequences.objects.filter(**sequence_keywords).distinct("code") elif sequence_keywords and keywords: sqs = Vouchers.objects.filter(**keywords).distinct("code") if sqs: voucher_list = sqs sqs = Sequences.objects.filter(**sequence_keywords).filter( code__in=voucher_list).distinct("code") else: self.no_query_found() if not sqs: self.no_query_found() return sqs def clean_search_keywords(self) -> Tuple[Dict[str, str], Dict[str, str]]: keywords = {} sequence_keywords = {} for key, value in self.cleaned_data.items(): if value in ['', None, 'Select', 'models'] or key == "models": continue if key in ['date_collection', 'date_collection_end', 'date_extraction']: value = datetime.date.strftime(value, "%Y-%m-%d") if key in ['lab_person', 'accession']: new_key = "{}__icontains".format(key) sequence_keywords[new_key] = value if key == 'gene_code': new_key = "gene__gene_code" sequence_keywords[new_key] = value.gene_code if key == 'genbank' and value == 'y': sequence_keywords[key] = True elif key == 'genbank': sequence_keywords[key] = False if key not in ['lab_person', 'accession', 'genbank', 'gene_code']: new_key = "{}__icontains".format(key) keywords[new_key] = value return keywords, sequence_keywords # The following form is for the admin site batch_changes action # It would be nice not to repeat the lines from the previous # model, but... class BatchChangesForm(forms.Form): NULL = None MALE = 'male' FEMALE = 'female' LARVA = 'larva' WORKER = 'worker' QUEEN = 'queen' SEX_CHOICES = ( (NULL, 'Select'), (MALE, 'male'), (FEMALE, 'female'), (LARVA, 'larva'), (WORKER, 'worker'), (QUEEN, 'queen'), ) NULL = None DONT_KNOW = 'unknown' YES = 'yes' NO = 'not' TYPE_SPECIES_CHOICES = ( (NULL, 'Select'), (DONT_KNOW, 'unknown'), (YES, 'yes'), (NO, 'not'), ) NULL = None SPREAD = 'spread' ENVELOPE = 'in envelope' PHOTO = 'only photo' NONE = 'no voucher' DESTROYED = 'destroyed' LOST = 'lost' VOUCHER_CHOICES = ( (NULL, 'Select'), (SPREAD, 'spread'), (ENVELOPE, 'in envelope'), (PHOTO, 'only photo'), (NONE, 'no voucher'), (DESTROYED, 'destroyed'), (LOST, 'lost'), ) code = forms.CharField(label="Code in voseq", max_length=100, required=False) orden = forms.CharField(label="Order", max_length=100, required=False) superfamily = forms.CharField(label="Superfamily", max_length=100, required=False) family = forms.CharField(label="Family", max_length=100, required=False) subfamily = forms.CharField(label="Subfamily", max_length=100, required=False) tribe = forms.CharField(label="Tribe", max_length=100, required=False) subtribe = forms.CharField(label="Subtribe", max_length=100, required=False) genus = forms.CharField(label="Genus", max_length=100, required=False) species = forms.CharField(label="Species", max_length=100, required=False) subspecies = forms.CharField(label="Subspecies", max_length=100, required=False) country = forms.CharField(label="Country", max_length=100, required=False) specific_locality = forms.CharField( label="Specific Locality", max_length=250, required=False) type_species = forms.ChoiceField( label="Type species", choices=TYPE_SPECIES_CHOICES, widget=forms.Select, required=False) latitude = forms.FloatField(label="Latitude", required=False) longitude = forms.FloatField(label="Longitude", required=False) max_altitude = forms.IntegerField(label="Maximum altitude", required=False) min_altitude = forms.IntegerField(label="Minimum altitude", required=False) collector = forms.CharField(label="Collector", max_length=100, required=False) date_collection = forms.DateField(label="Date of collection start", required=False) date_collection_end = forms.DateField(label="Date of collection end", required=False) extraction = forms.CharField( label="Extraction", max_length=50, help_text="Number of extraction event.", required=False) extraction_tube = forms.CharField( label="Extraction tube", max_length=50, help_text="Tube containing DNA extract.", required=False) date_extraction = forms.DateField(label="Date extraction", required=False) extractor = forms.CharField(label="Extractor", max_length=100, required=False) voucher_locality = forms.CharField( label="Voucher locality", max_length=200, required=False) published_in = forms.CharField(label="Published in", required=False) notes = forms.CharField(label="Notes", required=False) latest_editor = forms.CharField(label="Latest editor", required=False) hostorg = forms.CharField( label="Host organism", max_length=200, help_text="Hostplant or other host.", required=False) sex = forms.ChoiceField( label="Sex", choices=SEX_CHOICES, required=False) voucher = forms.ChoiceField( label="Voucher", choices=VOUCHER_CHOICES, required=False) voucher_code = forms.CharField( label="Alternative voucher code", max_length=100, help_text="Original code of voucher specimen.", required=False) code_bold = forms.CharField( label="Code in BOLD database", max_length=100, help_text="Optional code for specimens kept in the BOLD database.", required=False) determined_by = forms.CharField( label="Determined by", max_length=100, help_text="Person that identified the taxon for this specimen.", required=False) author = forms.CharField( label="Author", max_length=100, help_text="Person that described this taxon.", required=False)

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0.113813

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13,653

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false

0

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0

null

0

1

0

1

0

null

0

6

129f0fd8b898761dbcc8164d8b0b44a5402304e6

3,792

py

Python

tools/upgrade/codemods.py

tahmidbintaslim/pyre-check

59d694f7733d7b160ecaddbe79d5d79cef0e83bc

[ "MIT" ]

null

tools/upgrade/codemods.py

tahmidbintaslim/pyre-check

59d694f7733d7b160ecaddbe79d5d79cef0e83bc

[ "MIT" ]

null

tools/upgrade/codemods.py

tahmidbintaslim/pyre-check

59d694f7733d7b160ecaddbe79d5d79cef0e83bc

[ "MIT" ]

null

# Copyright (c) 2016-present, Facebook, Inc. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import logging import pathlib import re from logging import Logger from .commands.command import Command from .errors import Errors LOG: Logger = logging.getLogger(__name__) class MissingOverrideReturnAnnotations(Command): def run(self) -> None: errors = Errors.from_stdin(self._arguments.only_fix_error_code) for path, errors in errors: LOG.info("Patching errors in `%s`.", path) errors = sorted(errors, key=lambda error: error["line"], reverse=True) # pyre-fixme[6]: Expected `Union[_PathLike[str], str]` for 1st param but got # `Union[typing.Iterator[typing.Dict[str, typing.Any]], str]`. path = pathlib.Path(path) lines = path.read_text().split("\n") for error in errors: # pyre-fixme[6]: Expected `Union[int, slice]` for 1st param but got # `str`. if error["code"] != 15: continue # pyre-fixme[6]: Expected `int` for 1st param but got `str`. # pyre-fixme[6]: Expected `Union[int, slice]` for 1st param but got # `str`. line = error["line"] - 1 # pyre-fixme[6]: Expected `Union[int, slice]` for 1st param but got # `str`. match = re.match(r".*`(.*)`\.", error["description"]) if not match: continue annotation = match.groups()[0] # Find last closing parenthesis in after line. LOG.info("Looking at %d: %s", line, lines[line]) while True: if "):" in lines[line]: lines[line] = lines[line].replace("):", ") -> %s:" % annotation) LOG.info("%d: %s", line, lines[line]) break else: line = line + 1 LOG.warn("Writing patched %s", str(path)) path.write_text("\n".join(lines)) class MissingGlobalAnnotations(Command): def run(self) -> None: errors = Errors.from_stdin(self._arguments.only_fix_error_code) for path, errors in errors: LOG.info("Patching errors in `%s`", path) errors = sorted(errors, key=lambda error: error["line"], reverse=True) # pyre-fixme[6]: Expected `Union[_PathLike[str], str]` for 1st param but got # `Union[typing.Iterator[typing.Dict[str, typing.Any]], str]`. path = pathlib.Path(path) lines = path.read_text().split("\n") for error in errors: # pyre-fixme[6]: Expected `Union[int, slice]` for 1st param but got # `str`. if error["code"] != 5: continue # pyre-fixme[6]: Expected `int` for 1st param but got `str`. # pyre-fixme[6]: Expected `Union[int, slice]` for 1st param but got # `str`. line = error["line"] - 1 # pyre-fixme[6]: Expected `Union[int, slice]` for 1st param but got # `str`. match = re.match(r".*`.*`.*`(.*)`.*", error["description"]) if not match: continue annotation = match.groups()[0] LOG.info("Looking at %d: %s", line, lines[line]) if " =" in lines[line]: lines[line] = lines[line].replace(" =", ": %s =" % annotation) LOG.info("%d: %s", line, lines[line]) path.write_text("\n".join(lines))

39.5

88

0.513977

435

3,792

4.434483

0.248276

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0.05184

0.093313

0.776568

0.752722

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0

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3,792

95

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0

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0

null

0

1

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null

0

1

0

6

12bd33b688e68fdf725b49f7af6e6fae034847c5

210

py

Python

fem/gui/vtk_widget/vtk_graphics/picking/__init__.py

mjredmond/FEMApp

dd8cc53acf80d0a1bb83ce9c89bcfd51e85c6be8

[ "MIT" ]

1

2019-08-03T21:40:26.000Z

fem/gui/vtk_widget/vtk_graphics/picking/__init__.py

mjredmond/FEMApp

dd8cc53acf80d0a1bb83ce9c89bcfd51e85c6be8

[ "MIT" ]

null

fem/gui/vtk_widget/vtk_graphics/picking/__init__.py

mjredmond/FEMApp

dd8cc53acf80d0a1bb83ce9c89bcfd51e85c6be8

[ "MIT" ]

null

from __future__ import print_function, absolute_import from .box_picker import BoxPicker from .picking_manager import PickingManager from .poly_picker import PolyPicker from .single_picker import SinglePicker

30

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py

Python

wavepy3/__init__.py

alexrkaufman/WavePy3

1f5fc05b7c245975157eb77fab4201e3bd2cca5c

[ "Apache-2.0" ]

5

2020-11-17T11:58:19.000Z

2021-10-29T21:29:31.000Z

wavepy3/__init__.py

alexrkaufman/WavePy3

1f5fc05b7c245975157eb77fab4201e3bd2cca5c

[ "Apache-2.0" ]

3

2020-10-29T23:28:10.000Z

2020-10-30T17:01:12.000Z

wavepy3/__init__.py

alexrkaufman/WavePy3

1f5fc05b7c245975157eb77fab4201e3bd2cca5c

[ "Apache-2.0" ]

1

2020-10-23T00:58:32.000Z

from .atmos import Atmos from .constraint_analysis import constraint_analysis from .prop import split_step from . import analytic from . import sources

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py

Python

glosysnet/__init__.py

NareshAtnPLUS/glosysnet

e85df44727b8784766be7e728267e5699997e226

[ "MIT" ]

null

glosysnet/__init__.py

NareshAtnPLUS/glosysnet

e85df44727b8784766be7e728267e5699997e226

[ "MIT" ]

null

glosysnet/__init__.py

NareshAtnPLUS/glosysnet

e85df44727b8784766be7e728267e5699997e226

[ "MIT" ]

null

from glosysnet.nn import * from glosysnet.vision import *

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py

Python

misc/import_this.py

fcracker79/python_misc

be661a09a806010e440015b8caeb5e06773bb533

[ "MIT" ]

null

misc/import_this.py

fcracker79/python_misc

be661a09a806010e440015b8caeb5e06773bb533

[ "MIT" ]

null

misc/import_this.py

fcracker79/python_misc

be661a09a806010e440015b8caeb5e06773bb533

[ "MIT" ]

null

import accrocchio import this

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py

Python

tests/unit/test_spatial_methods/test_spectral_volume.py

katiezzzzz/PyBaMM

0b0fc47125c0f078da99a58f497e0700eb25225a

[ "BSD-3-Clause" ]

1

2021-03-06T15:10:34.000Z

tests/unit/test_spatial_methods/test_spectral_volume.py

katiezzzzz/PyBaMM

0b0fc47125c0f078da99a58f497e0700eb25225a

[ "BSD-3-Clause" ]

null

tests/unit/test_spatial_methods/test_spectral_volume.py

katiezzzzz/PyBaMM

0b0fc47125c0f078da99a58f497e0700eb25225a

[ "BSD-3-Clause" ]

null

# # Test for the operator class # import pybamm import numpy as np import unittest def get_mesh_for_testing( xpts=None, rpts=10, ypts=15, zpts=15, geometry=None, cc_submesh=None, order=2 ): param = pybamm.ParameterValues( values={ "Electrode width [m]": 0.4, "Electrode height [m]": 0.5, "Negative tab width [m]": 0.1, "Negative tab centre y-coordinate [m]": 0.1, "Negative tab centre z-coordinate [m]": 0.0, "Positive tab width [m]": 0.1, "Positive tab centre y-coordinate [m]": 0.3, "Positive tab centre z-coordinate [m]": 0.5, "Negative electrode thickness [m]": 0.3, "Separator thickness [m]": 0.3, "Positive electrode thickness [m]": 0.3, } ) if geometry is None: geometry = pybamm.battery_geometry() param.process_geometry(geometry) submesh_types = { "negative electrode": pybamm.MeshGenerator( pybamm.SpectralVolume1DSubMesh, {"order": order} ), "separator": pybamm.MeshGenerator(pybamm.SpectralVolume1DSubMesh, {"order": order}), "positive electrode": pybamm.MeshGenerator( pybamm.SpectralVolume1DSubMesh, {"order": order} ), "negative particle": pybamm.MeshGenerator( pybamm.SpectralVolume1DSubMesh, {"order": order} ), "positive particle": pybamm.MeshGenerator( pybamm.SpectralVolume1DSubMesh, {"order": order} ), "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), } if cc_submesh: submesh_types["current collector"] = cc_submesh if xpts is None: xn_pts, xs_pts, xp_pts = 40, 25, 35 else: xn_pts, xs_pts, xp_pts = xpts, xpts, xpts var = pybamm.standard_spatial_vars var_pts = { var.x_n: xn_pts, var.x_s: xs_pts, var.x_p: xp_pts, var.r_n: rpts, var.r_p: rpts, var.y: ypts, var.z: zpts, } return pybamm.Mesh(geometry, submesh_types, var_pts) def get_p2d_mesh_for_testing(xpts=None, rpts=10): geometry = pybamm.battery_geometry() return get_mesh_for_testing(xpts=xpts, rpts=rpts, geometry=geometry) def get_1p1d_mesh_for_testing( xpts=None, rpts=10, zpts=15, cc_submesh=pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), ): geometry = pybamm.battery_geometry(current_collector_dimension=1) return get_mesh_for_testing( xpts=xpts, rpts=rpts, zpts=zpts, geometry=geometry, cc_submesh=cc_submesh ) class TestSpectralVolume(unittest.TestCase): def test_exceptions(self): sp_meth = pybamm.SpectralVolume() with self.assertRaises(ValueError): sp_meth.chebyshev_differentiation_matrices(3, 3) mesh = get_mesh_for_testing() spatial_methods = {"macroscale": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) whole_cell = ["negative electrode", "separator", "positive electrode"] var = pybamm.Variable("var", domain=whole_cell) disc.set_variable_slices([var]) discretised_symbol = pybamm.StateVector(*disc.y_slices[var.id]) sp_meth.build(mesh) bcs = {"left": (pybamm.Scalar(0), "x"), "right": (pybamm.Scalar(3), "Neumann")} with self.assertRaisesRegex(ValueError, "boundary condition must be"): sp_meth.replace_dirichlet_values(var, discretised_symbol, bcs) with self.assertRaisesRegex(ValueError, "boundary condition must be"): sp_meth.replace_neumann_values(var, discretised_symbol, bcs) bcs = {"left": (pybamm.Scalar(0), "Neumann"), "right": (pybamm.Scalar(3), "x")} with self.assertRaisesRegex(ValueError, "boundary condition must be"): sp_meth.replace_dirichlet_values(var, discretised_symbol, bcs) with self.assertRaisesRegex(ValueError, "boundary condition must be"): sp_meth.replace_neumann_values(var, discretised_symbol, bcs) def test_grad_div_shapes_Dirichlet_bcs(self): """ Test grad and div with Dirichlet boundary conditions (applied by grad on var) and also test the case where only one Spectral Volume is discretised """ whole_cell = ["negative electrode", "separator", "positive electrode"] # create discretisation mesh = get_mesh_for_testing(1) spatial_methods = {"macroscale": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) combined_submesh = mesh.combine_submeshes(*whole_cell) # grad var = pybamm.Variable("var", domain=whole_cell) grad_eqn = pybamm.grad(var) boundary_conditions = { var.id: { "left": (pybamm.Scalar(1), "Dirichlet"), "right": (pybamm.Scalar(1), "Dirichlet"), } } disc.bcs = boundary_conditions disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(grad_eqn) constant_y = np.ones_like(combined_submesh.nodes[:, np.newaxis]) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, constant_y), np.zeros_like(combined_submesh.edges[:, np.newaxis]), ) # div: test on linear y (should have laplacian zero) so change bcs linear_y = combined_submesh.nodes N = pybamm.grad(var) div_eqn = pybamm.div(N) boundary_conditions = { var.id: { "left": (pybamm.Scalar(0), "Dirichlet"), "right": (pybamm.Scalar(1), "Dirichlet"), } } disc.bcs = boundary_conditions grad_eqn_disc = disc.process_symbol(grad_eqn) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, linear_y), np.ones_like(combined_submesh.edges[:, np.newaxis]), ) div_eqn_disc = disc.process_symbol(div_eqn) np.testing.assert_array_almost_equal( div_eqn_disc.evaluate(None, linear_y), np.zeros_like(combined_submesh.nodes[:, np.newaxis]), ) def test_grad_1plus1d(self): mesh = get_1p1d_mesh_for_testing() spatial_methods = {"macroscale": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) a = pybamm.Variable( "a", domain=["negative electrode"], auxiliary_domains={"secondary": "current collector"}, ) b = pybamm.Variable( "b", domain=["separator"], auxiliary_domains={"secondary": "current collector"}, ) c = pybamm.Variable( "c", domain=["positive electrode"], auxiliary_domains={"secondary": "current collector"}, ) var = pybamm.Concatenation(a, b, c) boundary_conditions = { var.id: { "left": (pybamm.Vector(np.linspace(0, 1, 15)), "Neumann"), "right": (pybamm.Vector(np.linspace(0, 1, 15)), "Neumann"), } } disc.bcs = boundary_conditions disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(pybamm.grad(var)) # Evaulate combined_submesh = mesh.combine_submeshes(*var.domain) linear_y = np.outer(np.linspace(0, 1, 15), combined_submesh.nodes).reshape( -1, 1 ) expected = np.outer( np.linspace(0, 1, 15), np.ones_like(combined_submesh.edges) ).reshape(-1, 1) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, linear_y), expected ) def test_spherical_grad_div_shapes_Dirichlet_bcs(self): """ Test grad and div with Dirichlet boundary conditions (applied by grad on var) """ # create discretisation mesh = get_1p1d_mesh_for_testing() spatial_methods = {"negative particle": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) submesh = mesh["negative particle"] # grad # grad(r) == 1 var = pybamm.Variable( "var", domain=["negative particle"], auxiliary_domains={ "secondary": "negative electrode", "tertiary": "current collector", }, ) grad_eqn = pybamm.grad(var) boundary_conditions = { var.id: { "left": (pybamm.Scalar(1), "Dirichlet"), "right": (pybamm.Scalar(1), "Dirichlet"), } } disc.bcs = boundary_conditions disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(grad_eqn) total_npts = ( submesh.npts * mesh["negative electrode"].npts * mesh["current collector"].npts ) total_npts_edges = ( (submesh.npts + 1) * mesh["negative electrode"].npts * mesh["current collector"].npts ) constant_y = np.ones((total_npts, 1)) np.testing.assert_array_equal( grad_eqn_disc.evaluate(None, constant_y), np.zeros((total_npts_edges, 1)) ) boundary_conditions = { var.id: { "left": (pybamm.Scalar(0), "Dirichlet"), "right": (pybamm.Scalar(1), "Dirichlet"), } } disc.bcs = boundary_conditions y_linear = np.tile( submesh.nodes, mesh["negative electrode"].npts * mesh["current collector"].npts, ) grad_eqn_disc = disc.process_symbol(grad_eqn) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, y_linear), np.ones((total_npts_edges, 1)) ) # div: test on linear r^2 # div (grad r^2) = 6 const = 6 * np.ones((total_npts, 1)) N = pybamm.grad(var) div_eqn = pybamm.div(N) boundary_conditions = { var.id: { "left": (pybamm.Scalar(6), "Dirichlet"), "right": (pybamm.Scalar(6), "Dirichlet"), } } disc.bcs = boundary_conditions div_eqn_disc = disc.process_symbol(div_eqn) np.testing.assert_array_almost_equal( div_eqn_disc.evaluate(None, const), np.zeros( ( submesh.npts * mesh["negative electrode"].npts * mesh["current collector"].npts, 1, ) ), ) def test_p2d_spherical_grad_div_shapes_Dirichlet_bcs(self): """ Test grad and div with Dirichlet boundary conditions (applied by grad on var) in the pseudo 2-dimensional case """ mesh = get_p2d_mesh_for_testing() spatial_methods = { "macroscale": pybamm.SpectralVolume(), "negative particle": pybamm.SpectralVolume(), "positive particle": pybamm.SpectralVolume(), } disc = pybamm.Discretisation(mesh, spatial_methods) n_mesh = mesh["negative particle"] mesh.add_ghost_meshes() disc.mesh.add_ghost_meshes() var = pybamm.Variable( "var", domain=["negative particle"], auxiliary_domains={"secondary": "negative electrode"}, ) grad_eqn = pybamm.grad(var) boundary_conditions = { var.id: { "left": (pybamm.Scalar(1), "Dirichlet"), "right": (pybamm.Scalar(1), "Dirichlet"), } } disc.bcs = boundary_conditions disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(grad_eqn) prim_pts = n_mesh.npts sec_pts = mesh["negative electrode"].npts constant_y = np.kron(np.ones(sec_pts), np.ones(prim_pts)) grad_eval = grad_eqn_disc.evaluate(None, constant_y) grad_eval = np.reshape(grad_eval, [sec_pts, prim_pts + 1]) np.testing.assert_array_equal(grad_eval, np.zeros([sec_pts, prim_pts + 1])) # div # div (grad r^2) = 6, N_left = N_right = 0 N = pybamm.grad(var) div_eqn = pybamm.div(N) bc_var = disc.process_symbol( pybamm.SpatialVariable("x_n", domain="negative electrode") ) boundary_conditions = { var.id: {"left": (bc_var, "Neumann"), "right": (bc_var, "Neumann")} } disc.bcs = boundary_conditions div_eqn_disc = disc.process_symbol(div_eqn) const = 6 * np.ones(sec_pts * prim_pts) div_eval = div_eqn_disc.evaluate(None, const) div_eval = np.reshape(div_eval, [sec_pts, prim_pts]) np.testing.assert_array_almost_equal( div_eval[:, :-1], np.zeros([sec_pts, prim_pts - 1]) ) def test_grad_div_shapes_Neumann_bcs(self): """Test grad and div with Neumann boundary conditions (applied by div on N)""" whole_cell = ["negative electrode", "separator", "positive electrode"] # create discretisation mesh = get_mesh_for_testing() spatial_methods = {"macroscale": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) combined_submesh = mesh.combine_submeshes(*whole_cell) # grad var = pybamm.Variable("var", domain=whole_cell) grad_eqn = pybamm.grad(var) disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(grad_eqn) constant_y = np.ones_like(combined_submesh.nodes[:, np.newaxis]) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, constant_y), np.zeros_like(combined_submesh.edges[:][:, np.newaxis]), ) # div N = pybamm.grad(var) div_eqn = pybamm.div(N) boundary_conditions = { var.id: { "left": (pybamm.Scalar(1), "Neumann"), "right": (pybamm.Scalar(1), "Neumann"), } } disc.bcs = boundary_conditions div_eqn_disc = disc.process_symbol(div_eqn) # Linear y should have laplacian zero linear_y = combined_submesh.nodes np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, linear_y), np.ones_like(combined_submesh.edges[:][:, np.newaxis]), ) np.testing.assert_array_almost_equal( div_eqn_disc.evaluate(None, linear_y), np.zeros_like(combined_submesh.nodes[:, np.newaxis]), ) def test_grad_div_shapes_Dirichlet_and_Neumann_bcs(self): """ Test grad and div with Dirichlet boundary conditions (applied by grad on c) on one side and Neumann boundary conditions (applied by div on N) on the other """ whole_cell = ["negative electrode", "separator", "positive electrode"] # create discretisation mesh = get_mesh_for_testing() spatial_methods = {"macroscale": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) combined_submesh = mesh.combine_submeshes(*whole_cell) # grad var = pybamm.Variable("var", domain=whole_cell) grad_eqn = pybamm.grad(var) disc.set_variable_slices([var]) # div N = pybamm.grad(var) div_eqn = pybamm.div(N) boundary_conditions = { var.id: { "left": (pybamm.Scalar(1), "Dirichlet"), "right": (pybamm.Scalar(0), "Neumann"), } } disc.bcs = boundary_conditions grad_eqn_disc = disc.process_symbol(grad_eqn) div_eqn_disc = disc.process_symbol(div_eqn) # Constant y should have gradient and laplacian zero constant_y = np.ones_like(combined_submesh.nodes[:, np.newaxis]) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, constant_y), np.zeros_like(combined_submesh.edges[:, np.newaxis]), ) np.testing.assert_array_almost_equal( div_eqn_disc.evaluate(None, constant_y), np.zeros_like(combined_submesh.nodes[:, np.newaxis]), ) boundary_conditions = { var.id: { "left": (pybamm.Scalar(1), "Neumann"), "right": (pybamm.Scalar(1), "Dirichlet"), } } disc.bcs = boundary_conditions grad_eqn_disc = disc.process_symbol(grad_eqn) div_eqn_disc = disc.process_symbol(div_eqn) # Linear y should have gradient one and laplacian zero linear_y = combined_submesh.nodes np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, linear_y), np.ones_like(combined_submesh.edges[:, np.newaxis]), ) np.testing.assert_array_almost_equal( div_eqn_disc.evaluate(None, linear_y), np.zeros_like(combined_submesh.nodes[:, np.newaxis]), ) def test_spherical_grad_div_shapes_Neumann_bcs(self): """Test grad and div with Neumann boundary conditions (applied by div on N)""" # create discretisation mesh = get_mesh_for_testing() spatial_methods = {"negative particle": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) combined_submesh = mesh.combine_submeshes("negative particle") # grad var = pybamm.Variable("var", domain="negative particle") grad_eqn = pybamm.grad(var) disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(grad_eqn) constant_y = np.ones_like(combined_submesh.nodes[:, np.newaxis]) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, constant_y), np.zeros_like(combined_submesh.edges[:][:, np.newaxis]), ) linear_y = combined_submesh.nodes np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, linear_y), np.ones_like(combined_submesh.edges[:][:, np.newaxis]), ) # div # div ( grad(r^2) ) == 6 , N_left = N_right = 0 N = pybamm.grad(var) div_eqn = pybamm.div(N) boundary_conditions = { var.id: { "left": (pybamm.Scalar(0), "Neumann"), "right": (pybamm.Scalar(0), "Neumann"), } } disc.bcs = boundary_conditions div_eqn_disc = disc.process_symbol(div_eqn) linear_y = combined_submesh.nodes const = 6 * np.ones(combined_submesh.npts) np.testing.assert_array_almost_equal( div_eqn_disc.evaluate(None, const), np.zeros((combined_submesh.npts, 1)) ) def test_p2d_spherical_grad_div_shapes_Neumann_bcs(self): """ Test grad and div with Dirichlet boundary conditions (applied by grad on var) in the pseudo 2-dimensional case """ mesh = get_p2d_mesh_for_testing() spatial_methods = {"negative particle": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) n_mesh = mesh["negative particle"] mesh.add_ghost_meshes() disc.mesh.add_ghost_meshes() # test grad var = pybamm.Variable( "var", domain=["negative particle"], auxiliary_domains={"secondary": "negative electrode"}, ) grad_eqn = pybamm.grad(var) disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(grad_eqn) prim_pts = n_mesh.npts sec_pts = mesh["negative electrode"].npts constant_y = np.kron(np.ones(sec_pts), np.ones(prim_pts)) grad_eval = grad_eqn_disc.evaluate(None, constant_y) grad_eval = np.reshape(grad_eval, [sec_pts, prim_pts + 1]) np.testing.assert_array_equal(grad_eval, np.zeros([sec_pts, prim_pts + 1])) # div # div (grad r^2) = 6, N_left = N_right = 0 N = pybamm.grad(var) div_eqn = pybamm.div(N) boundary_conditions = { var.id: { "left": (pybamm.Scalar(0), "Neumann"), "right": (pybamm.Scalar(0), "Neumann"), } } disc.bcs = boundary_conditions div_eqn_disc = disc.process_symbol(div_eqn) const = 6 * np.ones(sec_pts * prim_pts) div_eval = div_eqn_disc.evaluate(None, const) div_eval = np.reshape(div_eval, [sec_pts, prim_pts]) np.testing.assert_array_almost_equal(div_eval, np.zeros([sec_pts, prim_pts])) def test_grad_div_shapes_mixed_domain(self): """ Test grad and div with Dirichlet boundary conditions (applied by grad on var) """ # create discretisation mesh = get_mesh_for_testing() spatial_methods = {"macroscale": pybamm.SpectralVolume()} disc = pybamm.Discretisation(mesh, spatial_methods) # grad var = pybamm.Variable("var", domain=["negative electrode", "separator"]) grad_eqn = pybamm.grad(var) boundary_conditions = { var.id: { "left": (pybamm.Scalar(1), "Dirichlet"), "right": (pybamm.Scalar(1), "Dirichlet"), } } disc.bcs = boundary_conditions disc.set_variable_slices([var]) grad_eqn_disc = disc.process_symbol(grad_eqn) combined_submesh = mesh.combine_submeshes("negative electrode", "separator") constant_y = np.ones_like(combined_submesh.nodes[:, np.newaxis]) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, constant_y), np.zeros_like(combined_submesh.edges[:, np.newaxis]), ) # div: test on linear y (should have laplacian zero) so change bcs linear_y = combined_submesh.nodes N = pybamm.grad(var) div_eqn = pybamm.div(N) boundary_conditions = { var.id: { "left": (pybamm.Scalar(0), "Dirichlet"), "right": (pybamm.Scalar(combined_submesh.edges[-1]), "Dirichlet"), } } disc.bcs = boundary_conditions grad_eqn_disc = disc.process_symbol(grad_eqn) np.testing.assert_array_almost_equal( grad_eqn_disc.evaluate(None, linear_y), np.ones_like(combined_submesh.edges[:, np.newaxis]), ) div_eqn_disc = disc.process_symbol(div_eqn) np.testing.assert_array_almost_equal( div_eqn_disc.evaluate(None, linear_y), np.zeros_like(combined_submesh.nodes[:, np.newaxis]), ) if __name__ == "__main__": print("Add -v for more debug output") import sys if "-v" in sys.argv: debug = True pybamm.settings.debug_mode = True unittest.main()

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426af98da3c39994539ab6283c20b26e411835b7

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py

Python

pyPackage/__init__.py

20centcroak/pyPackage

521cdb8312ebfaf005744e077d783814175a2304

[ "MIT" ]

null

pyPackage/__init__.py

20centcroak/pyPackage

521cdb8312ebfaf005744e077d783814175a2304

[ "MIT" ]

null

pyPackage/__init__.py

20centcroak/pyPackage

521cdb8312ebfaf005744e077d783814175a2304

[ "MIT" ]

null

from pyPackage.options import Options from pyPackage.package import Package

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py

Python

sumospeak/traciwrapper/__init__.py

NASGregorio/sumospeak

3ea1415a381a2eb5a97eb0d8842f4f0d9bd7a4d7

[ "MIT" ]

null

sumospeak/traciwrapper/__init__.py

NASGregorio/sumospeak

3ea1415a381a2eb5a97eb0d8842f4f0d9bd7a4d7

[ "MIT" ]

null

sumospeak/traciwrapper/__init__.py

NASGregorio/sumospeak

3ea1415a381a2eb5a97eb0d8842f4f0d9bd7a4d7

[ "MIT" ]

null

from .traciwrapper import TraCIWrapper, SUMO_START, SUMO_STEP, SUMO_ARRIVAL, SUMO_CLOSE, SUMO_PHASE_LIST

104

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104

5.6

0.666667

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104

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104

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1

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1

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6

c420334440fcb7297e6bb09c69b615729cc98d70

6,357

py

Python

py/orbit/diagnostics/TeapotDiagnosticsNode.py

austin-hoover/py-orbit

cd3dbdd5d75a5a4a3fcf2ec079c898d760282b02

[ "MIT" ]

null

py/orbit/diagnostics/TeapotDiagnosticsNode.py

austin-hoover/py-orbit

cd3dbdd5d75a5a4a3fcf2ec079c898d760282b02

[ "MIT" ]

null

py/orbit/diagnostics/TeapotDiagnosticsNode.py

austin-hoover/py-orbit

cd3dbdd5d75a5a4a3fcf2ec079c898d760282b02

[ "MIT" ]

null

""" This module is a collimator node class for TEAPOT lattice """ import os import math # import the auxiliary classes from orbit.utils import orbitFinalize, NamedObject, ParamsDictObject # import general accelerator elements and lattice from orbit.lattice import AccNode, AccActionsContainer, AccNodeBunchTracker # import Diagnostics classes from diagnostics import StatLats, StatLatsSetMember from diagnostics import Moments, MomentsSetMember, BPMSignal # import teapot drift class from orbit.teapot import DriftTEAPOT #import Bunch diagnostics from bunch import BunchTuneAnalysis class TeapotStatLatsNode(DriftTEAPOT): """ The statlats node class for TEAPOT lattice """ def __init__(self, filename , name = "statlats no name"): """ Constructor. Creates the StatLats TEAPOT element. """ DriftTEAPOT.__init__(self,name) self.statlats = StatLats(filename) self.setType("statlats teapot") self.setLength(0.0) self.position = 0.0 self.lattlength = 0.0 self.file_out = open(filename,"w") def track(self, paramsDict): """ The statlats-teapot class implementation of the AccNodeBunchTracker class track(probe) method. """ length = self.getLength(self.getActivePartIndex()) bunch = paramsDict["bunch"] self.statlats.writeStatLats(self.position,bunch,self.lattlength) def setPosition(self,pos): self.position = pos def closeStatLats(self): self.file_out.close() def setLatticeLength(self, lattlength): self.lattlength = lattlength class TeapotStatLatsNodeSetMember(DriftTEAPOT): """ The statlats node class for TEAPOT lattice """ def __init__(self, file, name = "statlats no name"): """ Constructor. Creates the StatLats TEAPOT element. """ DriftTEAPOT.__init__(self,name) self.statlats = StatLatsSetMember(file) self.setType("statlats teapot") self.setLength(0.0) self.position = 0.0 self.lattlength = 0.0 self.active = True self.file = file def track(self, paramsDict): """ The statlats-teapot class implementation of the AccNodeBunchTracker class track(probe) method. """ if(self.active): length = self.getLength(self.getActivePartIndex()) bunch = paramsDict["bunch"] self.statlats.writeStatLats(self.position,bunch,self.lattlength) def setPosition(self,pos): self.position = pos def setLatticeLength(self, lattlength): self.lattlength = lattlength def activate(self): self.active = True def deactivate(self): self.active = False def resetFile(self, file): self.file = file self.statlats.resetFile(self.file) class TeapotMomentsNode(DriftTEAPOT): """ The moments node class for TEAPOT lattice """ def __init__(self, filename, order, nodispersion = True, emitnorm = False, name = "moments no name"): """ Constructor. Creates the StatLats TEAPOT element. """ DriftTEAPOT.__init__(self,name) self.moments = Moments(filename, order, nodispersion, emitnorm) self.setType("moments teapot") self.setLength(0.0) self.position = 0.0 self.lattlength = 0.0 self.file_out = open(filename,"w") def track(self, paramsDict): """ The moments-teapot class implementation of the AccNodeBunchTracker class track(probe) method. """ length = self.getLength(self.getActivePartIndex()) bunch = paramsDict["bunch"] self.moments.writeMoments(self.position,bunch,self.lattlength) def setPosition(self,pos): self.position = pos def closeMoments(self): self.file_out.close() def setLatticeLength(self, lattlength): self.lattlength = lattlength class TeapotMomentsNodeSetMember(DriftTEAPOT): """ The moments node class for TEAPOT lattice """ def __init__(self, file, order, nodispersion = True, emitnorm = False, name = "moments no name"): """ Constructor. Creates the Moments TEAPOT element. """ DriftTEAPOT.__init__(self,str(name)) self.file = file self.moments = MomentsSetMember(self.file, order, nodispersion, emitnorm) self.setType("moments teapot") self.setLength(0.0) self.position = 0.0 self.lattlength = 0.0 self.active = True def track(self, paramsDict): """ The moments-teapot class implementation of the AccNodeBunchTracker class track(probe) method. """ if(self.active): length = self.getLength(self.getActivePartIndex()) bunch = paramsDict["bunch"] self.moments.writeMoments(self.position, bunch, self.lattlength) def setPosition(self,pos): self.position = pos def setLatticeLength(self, lattlength): self.lattlength = lattlength def activate(self): self.active = True def deactivate(self): self.active = False def resetFile(self, file): self.file = file self.moments.resetFile(self.file) class TeapotTuneAnalysisNode(DriftTEAPOT): def __init__(self, name = "tuneanalysis no name"): """ Constructor. Creates the StatLats TEAPOT element. """ DriftTEAPOT.__init__(self,name) self.bunchtune = BunchTuneAnalysis() self.setType("tune calculator teapot") self.lattlength = 0.0 self.setLength(0.0) self.position = 0.0 def track(self, paramsDict): """ The bunchtuneanalysis-teapot class implementation of the AccNodeBunchTracker class track(probe) method. """ length = self.getLength(self.getActivePartIndex()) bunch = paramsDict["bunch"] self.bunchtune.analyzeBunch(bunch) def setPosition(self,pos): self.position = pos def setLatticeLength(self, lattlength): self.lattlength = lattlength def assignTwiss(self, betax, alphax, etax, etapx, betay, alphay): self.bunchtune.assignTwiss(betax, alphax, etax, etapx, betay, alphay) class TeapotBPMSignalNode(DriftTEAPOT): def __init__(self, name = "BPMSignal no name"): """ Constructor. Creates the StatLats TEAPOT element. """ DriftTEAPOT.__init__(self,name) self.bpm = BPMSignal() self.setType("BPMSignal") self.lattlength = 0.0 self.setLength(0.0) self.position = 0.0 def track(self, paramsDict): """ The bunchtuneanalysis-teapot class implementation of the AccNodeBunchTracker class track(probe) method. """ length = self.getLength(self.getActivePartIndex()) bunch = paramsDict["bunch"] self.bpm.analyzeSignal(bunch) def setPosition(self,pos): self.position = pos def setLatticeLength(self, lattlength): self.lattlength = lattlength def getSignal(self): xAvg = self.bpm.getSignalX() yAvg = self.bpm.getSignalY() return xAvg, yAvg

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6,357

243

106

26.160494

0.852848

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false

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0

null

0

1

0

null

0

1

0

6

c4332f962837980d336f231677daeea0d7511a01

2,841

py

Python

test/test_gpio_setup.py

olegantonyan/adafruit-beaglebone-io-python

36c5a136dfb93b40213b61e04b8bf760086015d0

[ "MIT" ]

null

test/test_gpio_setup.py

olegantonyan/adafruit-beaglebone-io-python

36c5a136dfb93b40213b61e04b8bf760086015d0

[ "MIT" ]

null

test/test_gpio_setup.py

olegantonyan/adafruit-beaglebone-io-python

36c5a136dfb93b40213b61e04b8bf760086015d0

[ "MIT" ]

null

import pytest import os import platform import Adafruit_BBIO.GPIO as GPIO kernel = platform.release() def teardown_module(module): GPIO.cleanup() class TestSetup: def test_setup_output_key(self): GPIO.setup("P8_10", GPIO.OUT) assert os.path.exists('/sys/class/gpio/gpio68') direction = open('/sys/class/gpio/gpio68/direction').read() assert direction == 'out\n' GPIO.cleanup() def test_setup_output_name(self): GPIO.setup("TIMER6", GPIO.OUT) assert os.path.exists('/sys/class/gpio/gpio68') direction = open('/sys/class/gpio/gpio68/direction').read() assert direction == 'out\n' GPIO.cleanup() def test_setup_input_key(self): GPIO.setup("P8_10", GPIO.IN) assert os.path.exists('/sys/class/gpio/gpio68') direction = open('/sys/class/gpio/gpio68/direction').read() assert direction == 'in\n' GPIO.cleanup() def test_setup_input_name(self): GPIO.setup("TIMER6", GPIO.IN) assert os.path.exists('/sys/class/gpio/gpio68') direction = open('/sys/class/gpio/gpio68/direction').read() assert direction == 'in\n' GPIO.cleanup() def test_setup_input_pull_up(self): GPIO.setup("P8_10", GPIO.IN, pull_up_down=GPIO.PUD_UP) assert os.path.exists('/sys/class/gpio/gpio68') direction = open('/sys/class/gpio/gpio68/direction').read() assert direction == 'in\n' GPIO.cleanup() def test_setup_input_pull_down(self): GPIO.setup("P8_10", GPIO.IN, pull_up_down=GPIO.PUD_DOWN) assert os.path.exists('/sys/class/gpio/gpio68') direction = open('/sys/class/gpio/gpio68/direction').read() assert direction == 'in\n' GPIO.cleanup() def test_setup_cleanup(self): GPIO.setup("P8_10", GPIO.OUT) assert os.path.exists('/sys/class/gpio/gpio68') GPIO.cleanup() if kernel < '4.1.0': assert not os.path.exists('/sys/class/gpio/gpio68') # for later kernels, the universal capemanager always loads the # UARTs. def test_setup_failed_type_error(self): with pytest.raises(TypeError): GPIO.setup("P8_10", "WEIRD") GPIO.cleanup() def test_setup_failed_value_error(self): with pytest.raises(ValueError): GPIO.setup("P8_10", 3) GPIO.cleanup() def test_setup_three_digit_gpio(self): GPIO.setup("P9_31", GPIO.OUT) assert os.path.exists('/sys/class/gpio/gpio110') GPIO.cleanup() if kernel < '4.1.0': assert not os.path.exists('/sys/class/gpio/gpio110') # for later kernels, the universal capemanager always loads the # UARTs.

33.821429

75

0.606829

367

2,841

4.561308

0.190736

0.076464

0.114695

0.150538

0.82736

0.770012

0.742533

0.713859

0.691756

0

0.031784

0.258008

2,841

83

76

34.228916

0.762334

0.048222

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0.53125

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0.187847

0.15339

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false

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0.25

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null

0

1

0

null

0

6

c45ff8e129435a4d8a018225b43a9ec8f181b2b3

112

py

Python

helpers/__init__.py

robot-acceleration/GRiDCodeGenerator

891490d6a02aa4119f7b7f03d5aa6524177e13c2

[ "MIT" ]

2

2021-12-25T17:00:07.000Z

2022-03-18T15:50:24.000Z

helpers/__init__.py

robot-acceleration/GRiDCodeGenerator

891490d6a02aa4119f7b7f03d5aa6524177e13c2

[ "MIT" ]

null

helpers/__init__.py

robot-acceleration/GRiDCodeGenerator

891490d6a02aa4119f7b7f03d5aa6524177e13c2

[ "MIT" ]

null

from ._code_generation_helpers import * from ._spatial_algebra_helpers import * from ._topology_helpers import *

37.333333

39

0.848214

14

112

6.214286

0.571429

0.448276

0.390805

0

0.098214

112

3

40

37.333333

0.861386

0

1

0

true

0

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1

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1

0

null

0

1

0

1

0

6

673cd7e7ceea09d7d02571f3f4c1fc7282c4407f

47

py

Python

xacro4sdf/__init__.py

ar-mine/xacro4sdf

9967bbb08007e12fd49838b82b396aa819a35f6d

[ "MIT" ]

12

2020-11-27T08:07:48.000Z

2022-03-11T04:32:07.000Z

xacro4sdf/__init__.py

ar-mine/xacro4sdf

9967bbb08007e12fd49838b82b396aa819a35f6d

[ "MIT" ]

null

xacro4sdf/__init__.py

ar-mine/xacro4sdf

9967bbb08007e12fd49838b82b396aa819a35f6d

[ "MIT" ]

2

2021-12-28T03:55:56.000Z

2022-01-12T07:50:36.000Z

from xacro4sdf.xacro4sdf import xacro4sdf_main

47

0.893617

6

47

6.833333

0.666667

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0.069767

0.085106

47

1

47

0.883721

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true

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1

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null

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1

0

null

0

1

0

1

0

1

0

6

675166a269565104b3daa39492381d59b9d6c0bd

122

py

Python

ecs/dashboard/views.py

programmierfabrik/ecs

2389a19453e21b2ea4e40b272552bcbd42b926a9

[ "Apache-2.0" ]

9

2017-02-13T18:17:13.000Z

2020-11-21T20:15:54.000Z

ecs/dashboard/views.py

programmierfabrik/ecs

2389a19453e21b2ea4e40b272552bcbd42b926a9

[ "Apache-2.0" ]

2

2021-05-20T14:26:47.000Z

2021-05-20T14:26:48.000Z

ecs/dashboard/views.py

programmierfabrik/ecs

2389a19453e21b2ea4e40b272552bcbd42b926a9

[ "Apache-2.0" ]

4

2017-04-02T18:48:59.000Z

2021-11-23T15:40:35.000Z

from django.shortcuts import render def view_dashboard(request): return render(request, 'dashboard/dashboard.html')

20.333333

54

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15

122

6.333333

0.733333

0

0.122951

122

5

55

24.4

0.88785

0

0.196721

0

1

0.333333

false

0

0.333333

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0

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null

0

1

0

null

0

1

0

1

0

6

679bdce17b55c1a089d8f2f8f54a242375ad4f15

199

py

Python

bridger/websockets/auth.py

intellineers/django-bridger

ed097984a99df7da40a4d01bd00c56e3c6083056

[ "BSD-3-Clause" ]

2

2020-03-17T00:53:23.000Z

2020-07-16T07:00:33.000Z

bridger/websockets/auth.py

intellineers/django-bridger

ed097984a99df7da40a4d01bd00c56e3c6083056

[ "BSD-3-Clause" ]

76

2019-12-05T01:15:57.000Z

2021-09-07T16:47:27.000Z

bridger/websockets/auth.py

intellineers/django-bridger

ed097984a99df7da40a4d01bd00c56e3c6083056

[ "BSD-3-Clause" ]

1

2020-02-05T15:09:47.000Z

from channels.sessions import CookieMiddleware from bridger.websockets.middleware import JWTAuthMiddleware def JWTAuthMiddlewareStack(inner): return CookieMiddleware(JWTAuthMiddleware(inner))

24.875

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0.854271

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199

9.444444

0.722222

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0.095477

199

7

60

28.428571

0.944444

0

1

0.25

false

0

0.5

0.25

1

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1

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null

0

1

0

null

0

1

0

1

0

6

67c22fee65b9d0192579c12f79db21bcca20f5cd

77,363

py

Python

resolversrv/tests/unittests/test_db_query.py

golnazads/resolver_service

782dce5a4daa864aff0b3d171185b2553a254a3f

[ "MIT" ]

1

2021-06-03T15:04:47.000Z

resolversrv/tests/unittests/test_db_query.py

golnazads/resolver_service

782dce5a4daa864aff0b3d171185b2553a254a3f

[ "MIT" ]

38

2017-11-20T15:53:59.000Z

2021-11-23T16:17:24.000Z

resolversrv/tests/unittests/test_db_query.py

golnazads/resolver_service

782dce5a4daa864aff0b3d171185b2553a254a3f

[ "MIT" ]

10

2017-10-06T19:23:20.000Z

2022-02-19T16:52:47.000Z

import sys, os project_home = os.path.abspath(os.path.join(os.path.dirname(__file__), '../../../')) if project_home not in sys.path: sys.path.insert(0, project_home) import unittest import json from resolversrv import app from resolversrv.tests.unittests.base import TestCaseDatabase from resolversrv.utils import get_records, add_records, get_records_new, add_records_new, del_records_new, get_ids from resolversrv.views import LinkRequest, PopulateRequest from adsmsg import DocumentRecords class TestDatabase(TestCaseDatabase): def create_app(self): '''Start the wsgi application''' a = app.create_app(**{ 'SQLALCHEMY_DATABASE_URI': self.postgresql_url, 'RESOLVER_GATEWAY_URL': '/{bibcode}/{link_type}/{url}', }) return a def add_stub_data(self): """ Add stub data :return: """ stub_data = [ ('2013MNRAS.435.1904M', 'TOC', '', [''], [''], 0), ('2013MNRAS.435.1904M', 'ESOURCE', 'EPRINT_HTML', ['http://arxiv.org/abs/1307.6556'], [''], 0), ('2013MNRAS.435.1904M', 'ESOURCE', 'EPRINT_PDF', ['http://arxiv.org/pdf/1307.6556'], [''], 0), ('2013MNRAS.435.1904M', 'ESOURCE', 'PUB_HTML', ['https://doi.org/10.1093%2Fmnras%2Fstt1379'], [''], 0), ('2013MNRAS.435.1904M', 'ESOURCE', 'PUB_PDF', ['http://mnras.oxfordjournals.org/content/435/3/1904.full.pdf'], [''], 0), ('2013MNRAS.435.1904M', 'DATA', 'Chandra', ['http://cda.harvard.edu/chaser?obsid=494'], ['Chandra Data Archive ObsIds 494'], 27), ('2013MNRAS.435.1904M', 'DATA', 'ESA', ['http://archives.esac.esa.int/ehst/#bibcode=2013MNRAS.435.1904M'], ['European HST References (EHST)'], 1), ('2013MNRAS.435.1904M', 'DATA', 'HEASARC', ['http://heasarc.gsfc.nasa.gov/cgi-bin/W3Browse/biblink.pl?code=2013MNRAS.435.1904M'], [], 1), ('2013MNRAS.435.1904M', 'DATA', 'Herschel', ['http://herschel.esac.esa.int/hpt/publicationdetailsview.do?bibcode=2013MNRAS.435.1904M'], [], 1), ('2013MNRAS.435.1904M', 'DATA', 'MAST', ['http://archive.stsci.edu/mastbibref.php?bibcode=2013MNRAS.435.1904M'], ['MAST References (GALEX EUVE HST)'], 3), ('2013MNRAS.435.1904M', 'DATA', 'NED', ['http://$NED$/cgi-bin/nph-objsearch?search_type=Search&refcode=2013MNRAS.435.1904M'], ['NED Objects (1)'], 1), ('2013MNRAS.435.1904M', 'DATA', 'SIMBAD', ['http://$SIMBAD$/simbo.pl?bibcode=2013MNRAS.435.1904M'], ['SIMBAD Objects (30)'], 30), ('2013MNRAS.435.1904M', 'DATA', 'XMM', ['http://nxsa.esac.esa.int/nxsa-web/#obsid=0097820101'], ['XMM-Newton Observation Number 0097820101'], 1), ('2017MNRAS.467.3556B', 'PRESENTATION', '', ['http://www.astro.lu.se/~alexey/animations.html'], [''], 0), ('1943RvMP...15....1C', 'INSPIRE', '', ['http://inspirehep.net/search?p=find+j+RMPHA,15,1'], [''], 0), ('1971ATsir.615....4D', 'ASSOCIATED', '', ['1971ATsir.615....4D', '1974Afz....10..315D', '1971ATsir.621....7D', '1976Afz....12..665D', '1971ATsir.624....1D', '1983Afz....19..229D', '1983Ap.....19..134D', '1973ATsir.759....6D', '1984Afz....20..525D', '1984Ap.....20..290D', '1974ATsir.809....1D', '1974ATsir.809....2D', '1974ATsir.837....2D'], ['Part 1', 'Part 2', 'Part 3', 'Part 4', 'Part 5', 'Part 6', 'Part 7', 'Part 8', 'Part 9', 'Part 10', 'Part 11', 'Part 12', 'Part 13'], 0), ('1514temg.book.....V', 'ASSOCIATED', '', ['1514temg.book.....V', 'https://www.si.edu/object/siris_sil_154413'], ['Main Paper', 'Supplementary Material'], 0), ('2007ASPC..368...27R', 'ESOURCE', 'ADS_PDF', ['http://articles.adsabs.harvard.edu/pdf/2007ASPC..368...27R'], [''], 0), ('2007ASPC..368...27R', 'ESOURCE', 'ADS_SCAN', ['http://articles.adsabs.harvard.edu/full/2007ASPC..368...27R'], [''], 0), ('2007ASPC..368...27R', 'ESOURCE', 'EPRINT_HTML', ['https://arxiv.org/abs/astro-ph/0703637'], [''], 0), ('2007ASPC..368...27R', 'ESOURCE', 'EPRINT_PDF', ['https://arxiv.org/pdf/astro-ph/0703637'], [''], 0), ('2007ASPC..368...27R', 'ESOURCE', 'PUB_HTML', ['http://aspbooks.org/custom/publications/paper/368-0027.html'], [''], 0), ('2007ASPC..368...27R', 'TOC', '', [''], [''], 0), ('2004astro.ph..1427R', 'DATA', 'MAST', ['http://archive.stsci.edu/prepds/gems','https://archive.stsci.edu/mastbibref.php?bibcode=2004ApJS..152..163R'],['GEMS: Galaxy Evolution from Morphologies and SEDs (Hans-Walter Rix)','MAST References (HST)'], 2), ] datalinks_list = [] for record in stub_data: datalinks_record = {'bibcode': record[0], 'data_links_rows': [{'link_type': record[1], 'link_sub_type': record[2], 'url': record[3], 'title': record[4], 'item_count': record[5]}]} datalinks_list.append(datalinks_record) headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.put('/update', data=json.dumps(datalinks_list), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'updated db with new data successfully') def test_link_type_all(self): """ return links for all types of a bibcode :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'count': 17, u'records': [ {u'url': u'/2013MNRAS.435.1904M/ABSTRACT', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'abstract', u'title': u'ABSTRACT (1)'}, {u'url': u'/2013MNRAS.435.1904M/CITATIONS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'citations', u'title': u'CITATIONS (1)'}, {u'url': u'/2013MNRAS.435.1904M/REFERENCES', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'references', u'title': u'REFERENCES (1)'}, {u'url': u'/2013MNRAS.435.1904M/COREADS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'coreads', u'title': u'COREADS (1)'}, {u'url': u'/2013MNRAS.435.1904M/TOC', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'toc', u'title': u'TOC (1)'}, {u'url': u'/2013MNRAS.435.1904M/OPENURL', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'openurl', u'title': u'OPENURL (1)'}, {u'url': u'/2013MNRAS.435.1904M/GRAPHICS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'graphics', u'title': u'GRAPHICS (1)'}, {u'url': u'/2013MNRAS.435.1904M/METRICS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'metrics', u'title': u'METRICS (1)'}, {u'url': u'/2013MNRAS.435.1904M/SIMILAR', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'similar', u'title': u'SIMILAR (1)'}, {u'url': u'/2013MNRAS.435.1904M/ESOURCE', u'count': 4, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'esource', u'title': u'ESOURCE (4)'}, {u'url': u'/2013MNRAS.435.1904M/DATA', u'count': 65, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'data', u'title': u'DATA (65)'}, {u'url': u'/2013MNRAS.435.1904M/DOI', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'doi', u'title': u'DOI (1)'}, {u'url': u'/2013MNRAS.435.1904M/ARXIV', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'arxiv', u'title': u'ARXIV (1)'}], u'link_type': 'all'}, u'service': u''}) def test_link_inspire(self): """ return a record of link type == inspire :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/1943RvMP...15....1C/INSPIRE', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://inspirehep.net/search?p=find+j+RMPHA,15,1', u'link_type': u'INSPIRE', u'service': u'http://inspirehep.net/search?p=find+j+RMPHA,15,1'}) def test_link_presentation(self): """ fetch record of a link_type presentation :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2017MNRAS.467.3556B/PRESENTATION', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://www.astro.lu.se/~alexey/animations.html', u'link_type': u'PRESENTATION', u'service': u'http://www.astro.lu.se/~alexey/animations.html'}) def test_link_associated(self): """ returning list of url, title pairs :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/1971ATsir.615....4D/ASSOCIATED', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'count': 13, u'records': [{u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1971ATsir.615....4D%2Fabstract', u'bibcode': u'1971ATsir.615....4D', u'title': u'Part 1'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974Afz....10..315D%2Fabstract', u'bibcode': u'1974Afz....10..315D', u'title': u'Part 2'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1971ATsir.621....7D%2Fabstract', u'bibcode': u'1971ATsir.621....7D', u'title': u'Part 3'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1976Afz....12..665D%2Fabstract', u'bibcode': u'1976Afz....12..665D', u'title': u'Part 4'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1971ATsir.624....1D%2Fabstract', u'bibcode': u'1971ATsir.624....1D', u'title': u'Part 5'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1983Afz....19..229D%2Fabstract', u'bibcode': u'1983Afz....19..229D', u'title': u'Part 6'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1983Ap.....19..134D%2Fabstract', u'bibcode': u'1983Ap.....19..134D', u'title': u'Part 7'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1973ATsir.759....6D%2Fabstract', u'bibcode': u'1973ATsir.759....6D', u'title': u'Part 8'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1984Afz....20..525D%2Fabstract', u'bibcode': u'1984Afz....20..525D', u'title': u'Part 9'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1984Ap.....20..290D%2Fabstract', u'bibcode': u'1984Ap.....20..290D', u'title': u'Part 10'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974ATsir.809....1D%2Fabstract', u'bibcode': u'1974ATsir.809....1D', u'title': u'Part 11'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974ATsir.809....2D%2Fabstract', u'bibcode': u'1974ATsir.809....2D', u'title': u'Part 12'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974ATsir.837....2D%2Fabstract', u'bibcode': u'1974ATsir.837....2D', u'title': u'Part 13'}], u'link_type': u'ASSOCIATED'}, u'service': u'/abs/1971ATsir.615....4D/associated'}) def test_link_esource_subtype(self): """ check status code for calling process_request for a esource sub type link :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/EPRINT_HTML', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://arxiv.org/abs/1307.6556', u'link_type': u'ESOURCE|EPRINT_HTML', u'service': u'http://arxiv.org/abs/1307.6556' }) def test_link_esource(self): """ returning list of urls :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/ESOURCE', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'count': 4, u'link_type': u'ESOURCE', u'bibcode': u'2013MNRAS.435.1904M', u'records': [ {u'url': u'http://arxiv.org/abs/1307.6556', u'title': u'http://arxiv.org/abs/1307.6556', u'link_type': u'ESOURCE|EPRINT_HTML'}, {u'url': u'http://arxiv.org/pdf/1307.6556', u'title': u'http://arxiv.org/pdf/1307.6556', u'link_type': u'ESOURCE|EPRINT_PDF'}, {u'url': u'https://doi.org/10.1093%2Fmnras%2Fstt1379', u'title': u'https://doi.org/10.1093%2Fmnras%2Fstt1379', u'link_type': u'ESOURCE|PUB_HTML'}, {u'url': u'http://mnras.oxfordjournals.org/content/435/3/1904.full.pdf', u'title': u'http://mnras.oxfordjournals.org/content/435/3/1904.full.pdf', u'link_type': u'ESOURCE|PUB_PDF'} ] }, u'service': u''}) def test_link_data_subtype(self): """ check status code for calling process_request for a data sub type link :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/ESA', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://archives.esac.esa.int/ehst/#bibcode=2013MNRAS.435.1904M', u'link_type': u'DATA|ESA', u'service': u'http://archives.esac.esa.int/ehst/#bibcode=2013MNRAS.435.1904M'}) def test_link_data(self): """ returning list of url, title pairs :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/DATA', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json,{u'action': u'display', u'service': u'', u'links': {u'count': 8, u'records': [{u'url': u'http://cxc.harvard.edu/cda', # Chandra u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|Chandra/http%3A%2F%2Fcda.harvard.edu%2Fchaser%3Fobsid%3D494', u'title': u'Chandra Data Archive ObsIds 494', u'link_type': u'DATA|Chandra'}], u'title': u'Chandra X-Ray Observatory'}, {u'url': u'http://archives.esac.esa.int', # ESA u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|ESA/http%3A%2F%2Farchives.esac.esa.int%2Fehst%2F%23bibcode%3D2013MNRAS.435.1904M', u'title': u'European HST References (EHST)', u'link_type': u'DATA|ESA'}], u'title': u'ESAC Science Data Center' }, {u'url': u'https://heasarc.gsfc.nasa.gov/', # HEASARC u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|HEASARC/http%3A%2F%2Fheasarc.gsfc.nasa.gov%2Fcgi-bin%2FW3Browse%2Fbiblink.pl%3Fcode%3D2013MNRAS.435.1904M', u'title': u'http://heasarc.gsfc.nasa.gov/cgi-bin/W3Browse/biblink.pl?code=2013MNRAS.435.1904M', u'link_type': u'DATA|HEASARC'}], u'title': u"NASA's High Energy Astrophysics Science Archive Research Center" }, {u'url': u'https://www.cosmos.esa.int/web/herschel/home', #Herschel u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|Herschel/http%3A%2F%2Fherschel.esac.esa.int%2Fhpt%2Fpublicationdetailsview.do%3Fbibcode%3D2013MNRAS.435.1904M', u'title': u'http://herschel.esac.esa.int/hpt/publicationdetailsview.do?bibcode=2013MNRAS.435.1904M', u'link_type': u'DATA|Herschel'}], u'title': u'Herschel Science Center' }, {u'url': u'http://archive.stsci.edu', # MAST u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|MAST/http%3A%2F%2Farchive.stsci.edu%2Fmastbibref.php%3Fbibcode%3D2013MNRAS.435.1904M', u'title': u'MAST References (GALEX EUVE HST)', u'link_type': u'DATA|MAST'}], u'title': u'Mikulski Archive for Space Telescopes' }, {u'url': u'https://ned.ipac.caltech.edu', # NED u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|NED/http%3A%2F%2Fned.ipac.caltech.edu%2Fcgi-bin%2Fnph-objsearch%3Fsearch_type%3DSearch%26refcode%3D2013MNRAS.435.1904M', u'title': u'NED Objects (1)', u'link_type': u'DATA|NED'}], u'title': u'NASA/IPAC Extragalactic Database' }, {u'url': u'http://simbad.u-strasbg.fr', # SIMBAD u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|SIMBAD/http%3A%2F%2Fsimbad.u-strasbg.fr%2Fsimbo.pl%3Fbibcode%3D2013MNRAS.435.1904M', u'title': u'SIMBAD Objects (30)', u'link_type': u'DATA|SIMBAD'}], u'title': u'SIMBAD Database at the CDS' }, {u'url': u'http://nxsa.esac.esa.int', # XMM u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|XMM/http%3A%2F%2Fnxsa.esac.esa.int%2Fnxsa-web%2F%23obsid%3D0097820101', u'title': u'XMM-Newton Observation Number 0097820101', u'link_type': u'DATA|XMM'}], u'title': u'XMM Newton Science Archive' }], u'bibcode': u'2013MNRAS.435.1904M'}}) def test_link_all_error_bibcode(self): """ call get_records to fetch all the records for a none existing bibcode :return: """ results = get_records(bibcode='errorbibcode') self.assertEqual(results, None) def test_error_with_sub_type(self): """ call get_records to fetch the records for a none existing bibcode, link_type, and link_subtype :return: """ results = get_records(bibcode='errorbibcode', link_type='errorlinktype', link_sub_type='errorlinksubtype') self.assertEqual(results, None) def test_link_associated_error_bibcode(self): """ return 404 for not finding any records :return: """ results = get_records(bibcode='errorbibcode', link_type='ASSOCIATED') response = LinkRequest(bibcode='').request_link_type_associated(results) self.assertEqual(response._status_code, 404) def test_link_esource_error_bibcode(self): """ return 404 for not finding any records :return: """ results = get_records(bibcode='errorbibcode', link_type='ESOURCE') response = LinkRequest(bibcode='').request_link_type_esource(results) self.assertEqual(response._status_code, 404) def test_link_data_error_bibcode(self): """ return 404 for not finding any records :return: """ results = get_records(bibcode='errorbibcode', link_type='DATA') response = LinkRequest(bibcode='').request_link_type_data(results) self.assertEqual(response._status_code, 404) def test_process_request_upsert(self): """ return 200 for successful insert/update to db :return: """ self.add_stub_data() datalinks_list = [{"bibcode": "1513efua.book.....S", "data_links_rows": [{"link_type": "LIBRARYCATALOG", "link_sub_type": "", "url": ["http://catalog.loc.gov/cgi-bin/Pwebrecon.cgi?v3=1&DB=local&CMD=010a+unk82013020&CNT=10+records+per+page"], "title": [""], "item_count": 0}]}] headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} # insert it here response = self.client.put('/update', data=json.dumps(datalinks_list), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'updated db with new data successfully') # select it here response = self.client.get('/1513efua.book.....S/LIBRARYCATALOG', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://catalog.loc.gov/cgi-bin/Pwebrecon.cgi?v3=1&DB=local&CMD=010a+unk82013020&CNT=10+records+per+page', u'link_type': u'LIBRARYCATALOG', u'service': u'http://catalog.loc.gov/cgi-bin/Pwebrecon.cgi?v3=1&DB=local&CMD=010a+unk82013020&CNT=10+records+per+page'}) def test_process_request_delete(self): """ return 200 for successful deletion from db :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} # delete it here bibcodes = {'bibcode': ['2013MNRAS.435.1904M']} response = self.client.delete('/delete', data=json.dumps(bibcodes), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'removed 13 records of 1 bibcodes') # select it here response = self.client.get('/2013MNRAS.435.1904M/ESOURCE', headers=headers) self.assertEqual(response._status_code, 404) self.assertEqual(response.json['error'], 'did not find any records') def test_link_toc(self): """ TOC was one of the on the fly types, as of 3/27/2019 we should have bibcodes with TOC in db so this link should not be created if the entry does not exists in db :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} # verify that TOC record does not exsits in db and hence return error response = self.client.get('/2019AIPC.2081c0032P/TOC', headers=headers) self.assertEqual(response._status_code, 404) # insert it here datalinks_list = [{"bibcode": "2019AIPC.2081c0032P", "data_links_rows": [{"link_type": "TOC", "link_sub_type": "", "url": [""], "title": [""], "item_count": 0}]}] response = self.client.put('/update', data=json.dumps(datalinks_list), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'updated db with new data successfully') # select it here response = self.client.get('/2019AIPC.2081c0032P/TOC', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'/abs/2019AIPC.2081c0032P/toc', u'service': u'/abs/2019AIPC.2081c0032P/toc', u'link_type': u'TOC'}) # delete it here bibcodes = {'bibcode': ['2019AIPC.2081c0032P']} response = self.client.delete('/delete', data=json.dumps(bibcodes), headers=headers) self.assertEqual(response._status_code, 200) # verify that is gone response = self.client.get('/2019AIPC.2081c0032P/TOC', headers=headers) self.assertEqual(response._status_code, 404) def test_link_esource_subtype_article(self): """ check status code for calling process_request for a esource sub type link for legacy type article :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2007ASPC..368...27R/ARTICLE', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://articles.adsabs.harvard.edu/pdf/2007ASPC..368...27R', u'service': u'http://articles.adsabs.harvard.edu/pdf/2007ASPC..368...27R', u'link_type': u'ESOURCE|ADS_PDF'}) response = self.client.get('/2013MNRAS.435.1904M/ARTICLE', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://mnras.oxfordjournals.org/content/435/3/1904.full.pdf', u'service': u'http://mnras.oxfordjournals.org/content/435/3/1904.full.pdf', u'link_type': u'ESOURCE|PUB_PDF'}) def test_data_subtype_multiple_links(self): """ :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2004astro.ph..1427R/MAST', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'bibcode': u'2004astro.ph..1427R', u'count': 1, u'records': [{u'data': [{u'link_type': u'DATA|MAST', u'title': u'GEMS: Galaxy Evolution from Morphologies and SEDs (Hans-Walter Rix)', u'url': u'/2004astro.ph..1427R/DATA|MAST/http%3A%2F%2Farchive.stsci.edu%2Fprepds%2Fgems'}], u'title': u'Mikulski Archive for Space Telescopes', u'url': u'http://archive.stsci.edu'}, {u'data': [{u'link_type': u'DATA|MAST', u'title': u'MAST References (HST)', u'url': u'/2004astro.ph..1427R/DATA|MAST/https%3A%2F%2Farchive.stsci.edu%2Fmastbibref.php%3Fbibcode%3D2004ApJS..152..163R'}], u'title': u'Mikulski Archive for Space Telescopes', u'url': u'http://archive.stsci.edu'}]}, u'service': u''}) def test_verify_url(self): """ :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/1514temg.book.....V/verify_url:https%3A%2F%2Fwww.si.edu%2Fobject%2Fsiris_sil_154413', headers=headers) self.assertEqual(response.json, {'link': 'verified'}) response = self.client.get('/1514temg.book.....V/verify_url:http%3A%2F%2Fwww.google.com', headers=headers) self.assertEqual(response.json, {'link': 'not found'}) class TestDatabaseNew(TestCaseDatabase): def create_app(self): '''Start the wsgi application''' a = app.create_app(**{ 'SQLALCHEMY_DATABASE_URI': self.postgresql_url, 'RESOLVER_GATEWAY_URL': '/{bibcode}/{link_type}/{url}', }) return a def add_stub_data(self): """ Add stub data :return: """ stub_data = [ { "bibcode": "2013MNRAS.435.1904M", "identifier": ["2013MNRAS.435.1904M", "2013arXiv1307.6556M", "2013MNRAS.tmp.2206M", "10.1093/mnras/stt1379", "arXiv:1307.6556"], "links": { "DOI": ["10.1093/mnras/stt1379"], "ARXIV": ["arXiv:1307.6556"], "DATA": { "Chandra": { "url": ["https://cda.harvard.edu/chaser?obsid=494,493,5290,5289,5286,5288,5287,3666,6162,6159,6163,6160,6161,13413,12028,10900,10898,13416,13414,12029,12027,13417,10899,13412,10901,13415,12026"], "title": ["Chandra Data Archive ObsIds 494, 493, 5290, 5289, 5286, 5288, 5287, 3666, 6162, 6159, 6163, 6160, 6161, 13413, 12028, 10900, 10898, 13416, 13414, 12029, 12027, 13417, 10899, 13412, 10901, 13415, 12026"], "count": 1 }, "ESA": { "url": ["http://archives.esac.esa.int/ehst/#bibcode=2013MNRAS.435.1904M"], "title": ["European HST References (EHST)"], "count": 1 }, "HEASARC": { "url": ["http://heasarc.gsfc.nasa.gov/cgi-bin/W3Browse/biblink.pl?code=2013MNRAS.435.1904M"], "title": ["http://heasarc.gsfc.nasa.gov/cgi-bin/W3Browse/biblink.pl?code=2013MNRAS.435.1904M"], "count": 1 }, "Herschel": { "url": ["http://archives.esac.esa.int/hsa/whsa/?ACTION=PUBLICATION&ID=2013MNRAS.435.1904M"], "title": ["http://archives.esac.esa.int/hsa/whsa/?ACTION=PUBLICATION&ID=2013MNRAS.435.1904M"], "count": 1 }, "MAST": { "url": ["https://archive.stsci.edu/mastbibref.php?bibcode=2013MNRAS.435.1904M"], "title": ["MAST References (HST, EUVE, GALEX)"], "count": 3 }, "NED": { "url": ["https://$NED$/uri/NED::InRefcode/2013MNRAS.435.1904M"], "title": ["NED Objects (1)"], "count": 1 }, "SIMBAD": { "url": ["http://$SIMBAD$/simbo.pl?bibcode=2013MNRAS.435.1904M"], "title": ["SIMBAD Objects (30)"], "count": 30 }, "XMM": { "url": ["https://nxsa.esac.esa.int/nxsa-web/#bibcode=2013MNRAS.435.1904M"], "title": ["XMM data (1 observations)"], "count": 1 } }, "ESOURCE": { "EPRINT_HTML": { "url": ["https://arxiv.org/abs/1307.6556"], "title": [''] }, "EPRINT_PDF": { "url": ["https://arxiv.org/pdf/1307.6556"], "title": [''] }, "PUB_HTML": { "url": ["https://doi.org/10.1093%2Fmnras%2Fstt1379"], "title": [''] }, "PUB_PDF": { "url": ["https://academic.oup.com/mnras/pdf-lookup/doi/10.1093/mnras/stt1379"], "title": [''] } }, "CITATIONS": True, "REFERENCES": True } }, { "bibcode": "2017MNRAS.467.3556B", "identifier": ["2017MNRAS.467.3556B", "2017arXiv170202377B", "10.1093/mnras/stx312", "arXiv:1702.02377"], "links": { "DOI": ["10.1093/mnras/stx312"], "ARXIV": ["arXiv:1702.02377"], "DATA": { "SIMBAD": { "url": ["http://$SIMBAD$/simbo.pl?bibcode=2017MNRAS.467.3556B"], "title": ["SIMBAD Objects (5)"], "count": 5 } }, "ESOURCE": { "EPRINT_HTML": { "url": ["https://arxiv.org/abs/1702.02377"], "title": [''] }, "EPRINT_PDF": { "url": ["https://arxiv.org/pdf/1702.02377"], "title": [''] }, "PUB_HTML": { "url": ["https://doi.org/10.1093%2Fmnras%2Fstx312"], "title": ['']}, "PUB_PDF": { "url": ["https://academic.oup.com/mnras/pdf-lookup/doi/10.1093/mnras/stx312"], "title": [''] } }, "ASSOCIATED": { "url": ["http://www.astro.lu.se/~alexey/animations.html"], "title": ["Supporting Media"] }, "PRESENTATION": { "url": ["http://www.astro.lu.se/~alexey/animations.html"], "title": [''] }, "CITATIONS": True, "REFERENCES": True } }, { "bibcode": "1943RvMP...15....1C", "identifier": ["1943RvMP...15....1C", "10.1103/RevModPhys.15.1"], "links": { "DOI": ["10.1103/RevModPhys.15.1"], "ESOURCE": { "PUB_HTML": { "url": ["http://link.aps.org/doi/10.1103/RevModPhys.15.1"], "title": [''] } }, "INSPIRE": { "url": ["http://inspirehep.net/search?p=find+j+RMPHA,15,1"], "title": [''] }, "CITATIONS": True, "REFERENCES": True } }, { "bibcode": "1971ATsir.615....4D", "identifier": ["1971ATsir.615....4D"], "links": { "ASSOCIATED": { "url": ["1971ATsir.615....4D", "1971ATsir.621....7D", "1971ATsir.624....1D", "1973ATsir.759....6D", "1974Afz....10..315D", "1974ATsir.809....1D", "1974ATsir.809....2D", "1974ATsir.837....2D", "1976Afz....12..665D", "1983Afz....19..229D", "1983Ap.....19..134D", "1984Afz....20..525D", "1984Ap.....20..290D"], "title": ["Part 1","Part 3","Part 5","Part 8","Part 2","Part 11","Part 12","Part 13","Part 4","Part 6","Part 7","Part 9","Part 10"], "count": 10 }, "CITATIONS": True, "REFERENCES": False } }, { "bibcode": "1514temg.book.....V", "identifier": ["1514temg.book.....V", "10.3931/e-rara-426"], "links": { "DOI": ["10.3931/e-rara-426"], "ESOURCE": { "PUB_HTML": { "url": ["https://doi.org/10.3931%2Fe-rara-426"], "title": [''] } }, "ASSOCIATED": { "url": ["1514temg.book.....V", "https://www.si.edu/object/siris_sil_154413"], "title": ["Main Paper", "Supplementary Material"], "count": 2 }, "CITATIONS": False, "REFERENCES": False } }, { "bibcode": "2007ASPC..368...27R", "identifier": ["2007ASPC..368...27R", "2007astro.ph..3637R", "arXiv:astro-ph/0703637"], "links": { "ARXIV": ["arXiv:astro-ph/0703637"], "TOC": True, "ESOURCE": { "ADS_PDF": { "url": ["http://articles.adsabs.harvard.edu/pdf/2007ASPC..368...27R"], "title": [''] }, "ADS_SCAN": { "url": ["http://articles.adsabs.harvard.edu/full/2007ASPC..368...27R"], "title": ['']}, "EPRINT_HTML": { "url": ["http://arxiv.org/abs/astro-ph/0703637"], "title": [''] }, "EPRINT_PDF": { "url": ["http://arxiv.org/pdf/astro-ph/0703637"], "title": [''] }, "PUB_HTML": { "url": ["http://aspbooks.org/custom/publications/paper/368-0027.html"], "title": [''] } }, "REFERENCES": True } }, { "bibcode": "2004ApJS..152..163R", "identifier": ["2004ApJS..152..163R", "2004astro.ph..1427R", "10.1086/420885", "arXiv:astro-ph/0401427"], "links": { "DOI": ["10.1086/420885"], "ARXIV": ["arXiv:astro-ph/0401427"], "DATA": { "ESA": { "url": ["http://archives.esac.esa.int/ehst/#bibcode=2004ApJS..152..163R"], "title": ["European HST References (EHST)"], "count": 1 }, "MAST": { "url": ["http://archive.stsci.edu/mastbibref.php?bibcode=2004ApJS..152..163R", "http://archive.stsci.edu/prepds/gems"], "title": ["MAST References (HST)", "GEMS: Galaxy Evolution from Morphologies and SEDs (Hans-Walter Rix)"], "count": 2 }, "SIMBAD": { "url": ["http://$SIMBAD$/simbo.pl?bibcode=2004ApJS..152..163R"], "title": ["SIMBAD Objects (3)"], "count": 3 } }, "ESOURCE": { "EPRINT_HTML": { "url": ["http://arxiv.org/abs/astro-ph/0401427"], "title": [''] }, "EPRINT_PDF": { "url": ["http://arxiv.org/pdf/astro-ph/0401427"], "title": [''] }, "PUB_HTML": { "url": ["https://doi.org/10.1086%2F420885"], "title": [''] }, "PUB_PDF": { "url": ["http://stacks.iop.org/0067-0049/152/163/pdf"], "title": [''] } }, "CITATIONS": True, "REFERENCES": True } }, { "bibcode": "2021JOSS....6.2807C", "identifier": ["2021JOSS....6.2807C", "10.21105/joss.02807"], "links": { "DOI": ["10.21105/joss.02807"], "CITATIONS": False, "REFERENCES": False } }, { "bibcode": "2021zndo...4441439K", "identifier": ["2021zndo...4441439K", "10.5281/zenodo.4441439"], "links": { "DOI": ["10.5281/zenodo.4441439"], "ESOURCE": { "PUB_HTML": { "url": ["https://doi.org/10.5281/zenodo.4441439"], "title": ["https://doi.org/10.5281/zenodo.4441439"] } }, "CITATIONS": True, "REFERENCES": False } } ] headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.put('/update_new', data=json.dumps(stub_data), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'updated db with new data successfully') def test_link_type_all(self): """ return links for all types of a bibcode :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'count': 17, u'records': [ {u'url': u'/2013MNRAS.435.1904M/ABSTRACT', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'abstract', u'title': u'ABSTRACT (1)'}, {u'url': u'/2013MNRAS.435.1904M/CITATIONS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'citations', u'title': u'CITATIONS (1)'}, {u'url': u'/2013MNRAS.435.1904M/REFERENCES', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'references', u'title': u'REFERENCES (1)'}, {u'url': u'/2013MNRAS.435.1904M/COREADS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'coreads', u'title': u'COREADS (1)'}, {u'url': u'/2013MNRAS.435.1904M/OPENURL', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'openurl', u'title': u'OPENURL (1)'}, {u'url': u'/2013MNRAS.435.1904M/GRAPHICS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'graphics', u'title': u'GRAPHICS (1)'}, {u'url': u'/2013MNRAS.435.1904M/METRICS', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'metrics', u'title': u'METRICS (1)'}, {u'url': u'/2013MNRAS.435.1904M/SIMILAR', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'similar', u'title': u'SIMILAR (1)'}, {u'url': u'/2013MNRAS.435.1904M/ESOURCE', u'count': 4, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'esource', u'title': u'ESOURCE (4)'}, {u'url': u'/2013MNRAS.435.1904M/DATA', u'count': 39, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'data', u'title': u'DATA (39)'}, {u'url': u'/2013MNRAS.435.1904M/DOI', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'doi', u'title': u'DOI (1)'}, {u'url': u'/2013MNRAS.435.1904M/ARXIV', u'count': 1, u'bibcode': u'2013MNRAS.435.1904M', u'type': u'arxiv', u'title': u'ARXIV (1)'}], u'link_type': 'all'}, u'service': u''}) def test_link_inspire(self): """ return a record of link type == inspire :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/1943RvMP...15....1C/INSPIRE/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://inspirehep.net/search?p=find+j+RMPHA,15,1', u'link_type': u'INSPIRE', u'service': u'http://inspirehep.net/search?p=find+j+RMPHA,15,1'}) def test_link_presentation(self): """ fetch record of a link_type presentation :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2017MNRAS.467.3556B/PRESENTATION/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://www.astro.lu.se/~alexey/animations.html', u'link_type': u'PRESENTATION', u'service': u'http://www.astro.lu.se/~alexey/animations.html'}) def test_link_associated(self): """ returning list of url, title pairs :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/1971ATsir.615....4D/ASSOCIATED/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'count': 13, u'records': [{u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1971ATsir.615....4D%2Fabstract', u'bibcode': u'1971ATsir.615....4D', u'title': u'Part 1'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974Afz....10..315D%2Fabstract', u'bibcode': u'1974Afz....10..315D', u'title': u'Part 2'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1971ATsir.621....7D%2Fabstract', u'bibcode': u'1971ATsir.621....7D', u'title': u'Part 3'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1976Afz....12..665D%2Fabstract', u'bibcode': u'1976Afz....12..665D', u'title': u'Part 4'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1971ATsir.624....1D%2Fabstract', u'bibcode': u'1971ATsir.624....1D', u'title': u'Part 5'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1983Afz....19..229D%2Fabstract', u'bibcode': u'1983Afz....19..229D', u'title': u'Part 6'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1983Ap.....19..134D%2Fabstract', u'bibcode': u'1983Ap.....19..134D', u'title': u'Part 7'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1973ATsir.759....6D%2Fabstract', u'bibcode': u'1973ATsir.759....6D', u'title': u'Part 8'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1984Afz....20..525D%2Fabstract', u'bibcode': u'1984Afz....20..525D', u'title': u'Part 9'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1984Ap.....20..290D%2Fabstract', u'bibcode': u'1984Ap.....20..290D', u'title': u'Part 10'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974ATsir.809....1D%2Fabstract', u'bibcode': u'1974ATsir.809....1D', u'title': u'Part 11'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974ATsir.809....2D%2Fabstract', u'bibcode': u'1974ATsir.809....2D', u'title': u'Part 12'}, {u'url': u'/1971ATsir.615....4D/associated/:%2Fabs%2F1974ATsir.837....2D%2Fabstract', u'bibcode': u'1974ATsir.837....2D', u'title': u'Part 13'}], u'link_type': u'ASSOCIATED'}, u'service': u'/abs/1971ATsir.615....4D/associated'}) def test_link_esource_subtype(self): """ check status code for calling process_request for a esource sub type link :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/EPRINT_HTML/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'https://arxiv.org/abs/1307.6556', u'link_type': u'ESOURCE|EPRINT_HTML', u'service': u'https://arxiv.org/abs/1307.6556' }) def test_link_esource(self): """ returning list of urls :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/ESOURCE/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'count': 4, u'link_type': u'ESOURCE', u'bibcode': u'2013MNRAS.435.1904M', u'records': [ {u'url': u'https://academic.oup.com/mnras/pdf-lookup/doi/10.1093/mnras/stt1379', u'title': u'https://academic.oup.com/mnras/pdf-lookup/doi/10.1093/mnras/stt1379', u'link_type': u'ESOURCE|PUB_PDF'}, {u'url': u'https://doi.org/10.1093%2Fmnras%2Fstt1379', u'title': u'https://doi.org/10.1093%2Fmnras%2Fstt1379', u'link_type': u'ESOURCE|PUB_HTML'}, {u'url': u'https://arxiv.org/pdf/1307.6556', u'title': u'https://arxiv.org/pdf/1307.6556', u'link_type': u'ESOURCE|EPRINT_PDF'}, {u'url': u'https://arxiv.org/abs/1307.6556', u'title': u'https://arxiv.org/abs/1307.6556', u'link_type': u'ESOURCE|EPRINT_HTML'}, ] }, u'service': u''}) def test_link_data_subtype(self): """ check status code for calling process_request for a data sub type link :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/ESA/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://archives.esac.esa.int/ehst/#bibcode=2013MNRAS.435.1904M', u'link_type': u'DATA|ESA', u'service': u'http://archives.esac.esa.int/ehst/#bibcode=2013MNRAS.435.1904M'}) def test_link_data(self): """ returning list of url, title pairs :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2013MNRAS.435.1904M/DATA/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json,{u'action': u'display', u'service': u'', u'links': {u'count': 8, u'records': [{u'url': u'http://archives.esac.esa.int', # ESA u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|ESA/http%3A%2F%2Farchives.esac.esa.int%2Fehst%2F%23bibcode%3D2013MNRAS.435.1904M', u'title': u'European HST References (EHST)', u'link_type': u'DATA|ESA'}], u'title': u'ESAC Science Data Center' }, {u'url': u'https://ned.ipac.caltech.edu', # NED u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|NED/https%3A%2F%2Fned.ipac.caltech.edu%2Furi%2FNED%3A%3AInRefcode%2F2013MNRAS.435.1904M', u'title': u'NED Objects (1)', u'link_type': u'DATA|NED'}], u'title': u'NASA/IPAC Extragalactic Database' }, {u'url': u'http://nxsa.esac.esa.int', # XMM u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|XMM/https%3A%2F%2Fnxsa.esac.esa.int%2Fnxsa-web%2F%23bibcode%3D2013MNRAS.435.1904M', u'title': u'XMM data (1 observations)', u'link_type': u'DATA|XMM'}], u'title': u'XMM Newton Science Archive' }, {u'url': u'http://archive.stsci.edu', # MAST u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|MAST/https%3A%2F%2Farchive.stsci.edu%2Fmastbibref.php%3Fbibcode%3D2013MNRAS.435.1904M', u'title': u'MAST References (HST, EUVE, GALEX)', u'link_type': u'DATA|MAST'}], u'title': u'Mikulski Archive for Space Telescopes' }, {u'url': u'http://simbad.u-strasbg.fr', # SIMBAD u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|SIMBAD/http%3A%2F%2Fsimbad.u-strasbg.fr%2Fsimbo.pl%3Fbibcode%3D2013MNRAS.435.1904M', u'title': u'SIMBAD Objects (30)', u'link_type': u'DATA|SIMBAD'}], u'title': u'SIMBAD Database at the CDS' }, {u'url': u'http://cxc.harvard.edu/cda', # Chandra u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|Chandra/https%3A%2F%2Fcda.harvard.edu%2Fchaser%3Fobsid%3D494%2C493%2C5290%2C5289%2C5286%2C5288%2C5287%2C3666%2C6162%2C6159%2C6163%2C6160%2C6161%2C13413%2C12028%2C10900%2C10898%2C13416%2C13414%2C12029%2C12027%2C13417%2C10899%2C13412%2C10901%2C13415%2C12026', u'title': u'Chandra Data Archive ObsIds 494, 493, 5290, 5289, 5286, 5288, 5287, 3666, 6162, 6159, 6163, 6160, 6161, 13413, 12028, 10900, 10898, 13416, 13414, 12029, 12027, 13417, 10899, 13412, 10901, 13415, 12026', u'link_type': u'DATA|Chandra'}], u'title': u'Chandra X-Ray Observatory' }, {u'url': u'https://heasarc.gsfc.nasa.gov/', # HEASARC u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|HEASARC/http%3A%2F%2Fheasarc.gsfc.nasa.gov%2Fcgi-bin%2FW3Browse%2Fbiblink.pl%3Fcode%3D2013MNRAS.435.1904M', u'title': u'http://heasarc.gsfc.nasa.gov/cgi-bin/W3Browse/biblink.pl?code=2013MNRAS.435.1904M', u'link_type': u'DATA|HEASARC'}], u'title': u"NASA's High Energy Astrophysics Science Archive Research Center" }, {u'url': u'https://www.cosmos.esa.int/web/herschel/home', #Herschel u'data': [{u'url': u'/2013MNRAS.435.1904M/DATA|Herschel/http%3A%2F%2Farchives.esac.esa.int%2Fhsa%2Fwhsa%2F%3FACTION%3DPUBLICATION%26ID%3D2013MNRAS.435.1904M', u'title': u'http://archives.esac.esa.int/hsa/whsa/?ACTION=PUBLICATION&ID=2013MNRAS.435.1904M', u'link_type': u'DATA|Herschel'}], u'title': u'Herschel Science Center' }], u'bibcode': u'2013MNRAS.435.1904M'}}) def test_link_all_error_bibcode(self): """ call get_records to fetch all the records for a none existing bibcode :return: """ results = get_records(bibcode='errorbibcode') self.assertEqual(results, None) def test_error_with_sub_type(self): """ call get_records to fetch the records for a none existing bibcode, link_type, and link_subtype :return: """ results = get_records(bibcode='errorbibcode', link_type='errorlinktype', link_sub_type='errorlinksubtype') self.assertEqual(results, None) def test_link_associated_error_bibcode(self): """ return 404 for not finding any records :return: """ results = get_records_new(bibcode='errorbibcode', link_type='ASSOCIATED') response = LinkRequest(bibcode='').request_link_type_associated(results) self.assertEqual(response._status_code, 404) def test_link_esource_error_bibcode(self): """ return 404 for not finding any records :return: """ results = get_records_new(bibcode='errorbibcode', link_type='ESOURCE') response = LinkRequest(bibcode='').request_link_type_esource(results) self.assertEqual(response._status_code, 404) def test_link_data_error_bibcode(self): """ return 404 for not finding any records :return: """ results = get_records_new(bibcode='errorbibcode', link_type='DATA') response = LinkRequest(bibcode='').request_link_type_data(results) self.assertEqual(response._status_code, 404) def test_process_request_upsert(self): """ return 200 for successful insert/update to db :return: """ self.add_stub_data() document_record = { "bibcode": "1513efua.book.....S", "identifier": [], "links": { "LIBRARYCATALOG": { "url": ["http://catalog.loc.gov/cgi-bin/Pwebrecon.cgi?v3=1&DB=local&CMD=010a+unk82013020&CNT=10+records+per+page"], "title": [''] } } } headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} # insert it here response = self.client.put('/update_new', data=json.dumps([document_record]), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'updated db with new data successfully') # select it here response = self.client.get('/1513efua.book.....S/LIBRARYCATALOG/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://catalog.loc.gov/cgi-bin/Pwebrecon.cgi?v3=1&DB=local&CMD=010a+unk82013020&CNT=10+records+per+page', u'link_type': u'LIBRARYCATALOG', u'service': u'http://catalog.loc.gov/cgi-bin/Pwebrecon.cgi?v3=1&DB=local&CMD=010a+unk82013020&CNT=10+records+per+page'}) def test_process_request_delete(self): """ return 200 for successful deletion from db :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} # delete it here bibcodes = {'bibcode': ['2013MNRAS.435.1904M']} response = self.client.delete('/delete_new', data=json.dumps(bibcodes), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'removed 1 records of 1 bibcodes') # select it here response = self.client.get('/2013MNRAS.435.1904M/ESOURCE/new', headers=headers) self.assertEqual(response._status_code, 404) self.assertEqual(response.json['error'], 'did not find any records') def test_link_toc(self): """ TOC was one of the on the fly types, as of 3/27/2019 we should have bibcodes with TOC in db so this link should not be created if the entry does not exists in db :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} # verify that TOC record does not exsits in db and hence return error response = self.client.get('/2019AIPC.2081c0032P/TOC/new', headers=headers) self.assertEqual(response._status_code, 404) # insert it here document_record = {"bibcode": "2019AIPC.2081c0032P", "identifier": [], "links": {"TOC": True}} response = self.client.put('/update_new', data=json.dumps([document_record]), headers=headers) self.assertEqual(response._status_code, 200) self.assertEqual(response.json['status'], 'updated db with new data successfully') # select it here response = self.client.get('/2019AIPC.2081c0032P/TOC/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'/abs/2019AIPC.2081c0032P/toc', u'service': u'/abs/2019AIPC.2081c0032P/toc', u'link_type': u'TOC'}) # delete it here bibcodes = {'bibcode': ['2019AIPC.2081c0032P']} response = self.client.delete('/delete_new', data=json.dumps(bibcodes), headers=headers) self.assertEqual(response._status_code, 200) # verify that is gone response = self.client.get('/2019AIPC.2081c0032P/TOC/new', headers=headers) self.assertEqual(response._status_code, 404) def test_link_esource_subtype_article(self): """ check status code for calling process_request for a esource sub type link for legacy type article :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2007ASPC..368...27R/ARTICLE/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'http://articles.adsabs.harvard.edu/pdf/2007ASPC..368...27R', u'service': u'http://articles.adsabs.harvard.edu/pdf/2007ASPC..368...27R', u'link_type': u'ESOURCE|ADS_PDF'}) response = self.client.get('/2013MNRAS.435.1904M/ARTICLE/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'redirect', u'link': u'https://academic.oup.com/mnras/pdf-lookup/doi/10.1093/mnras/stt1379', u'service': u'https://academic.oup.com/mnras/pdf-lookup/doi/10.1093/mnras/stt1379', u'link_type': u'ESOURCE|PUB_PDF'}) def test_data_subtype_multiple_links(self): """ :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/2004ApJS..152..163R/MAST/new', headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {u'action': u'display', u'links': {u'bibcode': u'2004ApJS..152..163R', u'count': 1, u'records': [{u'data': [{u'link_type': u'DATA|MAST', u'title': u'MAST References (HST)', u'url': u'/2004ApJS..152..163R/DATA|MAST/http%3A%2F%2Farchive.stsci.edu%2Fmastbibref.php%3Fbibcode%3D2004ApJS..152..163R'}], u'title': u'Mikulski Archive for Space Telescopes', u'url': u'http://archive.stsci.edu'}, {u'data': [{u'link_type': u'DATA|MAST', u'title': u'GEMS: Galaxy Evolution from Morphologies and SEDs (Hans-Walter Rix)', u'url': u'/2004ApJS..152..163R/DATA|MAST/http%3A%2F%2Farchive.stsci.edu%2Fprepds%2Fgems'}], u'title': u'Mikulski Archive for Space Telescopes', u'url': u'http://archive.stsci.edu'}]}, u'service': u''}) def test_verify_url(self): """ :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} response = self.client.get('/1514temg.book.....V/verify_url:https%3A%2F%2Fwww.si.edu%2Fobject%2Fsiris_sil_154413/new', headers=headers) self.assertEqual(response.json, {'link': 'verified'}) response = self.client.get('/1514temg.book.....V/verify_url:http%3A%2F%2Fwww.google.com/new', headers=headers) self.assertEqual(response.json, {'link': 'not found'}) def test_link_esource_subtype_article_no_record(self): """ check status code for calling process_request for a esource sub type link for legacy type article where there is no esource :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} # no esource record response = self.client.get('/2021JOSS....6.2807C/ARTICLE/new', headers=headers) self.assertEqual(response._status_code, 404) self.assertDictEqual(response.json, {'error': 'did not find any records'}) # no %_PDF record response = self.client.get('/2021zndo...4441439K/ARTICLE/new', headers=headers) self.assertEqual(response._status_code, 404) self.assertDictEqual(response.json, {'error': 'did not find any records'}) def test_get_records_failure(self): """ :return: """ with self.assertRaises(Exception) as context: get_records_new({'bibcode':'is single value'}) self.assertTrue("can't adapt type 'dict'" in str(context)) with self.assertRaises(Exception) as context: document_records = { 'status': 2, # name='new', index=2, number=2, 'document_records': [ { 'bibcode': '2021JOSS....6.2807C', 'identifier': ['2021JOSS....6.2807C'], 'links': { 'DOI': ['10.21105/joss.02807'], 'CITATIONS': False, 'REFERENCES': False } }, { 'bibcode': '2021JOSS....6.2807C', 'identifier': ['2021JOSS....6.2807C'], 'links': { 'DOI': ['10.21105/joss.02807'], 'CITATIONS': False, 'REFERENCES': False } }, ] } # duplicate records add_records_new(DocumentRecords(**document_records)) self.assertTrue("ON CONFLICT DO UPDATE command cannot affect row a second time" in str(context)) with self.assertRaises(Exception) as context: del_records_new([12, 14]) self.assertTrue("operator does not exist: character varying = integer" in str(context)) with self.assertRaises(Exception) as context: get_ids({'id': ['is a list']}) self.assertTrue("no matches found in database" in str(context)) def test_reconciliation(self): """ :return: """ self.add_stub_data() headers = {'Content-type': 'application/json', 'Accept': 'text/plain'} identifiers = ['doi:10.1093/mnras/stt1379', 'arXiv:1702.02377', 'https://doi.org/10.5281/zenodo.4441439', '10.1086/420885', 'astro-ph/0703637'] response = self.client.post('/reconciliation', data=json.dumps({'identifier':identifiers}), headers=headers) self.assertEqual(response._status_code, 200) self.assertDictEqual(response.json, {'ids': [ ['10.1093/mnras/stt1379', '2013MNRAS.435.1904M'], ['arXiv:1702.02377', '2017MNRAS.467.3556B'], ['10.5281/zenodo.4441439', '2021zndo...4441439K'], ['10.1086/420885', '2004ApJS..152..163R'], ['astro-ph/0703637', 'not in database'] ]}) if __name__ == '__main__': unittest.main()

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67c2fefe5e5837bdd50dbb1893b4854e1d55a134

19

py

Python

web3_erc20_predefined/predefined/bsc_testnet/__init__.py

kkristof200/py_web3_erc20_predefined

e95399bb14c61bb56e56f474937b0ace8565772b

[ "MIT" ]

null

web3_erc20_predefined/predefined/bsc_testnet/__init__.py

kkristof200/py_web3_erc20_predefined

e95399bb14c61bb56e56f474937b0ace8565772b

[ "MIT" ]

null

web3_erc20_predefined/predefined/bsc_testnet/__init__.py

kkristof200/py_web3_erc20_predefined

e95399bb14c61bb56e56f474937b0ace8565772b

[ "MIT" ]

null

from .wbnb import *

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py

Python

handwritten_multi_digit_number_recognition/models/__init__.py

kingyiusuen/handwritten-digit-string-recognition

a1527c72258ba374df5be38a7e76a82e845028fa

[ "MIT" ]

1

2021-08-24T10:10:02.000Z

handwritten_multi_digit_number_recognition/models/__init__.py

kingyiusuen/handwritten-multi-digit-number-recognition

a1527c72258ba374df5be38a7e76a82e845028fa

[ "MIT" ]

null

handwritten_multi_digit_number_recognition/models/__init__.py

kingyiusuen/handwritten-multi-digit-number-recognition

a1527c72258ba374df5be38a7e76a82e845028fa

[ "MIT" ]

1

2021-08-24T19:09:08.000Z

from .crnn import CRNN

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Python

pkg_dir/src/parameters/__init__.py

robperch/robase_datalysis

343cb59b16630ca776bd941897ab8da63f20bfe1

[ "MIT" ]

1

2022-01-09T18:20:58.000Z

pkg_dir/src/parameters/__init__.py

robperch/robasecode

343cb59b16630ca776bd941897ab8da63f20bfe1

[ "MIT" ]

2

2022-01-13T23:49:17.000Z

2022-01-13T23:51:14.000Z

pkg_dir/src/parameters/__init__.py

robperch/robasecode

343cb59b16630ca776bd941897ab8da63f20bfe1

[ "MIT" ]

null

## INITIALIZATION MODULE - PARAMETERS ## Imports "----------------------------------------------------------------------------------------------------------------------" "----------------------------------------------------------------------------------------------------------------------" ############################################# END OF FILE ############################################################## "----------------------------------------------------------------------------------------------------------------------" "----------------------------------------------------------------------------------------------------------------------"

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Python

networking_cisco/tests/unit/cisco/l3/test_asr1k_routertype_driver.py

CiscoSystems/networking-cisco

ed18627faf90caa1c0d1b7fe00f240a57901dee4

[ "Apache-2.0" ]

8

2016-02-12T01:25:29.000Z

2019-01-13T14:19:25.000Z

networking_cisco/tests/unit/cisco/l3/test_asr1k_routertype_driver.py

CiscoSystems/networking-cisco

ed18627faf90caa1c0d1b7fe00f240a57901dee4

[ "Apache-2.0" ]

25

2016-01-28T12:33:41.000Z

2016-07-28T21:18:03.000Z

networking_cisco/tests/unit/cisco/l3/test_asr1k_routertype_driver.py

CiscoSystems/networking-cisco

ed18627faf90caa1c0d1b7fe00f240a57901dee4

[ "Apache-2.0" ]

9

2015-05-07T02:47:55.000Z

2019-10-18T15:25:27.000Z

# Copyright 2015 Cisco Systems, Inc. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from oslo_config import cfg from oslo_utils import uuidutils from neutron import context from neutron.extensions import l3 from networking_cisco.plugins.cisco.common import cisco_constants from networking_cisco.plugins.cisco.db.l3 import ha_db from networking_cisco.plugins.cisco.extensions import ha from networking_cisco.plugins.cisco.extensions import routerhostingdevice from networking_cisco.plugins.cisco.extensions import routerrole from networking_cisco.plugins.cisco.extensions import routertype from networking_cisco.plugins.cisco.extensions import routertypeawarescheduler from networking_cisco.tests.unit.cisco.l3 import ( test_ha_l3_router_appliance_plugin as cisco_ha_test) from networking_cisco.tests.unit.cisco.l3 import ( test_l3_routertype_aware_schedulers as cisco_test_case) _uuid = uuidutils.generate_uuid EXTERNAL_GW_INFO = l3.EXTERNAL_GW_INFO AGENT_TYPE_L3_CFG = cisco_constants.AGENT_TYPE_L3_CFG ROUTER_ROLE_GLOBAL = cisco_constants.ROUTER_ROLE_GLOBAL ROUTER_ROLE_LOGICAL_GLOBAL = cisco_constants.ROUTER_ROLE_LOGICAL_GLOBAL ROUTER_ROLE_HA_REDUNDANCY = cisco_constants.ROUTER_ROLE_HA_REDUNDANCY LOGICAL_ROUTER_ROLE_NAME = cisco_constants.LOGICAL_ROUTER_ROLE_NAME ROUTER_ROLE_ATTR = routerrole.ROUTER_ROLE_ATTR HOSTING_DEVICE_ATTR = routerhostingdevice.HOSTING_DEVICE_ATTR AUTO_SCHEDULE_ATTR = routertypeawarescheduler.AUTO_SCHEDULE_ATTR class Asr1kRouterTypeDriverTestCase( cisco_test_case.L3RoutertypeAwareHostingDeviceSchedulerTestCaseBase): # Nexus router type for ASR1k driver tests, why? # - Yes(!), it does not matter and there is only one hosting device for # that router type in the test setup which makes scheduling deterministic router_type = 'Nexus_ToR_Neutron_router' def _verify_created_routers(self, router_ids, hd_id): # tenant routers q_p = '%s=None' % ROUTER_ROLE_ATTR r_ids = {r['id'] for r in self._list( 'routers', query_params=q_p)['routers']} self.assertEqual(len(r_ids), len(router_ids)) for r_id in r_ids: self.assertIn(r_id, router_ids) # global router on hosting device q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_GLOBAL) g_rtrs = self._list('routers', query_params=q_p)['routers'] self.assertEqual(len(g_rtrs), 1) g_rtr = g_rtrs[0] self.assertEqual(g_rtr['name'].endswith( hd_id[-cisco_constants.ROLE_ID_LEN:]), True) # logical global router for global routers HA q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_LOGICAL_GLOBAL) g_l_rtrs = self._list('routers', query_params=q_p)['routers'] self.assertEqual(len(g_l_rtrs), 1) g_l_rtr = g_l_rtrs[0] self.assertEqual(g_l_rtr['name'], LOGICAL_ROUTER_ROLE_NAME) self.assertEqual(g_l_rtr[AUTO_SCHEDULE_ATTR], False) # ensure first routers_updated notification was for global router notifier = self.plugin.agent_notifiers[AGENT_TYPE_L3_CFG] notify_call = notifier.method_calls[0] self.assertEqual(notify_call[0], 'routers_updated') updated_routers = notify_call[1][1] self.assertEqual(len(updated_routers), 1) self.assertEqual(updated_routers[0]['id'], g_rtr['id']) # ensure *no* update notifications where sent for logical global router for call in notifier.method_calls: self.assertNotIn(call[1][1][0][ROUTER_ROLE_ATTR], [ROUTER_ROLE_LOGICAL_GLOBAL]) def _test_gw_router_create_adds_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router1: r1 = router1['router'] self.plugin._process_backlogged_routers() r1_after = self._show('routers', r1['id'])['router'] hd_id = r1_after[HOSTING_DEVICE_ATTR] # should have one global router now self._verify_created_routers({r1['id']}, hd_id) with self.router(name='router2', tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router2: r2 = router2['router'] self.plugin._process_backlogged_routers() # should still have only one global router self._verify_created_routers({r1['id'], r2['id']}, hd_id) def test_gw_router_create_adds_global_router(self): self._test_gw_router_create_adds_global_router() def test_gw_router_create_adds_global_router_non_admin(self): self._test_gw_router_create_adds_global_router(True) def _test_router_create_adds_no_global_router(self, set_context=False): with self.router(set_context=set_context) as router: r = router['router'] self.plugin._process_backlogged_routers() # tenant routers q_p = '%s=None' % ROUTER_ROLE_ATTR t_rtrs = self._list('routers', query_params=q_p)['routers'] self.assertEqual(len(t_rtrs), 1) t_rtr = t_rtrs[0] self.assertEqual(t_rtr['id'], r['id']) # global router q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_GLOBAL) g_rtrs = self._list('routers', query_params=q_p)['routers'] self.assertEqual(len(g_rtrs), 0) # logical global router for global routers HA q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_LOGICAL_GLOBAL) g_l_rtrs = self._list('routers', query_params=q_p)['routers'] self.assertEqual(len(g_l_rtrs), 0) notifier = self.plugin.agent_notifiers[AGENT_TYPE_L3_CFG] # ensure *no* update notifications where sent for global # router (as there should be none) or logical global router for call in notifier.method_calls: if call[0] != 'router_deleted': self.assertNotIn(call[1][1][0][ROUTER_ROLE_ATTR], [ROUTER_ROLE_GLOBAL, ROUTER_ROLE_LOGICAL_GLOBAL]) def test_router_create_adds_no_global_router(self): self._test_router_create_adds_no_global_router() def test_router_create_adds_no_global_router_non_admin(self): self._test_router_create_adds_no_global_router(True) def _verify_updated_routers(self, router_ids, hd_id=None, call_index=1): # tenant routers q_p = '%s=None' % ROUTER_ROLE_ATTR r_ids = {r['id'] for r in self._list( 'routers', query_params=q_p)['routers']} self.assertEqual(len(r_ids), len(router_ids)) for r_id in r_ids: self.assertIn(r_id, router_ids) # global routers q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_GLOBAL) g_rtrs = self._list('routers', query_params=q_p)['routers'] # logical global router for global routers HA q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_LOGICAL_GLOBAL) g_l_rtrs = self._list('routers', query_params=q_p)['routers'] notifier = self.plugin.agent_notifiers[AGENT_TYPE_L3_CFG] if hd_id: self.assertEqual(len(g_rtrs), 1) g_rtr = g_rtrs[0] self.assertEqual( g_rtr['name'].endswith(hd_id[-cisco_constants.ROLE_ID_LEN:]), True) self.assertEqual(len(g_l_rtrs), 1) g_l_rtr = g_l_rtrs[0] self.assertEqual(g_l_rtr['name'], LOGICAL_ROUTER_ROLE_NAME) self.assertEqual(g_l_rtr[AUTO_SCHEDULE_ATTR], False) # routers_updated notification call_index is for global router notify_call = notifier.method_calls[call_index] self.assertEqual(notify_call[0], 'routers_updated') updated_routers = notify_call[1][1] self.assertEqual(len(updated_routers), 1) self.assertEqual(updated_routers[0]['id'], g_rtr['id']) else: self.assertEqual(len(g_rtrs), 0) self.assertEqual(len(g_l_rtrs), 0) # ensure *no* update notifications where sent for logical global router for call in notifier.method_calls: if call[0] != 'router_deleted': self.assertNotIn(call[1][1][0][ROUTER_ROLE_ATTR], [ROUTER_ROLE_LOGICAL_GLOBAL]) def _test_router_update_set_gw_adds_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) with self.router(tenant_id=tenant_id, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] # backlog processing will trigger one routers_updated # notification containing r1 and r2 self.plugin._process_backlogged_routers() # should have no global router yet r_ids = {r1['id'], r2['id']} self._verify_updated_routers(r_ids) ext_gw = {'network_id': s['subnet']['network_id']} r_spec = {'router': {l3.EXTERNAL_GW_INFO: ext_gw}} r1_after = self._update('routers', r1['id'], r_spec)['router'] hd_id = r1_after[HOSTING_DEVICE_ATTR] # should now have one global router self._verify_updated_routers(r_ids, hd_id) self._update('routers', r2['id'], r_spec) # should still have only one global router self._verify_updated_routers(r_ids, hd_id) def test_router_update_set_gw_adds_global_router(self): self._test_router_update_set_gw_adds_global_router() def test_router_update_set_gw_adds_global_router_non_admin(self): self._test_router_update_set_gw_adds_global_router(True) def _test_router_update_unset_gw_keeps_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] # backlog processing will trigger one routers_updated # notification containing r1 and r2 self.plugin._process_backlogged_routers() r1_after = self._show('routers', r1['id'])['router'] hd_id = r1_after[HOSTING_DEVICE_ATTR] r_ids = {r1['id'], r2['id']} # should have one global router now self._verify_updated_routers(r_ids, hd_id, 0) r_spec = {'router': {l3.EXTERNAL_GW_INFO: None}} self._update('routers', r1['id'], r_spec) # should still have one global router self._verify_updated_routers(r_ids, hd_id, 0) self._update('routers', r2['id'], r_spec) # should have no global router now self._verify_updated_routers(r_ids) def test_router_update_unset_gw_keeps_global_router(self): self._test_router_update_unset_gw_keeps_global_router() def test_router_update_unset_gw_keeps_global_router_non_admin(self): self._test_router_update_unset_gw_keeps_global_router(True) def _verify_deleted_routers(self, hd_id=None, id_global_router=None): # global routers q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_GLOBAL) g_rtrs = self._list('routers', query_params=q_p)['routers'] if hd_id: self.assertEqual(len(g_rtrs), 1) g_rtr = g_rtrs[0] self.assertEqual(g_rtr['name'].endswith( hd_id[-cisco_constants.ROLE_ID_LEN:]), True) return g_rtrs[0]['id'] else: self.assertEqual(len(g_rtrs), 0) notifier = self.plugin.agent_notifiers[AGENT_TYPE_L3_CFG] # ensure last router_deleted notification was for global router notify_call = notifier.method_calls[-1] self.assertEqual(notify_call[0], 'router_deleted') deleted_router = notify_call[1][1] self.assertEqual(deleted_router['id'], id_global_router) def _test_gw_router_delete_removes_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] self.plugin._process_backlogged_routers() r1_after = self._show('routers', r1['id'])['router'] hd_id = r1_after[HOSTING_DEVICE_ATTR] self._delete('routers', r1['id']) # should still have the global router id_global_router = self._verify_deleted_routers(hd_id) self._delete('routers', r2['id']) # should be no global router now self._verify_deleted_routers(id_global_router=id_global_router) def test_gw_router_delete_removes_global_router(self): self._test_gw_router_delete_removes_global_router() def test_gw_router_delete_removes_global_router_non_admin(self): self._test_gw_router_delete_removes_global_router(True) def _test_router_delete_removes_no_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] self.plugin._process_backlogged_routers() r1_after = self._show('routers', r1['id'])['router'] hd_id = r1_after[HOSTING_DEVICE_ATTR] self._delete('routers', r1['id']) # should still have the global router id_global_router = self._verify_deleted_routers(hd_id) self._delete('routers', r2['id']) # should be no global router now self._verify_deleted_routers(id_global_router=id_global_router) def test_router_delete_removes_no_global_router(self): self._test_router_delete_removes_no_global_router() def test_router_delete_removes_no_global_router_non_admin(self): self._test_router_delete_removes_no_global_router(True) class Asr1kHARouterTypeDriverTestCase( Asr1kRouterTypeDriverTestCase, cisco_ha_test.HAL3RouterTestsMixin): # For the HA tests we need more than one hosting device router_type = 'ASR1k_Neutron_router' _is_ha_tests = True def setUp(self, core_plugin=None, l3_plugin=None, dm_plugin=None, ext_mgr=None): if l3_plugin is None: l3_plugin = cisco_test_case.HA_L3_PLUGIN_KLASS if ext_mgr is None: ext_mgr = (cisco_test_case. TestHASchedulingL3RouterApplianceExtensionManager()) cfg.CONF.set_override('default_ha_redundancy_level', 1, group='ha') super(Asr1kHARouterTypeDriverTestCase, self).setUp( l3_plugin=l3_plugin, ext_mgr=ext_mgr) def _verify_ha_created_routers(self, router_ids, num_redundancy=1, has_gw=None): if has_gw is None: has_gw = [True for r_id in router_ids] temp = {} for i in range(len(router_ids)): temp[router_ids[i]] = has_gw[i] has_gw = temp # tenant HA user_visible routers q_p = '%s=None' % ROUTER_ROLE_ATTR uv_routers = self._list('routers', query_params=q_p)['routers'] uv_r_ids = {r['id'] for r in uv_routers} self.assertEqual(len(uv_r_ids), len(router_ids)) for uv_r_id in uv_r_ids: self.assertIn(uv_r_id, router_ids) # tenant HA redundancy routers q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_HA_REDUNDANCY) rr_id_to_rr = { r['id']: r for r in self._list('routers', query_params=q_p)['routers']} all_rr_ids = rr_id_to_rr.keys() num_rr_ids = 0 hd_ids = set() for uv_r in uv_routers: uv_r_hd_id = uv_r[HOSTING_DEVICE_ATTR] if has_gw[uv_r['id']] is True: self.assertIsNotNone(uv_r[EXTERNAL_GW_INFO]) hd_ids.add(uv_r_hd_id) else: self.assertIsNone(uv_r[EXTERNAL_GW_INFO]) rr_ids = [rr_info['id'] for rr_info in uv_r[ha.DETAILS][ha.REDUNDANCY_ROUTERS]] num = len(rr_ids) num_rr_ids += num self.assertEqual(num, num_redundancy) for rr_id in rr_ids: self.assertIn(rr_id, all_rr_ids) rr = rr_id_to_rr[rr_id] rr_hd_id = rr[HOSTING_DEVICE_ATTR] # redundancy router must not be hosted on same device as its # user visible router since that defeats HA self.assertFalse(uv_r_hd_id == rr_hd_id) if has_gw[uv_r['id']] is True: self.assertIsNotNone(rr[EXTERNAL_GW_INFO]) hd_ids.add(rr_hd_id) else: self.assertIsNone(rr[EXTERNAL_GW_INFO]) self.assertEqual(num_rr_ids, len(all_rr_ids)) # we should have a global router on all hosting devices that hosts # a router (user visible or redundancy router) with gateway set q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_GLOBAL) g_rtrs = self._list('routers', query_params=q_p)['routers'] self.assertEqual(len(g_rtrs), len(hd_ids)) g_rtr_ids = set() for g_rtr in g_rtrs: self.assertIn(g_rtr[HOSTING_DEVICE_ATTR], hd_ids) g_rtr_ids.add(g_rtr['id']) # logical global router for global routers HA q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_LOGICAL_GLOBAL) g_l_rtrs = self._list('routers', query_params=q_p)['routers'] if g_l_rtrs: self.assertEqual(len(g_l_rtrs), 1) g_l_rtr = g_l_rtrs[0] self.assertEqual(g_l_rtr['name'], LOGICAL_ROUTER_ROLE_NAME) self.assertEqual(g_l_rtr[AUTO_SCHEDULE_ATTR], False) else: self.assertEqual(len(g_l_rtrs), 0) notifier = self.plugin.agent_notifiers[AGENT_TYPE_L3_CFG] if g_l_rtrs: # ensure first routers_updated notifications were # for global routers for i in range(len(hd_ids)): notify_call = notifier.method_calls[i] self.assertEqual(notify_call[0], 'routers_updated') updated_routers = notify_call[1][1] self.assertEqual(len(updated_routers), 1) self.assertIn(updated_routers[0]['id'], g_rtr_ids) g_rtr_ids.remove(updated_routers[0]['id']) else: # ensure *no* update notifications where sent for global routers for call in notifier.method_calls: self.assertNotIn(call[1][1][0][ROUTER_ROLE_ATTR], [ROUTER_ROLE_GLOBAL]) # ensure *no* update notifications where sent for logical global router for call in notifier.method_calls: self.assertNotIn(call[1][1][0][ROUTER_ROLE_ATTR], [ROUTER_ROLE_LOGICAL_GLOBAL]) def _test_gw_router_create_adds_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router1: r = router1['router'] self.plugin._process_backlogged_routers() # should now have one user-visible router, its single # redundancy router and two global routers (one for each of # the hosting devices of the aforementioned routers) self._verify_ha_created_routers([r['id']]) def _test_router_create_adds_no_global_router(self, set_context=False): with self.router(set_context=set_context) as router: r = router['router'] self.plugin._process_backlogged_routers() self._verify_ha_created_routers([r['id']], 1, has_gw=[False]) def _verify_ha_updated_router(self, router_id, hd_ids=None, call_index=1, num_redundancy=1, has_gw=True): # ids of hosting devices hosting routers with gateway set hd_ids = hd_ids or set() if router_id: # tenant router uv_r = self._show('routers', router_id)['router'] uv_r_hd_id = uv_r[HOSTING_DEVICE_ATTR] if has_gw is True: self.assertIsNotNone(uv_r[EXTERNAL_GW_INFO]) hd_ids.add(uv_r_hd_id) else: self.assertIsNone(uv_r[EXTERNAL_GW_INFO]) rr_ids = [rr_info['id'] for rr_info in uv_r[ha.DETAILS][ha.REDUNDANCY_ROUTERS]] # tenant HA redundancy routers q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_HA_REDUNDANCY) rr_id_to_rr = { r['id']: r for r in self._list('routers', query_params=q_p)['routers']} all_rr_ids = rr_id_to_rr.keys() self.assertEqual(len(rr_ids), num_redundancy) for rr_id in rr_ids: self.assertIn(rr_id, all_rr_ids) rr = rr_id_to_rr[rr_id] rr_hd_id = rr[HOSTING_DEVICE_ATTR] # redundancy router must not be hosted on same device as its # user visible router since that defeats HA self.assertFalse(uv_r_hd_id == rr_hd_id) if has_gw is True: self.assertIsNotNone(rr[EXTERNAL_GW_INFO]) hd_ids.add(rr_hd_id) else: self.assertIsNone(rr[EXTERNAL_GW_INFO]) # we should have a global router on all hosting devices that hosts # a router (user visible or redundancy router) with gateway set num_devices_hosting_gateway_routers = len(hd_ids) q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_GLOBAL) g_rtrs = self._list('routers', query_params=q_p)['routers'] self.assertEqual(len(g_rtrs), num_devices_hosting_gateway_routers) g_rtr_ids = set() for g_rtr in g_rtrs: self.assertIn(g_rtr[HOSTING_DEVICE_ATTR], hd_ids) g_rtr_ids.add(g_rtr['id']) # logical global router for global routers HA q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_LOGICAL_GLOBAL) g_l_rtrs = self._list('routers', query_params=q_p)['routers'] if num_devices_hosting_gateway_routers > 0: self.assertEqual(len(g_l_rtrs), 1) g_l_rtr = g_l_rtrs[0] self.assertEqual(g_l_rtr['name'], LOGICAL_ROUTER_ROLE_NAME) self.assertEqual(g_l_rtr[AUTO_SCHEDULE_ATTR], False) else: self.assertEqual(len(g_l_rtrs), 0) # global routers notifier = self.plugin.agent_notifiers[AGENT_TYPE_L3_CFG] # routers_updated notification call_index is for global router notify_call = notifier.method_calls[call_index] self.assertEqual(notify_call[0], 'routers_updated') updated_routers = notify_call[1][1] self.assertEqual(len(updated_routers), 1) self.assertEqual(updated_routers[0][ROUTER_ROLE_ATTR], ROUTER_ROLE_GLOBAL) # ensure *no* update notifications where sent for logical global router for call in notifier.method_calls: if call[0] != 'router_deleted': self.assertNotIn(call[1][1][0][ROUTER_ROLE_ATTR], [ROUTER_ROLE_LOGICAL_GLOBAL]) return hd_ids def _test_router_update_set_gw_adds_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) with self.router(tenant_id=tenant_id, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] # backlog processing to schedule the routers self.plugin._process_backlogged_routers() # should have no global router yet r_ids = [r1['id'], r2['id']] self._verify_ha_created_routers(r_ids, 1, has_gw=[False, False]) ext_gw = {'network_id': s['subnet']['network_id']} r_spec = {'router': {l3.EXTERNAL_GW_INFO: ext_gw}} self._update('routers', r1['id'], r_spec) # should now have two global routers, one for hosting device # of user visible router r1 and one for the hosting device r1's # redundancy router hd_ids = self._verify_ha_updated_router(r1['id']) self._update('routers', r2['id'], r_spec) self._verify_ha_updated_router(r2['id'], hd_ids) def _test_router_update_unset_gw_keeps_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] # make sure we have only two eligible hosting devices # in this test qp = "template_id=00000000-0000-0000-0000-000000000005" hds = self._list('hosting_devices', query_params=qp) self._delete('hosting_devices', hds['hosting_devices'][1]['id']) # backlog processing to schedule the routers self.plugin._process_backlogged_routers() self._verify_ha_created_routers([r1['id'], r2['id']]) r_spec = {'router': {l3.EXTERNAL_GW_INFO: None}} self._update('routers', r1['id'], r_spec) # should still have two global routers, we verify using r2 self._verify_ha_updated_router(r2['id']) self._update('routers', r2['id'], r_spec) # should have no global routers now, we verify using r1 self._verify_ha_updated_router(r2['id'], has_gw=False) def _test_gw_router_delete_removes_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] # make sure we have only two eligible hosting devices # in this test qp = "template_id=00000000-0000-0000-0000-000000000005" hds = self._list('hosting_devices', query_params=qp) self._delete('hosting_devices', hds['hosting_devices'][1]['id']) # backlog processing to schedule the routers self.plugin._process_backlogged_routers() self._verify_ha_created_routers([r1['id'], r2['id']]) self._delete('routers', r1['id']) # should still have two global routers, we verify using r2 self._verify_ha_updated_router(r2['id']) self._delete('routers', r2['id']) # should have no global routers now self._verify_ha_updated_router(None) def _test_router_delete_removes_no_global_router(self, set_context=False): tenant_id = _uuid() with self.network(tenant_id=tenant_id) as n_external: res = self._create_subnet(self.fmt, n_external['network']['id'], cidr='10.0.1.0/24', tenant_id=tenant_id) s = self.deserialize(self.fmt, res) self._set_net_external(s['subnet']['network_id']) ext_gw = {'network_id': s['subnet']['network_id']} with self.router(tenant_id=tenant_id, set_context=set_context) as router1,\ self.router(name='router2', tenant_id=tenant_id, external_gateway_info=ext_gw, set_context=set_context) as router2: r1 = router1['router'] r2 = router2['router'] # make sure we have only two eligible hosting devices # in this test qp = "template_id=00000000-0000-0000-0000-000000000005" hds = self._list('hosting_devices', query_params=qp) self._delete('hosting_devices', hds['hosting_devices'][1]['id']) self.plugin._process_backlogged_routers() self._verify_ha_created_routers([r1['id'], r2['id']], has_gw=[False, True]) self._delete('routers', r1['id']) # should still have two global routers, we verify using r2 self._verify_ha_updated_router(r2['id']) self._delete('routers', r2['id']) # should have no global routers now self._verify_ha_updated_router(None) class L3CfgAgentAsr1kRouterTypeDriverTestCase( cisco_test_case.L3RoutertypeAwareHostingDeviceSchedulerTestCaseBase, cisco_ha_test.HAL3RouterTestsMixin): _is_ha_tests = True def setUp(self, core_plugin=None, l3_plugin=None, dm_plugin=None, ext_mgr=None): if l3_plugin is None: l3_plugin = cisco_test_case.HA_L3_PLUGIN_KLASS if ext_mgr is None: ext_mgr = (cisco_test_case. TestHASchedulingL3RouterApplianceExtensionManager()) cfg.CONF.set_override('default_ha_redundancy_level', 1, group='ha') super(L3CfgAgentAsr1kRouterTypeDriverTestCase, self).setUp( l3_plugin=l3_plugin, ext_mgr=ext_mgr) self.orig_get_sync_data = self.plugin.get_sync_data self.plugin.get_sync_data = self.plugin.get_sync_data_ext def tearDown(self): self.plugin.get_sync_data = self.orig_get_sync_data super(L3CfgAgentAsr1kRouterTypeDriverTestCase, self).tearDown() def _verify_sync_data(self, context, ids_colocated_routers, g_l_rtr, g_l_rtr_rr_ids, ha_settings): routers = self.plugin.get_sync_data_ext(context, ids_colocated_routers) self.assertEqual(len(routers), 2) global_router = [r for r in routers if r[ROUTER_ROLE_ATTR] == ROUTER_ROLE_GLOBAL][0] # verify that global router has HA information from logical # global router, in particular VIP address for the gw port # comes from the gw port of the logical global router ha_info = global_router['gw_port']['ha_info'] ha_port_id = ha_info['ha_port']['id'] vip_address = g_l_rtr[l3.EXTERNAL_GW_INFO][ 'external_fixed_ips'][0]['ip_address'] self.assertEqual( ha_info['ha_port']['fixed_ips'][0]['ip_address'], vip_address) self.assertEqual(global_router['gw_port_id'] == ha_port_id, False) self._verify_ha_settings(global_router, ha_settings) rr_info_list = global_router[ha.DETAILS][ha.REDUNDANCY_ROUTERS] self.assertEqual(len(rr_info_list), len(g_l_rtr_rr_ids)) for rr_info in rr_info_list: self.assertIn(rr_info['id'], g_l_rtr_rr_ids) def test_l3_cfg_agent_query_global_router_info(self): with self.subnet(cidr='10.0.1.0/24') as s_ext: self._set_net_external(s_ext['subnet']['network_id']) ext_gw = {'network_id': s_ext['subnet']['network_id']} with self.router(external_gateway_info=ext_gw) as router: r = router['router'] self.plugin._process_backlogged_routers() r_after = self._show('routers', r['id'])['router'] hd_id = r_after[HOSTING_DEVICE_ATTR] id_r_ha_backup = r_after[ha.DETAILS][ ha.REDUNDANCY_ROUTERS][0]['id'] r_ha_backup_after = self._show('routers', id_r_ha_backup)['router'] ha_backup_hd_id = r_ha_backup_after[HOSTING_DEVICE_ATTR] # logical global router for global routers HA q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_LOGICAL_GLOBAL) g_l_rtrs = self._list('routers', query_params=q_p)['routers'] # should be only one logical global router self.assertEqual(len(g_l_rtrs), 1) g_l_rtr = g_l_rtrs[0] g_l_rtr_rr_ids = {r_info['id'] for r_info in g_l_rtr[ ha.DETAILS][ha.REDUNDANCY_ROUTERS]} self.assertEqual(g_l_rtr[ha.ENABLED], True) self.assertEqual(g_l_rtr[routertype.TYPE_ATTR], r[routertype.TYPE_ATTR]) # no auto-scheduling to ensure logical global router is never # instantiated (unless an admin does some bad thing...) self.assertEqual(g_l_rtr[AUTO_SCHEDULE_ATTR], False) # global router on hosting devices q_p = '%s=%s' % (ROUTER_ROLE_ATTR, ROUTER_ROLE_GLOBAL) g_rtrs = {g_r[HOSTING_DEVICE_ATTR]: g_r for g_r in self._list( 'routers', query_params=q_p)['routers']} self.assertEqual(len(g_rtrs), 2) for g_r in g_rtrs.values(): self.assertEqual(g_r[routertype.TYPE_ATTR], r[routertype.TYPE_ATTR]) # global routers should have HA disabled in db self.assertEqual(g_r[ha.ENABLED], False) # global routers should never be auto-scheduled as that # can result in them being moved to another hosting device self.assertEqual(g_r[AUTO_SCHEDULE_ATTR], False) # global router should be redundancy router of the logical # global router for this router type self.assertIn(g_r['id'], g_l_rtr_rr_ids) e_context = context.get_admin_context() # global routers should here have HA setup information from # the logical global router ha_settings = self._get_ha_defaults( ha_type=cfg.CONF.ha.default_ha_mechanism, redundancy_level=2, priority=ha_db.DEFAULT_MASTER_PRIORITY) # verify global router co-located with the user visible router ids_colocated_routers = [r['id'], g_rtrs[hd_id]['id']] self._verify_sync_data(e_context, ids_colocated_routers, g_l_rtr, g_l_rtr_rr_ids, ha_settings) # verify global router co.located with the ha backup # router of the user visible router ids_colocated_routers = [r_ha_backup_after['id'], g_rtrs[ha_backup_hd_id]['id']] self._verify_sync_data(e_context, ids_colocated_routers, g_l_rtr, g_l_rtr_rr_ids, ha_settings)

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null

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e1de7ba01ef13562cad5954a88c5500f10276b50

36

py

Python

readers/__init__.py

nbalas/advent_of_code

7c67a07eccc6e07f56fc448e463c557c937a4aaa

[ "MIT" ]

null

readers/__init__.py

nbalas/advent_of_code

7c67a07eccc6e07f56fc448e463c557c937a4aaa

[ "MIT" ]

null

readers/__init__.py

nbalas/advent_of_code

7c67a07eccc6e07f56fc448e463c557c937a4aaa

[ "MIT" ]

null

from .file_reader import FileReader

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null

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1

0

6

c038cf8240d76a136e440e8bea225a9fa5bf8789

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py

Python

Level2/Lessons12980/najy.py

StudyForCoding/ProgrammersLevel

dc957b1c02cc4383a93b8cbf3d739e6c4d88aa25

[ "MIT" ]

null

Level2/Lessons12980/najy.py

StudyForCoding/ProgrammersLevel

dc957b1c02cc4383a93b8cbf3d739e6c4d88aa25

[ "MIT" ]

null

Level2/Lessons12980/najy.py

StudyForCoding/ProgrammersLevel

dc957b1c02cc4383a93b8cbf3d739e6c4d88aa25

[ "MIT" ]

1

2021-04-05T07:35:59.000Z

#점프와 순간 이동 def solution(n): # n까지 가는 최소 연료 = n/2에서 순간이동 if n==1: return 1 if n%2 == 0: return solution(n/2) else: return solution((n-1)/2)+1 # 홀수에선 n칸 전에 한번 점프 후 순간이동 ''' 정확성 테스트 테스트 1 〉 통과 (0.00ms, 10.1MB) 테스트 2 〉 통과 (0.00ms, 10.1MB) 테스트 3 〉 통과 (0.01ms, 10.2MB) 테스트 4 〉 통과 (0.01ms, 10.2MB) 테스트 5 〉 통과 (0.01ms, 10.2MB) 테스트 6 〉 통과 (0.01ms, 10.1MB) 테스트 7 〉 통과 (0.01ms, 10.1MB) 테스트 8 〉 통과 (0.01ms, 10.1MB) 테스트 9 〉 통과 (0.01ms, 10.2MB) 테스트 10 〉 통과 (0.01ms, 10.2MB) 테스트 11 〉 통과 (0.01ms, 10.1MB) 테스트 12 〉 통과 (0.01ms, 10.2MB) 테스트 13 〉 통과 (0.01ms, 10.2MB) 테스트 14 〉 통과 (0.01ms, 10.2MB) 테스트 15 〉 통과 (0.01ms, 10.1MB) 테스트 16 〉 통과 (0.01ms, 10.2MB) 테스트 17 〉 통과 (0.01ms, 10.1MB) 테스트 18 〉 통과 (0.01ms, 10.1MB) 효율성 테스트 테스트 1 〉 통과 (0.02ms, 10.3MB) 테스트 2 〉 통과 (0.02ms, 10.2MB) 테스트 3 〉 통과 (0.02ms, 10MB) 테스트 4 〉 통과 (0.02ms, 10.2MB) 테스트 5 〉 통과 (0.02ms, 10.1MB) 테스트 6 〉 통과 (0.02ms, 10.2MB) 테스트 7 〉 통과 (0.02ms, 10.2MB) 테스트 8 〉 통과 (0.02ms, 10.2MB) 테스트 9 〉 통과 (0.01ms, 10.1MB) 테스트 10 〉 통과 (0.01ms, 10.1MB) '''

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c0490b866b0b1915729667fff5c3e78d386a4579

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py

Python

pangea/core/tests/test_nested_api.py

LongTailBio/pangea-django

630551dded7f9e38f95eda8c36039e0de46961e7

[ "MIT" ]

null

pangea/core/tests/test_nested_api.py

LongTailBio/pangea-django

630551dded7f9e38f95eda8c36039e0de46961e7

[ "MIT" ]

27

2020-03-26T02:55:12.000Z

2022-03-12T00:55:04.000Z

pangea/core/tests/test_nested_api.py

LongTailBio/pangea-django

630551dded7f9e38f95eda8c36039e0de46961e7

[ "MIT" ]

1

2021-09-14T08:15:54.000Z

from django.urls import reverse from rest_framework import status from rest_framework.test import APITestCase from pangea.core.models import ( PangeaUser, Organization, SampleGroup, SampleLibrary, Sample, SampleGroupAnalysisResult, SampleAnalysisResult, ) class NestedSampleGroupTests(APITestCase): @classmethod def setUpTestData(cls): cls.organization = Organization.objects.create(name='Test Organization HJDH') cls.user = PangeaUser.objects.create(email='user@domain.com', password='Foobar22') def test_create_sample_group(self): """Ensure authorized user can create sample group.""" self.organization.users.add(self.user) self.client.force_authenticate(user=self.user) url = reverse('nested-sample-group-create', kwargs={'org_pk': self.organization.pk}) data = {'name': 'Test Sample Group HJKHJ', 'organization': self.organization.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(SampleGroup.objects.count(), 1) self.assertEqual(SampleGroup.objects.get().name, 'Test Sample Group HJKHJ') def test_create_sample_group_with_name(self): """Ensure authorized user can create sample group.""" self.organization.users.add(self.user) self.client.force_authenticate(user=self.user) url = reverse('nested-sample-group-create', kwargs={'org_pk': self.organization.name}) data = {'name': 'Test Sample Group NBYTU', 'organization': self.organization.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(SampleGroup.objects.count(), 1) self.assertEqual(SampleGroup.objects.get().name, 'Test Sample Group NBYTU') def test_retrieve_sample_group(self): """Ensure authorized user can create sample group.""" grp_name = 'Test Sample Group HGJHJ' self.organization.create_sample_group(name=grp_name, is_public=True) url = reverse('nested-sample-group-detail', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': grp_name, }) response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) def test_retrieve_sample_group_case_insensitive(self): """Ensure authorized user can create sample group.""" grp_name = 'Test Sample Group TRUGKH' self.organization.create_sample_group(name=grp_name, is_public=True) url = reverse('nested-sample-group-detail', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': grp_name.lower(), }) response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) class NestedSampleTests(APITestCase): @classmethod def setUpTestData(cls): cls.organization = Organization.objects.create(name='Test Organization EWKKK') cls.user = PangeaUser.objects.create(email='user@domain.com', password='Foobar22') def test_create_sample(self): """Ensure authorized user can create sample group.""" self.organization.users.add(self.user) self.client.force_authenticate(user=self.user) sample_library = self.organization.create_sample_group(name='Test Library JKLLL', is_library=True) url = reverse('nested-sample-create', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': sample_library.pk, }) data = {'name': 'Test Sample JKLLL', 'library': sample_library.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(Sample.objects.count(), 1) self.assertEqual(Sample.objects.get().name, 'Test Sample JKLLL') self.assertTrue(sample_library.sample_set.filter(pk=response.data.get('uuid')).exists()) def test_create_sample_with_name(self): """Ensure authorized user can create sample group.""" self.organization.users.add(self.user) self.client.force_authenticate(user=self.user) sample_library = self.organization.create_sample_group(name='Test Library', is_library=True) url = reverse('nested-sample-create', kwargs={ 'org_pk': self.organization.name, 'grp_pk': sample_library.name, }) data = {'name': 'Test Sample', 'library': sample_library.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(Sample.objects.count(), 1) self.assertEqual(Sample.objects.get().name, 'Test Sample') self.assertTrue(sample_library.sample_set.filter(pk=response.data.get('uuid')).exists()) def test_retrieve_sample(self): """Ensure authorized user can create sample group.""" grp = self.organization.create_sample_group( name='Test Sample Group KKJSGHFG', is_public=True, is_library=True, ) grp.create_sample(name='Test Sample KKJSGHFG') url = reverse('nested-sample-details', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': grp.name, 'sample_pk': 'Test Sample KKJSGHFG', }) response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) def test_retrieve_sample_from_non_library(self): """Ensure authorized user can create sample group.""" lib = self.organization.create_sample_group( name='Test Library RYJTSDCGEH', is_public=True, is_library=True, ) sample = lib.create_sample(name='Test Sample RYJTSDCGEH') grp = self.organization.create_sample_group( name='Test Sample Group RYJTSDCGEH', is_public=True, is_library=True, ) grp.add_sample(sample) url = reverse('nested-sample-details', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': grp.name, 'sample_pk': 'Test Sample RYJTSDCGEH', }) response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) class AnalysisResultTests(APITestCase): @classmethod def setUpTestData(cls): cls.organization = Organization.objects.create(name='Test Organization') cls.user = PangeaUser.objects.create(email='user@domain.com', password='Foobar22') cls.organization.users.add(cls.user) cls.sample_group = cls.organization.create_sample_group(name='Test Library', is_library=True) cls.sample_library = cls.sample_group.library cls.sample = cls.sample_group.create_sample(name='Test Sample') def test_retrieve_sample_analysis_result(self): """Ensure we can retrieve analysis result.""" self.sample.create_analysis_result(module_name='test_module_KKJSGHFG') url = reverse('nested-sample-ar-details', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': self.sample_group.name, 'sample_pk': self.sample.pk, 'ar_pk': 'test_module_KKJSGHFG', }) response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) def test_retrieve_sample_analysis_result_with_nonexistent_replicate(self): """Ensure we can retrieve analysis result.""" self.sample.create_analysis_result(module_name='test_module_IUWJHREWJ', replicate='foo') url = reverse('nested-sample-ar-details', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': self.sample_group.name, 'sample_pk': self.sample.pk, 'ar_pk': 'test_module_IUWJHREWJ', }) url += '?replicate=bar' response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND) def test_retrieve_sample_analysis_result_with_replicate(self): """Ensure we can retrieve analysis result.""" s1 = self.sample.create_analysis_result(module_name='test_module_TYUKDSJGHV', replicate='foo') s2 = self.sample.create_analysis_result(module_name='test_module_TYUKDSJGHV', replicate='bar') base_url = reverse('nested-sample-ar-details', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': self.sample_group.name, 'sample_pk': self.sample.pk, 'ar_pk': 'test_module_TYUKDSJGHV', }) url = base_url + '?replicate=foo' response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.json()['uuid'], str(s1.uuid)) url = base_url + '?replicate=bar' response = self.client.get(url, format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.json()['uuid'], str(s2.uuid)) def test_create_sample_group_analysis_result(self): self.client.force_authenticate(user=self.user) url = reverse('nested-sample-group-ar-create', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': self.sample_library.pk, }) data = {'module_name': 'taxa', 'sample_group': self.sample_group.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(SampleGroupAnalysisResult.objects.count(), 1) self.assertEqual(SampleGroupAnalysisResult.objects.get().sample_group, self.sample_group) self.assertEqual(SampleGroupAnalysisResult.objects.get().module_name, 'taxa') def test_create_sample_analysis_result(self): self.client.force_authenticate(user=self.user) url = reverse('nested-sample-ar-create', kwargs={ 'org_pk': self.organization.pk, 'grp_pk': self.sample_library.pk, 'sample_pk': self.sample.pk, }) data = {'module_name': 'taxa', 'sample': self.sample.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(SampleAnalysisResult.objects.count(), 1) self.assertEqual(SampleAnalysisResult.objects.get().sample, self.sample) self.assertEqual(SampleAnalysisResult.objects.get().module_name, 'taxa') def test_create_sample_group_analysis_result_with_name(self): self.client.force_authenticate(user=self.user) url = reverse('nested-sample-group-ar-create', kwargs={ 'org_pk': self.organization.name, 'grp_pk': self.sample_library.group.name, }) data = {'module_name': 'taxa', 'sample_group': self.sample_group.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(SampleGroupAnalysisResult.objects.count(), 1) self.assertEqual(SampleGroupAnalysisResult.objects.get().sample_group, self.sample_group) self.assertEqual(SampleGroupAnalysisResult.objects.get().module_name, 'taxa') def test_create_sample_analysis_result_with_name(self): self.client.force_authenticate(user=self.user) url = reverse('nested-sample-ar-create', kwargs={ 'org_pk': self.organization.name, 'grp_pk': self.sample_library.group.name, 'sample_pk': self.sample.name, }) data = {'module_name': 'taxa', 'sample': self.sample.pk} response = self.client.post(url, data, format='json') self.assertEqual(response.status_code, status.HTTP_201_CREATED) self.assertEqual(SampleAnalysisResult.objects.count(), 1) self.assertEqual(SampleAnalysisResult.objects.get().sample, self.sample) self.assertEqual(SampleAnalysisResult.objects.get().module_name, 'taxa')

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0

0.115207

0

null

0

1

0

null

0

6

fbebdd25a13948ec86f09da238b915a6d1385980

168

py

Python

board/views.py

dbwodlf3/DjangoBoard

1d7728f48d83d97c20c46995f2e5e4d2b3052130

[ "MIT" ]

null

board/views.py

dbwodlf3/DjangoBoard

1d7728f48d83d97c20c46995f2e5e4d2b3052130

[ "MIT" ]

null

board/views.py

dbwodlf3/DjangoBoard

1d7728f48d83d97c20c46995f2e5e4d2b3052130

[ "MIT" ]

null

from django.shortcuts import render from django.http import HttpResponse # Create your views here. def views1(request): return render(request, "board/index.html")

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2200f8509df07cb5093489a5f2c78afc2deaa9ae

113

py

Python

src/kinorrt/utilities/__init__.py

XianyiCheng/kinorrt

99e22914e52623bad5aad797971735ad5f339e0f

[ "MIT" ]

1

2022-03-21T01:08:34.000Z

src/kinorrt/utilities/__init__.py

XianyiCheng/kinorrt

99e22914e52623bad5aad797971735ad5f339e0f

[ "MIT" ]

null

src/kinorrt/utilities/__init__.py

XianyiCheng/kinorrt

99e22914e52623bad5aad797971735ad5f339e0f

[ "MIT" ]

2

2021-09-30T21:38:45.000Z

2022-03-01T07:43:42.000Z

from .geometry import * from .obstacle_generation import * from .plotting import * from .transformations import *

28.25

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null

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1

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6

223eaac0cddd7fa955926a13accebb3ee5a535d4

201

py

Python

tests/test_package_info.py

boo13/xCV

9287ba0289420f5d3460821ad2e95c1dab08d1b8

[ "MIT" ]

2

2019-06-05T17:21:03.000Z

2019-07-10T01:34:23.000Z

tests/test_package_info.py

boo13/xCV

9287ba0289420f5d3460821ad2e95c1dab08d1b8

[ "MIT" ]

6

2019-07-16T21:46:42.000Z

2022-01-13T01:30:15.000Z

tests/test_package_info.py

boo13/xCV

9287ba0289420f5d3460821ad2e95c1dab08d1b8

[ "MIT" ]

1

2019-07-16T21:44:20.000Z

def test_package_info(): import xcv from xcv.version import XCV_VERSION assert XCV_VERSION == "0.1.3" assert xcv.__email__ == "boo13bot@gmail.com" assert xcv.__author__ == "Boo13"

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201

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0

null

0

1

0

1

0

1

0

6

22602431a2915090ee31c9f7951b3b3bc3290d8b

233

py

Python

tests/test_fileregistry.py

ownbite/delta_utils

3fd006fb90e5b633486e5f7923c779bfd5ff3140

[ "MIT" ]

null

tests/test_fileregistry.py

ownbite/delta_utils

3fd006fb90e5b633486e5f7923c779bfd5ff3140

[ "MIT" ]

null

tests/test_fileregistry.py

ownbite/delta_utils

3fd006fb90e5b633486e5f7923c779bfd5ff3140

[ "MIT" ]

null

from delta_utils.fileregistry import S3FullScan def test_initiate_fileregistry(spark): file_registry = S3FullScan("/mnt/husqvarna-datalake-omega-live/analytics/usr/linus.wallin/step-poc/file-registry/raw/step-product" , spark)

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233

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1

null

0

1

0

1

0

1

0

6

3f3d2e0057a233abee5a1c670deec9a08f402a3f

53

py

Python

lib/GeneralSchoolCourse/__init__.py

JoshOrndorff/snippets

ef06e03de09897014f88d89a84b597aabde7edaa

[ "Unlicense" ]

null

lib/GeneralSchoolCourse/__init__.py

JoshOrndorff/snippets

ef06e03de09897014f88d89a84b597aabde7edaa

[ "Unlicense" ]

null

lib/GeneralSchoolCourse/__init__.py

JoshOrndorff/snippets

ef06e03de09897014f88d89a84b597aabde7edaa

[ "Unlicense" ]

null

from .GeneralSchoolCourse import GeneralSchoolCourse

26.5

52

0.90566

4

53

12

0.75

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53

1

53

0.979592

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true

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1

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null

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1

0

null

0

1

0

1

0

1

0

6

58c402e2d553f72dcf25fcce18e44b3703fee45d

7,327

py

Python

cyder/cydns/domain/tests/auto_delete.py

ngokevin/chili

36c354ac567471d5e36dccf9eea5096c6b02d4b9

[ "BSD-3-Clause" ]

2

2019-03-16T00:47:09.000Z

2022-03-04T14:39:08.000Z

cyder/cydns/domain/tests/auto_delete.py

ngokevin/chili

36c354ac567471d5e36dccf9eea5096c6b02d4b9

[ "BSD-3-Clause" ]

1

2020-04-24T08:24:55.000Z

cyder/cydns/domain/tests/auto_delete.py

ngokevin/chili

36c354ac567471d5e36dccf9eea5096c6b02d4b9

[ "BSD-3-Clause" ]

null

from django.test import TestCase from cyder.core.system.models import System from cyder.cydns.address_record.models import AddressRecord from cyder.cydhcp.interface.static_intr.models import StaticInterface from cyder.cydns.cname.models import CNAME from cyder.cydns.txt.models import TXT from cyder.cydns.mx.models import MX from cyder.cydns.srv.models import SRV from cyder.cydns.domain.models import Domain from cyder.cydns.nameserver.models import Nameserver from cyder.cydns.utils import ensure_label_domain, prune_tree from cyder.cydns.tests.utils import create_fake_zone class AutoDeleteTests(TestCase): def setUp(self): c = Domain(name='poo') c.save() self.assertFalse(c.purgeable) self.f_c = create_fake_zone('foo.poo', suffix="") self.assertEqual(self.f_c.name, 'foo.poo') def test_cleanup_txt(self): self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) self.assertFalse(self.f_c.purgeable) fqdn = "bar.x.y.z.foo.poo" label, the_domain = ensure_label_domain(fqdn) txt = TXT(label=label, domain=the_domain, txt_data="Nthing") txt.save() self.assertFalse(prune_tree(the_domain)) txt.delete() self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) def test_cleanup_address(self): self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) fqdn = "bar.x.y.z.foo.poo" label, the_domain = ensure_label_domain(fqdn) addr = AddressRecord(label=label, domain=the_domain, ip_type='4', ip_str="10.2.3.4") addr.save() self.assertFalse(prune_tree(the_domain)) addr.delete() self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) def test_cleanup_mx(self): self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) fqdn = "bar.x.y.z.foo.poo" label, the_domain = ensure_label_domain(fqdn) mx = MX(label=label, domain=the_domain, server="foo", priority=4) mx.save() self.assertFalse(prune_tree(the_domain)) mx.delete() self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) def test_ns_cleanup(self): self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) fqdn = "bar.x.y.z.foo.poo" label, the_domain = ensure_label_domain(fqdn) ns = Nameserver(domain=the_domain, server="asdfasffoo") ns.save() self.assertFalse(prune_tree(the_domain)) ns.delete() self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) def test_srv_cleanup(self): self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) fqdn = "bar.x.y.z.foo.poo" label, the_domain = ensure_label_domain(fqdn) srv = SRV( label='_' + label, domain=the_domain, target="foo", priority=4, weight=4, port=34 ) srv.save() self.assertFalse(prune_tree(the_domain)) srv.delete() self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) def test_cleanup_cname(self): # Make sure CNAME record block c = Domain(name='foo1') c.save() self.assertFalse(c.purgeable) f_c = create_fake_zone('foo.foo1', suffix="") self.assertEqual(f_c.name, 'foo.foo1') self.assertFalse(Domain.objects.filter(name="x.y.z.foo.foo1")) self.assertFalse(Domain.objects.filter(name="y.z.foo.foo1")) self.assertFalse(Domain.objects.filter(name="z.foo.foo1")) self.assertTrue(Domain.objects.filter(name="foo.foo1")) self.assertFalse(f_c.purgeable) fqdn = "cname.x.y.z.foo.foo1" label, the_domain = ensure_label_domain(fqdn) cname = CNAME(label=label, domain=the_domain, target="foo") cname.save() self.assertFalse(prune_tree(the_domain)) cname.delete() self.assertFalse(Domain.objects.filter(name="x.y.z.foo.foo1")) self.assertFalse(Domain.objects.filter(name="y.z.foo.foo1")) self.assertFalse(Domain.objects.filter(name="z.foo.foo1")) fqdn = "bar.x.y.z.foo.poo" self.assertTrue(Domain.objects.filter(name="foo.foo1")) def test_cleanup_intr(self): self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo")) Domain.objects.get_or_create(name="arpa") Domain.objects.get_or_create(name="in-addr.arpa") Domain.objects.get_or_create(name="10.in-addr.arpa") fqdn = "bar.x.y.z.foo.poo" label, the_domain = ensure_label_domain(fqdn) system = System() addr = StaticInterface( label=label, domain=the_domain, ip_type='4', ip_str="10.2.3.4", mac="00:11:22:33:44:55", system=system ) addr.save() self.assertFalse(prune_tree(the_domain)) addr.delete() self.assertFalse(Domain.objects.filter(name="x.y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="y.z.foo.poo")) self.assertFalse(Domain.objects.filter(name="z.foo.poo")) self.assertTrue(Domain.objects.filter(name="foo.poo"))

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null

0

1

0

6

58fd78b31ac89d33700f97e5aa69becd83be57ef

12,705

py

Python

test-framework/test-suites/unit/tests/command/stack/commands/remove/host/firmware/mapping/test_command_stack_commands_remove_host_firmware_mapping_plugin_basic.py

kmcm0/stacki

eb9dff1b45d5725b4986e567876bf61707fec28f

[ "BSD-3-Clause" ]

123

2015-05-12T23:36:45.000Z

2017-07-05T23:26:57.000Z

test-framework/test-suites/unit/tests/command/stack/commands/remove/host/firmware/mapping/test_command_stack_commands_remove_host_firmware_mapping_plugin_basic.py

kmcm0/stacki

eb9dff1b45d5725b4986e567876bf61707fec28f

[ "BSD-3-Clause" ]

177

2015-06-05T19:17:47.000Z

2017-07-07T17:57:24.000Z

test-framework/test-suites/unit/tests/command/stack/commands/remove/host/firmware/mapping/test_command_stack_commands_remove_host_firmware_mapping_plugin_basic.py

kmcm0/stacki

eb9dff1b45d5725b4986e567876bf61707fec28f

[ "BSD-3-Clause" ]

32

2015-06-07T02:25:03.000Z

2017-06-23T07:35:35.000Z

from unittest.mock import create_autospec, ANY, patch, call import pytest from stack.commands import DatabaseConnection from stack.commands.remove.host.firmware.mapping import Command from stack.exception import CommandError from stack.commands.remove.host.firmware.mapping.plugin_basic import Plugin class TestRemoveHostFirmwareMappingBasicPlugin: """A test case for the remove host firmware mapping basic plugin.""" @pytest.fixture def basic_plugin(self): """A fixture that returns the plugin instance for use in tests. This sets up the required mocks needed to construct the plugin class. """ mock_command = create_autospec( spec = Command, instance = True, ) mock_command.db = create_autospec( spec = DatabaseConnection, spec_set = True, instance = True, ) return Plugin(command = mock_command) def test_provides(self, basic_plugin): """Ensure that provides returns 'basic'.""" assert basic_plugin.provides() == "basic" def test_validate_make(self, basic_plugin): """Ensure the make is validated if it exists.""" mock_make = "foo" basic_plugin.validate_make(make = mock_make) basic_plugin.owner.ensure_make_exists.assert_called_once_with( make = mock_make, ) def test_validate_make_not_provided(self, basic_plugin): """Ensure the make is not validated if not provided.""" mock_make = "" basic_plugin.validate_make(make = mock_make) basic_plugin.owner.ensure_make_exists.assert_not_called() def test_validate_make_error(self, basic_plugin): """Ensure that validation fails when the make is invalid.""" mock_make = "foo" basic_plugin.owner.ensure_make_exists.side_effect = CommandError( cmd = basic_plugin.owner, msg = "Test error", ) with pytest.raises(CommandError): basic_plugin.validate_make(make = mock_make) def test_validate_model(self, basic_plugin): """Ensure the model is validated if it exists.""" mock_make = "foo" mock_model = "bar" basic_plugin.validate_model(make = mock_make, model = mock_model) basic_plugin.owner.ensure_model_exists.assert_called_once_with( make = mock_make, model = mock_model, ) def test_validate_model_not_provided(self, basic_plugin): """Ensure the model is not validated if not provided.""" mock_make = "foo" mock_model = "" basic_plugin.validate_model(make = mock_make, model = mock_model) basic_plugin.owner.ensure_model_exists.assert_not_called() def test_validate_model_error(self, basic_plugin): """Ensure that validation fails when the model is invalid.""" mock_make = "foo" mock_model = "bar" basic_plugin.owner.ensure_model_exists.side_effect = CommandError( cmd = basic_plugin.owner, msg = "Test error", ) with pytest.raises(CommandError): basic_plugin.validate_model(make = mock_make, model = mock_model) @pytest.mark.parametrize( "hosts, versions, make, model", ( (["foo"], ["bar"], "baz", "bag"), (["foo"], [], "baz", "bag"), (["foo"], [], "baz", ""), (["foo"], [], "", ""), ([], ["bar"], "baz", "bag"), ([], [], "baz", "bag"), ([], [], "baz", ""), ([], [], "", ""), ) ) def test_get_firmware_mappings_to_remove(self, hosts, versions, make, model, basic_plugin): """Test that get_firmware_mappings_to_remove works as expected for every valid argument combination.""" test_inputs = { "hosts": hosts, "versions": versions, "make": make, "model": model, } basic_plugin.owner.db.select.return_value = [["1"]] expected_query_params = list(value for value in test_inputs.values() if value) assert [basic_plugin.owner.db.select.return_value[0][0]] == basic_plugin.get_firmware_mappings_to_remove(**test_inputs) basic_plugin.owner.db.select.assert_called_once_with(ANY, expected_query_params) @patch.object(target = Plugin, attribute = "get_firmware_mappings_to_remove", autospec = True) @patch.object(target = Plugin, attribute = "validate_model", autospec = True) @patch.object(target = Plugin, attribute = "validate_make", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.lowered", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.unique_everseen", autospec = True) def test_run( self, mock_unique_everseen, mock_lowered, mock_validate_make, mock_validate_model, mock_get_firmware_mappings_to_remove, basic_plugin, ): """Test that run works as expected when all params and args are provided and valid.""" mock_args = ["foo", "bar"] expected_hosts = tuple(mock_args) mock_params = {"make": "fizz", "model": "buzz", "versions": "bazz, bang"} expected_versions = tuple(version.strip() for version in mock_params["versions"].split(",") if version.strip()) mock_lowered.return_value = mock_params.values() mock_unique_everseen.side_effect = ( mock_args, expected_versions, ) basic_plugin.owner.getHosts.return_value = expected_hosts mock_get_firmware_mappings_to_remove.return_value = ["1", "2"] basic_plugin.run(args = (mock_params, mock_args)) assert [call(mock_args), call(basic_plugin.owner.fillParams.return_value)] == mock_lowered.mock_calls mock_unique_everseen.assert_any_call(mock_lowered.return_value) # Check the generator expression passed to the second call of unique_everseen assert tuple(mock_unique_everseen.call_args_list[1][0][0]) == expected_versions basic_plugin.owner.getHosts.assert_called_once_with(args = expected_hosts) basic_plugin.owner.fillParams.assert_called_once_with( names = [ ("make", ""), ("model", ""), ("versions", ""), ], params = mock_params, ) mock_validate_make.assert_called_once_with( basic_plugin, make = mock_params["make"], ) mock_validate_model.assert_called_once_with( basic_plugin, make = mock_params["make"], model = mock_params["model"], ) basic_plugin.owner.ensure_firmwares_exist.assert_called_once_with( make = mock_params["make"], model = mock_params["model"], versions = expected_versions, ) mock_get_firmware_mappings_to_remove.assert_called_once_with( basic_plugin, hosts = expected_hosts, make = mock_params["make"], model = mock_params["model"], versions = expected_versions, ) basic_plugin.owner.db.execute.assert_called_once_with( ANY, (mock_get_firmware_mappings_to_remove.return_value,), ) @patch.object(target = Plugin, attribute = "get_firmware_mappings_to_remove", autospec = True) @patch.object(target = Plugin, attribute = "validate_model", autospec = True) @patch.object(target = Plugin, attribute = "validate_make", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.lowered", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.unique_everseen", autospec = True) def test_run_no_hosts_or_versions( self, mock_unique_everseen, mock_lowered, mock_validate_make, mock_validate_model, mock_get_firmware_mappings_to_remove, basic_plugin, ): """Test that run works as expected when hosts and versions are not provided.""" mock_args = [] expected_hosts = tuple(mock_args) mock_params = {"make": "fizz", "model": "buzz", "versions": ""} mock_lowered.return_value = mock_params.values() mock_unique_everseen.return_value = mock_args mock_get_firmware_mappings_to_remove.return_value = ["1", "2"] basic_plugin.run(args = (mock_params, mock_args)) assert [call(mock_args), call(basic_plugin.owner.fillParams.return_value)] == mock_lowered.mock_calls mock_unique_everseen.assert_called_once_with(mock_lowered.return_value) basic_plugin.owner.getHosts.assert_not_called() basic_plugin.owner.fillParams.assert_called_once_with( names = [ ("make", ""), ("model", ""), ("versions", ""), ], params = mock_params, ) mock_validate_make.assert_called_once_with( basic_plugin, make = mock_params["make"], ) mock_validate_model.assert_called_once_with( basic_plugin, make = mock_params["make"], model = mock_params["model"], ) basic_plugin.owner.ensure_firmwares_exist.assert_not_called() mock_get_firmware_mappings_to_remove.assert_called_once_with( basic_plugin, hosts = expected_hosts, make = mock_params["make"], model = mock_params["model"], versions = mock_params["versions"], ) basic_plugin.owner.db.execute.assert_called_once_with( ANY, (mock_get_firmware_mappings_to_remove.return_value,), ) @patch.object(target = Plugin, attribute = "get_firmware_mappings_to_remove", autospec = True) @patch.object(target = Plugin, attribute = "validate_model", autospec = True) @patch.object(target = Plugin, attribute = "validate_make", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.lowered", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.unique_everseen", autospec = True) def test_run_no_mappings_to_remove( self, mock_unique_everseen, mock_lowered, mock_validate_make, mock_validate_model, mock_get_firmware_mappings_to_remove, basic_plugin, ): """Test that run works as expected when there are no mappings to remove.""" mock_args = ["foo", "bar"] expected_hosts = tuple(mock_args) mock_params = {"make": "fizz", "model": "buzz", "versions": "bazz, bang"} expected_versions = tuple(version.strip() for version in mock_params["versions"].split(",") if version.strip()) mock_lowered.return_value = mock_params.values() mock_unique_everseen.side_effect = ( mock_args, expected_versions, ) basic_plugin.owner.getHosts.return_value = expected_hosts mock_get_firmware_mappings_to_remove.return_value = [] basic_plugin.run(args = (mock_params, mock_args)) assert [call(mock_args), call(basic_plugin.owner.fillParams.return_value)] == mock_lowered.mock_calls mock_unique_everseen.assert_any_call(mock_lowered.return_value) # Check the generator expression passed to the second call of unique_everseen assert tuple(mock_unique_everseen.call_args_list[1][0][0]) == expected_versions basic_plugin.owner.getHosts.assert_called_once_with(args = expected_hosts) basic_plugin.owner.fillParams.assert_called_once_with( names = [ ("make", ""), ("model", ""), ("versions", ""), ], params = mock_params, ) mock_validate_make.assert_called_once_with( basic_plugin, make = mock_params["make"], ) mock_validate_model.assert_called_once_with( basic_plugin, make = mock_params["make"], model = mock_params["model"], ) basic_plugin.owner.ensure_firmwares_exist.assert_called_once_with( make = mock_params["make"], model = mock_params["model"], versions = expected_versions, ) mock_get_firmware_mappings_to_remove.assert_called_once_with( basic_plugin, hosts = expected_hosts, make = mock_params["make"], model = mock_params["model"], versions = expected_versions, ) basic_plugin.owner.db.execute.assert_not_called() @pytest.mark.parametrize("failure_mock", ("validate_make", "validate_model", "ensure_firmwares_exist")) @patch.object(target = Plugin, attribute = "get_firmware_mappings_to_remove", autospec = True) @patch.object(target = Plugin, attribute = "validate_model", autospec = True) @patch.object(target = Plugin, attribute = "validate_make", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.lowered", autospec = True) @patch(target = "stack.commands.remove.host.firmware.mapping.plugin_basic.unique_everseen", autospec = True) def test_run_errors( self, mock_unique_everseen, mock_lowered, mock_validate_make, mock_validate_model, mock_get_firmware_mappings_to_remove, failure_mock, basic_plugin, ): """Test that run fails when the params or args are invalid.""" mock_args = ["foo", "bar"] expected_hosts = tuple(mock_args) mock_params = {"make": "fizz", "model": "buzz", "versions": "bazz, bang"} expected_versions = tuple(version.strip() for version in mock_params["versions"].split(",") if version.strip()) mock_lowered.return_value = mock_params.values() mock_unique_everseen.side_effect = ( mock_args, expected_versions, ) basic_plugin.owner.getHosts.return_value = expected_hosts mock_validation_functions = { "validate_make": mock_validate_make, "validate_model": mock_validate_model, "ensure_firmwares_exist": basic_plugin.owner.ensure_firmwares_exist, } mock_validation_functions[failure_mock].side_effect = CommandError( cmd = basic_plugin.owner, msg = "test error", ) with pytest.raises(CommandError): basic_plugin.run(args = (mock_params, mock_args)) basic_plugin.owner.db.execute.assert_not_called()

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4519a092e3b4dba6cd108a0022c8e4d69d652043

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py

Python

examples/ccsd_d2.py

maxscheurer/pdaggerq

e9fef3466e0d0170afc3094ab79e603200e78dfb

[ "Apache-2.0" ]

37

2020-09-17T19:29:18.000Z

2022-03-03T16:29:16.000Z

examples/ccsd_d2.py

maxscheurer/pdaggerq

e9fef3466e0d0170afc3094ab79e603200e78dfb

[ "Apache-2.0" ]

7

2021-02-28T19:22:12.000Z

2022-02-22T15:17:47.000Z

examples/ccsd_d2.py

maxscheurer/pdaggerq

e9fef3466e0d0170afc3094ab79e603200e78dfb

[ "Apache-2.0" ]

6

2021-02-16T22:34:29.000Z

2021-12-04T19:37:23.000Z

import pdaggerq from pdaggerq.parser import contracted_strings_to_tensor_terms def main(): pq = pdaggerq.pq_helper("fermi") # D2(p,q,r,s) = <0|(1 + l1 + l2) e(-T) p*q*sr e(T) |0> pq.set_left_operators(['1','l1','l2']) print('\n', '# D2(i,j,k,l):', '\n') pq.set_left_operators(['1','l1','l2']) pq.add_st_operator(1.0,['e2(i,j,l,k)'],['t1','t2']) pq.simplify() d2_terms_deprince = pq.fully_contracted_strings() d2_terms_ncr = contracted_strings_to_tensor_terms(d2_terms_deprince) for my_term, deprince_term in zip(d2_terms_ncr, d2_terms_deprince): print("#\t", deprince_term) print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, o, o, o]', output_variables=['i', 'j', 'k', 'l'])) print() pq.clear() print('\n', '# D2(i,j,k,a):', '\n') pq.set_left_operators(['1','l1','l2']) pq.add_st_operator(1.0,['e2(i,j,a,k)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, o, o, v]', output_variables=['i', 'j', 'k', 'a'])) print() pq.clear() print('\n', '# D2(i,j,a,l):', '\n') pq.set_left_operators(['1','l1','l2']) pq.add_st_operator(1.0,['e2(i,j,l,a)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, o, v, o]', output_variables=['i', 'j', 'a', 'l'])) print() pq.clear() print('\n', '# D2(i,a,k,l):', '\n') pq.set_left_operators(['1','l1','l2']) pq.add_st_operator(1.0,['e2(i,a,l,k)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, v, o, o]', output_variables=['i', 'a', 'k', 'l'])) print() pq.clear() print('\n', '# D2(a,j,k,l):', '\n') pq.set_left_operators(['1','l1','l2']) pq.add_st_operator(1.0,['e2(a,j,l,k)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, o, o, o]', output_variables=['a', 'j', 'k', 'l'])) print() pq.clear() print('\n', '# D2(a,b,c,d):', '\n') pq.set_left_operators(['1','l1','l2']) pq.add_st_operator(1.0,['e2(a,b,d,c)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, v, v, v]', output_variables=['a', 'b', 'c', 'd'])) print() pq.clear() print('\n', '# D2(a,b,c,i):', '\n') pq.add_st_operator(1.0,['e2(a,b,i,c)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, v, v, o]', output_variables=['a', 'b', 'c', 'i'])) print() pq.clear() print('\n', '# D2(a,b,i,d):', '\n') pq.add_st_operator(1.0,['e2(a,b,d,i)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, v, o, v]', output_variables=['a', 'b', 'i', 'd'])) print() pq.clear() print('\n', '# D2(i,b,c,d):', '\n') pq.add_st_operator(1.0,['e2(i,b,d,c)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, v, v, v]', output_variables=['i', 'b', 'c', 'd'])) print() pq.clear() print('\n', '# D2(a,i,c,d):', '\n') pq.add_st_operator(1.0,['e2(a,i,d,c)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, o, v, v]', output_variables=['a', 'i', 'c', 'd'])) print() pq.clear() print('\n', '# D2(i,j,a,b):', '\n') pq.add_st_operator(1.0,['e2(i,j,b,a)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, o, v, v]', output_variables=['i', 'j', 'a', 'b'])) print() pq.clear() print('\n', '# D2(a,b,i,j):', '\n') pq.add_st_operator(1.0, ['e2(a,b,j,i)'], ['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, v, o, o]', output_variables=['a', 'b', 'i', 'j'])) print() pq.clear() print('\n', '# D2(i,a,j,b):', '\n') pq.add_st_operator(1.0,['e2(i,a,b,j)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, v, o, v]', output_variables=['i', 'a', 'j', 'b'])) print() pq.clear() print('\n', '# D2(a,i,j,b):', '\n') pq.add_st_operator(1.0,['e2(a,i,b,j)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, o, o, v]', output_variables=['a', 'i', 'j', 'b'])) print() pq.clear() print('\n', '# D2(i,a,b,j):', '\n') pq.add_st_operator(1.0, ['e2(i,a,j,b)'], ['t1', 't2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[o, v, v, o]', output_variables=['i', 'a', 'b', 'j'])) print() pq.clear() print('\n', '# D2(a,i,b,j):', '\n') pq.add_st_operator(1.0,['e2(a,i,j,b)'],['t1','t2']) pq.simplify() d2_terms = pq.fully_contracted_strings() d2_terms = contracted_strings_to_tensor_terms(d2_terms) for my_term in d2_terms: print("#\t", my_term) print(my_term.einsum_string(update_val='tpdm[v, o, v, o]', output_variables=['a', 'i', 'b', 'j'])) print() pq.clear() if __name__ == "__main__": main()

36.906977

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36.906977

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0.342105

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null

0

1

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null

0

6

452e331b47da099c036a21e2ea034f678cae5291

17,905

py

Python

datadog_checks_dev/tests/tooling/manifest_validator/test_v2_validator.py

abraham-leal/integrations-core

5062702ddae5314f504e6161c7720a1fcde777ea

[ "BSD-3-Clause" ]

663

2016-08-23T05:23:45.000Z

2022-03-29T00:37:23.000Z

datadog_checks_dev/tests/tooling/manifest_validator/test_v2_validator.py

abraham-leal/integrations-core

5062702ddae5314f504e6161c7720a1fcde777ea

[ "BSD-3-Clause" ]

6,642

2016-06-09T16:29:20.000Z

2022-03-31T22:24:09.000Z

datadog_checks_dev/tests/tooling/manifest_validator/test_v2_validator.py

abraham-leal/integrations-core

5062702ddae5314f504e6161c7720a1fcde777ea

[ "BSD-3-Clause" ]

1,222

2017-01-27T15:51:38.000Z

2022-03-31T18:17:51.000Z

# (C) Datadog, Inc. 2021-present # All rights reserved # Licensed under a 3-clause BSD style license (see LICENSE) import json import os from copy import deepcopy from pathlib import Path import mock import pytest import tests.tooling.manifest_validator.input_constants as input_constants import datadog_checks.dev.tooling.manifest_validator.common.validator as common import datadog_checks.dev.tooling.manifest_validator.v2.validator as v2_validators from datadog_checks.dev.tooling.constants import get_root, set_root from datadog_checks.dev.tooling.datastructures import JSONDict from datadog_checks.dev.tooling.manifest_validator import get_all_validators from datadog_checks.dev.tooling.manifest_validator.constants import V2 # Helpers def get_changed_immutable_short_name_manifest(): """ Helper function to change immutable short names in a manifest """ immutable_attributes_changed_short_name = JSONDict(deepcopy(input_constants.V2_VALID_MANIFEST)) immutable_attributes_changed_short_name['assets']['dashboards'] = { "oracle-changed": "assets/dashboards/example.json" } return immutable_attributes_changed_short_name def get_changed_immutable_attribute_manifest(): """ Helper function to change other immutable attributes in a manifest """ immutable_attributes_changed_attribute = JSONDict(deepcopy(input_constants.V2_VALID_MANIFEST)) immutable_attributes_changed_attribute['app_id'] = 'datadog-oracle-changed' return immutable_attributes_changed_attribute @pytest.fixture def setup_route(): # We want to change the path before and after running each individual test root = Path(os.path.realpath(__file__)).parent.parent.parent.parent.parent.absolute() current_root = get_root() set_root(str(root)) yield root set_root(current_root) @mock.patch( 'datadog_checks.dev.tooling.utils.read_metadata_rows', return_value=input_constants.ORACLE_METADATA_CSV_EXAMPLE ) def test_manifest_v2_all_pass(_, setup_route): """ Run a valid manifest through all V2 validators """ validators = get_all_validators(False, "2.0.0") for validator in validators: # Currently skipping SchemaValidator because of no context object and config if isinstance(validator, v2_validators.SchemaValidator): continue validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) assert not validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_maintainer_validator_incorrect_maintainer(setup_route): """ Ensure MaintainerValidator fails if supplied an incorrect support_email """ incorrect_maintainer_manifest = JSONDict( { "author": { "homepage": "https://www.datadoghq.com", "name": "Datadog", "sales_email": "help@datadoghq.com", "support_email": "fake_email@datadoghq.com", }, } ) # Use specific validator validator = common.MaintainerValidator( is_extras=False, is_marketplace=False, check_in_extras=False, check_in_marketplace=False, version=V2 ) validator.validate('active_directory', incorrect_maintainer_manifest, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_maintainer_validator_invalid_maintainer(setup_route): """ Ensure MaintainerValidator fails if supplied a support_email with non-ASCII characters """ invalid_maintainer_manifest = JSONDict( { "author": { "homepage": "https://www.datadoghq.com", "name": "Datadog", "sales_email": "help@datadoghq.com", "support_email": "Ǩ_help@datadoghq.com", }, } ) # Use specific validator validator = common.MaintainerValidator( is_extras=False, is_marketplace=False, check_in_extras=False, check_in_marketplace=False, version=V2 ) validator.validate('active_directory', invalid_maintainer_manifest, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_maintainer_validator_correct_maintainer(setup_route): # Use specific validator validator = common.MaintainerValidator( is_extras=False, is_marketplace=False, check_in_extras=False, check_in_marketplace=False, version=V2 ) validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_metrics_metadata_validator_file_exists_not_in_manifest(setup_route): """ Ensure MetricsMetadataValidator fails if supplied an empty metadata_path value """ file_exists_not_in_manifest = JSONDict( { "assets": { "integration": { "metrics": { "auto_install": True, "check": "oracle.session_count", "metadata_path": "", "prefix": "oracle.", }, }, }, } ) # Use specific validator validator = common.MetricsMetadataValidator(version=V2) validator.validate('active_directory', file_exists_not_in_manifest, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('os.path.isfile', return_value=False) def test_manifest_v2_metrics_metadata_validator_file_in_manifest_not_exist(_, setup_route): """ Ensure MetricsMetadataValidator fails if supplied a path to a non-existant metadata.csv """ file_in_manifest_does_not_exist = JSONDict( { "assets": { "integration": { "metrics": { "auto_install": True, "check": "oracle.session_count", "metadata_path": "metrics_metadata1.csv", "prefix": "oracle.", }, }, }, } ) # Use specific validator validator = common.MetricsMetadataValidator(version=V2) validator.validate('active_directory', file_in_manifest_does_not_exist, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch( 'datadog_checks.dev.tooling.utils.read_metadata_rows', return_value=input_constants.ORACLE_METADATA_CSV_EXAMPLE ) def test_manifest_v2_metrics_metadata_validator_correct_metadata(_, setup_route): # Use specific validator validator = common.MetricsMetadataValidator(version=V2) validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_metrics_to_check_validator_check_not_in_metadata(setup_route): """ Ensure MetricToCheckValidator fails if the check value is not present in the metadata.csv """ check_not_in_metadata_csv = JSONDict( { "assets": { "integration": { "metrics": { "auto_install": True, "check": "oracle.session_count", "metadata_path": "metrics_metadata.csv", "prefix": "oracle.", }, }, }, } ) # Use specific validator validator = common.MetricToCheckValidator(version=V2) validator.validate('active_directory', check_not_in_metadata_csv, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_metrics_to_check_validator_check_not_in_manifest(setup_route): """ Ensure MetricToCheckValidator fails if supplied an empty check value """ check_not_in_manifest = JSONDict( { "assets": { "integration": { "metrics": { "auto_install": True, "check": "", "metadata_path": "metrics_metadata.csv", "prefix": "oracle.", }, }, }, } ) # Use specific validator validator = common.MetricToCheckValidator(version=V2) validator.validate('active_directory', check_not_in_manifest, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch( 'datadog_checks.dev.tooling.utils.read_metadata_rows', return_value=input_constants.ORACLE_METADATA_CSV_EXAMPLE ) def test_manifest_v2_metrics_metadata_validator_correct_check_in_metadata(_, setup_route): # Use specific validator validator = common.MetricToCheckValidator(version=V2) validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('datadog_checks.dev.tooling.utils.has_logs', return_value=True) def test_manifest_v2_logs_category_validator_has_logs_no_tag(_, setup_route): """ Ensure LogsCategoryValidator fails if the integration has logs but no Log Collection tag """ has_logs_no_tag_manifest = JSONDict( { "classifier_tags": [ "Category::Marketplace", "Offering::Integration", "Offering::UI Extension", ], } ) # Use specific validator validator = common.LogsCategoryValidator(version=V2) validator.validate('active_directory', has_logs_no_tag_manifest, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('datadog_checks.dev.tooling.utils.has_logs', return_value=True) def test_manifest_v2_logs_category_validator_correct_has_logs_correct_tag(_, setup_route): # Use specific validator validator = common.LogsCategoryValidator(version=V2) validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_display_on_public_validator_invalid(setup_route): """ Ensure DisplayOnPublicValidator fails if the display_on_public_website attribute is not True """ display_on_public_invalid_manifest = JSONDict({"app_id": "datadog-oracle"}) # Use specific validator validator = v2_validators.DisplayOnPublicValidator(version=V2) validator.validate('active_directory', display_on_public_invalid_manifest, False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed def test_manifest_v2_display_on_public_validator_valid(setup_route): display_on_public_valid_manifest = JSONDict({"display_on_public_website": True}) # Use specific validator validator = v2_validators.DisplayOnPublicValidator(version=V2) validator.validate('active_directory', display_on_public_valid_manifest, False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('requests.post', return_value=input_constants.MockedResponseInvalid()) def test_manifest_v2_schema_validator_manifest_invalid(_, setup_route): """ Ensure SchemaValidator fails if a 400 status_code is received from request """ # Use specific validator validator = v2_validators.SchemaValidator(ctx=input_constants.MockedContextObj(), version=V2, skip_if_errors=False) validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('requests.post', return_value=input_constants.MockedResponseValid()) def test_manifest_v2_schema_validator_manifest_valid(_, setup_route): # Use specific validator validator = v2_validators.SchemaValidator(ctx=input_constants.MockedContextObj(), version=V2, skip_if_errors=False) validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed @mock.patch( 'datadog_checks.dev.tooling.manifest_validator.common.validator.git_show_file', return_value=json.dumps(input_constants.V2_VALID_MANIFEST), ) def test_manifest_v2_immutable_attributes_validator_invalid_attribute_change(_, setup_route): """ Ensure ImmutableAttributesValidator fails if an immutable attribute is changed """ # Use specific validator validator = common.ImmutableAttributesValidator(version=V2) validator.validate('active_directory', JSONDict(get_changed_immutable_attribute_manifest()), False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch( 'datadog_checks.dev.tooling.manifest_validator.common.validator.git_show_file', return_value=json.dumps(input_constants.V2_VALID_MANIFEST), ) def test_manifest_v2_immutable_attributes_validator_invalid_short_name_change(_, setup_route): """ Ensure ImmutableAttributesValidator fails if the short name of an asset is changed """ # Use specific validator validator = common.ImmutableAttributesValidator(version=V2) validator.validate('active_directory', JSONDict(get_changed_immutable_short_name_manifest()), False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch( 'datadog_checks.dev.tooling.manifest_validator.common.validator.git_show_file', return_value=input_constants.IMMUTABLE_ATTRIBUTES_V1_MANIFEST, ) def test_manifest_v2_immutable_attributes_validator_version_upgrade(_, setup_route): """ Ensure ImmutableAttributesValidator skips validations if the manifest is being upgraded from v1 to v2 """ # Use specific validator validator = common.ImmutableAttributesValidator(version=V2) validator.validate('active_directory', input_constants.IMMUTABLE_ATTRIBUTES_V2_MANIFEST, False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed @mock.patch( 'datadog_checks.dev.tooling.manifest_validator.common.validator.git_show_file', return_value=json.dumps(input_constants.V2_VALID_MANIFEST), ) def test_manifest_v2_immutable_attributes_validator_valid_change(_, setup_route): # Use specific validator validator = common.ImmutableAttributesValidator(version=V2) validator.validate('active_directory', JSONDict(input_constants.V2_VALID_MANIFEST), False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('os.path.getsize', return_value=300000) def test_manifest_v2_media_gallery_validator_pass(_, setup_route): # Use specific validator validator = v2_validators.MediaGalleryValidator(is_marketplace=True, version=V2, check_in_extras=False) validator.validate('active_directory', JSONDict(input_constants.VALID_MEDIA_MANIFEST), False) # Assert test case assert not validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('os.path.getsize', return_value=1300000) def test_manifest_v2_media_gallery_validator_image_size_too_large(_, setup_route): # Use specific validator validator = v2_validators.MediaGalleryValidator(is_marketplace=True, version=V2, check_in_extras=False) validator.validate('active_directory', JSONDict(input_constants.VALID_MEDIA_MANIFEST), False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('os.path.getsize', return_value=300000) def test_manifest_v2_media_gallery_validator_too_many_videos(_, setup_route): # Use specific validator validator = v2_validators.MediaGalleryValidator(is_marketplace=True, version=V2, check_in_extras=False) validator.validate('active_directory', JSONDict(input_constants.INVALID_MEDIA_MANIFEST_TOO_MANY_VIDEOS), False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('os.path.getsize', return_value=300000) def test_manifest_v2_media_gallery_validator_bad_structure(_, setup_route): # Use specific validator validator = v2_validators.MediaGalleryValidator(is_marketplace=True, version=V2, check_in_extras=False) validator.validate('active_directory', JSONDict(input_constants.INVALID_MEDIA_MANIFEST_BAD_STRUCTURE), False) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed @mock.patch('os.path.getsize', return_value=300000) def test_manifest_v2_media_gallery_validator_incorrect_vimeo_id_type(_, setup_route): # Use specific validator validator = v2_validators.MediaGalleryValidator(is_marketplace=True, version=V2, check_in_extras=False) validator.validate( 'active_directory', JSONDict(input_constants.INVALID_MEDIA_MANIFEST_INCORRECT_VIMEO_ID_TYPE), False ) # Assert test case assert validator.result.failed, validator.result assert not validator.result.fixed

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453d02047f5575a1896445c8fa5317d5dc2bd4c9

213

py

Python

tests/calendar/test_calendar.py

matthewgdv/office

8a779cecb9382a196a34a358c43d23a30c48bb04

[ "MIT" ]

1

2020-12-26T16:08:42.000Z

tests/calendar/test_calendar.py

matthewgdv/office

8a779cecb9382a196a34a358c43d23a30c48bb04

[ "MIT" ]

null

tests/calendar/test_calendar.py

matthewgdv/office

8a779cecb9382a196a34a358c43d23a30c48bb04

[ "MIT" ]

1

2021-05-30T11:25:20.000Z

# import pytest class TestCalendar: def test_events(self): # synced assert True def test_event(self): # synced assert True def test_new_event(self): # synced assert True

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13,026

py

Python

models/encoder.py

laddie132/LW-PT

28b469ba68a5d4fba68b992cff5372e63ec2ed42

[ "MIT" ]

9

2020-08-20T18:15:43.000Z

2022-02-10T02:54:30.000Z

models/encoder.py

laddie132/LW-PT

28b469ba68a5d4fba68b992cff5372e63ec2ed42

[ "MIT" ]

1

2021-11-19T01:29:47.000Z

2021-11-19T09:58:38.000Z

models/encoder.py

laddie132/LW-PT

28b469ba68a5d4fba68b992cff5372e63ec2ed42

[ "MIT" ]

3

2021-05-29T02:11:34.000Z

2021-12-14T15:43:22.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- __author__ = "Han" __email__ = "liuhan132@foxmail.com" from .layers import * class LWBiRNNEncoder(torch.nn.Module): """ Label-Wise Bidirectional RNN encoder on word-level for document representation Inputs: doc_emb: (batch, doc_len, emb_dim) doc_mask: (batch, doc_len) label: (batch, label_size) or None Outputs: doc_rep: (batch, hidden_size * 2) / (batch, label_size, hidden_size * 2) """ def __init__(self, model_config): super(LWBiRNNEncoder, self).__init__() embedding_dim = model_config['embedding_dim'] hidden_size = model_config['hidden_size'] label_size = model_config['label_size'] dropout_p = model_config['dropout_p'] enable_layer_norm = model_config['layer_norm'] cell = model_config['cell'] num_layers = model_config['num_layers'] self.doc_rnn = MyRNNBase(mode=cell, input_size=embedding_dim, hidden_size=hidden_size, bidirectional=True, dropout_p=dropout_p, enable_layer_norm=enable_layer_norm, batch_first=True, num_layers=num_layers) self.doc_attention = MultiHeadSelfAttention(in_features=hidden_size * 2, labels=label_size) def forward(self, doc_emb, doc_mask, label=None): visual_parm = {} # (batch, doc_len, hidden_size * 2) doc_rep, _ = self.doc_rnn(doc_emb, doc_mask) # (batch, hidden_size * 2) / (batch, label_size, hidden_size * 2) doc_rep, doc_word_att_p = self.doc_attention(doc_rep, label, doc_mask) visual_parm['doc_word_att_p'] = doc_word_att_p return doc_rep, visual_parm class HLWANEncoder(torch.nn.Module): """ Hierarchical Label-Wise Attention Network for document representation Inputs: doc_emb: (batch, doc_sent_len, doc_word_len, emb_dim) doc_mask: (batch, doc_sent_len, doc_word_len) label: (batch, label_size) Outputs: doc_rep: (batch, hidden_size * 2) """ def __init__(self, model_config): super(HLWANEncoder, self).__init__() embedding_dim = model_config['embedding_dim'] hidden_size = model_config['hidden_size'] label_size = model_config['label_size'] dropout_p = model_config['dropout_p'] enable_layer_norm = model_config['layer_norm'] cell = model_config['cell'] num_layers = model_config['num_layers'] self.doc_word_rnn = MyRNNBase(mode=cell, input_size=embedding_dim, hidden_size=hidden_size, bidirectional=True, dropout_p=dropout_p, enable_layer_norm=enable_layer_norm, batch_first=True, num_layers=num_layers) self.doc_word_attention = MultiHeadSelfAttention(in_features=hidden_size * 2, labels=label_size) self.doc_sentence_rnn = MyRNNBase(mode=cell, input_size=hidden_size * 2, hidden_size=hidden_size, bidirectional=True, dropout_p=dropout_p, enable_layer_norm=enable_layer_norm, batch_first=True, num_layers=num_layers) self.doc_sentence_attention = MultiHeadSelfAttention(in_features=hidden_size * 2, labels=label_size) def forward(self, doc_emb, doc_mask, label=None): visual_parm = {} batch, doc_sent_len, doc_word_len, _ = doc_emb.size() doc_word_emb = doc_emb.view(batch * doc_sent_len, doc_word_len, -1) doc_word_mask = doc_mask.view(batch * doc_sent_len, doc_word_len) if label is not None: word_level_label = label.unsqueeze(1).expand(batch, doc_sent_len, -1).contiguous() word_level_label = word_level_label.view(batch * doc_sent_len, -1) else: word_level_label = None # (batch * doc_sent_len, doc_word_len, hidden_size * 2) doc_word_rep, _ = self.doc_word_rnn(doc_word_emb, doc_word_mask) # (batch * doc_sent_len, hidden_size * 2) / (batch * doc_sent_len, label_size, hidden_size * 2) doc_sent_emb, doc_word_att_p = self.doc_word_attention(doc_word_rep, word_level_label, doc_word_mask) visual_parm['doc_word_att_p'] = doc_word_att_p doc_sent_mask = compute_top_layer_mask(doc_mask) # TODO: mismatch for aapd hier if label is not None: # (batch, doc_sent_len, hidden_size * 2) doc_sent_emb = doc_sent_emb.view(batch, doc_sent_len, -1) else: # (batch * label_size, doc_sent_len, hidden * 2) label_size = doc_sent_emb.shape[1] doc_sent_emb = doc_sent_emb.view(batch, doc_sent_len, label_size, -1).transpose(1, 2) doc_sent_emb = doc_sent_emb.reshape(batch * label_size, doc_sent_len, -1) doc_sent_mask = doc_sent_mask.unsqueeze(1).expand(-1, label_size, -1) doc_sent_mask = doc_sent_mask.reshape(batch * label_size, -1) # (batch, doc_sent_len, hidden_size * 2) / (batch * label_size, doc_sent_len, hidden_size * 2) doc_sent_rep, _ = self.doc_sentence_rnn(doc_sent_emb, doc_sent_mask) doc_sent_len = doc_sent_rep.shape[1] doc_sent_mask = doc_sent_mask[:, :doc_sent_len] # (batch, hidden_size * 2) / (batch * label_size, label_size, hidden_size * 2) doc_rep, doc_sent_att_p = self.doc_sentence_attention(doc_sent_rep, label, doc_sent_mask) if label is None: label_size = doc_rep.shape[1] hsize = doc_rep.shape[-1] doc_rep = doc_rep.view(batch, label_size, label_size, -1) select_idx = torch.eye(label_size, device=doc_rep.device).unsqueeze(-1).\ repeat(batch, 1, 1, hsize).bool() doc_rep = doc_rep[select_idx].view(batch, label_size, -1) # (batch, label_size, h * 2) doc_sent_att_p = doc_sent_att_p.view(batch, label_size, label_size, -1) select_idx = torch.eye(label_size, device=doc_rep.device).unsqueeze(-1).\ repeat(batch, 1, 1, doc_sent_len).bool() doc_sent_att_p = doc_sent_att_p[select_idx].view(batch, label_size, -1) # (batch, label_size, len) visual_parm['doc_sent_att_p'] = doc_sent_att_p return doc_rep, visual_parm class BiRNNEncoder(torch.nn.Module): """ Bidirectional RNN encoder on word-level for document representation Inputs: doc_emb: (batch, doc_len, emb_dim) doc_mask: (batch, doc_len) label: (batch, label_size) Outputs: doc_rep: (batch, hidden_size * 2) """ def __init__(self, model_config): super(BiRNNEncoder, self).__init__() embedding_dim = model_config['embedding_dim'] hidden_size = model_config['hidden_size'] dropout_p = model_config['dropout_p'] enable_layer_norm = model_config['layer_norm'] cell = model_config['cell'] num_layers = model_config['num_layers'] self.doc_rnn = MyRNNBase(mode=cell, input_size=embedding_dim, hidden_size=hidden_size, bidirectional=True, dropout_p=dropout_p, enable_layer_norm=enable_layer_norm, batch_first=True, num_layers=num_layers) self.doc_attention = SelfAttention(in_features=hidden_size * 2) def forward(self, doc_emb, doc_mask, label=None): visual_parm = {} # (batch, doc_len, hidden_size * 2) doc_rep, _ = self.doc_rnn(doc_emb, doc_mask) # (batch, hidden_size * 2) doc_rep, doc_word_att_p = self.doc_attention(doc_rep, doc_mask) visual_parm['doc_word_att_p'] = doc_word_att_p return doc_rep, visual_parm class HANEncoder(torch.nn.Module): """ Hierarchical Attention Network for document representation Inputs: doc_emb: (batch, doc_sent_len, doc_word_len, emb_dim) doc_mask: (batch, doc_sent_len, doc_word_len) Outputs: doc_rep: (batch, hidden_size * 2) """ def __init__(self, model_config): super(HANEncoder, self).__init__() embedding_dim = model_config['embedding_dim'] hidden_size = model_config['hidden_size'] dropout_p = model_config['dropout_p'] enable_layer_norm = model_config['layer_norm'] cell = model_config['cell'] num_layers = model_config['num_layers'] self.doc_word_rnn = MyRNNBase(mode=cell, input_size=embedding_dim, hidden_size=hidden_size, bidirectional=True, dropout_p=dropout_p, enable_layer_norm=enable_layer_norm, batch_first=True, num_layers=num_layers) self.doc_word_attention = SelfAttention(in_features=hidden_size * 2) self.doc_sentence_rnn = MyRNNBase(mode=cell, input_size=hidden_size * 2, hidden_size=hidden_size, bidirectional=True, dropout_p=dropout_p, enable_layer_norm=enable_layer_norm, batch_first=True, num_layers=num_layers) self.doc_sentence_attention = SelfAttention(in_features=hidden_size * 2) def forward(self, doc_emb, doc_mask, label=None): visual_parm = {} batch, doc_sent_len, doc_word_len, _ = doc_emb.size() doc_word_emb = doc_emb.view(batch * doc_sent_len, doc_word_len, -1) doc_word_mask = doc_mask.view(batch * doc_sent_len, doc_word_len) # (batch * doc_sent_len, doc_word_len, hidden_size * 2) doc_word_rep, _ = self.doc_word_rnn(doc_word_emb, doc_word_mask) # (batch * doc_sent_len, hidden_size * 2) doc_sent_emb, doc_word_att_p = self.doc_word_attention(doc_word_rep, doc_word_mask) visual_parm['doc_word_att_p'] = doc_word_att_p # (batch, doc_sent_len, hidden_size * 2) doc_sent_emb = doc_sent_emb.view(batch, doc_sent_len, -1) doc_sent_mask = compute_top_layer_mask(doc_mask) # (batch, doc_sent_len, hidden_size * 2) doc_sent_rep, _ = self.doc_sentence_rnn(doc_sent_emb, doc_sent_mask) doc_sent_len = doc_sent_rep.shape[1] doc_sent_mask = doc_sent_mask[:, :doc_sent_len] # (batch, hidden_size * 2) doc_rep, doc_sent_att_p = self.doc_sentence_attention(doc_sent_rep, doc_sent_mask) visual_parm['doc_sent_att_p'] = doc_sent_att_p return doc_rep, visual_parm class CNNEncoder(torch.nn.Module): def __init__(self, model_config): super(CNNEncoder, self).__init__() embedding_dim = model_config['embedding_dim'] dropout_p = model_config['dropout_p'] Co = 100 Ks = [3, 4, 5] self.convs1 = torch.nn.ModuleList([torch.nn.Conv2d(1, Co, (K, embedding_dim)) for K in Ks]) ''' self.conv13 = nn.Conv2d(Ci, Co, (3, D)) self.conv14 = nn.Conv2d(Ci, Co, (4, D)) self.conv15 = nn.Conv2d(Ci, Co, (5, D)) ''' self.dropout = torch.nn.Dropout(dropout_p) def conv_and_pool(self, x, conv): x = F.relu(conv(x)).squeeze(3) # (N, Co, W) x = F.max_pool1d(x, x.size(2)).squeeze(2) return x def forward(self, x, *args): x = x.unsqueeze(1) # (N, Ci, W, D) x = [F.relu(conv(x)).squeeze(3) for conv in self.convs1] # [(N, Co, W), ...]*len(Ks) x = [F.max_pool1d(i, i.size(2)).squeeze(2) for i in x] # [(N, Co), ...]*len(Ks) x = torch.cat(x, 1) ''' x1 = self.conv_and_pool(x,self.conv13) #(N,Co) x2 = self.conv_and_pool(x,self.conv14) #(N,Co) x3 = self.conv_and_pool(x,self.conv15) #(N,Co) x = torch.cat((x1, x2, x3), 1) # (N,len(Ks)*Co) ''' x = self.dropout(x) # (N, len(Ks)*Co) return x, None

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4.142857

0.085956

0.07671

0.046756

0.052601

0.841029

0.831239

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0.77294

0.753653

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0.124324

0

null

0

1

0

null

0

6

18a6176a4ac419eb508a129af46b130cc0b1f5ff

398

py

Python

h/claim/util.py

noscripter/h

a7a4095a46683ea08dae62335bbcd53f7ab313e2

[ "MIT" ]

null

h/claim/util.py

noscripter/h

a7a4095a46683ea08dae62335bbcd53f7ab313e2

[ "MIT" ]

null

h/claim/util.py

noscripter/h

a7a4095a46683ea08dae62335bbcd53f7ab313e2

[ "MIT" ]

null

# -*- coding: utf-8 -*- def generate_claim_token(request, userid): return request.registry.claim_serializer.dumps({'userid': userid}) def generate_claim_url(request, userid): ''' Generates a url that a user can visit to claim their account. ''' token = generate_claim_token(request, userid) return request.route_url('claim_account', token=token) def includeme(config): pass

28.428571

73

0.723618

53

398

5.264151

0.509434

0.139785

0.114695

0.179211

0.315412

0

0.002976

0.155779

398

13

74

30.615385

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null

0

1

0

1

0

1

0

6

7a00120e15918c9370a96ab94db0dd57a5ce8b17

32

py

Python

teste.py

gabrielvieira1/Python-course

20e6deca6a75a41e71dcc311ce78acc443feb642

[ "MIT" ]

null

teste.py

gabrielvieira1/Python-course

20e6deca6a75a41e71dcc311ce78acc443feb642

[ "MIT" ]

null

teste.py

gabrielvieira1/Python-course

20e6deca6a75a41e71dcc311ce78acc443feb642

[ "MIT" ]

null

print('Geek University gabriel')

32

0.8125

4

32

6.5

1

0

0.0625

32

1

32

0.866667

0

0.69697

0

1

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true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

e13b598e657c8eeba9152419e8963d91acf68028

123

py

Python

self_supervised/models/layers/__init__.py

jianzhnie/self_supervised

d1e0f31ab032150ab0ad007c1e19773135a5fb79

[ "Apache-2.0" ]

1

2021-12-13T12:31:47.000Z

self_supervised/models/layers/__init__.py

jianzhnie/self_supervised

d1e0f31ab032150ab0ad007c1e19773135a5fb79

[ "Apache-2.0" ]

null

self_supervised/models/layers/__init__.py

jianzhnie/self_supervised

d1e0f31ab032150ab0ad007c1e19773135a5fb79

[ "Apache-2.0" ]

null

''' Author: jianzhnie Date: 2021-12-14 15:15:19 LastEditTime: 2021-12-14 15:15:20 LastEditors: jianzhnie Description: '''

13.666667

33

0.731707

19

123

4.736842

0.631579

0.133333

0.177778

0.222222

0.266667

0

0.256881

0.113821

123

8

34

15.375

0.568807

0.918699

0

null

0

null

0

null

0

null

1

null

true

0

null

1

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null

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1

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1

0

1

0

1

0

null

0

1

0

6

e13b776c9b1fef30b51f97637730369a1abc1e67

36

py

Python

celery_app.py

Hack4Eugene/15th-night-by-dumpsterfire

e130c5bee868f11e7f5c34f1efc5ad6a6dcc022a

[ "MIT" ]

null

celery_app.py

Hack4Eugene/15th-night-by-dumpsterfire

e130c5bee868f11e7f5c34f1efc5ad6a6dcc022a

[ "MIT" ]

null

celery_app.py

Hack4Eugene/15th-night-by-dumpsterfire

e130c5bee868f11e7f5c34f1efc5ad6a6dcc022a

[ "MIT" ]

null

from _15thnight.queue import celery

18

35

0.861111

5

36

6

1

0

0.0625

0.111111

36

1

36

0.875

0

1

0

true

0

1

0

1

0

1

0

null

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1

0

null

0

1

0

1

0

1

0

6

e13ec23a33c2e6713e9fa947efca242468c7808c

36

py

Python

rplugin/python3/lfx/__init__.py

dcampos/nvim-ulf

9b70096bf04133a33f09691b1ef1ac89f8f29a85

[ "MIT" ]

2

2020-10-15T09:34:53.000Z

2020-10-26T10:31:48.000Z

rplugin/python3/lfx/__init__.py

dcampos/nvim-ulf

9b70096bf04133a33f09691b1ef1ac89f8f29a85

[ "MIT" ]

null

rplugin/python3/lfx/__init__.py

dcampos/nvim-ulf

9b70096bf04133a33f09691b1ef1ac89f8f29a85

[ "MIT" ]

1

2020-10-15T09:35:05.000Z

from .lfx import LFX, RequestHelper

18

35

0.805556

5

36

5.8

0.8

0

0.138889

36

1

36

0.935484

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

e16cec62a95786acfea3c7181b4e46463c00af5b

94

py

Python

acondbs/blueprint/graphql_ide/__init__.py

simonsobs/acondbs

6ca11c2889d827ecdb2b54d0cf3b94b8cdd281e6

[ "MIT" ]

null

acondbs/blueprint/graphql_ide/__init__.py

simonsobs/acondbs

6ca11c2889d827ecdb2b54d0cf3b94b8cdd281e6

[ "MIT" ]

24

2020-04-02T19:29:07.000Z

2022-03-08T03:05:43.000Z

acondbs/blueprint/graphql_ide/__init__.py

simonsobs/acondbs

6ca11c2889d827ecdb2b54d0cf3b94b8cdd281e6

[ "MIT" ]

1

2020-04-08T15:48:28.000Z

from .graphiql_newer import GRAPHIQL_NEWER from .graphql_playground import GRAPHQL_PLAYGROUND

31.333333

50

0.893617

12

94

6.666667

0.5

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94

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true

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0

null

0

1

0

1

0

1

0

6

e19c251189f575ab7ec7168997d0b6307ee0edb0

19

py

Python

python/testData/psi/FStringTerminatedByQuoteOfNestedStringLiteral.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/psi/FStringTerminatedByQuoteOfNestedStringLiteral.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/psi/FStringTerminatedByQuoteOfNestedStringLiteral.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

s = f'{f"{'foo'}"}'

19

0.315789

4

19

1.5

0.75

0

0.105263

19

1

19

0.352941

0

0.35

0

null

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null

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null

0

1

0

1

0

null

0

1

0

6

e1ac294cd876b4c88339f435a34c4e7092e67025

1,280

py

Python

blog/migrations/0006_auto_20191202_1249.py

TEOTD/Travel

013deb247429cc4fbff910d1d068a7b87bebe324

[ "MIT" ]

null

blog/migrations/0006_auto_20191202_1249.py

TEOTD/Travel

013deb247429cc4fbff910d1d068a7b87bebe324

[ "MIT" ]

null

blog/migrations/0006_auto_20191202_1249.py

TEOTD/Travel

013deb247429cc4fbff910d1d068a7b87bebe324

[ "MIT" ]

null

# Generated by Django 2.2.7 on 2019-12-02 12:49 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0005_book'), ] operations = [ migrations.AlterField( model_name='places', name='adv1', field=models.CharField(max_length=100), ), migrations.AlterField( model_name='places', name='adv2', field=models.CharField(max_length=100), ), migrations.AlterField( model_name='places', name='adv3', field=models.CharField(max_length=100), ), migrations.AlterField( model_name='places', name='adv4', field=models.CharField(max_length=100), ), migrations.AlterField( model_name='places', name='name', field=models.CharField(max_length=100), ), migrations.AlterField( model_name='places', name='per', field=models.CharField(max_length=100), ), migrations.AlterField( model_name='places', name='price', field=models.CharField(max_length=100), ), ]

26.122449

51

0.527344

118

1,280

5.59322

0.313559

0.212121

0.265152

0.307576

0.75303

0.645455

0

0.053204

0.353906

1,280

48

52

26.666667

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0.035156

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0.666667

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1

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false

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null

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1

0

1

0

1

0

null

0

6

e1c0622e3670de287f2c139a1ee37d8b6f011285

6,669

py

Python

dlmb/losses.py

Jonathan-Andrews/dlmb

552148bcac2ffb4308c8db24599c458652684ed2

[ "MIT" ]

5

2019-11-23T13:32:21.000Z

2022-01-01T16:32:48.000Z

dlmb/losses.py

Jonathan-Andrews/dlmb

552148bcac2ffb4308c8db24599c458652684ed2

[ "MIT" ]

null

dlmb/losses.py

Jonathan-Andrews/dlmb

552148bcac2ffb4308c8db24599c458652684ed2

[ "MIT" ]

null

from abc import ABCMeta, abstractmethod import numpy as np from utils.function_helpers import * class Base_Loss(metaclass=ABCMeta): @abstractmethod def __init__(self) -> None: """ The Base_Loss class is an abstract class for all loss functions. All loss functions must inherit from Base_Loss. """ pass @abstractmethod def map_data(self, y_true:np.ndarray, y_pred:np.ndarray) -> np.ndarray: """ map_data() takes some data and applies a mathematical mapping to it. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Return: output : np.ndarray : An n dimensional numpy array of the mapped data. """ return output @abstractmethod def calculate_gradients(self, y_true:np.ndarray, y_pred:np.ndarray) -> np.ndarray: """ calculate_gradients returns the derivative of the loss function W.R.T the data. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Return: output : np.ndarray : An n dimensional numpy array of gradients. """ return output class Mean_Squared_Error(Base_Loss): def __init__(self) -> None: """ The MSE class is a commonly used regression loss function. """ pass @accepts(self="any", y_true=np.ndarray, y_pred=np.ndarray) def map_data(self, y_true, y_pred) -> np.ndarray: """ Calculates the squared distance between y_true and y_pred. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Returns: output : np.ndarray : An n dimensional numpy array of the mean squared distance between y_true and y_pred. """ return (y_pred-y_true)**2/2 @accepts(self="any", y_true=np.ndarray, y_pred=np.ndarray) def calculate_gradients(self, y_true, y_pred) -> np.ndarray: """ Calculates the derivatives of the function W.R.T y_pred. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Returns: output : np.ndarray : An n dimensional numpy array of the calculated derivatives of the function W.R.T y_pred. """ return y_pred - y_true class Binary_Crossentropy(Base_Loss): def __init__(self) -> None: """ The Binary_crossentropy class measures the performance of a classification model whose output is a probability value between 0 and 1, and where the number of outputs is less than 3. """ pass @accepts(self="any", y_true=np.ndarray, y_pred=np.ndarray) def map_data(self, y_true, y_pred) -> np.ndarray: """ Calculates the distance between y_true and y_pred. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Returns: output : np.ndarray : The mean squared distance between y_true and y_pred. """ part1 = y_true*np.log(y_pred+1.0e-8) # I add 1.0e-8 to make sure 0 isn't going into np.log part2 = (1-y_true)*np.log(1-y_pred+1.0e-8) return -(part1 + part2) @accepts(self="any", y_true=np.ndarray, y_pred=np.ndarray) def calculate_gradients(self, y_true, y_pred) -> np.ndarray: """ Calculates the derivatives of the function W.R.T y_pred. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Returns: output : np.ndarray : An n dimensional numpy array of the calculated derivatives of the function W.R.T y_pred. """ return division_check(y_true,y_pred) - division_check(1-y_true, 1-y_pred) class Crossentropy(Base_Loss): def __init__(self) -> None: """ The Crossentropy class measures the performance of a classification model whose output is a probability value between 0 and 1, and where the number of outputs is more than 2. """ pass @accepts(self="any", y_true=np.ndarray, y_pred=np.ndarray) def map_data(self, y_true, y_pred) -> np.ndarray: """ Calculates the distance between y_true and y_pred. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Returns: output : np.ndarray : The mean squared distance between y_true and y_pred. """ return -(y_true*np.log(y_pred+1.0e-8)) def calculate_gradients(self, y_pred:np.ndarray, y_true:np.ndarray) -> np.ndarray: """ Calculates the derivatives of the function W.R.T y_pred. Arguments: y_true : np.ndarray : An n dimensional numpy array of target values for the output of a neural-net model. y_pred : np.ndarray : An n dimensional numpy array of predicted values from a neural-net model. Returns: output : np.ndarray : An n dimensional numpy array of the calculated derivatives of the function W.R.T y_pred. """ return division_check(y_true, y_pred) def get(loss) -> Base_Loss: """ Finds and returns the correct loss function. Arguments: loss : Base_Loss/str : The loss function the user wants to use. Returns: loss : Base_Loss : The correct loss function. """ if isinstance(loss, str): if loss.lower() in ("mse", "mean_squared_error"): return Mean_Squared_Error() elif loss.lower() in ("bc", "bce", "binary_crossentropy"): return Binary_Crossentropy() elif loss.lower() in ("ce", "crossentropy"): return Crossentropy() else: print("At losses.get(): '%s' is not an available loss function. Has been set to 'Mean_squared_error' by default" % loss) return Mean_squared_error() elif isinstance(loss, Base_Loss): return loss else: raise ValueError("At losses.get(): Expected 'class inheriting from Base_Loss' or 'str' for the argument 'loss', recieved '%s'" % type(loss))

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py

Python

sscls/datasets/utils/__init__.py

poodarchu/sscls

8b1bd94b1ef4f0cef3ec6ecbb48be9dab129687b

[ "MIT" ]

2

2020-04-26T13:41:24.000Z

2020-05-06T10:15:06.000Z

sscls/datasets/utils/__init__.py

poodarchu/sscls

8b1bd94b1ef4f0cef3ec6ecbb48be9dab129687b

[ "MIT" ]

null

sscls/datasets/utils/__init__.py

poodarchu/sscls

8b1bd94b1ef4f0cef3ec6ecbb48be9dab129687b

[ "MIT" ]

null

from .imgproc import imdecode

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py

Python

pycozmo/expressions/__init__.py

nalbion/pycozmo

35ee1ea741ecf7a39affc38d4ff5ad17865fea16

[ "MIT" ]

123

2019-08-25T21:28:23.000Z

2022-03-12T13:54:59.000Z

pycozmo/expressions/__init__.py

nalbion/pycozmo

35ee1ea741ecf7a39affc38d4ff5ad17865fea16

[ "MIT" ]

41

2019-08-25T21:21:37.000Z

2022-02-09T14:20:54.000Z

pycozmo/expressions/__init__.py

nalbion/pycozmo

35ee1ea741ecf7a39affc38d4ff5ad17865fea16

[ "MIT" ]

51

2019-09-04T13:30:02.000Z

2022-01-09T01:20:24.000Z

from .expressions import * # noqa

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py

Python

tests/models/programdb/usage_profile/usage_profile_integration_test.py

weibullguy/ramstk

3ec41d7e2933045a7a8028aed6c6b04365495095

[ "BSD-3-Clause" ]

4

2018-08-26T09:11:36.000Z

2019-05-24T12:01:02.000Z

tests/models/programdb/usage_profile/usage_profile_integration_test.py

weibullguy/ramstk

3ec41d7e2933045a7a8028aed6c6b04365495095

[ "BSD-3-Clause" ]

52

2018-08-24T12:51:22.000Z

2020-12-28T04:59:42.000Z

tests/models/programdb/usage_profile/usage_profile_integration_test.py

weibullguy/ramstk

3ec41d7e2933045a7a8028aed6c6b04365495095

[ "BSD-3-Clause" ]

1

2018-10-11T07:57:55.000Z

# pylint: skip-file # type: ignore # -*- coding: utf-8 -*- # # tests.models.usage_profile.usage_profile_integration_test.py is part of The # RAMSTK Project # # All rights reserved. # Copyright since 2007 Doyle "weibullguy" Rowland doyle.rowland <AT> reliaqual <DOT> com """Class for testing Usage Profile integrations.""" # Third Party Imports import pytest from pubsub import pub from treelib import Tree # RAMSTK Package Imports from ramstk.models.dbrecords import ( RAMSTKEnvironmentRecord, RAMSTKMissionPhaseRecord, RAMSTKMissionRecord, ) from ramstk.models.dbviews import RAMSTKUsageProfileView @pytest.mark.usefixtures( "test_view_model", "test_mission_table_model", "test_mission_phase_table_model", "test_environment_table_model", ) class TestSelectUsageProfile: """Class for testing Usage Profile do_select() and do_select_all() methods.""" def on_succeed_on_select_all(self, tree): """Listen for succeed_retrieve messages.""" assert isinstance(tree, Tree) assert isinstance(tree.get_node("1").data["usage_profile"], RAMSTKMissionRecord) assert isinstance( tree.get_node("1.1").data["usage_profile"], RAMSTKMissionPhaseRecord ) assert isinstance( tree.get_node("1.1.1").data["usage_profile"], RAMSTKEnvironmentRecord ) print("\033[36m\n\tsucceed_retrieve_usage_profile topic was broadcast.") @pytest.mark.integration def test_on_select_all( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should return records tree with missions, mission phases, environments.""" pub.subscribe(self.on_succeed_on_select_all, "succeed_retrieve_usage_profile") test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all(attributes={"revision_id": 1}) test_environment_table_model.do_select_all(attributes={"revision_id": 1}) assert isinstance( test_view_model.tree.get_node("1").data["usage_profile"], RAMSTKMissionRecord, ) assert isinstance( test_view_model.tree.get_node("1.1").data["usage_profile"], RAMSTKMissionPhaseRecord, ) assert isinstance( test_view_model.tree.get_node("1.1.1").data["usage_profile"], RAMSTKEnvironmentRecord, ) assert isinstance( test_view_model.tree.get_node("2").data["usage_profile"], RAMSTKMissionRecord, ) assert isinstance( test_view_model.tree.get_node("2.2").data["usage_profile"], RAMSTKMissionPhaseRecord, ) assert isinstance( test_view_model.tree.get_node("2.2.2").data["usage_profile"], RAMSTKEnvironmentRecord, ) assert isinstance( test_view_model.tree.get_node("3").data["usage_profile"], RAMSTKMissionRecord, ) assert isinstance( test_view_model.tree.get_node("3.3").data["usage_profile"], RAMSTKMissionPhaseRecord, ) assert isinstance( test_view_model.tree.get_node("3.3.3").data["usage_profile"], RAMSTKEnvironmentRecord, ) pub.unsubscribe(self.on_succeed_on_select_all, "succeed_retrieve_usage_profile") @pytest.mark.integration def test_on_select_all_populated_tree( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should clear existing nodes from the records tree and then re-populate.""" test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all(attributes={"revision_id": 1}) test_environment_table_model.do_select_all(attributes={"revision_id": 1}) assert isinstance( test_view_model.tree.get_node("1").data["usage_profile"], RAMSTKMissionRecord, ) assert isinstance( test_view_model.tree.get_node("1.1").data["usage_profile"], RAMSTKMissionPhaseRecord, ) assert isinstance( test_view_model.tree.get_node("1.1.1").data["usage_profile"], RAMSTKEnvironmentRecord, ) pub.subscribe(self.on_succeed_on_select_all, "succeed_retrieve_usage_profile") test_view_model.on_select_all() assert isinstance( test_view_model.tree.get_node("1").data["usage_profile"], RAMSTKMissionRecord, ) assert isinstance( test_view_model.tree.get_node("1.1").data["usage_profile"], RAMSTKMissionPhaseRecord, ) assert isinstance( test_view_model.tree.get_node("1.1.1").data["usage_profile"], RAMSTKEnvironmentRecord, ) pub.unsubscribe(self.on_succeed_on_select_all, "succeed_retrieve_usage_profile") @pytest.mark.integration def test_on_select_all_empty_base_tree( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should return an empty records tree if the base tree is empty.""" test_view_model._dic_trees["mission"] = Tree() assert test_view_model.on_select_all() is None assert test_view_model.tree.depth() == 0 @pytest.mark.usefixtures( "test_view_model", "test_mission_table_model", "test_mission_phase_table_model", "test_environment_table_model", ) class TestInsertUsageProfile: """Class for testing the Usage Profile on_insert() method.""" def on_succeed_insert_mission(self, tree): """Listen for succeed_insert messages.""" assert isinstance(tree, Tree) assert tree.contains("4") print( "\033[36m\n\tsucceed_insert_mission topic was broadcast on mission insert." ) def on_succeed_insert_mission_phase(self, tree): """Listen for succeed_insert messages.""" assert isinstance(tree, Tree) assert tree.contains("1.4") print( "\033[36m\n\tsucceed_insert_mission_phase topic was broadcast on mission " "phase insert." ) def on_succeed_insert_environment(self, tree): """Listen for succeed_insert messages.""" assert isinstance(tree, Tree) assert tree.contains("1.1.4") print( "\033[36m\n\tsucceed_insert_environment topic was broadcast on " "environment insert." ) @pytest.mark.integration def test_do_insert_mission( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should add a new mission record to the records tree.""" test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all( attributes={"revision_id": 1, "mission_id": 1} ) test_environment_table_model.do_select_all( attributes={"revision_id": 1, "mission_phase_id": 1} ) assert not test_view_model.tree.contains("4") pub.subscribe(self.on_succeed_insert_mission, "succeed_retrieve_usage_profile") pub.sendMessage( "request_insert_mission", attributes={ "revision_id": 1, "mission_id": 1, }, ) pub.unsubscribe( self.on_succeed_insert_mission, "succeed_retrieve_usage_profile" ) @pytest.mark.integration def test_do_insert_mission_phase( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should add a new mission phase record to the records tree.""" test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all( attributes={"revision_id": 1, "mission_id": 1} ) test_environment_table_model.do_select_all( attributes={"revision_id": 1, "mission_phase_id": 1} ) assert not test_view_model.tree.contains("1.4") pub.subscribe( self.on_succeed_insert_mission_phase, "succeed_retrieve_usage_profile" ) pub.sendMessage( "request_insert_mission_phase", attributes={ "revision_id": 1, "mission_id": 1, "mission_phase_id": 1, }, ) assert test_view_model.tree.contains("1.4") pub.unsubscribe( self.on_succeed_insert_mission_phase, "succeed_retrieve_usage_profile" ) @pytest.mark.integration def test_do_insert_environment( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should add a new environment record to the records tree.""" test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all( attributes={"revision_id": 1, "mission_id": 1} ) test_environment_table_model.do_select_all( attributes={"revision_id": 1, "mission_id": 1, "mission_phase_id": 1} ) assert not test_view_model.tree.contains("1.1.4") pub.subscribe( self.on_succeed_insert_environment, "succeed_retrieve_usage_profile" ) pub.sendMessage( "request_insert_environment", attributes={ "revision_id": 1, "mission_id": 1, "mission_phase_id": 1, "environment_id": 1, "name": "Condition Name", }, ) assert test_view_model.tree.contains("1.1.4") pub.unsubscribe( self.on_succeed_insert_environment, "succeed_retrieve_usage_profile" ) @pytest.mark.usefixtures( "test_view_model", "test_mission_table_model", "test_mission_phase_table_model", "test_environment_table_model", ) class TestDeleteUsageProfile: """Class for testing the Usage Profile do_delete() method.""" def on_succeed_delete_mission(self, tree): """Listen for succeed_delete messages.""" assert isinstance(tree, Tree) assert not tree.contains("1.1.1") assert not tree.contains("1.1") assert not tree.contains("1") print( "\033[36m\n\tsucceed_retrieve_usage_profile topic was broadcast on mission " "delete." ) def on_succeed_delete_mission_phase(self, tree): """Listen for succeed_delete messages.""" assert isinstance(tree, Tree) assert not tree.contains("2.2.2") assert not tree.contains("2.2") assert tree.contains("2") print( "\033[36m\n\tsucceed_retrieve_usage_profile topic was broadcast on mission " "phase delete." ) def on_succeed_delete_environment(self, tree): """Listen for succeed_delete messages.""" assert isinstance(tree, Tree) assert not tree.contains("3.3.3") assert tree.contains("3.3") assert tree.contains("3") print( "\033[36m\n\tsucceed_retrieve_usage_profile topic was broadcast on " "environment delete." ) @pytest.mark.integration def test_do_delete_environment( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should remove deleted environment record from the records tree.""" test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all( attributes={"revision_id": 1, "mission_id": 3} ) test_environment_table_model.do_select_all( attributes={"revision_id": 1, "mission_phase_id": 3} ) assert test_view_model.tree.contains("3.3.3") assert test_view_model.tree.contains("3.3") assert test_view_model.tree.contains("3") pub.subscribe( self.on_succeed_delete_environment, "succeed_retrieve_usage_profile" ) pub.sendMessage("request_delete_environment", node_id=3) pub.unsubscribe( self.on_succeed_delete_environment, "succeed_retrieve_usage_profile" ) @pytest.mark.integration def test_do_delete_mission_phase( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should remove deleted phase and environment records from records tree.""" test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all( attributes={"revision_id": 1, "mission_id": 2} ) test_environment_table_model.do_select_all( attributes={"revision_id": 1, "mission_phase_id": 2} ) assert test_view_model.tree.contains("2.2.2") assert test_view_model.tree.contains("2.2") assert test_view_model.tree.contains("2") pub.subscribe( self.on_succeed_delete_mission_phase, "succeed_retrieve_usage_profile" ) pub.sendMessage("request_delete_mission_phase", node_id=2) pub.unsubscribe( self.on_succeed_delete_mission_phase, "succeed_retrieve_usage_profile" ) @pytest.mark.integration def test_do_delete_mission( self, test_view_model, test_mission_table_model, test_mission_phase_table_model, test_environment_table_model, ): """Should remove deleted mission, phase, and environment from records tree.""" test_mission_table_model.do_select_all(attributes={"revision_id": 1}) test_mission_phase_table_model.do_select_all( attributes={"revision_id": 1, "mission_id": 1} ) test_environment_table_model.do_select_all( attributes={"revision_id": 1, "mission_phase_id": 1} ) assert test_view_model.tree.contains("1.1.1") assert test_view_model.tree.contains("1.1") assert test_view_model.tree.contains("1") pub.subscribe(self.on_succeed_delete_mission, "succeed_retrieve_usage_profile") pub.sendMessage("request_delete_mission", node_id=1) pub.unsubscribe( self.on_succeed_delete_mission, "succeed_retrieve_usage_profile" )

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null

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null

0

6

55cf6a2582273a280e4356d752cb29b4f15375e6

168

py

Python

swampyer/__init__.py

zabertech/python-swampyer

4181db7d11439cc2a79b5a7d7b2b7c581abf59ec

[ "MIT" ]

1

2022-03-10T00:10:19.000Z

swampyer/__init__.py

zabertech/python-swampyer

4181db7d11439cc2a79b5a7d7b2b7c581abf59ec

[ "MIT" ]

4

2021-05-12T21:56:56.000Z

2021-05-12T22:02:20.000Z

swampyer/__init__.py

zabertech/python-swampyer

4181db7d11439cc2a79b5a7d7b2b7c581abf59ec

[ "MIT" ]

2

2018-06-10T12:50:21.000Z

2019-10-23T17:16:26.000Z

from .common import * from .messages import * from .utils import logger from .exceptions import * from .transport import * from .queues import * from .client import *

18.666667

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1

0

6

55ee606c2fe5385d533c68b78a27c069b69af8d4

4,765

py

Python

maximum_profit_dp.py

ndsvw/Maximum-Profit-Problem

a97359039f448fcb110573d68afc7e87e47821d8

[ "MIT" ]

null

maximum_profit_dp.py

ndsvw/Maximum-Profit-Problem

a97359039f448fcb110573d68afc7e87e47821d8

[ "MIT" ]

null

maximum_profit_dp.py

ndsvw/Maximum-Profit-Problem

a97359039f448fcb110573d68afc7e87e47821d8

[ "MIT" ]

null

def maximum_profit_unlimited_dp(prices): """ A method that calculates the maximum profit that can be made by buying and selling unlimited often Problem description: https://practice.geeksforgeeks.org/problems/maximum-profit/0 time complexity: O(n) space complexity: O(n) Parameters ---------- prices : int[] a list of int values representing the price of something over a time span Returns ------- x : int the maximum profit that can be made by buying and selling unlimited often """ n = len(prices) if n == 0: return 0 s, t = [None] * n, [None] * n s[0], t[0] = -prices[0], 0 for i in range(1, n): t[i] = max(prices[i] + s[i-1], t[i-1]) s[i] = max(-prices[i] + t[i-1], s[i-1]) return t[n-1] def maximum_profit_limited_dp(prices, k): """ A method that calculates the maximum profit that can be made by buying and selling at most k times Problem description: https://practice.geeksforgeeks.org/problems/maximum-profit/0 time complexity: O(n*k) space complexity: O(n*k) Parameters ---------- prices : int[] a list of int values representing the price of something over a time span k : int integer that restricts how often you can buy and sell Returns ------- x : int the maximum profit that can be made by buying and selling unlimited often """ n = len(prices) if n == 0: return 0 s = [[0 for _ in range(n)] for _ in range(k+1)] t = [[0 for _ in range(n)] for _ in range(k+1)] for i in range(k+1): s[i][0], t[i][0] = -prices[0], 0 for j in range(1, k+1): for i in range(1, n): t[j][i] = max(prices[i] + s[j][i-1], t[j][i-1]) s[j][i] = max(-prices[i] + t[j-1][i-1], s[j][i-1]) return t[k][n-1] def maximum_profit_limited_spaceoptimized1_dp(prices, k): """ A method that calculates the maximum profit that can be made by buying and selling at most k times (space-optimized 1/2) Problem description: https://practice.geeksforgeeks.org/problems/maximum-profit/0 time complexity: O(n*k) space complexity: O(n*k) Parameters ---------- prices : int[] a list of int values representing the price of something over a time span k : int integer that restricts how often you can buy and sell Returns ------- x : int the maximum profit that can be made by buying and selling unlimited often """ n = len(prices) if n == 0: return 0 s = [0 for _ in range(n)] t = [[0 for _ in range(n)] for _ in range(k+1)] s[0] = -prices[0] for i in range(k+1): t[i][0] = 0 for j in range(1, k+1): for i in range(1, n): t[j][i] = max(prices[i] + s[i-1], t[j][i-1]) s[i] = max(-prices[i] + t[j-1][i-1], s[i-1]) return t[k][n-1] def maximum_profit_limited_spaceoptimized2_dp(prices, k): """ A method that calculates the maximum profit that can be made by buying and selling at most k times (space-optimized 2/2) Problem description: https://practice.geeksforgeeks.org/problems/maximum-profit/0 time complexity: O(n*k) space complexity: O(n) Parameters ---------- prices : int[] a list of int values representing the price of something over a time span k : int integer that restricts how often you can buy and sell Returns ------- x : int the maximum profit that can be made by buying and selling unlimited often """ n = len(prices) if n == 0: return 0 s = [0 for _ in range(n)] t = [ [0 for _ in range(n)], [0 for _ in range(n)] ] s[0] = -prices[0] t[0][0] = 0 for _ in range(1, k+1): for i in range(1, n): t[1][i] = max(prices[i] + s[i-1], t[1][i-1]) s[i] = max(-prices[i] + t[0][i-1], s[i-1]) t[0] = [e for e in t[1]] return t[1][n-1] def max_profit_dp(prices, k): """ A method that calculates the maximum profit that can be made by buying and selling at most k times (space-optimized) Problem description: https://practice.geeksforgeeks.org/problems/maximum-profit/0 time complexity: O(n*k) space complexity: O(n) Parameters ---------- prices : int[] a list of int values representing the price of something over a time span k : int integer that restricts how often you can buy and sell Returns ------- x : int the maximum profit that can be made by buying and selling unlimited often """ return maximum_profit_limited_spaceoptimized2_dp(prices, k)

30.158228

124

0.581952

766

4,765

3.579634

0.0953

0.094821

0.040117

0.072939

0.951131

0.936543

0.917943

0.884026

0.859956

0

0.02577

0.291501

4,765

157

125

30.350318

0.786434

0.547954

0

0.5

0

1

0.089286

false

0

0.25

0

null

0

1

0

null

0

6

36251b042ddda173f5949810b59cf3ed4f60608b

32

py

Python

datasets/torchvision_datasets/__init__.py

jaehyek/deformable-DETR-2

930f36b9c491e35ce7870f2711c28243152ee058

[ "MIT" ]

12

2021-03-16T15:33:06.000Z

2022-03-03T00:31:52.000Z

datasets/torchvision_datasets/__init__.py

ver0z/Deformable-DETR

7f1f4ffd1d716f681c7cbb2570e2c7a3d4bcf417

[ "Apache-2.0" ]

3

2021-07-15T20:55:13.000Z

2022-01-20T11:56:05.000Z

datasets/torchvision_datasets/__init__.py

ver0z/Deformable-DETR

7f1f4ffd1d716f681c7cbb2570e2c7a3d4bcf417

[ "Apache-2.0" ]

6

2021-03-16T15:26:15.000Z

2021-12-29T01:55:15.000Z

from .coco import CocoDetection

16

31

0.84375

4

32

6.75

1

0

0.125

32

2

31

16

0.964286

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

364c2263fe67f476dab34b9f46e5ace20a13fe64

5,940

py

Python

testsuite/mix-reg/run.py

luyatshimbalanga/OpenShadingLanguage

2120647911af732f0d12d70e2f7f4e1ebe8fadcb

[ "BSD-3-Clause" ]

1,105

2015-01-02T20:47:19.000Z

2021-01-25T13:20:56.000Z

testsuite/mix-reg/run.py

luyatshimbalanga/OpenShadingLanguage

2120647911af732f0d12d70e2f7f4e1ebe8fadcb

[ "BSD-3-Clause" ]

696

2015-01-07T23:42:08.000Z

2021-01-25T03:55:08.000Z

testsuite/mix-reg/run.py

luyatshimbalanga/OpenShadingLanguage

2120647911af732f0d12d70e2f7f4e1ebe8fadcb

[ "BSD-3-Clause" ]

248

2015-01-05T13:41:28.000Z

2021-01-24T23:29:55.000Z

#!/usr/bin/env python # Copyright Contributors to the Open Shading Language project. # SPDX-License-Identifier: BSD-3-Clause # https://github.com/AcademySoftwareFoundation/OpenShadingLanguage # mix float, float, float includes masking command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_float_u_float_u_float.tif test_mix_u_float_u_float_u_float") outputs.append ("mix_u_float_u_float_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_float_u_float_v_float.tif test_mix_u_float_u_float_v_float") outputs.append ("mix_u_float_u_float_v_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_float_u_float_v_float.tif test_mix_v_float_u_float_v_float") outputs.append ("mix_v_float_u_float_v_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_float_v_float_v_float.tif test_mix_u_float_v_float_v_float") outputs.append ("mix_u_float_v_float_v_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_float_v_float_u_float.tif test_mix_u_float_v_float_u_float") outputs.append ("mix_u_float_v_float_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_float_u_float_u_float.tif test_mix_v_float_u_float_u_float") outputs.append ("mix_v_float_u_float_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_float_v_float_u_float.tif test_mix_v_float_v_float_u_float") outputs.append ("mix_v_float_v_float_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_float_v_float_v_float.tif test_mix_v_float_v_float_v_float") outputs.append ("mix_v_float_v_float_v_float.tif") command += testshade("--vary_udxdy --vary_udxdy -t 1 -g 32 32 -od uint8 -o Cout mix_v_dfloat_v_dfloat_v_dfloat.tif test_mix_v_dfloat_v_dfloat_v_dfloat") outputs.append ("mix_v_dfloat_v_dfloat_v_dfloat.tif") command += testshade("--vary_udxdy --vary_udxdy -t 1 -g 32 32 -od uint8 -o Cout mix_v_dfloat_v_dfloat_c_float.tif test_mix_v_dfloat_v_dfloat_c_float") outputs.append ("mix_v_dfloat_v_dfloat_c_float.tif") # mix vector, vector, float includes masking command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_u_vector_u_float.tif test_mix_u_vector_u_vector_u_float") outputs.append ("mix_u_vector_u_vector_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_u_vector_v_float.tif test_mix_u_vector_u_vector_v_float") outputs.append ("mix_u_vector_u_vector_v_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_v_vector_u_float.tif test_mix_u_vector_v_vector_u_float") outputs.append ("mix_u_vector_v_vector_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_v_vector_v_float.tif test_mix_u_vector_v_vector_v_float") outputs.append ("mix_u_vector_v_vector_v_float.tif") command += testshade("--vary_udxdy --vary_udxdy -t 1 -g 32 32 -od uint8 -o Cout mix_v_dvector_v_dvector_c_float.tif test_mix_v_dvector_v_dvector_c_float") outputs.append ("mix_v_dvector_v_dvector_c_float.tif") command += testshade("--vary_udxdy --vary_udxdy -t 1 -g 32 32 -od uint8 -o Cout mix_v_dvector_v_dvector_v_dfloat.tif test_mix_v_dvector_v_dvector_v_dfloat") outputs.append ("mix_v_dvector_v_dvector_v_dfloat.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_u_vector_u_float.tif test_mix_v_vector_u_vector_u_float") outputs.append ("mix_v_vector_u_vector_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_u_vector_v_float.tif test_mix_v_vector_u_vector_v_float") outputs.append ("mix_v_vector_u_vector_v_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_v_vector_u_float.tif test_mix_v_vector_v_vector_u_float") outputs.append ("mix_v_vector_v_vector_u_float.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_v_vector_v_float.tif test_mix_v_vector_v_vector_v_float") outputs.append ("mix_v_vector_v_vector_v_float.tif") # mix vector, vector, vector includes masking command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_u_vector_u_vector.tif test_mix_u_vector_u_vector_u_vector") outputs.append ("mix_u_vector_u_vector_u_vector.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_u_vector_v_vector.tif test_mix_u_vector_u_vector_v_vector") outputs.append ("mix_u_vector_u_vector_v_vector.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_v_vector_u_vector.tif test_mix_u_vector_v_vector_u_vector") outputs.append ("mix_u_vector_v_vector_u_vector.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_u_vector_v_vector_v_vector.tif test_mix_u_vector_v_vector_v_vector") outputs.append ("mix_u_vector_v_vector_v_vector.tif") command += testshade("--vary_udxdy --vary_udxdy -t 1 -g 32 32 -od uint8 -o Cout mix_v_dvector_v_dvector_c_vector.tif test_mix_v_dvector_v_dvector_c_vector") outputs.append ("mix_v_dvector_v_dvector_c_vector.tif") command += testshade("--vary_udxdy --vary_udxdy -t 1 -g 32 32 -od uint8 -o Cout mix_v_dvector_v_dvector_v_dvector.tif test_mix_v_dvector_v_dvector_v_dvector") outputs.append ("mix_v_dvector_v_dvector_v_dvector.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_u_vector_u_vector.tif test_mix_v_vector_u_vector_u_vector") outputs.append ("mix_v_vector_u_vector_u_vector.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_u_vector_v_vector.tif test_mix_v_vector_u_vector_v_vector") outputs.append ("mix_v_vector_u_vector_v_vector.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_v_vector_u_vector.tif test_mix_v_vector_v_vector_u_vector") outputs.append ("mix_v_vector_v_vector_u_vector.tif") command += testshade("-t 1 -g 32 32 -od uint8 -o Cout mix_v_vector_v_vector_v_vector.tif test_mix_v_vector_v_vector_v_vector") outputs.append ("mix_v_vector_v_vector_v_vector.tif") # expect a few LSB failures failthresh = 0.008 failpercent = 3

53.513514

158

0.811785

1,185

5,940

3.578059

0.048945

0.099057

0.110377

0.035377

0.947642

0.940566

0.915802

0.516981

0

0.034515

0.092761

5,940

110

159

54

0.752273

0.056902

0

0.096774

0.743966

0.539067

0

1

0

false

0

null

0

1

0

1

null

0

6

365974881dc4f0379ee51a7e302c4dd5c7e252b1

39

py

Python

basics/hello.py

SimoPrG/python_playground

65e824b219f093c9071a1cffed3a2d43967ed9de

[ "MIT" ]

null

basics/hello.py

SimoPrG/python_playground

65e824b219f093c9071a1cffed3a2d43967ed9de

[ "MIT" ]

null

basics/hello.py

SimoPrG/python_playground

65e824b219f093c9071a1cffed3a2d43967ed9de

[ "MIT" ]

null

print "Hello world, I code anywhere :)"

39

0.717949

6

39

4.666667

1

0

0.153846

39

1

39

0.848485

0

0.775

0

null

0

null

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

3689e871bf99c45ed41e1dcce24661b35294362b

15,295

py

Python

project/editorial/migrations/0028_auto_20171019_2207.py

cojennin/facet

230e65316134b3399a35d40034728e61ba63cb2a

[ "MIT" ]

25

2015-07-13T22:16:36.000Z

2021-11-11T02:45:32.000Z

project/editorial/migrations/0028_auto_20171019_2207.py

cojennin/facet

230e65316134b3399a35d40034728e61ba63cb2a

[ "MIT" ]

74

2015-12-01T18:57:47.000Z

2022-03-11T23:25:47.000Z

project/editorial/migrations/0028_auto_20171019_2207.py

cojennin/facet

230e65316134b3399a35d40034728e61ba63cb2a

[ "MIT" ]

6

2016-01-08T21:12:43.000Z

2019-05-20T16:07:56.000Z

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion import django.contrib.postgres.fields from django.conf import settings class Migration(migrations.Migration): dependencies = [ ('editorial', '0027_auto_20171012_2329'), ] operations = [ migrations.CreateModel( name='ContentLicense', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('name', models.TextField(help_text=b'Name for the license.')), ('terms', models.TextField(help_text=b'Content of the terms.', blank=True)), ('upload', models.FileField(null=True, upload_to=b'license/%Y/%m/%d/', blank=True)), ('organization', models.ForeignKey(help_text=b'Organization that owns this license.', to='editorial.Organization')), ], options={ 'ordering': ['name'], 'verbose_name': 'Content License', 'verbose_name_plural': 'Content Licenses', }, ), migrations.CreateModel( name='Facet', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('original', models.BooleanField(default=True, help_text=b'Was this facet originally created by a user from this organization?')), ('creation_date', models.DateTimeField(help_text=b'Day facet was created.', auto_now_add=True)), ('name', models.TextField(help_text=b'Internal name for facet.')), ('headline', models.TextField(help_text=b'Headline of the facet')), ('description', models.TextField(help_text=b'Description of the facet.', blank=True)), ('content', models.TextField(help_text=b'Content of the facet.', blank=True)), ('status', models.CharField(help_text=b'Facet status choice.', max_length=25, choices=[(b'Draft', b'Draft'), (b'Pitch', b'Pitch'), (b'In Progress', b'In Progress'), (b'Edit', b'Edit'), (b'Revision', b'Revision'), (b'Needs Review', b'Needs Review'), (b'Ready', b'Ready')])), ('due_edit', models.DateTimeField(help_text=b'Due for edit.', null=True, blank=True)), ('run_date', models.DateTimeField(help_text=b'Planned run date.', null=True, blank=True)), ('keywords', django.contrib.postgres.fields.ArrayField(default=list, help_text=b'List of keywords for search.', size=None, base_field=models.CharField(max_length=100), blank=True)), ('update_notes', models.TextField(help_text=b'Text commenting regarding any updates or corrections made to the facet.', blank=True)), ('excerpt', models.TextField(help_text=b'Excerpt from the facet.', blank=True)), ('dateline', models.CharField(help_text=b'Where and when the facet was created.', max_length=150, blank=True)), ('share_note', models.TextField(help_text=b'Information for organizations making a copy of the facet.', blank=True)), ('topic_code', models.CharField(help_text=b'Unique code as needed to designate topic or coverage.', max_length=75, blank=True)), ('internal_code', models.CharField(help_text=b'Unique code as needed for ingest sytems or internal use. Use as needed.', max_length=75, blank=True)), ('length', models.CharField(help_text=b'Length of facet for audio or video.', max_length=75, blank=True)), ('wordcount', models.CharField(help_text=b'Wordcount for text-based facets.', max_length=75, blank=True)), ('related_links', models.TextField(help_text=b'Relevant links that can be included with the facet.', blank=True)), ('github_link', models.URLField(help_text=b'Link to code for any custom feature.', max_length=300, blank=True)), ('source', models.TextField(help_text=b'List of sources in the facet.', blank=True)), ('edit_notes', models.TextField(help_text=b'Information regarding allowable extent of editing and suggestions for specific kinds of edits.', blank=True)), ('pronunciations', models.TextField(help_text=b'Information about pronouncing names or potentially difficult words.', blank=True)), ('sponsors', models.TextField(help_text=b'Sponsors or underwriters if need to indicate any.', blank=True)), ('pull_quotes', models.TextField(help_text=b'List of quotes and attributions to be used as pull quotes.', blank=True)), ('embeds', models.TextField(help_text=b'The necessary information to embed something like a Tweet, FB post, map or video.', blank=True)), ('pushed_to_wp', models.BooleanField(default=False, help_text=b'Whether the facet has been pushed to the organization WordPress site.')), ('sidebar_content', models.TextField(help_text=b'Content separate from body text meant for sidebar or inset presentation.', blank=True)), ('series_title', models.TextField(help_text=b'Title of the video series.', blank=True)), ('episode_number', models.CharField(help_text=b'If the video is part of a series, the episode number.', max_length=75, blank=True)), ('usage_rights', models.TextField(help_text=b'Information regarding the usage of the video if shared.', blank=True)), ('tape_datetime', models.DateTimeField(help_text=b'Tape date.', null=True, blank=True)), ('locations', models.TextField(help_text=b'Shoot locations.', blank=True)), ('custom_one', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_two', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_three', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_four', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_five', models.TextField(help_text=b'User-defined field.', blank=True)), ('audio_assets', models.ManyToManyField(to='editorial.AudioAsset', blank=True)), ('content_license', models.ForeignKey(related_name='facetlicense', blank=True, to='editorial.ContentLicense')), ('credit', models.ManyToManyField(help_text=b'The full user name(s) to be listed as the credit for the facet.', related_name='facetcredit', to=settings.AUTH_USER_MODEL, blank=True)), ('document_assets', models.ManyToManyField(to='editorial.DocumentAsset', blank=True)), ('editor', models.ManyToManyField(help_text=b'The full user name(s) to be listed as the editor(s) for the facet.', related_name='faceteditor', to=settings.AUTH_USER_MODEL, blank=True)), ('image_assets', models.ManyToManyField(to='editorial.ImageAsset', blank=True)), ('organization', models.ForeignKey(help_text=b'Organization that owns this facet.', to='editorial.Organization')), ('owner', models.ForeignKey(related_name='facetowner', to=settings.AUTH_USER_MODEL)), ('producer', models.ForeignKey(related_name='facetproducer', blank=True, to=settings.AUTH_USER_MODEL)), ('story', models.ForeignKey(related_name='facetstory', to='editorial.Story')), ], options={ 'verbose_name': 'Facet', 'verbose_name_plural': 'Facets', }, ), migrations.CreateModel( name='FacetContributor', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('user_role', models.CharField(help_text=b'What did the user do?', max_length=255)), ('facet', models.ForeignKey(to='editorial.Facet')), ('user', models.ForeignKey(to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='HistoricalFacet', fields=[ ('id', models.IntegerField(verbose_name='ID', db_index=True, auto_created=True, blank=True)), ('original', models.BooleanField(default=True, help_text=b'Was this facet originally created by a user from this organization?')), ('creation_date', models.DateTimeField(help_text=b'Day facet was created.', editable=False, blank=True)), ('name', models.TextField(help_text=b'Internal name for facet.')), ('headline', models.TextField(help_text=b'Headline of the facet')), ('description', models.TextField(help_text=b'Description of the facet.', blank=True)), ('content', models.TextField(help_text=b'Content of the facet.', blank=True)), ('status', models.CharField(help_text=b'Facet status choice.', max_length=25, choices=[(b'Draft', b'Draft'), (b'Pitch', b'Pitch'), (b'In Progress', b'In Progress'), (b'Edit', b'Edit'), (b'Revision', b'Revision'), (b'Needs Review', b'Needs Review'), (b'Ready', b'Ready')])), ('due_edit', models.DateTimeField(help_text=b'Due for edit.', null=True, blank=True)), ('run_date', models.DateTimeField(help_text=b'Planned run date.', null=True, blank=True)), ('keywords', django.contrib.postgres.fields.ArrayField(default=list, help_text=b'List of keywords for search.', size=None, base_field=models.CharField(max_length=100), blank=True)), ('update_notes', models.TextField(help_text=b'Text commenting regarding any updates or corrections made to the facet.', blank=True)), ('excerpt', models.TextField(help_text=b'Excerpt from the facet.', blank=True)), ('dateline', models.CharField(help_text=b'Where and when the facet was created.', max_length=150, blank=True)), ('share_note', models.TextField(help_text=b'Information for organizations making a copy of the facet.', blank=True)), ('topic_code', models.CharField(help_text=b'Unique code as needed to designate topic or coverage.', max_length=75, blank=True)), ('internal_code', models.CharField(help_text=b'Unique code as needed for ingest sytems or internal use. Use as needed.', max_length=75, blank=True)), ('length', models.CharField(help_text=b'Length of facet for audio or video.', max_length=75, blank=True)), ('wordcount', models.CharField(help_text=b'Wordcount for text-based facets.', max_length=75, blank=True)), ('related_links', models.TextField(help_text=b'Relevant links that can be included with the facet.', blank=True)), ('github_link', models.URLField(help_text=b'Link to code for any custom feature.', max_length=300, blank=True)), ('source', models.TextField(help_text=b'List of sources in the facet.', blank=True)), ('edit_notes', models.TextField(help_text=b'Information regarding allowable extent of editing and suggestions for specific kinds of edits.', blank=True)), ('pronunciations', models.TextField(help_text=b'Information about pronouncing names or potentially difficult words.', blank=True)), ('sponsors', models.TextField(help_text=b'Sponsors or underwriters if need to indicate any.', blank=True)), ('pull_quotes', models.TextField(help_text=b'List of quotes and attributions to be used as pull quotes.', blank=True)), ('embeds', models.TextField(help_text=b'The necessary information to embed something like a Tweet, FB post, map or video.', blank=True)), ('pushed_to_wp', models.BooleanField(default=False, help_text=b'Whether the facet has been pushed to the organization WordPress site.')), ('sidebar_content', models.TextField(help_text=b'Content separate from body text meant for sidebar or inset presentation.', blank=True)), ('series_title', models.TextField(help_text=b'Title of the video series.', blank=True)), ('episode_number', models.CharField(help_text=b'If the video is part of a series, the episode number.', max_length=75, blank=True)), ('usage_rights', models.TextField(help_text=b'Information regarding the usage of the video if shared.', blank=True)), ('tape_datetime', models.DateTimeField(help_text=b'Tape date.', null=True, blank=True)), ('locations', models.TextField(help_text=b'Shoot locations.', blank=True)), ('custom_one', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_two', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_three', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_four', models.TextField(help_text=b'User-defined field.', blank=True)), ('custom_five', models.TextField(help_text=b'User-defined field.', blank=True)), ('history_id', models.AutoField(serialize=False, primary_key=True)), ('history_date', models.DateTimeField()), ('history_type', models.CharField(max_length=1, choices=[('+', 'Created'), ('~', 'Changed'), ('-', 'Deleted')])), ('content_license', models.ForeignKey(related_name='+', on_delete=django.db.models.deletion.DO_NOTHING, db_constraint=False, blank=True, to='editorial.ContentLicense', null=True)), ('history_user', models.ForeignKey(related_name='+', on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, null=True)), ('organization', models.ForeignKey(related_name='+', on_delete=django.db.models.deletion.DO_NOTHING, db_constraint=False, blank=True, to='editorial.Organization', null=True)), ('owner', models.ForeignKey(related_name='+', on_delete=django.db.models.deletion.DO_NOTHING, db_constraint=False, blank=True, to=settings.AUTH_USER_MODEL, null=True)), ('producer', models.ForeignKey(related_name='+', on_delete=django.db.models.deletion.DO_NOTHING, db_constraint=False, blank=True, to=settings.AUTH_USER_MODEL, null=True)), ('story', models.ForeignKey(related_name='+', on_delete=django.db.models.deletion.DO_NOTHING, db_constraint=False, blank=True, to='editorial.Story', null=True)), ], options={ 'ordering': ('-history_date', '-history_id'), 'get_latest_by': 'history_date', 'verbose_name': 'historical Facet', }, ), migrations.AddField( model_name='facet', name='team', field=models.ManyToManyField(help_text=b'Users that contributed to a facet. Used to associate multiple users to a facet.', to=settings.AUTH_USER_MODEL, through='editorial.FacetContributor', blank=True), ), migrations.AddField( model_name='facet', name='video_assets', field=models.ManyToManyField(to='editorial.VideoAsset', blank=True), ), ]

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1,899

15,295

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0.148499

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0.077986

0.113885

0.84413

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0.785022

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0.765319

0

0.005216

0.21033

15,295

167

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91.586826

0.7974

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0.63354

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0.342326

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false

0

0.031056

0

0.049689

0

null

0

1

0

null

0

6

3696ca0009362c14befa65dca0c2c1355d248a07

142

py

Python

src/lambdaplatform/tasks/lambda_function.py

schlarpc/lambdaplatform

0f58174bf156cdfd03302b6beef998c24b5d0654

[ "MIT" ]

4

2021-07-14T23:09:59.000Z

2021-08-07T02:33:34.000Z

src/lambdaplatform/tasks/lambda_function.py

schlarpc/lambdaplatform

0f58174bf156cdfd03302b6beef998c24b5d0654

[ "MIT" ]

null

src/lambdaplatform/tasks/lambda_function.py

schlarpc/lambdaplatform

0f58174bf156cdfd03302b6beef998c24b5d0654

[ "MIT" ]

null

import urllib.request def handler(event): return urllib.request.urlopen("https://checkip.amazonaws.com").read().decode("utf-8").strip()

23.666667

97

0.725352

19

142

5.421053

0.894737

0.252427

0

0.007692

0.084507

142

5

98

28.4

0.784615

0

0.239437

0

1

0.333333

false

0

0.333333

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0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

36c69227cde80ff3de0a37328a70a7b7e1cea257

202

py

Python

functions/__init__.py

Jerrypiglet/Deformable-Convolution-V2-PyTorch

b7598e95507d1848081f1bb315c67059555e14af

[ "MIT" ]

3

2021-05-15T03:49:39.000Z

2022-01-24T05:05:04.000Z

functions/__init__.py

Jerrypiglet/Deformable-im2col-unfold-Deformable-Convolution-V2-PyTorch

b7598e95507d1848081f1bb315c67059555e14af

[ "MIT" ]

null

functions/__init__.py

Jerrypiglet/Deformable-im2col-unfold-Deformable-Convolution-V2-PyTorch

b7598e95507d1848081f1bb315c67059555e14af

[ "MIT" ]

null

from .deform_conv_func import DeformConvFunction, DeformIm2colFunction from .modulated_deform_conv_func import ModulatedDeformConvFunction from .deform_psroi_pooling_func import DeformRoIPoolingFunction

67.333333

70

0.920792

21

202

8.47619

0.571429

0.168539

0.157303

0.224719

0

0.005263

0.059406

202

3

71

67.333333

0.931579

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true

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null

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0

1

0

null

0

1

0

1

0

1

0

6

36e0060030db375dbcc5b414a67e93dee5f6fab4

252

py

Python

rpython/jit/backend/ppc/test/test_del.py

nanjekyejoannah/pypy

e80079fe13c29eda7b2a6b4cd4557051f975a2d9

[ "Apache-2.0", "OpenSSL" ]

381

2018-08-18T03:37:22.000Z

2022-02-06T23:57:36.000Z

rpython/jit/backend/ppc/test/test_del.py

nanjekyejoannah/pypy

e80079fe13c29eda7b2a6b4cd4557051f975a2d9

[ "Apache-2.0", "OpenSSL" ]

16

2018-09-22T18:12:47.000Z

2022-02-22T20:03:59.000Z

rpython/jit/backend/ppc/test/test_del.py

nanjekyejoannah/pypy

e80079fe13c29eda7b2a6b4cd4557051f975a2d9

[ "Apache-2.0", "OpenSSL" ]

55

2015-08-16T02:41:30.000Z

2022-03-20T20:33:35.000Z

from rpython.jit.backend.ppc.test.support import JitPPCMixin from rpython.jit.metainterp.test.test_del import DelTests class TestDel(JitPPCMixin, DelTests): # for the individual tests see # ====> ../../../metainterp/test/test_del.py pass

28

60

0.734127

33

252

5.545455

0.636364

0.120219

0.153005

0.229508

0

0.138889

252

8

61

31.5

0.843318

0.281746

0

1

0

true

0.25

0.5

0

0.75

0

null

0

1

0

1

0

null

0

1

0

1

0

6

36edab6be5ffa86b73e8b328ce15ed011d2543c2

71

py

Python

jacdac/uv_index/__init__.py

microsoft/jacdac-python

712ad5559e29065f5eccb5dbfe029c039132df5a

[ "MIT" ]

1

2022-02-15T21:30:36.000Z

jacdac/uv_index/__init__.py

microsoft/jacdac-python

712ad5559e29065f5eccb5dbfe029c039132df5a

[ "MIT" ]

null

jacdac/uv_index/__init__.py

microsoft/jacdac-python

712ad5559e29065f5eccb5dbfe029c039132df5a

[ "MIT" ]

1

2022-02-08T19:32:45.000Z

# Autogenerated file. from .client import UvIndexClient # type: ignore

23.666667

48

0.788732

8

71

7

1

0

0.140845

71

2

49

35.5

0.918033

0.450704

0

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

36ef45a718fbec327c4ce18df55d55df45f4a570

44,142

py

Python

sixparser.py

charlesap/ibnf

0efc87c7f250594d77fe400ba2f90f812ebe5aa1

[ "MIT", "Unlicense" ]

1

2019-07-29T11:12:53.000Z

sixparser.py

charlesap/ibnf

0efc87c7f250594d77fe400ba2f90f812ebe5aa1

[ "MIT", "Unlicense" ]

null

sixparser.py

charlesap/ibnf

0efc87c7f250594d77fe400ba2f90f812ebe5aa1

[ "MIT", "Unlicense" ]

null

import sys from binascii import * fi = file(sys.argv[1]).read() semantics = file(sys.argv[2]).read() fo = open(sys.argv[3], "w+") h={}; registers={}; context={}; mseq=0; dseq=1; T=True; F=False def n2z( a ): return ( '0' if a=='' else a ) def be2le( a ): return a[6:8]+a[4:6]+a[2:4]+a[0:2] def mark( p, s, t ): ( v, m, ss, l, c, a ) = t if t[1]: x = p +"-" + str(s); h[x]=(v,m,l,a); return t else: if not t[0]: x = p +"-" + str(s); h[x]=(v,m,l,a); return t return t def been(p, s): if h.has_key( p +"-" + str(s) ): return h[p +"-" + str(s)][1] else: return False def was(c,p,s): (v,m,l,a) = h[p+"-"+str(s)]; return (v,m,s,l,c,a) def cm( ch, s, c ): if s < len(fi): if fi[s] == ch: return ( T, T, s, 1, c, ( "cm", fi[s] ) ) return ( False, True, s, 0, c, ( "cm", "") ) def andmemo( m ): r = True for i in m: if not m[i]: r = False return r outdata = "" def output( s ): global outdata outdata = outdata + str(s) def syntax_p( s, c): if been("syntax",s): return was( c, "syntax",s) else: mark("syntax",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ srules_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ end_p ( (ts+tl), tc) if ok: rv=syntax_s(a,andmemo(mem),s,ts+tl,tc,"syntax") return mark("syntax",s,rv) return mark("syntax",s,(F,T,s,0,c,("",""))) def srules_p( s, c): if been("srules",s): return was( c, "srules",s) else: mark("srules",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ srule_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ srules_p ( (ts+tl), tc) if ok: rv=srules_s(a,andmemo(mem),s,ts+tl,tc,"srules") return mark("srules",s,rv) return mark("srules",s,(F,T,s,0,c,("",""))) def srule_p( s, c): if been("srule",s): return was( c, "srule",s) else: mark("srule",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=blankline_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=base_p(s,c) if not met: return mark("srule",s,(F,T,s,0,c,("",""))) else: return mark("srule",s,(met,mem,s,tl,tc,ta)) def blankline_p( s, c): if been("blankline",s): return was( c, "blankline",s) else: mark("blankline",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(10) ,(ts+tl), tc) if ok: rv=blankline_s(a,andmemo(mem),s,ts+tl,tc,"blankline") return mark("blankline",s,rv) return mark("blankline",s,(F,T,s,0,c,("",""))) def base_p( s, c): if been("base",s): return was( c, "base",s) else: mark("base",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ name_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ setup_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ body_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ recr_p ( (ts+tl), tc) if ok: rv=base_s(a,andmemo(mem),s,ts+tl,tc,"base") return mark("base",s,rv) return mark("base",s,(F,T,s,0,c,("",""))) def body_p( s, c): if been("body",s): return was( c, "body",s) else: mark("body",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=qlineset_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=cline_p(s,c) if not met: return mark("body",s,(F,T,s,0,c,("",""))) else: return mark("body",s,(met,mem,s,tl,tc,ta)) def setup_p( s, c): if been("setup",s): return was( c, "setup",s) else: mark("setup",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(':',(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ code_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(10) ,(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ setup_p ( (ts+tl), tc) if ok: rv=setup_s(a,andmemo(mem),s,ts+tl,tc,"setup") return mark("setup",s,rv) return mark("setup",s,(F,T,s,0,c,("",""))) def recr_p( s, c): if been("recr",s): return was( c, "recr",s) else: mark("recr",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('.',(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ name_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ rsetup_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ body_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ recr_p ( (ts+tl), tc) if ok: rv=recr_s(a,andmemo(mem),s,ts+tl,tc,"recr") return mark("recr",s,rv) return mark("recr",s,(F,T,s,0,c,("",""))) def rsetup_p( s, c): if been("rsetup",s): return was( c, "rsetup",s) else: mark("rsetup",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(':',(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ rcode_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(10) ,(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ rsetup_p ( (ts+tl), tc) if ok: rv=rsetup_s(a,andmemo(mem),s,ts+tl,tc,"rsetup") return mark("rsetup",s,rv) return mark("rsetup",s,(F,T,s,0,c,("",""))) def rcode_p( s, c): if been("rcode",s): return was( c, "rcode",s) else: mark("rcode",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ ritm_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ rcode_p ( (ts+tl), tc) if ok: rv=rcode_s(a,andmemo(mem),s,ts+tl,tc,"rcode") return mark("rcode",s,rv) return mark("rcode",s,(F,T,s,0,c,("",""))) def ritm_p( s, c): if been("ritm",s): return was( c, "ritm",s) else: mark("ritm",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=string_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=rcr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=lwr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=dpathw_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=dhas_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=pnt_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('>',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('<',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('{',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('}',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(':',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('%',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('(',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(',',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(')',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('_',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('[',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(']',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(';',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('+',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('-',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('*',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('/',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('=',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('!',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(' ',s,c) if not met: return mark("ritm",s,(F,T,s,0,c,("",""))) else: return mark("ritm",s,(met,mem,s,tl,tc,ta)) def cline_p( s, c): if been("cline",s): return was( c, "cline",s) else: mark("cline",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('^',(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ code_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(10) ,(ts+tl), tc) if ok: rv=cline_s(a,andmemo(mem),s,ts+tl,tc,"cline") return mark("cline",s,rv) return mark("cline",s,(F,T,s,0,c,("",""))) def qlineset_p( s, c): if been("qlineset",s): return was( c, "qlineset",s) else: mark("qlineset",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ qlines_p ( (ts+tl), tc) if ok: rv=qlineset_s(a,andmemo(mem),s,ts+tl,tc,"qlineset") return mark("qlineset",s,rv) return mark("qlineset",s,(F,T,s,0,c,("",""))) def qlines_p( s, c): if been("qlines",s): return was( c, "qlines",s) else: mark("qlines",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ qlsep_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ qline_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ qlines_p ( (ts+tl), tc) if ok: rv=qlines_s(a,andmemo(mem),s,ts+tl,tc,"qlines") return mark("qlines",s,rv) return mark("qlines",s,(F,T,s,0,c,("",""))) def qlsep_p( s, c): if been("qlsep",s): return was( c, "qlsep",s) else: mark("qlsep",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('|',(ts+tl), tc) if ok: rv=qlsep_s(a,andmemo(mem),s,ts+tl,tc,"qlsep") return mark("qlsep",s,rv) return mark("qlsep",s,(F,T,s,0,c,("",""))) def qline_p( s, c): if been("qline",s): return was( c, "qline",s) else: mark("qline",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ qchs_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(10) ,(ts+tl), tc) if ok: rv=qline_s(a,andmemo(mem),s,ts+tl,tc,"qline") return mark("qline",s,rv) return mark("qline",s,(F,T,s,0,c,("",""))) def qchs_p( s, c): if been("qchs",s): return was( c, "qchs",s) else: mark("qchs",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ qch_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ qchs_p ( (ts+tl), tc) if ok: rv=qchs_s(a,andmemo(mem),s,ts+tl,tc,"qchs") return mark("qchs",s,rv) return mark("qchs",s,(F,T,s,0,c,("",""))) def qch_p( s, c): if been("qch",s): return was( c, "qch",s) else: mark("qch",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=aln_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=qq_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=qt_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=qs_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=qsmb_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(' ',s,c) if not met: (met,mem,ts,tl,tc,ta)=qcode_p(s,c) if not met: return mark("qch",s,(F,T,s,0,c,("",""))) else: return mark("qch",s,(met,mem,s,tl,tc,ta)) def qq_p( s, c): if been("qq",s): return was( c, "qq",s) else: mark("qq",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(34) ,(ts+tl), tc) if ok: rv=qq_s(a,andmemo(mem),s,ts+tl,tc,"qq") return mark("qq",s,rv) return mark("qq",s,(F,T,s,0,c,("",""))) def qt_p( s, c): if been("qt",s): return was( c, "qt",s) else: mark("qt",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(39) ,(ts+tl), tc) if ok: rv=qt_s(a,andmemo(mem),s,ts+tl,tc,"qt") return mark("qt",s,rv) return mark("qt",s,(F,T,s,0,c,("",""))) def qs_p( s, c): if been("qs",s): return was( c, "qs",s) else: mark("qs",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(92) ,(ts+tl), tc) if ok: rv=qs_s(a,andmemo(mem),s,ts+tl,tc,"qs") return mark("qs",s,rv) return mark("qs",s,(F,T,s,0,c,("",""))) def qcode_p( s, c): if been("qcode",s): return was( c, "qcode",s) else: mark("qcode",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('`',(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ code_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('`',(ts+tl), tc) if ok: rv=qcode_s(a,andmemo(mem),s,ts+tl,tc,"qcode") return mark("qcode",s,rv) return mark("qcode",s,(F,T,s,0,c,("",""))) def name_p( s, c): if been("name",s): return was( c, "name",s) else: mark("name",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ lwr_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ name_p ( (ts+tl), tc) if ok: rv=name_s(a,andmemo(mem),s,ts+tl,tc,"name") return mark("name",s,rv) return mark("name",s,(F,T,s,0,c,("",""))) def name_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def qsmb_p( s, c): if been("qsmb",s): return was( c, "qsmb",s) else: mark("qsmb",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=cm('-',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('_',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('+',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('=',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('~',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('!',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('@',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('#',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('$',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('%',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('^',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('&',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('!',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('|',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('/',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(':',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(';',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('*',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('(',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(')',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('[',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(']',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('{',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('}',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(',',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('.',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('<',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('>',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('?',s,c) if not met: return mark("qsmb",s,(F,T,s,0,c,("",""))) else: return mark("qsmb",s,(met,mem,s,tl,tc,ta)) def string_p( s, c): if been("string",s): return was( c, "string",s) else: mark("string",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(34) ,(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ strcs_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(34) ,(ts+tl), tc) if ok: rv=string_s(a,andmemo(mem),s,ts+tl,tc,"string") return mark("string",s,rv) return mark("string",s,(F,T,s,0,c,("",""))) def strcs_p( s, c): if been("strcs",s): return was( c, "strcs",s) else: mark("strcs",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ sch_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ strcs_p ( (ts+tl), tc) if ok: rv=strcs_s(a,andmemo(mem),s,ts+tl,tc,"strcs") return mark("strcs",s,rv) return mark("strcs",s,(F,T,s,0,c,("",""))) def code_p( s, c): if been("code",s): return was( c, "code",s) else: mark("code",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ citm_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ code_p ( (ts+tl), tc) if ok: rv=code_s(a,andmemo(mem),s,ts+tl,tc,"code") return mark("code",s,rv) return mark("code",s,(F,T,s,0,c,("",""))) def citm_p( s, c): if been("citm",s): return was( c, "citm",s) else: mark("citm",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=string_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=cnl_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=rcr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=lwr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=dpathw_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=dhas_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=pnt_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('>',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('<',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('{',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('}',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(':',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('%',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('(',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(',',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(')',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('_',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('[',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(']',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(';',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('+',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('-',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('*',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('/',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('=',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('!',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(' ',s,c) if not met: return mark("citm",s,(F,T,s,0,c,("",""))) else: return mark("citm",s,(met,mem,s,tl,tc,ta)) def cnl_p( s, c): if been("cnl",s): return was( c, "cnl",s) else: mark("cnl",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(10) ,(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('^',(ts+tl), tc) if ok: rv=cnl_s(a,andmemo(mem),s,ts+tl,tc,"cnl") return mark("cnl",s,rv) return mark("cnl",s,(F,T,s,0,c,("",""))) def dpathw_p( s, c): if been("dpathw",s): return was( c, "dpathw",s) else: mark("dpathw",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ dpath_p ( (ts+tl), tc) if ok: rv=dpathw_s(a,andmemo(mem),s,ts+tl,tc,"dpathw") return mark("dpathw",s,rv) return mark("dpathw",s,(F,T,s,0,c,("",""))) def dpath_p( s, c): if been("dpath",s): return was( c, "dpath",s) else: mark("dpath",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('.',(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ pnt_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ dpath_p ( (ts+tl), tc) if ok: rv=dpath_s(a,andmemo(mem),s,ts+tl,tc,"dpath") return mark("dpath",s,rv) return mark("dpath",s,(F,T,s,0,c,("",""))) def dhas_p( s, c): if been("dhas",s): return was( c, "dhas",s) else: mark("dhas",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('.',(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('.',(ts+tl), tc) if ok: rv=dhas_s(a,andmemo(mem),s,ts+tl,tc,"dhas") return mark("dhas",s,rv) return mark("dhas",s,(F,T,s,0,c,("",""))) def rcr_p( s, c): if been("rcr",s): return was( c, "rcr",s) else: mark("rcr",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=rca_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=rcb_p(s,c) if not met: return mark("rcr",s,(F,T,s,0,c,("",""))) else: return mark("rcr",s,(met,mem,s,tl,tc,ta)) def rca_p( s, c): if been("rca",s): return was( c, "rca",s) else: mark("rca",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('#',(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ name_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(':',(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ code_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('#',(ts+tl), tc) if ok: rv=rca_s(a,andmemo(mem),s,ts+tl,tc,"rca") return mark("rca",s,rv) return mark("rca",s,(F,T,s,0,c,("",""))) def rcb_p( s, c): if been("rcb",s): return was( c, "rcb",s) else: mark("rcb",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('#',(ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ code_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('#',(ts+tl), tc) if ok: rv=rcb_s(a,andmemo(mem),s,ts+tl,tc,"rcb") return mark("rcb",s,rv) return mark("rcb",s,(F,T,s,0,c,("",""))) def end_p( s, c): if been("end",s): return was( c, "end",s) else: mark("end",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: rv=end_s(a,andmemo(mem),s,ts+tl,tc,"end") return mark("end",s,rv) return mark("end",s,(F,T,s,0,c,("",""))) def dgt_p( s, c): if been("dgt",s): return was( c, "dgt",s) else: mark("dgt",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=cm('0',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('1',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('2',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('3',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('4',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('5',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('6',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('7',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('8',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('9',s,c) if not met: return mark("dgt",s,(F,T,s,0,c,("",""))) else: return mark("dgt",s,(met,mem,s,tl,tc,ta)) def upr_p( s, c): if been("upr",s): return was( c, "upr",s) else: mark("upr",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=cm('A',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('B',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('C',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('D',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('E',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('F',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('G',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('H',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('I',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('J',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('K',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('L',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('M',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('N',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('O',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('P',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('Q',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('R',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('S',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('T',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('U',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('V',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('W',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('X',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('Y',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('Z',s,c) if not met: return mark("upr",s,(F,T,s,0,c,("",""))) else: return mark("upr",s,(met,mem,s,tl,tc,ta)) def lwr_p( s, c): if been("lwr",s): return was( c, "lwr",s) else: mark("lwr",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=cm('a',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('b',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('c',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('d',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('e',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('f',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('g',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('h',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('i',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('j',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('k',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('l',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('m',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('n',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('o',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('p',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('q',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('r',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('s',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('t',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('u',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('v',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('w',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('x',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('y',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('z',s,c) if not met: return mark("lwr",s,(F,T,s,0,c,("",""))) else: return mark("lwr",s,(met,mem,s,tl,tc,ta)) def alp_p( s, c): if been("alp",s): return was( c, "alp",s) else: mark("alp",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=upr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=lwr_p(s,c) if not met: return mark("alp",s,(F,T,s,0,c,("",""))) else: return mark("alp",s,(met,mem,s,tl,tc,ta)) def aln_p( s, c): if been("aln",s): return was( c, "aln",s) else: mark("aln",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=upr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=lwr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=dgt_p(s,c) if not met: return mark("aln",s,(F,T,s,0,c,("",""))) else: return mark("aln",s,(met,mem,s,tl,tc,ta)) def hex_p( s, c): if been("hex",s): return was( c, "hex",s) else: mark("hex",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=dgt_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('A',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('B',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('C',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('D',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('E',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('F',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('a',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('b',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('c',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('d',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('e',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('f',s,c) if not met: return mark("hex",s,(F,T,s,0,c,("",""))) else: return mark("hex",s,(met,mem,s,tl,tc,ta)) def smb_p( s, c): if been("smb",s): return was( c, "smb",s) else: mark("smb",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=cm('-',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('_',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('+',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('=',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('`',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('~',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('!',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('@',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('#',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('$',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('%',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('^',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('&',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('|',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('/',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(':',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(';',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('*',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('(',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(')',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('[',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(']',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('{',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('}',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm(',',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('.',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('<',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('>',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('?',s,c) if not met: return mark("smb",s,(F,T,s,0,c,("",""))) else: return mark("smb",s,(met,mem,s,tl,tc,ta)) def sps_p( s, c): if been("sps",s): return was( c, "sps",s) else: mark("sps",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=bsl_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=btk_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=bqt_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=bnl_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=btb_p(s,c) if not met: return mark("sps",s,(F,T,s,0,c,("",""))) else: return mark("sps",s,(met,mem,s,tl,tc,ta)) def bsl_p( s, c): if been("bsl",s): return was( c, "bsl",s) else: mark("bsl",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(92) ,(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(92) ,(ts+tl), tc) if ok: rv=bsl_s(a,andmemo(mem),s,ts+tl,tc,"bsl") return mark("bsl",s,rv) return mark("bsl",s,(F,T,s,0,c,("",""))) def bsl_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def btk_p( s, c): if been("btk",s): return was( c, "btk",s) else: mark("btk",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(92) ,(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(39) ,(ts+tl), tc) if ok: rv=btk_s(a,andmemo(mem),s,ts+tl,tc,"btk") return mark("btk",s,rv) return mark("btk",s,(F,T,s,0,c,("",""))) def btk_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def bqt_p( s, c): if been("bqt",s): return was( c, "bqt",s) else: mark("bqt",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(92) ,(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(34) ,(ts+tl), tc) if ok: rv=bqt_s(a,andmemo(mem),s,ts+tl,tc,"bqt") return mark("bqt",s,rv) return mark("bqt",s,(F,T,s,0,c,("",""))) def bqt_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def bnl_p( s, c): if been("bnl",s): return was( c, "bnl",s) else: mark("bnl",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(92) ,(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('n',(ts+tl), tc) if ok: rv=bnl_s(a,andmemo(mem),s,ts+tl,tc,"bnl") return mark("bnl",s,rv) return mark("bnl",s,(F,T,s,0,c,("",""))) def bnl_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def btb_p( s, c): if been("btb",s): return was( c, "btb",s) else: mark("btb",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm(chr(92) ,(ts+tl), tc) if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ cm('t',(ts+tl), tc) if ok: rv=btb_s(a,andmemo(mem),s,ts+tl,tc,"btb") return mark("btb",s,rv) return mark("btb",s,(F,T,s,0,c,("",""))) def btb_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def wsc_p( s, c): if been("wsc",s): return was( c, "wsc",s) else: mark("wsc",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=cm(' ',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('\t',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('\n',s,c) if not met: return mark("wsc",s,(F,T,s,0,c,("",""))) else: return mark("wsc",s,(met,mem,s,tl,tc,ta)) def s_p( s, c): if been("s",s): return was( c, "s",s) else: mark("s",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ sp_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ s_p ( (ts+tl), tc) if ok: rv=s_s(a,andmemo(mem),s,ts+tl,tc,"s") return mark("s",s,rv) return mark("s",s,(F,T,s,0,c,("",""))) def s_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def sp_p( s, c): if been("sp",s): return was( c, "sp",s) else: mark("sp",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=cm(' ',s,c) if not met: (met,mem,ts,tl,tc,ta)=cm('\t',s,c) if not met: return mark("sp",s,(F,T,s,0,c,("",""))) else: return mark("sp",s,(met,mem,s,tl,tc,ta)) def sch_p( s, c): if been("sch",s): return was( c, "sch",s) else: mark("sch",s,(F,T,s,0,c,("","")));met = F if not met: (met,mem,ts,tl,tc,ta)=dgt_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=upr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=lwr_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=smb_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=wsc_p(s,c) if not met: (met,mem,ts,tl,tc,ta)=sps_p(s,c) if not met: return mark("sch",s,(F,T,s,0,c,("",""))) else: return mark("sch",s,(met,mem,s,tl,tc,ta)) def chs_p( s, c): if been("chs",s): return was( c, "chs",s) else: mark("chs",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ sch_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ chs_p ( (ts+tl), tc) if ok: rv=chs_s(a,andmemo(mem),s,ts+tl,tc,"chs") return mark("chs",s,rv) return mark("chs",s,(F,T,s,0,c,("",""))) def chs_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def pnt_p( s, c): if been("pnt",s): return was( c, "pnt",s) else: mark("pnt",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ dgt_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ pnt_p ( (ts+tl), tc) if ok: rv=pnt_s(a,andmemo(mem),s,ts+tl,tc,"pnt") return mark("pnt",s,rv) return mark("pnt",s,(F,T,s,0,c,("",""))) def pnt_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def als_p( s, c): if been("als",s): return was( c, "als",s) else: mark("als",s,(F,T,s,0,c,("",""))) ok=True; ts=s; tl=0; a={0: ("","")} mem={0:True}; tc=c; n=0 if ok: n=n+1; ( ok,mem[n],ts,tl,tc,a[n])=\ aln_p ( (ts+tl), tc) if ok: n=n+1; ( nok,mem[n],ts,tl,tc,a[n])=\ als_p ( (ts+tl), tc) if ok: rv=als_s(a,andmemo(mem),s,ts+tl,tc,"als") return mark("als",s,rv) return mark("als",s,(F,T,s,0,c,("",""))) def als_s(a,m,s,e,c,n): return(T,T,s,e-s,c,(n,fi[s:e])) def syntax_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "syntax", a[1][1] + a[2][1] )) def srules_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "srules", a[1][1] + a[2][1] )) def blankline_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "blankline", "" )) def base_s(a,m,s,e,c,n): rbody=" o = \"\"\n rx="+a[2][1]+"_r\n if a != \"\":\n"+a[5][1]+" return (o)\n" return (T,T,s,e-s,c,( "base", "\n" + \ "def " + a[2][1] + "_s(a,m,s,e,c,n):\n" + \ "" + (" rx="+a[2][1]+"_r " if a[5][1] != "" else "") + "\n" + \ "" + (" "+a[3][1] if a[3][1] != "" else "") + "\n" + \ " return (T,T,s,e-s,c,( \"" + a[2][1] + "\", " + a[4][1] + " ))\n" + \ "" + ("def "+a[2][1]+"_r(a,m,s,e,c,n):\n"+rbody if a[5][1] != "" else "") + "" )) def setup_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "setup", ( ( a[4][1] + "\n " + a[7][1]) if a[7][1] != "" else a[4][1] ) )) def rsetup_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "rsetup", ( ( " " + a[4][1] + "\n " + a[7][1]+"\n") if a[7][1] != "" else "\n "+a[4][1]+"\n" ) )) def recr_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "recr", " if a[0] ==\"" + a[3][1] + "\":\n" + a[4][1] + " o=o+" + a[5][1] +"\n"+ a[6][1] )) def cline_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "cline", a[4][1] )) def qlineset_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qlineset", "\"" + a[1][1] + "\"" )) def qlines_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qlines", a[2][1] + a[3][1] + a[4][1] )) def qlsep_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qlsep", "\\n\" + \\\n\"" )) def qline_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qline", a[1][1] )) def qchs_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qchs", a[1][1] + a[2][1] )) def qq_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qq", "\\\"" )) def qt_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qt", "\\\'" )) def qs_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qs", "\\\\" )) def qcode_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "qcode", "\" + " + a[3][1] + " + \"" )) def string_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "string", "\"" + a[2][1] + "\"" )) def strcs_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "strcs", a[1][1] + a[2][1] )) def code_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "code", a[1][1] + a[2][1] )) def rcode_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "rcode", a[1][1] + a[2][1] )) def cnl_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "cnl", "\\\n" )) def dpathw_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "dpathw", "a" + a[1][1] )) def dpath_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "dpath", "[" + a[2][1] + "]" + a[3][1] )) def dhas_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "dhas", "a" )) def rca_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "rca", a[3][1] +"_s(" + a[7][1] + ",m,s,e,c,n)[5][1]" )) def rcb_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "rcb", "rx(" + a[3][1] + ",m,s,e,c,n)" )) def end_s(a,m,s,e,c,n): return (T,T,s,e-s,c,( "end", "\n" + \ "prologue=\"\"\"import sys\n" + \ "from binascii import *\n" + \ "fi = file(sys.argv[1]).read()\n" + \ "semantics = file(sys.argv[2]).read()\n" + \ "fo = open(sys.argv[3], \"w+\")\n" + \ "\n" + \ "h={}; registers={}; context={}; mseq=0; dseq=1; T=True; F=False\n" + \ "\n" + \ "def n2z( a ):\n" + \ " return ( \'0\' if a==\'\' else a )\n" + \ "\n" + \ "def be2le( a ):\n" + \ " return a[6:8]+a[4:6]+a[2:4]+a[0:2]\n" + \ "\n" + \ "def mark( p, s, t ):\n" + \ " ( v, m, ss, l, c, a ) = t\n" + \ " if t[1]: x = p +\"-\" + str(s); h[x]=(v,m,l,a); return t\n" + \ " else:\n" + \ " if not t[0]: x = p +\"-\" + str(s); h[x]=(v,m,l,a); return t\n" + \ " return t\n" + \ "\n" + \ "def been(p, s):\n" + \ " if h.has_key( p +\"-\" + str(s) ): return h[p +\"-\" + str(s)][1]\n" + \ " else: return False\n" + \ "\n" + \ "def was(c,p,s): (v,m,l,a) = h[p+\"-\"+str(s)]; return (v,m,s,l,c,a) \n" + \ "\n" + \ "def cm( ch, s, c ):\n" + \ " if s < len(fi):\n" + \ " if fi[s] == ch: return ( T, T, s, 1, c, ( \"cm\", fi[s] ) )\n" + \ " return ( False, True, s, 0, c, ( \"cm\", \"\") )\n" + \ "\n" + \ "def andmemo( m ):\n" + \ " r = True\n" + \ " for i in m:\n" + \ " if not m[i]: r = False\n" + \ " return r\n" + \ "\n" + \ "outdata = \"\"\n" + \ "\n" + \ "def output( s ):\n" + \ " global outdata\n" + \ " outdata = outdata + str(s)\n" + \ "\n" + \ "\"\"\"; epilogue=\"\"\"\n" + \ "\n" + \ "(v,m,s,l,c,a) = syntax_p( 0, ({},\'<1>\',\'<0>\') )\n" + \ "if v: \n" + \ " print \"Parsed \"+a[0]+\" OK\"\n" + \ "else: print \"Failed to Parse\"\n" + \ "print >> fo, a[1] \n" + \ "fo.close()\n" + \ "\"\"\"" )) def build (v,m,s,l,c,a): return 'success' T=True; F=False prologue = """import sys from binascii import * fi = file(sys.argv[1]).read() semantics = file(sys.argv[2]).read() fo = open(sys.argv[3], "w+") h={}; registers={}; context={}; mseq=0; dseq=1; T=True; F=False def n2z( a ): return ( '0' if a=='' else a ) def be2le( a ): return a[6:8]+a[4:6]+a[2:4]+a[0:2] def mark( p, s, t ): ( v, m, ss, l, c, a ) = t if t[1]: x = p +"-" + str(s); h[x]=(v,m,l,a); return t else: if not t[0]: x = p +"-" + str(s); h[x]=(v,m,l,a); return t return t def been(p, s): if h.has_key( p +"-" + str(s) ): return h[p +"-" + str(s)][1] else: return False def was(c,p,s): (v,m,l,a) = h[p+"-"+str(s)]; return (v,m,s,l,c,a) def cm( ch, s, c ): if s < len(fi): if fi[s] == ch: return ( T, T, s, 1, c, ( "cm", fi[s] ) ) return ( False, True, s, 0, c, ( "cm", "") ) def andmemo( m ): r = True for i in m: if not m[i]: r = False return r outdata = "" def output( s ): global outdata outdata = outdata + str(s) """ epilogue = """ q3 = chr(34)+chr(34)+chr(34) predefs = "prologue="+q3+prologue+q3+"; epilogue="+q3+epilogue+q3 (v,m,s,l,c,a) = syntax_p( 0, ({},'<1>','<0>') ) if v: print "Parsed "+a[0]+" OK" else: print "Failed to Parse" print >> fo, a[1] fo.close() """ outdata = "" def output( s ): global outdata outdata = outdata + str(s) q3 = chr(34)+chr(34)+chr(34) predefs = "prologue="+q3+prologue+q3+"; epilogue="+q3+epilogue+q3 (v,m,s,l,c,a) = syntax_p( 0, ({},'<1>','<0>') ) if v: print "Parsed "+a[0]+" OK" else: print "Failed to Parse" print >> fo, a[1] fo.close()

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0.767524

0.657233

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null

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1

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6

36efa0337873f88d446db314cebd163e03506cec

4,447

py

Python

tests/compiler_env_state_test.py

kokizzu/CompilerGym

4dd454f7a386c26308ab60be12315c28f3fa1cbc

[ "MIT" ]

null

tests/compiler_env_state_test.py

kokizzu/CompilerGym

4dd454f7a386c26308ab60be12315c28f3fa1cbc

[ "MIT" ]

null

tests/compiler_env_state_test.py

kokizzu/CompilerGym

4dd454f7a386c26308ab60be12315c28f3fa1cbc

[ "MIT" ]

null

# Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """Unit tests for //compiler_gym:compiler_env_state.""" import pytest from compiler_gym import CompilerEnvState from tests.test_main import main def test_state_to_csv_from_csv(): original_state = CompilerEnvState( benchmark="foo", walltime=100, reward=1.5, commandline="-a -b -c" ) state_from_csv = CompilerEnvState.from_csv(original_state.to_csv()) assert state_from_csv.benchmark == "foo" assert state_from_csv.walltime == 100 assert state_from_csv.reward == 1.5 assert state_from_csv.commandline == "-a -b -c" def test_state_to_csv_from_csv_no_reward(): original_state = CompilerEnvState( benchmark="foo", walltime=100, commandline="-a -b -c" ) state_from_csv = CompilerEnvState.from_csv(original_state.to_csv()) assert state_from_csv.benchmark == "foo" assert state_from_csv.walltime == 100 assert state_from_csv.reward is None assert state_from_csv.commandline == "-a -b -c" def test_state_from_csv_empty(): with pytest.raises(ValueError) as ctx: CompilerEnvState.from_csv("") assert str(ctx.value) == "Failed to parse input: ``" def test_state_from_csv_invalid_format(): with pytest.raises(ValueError) as ctx: CompilerEnvState.from_csv("abcdef") assert str(ctx.value).startswith("Failed to parse input: `abcdef`: ") def test_state_to_json_from_json(): original_state = CompilerEnvState( benchmark="foo", walltime=100, reward=1.5, commandline="-a -b -c" ) state_from_json = CompilerEnvState.from_json(original_state.json()) assert state_from_json.benchmark == "foo" assert state_from_json.walltime == 100 assert state_from_json.reward == 1.5 assert state_from_json.commandline == "-a -b -c" def test_state_to_json_from_json_no_reward(): original_state = CompilerEnvState( benchmark="foo", walltime=100, commandline="-a -b -c" ) state_from_json = CompilerEnvState.from_json(original_state.json()) assert state_from_json.benchmark == "foo" assert state_from_json.walltime == 100 assert state_from_json.reward is None assert state_from_json.commandline == "-a -b -c" def test_state_from_json_empty(): with pytest.raises(TypeError): CompilerEnvState.from_json({}) def test_state_equality_different_types(): state = CompilerEnvState(benchmark="foo", walltime=10, commandline="-a -b -c") assert not state == 5 # noqa testing __eq__ assert state != 5 # testing __ne__ def test_state_equality_same(): a = CompilerEnvState(benchmark="foo", walltime=10, commandline="-a -b -c") b = CompilerEnvState(benchmark="foo", walltime=10, commandline="-a -b -c") assert a == b # testing __eq__ assert not a != b # noqa testing __ne__ def test_state_equality_differnt_walltime(): """Test that walltime is not compared.""" a = CompilerEnvState(benchmark="foo", walltime=10, commandline="-a -b -c") b = CompilerEnvState(benchmark="foo", walltime=5, commandline="-a -b -c") assert a == b # testing __eq__ assert not a != b # noqa testing __ne__ def test_state_equality_one_sided_reward(): a = CompilerEnvState(benchmark="foo", walltime=5, commandline="-a -b -c", reward=2) b = CompilerEnvState(benchmark="foo", walltime=5, commandline="-a -b -c") assert a == b # testing __eq__ assert b == a # testing __eq__ assert not a != b # noqa testing __ne__ assert not b != a # noqa testing __ne__ def test_state_equality_equal_reward(): a = CompilerEnvState(benchmark="foo", walltime=5, commandline="-a -b -c", reward=2) b = CompilerEnvState(benchmark="foo", walltime=5, commandline="-a -b -c", reward=2) assert a == b # testing __eq__ assert b == a # testing __eq__ assert not a != b # noqa testing __ne__ assert not b != a # noqa testing __ne__ def test_state_equality_unequal_reward(): a = CompilerEnvState(benchmark="foo", walltime=5, commandline="-a -b -c", reward=2) b = CompilerEnvState(benchmark="foo", walltime=5, commandline="-a -b -c", reward=3) assert not a == b # noqa testing __eq__ assert not b == a # noqatesting __eq__ assert a != b # testing __ne__ assert b != a # testing __ne__ if __name__ == "__main__": main()

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87

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0.02

0.085172

0.091724

0.783103

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0.75069

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0.684483

0

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4,447

128

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0.785537

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0

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0.073063

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false

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0

null

0

1

0

null

0

1

0

6

7fc2268f1854da9bfcdae8388e5f01f68ccf4652

14,617

py

Python

wyvern-python/wyvern/types.py

carlocastoldi/wyvern

7d762c0a26552458799f39230a9c89ef9524550b

[ "Apache-2.0" ]

5

2018-11-21T09:53:19.000Z

2021-02-11T11:04:50.000Z

wyvern-python/wyvern/types.py

carlocastoldi/wyvern

7d762c0a26552458799f39230a9c89ef9524550b

[ "Apache-2.0" ]

null

wyvern-python/wyvern/types.py

carlocastoldi/wyvern

7d762c0a26552458799f39230a9c89ef9524550b

[ "Apache-2.0" ]

1

2018-10-08T14:00:28.000Z

#!/usr/bin/env python3 # # Copyright 2018 | Dario Ostuni <dario.ostuni@gmail.com> # # 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 enum import Enum from .util import UnreachableError class DataType(Enum): int32 = "I32" uint32 = "U32" float32 = "F32" bool = "Bool" class IoType(Enum): input = "input" output = "output" private = "private" class Variable: pass class Array: def _get_key(self, key): if type(key) == int: key = Constant.uint32(key, self._ctx) elif type(key) == Constant and key._ty == DataType.uint32: pass else: raise TypeError return key def __setitem__(self, key, value): key = self._get_key(key) value = self._ctx._sanitize(value) if type(value) != Constant or value._ty != self._ty: raise TypeError self._ctx.getProgramBuilder()._add_command({ "ArrayStore": [self._tid, key._tid, value._tid] }) def __getitem__(self, key): key = self._get_key(key) element = Constant._new_constant(self._ctx, self._ty) self._ctx.getProgramBuilder()._add_command({ "ArrayLoad": [element._tid, self._tid, key._tid] }) return element def __len__(self): length = Constant._new_constant(self._ctx, DataType.uint32) self._ctx.getProgramBuilder()._add_command({ "ArrayLen": [length._tid, self._tid] }) return length class Constant: def getContext(self): return self._ctx def getProgramBuilder(self): return self.getContext().getProgramBuilder() def __add__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Add": [result._tid, self._tid, other._tid] }) return result def __sub__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Sub": [result._tid, self._tid, other._tid] }) return result def __mul__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Mul": [result._tid, self._tid, other._tid] }) return result def __floordiv__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Div": [result._tid, self._tid, other._tid] }) return result def __truediv__(self, other): return self.__floordiv__(other) def __mod__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Rem": [result._tid, self._tid, other._tid] }) return result def __inv__(self): assert self._ty in (DataType.int32, DataType.uint32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Not": [result._tid, self._tid] }) return result def not_(self): assert self._ty in (DataType.bool,) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Not": [result._tid, self._tid] }) return result def __neg__(self): assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Neg": [result._tid, self._tid] }) return result def __lshift__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Shl": [result._tid, self._tid, other._tid] }) return result def __rshift__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "Shr": [result._tid, self._tid, other._tid] }) return result def __xor__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.bool) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "BitXor": [result._tid, self._tid, other._tid] }) return result def __and__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.bool) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "BitAnd": [result._tid, self._tid, other._tid] }) return result def __or__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.bool) result = Constant._new_constant(self.getContext(), self._ty) self.getProgramBuilder()._add_command({ "BitOr": [result._tid, self._tid, other._tid] }) return result def __eq__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32, DataType.bool) result = Constant._new_constant(self.getContext(), DataType.bool) self.getProgramBuilder()._add_command({ "Eq": [result._tid, self._tid, other._tid] }) return result def __ne__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32, DataType.bool) result = Constant._new_constant(self.getContext(), DataType.bool) self.getProgramBuilder()._add_command({ "Ne": [result._tid, self._tid, other._tid] }) return result def __lt__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), DataType.bool) self.getProgramBuilder()._add_command({ "Lt": [result._tid, self._tid, other._tid] }) return result def __le__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), DataType.bool) self.getProgramBuilder()._add_command({ "Le": [result._tid, self._tid, other._tid] }) return result def __gt__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), DataType.bool) self.getProgramBuilder()._add_command({ "Gt": [result._tid, self._tid, other._tid] }) return result def __ge__(self, other): other = self._ctx._sanitize(other) assert self.getProgramBuilder() == other.getProgramBuilder() assert self._ty == other._ty assert self._ty in (DataType.int32, DataType.uint32, DataType.float32) result = Constant._new_constant(self.getContext(), DataType.bool) self.getProgramBuilder()._add_command({ "Ge": [result._tid, self._tid, other._tid] }) return result @staticmethod def _new_constant(ctx, ty): const = Constant() const._ctx = ctx const._ty = ty const._tid = ctx._new_constant(ty) return const @staticmethod def int32(value, ctx=None): if type(value) not in (int, Constant): value = int(value) if type(value) == Constant: ctx = value.getContext() const = Constant._new_constant(ctx, DataType.int32) p = ctx.getProgramBuilder() if type(value) == int: if value < -2**31 or value >= 2**31: raise ValueError p._add_command({ "Constant": [const._tid, {DataType.int32.value: value}] }) elif type(value) == Constant: assert p == value.getProgramBuilder() if value._ty == DataType.int32: const._tid = value._tid elif value._ty == DataType.uint32: p._add_command({"I32fromU32": [const._tid, value._tid]}) elif value._ty == DataType.float32: p._add_command({"I32fromF32": [const._tid, value._tid]}) else: raise TypeError else: raise UnreachableError return const @staticmethod def uint32(value, ctx=None): if type(value) not in (int, Constant): value = int(value) if type(value) == Constant: ctx = value.getContext() const = Constant._new_constant(ctx, DataType.uint32) p = ctx.getProgramBuilder() if type(value) == int: if value < 0 or value >= 2**32: raise ValueError p._add_command({ "Constant": [const._tid, {DataType.uint32.value: value}] }) elif type(value) == Constant: assert p == value.getProgramBuilder() if value._ty == DataType.uint32: const._tid = value._tid elif value._ty == DataType.int32: p._add_command({"U32fromI32": [const._tid, value._tid]}) elif value._ty == DataType.float32: p._add_command({"U32fromF32": [const._tid, value._tid]}) else: raise TypeError else: raise UnreachableError return const @staticmethod def float32(value, ctx=None): if type(value) not in (float, Constant): value = float(value) if type(value) == Constant: ctx = value.getContext() const = Constant._new_constant(ctx, DataType.float32) p = ctx.getProgramBuilder() if type(value) == float: p._add_command({ "Constant": [const._tid, {DataType.float32.value: value}] }) elif type(value) == Constant: assert p == value.getProgramBuilder() if value._ty == DataType.uint32: p._add_command({"F32fromU32": [const._tid, value._tid]}) elif value._ty == DataType.int32: p._add_command({"F32fromI32": [const._tid, value._tid]}) elif value._ty == DataType.float32: const._tid = value._tid else: raise TypeError else: raise UnreachableError return const @staticmethod def bool(value, ctx=None): if type(value) not in (bool, Constant): value = bool(value) if type(value) == Constant: ctx = value.getContext() const = Constant._new_constant(ctx, DataType.bool) p = ctx.getProgramBuilder() if type(value) == bool: p._add_command({ "Constant": [const._tid, {DataType.bool.value: value}] }) elif type(value) == Constant: assert p == value.getProgramBuilder() if value._ty == DataType.bool: const._tid = value._tid else: raise TypeError else: raise UnreachableError return const

36.911616

78

0.604023

1,573

14,617

5.342657

0.102352

0.060685

0.049976

0.057473

0.808187

0.783198

0.773441

0.758091

0.74298

0.645526

0

0.018381

0.281658

14,617

395

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37.005063

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0.220588

0

null

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null

0

6

7fe8d50554c24fb061cdc608cedcb32073db5589

8,753

py

Python

code/CreateInputFeatureMaps_average_pooling_multiple_magnifications.py

saloniagarwal0403/SSCNN

30dafb61e5822d0011516c1d600450818844c106

[ "MIT" ]

null

code/CreateInputFeatureMaps_average_pooling_multiple_magnifications.py

saloniagarwal0403/SSCNN

30dafb61e5822d0011516c1d600450818844c106

[ "MIT" ]

null

code/CreateInputFeatureMaps_average_pooling_multiple_magnifications.py

saloniagarwal0403/SSCNN

30dafb61e5822d0011516c1d600450818844c106

[ "MIT" ]

null

import pickle import os import numpy as np import tensorflow as tf def get_model_predictions(original_image_features_pickle_file): filenames_and_features = [] with open(original_image_features_pickle_file, "rb") as input_file: filenames_and_features = pickle.load(input_file) filenames = filenames_and_features[0] features = filenames_and_features[1] max_x = -1 max_y = -1 index_level_x_y = [] for filename in filenames: tile_name = os.path.split(filename)[-1] tile_name = tile_name.split(".")[0] splited_tile_name = tile_name.split("_") tile_level = int(splited_tile_name[-3]) tile_x = int(splited_tile_name[-2]) tile_y = int(splited_tile_name[-1]) index_level_x_y.append([tile_level,tile_x,tile_y]) if max_x<tile_x: max_x = tile_x if max_y<tile_y: max_y = tile_y num_feature = np.array(features[0]).shape[-1] feature_map = {} # print(index_level_x_y) for i in range(len(features)): feature_i = np.mean(np.mean(features[i],axis=0),axis=0) feature_i = np.reshape(feature_i,(num_feature)) start_channel = num_feature*index_level_x_y[i][0] end_channel = num_feature*(index_level_x_y[i][0]+1) x = index_level_x_y[i][1] y = index_level_x_y[i][2] if (x,y) in feature_map: temp_feature = feature_map[(x,y)] temp_feature[start_channel:end_channel] = feature_i feature_map[(x,y)] = temp_feature else: temp_feature = np.zeros(3*num_feature) temp_feature[start_channel:end_channel] = feature_i feature_map[(x,y)] = temp_feature return list(feature_map.values()) def pca_transform_tensors(pca, num_feature, tensor_width, tensor_height, tensor_3D): number_of_samples = len(tensor_3D) resized_tensor = [] for sample in range(number_of_samples): w = len(tensor_3D[sample]) h = len(tensor_3D[sample][0]) feature_map = np.zeros((w,h,num_feature)) for i in range(w): for j in range(h): feature_i_j = tensor_3D[sample][i][j] transformed_feature_i_j = pca.transform([feature_i_j])[0] feature_map[i,j,:] = transformed_feature_i_j resized_tensor.append(tf.image.resize_with_crop_or_pad(feature_map, tensor_width, tensor_height)) resized_tensor = np.asarray(resized_tensor) return resized_tensor def create_tensors(original_image_features_pickle_file, pca, pca_num_feature, tensors_size, saving_folder): filenames_and_features = [] with open(original_image_features_pickle_file, "rb") as input_file: filenames_and_features = pickle.load(input_file) filenames = filenames_and_features[0] features = filenames_and_features[1] ### find the height and width of input tensor using filenames_and_features ### filename pattern tile_path = os.path.join(tile_folder,image_name+"_"+str(i)+"_"+str(x)+"_"+str(y)+".png") max_x = -1 max_y = -1 index_level_x_y = [] for filename in filenames: tile_name = os.path.split(filename)[-1] tile_name = tile_name.split(".")[0] splited_tile_name = tile_name.split("_") tile_level = int(splited_tile_name[-3]) tile_x = int(splited_tile_name[-2]) tile_y = int(splited_tile_name[-1]) index_level_x_y.append([tile_level,tile_x,tile_y]) if max_x<tile_x: max_x = tile_x if max_y<tile_y: max_y = tile_y num_feature = np.array(features[0]).shape[-1] feature_map = np.zeros(((max_x+1),(max_y+1),num_feature*3)) for i in range(len(features)): feature_i = np.mean(np.mean(features[i],axis=0),axis=0) feature_i = np.reshape(feature_i,(num_feature)) start_channel = num_feature*index_level_x_y[i][0] end_channel = num_feature*(index_level_x_y[i][0]+1) x = index_level_x_y[i][1] y = index_level_x_y[i][2] feature_map[x,y,start_channel:end_channel] = feature_i w = len(feature_map) h = len(feature_map[0]) resized_tensor = np.zeros((w,h,pca_num_feature)) for i in range(w): for j in range(h): feature_i_j = feature_map[i][j] transformed_feature_i_j = pca.transform([feature_i_j])[0] resized_tensor[i,j,:] = transformed_feature_i_j resized_tensor = tf.image.resize_with_crop_or_pad(resized_tensor, tensors_size, tensors_size) original_image_features_pickle_file_name = os.path.split(original_image_features_pickle_file)[-1] # print(original_image_features_pickle_file_name) with open(os.path.join(saving_folder,original_image_features_pickle_file_name), 'wb') as handle: pickle.dump(resized_tensor, handle) # return resized_tensor # for i in range(len(features)): # feature_i = np.mean(np.mean(features[i],axis=0),axis=0) # feature_i = np.reshape(feature_i,(num_feature)) # start_channel = num_feature*index_level_x_y[i][0] # end_channel = num_feature*(index_level_x_y[i][0]+1) # x = index_level_x_y[i][1] # y = index_level_x_y[i][2] # feature_map[x,y,start_channel:end_channel] = feature_i # return np.amax(np.amax(feature_map,axis=0),axis=0) # num_feature = np.array(features[0]).shape[-1] # feature_map = np.zeros(num_feature) # for i in range(len(features)): # feature_i = np.mean(np.mean(features[i],axis=0),axis=0) # feature_i = np.reshape(feature_i,(num_feature)) # if index_level_x_y[i][0]==1: # feature_map = feature_map+feature_i # return feature_map/(len(features)/3.0) # feature_map = np.zeros((42,42,num_feature)) # for i in range(len(features)): # if index_level_x_y[i][0]==0: # feature_i = np.mean(np.mean(features[i],axis=0),axis=0) # feature_i = np.reshape(feature_i,(num_feature)) # x = index_level_x_y[i][1] # y = index_level_x_y[i][2] # feature_map[x,y,:] = feature_i # return np.amax(np.amax(feature_map,axis=0),axis=0) # def create_tensors(original_image_features_pickle_file): # filenames_and_features = [] # with open(original_image_features_pickle_file, "rb") as input_file: # filenames_and_features = pickle.load(input_file) # filenames = filenames_and_features[0] # features = filenames_and_features[1] # ### find the height and width of input tensor using filenames_and_features # ### filename pattern tile_path = os.path.join(tile_folder,image_name+"_"+str(i)+"_"+str(x)+"_"+str(y)+".png") # max_x = -1 # max_y = -1 # index_level_x_y = [] # for filename in filenames: # tile_name = os.path.split(filename)[-1] # tile_name = tile_name.split(".")[0] # splited_tile_name = tile_name.split("_") # tile_level = int(splited_tile_name[-3]) # tile_x = int(splited_tile_name[-2]) # tile_y = int(splited_tile_name[-1]) # index_level_x_y.append([tile_level,tile_x,tile_y]) # if max_x<tile_x: # max_x = tile_x # if max_y<tile_y: # max_y = tile_y # # for i in range(len(features)): # # feature_i = np.mean(np.mean(features[i],axis=0),axis=0) # # feature_i = np.reshape(feature_i,(num_feature)) # # start_channel = num_feature*index_level_x_y[i][0] # # end_channel = num_feature*(index_level_x_y[i][0]+1) # # x = index_level_x_y[i][1] # # y = index_level_x_y[i][2] # # feature_map[x,y,start_channel:end_channel] = feature_i # # return np.amax(np.amax(feature_map,axis=0),axis=0) # # num_feature = np.array(features[0]).shape[-1] # feature_map = np.zeros(num_feature) # for i in range(len(features)): # feature_i = np.mean(np.mean(features[i],axis=0),axis=0) # feature_i = np.reshape(feature_i,(num_feature)) # if index_level_x_y[i][0]==1: # feature_map = feature_map+feature_i # return feature_map/(len(features)/3.0) # # # feature_map = np.zeros((42,42,num_feature)) # # for i in range(len(features)): # # if index_level_x_y[i][0]==0: # # feature_i = np.mean(np.mean(features[i],axis=0),axis=0) # # feature_i = np.reshape(feature_i,(num_feature)) # # x = index_level_x_y[i][1] # # y = index_level_x_y[i][2] # # feature_map[x,y,:] = feature_i # # return np.amax(np.amax(feature_map,axis=0),axis=0)

45.118557

116

0.62927

1,322

8,753

3.822239

0.076399

0.064912

0.067485

0.07362

0.860281

0.848407

0.823273

0.812982

0.782703

0

0.01762

0.241403

8,753

193

117

45.352332

0.743373

0.423283

0

0.653465

0

0.002108

0

1

0.029703

false

0

0.039604

0

0.089109

0

null

0

1

0

null

0

6

3d1224f1c3cbebc84146a6ecfea9252f233cedce

26,790

py

Python

tests/orca_unit_testing/test_combining_merge_asof_partition.py

jiajiaxu123/Orca

e86189e70c1d0387816bb98b8047a6232fbda9df

[ "Apache-2.0" ]

20

2019-12-02T11:49:12.000Z

2021-12-24T19:34:32.000Z

tests/orca_unit_testing/test_combining_merge_asof_partition.py

jiajiaxu123/Orca

e86189e70c1d0387816bb98b8047a6232fbda9df

[ "Apache-2.0" ]

null

tests/orca_unit_testing/test_combining_merge_asof_partition.py

jiajiaxu123/Orca

e86189e70c1d0387816bb98b8047a6232fbda9df

[ "Apache-2.0" ]

5

2019-12-02T12:16:22.000Z

2021-10-22T02:27:47.000Z

import unittest import orca import os.path as path from setup.settings import * from pandas.util.testing import * def _create_odf_csv(datal, datar): dfsDatabase = "dfs://testMergeAsofDB" s = orca.default_session() dolphindb_script = """ login('admin', '123456') if(existsDatabase('{dbPath}')) dropDatabase('{dbPath}') db=database('{dbPath}', VALUE, 2010.01M..2010.05M) stb1=extractTextSchema('{data1}') update stb1 set type="SYMBOL" where name="type" stb2=extractTextSchema('{data2}') update stb2 set type="SYMBOL" where name="ticker" loadTextEx(db,`tickers,`date, '{data1}',,stb1) loadTextEx(db,`values,`date, '{data2}',,stb2) """.format(dbPath=dfsDatabase, data1=datal, data2=datar) s.run(dolphindb_script) class Csv: odfs_csv_left = None odfs_csv_right = None pdf_csv_left = None pdf_csv_right = None class DfsMergeTest(unittest.TestCase): @classmethod def setUpClass(cls): # configure data directory DATA_DIR = path.abspath(path.join(__file__, "../setup/data")) left_fileName = 'test_merge_asof_left_table.csv' right_fileName = 'test_merge_asof_right_table.csv' datal = os.path.join(DATA_DIR, left_fileName) datal= datal.replace('\\', '/') datar = os.path.join(DATA_DIR, right_fileName) datar = datar.replace('\\', '/') dfsDatabase = "dfs://testMergeAsofDB" # connect to a DolphinDB server orca.connect(HOST, PORT, "admin", "123456") _create_odf_csv(datal, datar) # import Csv.odfs_csv_left = orca.read_table(dfsDatabase, 'tickers') Csv.pdf_csv_left = pd.read_csv(datal, parse_dates=[0]) Csv.odfs_csv_right = orca.read_table(dfsDatabase, 'values') Csv.pdf_csv_right = pd.read_csv(datar, parse_dates=[0]) @property def odfs_csv_left(self): return Csv.odfs_csv_left @property def odfs_csv_right(self): return Csv.odfs_csv_right @property def pdf_csv_left(self): return Csv.pdf_csv_left @property def pdf_csv_right(self): return Csv.pdf_csv_right @property def odfs_csv_left_index(self): return Csv.odfs_csv_left.set_index("date") @property def odfs_csv_right_index(self): return Csv.odfs_csv_right.set_index("date") @property def pdf_csv_left_index(self): return Csv.pdf_csv_left.set_index("date") @property def pdf_csv_right_index(self): return Csv.pdf_csv_right.set_index("date") @property def odfs_bid_csv_left(self): return self.odfs_csv_left.sort_values(by=['bid', 'date']).reset_index(drop=True) @property def odfs_bid_csv_right(self): return self.odfs_csv_right.sort_values(by=['bid', 'date']).reset_index(drop=True) @property def pdf_bid_csv_left(self): return self.pdf_csv_left.sort_values(by=['bid', 'date']).reset_index(drop=True) @property def pdf_bid_csv_right(self): return self.pdf_csv_right.sort_values(by=['bid', 'date']).reset_index(drop=True) @property def odfs_bid_csv_left_index(self): return self.odfs_csv_left.sort_values(by=['bid', 'date']).set_index('bid') @property def odfs_bid_csv_right_index(self): return self.odfs_csv_right.sort_values(by=['bid', 'date']).set_index('bid') @property def pdf_bid_csv_left_index(self): return self.pdf_csv_left.sort_values(by=['bid', 'date']).set_index('bid') @property def pdf_bid_csv_right_index(self): return self.pdf_csv_right.sort_values(by=['bid', 'date']).set_index('bid') def test_assert_original_dataframe_equal(self): assert_frame_equal(self.odfs_csv_left.to_pandas(), self.pdf_csv_left, check_dtype=False) assert_frame_equal(self.odfs_csv_right.to_pandas(), self.pdf_csv_right, check_dtype=False) assert_frame_equal(self.odfs_csv_left_index.to_pandas(), self.pdf_csv_left_index, check_dtype=False) assert_frame_equal(self.odfs_csv_right_index.to_pandas(), self.pdf_csv_right_index, check_dtype=False) assert_frame_equal(self.odfs_bid_csv_left.to_pandas(), self.pdf_bid_csv_left, check_dtype=False) assert_frame_equal(self.odfs_bid_csv_right.to_pandas(), self.pdf_bid_csv_right, check_dtype=False) assert_frame_equal(self.odfs_bid_csv_left_index.to_pandas(), self.pdf_bid_csv_left_index, check_dtype=False) assert_frame_equal(self.odfs_bid_csv_right_index.to_pandas(), self.pdf_bid_csv_right_index, check_dtype=False) def test_merge_asof_from_dfs_param_on(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, on='date') odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, on='date') assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, on='bid') odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, on='bid') assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_leftonrighton(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, left_on='date', right_on='date') odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, left_on='date', right_on='date') assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, left_on='bid', right_on='bid') odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, left_on='bid', right_on='bid') assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_index(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right_index, left_index=True, right_index=True) odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_index=True) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right_index, left_index=True, right_index=True) odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right_index, left_index=True, right_index=True) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_by(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, on='date', by='ticker') odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, on='date', by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, on='bid', by='ticker') odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, on='bid', by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_leftbyrightby(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, on='date', left_by='ticker', right_by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, on='date', left_by='ticker', right_by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, on='bid', left_by='ticker', right_by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, on='bid', left_by='ticker', right_by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, on='date', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, on='date', suffixes=('_left', '_right')) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, on='bid', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, on='bid', suffixes=('_left', '_right')) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_leftonrighton_param_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, left_on='date', right_on='date', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, left_on='date', right_on='date', suffixes=('_left', '_right')) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, left_on='bid', right_on='bid', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, left_on='bid', right_on='bid', suffixes=('_left', '_right')) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_leftonrighton_param_by(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, left_on='date', right_on='date', by='ticker') odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, left_on='date', right_on='date', by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, left_on='bid', right_on='bid', by='ticker') odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, left_on='bid', right_on='bid', by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_leftonrighton_param_leftbyrightby(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, on='date', left_by='ticker', right_by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, on='date', left_by='ticker', right_by='ticker') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, on='bid', left_by='ticker', right_by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, on='bid', left_by='ticker', right_by='ticker') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_index_param_by(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right_index, left_index=True, right_index=True, by='ticker') odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_index=True, by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right_index, left_index=True, right_index=True, by='ticker') odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right_index, left_index=True, right_index=True, by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_index_param_leftbyrightby(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right_index, left_index=True, right_index=True, left_by='ticker', right_by='ticker') odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_index=True, left_by='ticker', right_by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right_index, left_index=True, right_index=True, left_by='ticker', right_by='ticker') odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right_index, left_index=True, right_index=True, left_by='ticker', right_by='ticker') # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_index_param_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right_index, left_index=True, right_index=True, suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_index=True, suffixes=('_left', '_right')) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right_index, left_index=True, right_index=True, suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right_index, left_index=True, right_index=True, suffixes=('_left', '_right')) assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_on_param_by_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, on='date', by='ticker', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, on='date', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, on='bid', by='ticker', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, on='bid', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_on_param_leftbyrightby_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, on='date', left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, on='date', # left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, on='bid', left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, on='bid', left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_leftonrighton_param_by_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, left_on='date', right_on='date', by='ticker', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, left_on='date', right_on='date', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, left_on='bid', right_on='bid', by='ticker', suffixes=('_left', '_right')) pdf.fillna("", inplace=True) odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, left_on='bid', right_on='bid', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_leftonrighton_param_leftbyrightby_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right, left_on='date', right_on='date', left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right, left_on='date', right_on='date', # left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right, left_on='bid', right_on='bid', left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right, left_on='bid', right_on='bid', # left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_index_param_by_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right_index, left_index=True, right_index=True, by='ticker', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_index=True, by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right_index, left_index=True, right_index=True, by='ticker', suffixes=('_left', '_right')) odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right_index, left_index=True, right_index=True, by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_index_param_leftbyrightby_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right_index, left_index=True, right_index=True, left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_index=True, # left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right_index, left_index=True, right_index=True, left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right_index, left_index=True, right_index=True, # left_by='ticker', right_by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_on_param_index(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right, left_index=True, right_on='date') # TODO:ORCA error left_index, right_on not supported # odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_on='date') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right_index, right_index=True, left_on='date') # TODO:ORCA error left_index, right_on not supported # odf = orca.merge_asof(self.odfs_csv_left, self.odfs_csv_right_index, right_index=True, left_on='date') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right, left_index=True, right_on='bid') # TODO:ORCA error left_index, right_on not supported # odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right, left_index=True, right_on='bid') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right_index, right_index=True, left_on='bid') # TODO:ORCA error left_index, right_on not supported # odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right_index, right_index=True, left_on='bid') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_on_param_index_param_by(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right, left_index=True, right_on='date', by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_on='date', by='ticker') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right_index, right_index=True, left_on='date', by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, right_index=True, left_on='date', by='ticker') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right, left_index=True, right_on='bid', by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right, left_index=True, right_on='bid', by='ticker') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right_index, right_index=True, left_on='bid', by='ticker') # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right_index, right_index=True, left_on='bid', by='ticker') # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) def test_merge_asof_from_dfs_param_on_param_index_param_by_param_suffixes(self): pdf = pd.merge_asof(self.pdf_csv_left_index, self.pdf_csv_right, left_index=True, right_on='date', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, left_index=True, right_on='date', # by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_csv_left, self.pdf_csv_right_index, right_index=True, left_on='date', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_csv_left_index, self.odfs_csv_right_index, right_index=True, left_on='date', # by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False) pdf = pd.merge_asof(self.pdf_bid_csv_left_index, self.pdf_bid_csv_right, left_index=True, right_on='bid', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left_index, self.odfs_bid_csv_right, left_index=True, right_on='bid', # by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) pdf = pd.merge_asof(self.pdf_bid_csv_left, self.pdf_bid_csv_right_index, right_index=True, left_on='bid', by='ticker', suffixes=('_left', '_right')) # TODO:ORCA by bug # odf = orca.merge_asof(self.odfs_bid_csv_left, self.odfs_bid_csv_right_index, right_index=True, left_on='bid', # by='ticker', suffixes=('_left', '_right')) # assert_frame_equal(odf.to_pandas().fillna(""), pdf.fillna(""), check_dtype=False, check_like=False) if __name__ == '__main__': unittest.main()

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0.661627

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26,790

4.190254

0.032141

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0.077199

0.045033

0.930471

0.916553

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0.2607

0

null

0

1

0

null

0

6

3d131a81b328755630687d48ce0728b9904b030e

2,525

py

Python

ensemble_transformers/ensemble.py

jaketae/ensemble-transformers

14eb9639de20d694356b374e2bd8223b02c3472e

[ "MIT" ]

18

2022-03-28T09:24:37.000Z

2022-03-31T06:32:00.000Z

ensemble_transformers/ensemble.py

jaketae/ensemble-transformers

14eb9639de20d694356b374e2bd8223b02c3472e

[ "MIT" ]

null

ensemble_transformers/ensemble.py

jaketae/ensemble-transformers

14eb9639de20d694356b374e2bd8223b02c3472e

[ "MIT" ]

null

from typing import List, Union import numpy as np import torch from PIL.Image import Image from ensemble_transformers.base import EnsembleBaseModel class EnsembleModelForSequenceClassification(EnsembleBaseModel): def forward( self, text: List[str], main_device: Union[str, torch.device] = "cpu", return_all_outputs: bool = False, preprocessor_kwargs: dict = {"return_tensors": "pt", "padding": True}, ): outputs = [] for i, (model, preprocessor) in enumerate(zip(self.models, self.preprocessors)): inputs = preprocessor(text, **preprocessor_kwargs).to(self.devices[i]) output = model(**inputs) outputs.append(output) if return_all_outputs: return outputs return torch.stack( [weight * output.logits.to(main_device) for weight, output in zip(self.config.weights, outputs)] ).sum(dim=0) class EnsembleModelForImageClassification(EnsembleBaseModel): def forward( self, images: List[Image], main_device: Union[str, torch.device] = "cpu", return_all_outputs: bool = False, preprocessor_kwargs: dict = {"return_tensors": "pt"}, ): outputs = [] for i, (model, preprocessor) in enumerate(zip(self.models, self.preprocessors)): inputs = preprocessor(images, **preprocessor_kwargs).to(self.devices[i]) output = model(**inputs) outputs.append(output) if return_all_outputs: return outputs return torch.stack( [weight * output.logits.to(main_device) for weight, output in zip(self.config.weights, outputs)] ).sum(dim=0) class EnsembleModelForAudioClassification(EnsembleBaseModel): def forward( self, audio: np.ndarray, main_device: Union[str, torch.device] = "cpu", return_all_outputs: bool = False, preprocessor_kwargs: dict = {"return_tensors": "pt", "sampling_rate": None, "padding": "longest"}, ): outputs = [] for i, (model, preprocessor) in enumerate(zip(self.models, self.preprocessors)): inputs = preprocessor(audio, **preprocessor_kwargs).to(self.devices[i]) output = model(**inputs) outputs.append(output) if return_all_outputs: return outputs return torch.stack( [weight * output.logits.to(main_device) for weight, output in zip(self.config.weights, outputs)] ).sum(dim=0)

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0.632475

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0.25

0.038265

0.061224

0.059311

0.727679

0

0.001596

0.255446

2,525

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0

null

0

1

0

1

0

null

0

6

3d41e9a07845b7d59eb29ff545db8929e09e40c1

130

py

Python

DonkiPlayer/scripts/mcstas-generator/src/neventarray.py

ess-dmsc/do-ess-data-simulator

37ef0d87ad0152b092e3a636ef8d080db0711aaa

[ "BSD-2-Clause" ]

null

DonkiPlayer/scripts/mcstas-generator/src/neventarray.py

ess-dmsc/do-ess-data-simulator

37ef0d87ad0152b092e3a636ef8d080db0711aaa

[ "BSD-2-Clause" ]

null

DonkiPlayer/scripts/mcstas-generator/src/neventarray.py

ess-dmsc/do-ess-data-simulator

37ef0d87ad0152b092e3a636ef8d080db0711aaa

[ "BSD-2-Clause" ]

null

import numpy as np event_t = np.dtype(np.uint64) def multiplyNEventArray(data,multiplier) : return np.tile(data,multiplier)

18.571429

42

0.761538

19

130

5.157895

0.736842

0.285714

0

0.017857

0.138462

130

6

43

21.666667

0.857143

0

1

0.25

false

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0.25

0.75

0

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null

1

0

1

0

null

0

1

0

1

0

6

3d4fded10fddcb5590f4e2a2320bcfa1726fa1ac

45

py

Python

spacy/tests/enable_gpu.py

snosrap/spaCy

3f68bbcfec44ef55d101e6db742d353b72652129

[ "MIT" ]

22,040

2016-10-03T11:58:15.000Z

2022-03-31T21:08:19.000Z

spacy/tests/enable_gpu.py

snosrap/spaCy

3f68bbcfec44ef55d101e6db742d353b72652129

[ "MIT" ]

6,927

2016-10-03T13:11:11.000Z

2022-03-31T17:01:25.000Z

spacy/tests/enable_gpu.py

snosrap/spaCy

3f68bbcfec44ef55d101e6db742d353b72652129

[ "MIT" ]

4,403

2016-10-04T03:36:33.000Z

2022-03-31T14:12:34.000Z

from spacy import require_gpu require_gpu()

11.25

29

0.822222

7

45

5

0.714286

0.571429

0

0.133333

45

3

30

15

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true

0

0.5

0

0.5

0

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1

0

1

0

null

0

1

0

1

0

6

18503c11b24cdd3fce4041c5c79c4283681a0823

6,355

py

Python

boltzgen/distributions.py

VincentStimper/boltzmann-generators

2ef7d9d5ee90277a4556339b71d0eba1443351ec

[ "MIT" ]

2

2021-06-09T11:16:18.000Z

2022-02-03T08:12:15.000Z

boltzgen/distributions.py

VincentStimper/boltzmann-generators

2ef7d9d5ee90277a4556339b71d0eba1443351ec

[ "MIT" ]

null

boltzgen/distributions.py

VincentStimper/boltzmann-generators

2ef7d9d5ee90277a4556339b71d0eba1443351ec

[ "MIT" ]

null

import torch import numpy as np import normflow as nf import multiprocessing as mp from torch import nn from . import openmm_interface as omi class Boltzmann(nf.distributions.PriorDistribution): """ Boltzmann distribution using OpenMM to get energy and forces """ def __init__(self, sim_context, temperature, energy_cut, energy_max): """ Constructor :param sim_context: Context of the simulation object used for energy and force calculation :param temperature: Temperature of System """ # Save input parameters self.sim_context = sim_context self.temperature = temperature self.energy_cut = torch.tensor(energy_cut) self.energy_max = torch.tensor(energy_max) # Set up functions self.openmm_energy = omi.OpenMMEnergyInterface.apply self.regularize_energy = omi.regularize_energy self.norm_energy = lambda pos: self.regularize_energy( self.openmm_energy(pos, self.sim_context, temperature)[:, 0], self.energy_cut, self.energy_max) def log_prob(self, z): return -self.norm_energy(z) class TransformedBoltzmann(nn.Module): """ Boltzmann distribution with respect to transformed variables, uses OpenMM to get energy and forces """ def __init__(self, sim_context, temperature, energy_cut, energy_max, transform): """ Constructor :param sim_context: Context of the simulation object used for energy and force calculation :param temperature: Temperature of System :param energy_cut: Energy at which logarithm is applied :param energy_max: Maximum energy :param transform: Coordinate transformation """ super().__init__() # Save input parameters self.sim_context = sim_context self.temperature = temperature self.energy_cut = torch.tensor(energy_cut) self.energy_max = torch.tensor(energy_max) # Set up functions self.openmm_energy = omi.OpenMMEnergyInterface.apply self.regularize_energy = omi.regularize_energy self.norm_energy = lambda pos: self.regularize_energy( self.openmm_energy(pos, self.sim_context, temperature)[:, 0], self.energy_cut, self.energy_max) self.transform = transform def log_prob(self, z): z, log_det = self.transform(z) return -self.norm_energy(z) + log_det class BoltzmannParallel(nf.distributions.PriorDistribution): """ Boltzmann distribution using OpenMM to get energy and forces and processes the batch of states in parallel """ def __init__(self, system, temperature, energy_cut, energy_max, n_threads=None): """ Constructor :param system: Molecular system :param temperature: Temperature of System :param energy_cut: Energy at which logarithm is applied :param energy_max: Maximum energy :param n_threads: Number of threads to use to process batches, set to the number of cpus if None """ # Save input parameters self.system = system self.temperature = temperature self.energy_cut = torch.tensor(energy_cut) self.energy_max = torch.tensor(energy_max) self.n_threads = mp.cpu_count() if n_threads is None else n_threads # Create pool for parallel processing self.pool = mp.Pool(self.n_threads, omi.OpenMMEnergyInterfaceParallel.var_init, (system, temperature)) # Set up functions self.openmm_energy = omi.OpenMMEnergyInterfaceParallel.apply self.regularize_energy = omi.regularize_energy self.norm_energy = lambda pos: self.regularize_energy( self.openmm_energy(pos, self.pool)[:, 0], self.energy_cut, self.energy_max) def log_prob(self, z): return -self.norm_energy(z) class TransformedBoltzmannParallel(nn.Module): """ Boltzmann distribution with respect to transformed variables, uses OpenMM to get energy and forces and processes the batch of states in parallel """ def __init__(self, system, temperature, energy_cut, energy_max, transform, n_threads=None): """ Constructor :param system: Molecular system :param temperature: Temperature of System :param energy_cut: Energy at which logarithm is applied :param energy_max: Maximum energy :param transform: Coordinate transformation :param n_threads: Number of threads to use to process batches, set to the number of cpus if None """ super().__init__() # Save input parameters self.system = system self.temperature = temperature self.energy_cut = torch.tensor(energy_cut) self.energy_max = torch.tensor(energy_max) self.n_threads = mp.cpu_count() if n_threads is None else n_threads # Create pool for parallel processing self.pool = mp.Pool(self.n_threads, omi.OpenMMEnergyInterfaceParallel.var_init, (system, temperature)) # Set up functions self.openmm_energy = omi.OpenMMEnergyInterfaceParallel.apply self.regularize_energy = omi.regularize_energy self.norm_energy = lambda pos: self.regularize_energy( self.openmm_energy(pos, self.pool)[:, 0], self.energy_cut, self.energy_max) self.transform = transform def log_prob(self, z): z_, log_det = self.transform(z) return -self.norm_energy(z_) + log_det class DoubleWell(nf.distributions.PriorDistribution): """ Boltzmann distribution of the double well potential of the form U(x, y) = 1/4 * a * x**4 - 1/2 * b * x**2 + c * x + 1/2 * d * y**2 """ def __init__(self, a=1, b=6, c=1, d=1): """ Constructor :param a: Parameter of the potential :param b: Parameter of the potential :param c: Parameter of the potential :param d: Parameter of the potential """ self.a = a self.b = b self.c = c self.d = d def log_prob(self, z): return -self.a / 4 * z[:, 0] ** 4 + self.b / 2 * z[:, 0] ** 2 - self.c * z[:, 0] - self.d / 2 * z[:, 1] ** 2

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0

null

0

1

0

null

0

6

185b9ebef27c6f66b6db599680fd48cace05d26b

14,736

py

Python

tests/test_class_decoration.py

paulroujansky/pydeco

9bb31e8cf801f6316fd0c5c554000ae26256019a

[ "MIT" ]

1

2019-08-26T09:10:48.000Z

tests/test_class_decoration.py

paulroujansky/pydeco

9bb31e8cf801f6316fd0c5c554000ae26256019a

[ "MIT" ]

4

2019-07-23T13:38:08.000Z

2019-08-26T07:53:00.000Z

tests/test_class_decoration.py

paulroujansky/pydeco

9bb31e8cf801f6316fd0c5c554000ae26256019a

[ "MIT" ]

2

2019-08-26T09:06:00.000Z

2021-04-29T16:42:33.000Z

"""Test class decoration.""" import os import pickle as pkl import sys from copy import deepcopy import pytest from joblib import Parallel, delayed from pydeco import Decorator, MethodsDecorator from pydeco.utils.register import unregister_all from pydeco.utils import PYTHON_VERSION global logs logs = [] # Utils # ----------------------------------------------------------------------------- # Defining custom func decorators # ------------------------------- class Decorator1(Decorator): """Decorator 1.""" def __init__(self, name, *args, **kwargs): self.name = name Decorator.__init__(self) def __repr__(self): """Return the string representation.""" return '{}[id={}]'.format(self.__class__.__name__, id(self)) def wrapper(self, instance, func, *args, **kwargs): """Wrap input instance method with runtime measurement.""" logs.append({ self.__class__.__name__: id(self), instance.__class__.__name__: id(instance) }) print('{} decorating {}[id={}]'.format(self, instance, id(instance))) instance.cnt_dec_1 += 1 # updating instance cnt for decorator return func(instance, *args, **kwargs) class Decorator2(Decorator): """Decorator 2.""" def __init__(self, name, *args, **kwargs): self.name = name Decorator.__init__(self) def __repr__(self): """Return the string representation.""" return '{}[id={}]'.format(self.__class__.__name__, id(self)) def wrapper(self, instance, func, *args, **kwargs): """Wrap input instance method with runtime measurement.""" logs.append({ self.__class__.__name__: id(self), instance.__class__.__name__: id(instance) }) print('{} decorating {}[id={}]'.format(self, instance, id(instance))) instance.cnt_dec_2 += 1 # updating instance cnt for decorator return func(instance, *args, **kwargs) # Defining custom processing class # -------------------------------- class MyClass(): """Custom class.""" def __init__(self, *args, **kwargs): self.cnt_dec_1 = 0 self.cnt_dec_2 = 0 def method_1(self, *args, **kwargs): # print('Run method 1') pass def method_2(self, *args, **kwargs): # print('Run method 2') pass def method_3(self, *args, **kwargs): # print('Run method 3') pass def __repr__(self): return '{}(cnt_dec_1={}, cnt_dec_1={})'.format( self.__class__.__name__, self.cnt_dec_1, self.cnt_dec_2) # Define custom function # ---------------------- def myfunc(i, instance, copy, iter_process, verbose=True): """In the title.""" # keep track of iterations within each PID pid = os.getpid() # get current process ID if verbose: print('Iter {}: PID={}\n'.format(i + 1, pid)) # run methods instance.method_1() instance.method_2() instance.method_3() return (pid, id(instance)) # Tests # ---------------------------------------------------------------------------- def test_class_decoration(verbose=False): """Test class decoration.""" from pydeco.utils.parser import CONFIG CONFIG['N_DISPATCH'] = None unregister_all() global logs logs = [] # instantiate the class instance = MyClass() assert repr(instance) == 'MyClass(cnt_dec_1=0, cnt_dec_1=0)' # run methods instance.method_1() instance.method_2() instance.method_3() assert instance.cnt_dec_1 == 0 and instance.cnt_dec_2 == 0 # decorate methods MyClass_deco = MethodsDecorator( mapping={ Decorator1(name='decorator_1'): ['method_1', 'method_2'], Decorator2(name='decorator_2'): 'method_1' })(MyClass) # instantiate the class instance = MyClass_deco() assert repr(instance) == 'Wrapped(MyClass)(cnt_dec_1=0, cnt_dec_1=0)' # run methods instance.method_1() instance.method_2() instance.method_3() assert repr(instance) == 'Wrapped(MyClass)(cnt_dec_1=2, cnt_dec_1=1)' assert instance.cnt_dec_1 == 2 and instance.cnt_dec_2 == 1 # decorate methods with pytest.raises(ValueError, match='Input class has not method "method_4"'): MyClass_deco = MethodsDecorator( mapping={ Decorator1(name='decorator_1'): ['method_1', 'method_2'], Decorator2(name='decorator_2'): ['method_1', 'method_4'] })(MyClass) unregister_all() def test_deepcopying(verbose=True): """Test deepcopying.""" from pydeco.utils.parser import CONFIG CONFIG['N_DISPATCH'] = 1 unregister_all() global logs logs = [] # decorate methods of base class MyClass_deco = MethodsDecorator( mapping={ Decorator1(name='decorator_1'): ['method_1', 'method_2'], Decorator2(name='decorator_2'): 'method_1' })(MyClass) # instantiate the decorated class instance = MyClass_deco() if verbose: print('Before deepcopy...\n' + '-' * 18) for inst in [instance]: print('Instance: {} (id={})'.format(inst, id(inst))) print('Mapping:') print(inst._decorator_mapping) print('Decorators') for deco_name, deco in inst.decorators.items(): print('\t Decorator: {}'.format(deco)) print('\n') # create a deepcopy of `instance` instance_2 = deepcopy(instance) if verbose: print('After deepcopy...\n' + '-' * 17) for inst in [instance, instance_2]: print('Instance: {} (id={})'.format(inst, id(inst))) print('Mapping:') print(inst._decorator_mapping) print('Decorators') for deco_name, deco in inst.decorators.items(): print('\t Decorator: {}'.format(deco)) print('\n') # check that `instance` and `instance_2` are distinct objects assert instance is not instance_2 # check that decorators of `instance` and `instance_2` are distinct objects for (deco1_name, deco1), (deco2_name, deco2) in zip( instance.decorators.items(), instance_2.decorators.items()): assert deco1 is not deco2 assert instance.cnt_dec_1 == 0 and instance.cnt_dec_2 == 0 assert instance_2.cnt_dec_1 == 0 and instance_2.cnt_dec_2 == 0 assert instance.cnt_dec_1 == 0 and instance.cnt_dec_2 == 0 assert instance_2.cnt_dec_1 == 0 and instance_2.cnt_dec_2 == 0 # run methods for `instance` # run methods instance_2.method_1() instance_2.method_2() instance_2.method_3() for j, entry in enumerate(logs): assert entry['Wrapped2(MyClass)'] == id(instance_2) if j == 0: assert (entry['Decorator2'] == id(instance_2.decorators['Decorator2'])) elif j == 1: assert (entry['Decorator1'] == id(instance_2.decorators['Decorator1'])) elif j == 2: assert (entry['Decorator1'] == id(instance_2.decorators['Decorator1'])) # check that internal variables of `instance`' have changed but not of # `instance_2` assert instance.cnt_dec_1 == 0 and instance.cnt_dec_2 == 0 assert instance_2.cnt_dec_1 == 2 and instance_2.cnt_dec_2 == 1 # run methods instance.method_1() instance.method_2() instance.method_3() for j, entry in enumerate(logs): if j < 3: assert entry['Wrapped2(MyClass)'] == id(instance_2) if j == 0: assert (entry['Decorator2'] == id(instance_2.decorators['Decorator2'])) elif j == 1: assert (entry['Decorator1'] == id(instance_2.decorators['Decorator1'])) elif j == 2: assert (entry['Decorator1'] == id(instance_2.decorators['Decorator1'])) else: assert entry['Wrapped(MyClass)'] == id(instance) if j == 3: assert (entry['Decorator2'] == id(instance.decorators['Decorator2'])) elif j == 4: assert (entry['Decorator1'] == id(instance.decorators['Decorator1'])) elif j == 5: assert (entry['Decorator1'] == id(instance.decorators['Decorator1'])) assert instance.cnt_dec_1 == 2 and instance.cnt_dec_2 == 1 assert instance_2.cnt_dec_1 == 2 and instance_2.cnt_dec_2 == 1 unregister_all() @pytest.mark.parametrize('dcopy', (False, True)) def test_pickling(dcopy, verbose=True): """Test pickling.""" from pydeco.utils.parser import CONFIG CONFIG['N_DISPATCH'] = 1 unregister_all() global logs logs = [] # decorate methods of base class MyClass_deco = MethodsDecorator( mapping={ Decorator1(name='decorator_1'): ['method_1', 'method_2'], Decorator2(name='decorator_2'): 'method_1' })(MyClass) # instantiate the decorated class instance = MyClass_deco() if verbose: print('Before pickling...\n' + '-' * 18) for inst in [instance]: print('Instance: {} (id={})'.format(inst, id(inst))) print('Mapping:') print(inst._decorator_mapping) print('Decorators') for deco_name, deco in inst.decorators.items(): print('\t Decorator: {}'.format(deco)) print('\n') instance_ = deepcopy(instance) if dcopy else instance # Save instance as a pickle object tmp = pkl.dumps(instance_) # Load pickled module instance_2 = pkl.loads(tmp) if verbose: print('After pickling...\n' + '-' * 17) for inst in [instance, instance_2]: print('Instance: {} (id={})'.format(inst, id(inst))) print('Mapping:') print(inst._decorator_mapping) print('Decorators') for deco_name, deco in inst.decorators.items(): print('\t Decorator: {}'.format(deco)) print('\n') # check that `instance` and `instance_2` are distinct objects assert instance is not instance_2 # check that decorators of `instance` and `instance_2` are distinct objects for (deco1_name, deco1), (deco2_name, deco2) in zip( instance.decorators.items(), instance_2.decorators.items()): assert deco1 is not deco2 assert instance.cnt_dec_1 == 0 and instance.cnt_dec_2 == 0 assert instance_2.cnt_dec_1 == 0 and instance_2.cnt_dec_2 == 0 # run methods for `instance` # run methods instance_2.method_1() instance_2.method_2() instance_2.method_3() new_classname = 'Wrapped2(MyClass)' if dcopy else 'Wrapped(MyClass)' for j, entry in enumerate(logs): assert entry[new_classname] == id(instance_2) if j == 0: assert (entry['Decorator2'] == id(instance_.decorators['Decorator2'])) elif j == 1: assert (entry['Decorator1'] == id(instance_.decorators['Decorator1'])) elif j == 2: assert (entry['Decorator1'] == id(instance_.decorators['Decorator1'])) # check that internal variables of `instance`' have changed but not of # `instance_2` assert instance.cnt_dec_1 == 0 and instance.cnt_dec_2 == 0 assert instance_2.cnt_dec_1 == 2 and instance_2.cnt_dec_2 == 1 # run methods instance.method_1() instance.method_2() instance.method_3() for j, entry in enumerate(logs): if j < 3: assert entry[new_classname] == id(instance_2) if j == 0: assert (entry['Decorator2'] == id(instance_.decorators['Decorator2'])) elif j == 1: assert (entry['Decorator1'] == id(instance_.decorators['Decorator1'])) elif j == 2: assert (entry['Decorator1'] == id(instance_.decorators['Decorator1'])) else: assert entry['Wrapped(MyClass)'] == id(instance) if j == 3: assert (entry['Decorator2'] == id(instance.decorators['Decorator2'])) elif j == 4: assert (entry['Decorator1'] == id(instance.decorators['Decorator1'])) elif j == 5: assert (entry['Decorator1'] == id(instance.decorators['Decorator1'])) assert instance.cnt_dec_1 == 2 and instance.cnt_dec_2 == 1 assert instance_2.cnt_dec_1 == 2 and instance_2.cnt_dec_2 == 1 unregister_all() @pytest.mark.parametrize(argnames='copy', argvalues=(True, False)) @pytest.mark.parametrize(argnames='n_iter', argvalues=(10, 20, 30)) def test_parallelizing(copy, n_iter, n_jobs=1, verbose=True): """Test parallelizing.""" from pydeco.utils.parser import CONFIG CONFIG['N_DISPATCH'] = n_iter + 1 unregister_all() global logs logs = [] # store number of iterations for each process global iter_process iter_process = dict() # decorate methods of base class MyClass_deco = MethodsDecorator( mapping={ Decorator1(name='decorator_1'): ['method_1', 'method_2'], Decorator2(name='decorator_2'): 'method_1' })(MyClass) # instantiate the decorated class instance = MyClass_deco() # create a "reference" instance instance_ref = deepcopy(instance) if verbose: print('Before deepcopy...\n' + '-' * 18) for inst in [instance, instance_ref]: print('Instance: {} (id={})'.format(inst, id(inst))) print('Mapping:') print(inst._decorator_mapping) print('Decorators') for deco_name, deco in inst.decorators.items(): print('\t Decorator: {}'.format(deco)) print('\n') # run parallel jobs if verbose: print('Parallelizing: {} iterations distributed on {} jobs'.format( n_iter, n_jobs)) backend = 'multiprocessing' if copy else 'threading' with Parallel(n_jobs=n_jobs, verbose=verbose, pre_dispatch='all', backend=backend) as parallel: res = parallel( delayed(myfunc)(i, deepcopy(instance), copy=copy, verbose=verbose, iter_process=iter_process) for i in range(n_iter) ) unregister_all() if __name__ == "__main__": pytest.main([__file__])

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43e56935f5c7f9942ef424cf34e77d1555d573b4

177

py

Python

gs_extensions/exceptions.py

ilyachch/gnome_shell_extensions_install_tool

e1e19b4d390db99e243fa0e0cd4466fd843482c9

[ "MIT" ]

null

gs_extensions/exceptions.py

ilyachch/gnome_shell_extensions_install_tool

e1e19b4d390db99e243fa0e0cd4466fd843482c9

[ "MIT" ]

4

2019-03-25T07:27:45.000Z

2020-01-16T14:54:07.000Z

gs_extensions/exceptions.py

ilyachch/gs_extensions

e1e19b4d390db99e243fa0e0cd4466fd843482c9

[ "MIT" ]

null

class GnomeShellNotInstalledError(RuntimeError): pass class ExtensionNotFoundInHub(RuntimeError): pass class NoExtensionVersionForGnomeShell(RuntimeError): pass

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a176754ec9a778e1b2045ae7defa8b110abf246f

123

py

Python

tracklib/util/__init__.py

SGrosse-Holz/tracklib

e0b88e3959db2ce65869d8292ce5792f4c77c7a4

[ "MIT" ]

1

2022-01-30T15:10:51.000Z

tracklib/util/__init__.py

SGrosse-Holz/tracklib

e0b88e3959db2ce65869d8292ce5792f4c77c7a4

[ "MIT" ]

null

tracklib/util/__init__.py

SGrosse-Holz/tracklib

e0b88e3959db2ce65869d8292ce5792f4c77c7a4

[ "MIT" ]

null

from .util import * from . import mcmc from .sweep import Sweeper from . import plotting from .parallel import Parallelize

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a188a17ac12a6847a914161fd1960b3020690f3a

49

py

Python

src/token_secret.py

hpkishere/telebiblebot

de72006d1a08f7e3c15641406c99a78d6609bbac

[ "MIT" ]

null

src/token_secret.py

hpkishere/telebiblebot

de72006d1a08f7e3c15641406c99a78d6609bbac

[ "MIT" ]

1

2018-01-03T08:30:46.000Z

src/token_secret.py

hpkishere/telebiblebot

de72006d1a08f7e3c15641406c99a78d6609bbac

[ "MIT" ]

null

#insert token here token = '<insert token here>'

24.5

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null

0

6

a1a57fbdcd7e54a8d8a64e827541c84d1783830a

275

py

Python

snmpagent_unity/unity_impl/DiskSerialNumber.py

factioninc/snmp-unity-agent

3525dc0fac60d1c784dcdd7c41693544bcbef843

[ "Apache-2.0" ]

2

2019-03-01T11:14:59.000Z

2019-10-02T17:47:59.000Z

snmpagent_unity/unity_impl/DiskSerialNumber.py

factioninc/snmp-unity-agent

3525dc0fac60d1c784dcdd7c41693544bcbef843

[ "Apache-2.0" ]

2

2019-03-01T11:26:29.000Z

2019-10-11T18:56:54.000Z

snmpagent_unity/unity_impl/DiskSerialNumber.py

factioninc/snmp-unity-agent

3525dc0fac60d1c784dcdd7c41693544bcbef843

[ "Apache-2.0" ]

1

2019-10-03T21:09:17.000Z

class DiskSerialNumber(object): def read_get(self, name, idx_name, unity_client): return unity_client.get_disk_serial_number(idx_name) class DiskSerialNumberColumn(object): def get_idx(self, name, idx, unity_client): return unity_client.get_disks()

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null

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6

a1dafe77e624a0abc16c90271e68e80a9c1a9022

22,160

py

Python

pybind/slxos/v16r_1_00b/brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/__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__ import stp import rstp import mstp import pvstp import rpvstp class spanning_tree_info(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module brocade-xstp-ext - based on the path /brocade_xstp_ext_rpc/get-stp-brief-info/output/spanning-tree-info. 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', '__stp_mode','__stp','__rstp','__mstp','__pvstp','__rpvstp',) _yang_name = 'spanning-tree-info' _rest_name = 'spanning-tree-info' _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.__rstp = YANGDynClass(base=rstp.rstp, is_container='container', presence=False, yang_name="rstp", rest_name="rstp", parent=self, choice=(u'spanning-tree-mode', u'rstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) self.__mstp = YANGDynClass(base=mstp.mstp, is_container='container', presence=False, yang_name="mstp", rest_name="mstp", parent=self, choice=(u'spanning-tree-mode', u'mstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) self.__rpvstp = YANGDynClass(base=YANGListType("vlan_id",rpvstp.rpvstp, yang_name="rpvstp", rest_name="rpvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="rpvstp", rest_name="rpvstp", parent=self, choice=(u'spanning-tree-mode', u'rpvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True) self.__stp_mode = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'none': {'value': 1}, u'rstp': {'value': 3}, u'mstp': {'value': 4}, u'rpvstp': {'value': 6}, u'pvstp': {'value': 5}, u'stp': {'value': 2}},), is_leaf=True, yang_name="stp-mode", rest_name="stp-mode", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='stp-type', is_config=True) self.__pvstp = YANGDynClass(base=YANGListType("vlan_id",pvstp.pvstp, yang_name="pvstp", rest_name="pvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="pvstp", rest_name="pvstp", parent=self, choice=(u'spanning-tree-mode', u'pvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True) self.__stp = YANGDynClass(base=stp.stp, is_container='container', presence=False, yang_name="stp", rest_name="stp", parent=self, choice=(u'spanning-tree-mode', u'stp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', 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'brocade_xstp_ext_rpc', u'get-stp-brief-info', u'output', u'spanning-tree-info'] 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'get-stp-brief-info', u'output', u'spanning-tree-info'] def _get_stp_mode(self): """ Getter method for stp_mode, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/stp_mode (stp-type) YANG Description: Type of the spanning tree protocol configured on this switch """ return self.__stp_mode def _set_stp_mode(self, v, load=False): """ Setter method for stp_mode, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/stp_mode (stp-type) If this variable is read-only (config: false) in the source YANG file, then _set_stp_mode is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_stp_mode() directly. YANG Description: Type of the spanning tree protocol configured on this switch """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'none': {'value': 1}, u'rstp': {'value': 3}, u'mstp': {'value': 4}, u'rpvstp': {'value': 6}, u'pvstp': {'value': 5}, u'stp': {'value': 2}},), is_leaf=True, yang_name="stp-mode", rest_name="stp-mode", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='stp-type', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """stp_mode must be of a type compatible with stp-type""", 'defined-type': "brocade-xstp-ext:stp-type", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'none': {'value': 1}, u'rstp': {'value': 3}, u'mstp': {'value': 4}, u'rpvstp': {'value': 6}, u'pvstp': {'value': 5}, u'stp': {'value': 2}},), is_leaf=True, yang_name="stp-mode", rest_name="stp-mode", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='stp-type', is_config=True)""", }) self.__stp_mode = t if hasattr(self, '_set'): self._set() def _unset_stp_mode(self): self.__stp_mode = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'none': {'value': 1}, u'rstp': {'value': 3}, u'mstp': {'value': 4}, u'rpvstp': {'value': 6}, u'pvstp': {'value': 5}, u'stp': {'value': 2}},), is_leaf=True, yang_name="stp-mode", rest_name="stp-mode", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='stp-type', is_config=True) def _get_stp(self): """ Getter method for stp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/stp (container) """ return self.__stp def _set_stp(self, v, load=False): """ Setter method for stp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/stp (container) If this variable is read-only (config: false) in the source YANG file, then _set_stp is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_stp() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=stp.stp, is_container='container', presence=False, yang_name="stp", rest_name="stp", parent=self, choice=(u'spanning-tree-mode', u'stp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """stp must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=stp.stp, is_container='container', presence=False, yang_name="stp", rest_name="stp", parent=self, choice=(u'spanning-tree-mode', u'stp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True)""", }) self.__stp = t if hasattr(self, '_set'): self._set() def _unset_stp(self): self.__stp = YANGDynClass(base=stp.stp, is_container='container', presence=False, yang_name="stp", rest_name="stp", parent=self, choice=(u'spanning-tree-mode', u'stp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) def _get_rstp(self): """ Getter method for rstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/rstp (container) """ return self.__rstp def _set_rstp(self, v, load=False): """ Setter method for rstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/rstp (container) If this variable is read-only (config: false) in the source YANG file, then _set_rstp is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_rstp() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=rstp.rstp, is_container='container', presence=False, yang_name="rstp", rest_name="rstp", parent=self, choice=(u'spanning-tree-mode', u'rstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """rstp must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=rstp.rstp, is_container='container', presence=False, yang_name="rstp", rest_name="rstp", parent=self, choice=(u'spanning-tree-mode', u'rstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True)""", }) self.__rstp = t if hasattr(self, '_set'): self._set() def _unset_rstp(self): self.__rstp = YANGDynClass(base=rstp.rstp, is_container='container', presence=False, yang_name="rstp", rest_name="rstp", parent=self, choice=(u'spanning-tree-mode', u'rstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) def _get_mstp(self): """ Getter method for mstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/mstp (container) YANG Description: CIST information """ return self.__mstp def _set_mstp(self, v, load=False): """ Setter method for mstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/mstp (container) If this variable is read-only (config: false) in the source YANG file, then _set_mstp is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_mstp() directly. YANG Description: CIST information """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=mstp.mstp, is_container='container', presence=False, yang_name="mstp", rest_name="mstp", parent=self, choice=(u'spanning-tree-mode', u'mstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """mstp must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=mstp.mstp, is_container='container', presence=False, yang_name="mstp", rest_name="mstp", parent=self, choice=(u'spanning-tree-mode', u'mstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True)""", }) self.__mstp = t if hasattr(self, '_set'): self._set() def _unset_mstp(self): self.__mstp = YANGDynClass(base=mstp.mstp, is_container='container', presence=False, yang_name="mstp", rest_name="mstp", parent=self, choice=(u'spanning-tree-mode', u'mstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='container', is_config=True) def _get_pvstp(self): """ Getter method for pvstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/pvstp (list) YANG Description: PVST instance information """ return self.__pvstp def _set_pvstp(self, v, load=False): """ Setter method for pvstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/pvstp (list) If this variable is read-only (config: false) in the source YANG file, then _set_pvstp is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_pvstp() directly. YANG Description: PVST instance information """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=YANGListType("vlan_id",pvstp.pvstp, yang_name="pvstp", rest_name="pvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="pvstp", rest_name="pvstp", parent=self, choice=(u'spanning-tree-mode', u'pvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """pvstp must be of a type compatible with list""", 'defined-type': "list", 'generated-type': """YANGDynClass(base=YANGListType("vlan_id",pvstp.pvstp, yang_name="pvstp", rest_name="pvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="pvstp", rest_name="pvstp", parent=self, choice=(u'spanning-tree-mode', u'pvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True)""", }) self.__pvstp = t if hasattr(self, '_set'): self._set() def _unset_pvstp(self): self.__pvstp = YANGDynClass(base=YANGListType("vlan_id",pvstp.pvstp, yang_name="pvstp", rest_name="pvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="pvstp", rest_name="pvstp", parent=self, choice=(u'spanning-tree-mode', u'pvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True) def _get_rpvstp(self): """ Getter method for rpvstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/rpvstp (list) YANG Description: RPVST instance information """ return self.__rpvstp def _set_rpvstp(self, v, load=False): """ Setter method for rpvstp, mapped from YANG variable /brocade_xstp_ext_rpc/get_stp_brief_info/output/spanning_tree_info/rpvstp (list) If this variable is read-only (config: false) in the source YANG file, then _set_rpvstp is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_rpvstp() directly. YANG Description: RPVST instance information """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=YANGListType("vlan_id",rpvstp.rpvstp, yang_name="rpvstp", rest_name="rpvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="rpvstp", rest_name="rpvstp", parent=self, choice=(u'spanning-tree-mode', u'rpvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """rpvstp must be of a type compatible with list""", 'defined-type': "list", 'generated-type': """YANGDynClass(base=YANGListType("vlan_id",rpvstp.rpvstp, yang_name="rpvstp", rest_name="rpvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="rpvstp", rest_name="rpvstp", parent=self, choice=(u'spanning-tree-mode', u'rpvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True)""", }) self.__rpvstp = t if hasattr(self, '_set'): self._set() def _unset_rpvstp(self): self.__rpvstp = YANGDynClass(base=YANGListType("vlan_id",rpvstp.rpvstp, yang_name="rpvstp", rest_name="rpvstp", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='vlan-id', extensions=None, choice=False), is_container='list', yang_name="rpvstp", rest_name="rpvstp", parent=self, choice=(u'spanning-tree-mode', u'rpvstp'), path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions=None, namespace='urn:brocade.com:mgmt:brocade-xstp-ext', defining_module='brocade-xstp-ext', yang_type='list', is_config=True) stp_mode = __builtin__.property(_get_stp_mode, _set_stp_mode) stp = __builtin__.property(_get_stp, _set_stp) rstp = __builtin__.property(_get_rstp, _set_rstp) mstp = __builtin__.property(_get_mstp, _set_mstp) pvstp = __builtin__.property(_get_pvstp, _set_pvstp) rpvstp = __builtin__.property(_get_rpvstp, _set_rpvstp) __choices__ = {u'spanning-tree-mode': {u'pvstp': [u'pvstp'], u'mstp': [u'mstp'], u'stp': [u'stp'], u'rstp': [u'rstp'], u'rpvstp': [u'rpvstp']}} _pyangbind_elements = {'stp_mode': stp_mode, 'stp': stp, 'rstp': rstp, 'mstp': mstp, 'pvstp': pvstp, 'rpvstp': rpvstp, }

69.034268

630

0.719043

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22,160

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0.062722

0.051424

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0.037975

0.842629

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0.298969

0

null

0

1

0

null

0

6

b80e1741c139aa8cd0d394288c8be26e9f3580de

57

py

Python

examples/example2.py

rsoaresp/pydep

bcd391d7fa538431e364f611e6cf652d5baa8556

[ "MIT" ]

null

examples/example2.py

rsoaresp/pydep

bcd391d7fa538431e364f611e6cf652d5baa8556

[ "MIT" ]

null

examples/example2.py

rsoaresp/pydep

bcd391d7fa538431e364f611e6cf652d5baa8556

[ "MIT" ]

null

from examples.example1 import f def s(): print(f(2))

14.25

31

0.666667

10

57

3.8

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0.043478

0.192982

57

4

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14.25

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0.333333

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null

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null

0

1

0

1

0

1

0

6

62a78e4aa886261faef7ec9a6f0a0e6f4ded0139

76

py

Python

py_tdlib/constructors/inline_keyboard_button_type_buy.py

Mr-TelegramBot/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

24

2018-10-05T13:04:30.000Z

2020-05-12T08:45:34.000Z

py_tdlib/constructors/inline_keyboard_button_type_buy.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

3

2019-06-26T07:20:20.000Z

2021-05-24T13:06:56.000Z

py_tdlib/constructors/inline_keyboard_button_type_buy.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

5

2018-10-05T14:29:28.000Z

2020-08-11T15:04:10.000Z

from ..factory import Type class inlineKeyboardButtonTypeBuy(Type): pass

12.666667

40

0.802632

8

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7.625

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true

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null

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1

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1

0

6

62dc6e227ac884df6cccce08d76ba69cdd0182bc

30,353

py

Python

examples/servicenet/plotresults.py

oascigil/icarus_edge_comp

b7bb9f9b8d0f27b4b01469dcba9cfc0c4949d64b

[ "MIT" ]

5

2021-03-20T09:22:55.000Z

2021-12-20T17:01:33.000Z

examples/servicenet/plotresults.py

oascigil/icarus_edge_comp

b7bb9f9b8d0f27b4b01469dcba9cfc0c4949d64b

[ "MIT" ]

null

examples/servicenet/plotresults.py

oascigil/icarus_edge_comp

b7bb9f9b8d0f27b4b01469dcba9cfc0c4949d64b

[ "MIT" ]

1

2020-01-02T12:39:54.000Z

# -*- coding: utf-8 -*- """Plot results read from a result set """ from __future__ import division import os import argparse import collections import logging import numpy as np import matplotlib as mpl mpl.use('Agg') import matplotlib.pyplot as plt from icarus.util import Settings, Tree, config_logging, step_cdf from icarus.tools import means_confidence_interval from icarus.results import plot_lines, plot_bar_chart from icarus.registry import RESULTS_READER # Logger object logger = logging.getLogger('plot') # These lines prevent insertion of Type 3 fonts in figures # Publishers don't want them plt.rcParams['ps.useafm'] = True plt.rcParams['pdf.use14corefonts'] = True # If True text is interpreted as LaTeX, e.g. underscore are interpreted as # subscript. If False, text is interpreted literally plt.rcParams['text.usetex'] = False # Aspect ratio of the output figures plt.rcParams['figure.figsize'] = 8, 5 # Size of font in legends LEGEND_SIZE = 14 # Line width in pixels LINE_WIDTH = 1.5 # Plot PLOT_EMPTY_GRAPHS = True # This dict maps strategy names to the style of the line to be used in the plots # Off-path strategies: solid lines # On-path strategies: dashed lines # No-cache: dotted line STRATEGY_STYLE = { 'HR_SYMM': 'b-o', 'HR_ASYMM': 'g-D', 'HR_MULTICAST': 'm-^', 'HR_HYBRID_AM': 'c-s', 'HR_HYBRID_SM': 'r-v', 'LCE': 'b--p', 'LCD': 'g-->', 'CL4M': 'g-->', 'PROB_CACHE': 'c--<', 'RAND_CHOICE': 'r--<', 'RAND_BERNOULLI': 'g--*', 'NO_CACHE': 'k:o', 'OPTIMAL': 'k-o' } # This dict maps name of strategies to names to be displayed in the legend STRATEGY_LEGEND = { 'LCE': 'LCE', 'LCD': 'LCD', 'HR_SYMM': 'HR Symm', 'HR_ASYMM': 'HR Asymm', 'HR_MULTICAST': 'HR Multicast', 'HR_HYBRID_AM': 'HR Hybrid AM', 'HR_HYBRID_SM': 'HR Hybrid SM', 'CL4M': 'CL4M', 'PROB_CACHE': 'ProbCache', 'RAND_CHOICE': 'Random (choice)', 'RAND_BERNOULLI': 'Random (Bernoulli)', 'NO_CACHE': 'No caching', 'OPTIMAL': 'Optimal' } # Color and hatch styles for bar charts of cache hit ratio and link load vs topology STRATEGY_BAR_COLOR = { 'LCE': 'k', 'LCD': '0.4', 'NO_CACHE': '0.5', 'HR_ASYMM': '0.6', 'HR_SYMM': '0.7' } STRATEGY_BAR_HATCH = { 'LCE': None, 'LCD': '//', 'NO_CACHE': 'x', 'HR_ASYMM': '+', 'HR_SYMM': '\\' } def plot_cache_hits_vs_alpha(resultset, topology, cache_size, alpha_range, strategies, plotdir): if 'NO_CACHE' in strategies: strategies.remove('NO_CACHE') desc = {} desc['title'] = 'Cache hit ratio: T=%s C=%s' % (topology, cache_size) desc['ylabel'] = 'Cache hit ratio' desc['xlabel'] = u'Content distribution \u03b1' desc['xparam'] = ('workload', 'alpha') desc['xvals'] = alpha_range desc['filter'] = {'topology': {'name': topology}, 'cache_placement': {'network_cache': cache_size}} desc['ymetrics'] = [('CACHE_HIT_RATIO', 'MEAN')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['errorbar'] = True desc['legend_loc'] = 'upper left' desc['line_style'] = STRATEGY_STYLE desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_lines(resultset, desc, 'CACHE_HIT_RATIO_T=%s@C=%s.pdf' % (topology, cache_size), plotdir) def plot_cache_hits_vs_cache_size(resultset, topology, alpha, cache_size_range, strategies, plotdir): desc = {} if 'NO_CACHE' in strategies: strategies.remove('NO_CACHE') desc['title'] = 'Cache hit ratio: T=%s A=%s' % (topology, alpha) desc['xlabel'] = u'Cache to population ratio' desc['ylabel'] = 'Cache hit ratio' desc['xscale'] = 'log' desc['xparam'] = ('cache_placement','network_cache') desc['xvals'] = cache_size_range desc['filter'] = {'topology': {'name': topology}, 'workload': {'name': 'STATIONARY', 'alpha': alpha}} desc['ymetrics'] = [('CACHE_HIT_RATIO', 'MEAN')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['errorbar'] = True desc['legend_loc'] = 'upper left' desc['line_style'] = STRATEGY_STYLE desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_lines(resultset, desc,'CACHE_HIT_RATIO_T=%s@A=%s.pdf' % (topology, alpha), plotdir) def plot_link_load_vs_alpha(resultset, topology, cache_size, alpha_range, strategies, plotdir): desc = {} desc['title'] = 'Internal link load: T=%s C=%s' % (topology, cache_size) desc['xlabel'] = u'Content distribution \u03b1' desc['ylabel'] = 'Internal link load' desc['xparam'] = ('workload', 'alpha') desc['xvals'] = alpha_range desc['filter'] = {'topology': {'name': topology}, 'cache_placement': {'network_cache': cache_size}} desc['ymetrics'] = [('LINK_LOAD', 'MEAN_INTERNAL')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['errorbar'] = True desc['legend_loc'] = 'upper right' desc['line_style'] = STRATEGY_STYLE desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_lines(resultset, desc, 'LINK_LOAD_INTERNAL_T=%s@C=%s.pdf' % (topology, cache_size), plotdir) def plot_link_load_vs_cache_size(resultset, topology, alpha, cache_size_range, strategies, plotdir): desc = {} desc['title'] = 'Internal link load: T=%s A=%s' % (topology, alpha) desc['xlabel'] = 'Cache to population ratio' desc['ylabel'] = 'Internal link load' desc['xscale'] = 'log' desc['xparam'] = ('cache_placement','network_cache') desc['xvals'] = cache_size_range desc['filter'] = {'topology': {'name': topology}, 'workload': {'name': 'stationary', 'alpha': alpha}} desc['ymetrics'] = [('LINK_LOAD', 'MEAN_INTERNAL')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['errorbar'] = True desc['legend_loc'] = 'upper right' desc['line_style'] = STRATEGY_STYLE desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_lines(resultset, desc, 'LINK_LOAD_INTERNAL_T=%s@A=%s.pdf' % (topology, alpha), plotdir) def plot_latency_vs_alpha(resultset, topology, cache_size, alpha_range, strategies, plotdir): desc = {} desc['title'] = 'Latency: T=%s C=%s' % (topology, cache_size) desc['xlabel'] = u'Content distribution \u03b1' desc['ylabel'] = 'Latency (ms)' desc['xparam'] = ('workload', 'alpha') desc['xvals'] = alpha_range desc['filter'] = {'topology': {'name': topology}, 'cache_placement': {'network_cache': cache_size}} desc['ymetrics'] = [('LATENCY', 'MEAN')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['errorbar'] = True desc['legend_loc'] = 'upper right' desc['line_style'] = STRATEGY_STYLE desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_lines(resultset, desc, 'LATENCY_T=%s@C=%s.pdf' % (topology, cache_size), plotdir) def plot_latency_vs_cache_size(resultset, topology, alpha, cache_size_range, strategies, plotdir): desc = {} desc['title'] = 'Latency: T=%s A=%s' % (topology, alpha) desc['xlabel'] = 'Cache to population ratio' desc['ylabel'] = 'Latency' desc['xscale'] = 'log' desc['xparam'] = ('cache_placement','network_cache') desc['xvals'] = cache_size_range desc['filter'] = {'topology': {'name': topology}, 'workload': {'name': 'STATIONARY', 'alpha': alpha}} desc['ymetrics'] = [('LATENCY', 'MEAN')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['metric'] = ('LATENCY', 'MEAN') desc['errorbar'] = True desc['legend_loc'] = 'upper right' desc['line_style'] = STRATEGY_STYLE desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_lines(resultset, desc, 'LATENCY_T=%s@A=%s.pdf' % (topology, alpha), plotdir) def plot_cache_hits_vs_topology(resultset, alpha, cache_size, topology_range, strategies, plotdir): """ Plot bar graphs of cache hit ratio for specific values of alpha and cache size for various topologies. The objective here is to show that our algorithms works well on all topologies considered """ if 'NO_CACHE' in strategies: strategies.remove('NO_CACHE') desc = {} desc['title'] = 'Cache hit ratio: A=%s C=%s' % (alpha, cache_size) desc['ylabel'] = 'Cache hit ratio' desc['xparam'] = ('topology', 'name') desc['xvals'] = topology_range desc['filter'] = {'cache_placement': {'network_cache': cache_size}, 'workload': {'name': 'STATIONARY', 'alpha': alpha}} desc['ymetrics'] = [('CACHE_HIT_RATIO', 'MEAN')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['errorbar'] = True desc['legend_loc'] = 'lower right' desc['bar_color'] = STRATEGY_BAR_COLOR desc['bar_hatch'] = STRATEGY_BAR_HATCH desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_bar_chart(resultset, desc, 'CACHE_HIT_RATIO_A=%s_C=%s.pdf' % (alpha, cache_size), plotdir) def plot_link_load_vs_topology(resultset, alpha, cache_size, topology_range, strategies, plotdir): """ Plot bar graphs of link load for specific values of alpha and cache size for various topologies. The objective here is to show that our algorithms works well on all topologies considered """ desc = {} desc['title'] = 'Internal link load: A=%s C=%s' % (alpha, cache_size) desc['ylabel'] = 'Internal link load' desc['xparam'] = ('topology', 'name') desc['xvals'] = topology_range desc['filter'] = {'cache_placement': {'network_cache': cache_size}, 'workload': {'name': 'STATIONARY', 'alpha': alpha}} desc['ymetrics'] = [('LINK_LOAD', 'MEAN_INTERNAL')]*len(strategies) desc['ycondnames'] = [('strategy', 'name')]*len(strategies) desc['ycondvals'] = strategies desc['errorbar'] = True desc['legend_loc'] = 'lower right' desc['bar_color'] = STRATEGY_BAR_COLOR desc['bar_hatch'] = STRATEGY_BAR_HATCH desc['legend'] = STRATEGY_LEGEND desc['plotempty'] = PLOT_EMPTY_GRAPHS plot_bar_chart(resultset, desc, 'LINK_LOAD_INTERNAL_A=%s_C=%s.pdf' % (alpha, cache_size), plotdir) def searchDictMultipleCat(lst, category_list, attr_value_pairs, num_pairs, collector, subtype): """ Search the resultset list for a particular [category, attribute, value] parameter such as ['strategy', 'extra_quota', 3]. attr_value_pairs include the key-value pairs. and once such a key is found, extract the result for a collector, subtype such as ['CACHE_HIT_RATIO', 'MEAN'] Returns the result if found in the dictionary lst; otherwise returns None """ result = None for l in lst: num_match = 0 for key, val in l[0].items(): #print key + '-and-' + category + '-\n' if key in category_list: if (isinstance(val, dict)): for key1, val1 in val.items(): for key2, val2 in attr_value_pairs.items(): if key1 == key2 and val1 == val2: num_match = num_match + 1 if num_match == num_pairs: result = l[1] break else: print 'Something is wrong with the search for attr-value pairs\n' return None if result is not None: break if result is None: print 'Error searched attribute, value pairs:\n' for k, v in attr_value_pairs.items(): print '[ ' + repr(k) + ' , ' + repr(v) + ' ] ' print 'is not found, returning none\n' return None found = None for key, val in result.items(): if key == collector: for key1, val1 in val.items(): if key1 == subtype: found = val1 break if found is not None: break if found is None: print 'Error searched collector, subtype ' + repr(collector) + ',' + repr(subtype) + 'is not found\n' return found def searchDictMultipleCat1(lst, category_list, attr_value_list, num_pairs, collector, subtype): """ Search the resultset list for a particular [category, attribute, value] parameter such as ['strategy', 'extra_quota', 3]. attr_value_pairs include the key-value pairs. and once such a key is found, extract the result for a collector, subtype such as ['CACHE_HIT_RATIO', 'MEAN'] Returns the result if found in the dictionary lst; otherwise returns None """ result = None for l in lst: num_match = 0 for key, val in l[0].items(): #print key + '-and-' + category + '-\n' if key in category_list: if (isinstance(val, dict)): for key1, val1 in val.items(): for arr in attr_value_list: key2 = arr[0] val2 = arr[1] if key1 == key2 and val1 == val2: num_match = num_match + 1 if num_match == num_pairs: result = l[1] break else: print 'Something is wrong with the search for attr-value pairs\n' return None if result is not None: break if result is None: print 'Error searched attribute, value pairs:\n' for arr in attr_value_list: k = arr[0] v = arr[1] print '[ ' + repr(k) + ' , ' + repr(v) + ' ] ' print 'is not found, returning none\n' return None found = None for key, val in result.items(): if key == collector: for key1, val1 in val.items(): if key1 == subtype: found = val1 break if found is not None: break if found is None: print 'Error searched collector, subtype ' + repr(collector) + ',' + repr(subtype) + 'is not found\n' return found def searchDict(lst, category, attr_value_pairs, num_pairs, collector, subtype): """ Search the resultset list for a particular [category, attribute, value] parameter such as ['strategy', 'extra_quota', 3]. attr_value_pairs include the key-value pairs. and once such a key is found, extract the result for a collector, subtype such as ['CACHE_HIT_RATIO', 'MEAN'] Returns the result if found in the dictionary lst; otherwise returns None """ result = None for l in lst: for key, val in l[0].items(): #print key + '-and-' + category + '-\n' if key == category: if (isinstance(val, dict)): num_match = 0 for key1, val1 in val.items(): for key2, val2 in attr_value_pairs.items(): if key1 == key2 and val1 == val2: num_match = num_match + 1 if num_match == num_pairs: result = l[1] break else: print 'Something is wrong with the search for attr-value pairs\n' return None if result is not None: break if result is None: print 'Error searched attribute, value pairs:\n' for k, v in attr_value_pairs.items(): print '[ ' + repr(k) + ' , ' + repr(v) + ' ] ' print 'is not found, returning none\n' return None found = None for key, val in result.items(): if key == collector: for key1, val1 in val.items(): if key1 == subtype: found = val1 break if found is not None: break if found is None: print 'Error searched collector, subtype ' + repr(collector) + ',' + repr(subtype) + 'is not found\n' return found def print_lru_probability_results(lst): probs = [0.1, 0.25, 0.50, 0.75, 1.0] strategies = ['LRU'] for strategy in strategies: for p in probs: filename = 'sat_' + str(strategy) + '_' + str(p) f = open(filename, 'w') f.write('# Sat. rate for LRU over time\n') f.write('#\n') f.write('# Time Sat. Rate\n') sat_times = searchDict(lst, 'strategy', {'name': strategy, 'p' : p}, 2, 'LATENCY', 'SAT_TIMES') for k in sorted(sat_times): s = str(k[0][0]) + "\t" + str(k[1]) + "\n" f.write(s) f.close() for strategy in strategies: for p in probs: filename = 'idle_' + str(strategy) + '_' + str(p) f = open(filename, 'w') f.write('# Idle time of strategies over time\n') f.write('#\n') f.write('# Time Idle percentage\n') idle_times = searchDict(lst, 'strategy', {'name': strategy, 'p' : p}, 2, 'LATENCY', 'IDLE_TIMES') for k in sorted(idle_times): s = str(k[0][0]) + "\t" + str(k[1]) + "\n" f.write(s) f.close() def print_strategies_performance(lst): strategies = ['SDF', 'HYBRID', 'MFU', 'COORDINATED'] #strategies = ['HYBRID'] service_budget = 500 alpha = 0.5 #0.75 replacement_interval = 30.0 n_services = 1000 # Print Sat. rates: for strategy in strategies: filename = 'sat_' + str(strategy) f = open(filename, 'w') f.write('# Sat. rate over time\n') f.write('#\n') f.write('# Time Sat. Rate\n') sat_times = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : service_budget, 'alpha' : alpha}, 3, 'LATENCY', 'SAT_TIMES') for k in sorted(sat_times): s = str(k[0][0]) + "\t" + str(k[1]) + "\n" f.write(s) f.close() # Print Idle times: for strategy in strategies: filename = 'idle_' + str(strategy) f = open(filename, 'w') f.write('# Idle time of strategies over time\n') f.write('#\n') f.write('# Time Idle percentage\n') idle_times = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : service_budget, 'alpha' : alpha}, 3, 'LATENCY', 'IDLE_TIMES') for k in sorted(idle_times): s = str(k[0][0]) + "\t" + str(k[1]) + "\n" f.write(s) f.close() # Print per-service Sat. rates: for strategy in strategies: filename = 'sat_service_' + str(strategy) f = open(filename, 'w') f.write('# Per-service Sat. rate over time\n') f.write('#\n') f.write('# Time Sat. Rate\n') sat_services = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : service_budget, 'alpha' : alpha}, 3, 'LATENCY', 'PER_SERVICE_SATISFACTION') #f.write(str(sat_services)) for indx in range(1, n_services): s = str(indx) + "\t" + str(sat_services[indx]) + "\n" f.write(s) f.close() def print_scheduling_experiments(lst): strategies = ['SDF', 'HYBRID', 'MFU'] schedule_policies = ['EDF', 'FIFO'] service_budget = 500 alpha = 0.75 replacement_interval = 30.0 # Print Sat. rates: for strategy in strategies: for policy in schedule_policies: filename = 'sat_' + str(strategy) + '_' + str(policy) f = open(filename, 'w') f.write('# Sat. rate over time\n') f.write('#\n') f.write('# Time Sat. Rate\n') sat_times = searchDictMultipleCat1(lst, ['strategy', 'computation_placement', 'workload', 'sched_policy'], [['name', strategy], ['service_budget', service_budget], ['alpha', alpha], ['name', policy]], 4, 'LATENCY', 'SAT_TIMES') for k in sorted(sat_times): s = str(k[0][0]) + "\t" + str(k[1]) + "\n" f.write(s) f.close() # Print idle times: for strategy in strategies: for policy in schedule_policies: filename = 'idle_' + str(strategy) + '_' + str(policy) f = open(filename, 'w') f.write('# Idle times over time\n') f.write('#\n') f.write('# Time Idle percentage\n') idle_times = searchDictMultipleCat1(lst, ['strategy', 'computation_placement', 'workload', 'sched_policy'], [['name', strategy], ['service_budget', service_budget], ['alpha', alpha], ['name', policy]], 4, 'LATENCY', 'IDLE_TIMES') for k in sorted(idle_times): s = str(k[0][0]) + "\t" + str((1.0*k[1])) + "\n" f.write(s) f.close() def print_zipf_experiment(lst): strategies = ['SDF', 'HYBRID', 'MFU'] alphas = [0.1, 0.25, 0.50, 0.75, 1.0] replacement_interval = 30.0 service_budget = 500 # Print Sat. rates: for strategy in strategies: for alpha in alphas: filename = 'sat_' + str(strategy) + '_' + str(alpha) f = open(filename, 'w') f.write('# Sat. rate over time\n') f.write('#\n') f.write('# Time Sat. Rate\n') sat_times = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : service_budget, 'alpha' : alpha}, 3, 'LATENCY', 'SAT_TIMES') for k in sorted(sat_times): s = str(k[0][0]) + "\t" + str(k[1]) + "\n" f.write(s) f.close() # Print Idle times: for strategy in strategies: for alpha in alphas: filename = 'idle_' + str(strategy) + '_' + str(alpha) f = open(filename, 'w') f.write('# Idle times over time\n') f.write('#\n') f.write('# Time Idle percentage\n') idle_times = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : service_budget, 'alpha' : alpha}, 3, 'LATENCY', 'IDLE_TIMES') for k in sorted(sat_times): s = str(k[0][0]) + "\t" + str((1.0*k[1])) + "\n" f.write(s) f.close() def print_budget_experiment(lst): strategies = ['COORDINATED', 'SDF', 'HYBRID', 'MFU'] TREE_DEPTH = 3 BRANCH_FACTOR = 2 NUM_CORES = 50 NUM_NODES = int(pow(BRANCH_FACTOR, TREE_DEPTH+1) -1) alpha = 0.75 replacement_interval = 30.0 N_SERVICES = 1000 budgets = [NUM_CORES*NUM_NODES*1, NUM_CORES*NUM_NODES*3/2, NUM_CORES*NUM_NODES*2, NUM_CORES*NUM_NODES*5/2, NUM_CORES*NUM_NODES*3] # Print Sat. rates: for strategy in strategies: for budget in budgets: filename = 'Results/VM_Budget_Results/' + 'sat_' + str(strategy) + '_' + str(budget) f = open(filename, 'w') f.write('# Sat. rate over time\n') f.write('#\n') f.write('# Time Sat. Rate\n') sat_times = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : budget, 'alpha' : alpha}, 3, 'LATENCY', 'SAT_TIMES') for k in sorted(sat_times): s = str(k[0][0]) + "\t" + str(k[1]) + "\n" f.write(s) f.close() # Print Idle times: for strategy in strategies: for budget in budgets: filename = 'Results/VM_Budget_Results/' + 'idle_' + str(strategy) + '_' + str(budget) f = open(filename, 'w') f.write('# Idle times over time\n') f.write('#\n') f.write('# Time Idle percentage\n') idle_times = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : budget, 'alpha' : alpha}, 3, 'LATENCY', 'IDLE_TIMES') for k in sorted(idle_times): s = str(k[0][0]) + "\t" + str((1.0*k[1])) + "\n" f.write(s) f.close() # Print Overhead times: for strategy in strategies: for budget in budgets: filename = 'Results/VM_Budget_Results/' + 'overhead_' + str(strategy) + '_' + str(budget) f = open(filename, 'w') f.write('# VM instantiation overhead over time\n') f.write('#\n') f.write('# Time Overhead\n') overhead_times = searchDictMultipleCat(lst, ['strategy', 'computation_placement', 'workload'], {'name' : strategy, 'service_budget' : budget, 'alpha' : alpha}, 3, 'LATENCY', 'INSTANTIATION_OVERHEAD') for k in sorted(overhead_times): s = str(k[0][0]) + "\t" + str((1.0*k[1])) + "\n" f.write(s) f.close() def printTree(tree, d = 0): if (tree == None or len(tree) == 0): print "\t" * d, "-" else: for key, val in tree.items(): if (isinstance(val, dict)): print "\t" * d, key printTree(val, d+1) else: print "\t" * d, key, str(val) def run(config, results, plotdir): """Run the plot script Parameters ---------- config : str The path of the configuration file results : str The file storing the experiment results plotdir : str The directory into which graphs will be saved """ resultset = RESULTS_READER['PICKLE'](results) #Onur: added this BEGIN lst = resultset.dump() for l in lst: print 'PARAMETERS:\n' printTree(l[0]) print 'RESULTS:\n' printTree(l[1]) #print_lru_probability_results(lst) #print_strategies_performance(lst) print_budget_experiment(lst) #print_scheduling_experiments(lst) #print_zipf_experiment(lst) # /home/uceeoas/.local/bin/python ./plotresults.py --results results.pickle --output ./ config.py """ settings = Settings() settings.read_from(config) config_logging(settings.LOG_LEVEL) resultset = RESULTS_READER[settings.RESULTS_FORMAT](results) # Create dir if not existsing if not os.path.exists(plotdir): os.makedirs(plotdir) # Parse params from settings topologies = settings.TOPOLOGIES cache_sizes = settings.NETWORK_CACHE alphas = settings.ALPHA strategies = settings.STRATEGIES # Plot graphs for topology in topologies: for cache_size in cache_sizes: logger.info('Plotting cache hit ratio for topology %s and cache size %s vs alpha' % (topology, str(cache_size))) plot_cache_hits_vs_alpha(resultset, topology, cache_size, alphas, strategies, plotdir) logger.info('Plotting link load for topology %s vs cache size %s' % (topology, str(cache_size))) plot_link_load_vs_alpha(resultset, topology, cache_size, alphas, strategies, plotdir) logger.info('Plotting latency for topology %s vs cache size %s' % (topology, str(cache_size))) plot_latency_vs_alpha(resultset, topology, cache_size, alphas, strategies, plotdir) for topology in topologies: for alpha in alphas: logger.info('Plotting cache hit ratio for topology %s and alpha %s vs cache size' % (topology, str(alpha))) plot_cache_hits_vs_cache_size(resultset, topology, alpha, cache_sizes, strategies, plotdir) logger.info('Plotting link load for topology %s and alpha %s vs cache size' % (topology, str(alpha))) plot_link_load_vs_cache_size(resultset, topology, alpha, cache_sizes, strategies, plotdir) logger.info('Plotting latency for topology %s and alpha %s vs cache size' % (topology, str(alpha))) plot_latency_vs_cache_size(resultset, topology, alpha, cache_sizes, strategies, plotdir) for cache_size in cache_sizes: for alpha in alphas: logger.info('Plotting cache hit ratio for cache size %s vs alpha %s against topologies' % (str(cache_size), str(alpha))) plot_cache_hits_vs_topology(resultset, alpha, cache_size, topologies, strategies, plotdir) logger.info('Plotting link load for cache size %s vs alpha %s against topologies' % (str(cache_size), str(alpha))) plot_link_load_vs_topology(resultset, alpha, cache_size, topologies, strategies, plotdir) logger.info('Exit. Plots were saved in directory %s' % os.path.abspath(plotdir)) """ def main(): parser = argparse.ArgumentParser(__doc__) parser.add_argument("-r", "--results", dest="results", help='the results file', required=True) parser.add_argument("-o", "--output", dest="output", help='the output directory where plots will be saved', required=True) parser.add_argument("config", help="the configuration file") args = parser.parse_args() run(args.config, args.results, args.output) if __name__ == '__main__': main()

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Python

eoxserver/resources/coverages/migrations/0001_initial.py

kalxas/eoxserver

8073447d926f3833923bde7b7061e8a1658dee06

[ "OML" ]

25

2015-08-10T19:34:34.000Z

2021-02-05T08:28:01.000Z

eoxserver/resources/coverages/migrations/0001_initial.py

kalxas/eoxserver

8073447d926f3833923bde7b7061e8a1658dee06

[ "OML" ]

153

2015-01-20T08:35:49.000Z

2022-03-16T11:00:56.000Z

eoxserver/resources/coverages/migrations/0001_initial.py

kalxas/eoxserver

8073447d926f3833923bde7b7061e8a1658dee06

[ "OML" ]

10

2015-01-23T15:48:30.000Z

2021-01-21T15:41:18.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.11.3 on 2017-09-06 19:09 from __future__ import unicode_literals import django.contrib.gis.db.models.fields import django.core.validators from django.db import migrations, models import django.db.models.deletion import re class Migration(migrations.Migration): initial = True dependencies = [ ('backends', '0001_initial'), ] operations = [ migrations.CreateModel( name='AcquisitionStation', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='AcquisitionSubType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='AllowedValueRange', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('start', models.FloatField()), ('end', models.FloatField()), ], ), migrations.CreateModel( name='ArchivingCenter', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='ArrayDataItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('location', models.CharField(max_length=1024)), ('format', models.CharField(blank=True, max_length=64, null=True)), ('field_index', models.PositiveSmallIntegerField(default=0)), ('band_count', models.PositiveSmallIntegerField(default=1)), ('subdataset_type', models.CharField(blank=True, max_length=64, null=True)), ('subdataset_locator', models.CharField(blank=True, max_length=1024, null=True)), ('bands_interpretation', models.PositiveSmallIntegerField(choices=[(0, b'fields'), (1, b'dimension')], default=0)), ], ), migrations.CreateModel( name='Browse', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('location', models.CharField(max_length=1024)), ('format', models.CharField(blank=True, max_length=64, null=True)), ('style', models.CharField(blank=True, max_length=256, null=True)), ('coordinate_reference_system', models.TextField()), ('min_x', models.FloatField()), ('min_y', models.FloatField()), ('max_x', models.FloatField()), ('max_y', models.FloatField()), ('width', models.PositiveIntegerField()), ('height', models.PositiveIntegerField()), ], ), migrations.CreateModel( name='BrowseType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=256, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_]*$'), message=b'This field must contain a valid Name.')])), ('red_or_grey_expression', models.CharField(blank=True, max_length=512, null=True)), ('green_expression', models.CharField(blank=True, max_length=512, null=True)), ('blue_expression', models.CharField(blank=True, max_length=512, null=True)), ('alpha_expression', models.CharField(blank=True, max_length=512, null=True)), ], ), migrations.CreateModel( name='CollectionMetadata', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('product_type', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('doi', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('platform', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('platform_serial_identifier', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('instrument', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('sensor_type', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('composite_type', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('processing_level', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('orbit_type', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('spectral_range', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('wavelength', models.IntegerField(blank=True, db_index=True, null=True)), ('product_metadata_summary', models.TextField(blank=True, null=True)), ('coverage_metadata_summary', models.TextField(blank=True, null=True)), ], ), migrations.CreateModel( name='CollectionType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=512, unique=True, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_]*$'), message=b'This field must contain a valid Name.')])), ], ), migrations.CreateModel( name='CoverageMetadata', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ], ), migrations.CreateModel( name='CoverageType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=512, unique=True, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_]*$'), message=b'This field must contain a valid Name.')])), ], ), migrations.CreateModel( name='EOObject', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('identifier', models.CharField(max_length=256, unique=True, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_.-]*$'), message=b'This field must contain a valid NCName.')])), ('begin_time', models.DateTimeField(blank=True, null=True)), ('end_time', models.DateTimeField(blank=True, null=True)), ('footprint', django.contrib.gis.db.models.fields.GeometryField(blank=True, null=True, srid=4326)), ('inserted', models.DateTimeField(auto_now_add=True)), ('updated', models.DateTimeField(auto_now=True)), ], ), migrations.CreateModel( name='FieldType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('index', models.PositiveSmallIntegerField()), ('identifier', models.CharField(max_length=512, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_.-]*$'), message=b'This field must contain a valid NCName.')])), ('description', models.TextField(blank=True, null=True)), ('definition', models.CharField(blank=True, max_length=512, null=True)), ('unit_of_measure', models.CharField(blank=True, max_length=64, null=True)), ('wavelength', models.FloatField(blank=True, null=True)), ('significant_figures', models.PositiveSmallIntegerField(blank=True, null=True)), ('numbits', models.PositiveSmallIntegerField(blank=True, null=True)), ('signed', models.BooleanField(default=True)), ('is_float', models.BooleanField(default=False)), ('coverage_type', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='field_types', to='coverages.CoverageType')), ], options={ 'ordering': ('index',), }, ), migrations.CreateModel( name='Frame', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Grid', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=256, null=True, unique=True, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_]*$'), message=b'This field must contain a valid Name.')])), ('coordinate_reference_system', models.TextField()), ('axis_1_name', models.CharField(max_length=256)), ('axis_2_name', models.CharField(blank=True, max_length=256, null=True)), ('axis_3_name', models.CharField(blank=True, max_length=256, null=True)), ('axis_4_name', models.CharField(blank=True, max_length=256, null=True)), ('axis_1_type', models.SmallIntegerField(choices=[(0, b'spatial'), (1, b'elevation'), (2, b'temporal'), (3, b'other')])), ('axis_2_type', models.SmallIntegerField(blank=True, choices=[(0, b'spatial'), (1, b'elevation'), (2, b'temporal'), (3, b'other')], null=True)), ('axis_3_type', models.SmallIntegerField(blank=True, choices=[(0, b'spatial'), (1, b'elevation'), (2, b'temporal'), (3, b'other')], null=True)), ('axis_4_type', models.SmallIntegerField(blank=True, choices=[(0, b'spatial'), (1, b'elevation'), (2, b'temporal'), (3, b'other')], null=True)), ('axis_1_offset', models.CharField(blank=True, max_length=256, null=True)), ('axis_2_offset', models.CharField(blank=True, max_length=256, null=True)), ('axis_3_offset', models.CharField(blank=True, max_length=256, null=True)), ('axis_4_offset', models.CharField(blank=True, max_length=256, null=True)), ('resolution', models.PositiveIntegerField(blank=True, null=True)), ], ), migrations.CreateModel( name='Mask', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('location', models.CharField(max_length=1024)), ('format', models.CharField(blank=True, max_length=64, null=True)), ('geometry', django.contrib.gis.db.models.fields.GeometryField(blank=True, null=True, srid=4326)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='MaskType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=512, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_]*$'), message=b'This field must contain a valid Name.')])), ], ), migrations.CreateModel( name='MetaDataItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('location', models.CharField(max_length=1024)), ('format', models.CharField(blank=True, max_length=64, null=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='NilValue', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(max_length=512)), ('reason', models.CharField(choices=[(b'http://www.opengis.net/def/nil/OGC/0/inapplicable', b'Inapplicable (There is no value)'), (b'http://www.opengis.net/def/nil/OGC/0/missing', b'Missing'), (b'http://www.opengis.net/def/nil/OGC/0/template', b'Template (The value will be available later)'), (b'http://www.opengis.net/def/nil/OGC/0/unknown', b'Unknown'), (b'http://www.opengis.net/def/nil/OGC/0/withheld', b'Withheld (The value is not divulged)'), (b'http://www.opengis.net/def/nil/OGC/0/AboveDetectionRange', b'Above detection range'), (b'http://www.opengis.net/def/nil/OGC/0/BelowDetectionRange', b'Below detection range')], max_length=512)), ('field_types', models.ManyToManyField(blank=True, related_name='nil_values', to='coverages.FieldType')), ], ), migrations.CreateModel( name='OrbitNumber', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='ProcessingCenter', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='ProcessingMode', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='ProcessorName', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='ProductMetadata', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('parent_identifier', models.CharField(blank=True, db_index=True, max_length=256, null=True)), ('production_status', models.PositiveSmallIntegerField(blank=True, choices=[(0, b'ARCHIVED'), (1, b'ACQUIRED'), (2, b'CANCELLED')], db_index=True, null=True)), ('acquisition_type', models.PositiveSmallIntegerField(blank=True, choices=[(0, b'NOMINAL'), (1, b'CALIBRATION'), (2, b'OTHER')], db_index=True, null=True)), ('orbit_direction', models.PositiveSmallIntegerField(blank=True, choices=[(0, b'ASCENDING'), (1, b'DESCENDING')], db_index=True, null=True)), ('product_quality_status', models.PositiveSmallIntegerField(blank=True, choices=[(0, b'NOMINAL'), (1, b'DEGRAGED')], db_index=True, null=True)), ('creation_date', models.DateTimeField(blank=True, db_index=True, null=True)), ('modification_date', models.DateTimeField(blank=True, db_index=True, null=True)), ('processing_date', models.DateTimeField(blank=True, db_index=True, null=True)), ('availability_time', models.DateTimeField(blank=True, db_index=True, null=True)), ('start_time_from_ascending_node', models.IntegerField(blank=True, db_index=True, null=True)), ('completion_time_from_ascending_node', models.IntegerField(blank=True, db_index=True, null=True)), ('illumination_azimuth_angle', models.FloatField(blank=True, db_index=True, null=True)), ('illumination_zenith_angle', models.FloatField(blank=True, db_index=True, null=True)), ('illumination_elevation_angle', models.FloatField(blank=True, db_index=True, null=True)), ('polarisation_mode', models.PositiveSmallIntegerField(blank=True, choices=[(0, b'single'), (1, b'dual'), (2, b'twin'), (3, b'quad'), (4, b'UNDEFINED')], db_index=True, null=True)), ('polarization_channels', models.PositiveSmallIntegerField(blank=True, choices=[(0, b'HV'), (1, b'HV, VH'), (2, b'VH'), (3, b'VV'), (4, b'HH, VV'), (5, b'HH, VH'), (6, b'HH, HV'), (7, b'VH, VV'), (8, b'VH, HV'), (9, b'VV, HV'), (10, b'VV, VH'), (11, b'HH'), (12, b'HH, HV, VH, VV'), (13, b'UNDEFINED')], db_index=True, null=True)), ('antenna_look_direction', models.PositiveSmallIntegerField(blank=True, choices=[(0, b'LEFT'), (1, b'RIGHT')], db_index=True, null=True)), ('minimum_incidence_angle', models.FloatField(blank=True, db_index=True, null=True)), ('maximum_incidence_angle', models.FloatField(blank=True, db_index=True, null=True)), ('doppler_frequency', models.FloatField(blank=True, db_index=True, null=True)), ('incidence_angle_variation', models.FloatField(blank=True, db_index=True, null=True)), ('cloud_cover', models.FloatField(blank=True, db_index=True, null=True)), ('snow_cover', models.FloatField(blank=True, db_index=True, null=True)), ('lowest_location', models.FloatField(blank=True, db_index=True, null=True)), ('highest_location', models.FloatField(blank=True, db_index=True, null=True)), ('acquisition_station', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.AcquisitionStation')), ('acquisition_sub_type', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.AcquisitionSubType')), ('archiving_center', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.ArchivingCenter')), ('frame', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.Frame')), ('orbit_number', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.OrbitNumber')), ('processing_center', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.ProcessingCenter')), ('processing_mode', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.ProcessingMode')), ('processor_name', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.ProcessorName')), ], ), migrations.CreateModel( name='ProductQualityDegredationTag', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='ProductType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=512, unique=True, validators=[django.core.validators.RegexValidator(re.compile(b'^[a-zA-z_][a-zA-Z0-9_]*$'), message=b'This field must contain a valid Name.')])), ('allowed_coverage_types', models.ManyToManyField(blank=True, related_name='allowed_product_types', to='coverages.CoverageType')), ], ), migrations.CreateModel( name='ProductVersion', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='SensorMode', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='SwathIdentifier', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Track', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('value', models.CharField(db_index=True, max_length=256, unique=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Collection', fields=[ ('eoobject_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='coverages.EOObject')), ], bases=('coverages.eoobject',), ), migrations.CreateModel( name='Coverage', fields=[ ('eoobject_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='coverages.EOObject')), ('axis_1_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_2_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_3_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_4_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_1_size', models.PositiveIntegerField()), ('axis_2_size', models.PositiveIntegerField(blank=True, null=True)), ('axis_3_size', models.PositiveIntegerField(blank=True, null=True)), ('axis_4_size', models.PositiveIntegerField(blank=True, null=True)), ('collections', models.ManyToManyField(blank=True, related_name='coverages', to='coverages.Collection')), ('coverage_type', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='coverages', to='coverages.CoverageType')), ('grid', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='coverages.Grid')), ], options={ 'abstract': False, }, bases=('coverages.eoobject', models.Model), ), migrations.CreateModel( name='Mosaic', fields=[ ('eoobject_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='coverages.EOObject')), ('axis_1_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_2_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_3_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_4_origin', models.CharField(blank=True, max_length=256, null=True)), ('axis_1_size', models.PositiveIntegerField()), ('axis_2_size', models.PositiveIntegerField(blank=True, null=True)), ('axis_3_size', models.PositiveIntegerField(blank=True, null=True)), ('axis_4_size', models.PositiveIntegerField(blank=True, null=True)), ('collections', models.ManyToManyField(blank=True, related_name='mosaics', to='coverages.Collection')), ('coverage_type', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='mosaics', to='coverages.CoverageType')), ('grid', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='coverages.Grid')), ], options={ 'abstract': False, }, bases=('coverages.eoobject', models.Model), ), migrations.CreateModel( name='Product', fields=[ ('eoobject_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='coverages.EOObject')), ('collections', models.ManyToManyField(blank=True, related_name='products', to='coverages.Collection')), ('package', models.OneToOneField(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='backends.Storage')), ('product_type', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='products', to='coverages.ProductType')), ], bases=('coverages.eoobject',), ), migrations.CreateModel( name='ReservedID', fields=[ ('eoobject_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='coverages.EOObject')), ('until', models.DateTimeField(blank=True, null=True)), ('request_id', models.CharField(blank=True, max_length=256, null=True)), ], bases=('coverages.eoobject',), ), migrations.AddField( model_name='productmetadata', name='product_quality_degradation_tag', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.ProductQualityDegredationTag'), ), migrations.AddField( model_name='productmetadata', name='product_version', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.ProductVersion'), ), migrations.AddField( model_name='productmetadata', name='sensor_mode', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.SensorMode'), ), migrations.AddField( model_name='productmetadata', name='swath_identifier', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.SwathIdentifier'), ), migrations.AddField( model_name='productmetadata', name='track', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='metadatas', to='coverages.Track'), ), migrations.AddField( model_name='metadataitem', name='eo_object', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='metadata_items', to='coverages.EOObject'), ), migrations.AddField( model_name='metadataitem', name='storage', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='backends.Storage'), ), migrations.AddField( model_name='masktype', name='product_type', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='mask_types', to='coverages.ProductType'), ), migrations.AddField( model_name='mask', name='mask_type', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='coverages.MaskType'), ), migrations.AddField( model_name='mask', name='storage', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='backends.Storage'), ), migrations.AddField( model_name='collectiontype', name='allowed_coverage_types', field=models.ManyToManyField(blank=True, related_name='allowed_collection_types', to='coverages.CoverageType'), ), migrations.AddField( model_name='collectiontype', name='allowed_product_types', field=models.ManyToManyField(blank=True, related_name='allowed_collection_types', to='coverages.ProductType'), ), migrations.AddField( model_name='browsetype', name='product_type', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='browse_types', to='coverages.ProductType'), ), migrations.AddField( model_name='browse', name='browse_type', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='coverages.BrowseType'), ), migrations.AddField( model_name='browse', name='storage', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='backends.Storage'), ), migrations.AddField( model_name='arraydataitem', name='coverage', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='arraydata_items', to='coverages.EOObject'), ), migrations.AddField( model_name='arraydataitem', name='storage', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='backends.Storage'), ), migrations.AddField( model_name='allowedvaluerange', name='field_type', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='allowed_value_ranges', to='coverages.FieldType'), ), migrations.AddField( model_name='productmetadata', name='product', field=models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='product_metadata', to='coverages.Product'), ), migrations.AlterUniqueTogether( name='masktype', unique_together=set([('name', 'product_type')]), ), migrations.AddField( model_name='mask', name='product', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='masks', to='coverages.Product'), ), migrations.AlterUniqueTogether( name='fieldtype', unique_together=set([('identifier', 'coverage_type'), ('index', 'coverage_type')]), ), migrations.AddField( model_name='coveragemetadata', name='coverage', field=models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='coverage_metadata', to='coverages.Coverage'), ), migrations.AddField( model_name='coverage', name='mosaics', field=models.ManyToManyField(blank=True, related_name='coverages', to='coverages.Mosaic'), ), migrations.AddField( model_name='coverage', name='parent_product', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='coverages', to='coverages.Product'), ), migrations.AddField( model_name='collectionmetadata', name='collection', field=models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='collection_metadata', to='coverages.Collection'), ), migrations.AddField( model_name='collection', name='collection_type', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='collections', to='coverages.CollectionType'), ), migrations.AddField( model_name='collection', name='grid', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='coverages.Grid'), ), migrations.AlterUniqueTogether( name='browsetype', unique_together=set([('name', 'product_type')]), ), migrations.AddField( model_name='browse', name='product', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='browses', to='coverages.Product'), ), migrations.AlterUniqueTogether( name='arraydataitem', unique_together=set([('coverage', 'field_index')]), ), migrations.AlterUniqueTogether( name='browse', unique_together=set([('product', 'browse_type', 'style')]), ), ]

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null

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6

1a0c7d6651be870290aa14fcf39354328f296984

189

py

Python

app/admin/views.py

djm4/quiz-button

33f5cf2ce042df1b7ce1951c07a1415fe2fda34f

[ "MIT" ]

null

app/admin/views.py

djm4/quiz-button

33f5cf2ce042df1b7ce1951c07a1415fe2fda34f

[ "MIT" ]

null

app/admin/views.py

djm4/quiz-button

33f5cf2ce042df1b7ce1951c07a1415fe2fda34f

[ "MIT" ]

null

from flask import render_template from flask_login import login_required from . import admin @admin.route('/') @login_required def index(): return render_template('admin/index.html')

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c519a01450f3249ebfadf6d46e0d4e37ef9f2b24

47,535

py

Python

tests/test_core.py

mirca/bt

0363e6fa100d9392dd18e32e3d8379d5e83c28fa

[ "MIT" ]

1

2021-05-07T19:40:16.000Z

tests/test_core.py

mirca/bt

0363e6fa100d9392dd18e32e3d8379d5e83c28fa

[ "MIT" ]

null

tests/test_core.py

mirca/bt

0363e6fa100d9392dd18e32e3d8379d5e83c28fa

[ "MIT" ]

3

2021-05-07T19:40:22.000Z

2022-01-19T19:37:15.000Z

from __future__ import division import copy import bt from bt.core import Node, StrategyBase, SecurityBase, AlgoStack, Strategy import pandas as pd import numpy as np from nose.tools import assert_almost_equal as aae import sys if sys.version_info < (3, 3): import mock else: from unittest import mock def test_node_tree(): c1 = Node('c1') c2 = Node('c2') p = Node('p', children=[c1, c2]) c1 = p['c1'] c2 = p['c2'] assert len(p.children) == 2 assert 'c1' in p.children assert 'c2' in p.children assert p == c1.parent assert p == c2.parent m = Node('m', children=[p]) p = m['p'] c1 = p['c1'] c2 = p['c2'] assert len(m.children) == 1 assert 'p' in m.children assert p.parent == m assert len(p.children) == 2 assert 'c1' in p.children assert 'c2' in p.children assert p == c1.parent assert p == c2.parent def test_strategybase_tree(): s1 = SecurityBase('s1') s2 = SecurityBase('s2') s = StrategyBase('p', [s1, s2]) s1 = s['s1'] s2 = s['s2'] assert len(s.children) == 2 assert 's1' in s.children assert 's2' in s.children assert s == s1.parent assert s == s2.parent def test_node_members(): s1 = SecurityBase('s1') s2 = SecurityBase('s2') s = StrategyBase('p', [s1, s2]) s1 = s['s1'] s2 = s['s2'] actual = s.members assert len(actual) == 3 assert s1 in actual assert s2 in actual assert s in actual actual = s1.members assert len(actual) == 1 assert s1 in actual actual = s2.members assert len(actual) == 1 assert s2 in actual def test_node_full_name(): s1 = SecurityBase('s1') s2 = SecurityBase('s2') s = StrategyBase('p', [s1, s2]) # we cannot access s1 and s2 directly since they are copied # we must therefore access through s assert s.full_name == 'p' assert s['s1'].full_name == 'p>s1' assert s['s2'].full_name == 'p>s2' def test_security_setup_prices(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[0]] = 105 data['c2'][dts[0]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) assert c1.price == 105 assert len(c1.prices) == 1 assert c1.prices[0] == 105 assert c2.price == 95 assert len(c2.prices) == 1 assert c2.prices[0] == 95 # now with setup c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[0]] = 105 data['c2'][dts[0]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) assert c1.price == 105 assert len(c1.prices) == 1 assert c1.prices[0] == 105 assert c2.price == 95 assert len(c2.prices) == 1 assert c2.prices[0] == 95 def test_strategybase_tree_setup(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) assert len(s.data) == 3 assert len(c1.data) == 3 assert len(c2.data) == 3 assert len(s._prices) == 3 assert len(c1._prices) == 3 assert len(c2._prices) == 3 assert len(s._values) == 3 assert len(c1._values) == 3 assert len(c2._values) == 3 def test_strategybase_tree_adjust(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) s.adjust(1000) assert s.capital == 1000 assert s.value == 1000 assert c1.value == 0 assert c2.value == 0 assert c1.weight == 0 assert c2.weight == 0 def test_strategybase_tree_update(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) c1.price == 100 c2.price == 100 i = 1 s.update(dts[i], data.ix[dts[i]]) c1.price == 105 c2.price == 95 i = 2 s.update(dts[i], data.ix[dts[i]]) c1.price == 100 c2.price == 100 def test_update_fails_if_price_is_nan_and_position_open(): c1 = SecurityBase('c1') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1'], data=100) data['c1'][dts[1]] = np.nan c1.setup(data) i = 0 # mock in position c1._position = 100 c1.update(dts[i], data.ix[dts[i]]) # test normal case - position & non-nan price assert c1._value == 100 * 100 i = 1 # this should fail, because we have non-zero position, and price is nan, so # bt has no way of updating the _value try: c1.update(dts[i], data.ix[dts[i]]) assert False except Exception as e: assert str(e).startswith('Position is open') # on the other hand, if position was 0, this should be fine, and update # value to 0 c1._position = 0 c1.update(dts[i], data.ix[dts[i]]) assert c1._value == 0 def test_strategybase_tree_allocate(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000) # since children have w == 0 this should stay in s s.allocate(1000) assert s.value == 1000 assert s.capital == 1000 assert c1.value == 0 assert c2.value == 0 # now allocate directly to child c1.allocate(500) assert c1.position == 5 assert c1.value == 500 assert s.capital == 1000 - 500 assert s.value == 1000 assert c1.weight == 500.0 / 1000 assert c2.weight == 0 def test_strategybase_tree_allocate_child_from_strategy(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000) # since children have w == 0 this should stay in s s.allocate(1000) assert s.value == 1000 assert s.capital == 1000 assert c1.value == 0 assert c2.value == 0 # now allocate to c1 s.allocate(500, 'c1') assert c1.position == 5 assert c1.value == 500 assert s.capital == 1000 - 500 assert s.value == 1000 assert c1.weight == 500.0 / 1000 assert c2.weight == 0 def test_strategybase_tree_allocate_level2(): c1 = SecurityBase('c1') c12 = copy.deepcopy(c1) c2 = SecurityBase('c2') c22 = copy.deepcopy(c2) s1 = StrategyBase('s1', [c1, c2]) s2 = StrategyBase('s2', [c12, c22]) m = StrategyBase('m', [s1, s2]) s1 = m['s1'] s2 = m['s2'] c1 = s1['c1'] c2 = s1['c2'] c12 = s2['c1'] c22 = s2['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 m.setup(data) i = 0 m.update(dts[i], data.ix[dts[i]]) m.adjust(1000) # since children have w == 0 this should stay in s m.allocate(1000) assert m.value == 1000 assert m.capital == 1000 assert s1.value == 0 assert s2.value == 0 assert c1.value == 0 assert c2.value == 0 # now allocate directly to child s1.allocate(500) assert s1.value == 500 assert m.capital == 1000 - 500 assert m.value == 1000 assert s1.weight == 500.0 / 1000 assert s2.weight == 0 # now allocate directly to child of child c1.allocate(200) assert s1.value == 500 assert s1.capital == 500 - 200 assert c1.value == 200 assert c1.weight == 200.0 / 500 assert c1.position == 2 assert m.capital == 1000 - 500 assert m.value == 1000 assert s1.weight == 500.0 / 1000 assert s2.weight == 0 assert c12.value == 0 def test_strategybase_tree_allocate_long_short(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000) c1.allocate(500) assert c1.position == 5 assert c1.value == 500 assert c1.weight == 500.0 / 1000 assert s.capital == 1000 - 500 assert s.value == 1000 c1.allocate(-200) assert c1.position == 3 assert c1.value == 300 assert c1.weight == 300.0 / 1000 assert s.capital == 1000 - 500 + 200 assert s.value == 1000 c1.allocate(-400) assert c1.position == -1 assert c1.value == -100 assert c1.weight == -100.0 / 1000 assert s.capital == 1000 - 500 + 200 + 400 assert s.value == 1000 # close up c1.allocate(-c1.value) assert c1.position == 0 assert c1.value == 0 assert c1.weight == 0 assert s.capital == 1000 - 500 + 200 + 400 - 100 assert s.value == 1000 def test_strategybase_tree_allocate_update(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) assert s.price == 100 s.adjust(1000) assert s.price == 100 assert s.value == 1000 assert s._value == 1000 c1.allocate(500) assert c1.position == 5 assert c1.value == 500 assert c1.weight == 500.0 / 1000 assert s.capital == 1000 - 500 assert s.value == 1000 assert s.price == 100 i = 1 s.update(dts[i], data.ix[dts[i]]) assert c1.position == 5 assert c1.value == 525 assert c1.weight == 525.0 / 1025 assert s.capital == 1000 - 500 assert s.value == 1025 assert np.allclose(s.price, 102.5) def test_strategybase_universe(): s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[0]] = 105 data['c2'][dts[0]] = 95 s.setup(data) i = 0 s.update(dts[i]) assert len(s.universe) == 1 assert 'c1' in s.universe assert 'c2' in s.universe assert s.universe['c1'][dts[i]] == 105 assert s.universe['c2'][dts[i]] == 95 # should not have children unless allocated assert len(s.children) == 0 def test_strategybase_allocate(): s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[0]] = 100 data['c2'][dts[0]] = 95 s.setup(data) i = 0 s.update(dts[i]) s.adjust(1000) s.allocate(100, 'c1') c1 = s['c1'] assert c1.position == 1 assert c1.value == 100 assert s.value == 1000 def test_strategybase_close(): s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) s.setup(data) i = 0 s.update(dts[i]) s.adjust(1000) s.allocate(100, 'c1') c1 = s['c1'] assert c1.position == 1 assert c1.value == 100 assert s.value == 1000 s.close('c1') assert c1.position == 0 assert c1.value == 0 assert s.value == 1000 def test_strategybase_flatten(): s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) s.setup(data) i = 0 s.update(dts[i]) s.adjust(1000) s.allocate(100, 'c1') c1 = s['c1'] s.allocate(100, 'c2') c2 = s['c2'] assert c1.position == 1 assert c1.value == 100 assert c2.position == 1 assert c2.value == 100 assert s.value == 1000 s.flatten() assert c1.position == 0 assert c1.value == 0 assert s.value == 1000 def test_strategybase_multiple_calls(): s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=5) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data.c2[dts[0]] = 95 data.c1[dts[1]] = 95 data.c2[dts[2]] = 95 data.c2[dts[3]] = 95 data.c2[dts[4]] = 95 data.c1[dts[4]] = 105 s.setup(data) # define strategy logic def algo(target): # close out any open positions target.flatten() # get stock w/ lowest price c = target.universe.ix[target.now].idxmin() # allocate all capital to that stock target.allocate(target.value, c) # replace run logic s.run = algo # start w/ 1000 s.adjust(1000) # loop through dates manually i = 0 # update t0 s.update(dts[i]) assert len(s.children) == 0 assert s.value == 1000 # run t0 s.run(s) assert len(s.children) == 1 assert s.value == 1000 assert s.capital == 50 c2 = s['c2'] assert c2.value == 950 assert c2.weight == 950.0 / 1000 assert c2.price == 95 # update out t0 s.update(dts[i]) c2 == s['c2'] assert len(s.children) == 1 assert s.value == 1000 assert s.capital == 50 assert c2.value == 950 assert c2.weight == 950.0 / 1000 assert c2.price == 95 # update t1 i = 1 s.update(dts[i]) assert s.value == 1050 assert s.capital == 50 assert len(s.children) == 1 assert 'c2' in s.children c2 == s['c2'] assert c2.value == 1000 assert c2.weight == 1000.0 / 1050.0 assert c2.price == 100 # run t1 - close out c2, open c1 s.run(s) assert len(s.children) == 2 assert s.value == 1050 assert s.capital == 5 c1 = s['c1'] assert c1.value == 1045 assert c1.weight == 1045.0 / 1050 assert c1.price == 95 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 100 # update out t1 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1050 assert s.capital == 5 assert c1 == s['c1'] assert c1.value == 1045 assert c1.weight == 1045.0 / 1050 assert c1.price == 95 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 100 # update t2 i = 2 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 5 assert c1.value == 1100 assert c1.weight == 1100.0 / 1105 assert c1.price == 100 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 95 # run t2 s.run(s) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update out t2 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update t3 i = 3 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # run t3 s.run(s) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update out t3 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update t4 i = 4 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 # accessing price should refresh - this child has been idle for a while - # must make sure we can still have a fresh prices assert c1.price == 105 assert len(c1.prices) == 5 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # run t4 s.run(s) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 105 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update out t4 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 105 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 def test_strategybase_multiple_calls_preset_secs(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('s', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=5) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data.c2[dts[0]] = 95 data.c1[dts[1]] = 95 data.c2[dts[2]] = 95 data.c2[dts[3]] = 95 data.c2[dts[4]] = 95 data.c1[dts[4]] = 105 s.setup(data) # define strategy logic def algo(target): # close out any open positions target.flatten() # get stock w/ lowest price c = target.universe.ix[target.now].idxmin() # allocate all capital to that stock target.allocate(target.value, c) # replace run logic s.run = algo # start w/ 1000 s.adjust(1000) # loop through dates manually i = 0 # update t0 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1000 # run t0 s.run(s) assert len(s.children) == 2 assert s.value == 1000 assert s.capital == 50 assert c2.value == 950 assert c2.weight == 950.0 / 1000 assert c2.price == 95 # update out t0 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1000 assert s.capital == 50 assert c2.value == 950 assert c2.weight == 950.0 / 1000 assert c2.price == 95 # update t1 i = 1 s.update(dts[i]) assert s.value == 1050 assert s.capital == 50 assert len(s.children) == 2 assert c2.value == 1000 assert c2.weight == 1000.0 / 1050. assert c2.price == 100 # run t1 - close out c2, open c1 s.run(s) assert c1.value == 1045 assert c1.weight == 1045.0 / 1050 assert c1.price == 95 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 100 assert len(s.children) == 2 assert s.value == 1050 assert s.capital == 5 # update out t1 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1050 assert s.capital == 5 assert c1.value == 1045 assert c1.weight == 1045.0 / 1050 assert c1.price == 95 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 100 # update t2 i = 2 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 5 assert c1.value == 1100 assert c1.weight == 1100.0 / 1105 assert c1.price == 100 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 95 # run t2 s.run(s) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update out t2 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update t3 i = 3 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # run t3 s.run(s) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update out t3 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update t4 i = 4 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 # accessing price should refresh - this child has been idle for a while - # must make sure we can still have a fresh prices assert c1.price == 105 assert len(c1.prices) == 5 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # run t4 s.run(s) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 105 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 # update out t4 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1105 assert s.capital == 60 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 105 assert c2.value == 1045 assert c2.weight == 1045.0 / 1105 assert c2.price == 95 def test_strategybase_multiple_calls_no_post_update(): s = StrategyBase('s') s.set_commissions(lambda q, p: 1) dts = pd.date_range('2010-01-01', periods=5) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data.c2[dts[0]] = 95 data.c1[dts[1]] = 95 data.c2[dts[2]] = 95 data.c2[dts[3]] = 95 data.c2[dts[4]] = 95 data.c1[dts[4]] = 105 s.setup(data) # define strategy logic def algo(target): # close out any open positions target.flatten() # get stock w/ lowest price c = target.universe.ix[target.now].idxmin() # allocate all capital to that stock target.allocate(target.value, c) # replace run logic s.run = algo # start w/ 1000 s.adjust(1000) # loop through dates manually i = 0 # update t0 s.update(dts[i]) assert len(s.children) == 0 assert s.value == 1000 # run t0 s.run(s) assert len(s.children) == 1 assert s.value == 999 assert s.capital == 49 c2 = s['c2'] assert c2.value == 950 assert c2.weight == 950.0 / 999 assert c2.price == 95 # update t1 i = 1 s.update(dts[i]) assert s.value == 1049 assert s.capital == 49 assert len(s.children) == 1 assert 'c2' in s.children c2 == s['c2'] assert c2.value == 1000 assert c2.weight == 1000.0 / 1049.0 assert c2.price == 100 # run t1 - close out c2, open c1 s.run(s) assert len(s.children) == 2 assert s.value == 1047 assert s.capital == 2 c1 = s['c1'] assert c1.value == 1045 assert c1.weight == 1045.0 / 1047 assert c1.price == 95 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 100 # update t2 i = 2 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1102 assert s.capital == 2 assert c1.value == 1100 assert c1.weight == 1100.0 / 1102 assert c1.price == 100 assert c2.value == 0 assert c2.weight == 0 assert c2.price == 95 # run t2 s.run(s) assert len(s.children) == 2 assert s.value == 1100 assert s.capital == 55 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1100 assert c2.price == 95 # update t3 i = 3 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1100 assert s.capital == 55 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1100 assert c2.price == 95 # run t3 s.run(s) assert len(s.children) == 2 assert s.value == 1098 assert s.capital == 53 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 100 assert c2.value == 1045 assert c2.weight == 1045.0 / 1098 assert c2.price == 95 # update t4 i = 4 s.update(dts[i]) assert len(s.children) == 2 assert s.value == 1098 assert s.capital == 53 assert c1.value == 0 assert c1.weight == 0 # accessing price should refresh - this child has been idle for a while - # must make sure we can still have a fresh prices assert c1.price == 105 assert len(c1.prices) == 5 assert c2.value == 1045 assert c2.weight == 1045.0 / 1098 assert c2.price == 95 # run t4 s.run(s) assert len(s.children) == 2 assert s.value == 1096 assert s.capital == 51 assert c1.value == 0 assert c1.weight == 0 assert c1.price == 105 assert c2.value == 1045 assert c2.weight == 1045.0 / 1096 assert c2.price == 95 def test_strategybase_prices(): dts = pd.date_range('2010-01-01', periods=21) rawd = [13.555, 13.75, 14.16, 13.915, 13.655, 13.765, 14.02, 13.465, 13.32, 14.65, 14.59, 14.175, 13.865, 13.865, 13.89, 13.85, 13.565, 13.47, 13.225, 13.385, 12.89] data = pd.DataFrame(index=dts, data=rawd, columns=['a']) s = StrategyBase('s') s.set_commissions(lambda q, p: 1) s.setup(data) # buy 100 shares on day 1 - hold until end # just enough to buy 100 shares + 1$ commission s.adjust(1356.50) s.update(dts[0]) # allocate all capital to child a # a should be dynamically created and should have # 100 shares allocated. s.capital should be 0 s.allocate(s.value, 'a') assert s.capital == 0 assert s.value == 1355.50 assert len(s.children) == 1 aae(s.price, 99.92628, 5) a = s['a'] assert a.position == 100 assert a.value == 1355.50 assert a.weight == 1 assert a.price == 13.555 assert len(a.prices) == 1 # update through all dates and make sure price is ok s.update(dts[1]) aae(s.price, 101.3638, 4) s.update(dts[2]) aae(s.price, 104.3863, 4) s.update(dts[3]) aae(s.price, 102.5802, 4) # finish updates and make sure ok at end for i in range(4, 21): s.update(dts[i]) assert len(s.prices) == 21 aae(s.prices[-1], 95.02396, 5) aae(s.prices[-2], 98.67306, 5) def test_fail_if_root_value_negative(): s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[0]] = 100 data['c2'][dts[0]] = 95 s.setup(data) s.adjust(-100) # trigger update s.update(dts[0]) assert s.bankrupt # make sure only triggered if root negative c1 = StrategyBase('c1') s = StrategyBase('s', children=[c1]) c1 = s['c1'] s.setup(data) s.adjust(1000) c1.adjust(-100) s.update(dts[0]) # now make it trigger c1.adjust(-1000) # trigger update s.update(dts[0]) assert s.bankrupt def test_fail_if_0_base_in_return_calc(): dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[0]] = 100 data['c2'][dts[0]] = 95 # must setup tree because if not negative root error pops up first c1 = StrategyBase('c1') s = StrategyBase('s', children=[c1]) c1 = s['c1'] s.setup(data) s.adjust(1000) c1.adjust(100) s.update(dts[0]) c1.adjust(-100) s.update(dts[1]) try: c1.adjust(-100) s.update(dts[1]) assert False except ZeroDivisionError as e: if 'Could not update' not in str(e): assert False def test_strategybase_tree_rebalance(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) s.set_commissions(lambda q, p: 1) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000) assert s.value == 1000 assert s.capital == 1000 assert c1.value == 0 assert c2.value == 0 # now rebalance c1 s.rebalance(0.5, 'c1') assert c1.position == 4 assert c1.value == 400 assert s.capital == 1000 - 401 assert s.value == 999 assert c1.weight == 400.0 / 999 assert c2.weight == 0 def test_strategybase_tree_decimal_position_rebalance(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) s.use_integer_positions(False) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000.2) s.rebalance(0.42, 'c1') s.rebalance(0.58, 'c2') aae(c1.value, 420.084) aae(c2.value, 580.116) aae(c1.value + c2.value, 1000.2) def test_rebalance_child_not_in_tree(): s = StrategyBase('p') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i]) s.adjust(1000) # rebalance to 0 w/ child that is not present - should ignore s.rebalance(0, 'c2') assert s.value == 1000 assert s.capital == 1000 assert len(s.children) == 0 def test_strategybase_tree_rebalance_to_0(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000) assert s.value == 1000 assert s.capital == 1000 assert c1.value == 0 assert c2.value == 0 # now rebalance c1 s.rebalance(0.5, 'c1') assert c1.position == 5 assert c1.value == 500 assert s.capital == 1000 - 500 assert s.value == 1000 assert c1.weight == 500.0 / 1000 assert c2.weight == 0 # now rebalance c1 s.rebalance(0, 'c1') assert c1.position == 0 assert c1.value == 0 assert s.capital == 1000 assert s.value == 1000 assert c1.weight == 0 assert c2.weight == 0 def test_strategybase_tree_rebalance_level2(): c1 = SecurityBase('c1') c12 = copy.deepcopy(c1) c2 = SecurityBase('c2') c22 = copy.deepcopy(c2) s1 = StrategyBase('s1', [c1, c2]) s2 = StrategyBase('s2', [c12, c22]) m = StrategyBase('m', [s1, s2]) s1 = m['s1'] s2 = m['s2'] c1 = s1['c1'] c2 = s1['c2'] c12 = s2['c1'] c22 = s2['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 m.setup(data) i = 0 m.update(dts[i], data.ix[dts[i]]) m.adjust(1000) assert m.value == 1000 assert m.capital == 1000 assert s1.value == 0 assert s2.value == 0 assert c1.value == 0 assert c2.value == 0 # now rebalance child s1 - since its children are 0, no waterfall alloc m.rebalance(0.5, 's1') assert s1.value == 500 assert m.capital == 1000 - 500 assert m.value == 1000 assert s1.weight == 500.0 / 1000 assert s2.weight == 0 # now allocate directly to child of child s1.rebalance(0.4, 'c1') assert s1.value == 500 assert s1.capital == 500 - 200 assert c1.value == 200 assert c1.weight == 200.0 / 500 assert c1.position == 2 assert m.capital == 1000 - 500 assert m.value == 1000 assert s1.weight == 500.0 / 1000 assert s2.weight == 0 assert c12.value == 0 # now rebalance child s1 again and make sure c1 also gets proportional # increase m.rebalance(0.8, 's1') assert s1.value == 800 aae(m.capital, 200, 1) assert m.value == 1000 assert s1.weight == 800 / 1000 assert s2.weight == 0 assert c1.value == 300.0 assert c1.weight == 300.0 / 800 assert c1.position == 3 # now rebalance child s1 to 0 - should close out s1 and c1 as well m.rebalance(0, 's1') assert s1.value == 0 assert m.capital == 1000 assert m.value == 1000 assert s1.weight == 0 assert s2.weight == 0 assert c1.weight == 0 def test_strategybase_tree_rebalance_base(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) s.set_commissions(lambda q, p: 1) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[1]] = 105 data['c2'][dts[1]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000) assert s.value == 1000 assert s.capital == 1000 assert c1.value == 0 assert c2.value == 0 # check that 2 rebalances of equal weight lead to two different allocs # since value changes after first call s.rebalance(0.5, 'c1') assert c1.position == 4 assert c1.value == 400 assert s.capital == 1000 - 401 assert s.value == 999 assert c1.weight == 400.0 / 999 assert c2.weight == 0 s.rebalance(0.5, 'c2') assert c2.position == 4 assert c2.value == 400 assert s.capital == 1000 - 401 - 401 assert s.value == 998 assert c2.weight == 400.0 / 998 assert c1.weight == 400.0 / 998 # close out everything s.flatten() # adjust to get back to 1000 s.adjust(4) assert s.value == 1000 assert s.capital == 1000 assert c1.value == 0 assert c2.value == 0 # now rebalance but set fixed base base = s.value s.rebalance(0.5, 'c1', base=base) assert c1.position == 4 assert c1.value == 400 assert s.capital == 1000 - 401 assert s.value == 999 assert c1.weight == 400.0 / 999 assert c2.weight == 0 s.rebalance(0.5, 'c2', base=base) assert c2.position == 4 assert c2.value == 400 assert s.capital == 1000 - 401 - 401 assert s.value == 998 assert c2.weight == 400.0 / 998 assert c1.weight == 400.0 / 998 def test_algo_stack(): a1 = mock.MagicMock(return_value=True) a2 = mock.MagicMock(return_value=False) a3 = mock.MagicMock(return_value=True) # no run_always for now del a1.run_always del a2.run_always del a3.run_always stack = AlgoStack(a1, a2, a3) target = mock.MagicMock() assert not stack(target) assert a1.called assert a2.called assert not a3.called # now test that run_always marked are run a1 = mock.MagicMock(return_value=True) a2 = mock.MagicMock(return_value=False) a3 = mock.MagicMock(return_value=True) # a3 will have run_always del a1.run_always del a2.run_always stack = AlgoStack(a1, a2, a3) target = mock.MagicMock() assert not stack(target) assert a1.called assert a2.called assert a3.called def test_set_commissions(): s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) s.set_commissions(lambda x, y: 1.0) s.setup(data) s.update(dts[0]) s.adjust(1000) s.allocate(500, 'c1') assert s.capital == 599 s.set_commissions(lambda x, y: 0.0) s.allocate(-400, 'c1') assert s.capital == 999 def test_strategy_tree_proper_return_calcs(): s1 = StrategyBase('s1') s2 = StrategyBase('s2') m = StrategyBase('m', [s1, s2]) s1 = m['s1'] s2 = m['s2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data.loc['c1', dts[1]] = 105 data.loc['c2', dts[1]] = 95 m.setup(data) i = 0 m.update(dts[i], data.ix[dts[i]]) m.adjust(1000) # since children have w == 0 this should stay in s m.allocate(1000) assert m.value == 1000 assert m.capital == 1000 assert m.price == 100 assert s1.value == 0 assert s2.value == 0 # now allocate directly to child s1.allocate(500) assert m.capital == 500 assert m.value == 1000 assert m.price == 100 assert s1.value == 500 assert s1.weight == 500.0 / 1000 assert s1.price == 100 assert s2.weight == 0 # allocate to child2 via master method m.allocate(500, 's2') assert m.capital == 0 assert m.value == 1000 assert m.price == 100 assert s1.value == 500 assert s1.weight == 500.0 / 1000 assert s1.price == 100 assert s2.value == 500 assert s2.weight == 500.0 / 1000 assert s2.price == 100 # now allocate and incur commission fee s1.allocate(500, 'c1') assert m.capital == 0 assert m.value == 1000 assert m.price == 100 assert s1.value == 500 assert s1.weight == 500.0 / 1000 assert s1.price == 100 assert s2.value == 500 assert s2.weight == 500.0 / 1000.0 assert s2.price == 100 def test_strategy_tree_proper_universes(): def do_nothing(x): return True child1 = Strategy('c1', [do_nothing], ['b', 'c']) master = Strategy('m', [do_nothing], [child1, 'a']) child1 = master['c1'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame( {'a': pd.Series(data=1, index=dts, name='a'), 'b': pd.Series(data=2, index=dts, name='b'), 'c': pd.Series(data=3, index=dts, name='c')}) master.setup(data) assert len(master.children) == 2 assert 'c1' in master.children assert 'a' in master.children assert len(master._universe.columns) == 2 assert 'c1' in master._universe.columns assert 'a' in master._universe.columns assert len(child1._universe.columns) == 2 assert 'b' in child1._universe.columns assert 'c' in child1._universe.columns def test_strategy_tree_paper(): dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['a'], data=100.) data['a'].ix[dts[1]] = 101 data['a'].ix[dts[2]] = 102 s = Strategy('s', [bt.algos.SelectWhere(data > 100), bt.algos.WeighEqually(), bt.algos.Rebalance()]) m = Strategy('m', [], [s]) s = m['s'] m.setup(data) m.update(dts[0]) m.run() assert m.price == 100 assert s.price == 100 assert s._paper_trade assert s._paper.price == 100 s.update(dts[1]) m.run() assert m.price == 100 assert m.value == 0 assert s.value == 0 assert s.price == 100 s.update(dts[2]) m.run() assert m.price == 100 assert m.value == 0 assert s.value == 0 assert np.allclose(s.price, 100. * (102 / 101.)) def test_outlays(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) data['c1'][dts[0]] = 105 data['c2'][dts[0]] = 95 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) # allocate 1000 to strategy s.adjust(1000) # now let's see what happens when we allocate 500 to each child c1.allocate(500) c2.allocate(500) # out update s.update(dts[i]) assert c1.data['outlay'][dts[0]] == (4 * 105) assert c2.data['outlay'][dts[0]] == (5 * 95) i = 1 s.update(dts[i], data.ix[dts[i]]) c1.allocate(-400) c2.allocate(100) # out update s.update(dts[i]) #print(c1.data['outlay']) assert c1.data['outlay'][dts[1]] == (-4 * 100) assert c2.data['outlay'][dts[1]] == 100 def test_child_weight_above_1(): # check for child weights not exceeding 1 s = StrategyBase('s') dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(np.random.randn(3, 2) + 100, index=dts, columns=['c1', 'c2']) s.setup(data) i = 0 s.update(dts[i]) s.adjust(1e6) s.allocate(1e6, 'c1') c1 = s['c1'] assert c1.weight <= 1 def test_fixed_commissions(): c1 = SecurityBase('c1') c2 = SecurityBase('c2') s = StrategyBase('p', [c1, c2]) # fixed $1 commission per transaction s.set_commissions(lambda q, p: 1) c1 = s['c1'] c2 = s['c2'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1', 'c2'], data=100) s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) # allocate 1000 to strategy s.adjust(1000) # now let's see what happens when we allocate 500 to each child c1.allocate(500) c2.allocate(500) # out update s.update(dts[i]) assert c1.value == 400 assert c2.value == 400 assert s.capital == 198 # de-alloc 100 from c1. This should force c1 to sell 2 units to raise at # least 100 (because of commissions) c1.allocate(-100) s.update(dts[i]) assert c1.value == 200 assert s.capital == 198 + 199 # allocate 100 to c2. This should leave things unchaged, since c2 cannot # buy one unit since the commission will cause total outlay to exceed # allocation c2.allocate(100) s.update(dts[i]) assert c2.value == 400 assert s.capital == 198 + 199 # ok try again w/ 101 allocation. This time, it should work c2.allocate(101) s.update(dts[i]) assert c2.value == 500 assert s.capital == 198 + 199 - 101 # ok now let's close the whole position. Since we are closing, we expect # the allocation to go through, even though the outlay > amount c2.allocate(-500) s.update(dts[i]) assert c2.value == 0 assert s.capital == 198 + 199 - 101 + 499 # now we are going to go short c2 # we want to 'raise' 100 dollars. Since we need at a minimum 100, but we # also have commissions, we will actually short 2 units in order to raise # at least 100 c2.allocate(-100) s.update(dts[i]) assert c2.value == -200 assert s.capital == 198 + 199 - 101 + 499 + 199 def test_degenerate_shorting(): # can have situation where you short infinitely if commission/share > share # price c1 = SecurityBase('c1') s = StrategyBase('p', [c1]) # $1/share commission s.set_commissions(lambda q, p: abs(q) * 1) c1 = s['c1'] dts = pd.date_range('2010-01-01', periods=3) # c1 trades at 0.01 data = pd.DataFrame(index=dts, columns=['c1'], data=0.01) s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) s.adjust(1000) try: c1.allocate(-10) assert False except Exception as e: assert 'full_outlay should always be approaching amount' in str(e) def test_securitybase_allocate(): c1 = SecurityBase('c1') s = StrategyBase('p', [c1]) c1 = s['c1'] dts = pd.date_range('2010-01-01', periods=3) data = pd.DataFrame(index=dts, columns=['c1'], data=100.) # set the price data['c1'][dts[0]] = 91.40246706608193 s.setup(data) i = 0 s.update(dts[i], data.ix[dts[i]]) # allocate 100000 to strategy original_capital = 100000. s.adjust(original_capital) # not integer positions c1.integer_positions = False # set the full_outlay and amount full_outlay = 1999.693706988672 amount = 1999.6937069886717 c1.allocate(amount) # the results that we want to be true assert np.isclose(full_outlay ,amount,rtol=0.) # check that the quantity wasn't decreased and the full_outlay == amount # we can get the full_outlay that was calculated by # original capital - current capital assert np.isclose(full_outlay, original_capital - s._capital, rtol=0.) def test_securitybase_allocate_commisions(): date_span = pd.DatetimeIndex(start='10/1/2017', end='10/11/2017', freq='B') numper = len(date_span.values) comms = 0.01 data = [[10, 15, 20, 25, 30, 35, 40, 45], [10, 10, 10, 10, 20, 20, 20, 20], [20, 20, 20, 30, 30, 30, 40, 40], [20, 10, 20, 10, 20, 10, 20, 10]] data = [[row[i] for row in data] for i in range(len(data[0]))] # Transpose price = pd.DataFrame(data=data, index=date_span) price.columns = ['a', 'b', 'c', 'd'] # price = price[['a', 'b']] sig1 = pd.DataFrame(price['a'] >= price['b'] + 10, columns=['a']) sig2 = pd.DataFrame(price['a'] < price['b'] + 10, columns=['b']) signal = sig1.join(sig2) signal1 = price.diff(1) > 0 signal2 = price.diff(1) < 0 tw = price.copy() tw.loc[:,:] = 0 # Initialize Set everything to 0 tw[signal1] = -1.0 tw[signal2] = 1.0 s1 = bt.Strategy('long_short', [bt.algos.WeighTarget(tw), bt.algos.RunDaily(), bt.algos.Rebalance()]) ####now we create the Backtest , commissions=(lambda q, p: abs(p * q) * comms) t = bt.Backtest(s1, price, initial_capital=1000000, commissions=(lambda q, p: abs(p * q) * comms), progress_bar=False) ####and let's run it! res = bt.run(t) ########################

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0.05128

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0.701806

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null

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6

c54fa9f258bf88ed1b606a69b5cf4707269ca6ab

140

py

Python

p_teste/main.py

gabriel-correia0408/Sala_Green_GabrielCorreia

1d22f466d372786c5f8c8eaba7202844b5f03445

[ "Apache-2.0" ]

null

p_teste/main.py

gabriel-correia0408/Sala_Green_GabrielCorreia

1d22f466d372786c5f8c8eaba7202844b5f03445

[ "Apache-2.0" ]

null

p_teste/main.py

gabriel-correia0408/Sala_Green_GabrielCorreia

1d22f466d372786c5f8c8eaba7202844b5f03445

[ "Apache-2.0" ]

null

#para teste desde do inicio # da pasta p_teste fazendo a importação do método soma from p_teste.calculadora import soma print(soma(10,10))

23.333333

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0.792857

25

140

4.36

0.72

0.110092

0

0.033613

0.15

140

6

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23.333333

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0

1

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6

3d858fdc137e866ec85706d57b36612eeed22e17

2,526

py

Python

covid19-dashboard/config.py

pradh/tools

b7c1e4feefcb4c6eb532af5be6a65370487841ab

[ "Apache-2.0" ]

null

covid19-dashboard/config.py

pradh/tools

b7c1e4feefcb4c6eb532af5be6a65370487841ab

[ "Apache-2.0" ]

null

covid19-dashboard/config.py

pradh/tools

b7c1e4feefcb4c6eb532af5be6a65370487841ab

[ "Apache-2.0" ]

null

# Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # DataCommons Host Server. DC_SERVER = "https://api.datacommons.org/" # A dictionary of stat_vars where place_type->key->stat_var. # There must be at least one stat_var per place_type. # The key can be made up, this key will be used to output the data. # Instead of using the long stat_var name. # The key will be used to identify the stat_var. STAT_VARS = { "Country": { "Cases": "CumulativeCount_MedicalConditionIncident_COVID_19_ConfirmedCase", "Deaths": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientDeceased", "Hospitalized": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientHospitalized", "Recovered": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientRecovered", "ICU": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientInICU" }, "State": { "Cases": "CumulativeCount_MedicalConditionIncident_COVID_19_ConfirmedOrProbableCase", "Deaths": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientDeceased", "Hospitalized": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientHospitalized", "Recovered": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientRecovered", "ICU": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientInICU" }, "County": { "Cases": "CumulativeCount_MedicalConditionIncident_COVID_19_ConfirmedOrProbableCase", "Deaths": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientDeceased", "Hospitalized": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientHospitalized", "Recovered": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientRecovered", "ICU": "CumulativeCount_MedicalConditionIncident_COVID_19_PatientInICU" }, }

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0.723278

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7.060241

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0.209026

2,526

62

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0.68705

0.596523

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0

null

1

0

1

0

1

null

0

6

ad001e96bafb2929b3139604416b5e2a6173ed0e

25

py

Python

main.py

lordjack/oficina_introducao_programacao_python

d432e3d39cfb4790da5f3e75c2bf3ee86fa29f8e

[ "MIT" ]

null

main.py

lordjack/oficina_introducao_programacao_python

d432e3d39cfb4790da5f3e75c2bf3ee86fa29f8e

[ "MIT" ]

null

main.py

lordjack/oficina_introducao_programacao_python

d432e3d39cfb4790da5f3e75c2bf3ee86fa29f8e

[ "MIT" ]

null

import exercicios.ex01

6.25

22

0.8

3

25

6.666667

1

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0.095238

0.16

25

3

23

8.333333

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0

1

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null

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1

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null

0

1

0

1

0

1

0

6

9a94366e201ee1444440131935bc9475911c5d84

202

py

Python

fibonacci.py

andremartins746/curso_de_PYTHON

3b4d79e3310b2442cf57a98f213a153492f2a89a

[ "MIT" ]

null

fibonacci.py

andremartins746/curso_de_PYTHON

3b4d79e3310b2442cf57a98f213a153492f2a89a

[ "MIT" ]

null

fibonacci.py

andremartins746/curso_de_PYTHON

3b4d79e3310b2442cf57a98f213a153492f2a89a

[ "MIT" ]

null

def fibinacci(quantidade, sequencia=(0,1)): return sequencia if len(sequencia) == quantidade else fibinacci(quantidade, sequencia + (sum(sequencia[-2:]),)) for fib in fibinacci(20): print(fib)

33.666667

115

0.712871

26

202

5.538462

0.653846

0.263889

0.388889

0

0.028736

0.138614

202

6

116

33.666667

0.798851

0

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null

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1

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6

9aa0e8a506fc5a782081aed3fca2aa416206428e

533

py

Python

chainerex/dataset/__init__.py

corochann/chainerex

15efb34a8fa6afab1ce5ad52c3802960ab6d49c2

[ "MIT" ]

1

2018-08-30T08:59:50.000Z

chainerex/dataset/__init__.py

corochann/chainerex

15efb34a8fa6afab1ce5ad52c3802960ab6d49c2

[ "MIT" ]

null

chainerex/dataset/__init__.py

corochann/chainerex

15efb34a8fa6afab1ce5ad52c3802960ab6d49c2

[ "MIT" ]

null

from chainerex.dataset import dataset_mixin_ex # NOQA from chainerex.dataset import indexers # NOQA from chainerex.dataset.dataset_mixin_ex import DatasetMixinEX # NOQA from chainerex.dataset.dataset_mixin_ex import DatasetMixinEXFeatureIndexer # NOQA from chainerex.dataset.indexers import indexer from chainerex.dataset.indexers.feature_indexer import BaseFeatureIndexer from chainerex.dataset.indexers.indexer import BaseIndexer # NOQA from chainerex.dataset.indexers.indexer import ExtractBySliceNotSupportedError # NOQA

48.454545

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0.354767

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0

0.097561

533

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1

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6

9aa1113f2ff2ced5508f51349eb9c9d460620653

238

py

Python

app/admin.py

haibincoder/DjangoTensorflow

7fc606fa5121f0c48d7c8e649775094d86e6387a

[ "MIT" ]

17

2018-07-21T04:14:09.000Z

2022-03-09T08:32:49.000Z

app/admin.py

haibincoder/DjangoTensorflow

7fc606fa5121f0c48d7c8e649775094d86e6387a

[ "MIT" ]

24

2020-01-28T22:11:42.000Z

2022-03-11T23:47:43.000Z

app/admin.py

haibincoder/DjangoTensorflow

7fc606fa5121f0c48d7c8e649775094d86e6387a

[ "MIT" ]

7

2018-12-13T08:55:07.000Z

2021-06-26T08:08:01.000Z

from django.contrib import admin #from .models import Article, Category, BlogComment, Tag #from .models import Image # Register your models here. #admin.site.register([Article, Category, BlogComment, Tag]) #admin.site.register([Image])

26.444444

59

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238

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0.108696

0.173913

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238

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0.810924

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